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Sample records for abnormal event detection

  1. Detection of abnormal events via optical flow feature analysis.

    PubMed

    Wang, Tian; Snoussi, Hichem

    2015-03-24

    In this paper, a novel algorithm is proposed to detect abnormal events in video streams. The algorithm is based on the histogram of the optical flow orientation descriptor and the classification method. The details of the histogram of the optical flow orientation descriptor are illustrated for describing movement information of the global video frame or foreground frame. By combining one-class support vector machine and kernel principal component analysis methods, the abnormal events in the current frame can be detected after a learning period characterizing normal behaviors. The difference abnormal detection results are analyzed and explained. The proposed detection method is tested on benchmark datasets, then the experimental results show the effectiveness of the algorithm.

  2. Detection of Abnormal Events via Optical Flow Feature Analysis

    PubMed Central

    Wang, Tian; Snoussi, Hichem

    2015-01-01

    In this paper, a novel algorithm is proposed to detect abnormal events in video streams. The algorithm is based on the histogram of the optical flow orientation descriptor and the classification method. The details of the histogram of the optical flow orientation descriptor are illustrated for describing movement information of the global video frame or foreground frame. By combining one-class support vector machine and kernel principal component analysis methods, the abnormal events in the current frame can be detected after a learning period characterizing normal behaviors. The difference abnormal detection results are analyzed and explained. The proposed detection method is tested on benchmark datasets, then the experimental results show the effectiveness of the algorithm. PMID:25811227

  3. A computational method for reliable gait event detection and abnormality detection for feedback in rehabilitation.

    PubMed

    Senanayake, Chathuri; Senanayake, S M N Arosha

    2011-10-01

    In this paper, a gait event detection algorithm is presented that uses computer intelligence (fuzzy logic) to identify seven gait phases in walking gait. Two inertial measurement units and four force-sensitive resistors were used to obtain knee angle and foot pressure patterns, respectively. Fuzzy logic is used to address the complexity in distinguishing gait phases based on discrete events. A novel application of the seven-dimensional vector analysis method to estimate the amount of abnormalities detected was also investigated based on the two gait parameters. Experiments were carried out to validate the application of the two proposed algorithms to provide accurate feedback in rehabilitation. The algorithm responses were tested for two cases, normal and abnormal gait. The large amount of data required for reliable gait-phase detection necessitate the utilisation of computer methods to store and manage the data. Therefore, a database management system and an interactive graphical user interface were developed for the utilisation of the overall system in a clinical environment.

  4. Online Least Squares One-Class Support Vector Machines-Based Abnormal Visual Event Detection

    PubMed Central

    Wang, Tian; Chen, Jie; Zhou, Yi; Snoussi, Hichem

    2013-01-01

    The abnormal event detection problem is an important subject in real-time video surveillance. In this paper, we propose a novel online one-class classification algorithm, online least squares one-class support vector machine (online LS-OC-SVM), combined with its sparsified version (sparse online LS-OC-SVM). LS-OC-SVM extracts a hyperplane as an optimal description of training objects in a regularized least squares sense. The online LS-OC-SVM learns a training set with a limited number of samples to provide a basic normal model, then updates the model through remaining data. In the sparse online scheme, the model complexity is controlled by the coherence criterion. The online LS-OC-SVM is adopted to handle the abnormal event detection problem. Each frame of the video is characterized by the covariance matrix descriptor encoding the moving information, then is classified into a normal or an abnormal frame. Experiments are conducted, on a two-dimensional synthetic distribution dataset and a benchmark video surveillance dataset, to demonstrate the promising results of the proposed online LS-OC-SVM method. PMID:24351629

  5. Online least squares one-class support vector machines-based abnormal visual event detection.

    PubMed

    Wang, Tian; Chen, Jie; Zhou, Yi; Snoussi, Hichem

    2013-12-12

    The abnormal event detection problem is an important subject in real-time video surveillance. In this paper, we propose a novel online one-class classification algorithm, online least squares one-class support vector machine (online LS-OC-SVM), combined with its sparsified version (sparse online LS-OC-SVM). LS-OC-SVM extracts a hyperplane as an optimal description of training objects in a regularized least squares sense. The online LS-OC-SVM learns a training set with a limited number of samples to provide a basic normal model, then updates the model through remaining data. In the sparse online scheme, the model complexity is controlled by the coherence criterion. The online LS-OC-SVM is adopted to handle the abnormal event detection problem. Each frame of the video is characterized by the covariance matrix descriptor encoding the moving information, then is classified into a normal or an abnormal frame. Experiments are conducted, on a two-dimensional synthetic distribution dataset and a benchmark video surveillance dataset, to demonstrate the promising results of the proposed online LS-OC-SVM method.

  6. Online least squares one-class support vector machines-based abnormal visual event detection.

    PubMed

    Wang, Tian; Chen, Jie; Zhou, Yi; Snoussi, Hichem

    2013-01-01

    The abnormal event detection problem is an important subject in real-time video surveillance. In this paper, we propose a novel online one-class classification algorithm, online least squares one-class support vector machine (online LS-OC-SVM), combined with its sparsified version (sparse online LS-OC-SVM). LS-OC-SVM extracts a hyperplane as an optimal description of training objects in a regularized least squares sense. The online LS-OC-SVM learns a training set with a limited number of samples to provide a basic normal model, then updates the model through remaining data. In the sparse online scheme, the model complexity is controlled by the coherence criterion. The online LS-OC-SVM is adopted to handle the abnormal event detection problem. Each frame of the video is characterized by the covariance matrix descriptor encoding the moving information, then is classified into a normal or an abnormal frame. Experiments are conducted, on a two-dimensional synthetic distribution dataset and a benchmark video surveillance dataset, to demonstrate the promising results of the proposed online LS-OC-SVM method. PMID:24351629

  7. Real-Time Microbiology Laboratory Surveillance System to Detect Abnormal Events and Emerging Infections, Marseille, France.

    PubMed

    Abat, Cédric; Chaudet, Hervé; Colson, Philippe; Rolain, Jean-Marc; Raoult, Didier

    2015-08-01

    Infectious diseases are a major threat to humanity, and accurate surveillance is essential. We describe how to implement a laboratory data-based surveillance system in a clinical microbiology laboratory. Two historical Microsoft Excel databases were implemented. The data were then sorted and used to execute the following 2 surveillance systems in Excel: the Bacterial real-time Laboratory-based Surveillance System (BALYSES) for monitoring the number of patients infected with bacterial species isolated at least once in our laboratory during the study periodl and the Marseille Antibiotic Resistance Surveillance System (MARSS), which surveys the primary β-lactam resistance phenotypes for 15 selected bacterial species. The first historical database contained 174,853 identifications of bacteria, and the second contained 12,062 results of antibiotic susceptibility testing. From May 21, 2013, through June 4, 2014, BALYSES and MARSS enabled the detection of 52 abnormal events for 24 bacterial species, leading to 19 official reports. This system is currently being refined and improved.

  8. Architecture design of the multi-functional wavelet-based ECG microprocessor for realtime detection of abnormal cardiac events.

    PubMed

    Cheng, Li-Fang; Chen, Tung-Chien; Chen, Liang-Gee

    2012-01-01

    Most of the abnormal cardiac events such as myocardial ischemia, acute myocardial infarction (AMI) and fatal arrhythmia can be diagnosed through continuous electrocardiogram (ECG) analysis. According to recent clinical research, early detection and alarming of such cardiac events can reduce the time delay to the hospital, and the clinical outcomes of these individuals can be greatly improved. Therefore, it would be helpful if there is a long-term ECG monitoring system with the ability to identify abnormal cardiac events and provide realtime warning for the users. The combination of the wireless body area sensor network (BASN) and the on-sensor ECG processor is a possible solution for this application. In this paper, we aim to design and implement a digital signal processor that is suitable for continuous ECG monitoring and alarming based on the continuous wavelet transform (CWT) through the proposed architectures--using both programmable RISC processor and application specific integrated circuits (ASIC) for performance optimization. According to the implementation results, the power consumption of the proposed processor integrated with an ASIC for CWT computation is only 79.4 mW. Compared with the single-RISC processor, about 91.6% of the power reduction is achieved.

  9. Abnormal behaviors detection using particle motion model

    NASA Astrophysics Data System (ADS)

    Chen, Yutao; Zhang, Hong; Cheng, Feiyang; Yuan, Ding; You, Yuhu

    2015-03-01

    Human abnormal behaviors detection is one of the most challenging tasks in the video surveillance for the public security control. Interaction Energy Potential model is an effective and competitive method published recently to detect abnormal behaviors, but their model of abnormal behaviors is not accurate enough, so it has some limitations. In order to solve this problem, we propose a novel Particle Motion model. Firstly, we extract the foreground to improve the accuracy of interest points detection since the complex background usually degrade the effectiveness of interest points detection largely. Secondly, we detect the interest points using the graphics features. Here, the movement of each human target can be represented by the movements of detected interest points of the target. Then, we track these interest points in videos to record their positions and velocities. In this way, the velocity angles, position angles and distance between each two points can be calculated. Finally, we proposed a Particle Motion model to calculate the eigenvalue of each frame. An adaptive threshold method is proposed to detect abnormal behaviors. Experimental results on the BEHAVE dataset and online videos show that our method could detect fight and robbery events effectively and has a promising performance.

  10. Varenicline and Abnormal Sleep Related Events

    PubMed Central

    Savage, Ruth L.; Zekarias, Alem; Caduff-Janosa, Pia

    2015-01-01

    Study Objectives: To assess adverse drug reaction reports of “abnormal sleep related events” associated with varenicline, a partial agonist to the α4β2 subtype of nicotinic acetylcholine receptors on neurones, indicated for smoking cessation. Design: Twenty-seven reports of “abnormal sleep related events” often associated with abnormal dreams, nightmares, or somnambulism, which are known to be associated with varenicline use, were identified in the World Health Organisation (WHO) Global Individual Case Safety Reports Database. Original anonymous reports were obtained from the four national pharmacovigilance centers that submitted these reports and assessed for reaction description and causality. Measurements and Results: These 27 reports include 10 of aggressive activity occurring during sleep and seven of other sleep related harmful or potentially harmful activities, such as apparently deliberate self-harm, moving a child or a car, or lighting a stove or a cigarette. Assessment of these 17 reports of aggression or other actual or potential harm showed that nine patients recovered or were recovering on varenicline withdrawal and there were no consistent alternative explanations. Thirteen patients experienced single events, and two had multiple events. Frequency was not stated for the remaining two patients. Conclusions: The descriptions of the reports of aggression during sleep with violent dreaming are similar to those of rapid eye movement sleep behavior disorder and also nonrapid eye movement (NREM) sleep parasomnias in some adults. Patients who experience somnambulism or dreams of a violent nature while taking varenicline should be advised to consult their health providers. Consideration should be given to clarifying the term sleep disorders in varenicline product information and including sleep related harmful and potentially harmful events. Citation: Savage RL, Zekarias A, Caduff-Janosa P. Varenicline and abnormal sleep related events. SLEEP 2015

  11. Detection of Structural Abnormalities Using Neural Nets

    NASA Technical Reports Server (NTRS)

    Zak, M.; Maccalla, A.; Daggumati, V.; Gulati, S.; Toomarian, N.

    1996-01-01

    This paper describes a feed-forward neural net approach for detection of abnormal system behavior based upon sensor data analyses. A new dynamical invariant representing structural parameters of the system is introduced in such a way that any structural abnormalities in the system behavior are detected from the corresponding changes to the invariant.

  12. Detection of anomalous events

    DOEpatents

    Ferragut, Erik M.; Laska, Jason A.; Bridges, Robert A.

    2016-06-07

    A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The system can include a plurality of anomaly detectors that together implement an algorithm to identify low-probability events and detect atypical traffic patterns. The anomaly detector provides for comparability of disparate sources of data (e.g., network flow data and firewall logs.) Additionally, the anomaly detector allows for regulatability, meaning that the algorithm can be user configurable to adjust a number of false alerts. The anomaly detector can be used for a variety of probability density functions, including normal Gaussian distributions, irregular distributions, as well as functions associated with continuous or discrete variables.

  13. Detection of solar events

    DOEpatents

    Fischbach, Ephraim; Jenkins, Jere

    2013-08-27

    A flux detection apparatus can include a radioactive sample having a decay rate capable of changing in response to interaction with a first particle or a field, and a detector associated with the radioactive sample. The detector is responsive to a second particle or radiation formed by decay of the radioactive sample. The rate of decay of the radioactive sample can be correlated to flux of the first particle or the field. Detection of the first particle or the field can provide an early warning for an impending solar event.

  14. Unsupervised detection of abnormalities in medical images using salient features

    NASA Astrophysics Data System (ADS)

    Alpert, Sharon; Kisilev, Pavel

    2014-03-01

    In this paper we propose a new method for abnormality detection in medical images which is based on the notion of medical saliency. The proposed method is general and is suitable for a variety of tasks related to detection of: 1) lesions and microcalcifications (MCC) in mammographic images, 2) stenoses in angiographic images, 3) lesions found in magnetic resonance (MRI) images of brain. The main idea of our approach is that abnormalities manifest as rare events, that is, as salient areas compared to normal tissues. We define the notion of medical saliency by combining local patch information from the lightness channel with geometric shape local descriptors. We demonstrate the efficacy of the proposed method by applying it to various modalities, and to various abnormality detection problems. Promising results are demonstrated for detection of MCC and of masses in mammographic images, detection of stenoses in angiography images, and detection of lesions in brain MRI. We also demonstrate how the proposed automatic abnormality detection method can be combined with a system that performs supervised classification of mammogram images into benign or malignant/premalignant MCC's. We use a well known DDSM mammogram database for the experiment on MCC classification, and obtain 80% accuracy in classifying images containing premalignant MCC versus benign ones. In contrast to supervised detection methods, the proposed approach does not rely on ground truth markings, and, as such, is very attractive and applicable for big corpus image data processing.

  15. Abnormal Activity Detection Using Pyroelectric Infrared Sensors

    PubMed Central

    Luo, Xiaomu; Tan, Huoyuan; Guan, Qiuju; Liu, Tong; Zhuo, Hankz Hankui; Shen, Baihua

    2016-01-01

    Healthy aging is one of the most important social issues. In this paper, we propose a method for abnormal activity detection without any manual labeling of the training samples. By leveraging the Field of View (FOV) modulation, the spatio-temporal characteristic of human activity is encoded into low-dimension data stream generated by the ceiling-mounted Pyroelectric Infrared (PIR) sensors. The similarity between normal training samples are measured based on Kullback-Leibler (KL) divergence of each pair of them. The natural clustering of normal activities is discovered through a self-tuning spectral clustering algorithm with unsupervised model selection on the eigenvectors of a modified similarity matrix. Hidden Markov Models (HMMs) are employed to model each cluster of normal activities and form feature vectors. One-Class Support Vector Machines (OSVMs) are used to profile the normal activities and detect abnormal activities. To validate the efficacy of our method, we conducted experiments in real indoor environments. The encouraging results show that our method is able to detect abnormal activities given only the normal training samples, which aims to avoid the laborious and inconsistent data labeling process. PMID:27271632

  16. Abnormality degree detection method using negative potential field group detectors

    NASA Astrophysics Data System (ADS)

    Zhang, Hongli; Liu, Shulin; Li, Dong; Shi, Kunju; Wang, Bo; Cui, Jiqiang

    2015-09-01

    Online monitoring methods have been widely used in many major devices, however the normal and abnormal states of equipment are estimated mainly based on the monitoring results whether monitored parameters exceed the setting thresholds. Using these monitoring methods may cause serious false positive or false negative results. In order to precisely monitor the state of equipment, the problem of abnormality degree detection without fault sample is studied with a new detection method called negative potential field group detectors(NPFG-detectors). This method achieves the quantitative expression of abnormality degree and provides the better detection results compared with other methods. In the process of Iris data set simulation, the new algorithm obtains the successful results in abnormal detection. The detection rates for 3 types of Iris data set respectively reach 100%, 91.6%, and 95.24% with 50% training samples. The problem of Bearing abnormality degree detection via an abnormality degree curve is successfully solved.

  17. Hepatic perfusion abnormalities during CT angiography: Detection and interpretation

    SciTech Connect

    Freeny, P.C.; Marks, W.M.

    1986-06-01

    Twenty-seven perfusion abnormalities were detected in 17 of 50 patients who underwent computed tomographic angiography (CTA) of the liver. All but one of the perfusion abnormalities occurred in patients with primary or metastatic liver tumors. Perfusion abnormalities were lobar in nine cases, segmental in 11, and subsegmental in seven; 14 were hypoperfusion and 13 were hyperperfusion abnormalities. The causes for the abnormalities included nonperfusion of a replaced hepatic artery (n = 11), cirrhosis and nodular regeneration (n = 3), altered hepatic hemodynamics (e.g., siphoning, laminar flow) caused by tumor (n = 7), contrast media washout from a nonperfused vessel (n = 1), compression of adjacent hepatic parenchyma (n = 1), and unknown (n = 4). Differentiation of perfusion abnormalities from tumor usually can be made by comparing the morphology of the known tumor with the suspected perfusion abnormality, changes of each on delayed CTA scans, and review of initial angiograms and other imaging studies.

  18. Improvement of Abnormality Detection System for Bathers Using Ultrasonic Sensors

    NASA Astrophysics Data System (ADS)

    Dobashi, Hiroki; Tajima, Takuya; Abe, Takehiko; Nambo, Hidetaka; Kimura, Haruhiko

    This paper proposes a new method for improving an existing abnormality detection system for person who soaks in a bathtub. As the number of aged people increases year by year in Japan, bathing accident of the aged is growing at a rapid rate, especially in-bathtub drowning accident. Therefore, prompt detection of bather's abnormality such as dizziness and fainting is important to prevent in-bathtub drowning. In order to detect bather's abnormality promptly, an abnormality detection system using seven ultrasonic sensors has been proposed. The system uses the following two methods: posture detection and behavior detection, to detect bather's different state from normal before an accident occurs, and improves a delay of detection considered to be a serious problem heretofore. There was however plenty of room for improvement. In order to improve detection rate of the system, we propose a new detection method in this paper. The method uses two ultrasonic sensors to beam bather's head and neck, and detects the head height and swing speed of the head. Experimental results are superior to the accuracy of the existing system, which enables us to detect bather's abnormality more accurately.

  19. Detection of abnormalities in a human gait using smart shoes

    NASA Astrophysics Data System (ADS)

    Kong, Kyoungchul; Bae, Joonbum; Tomizuka, Masayoshi

    2008-03-01

    Health monitoring systems require a means for detecting and quantifying abnormalities from measured signals. In this paper, a new method for detecting abnormalities in a human gait is proposed for an improved gait monitoring system for patients with walking problems. In the previous work, we introduced a fuzzy logic algorithm for detecting phases in a human gait based on four foot pressure sensors for each of the right and left foot. The fuzzy logic algorithm detects the gait phases smoothly and continuously, and retains all information obtained from sensors. In this paper, a higher level algorithm for detecting abnormalities in the gait phases obtained from the fuzzy logic is discussed. In the proposed algorithm, two major abnormalities are detected 1) when the sensors measure improper foot pressure patterns, and 2) when the human does not follow a natural sequence of gait phases. For mathematical realization of the algorithm, the gait phases are dealt with by a vector analysis method. The proposed detection algorithm is verified by experiments on abnormal gaits as well as normal gaits. The experiment makes use of the Smart Shoes that embeds four bladders filled with air, the pressure changes in which are detected by pressure transducers.

  20. Development of Abnormality Detection System for Bathers using Ultrasonic Sensors

    NASA Astrophysics Data System (ADS)

    Ohnishi, Yosuke; Abe, Takehiko; Nambo, Hidetaka; Kimura, Haruhiko; Ogoshi, Yasuhiro

    This paper proposes an abnormality detection system for bather sitting in bathtub. Increasing number of in-bathtub drowning accidents in Japan draws attention. Behind this large number of bathing accidents, Japan's unique social and cultural background come surface. For majority of people in Japan, bathing serves purpose in deep warming up of body, relax and enjoyable time. Therefore it is the custom for the Japanese to soak in bathtub. However overexposure to hot water may cause dizziness or fainting, which is possible to cause in-bathtub drowning. For drowning prevention, the system detects bather's abnormal state using an ultrasonic sensor array. The array, which has many ultrasonic sensors, is installed on the ceiling of bathroom above bathtub. The abnormality detection system uses the following two methods: posture detection and behavior detection. The function of posture detection is to estimate the risk of drowning by monitoring bather's posture. Meanwhile, the function of behavior detection is to estimate the risk of drowning by monitoring bather's behavior. By using these methods, the system detects bathers' different state from normal. As a result of experiment with a subject in the bathtub, the system was possible to detect abnormal state using subject's posture and behavior. Therefore the system is useful for monitoring bather to prevent drowning in bathtub.

  1. [Neural network detection of abnormalities in fed-batch fermentation].

    PubMed

    Li, Yun-Feng; Yuan, Jing-Qi

    2005-01-01

    During fermentation, it is often difficult to detect the abnormalities, for example, caused by contamination on-line. Instead, the faults were detected usually by off-line laboratory analysis or other ways, which in most cases, is too late to remedy the situation. In this paper, a simple three-layers BP network was used for the early prediction of the amount of product, based on the difference in prediction errors between normal and abnormal charges and other accessorial information, such as profit function and pH value. In addition, three indications characteristic to abnormal charge are incorporated in practical operation. The prediction for Cephalosporin C Fed-batch Fermentation in a Chinese pharmaceutical factory was studied in details as an example and the result shows the abnormal charge can be discovered early successfully using the method. PMID:15859337

  2. Detecting Abnormal Machine Characteristics in Cloud Infrastructures

    NASA Technical Reports Server (NTRS)

    Bhaduri, Kanishka; Das, Kamalika; Matthews, Bryan L.

    2011-01-01

    In the cloud computing environment resources are accessed as services rather than as a product. Monitoring this system for performance is crucial because of typical pay-peruse packages bought by the users for their jobs. With the huge number of machines currently in the cloud system, it is often extremely difficult for system administrators to keep track of all machines using distributed monitoring programs such as Ganglia1 which lacks system health assessment and summarization capabilities. To overcome this problem, we propose a technique for automated anomaly detection using machine performance data in the cloud. Our algorithm is entirely distributed and runs locally on each computing machine on the cloud in order to rank the machines in order of their anomalous behavior for given jobs. There is no need to centralize any of the performance data for the analysis and at the end of the analysis, our algorithm generates error reports, thereby allowing the system administrators to take corrective actions. Experiments performed on real data sets collected for different jobs validate the fact that our algorithm has a low overhead for tracking anomalous machines in a cloud infrastructure.

  3. Using State Estimation Residuals to Detect Abnormal SCADA Data

    SciTech Connect

    Ma, Jian; Chen, Yousu; Huang, Zhenyu; Wong, Pak C.

    2010-04-30

    Detection of abnormal supervisory control and data acquisition (SCADA) data is critically important for safe and secure operation of modern power systems. In this paper, a methodology of abnormal SCADA data detection based on state estimation residuals is presented. Preceded with a brief overview of outlier detection methods and bad SCADA data detection for state estimation, the framework of the proposed methodology is described. Instead of using original SCADA measurements as the bad data sources, the residuals calculated based on the results of the state estimator are used as the input for the outlier detection algorithm. The BACON algorithm is applied to the outlier detection task. The IEEE 118-bus system is used as a test base to evaluate the effectiveness of the proposed methodology. The accuracy of the BACON method is compared with that of the 3-σ method for the simulated SCADA measurements and residuals.

  4. GPU Accelerated Event Detection Algorithm

    2011-05-25

    Smart grid external require new algorithmic approaches as well as parallel formulations. One of the critical components is the prediction of changes and detection of anomalies within the power grid. The state-of-the-art algorithms are not suited to handle the demands of streaming data analysis. (i) need for events detection algorithms that can scale with the size of data, (ii) need for algorithms that can not only handle multi dimensional nature of the data, but alsomore » model both spatial and temporal dependencies in the data, which, for the most part, are highly nonlinear, (iii) need for algorithms that can operate in an online fashion with streaming data. The GAEDA code is a new online anomaly detection techniques that take into account spatial, temporal, multi-dimensional aspects of the data set. The basic idea behind the proposed approach is to (a) to convert a multi-dimensional sequence into a univariate time series that captures the changes between successive windows extracted from the original sequence using singular value decomposition (SVD), and then (b) to apply known anomaly detection techniques for univariate time series. A key challenge for the proposed approach is to make the algorithm scalable to huge datasets by adopting techniques from perturbation theory, incremental SVD analysis. We used recent advances in tensor decomposition techniques which reduce computational complexity to monitor the change between successive windows and detect anomalies in the same manner as described above. Therefore we propose to develop the parallel solutions on many core systems such as GPUs, because these algorithms involve lot of numerical operations and are highly data-parallelizable.« less

  5. GPU Accelerated Event Detection Algorithm

    SciTech Connect

    2011-05-25

    Smart grid external require new algorithmic approaches as well as parallel formulations. One of the critical components is the prediction of changes and detection of anomalies within the power grid. The state-of-the-art algorithms are not suited to handle the demands of streaming data analysis. (i) need for events detection algorithms that can scale with the size of data, (ii) need for algorithms that can not only handle multi dimensional nature of the data, but also model both spatial and temporal dependencies in the data, which, for the most part, are highly nonlinear, (iii) need for algorithms that can operate in an online fashion with streaming data. The GAEDA code is a new online anomaly detection techniques that take into account spatial, temporal, multi-dimensional aspects of the data set. The basic idea behind the proposed approach is to (a) to convert a multi-dimensional sequence into a univariate time series that captures the changes between successive windows extracted from the original sequence using singular value decomposition (SVD), and then (b) to apply known anomaly detection techniques for univariate time series. A key challenge for the proposed approach is to make the algorithm scalable to huge datasets by adopting techniques from perturbation theory, incremental SVD analysis. We used recent advances in tensor decomposition techniques which reduce computational complexity to monitor the change between successive windows and detect anomalies in the same manner as described above. Therefore we propose to develop the parallel solutions on many core systems such as GPUs, because these algorithms involve lot of numerical operations and are highly data-parallelizable.

  6. Proportionate Responses to Life Events Influence Clinicians' Judgments of Psychological Abnormality

    ERIC Educational Resources Information Center

    Kim, Nancy S.; Paulus, Daniel J.; Gonzalez, Jeffrey S.; Khalife, Danielle

    2012-01-01

    Psychological abnormality is a fundamental concept in the "Diagnostic and Statistical Manual of Mental Disorders" ("DSM-IV-TR"; American Psychiatric Association, 2000) and in all clinical evaluations. How do practicing clinical psychologists use the context of life events to judge the abnormality of a person's current behaviors? The appropriate…

  7. Environmental impact assessment of abnormal events: a follow-up study

    SciTech Connect

    Hunsaker, D.B. Jr.; Lee, D.W.

    1985-01-01

    Impact analyses included in environmental assessments for a selected nuclear power plant, petroleum storage facility, crude oil pipeline, and geopressure well that have experienced operational, abnormal events are compared with the data quantifying the environmental impacts of the events. Comparisons of predicted vs actual impacts suggests that prediction of the types of events and associated impacts could be improved; in some instances, impacts have been underestimated. Analysis of abnormal events is especially important in environmental assessment documents addressing a technology that is novel or unique to a particular area. Incorporation of abnormal event impact analysis into project environmental monitoring and emergency response plans can help improve these plans and can help reduce the magnitude of environmental impacts resulting from said events.

  8. Guide to good practices for notifications and investigation of abnormal events

    SciTech Connect

    Not Available

    1993-06-01

    This Guide to Good Practices is written to enhance understanding of, and provide direction for, Notifications, Chapter VII, and Investigation of Abnormal Events, Chapter VI, of Department of Energy (DOE) Order 5480.19, ``Conduct of Operations Requirements for DOE Facilities.`` The practices in this guide should be considered when planning or reviewing programs for notifications and investigation of abnormal events. Contractors are advised to adopt procedures that meet the intent of DOE Order 5480.19. ``Notifications`` and ``Investigation of Abnormal Events`` are elements of an effective Conduct of Operations program. The complexity and array of activities performed in DOE facilities dictate the necessity for a coordinated notifications program and a consistent method for investigating abnormal events to promote safe and efficient operations.

  9. Guide to good practices for notifications and investigation of abnormal events

    SciTech Connect

    1998-12-01

    This Guide to Good Practices is written to enhance understanding of, and provide direction for, Notifications, Chapter VII, and Investigation of Abnormal Events, Chapter VI, of Department of Energy (DOE) Order 5480.19, Conduct of Operations Requirements for DOE Facilities. The practices in this guide should be considered when planning or reviewing programs for notifications and investigation of abnormal events. Contractors are advised to adopt procedures that meet the intent of DOE Order 5480.19. Notifications and Investigation of Abnormal Events are elements of an effective Conduct of Operations program. The complexity and array of activities performed in DOE facilities dictate the necessity for a coordinated notifications program and a consistent method for investigating abnormal events to promote safe and efficient operations.

  10. Methods and systems for detecting abnormal digital traffic

    DOEpatents

    Goranson, Craig A [Kennewick, WA; Burnette, John R [Kennewick, WA

    2011-03-22

    Aspects of the present invention encompass methods and systems for detecting abnormal digital traffic by assigning characterizations of network behaviors according to knowledge nodes and calculating a confidence value based on the characterizations from at least one knowledge node and on weighting factors associated with the knowledge nodes. The knowledge nodes include a characterization model based on prior network information. At least one of the knowledge nodes should not be based on fixed thresholds or signatures. The confidence value includes a quantification of the degree of confidence that the network behaviors constitute abnormal network traffic.

  11. Rare Event Detection Algorithm Of Water Quality

    NASA Astrophysics Data System (ADS)

    Ungs, M. J.

    2011-12-01

    A novel method is presented describing the development and implementation of an on-line water quality event detection algorithm. An algorithm was developed to distinguish between normal variation in water quality parameters and changes in these parameters triggered by the presence of contaminant spikes. Emphasis is placed on simultaneously limiting the number of false alarms (which are called false positives) that occur and the number of misses (called false negatives). The problem of excessive false alarms is common to existing change detection algorithms. EPA's standard measure of evaluation for event detection algorithms is to have a false alarm rate of less than 0.5 percent and a false positive rate less than 2 percent (EPA 817-R-07-002). A detailed description of the algorithm's development is presented. The algorithm is tested using historical water quality data collected by a public water supply agency at multiple locations and using spiking contaminants developed by the USEPA, Water Security Division. The water quality parameters of specific conductivity, chlorine residual, total organic carbon, pH, and oxidation reduction potential are considered. Abnormal data sets are generated by superimposing water quality changes on the historical or baseline data. Eddies-ET has defined reaction expressions which specify how the peak or spike concentration of a particular contaminant affects each water quality parameter. Nine default contaminants (Eddies-ET) were previously derived from pipe-loop tests performed at EPA's National Homeland Security Research Center (NHSRC) Test and Evaluation (T&E) Facility. A contaminant strength value of approximately 1.5 is considered to be a significant threat. The proposed algorithm has been able to achieve a combined false alarm rate of less than 0.03 percent for both false positives and for false negatives using contaminant spikes of strength 2 or more.

  12. On forecasting abnormal climatic events in the tropical Atlantic Ocean

    NASA Astrophysics Data System (ADS)

    Servain, Jacques; Arnault, Sabine

    1995-09-01

    Modelling and observational evidence indicate that interannual variabilities of dynamic height and sea surface temperature (SST) in the eastern part of the tropical Atlantic Ocean (Gulf of Guinea) are largely induced by preceding fluctuations in wind stress, mainly in the western equatorial basin. A wind-driven linear ocean model is used here to test the possibility of forecasting the abnormal dynamic heights. A control run of the model, forced by 1964-1993 wind stress monthly means, is first conducted. Yearly test runs (1964-1994) are subsequently performed from January to August by forcing the model with observed winds from January to May, and then by forcing with the May wind assumed to persist from June to August. During the last three decades the largest deviations of dynamic height simulated by the control run in the Gulf of Guinea in boreal summer would have been correctly forecast from wind data related only to conditions in May of each year. However, for weak climatic anomalies, the model may forecast overestimated values. For the most part (about 20 times during the last 30 years), the sign of the observed SST anomaly in the centre of the Gulf of Guinea during the boreal summer is identical to the sign of simulated anomalies of dynamic height deduced from both control and test runs. Along the eastern equatorial waveguide, the sea level forecasting skill slowly decreases from the first 2 weeks of June until the second 2 weeks of August, but remains high on both sides of the equator throughout boreal summer, as is expected from the adjustment in a linear ocean model. It is established that throughout the year in the Gulf of Guinea the accuracy of the 1-month forecast dynamic height anomaly provided by the simple linear method is greater than that of the 1-month forecast assuming persistence. Acknowledgements. The authors are grateful to Prof. A. K. Sen of the Institute of Radio Physics and Electronics, University of Calcutta for valuable discussions. One of

  13. Event oriented dictionary learning for complex event detection.

    PubMed

    Yan, Yan; Yang, Yi; Meng, Deyu; Liu, Gaowen; Tong, Wei; Hauptmann, Alexander G; Sebe, Nicu

    2015-06-01

    Complex event detection is a retrieval task with the goal of finding videos of a particular event in a large-scale unconstrained Internet video archive, given example videos and text descriptions. Nowadays, different multimodal fusion schemes of low-level and high-level features are extensively investigated and evaluated for the complex event detection task. However, how to effectively select the high-level semantic meaningful concepts from a large pool to assist complex event detection is rarely studied in the literature. In this paper, we propose a novel strategy to automatically select semantic meaningful concepts for the event detection task based on both the events-kit text descriptions and the concepts high-level feature descriptions. Moreover, we introduce a novel event oriented dictionary representation based on the selected semantic concepts. Toward this goal, we leverage training images (frames) of selected concepts from the semantic indexing dataset with a pool of 346 concepts, into a novel supervised multitask lp -norm dictionary learning framework. Extensive experimental results on TRECVID multimedia event detection dataset demonstrate the efficacy of our proposed method. PMID:25794390

  14. How to accurately detect autobiographical events.

    PubMed

    Sartori, Giuseppe; Agosta, Sara; Zogmaister, Cristina; Ferrara, Santo Davide; Castiello, Umberto

    2008-08-01

    We describe a new method, based on indirect measures of implicit autobiographical memory, that allows evaluation of which of two contrasting autobiographical events (e.g., crimes) is true for a given individual. Participants were requested to classify sentences describing possible autobiographical events by pressing one of two response keys. Responses were faster when sentences related to truly autobiographical events shared the same response key with other sentences reporting true events and slower when sentences related to truly autobiographical events shared the same response key with sentences reporting false events. This method has possible application in forensic settings and as a lie-detection technique.

  15. Applying data mining techniques to detect abnormal flight characteristics

    NASA Astrophysics Data System (ADS)

    Aslaner, H. E.; Unal, Cagri; Iyigun, Cem

    2016-05-01

    This paper targets to highlight flight safety issues by applying data mining techniques to recorded flight data and proactively detecting abnormalities in certain flight phases. For this purpose, a result oriented method is offered which facilitates the process of post flight data analysis. In the first part of the study, a common time period of flight is defined and critical flight parameters are selected to be analyzed. Then the similarities of the flight parameters in time series basis are calculated for each flight by using Dynamic Time Warping (DTW) method. In the second part, hierarchical clustering technique is applied to the aggregate data matrix which is comprised of all the flights to be studied in terms of similarities among chosen parameters. Consequently, proximity levels among flight phases are determined. In the final part, an algorithm is constructed to distinguish outliers from clusters and classify them as suspicious flights.

  16. Detecting Extreme Events in Gridded Climate Data

    SciTech Connect

    Ramachandra, Bharathkumar; Gadiraju, Krishna; Vatsavai, Raju; Kaiser, Dale Patrick; Karnowski, Thomas Paul

    2016-01-01

    Detecting and tracking extreme events in gridded climatological data is a challenging problem on several fronts: algorithms, scalability, and I/O. Successful detection of these events will give climate scientists an alternate view of the behavior of different climatological variables, leading to enhanced scientific understanding of the impacts of events such as heat and cold waves, and on a larger scale, the El Nin o Southern Oscillation. Recent advances in computing power and research in data sciences enabled us to look at this problem with a different perspective from what was previously possible. In this paper we present our computationally efficient algorithms for anomalous cluster detection on climate change big data. We provide results on detection and tracking of surface temperature and geopotential height anomalies, a trend analysis, and a study of relationships between the variables. We also identify the limitations of our approaches, future directions for research and alternate approaches.

  17. Semantic Context Detection Using Audio Event Fusion

    NASA Astrophysics Data System (ADS)

    Chu, Wei-Ta; Cheng, Wen-Huang; Wu, Ja-Ling

    2006-12-01

    Semantic-level content analysis is a crucial issue in achieving efficient content retrieval and management. We propose a hierarchical approach that models audio events over a time series in order to accomplish semantic context detection. Two levels of modeling, audio event and semantic context modeling, are devised to bridge the gap between physical audio features and semantic concepts. In this work, hidden Markov models (HMMs) are used to model four representative audio events, that is, gunshot, explosion, engine, and car braking, in action movies. At the semantic context level, generative (ergodic hidden Markov model) and discriminative (support vector machine (SVM)) approaches are investigated to fuse the characteristics and correlations among audio events, which provide cues for detecting gunplay and car-chasing scenes. The experimental results demonstrate the effectiveness of the proposed approaches and provide a preliminary framework for information mining by using audio characteristics.

  18. Detection of cryptic chromosomal abnormalities in unexplained mental retardation: a general strategy using hypervariable subtelomeric DNA polymorphisms.

    PubMed Central

    Wilkie, A O

    1993-01-01

    Given the availability of DNA from both parents, unusual segregation of hypervariable DNA polymorphisms (HVPs) in the offspring may be attributable to deletion, unbalanced chromosomal translocation, or uniparental disomy. The telomeric regions of chromosomes are rich in both genes and hypervariable minisatellite sequences and may also be particularly prone to cryptic breakage events. Here I describe and analyze a general approach to the detection of subtelomeric abnormalities and uniparental disomy in patients with unexplained mental retardation. With 29 available polymorphic systems, approximately 50%-70% of these abnormalities could currently be detected. Development of subtelomeric HVPs physically localized with respect to their telomeres should provide a valuable resource in routine diagnostics. PMID:8352277

  19. Automated Detection of Events of Scientific Interest

    NASA Technical Reports Server (NTRS)

    James, Mark

    2007-01-01

    A report presents a slightly different perspective of the subject matter of Fusing Symbolic and Numerical Diagnostic Computations (NPO-42512), which appears elsewhere in this issue of NASA Tech Briefs. Briefly, the subject matter is the X-2000 Anomaly Detection Language, which is a developmental computing language for fusing two diagnostic computer programs one implementing a numerical analysis method, the other implementing a symbolic analysis method into a unified event-based decision analysis software system for real-time detection of events. In the case of the cited companion NASA Tech Briefs article, the contemplated events that one seeks to detect would be primarily failures or other changes that could adversely affect the safety or success of a spacecraft mission. In the case of the instant report, the events to be detected could also include natural phenomena that could be of scientific interest. Hence, the use of X- 2000 Anomaly Detection Language could contribute to a capability for automated, coordinated use of multiple sensors and sensor-output-data-processing hardware and software to effect opportunistic collection and analysis of scientific data.

  20. Abnormal/Emergency Situations. Impact of Unmanned Aircraft Systems Emergency and Abnormal Events on the National Airspace System

    NASA Technical Reports Server (NTRS)

    2006-01-01

    Access 5 analyzed the differences between UAS and manned aircraft operations under five categories of abnormal or emergency situations: Link Failure, Lost Communications, Onboard System Failures, Control Station Failures and Abnormal Weather. These analyses were made from the vantage point of the impact that these operations have on the US air traffic control system, with recommendations for new policies and procedures included where appropriate.

  1. Abnormal Policy Detection and Correction Using Overlapping Transition

    NASA Astrophysics Data System (ADS)

    Kim, Sunghyun; Lee, Heejo

    Policy in security devices such as firewalls and Network Intrusion Prevention Systems (NIPS) is usually implemented as a sequence of rules. This allows network packets to proceed or to be discarded based on rule's decision. Since attack methods are increasing rapidly, a huge number of security rules are generated and maintained in security devices. Under attack or during heavy traffic, the policy configured wrong creates security holes and prevents the system from deciding quickly whether to allow or deny a packet. Anomalies between the rules occur when there is overlap among the rules. In this paper, we propose a new method to detect anomalies among rules and generate new rules without configuration error in multiple security devices as well as in a single security device. The proposed method cuts the overlap regions among rules into minimum overlap regions and finds the abnormal domain regions of rules' predicates. Classifying rules by the network traffic flow, the proposed method not only reduces computation overhead but blocks unnecessary traffic among distributed devices.

  2. Methodology to automatically detect abnormal values of vital parameters in anesthesia time-series: Proposal for an adaptable algorithm.

    PubMed

    Lamer, Antoine; Jeanne, Mathieu; Marcilly, Romaric; Kipnis, Eric; Schiro, Jessica; Logier, Régis; Tavernier, Benoît

    2016-06-01

    Abnormal values of vital parameters such as hypotension or tachycardia may occur during anesthesia and may be detected by analyzing time-series data collected during the procedure by the Anesthesia Information Management System. When crossed with other data from the Hospital Information System, abnormal values of vital parameters have been linked with postoperative morbidity and mortality. However, methods for the automatic detection of these events are poorly documented in the literature and differ between studies, making it difficult to reproduce results. In this paper, we propose a methodology for the automatic detection of abnormal values of vital parameters. This methodology uses an algorithm allowing the configuration of threshold values for any vital parameters as well as the management of missing data. Four examples illustrate the application of the algorithm, after which it is applied to three vital signs (heart rate, SpO2, and mean arterial pressure) to all 2014 anesthetic records at our institution. PMID:26817405

  3. Subnoise detection of a fast random event.

    PubMed

    Ataie, V; Esman, D; Kuo, B P-P; Alic, N; Radic, S

    2015-12-11

    Observation of random, nonrepetitive phenomena is of critical importance in astronomy, spectroscopy, biology, and remote sensing. Heralded by weak signals, hidden in noise, they pose basic detection challenges. In contrast to repetitive waveforms, a single-instance signal cannot be separated from noise through averaging. Here, we show that a fast, randomly occurring event can be detected and extracted from a noisy background without conventional averaging. An isolated 80-picosecond pulse was received with confidence level exceeding 99%, even when accompanied by noise. Our detector relies on instantaneous spectral cloning and a single-step, coherent field processor. The ability to extract fast, subnoise events is expected to increase detection sensitivity in multiple disciplines. Additionally, the new spectral-cloning receiver can potentially intercept communication signals that are presently considered secure. PMID:26659052

  4. Detection and diagnosis of abnormal transients in nuclear power plants

    SciTech Connect

    Lee, J.C.; Rank, P.J.; Hawkes, E.; Wehe, D.K. . Dept. of Nuclear Engineering); Reifman, J. )

    1991-01-01

    This document describes a simulation-based algorithm that combines fuzzy logic with macroscopic conservation equations to diagnose multiple-failure events subject to uncertainties in transient data. Clusters of single-failure data points of similar characteristics are obtained through a pattern recognition algorithm and the cluster centers are combined in the space of macroscopic inventory derivatives to generate multiple-failure cluster centers. A fuzzy membership function is used to represent the likelihood of a data point belonging to a cluster, and failure estimates are obtained through solution of a fuzzy matrix equation. The algorithm has been successful in detecting simulated malfunctions in the pressurizer of a pressurized water reactor. 11 refs., 9 figs., 1 tab.

  5. Abnormal Trichuris trichiura eggs detected during an epidemiological survey.

    PubMed

    Ferrer-Rodríguez, Iván; Kozek, Wieslaw J

    2007-09-01

    Abnormal eggs of Trichuris trichiura were found in the stools of one of the patients during a study on the prevalence of intestinal parasitoses among an institutionalized population. The abnormalities observed included great variation in shape, size, and color. Similar atypical whipworm eggs have been reported in patients after treatment with mebendazole, thiabendazole, tetracloroethylene, and dithiazanine. Apparently some anthelminthics have an effect on the reproductive system of female T. trichiura, resulting in production of abnormal eggs, which could lead to misdiagnosis of the infection, since they can be mistaken as eggs of other parasites or artifacts.

  6. Phenological Event Detection from Multitemporal Image Data

    SciTech Connect

    Vatsavai, Raju

    2009-01-01

    Monitoring biomass over large geographic regions for seasonal changes in vegetation and crop phenology is important for many applications. In this paper we a present a novel clustering based change detection method using MODIS NDVI time series data. We used well known EM technique to find GMM parameters and Bayesian Information Criteria (BIC) for determining the number of clusters. KL Divergence measure is then used to establish the cluster correspondence across two years (2001 and 2006) to determine changes between these two years. The changes identied were further analyzed for understanding phenological events. This preliminary study shows interesting relationships between key phenological events such as onset, length, end of growing seasons.

  7. Multimedia event detection using visual concept signatures

    NASA Astrophysics Data System (ADS)

    Younessian, Ehsan; Quinn, Michael; Mitamura, Teruko; Hauptmann, Alex

    2013-03-01

    Multimedia Event Detection (MED) is a multimedia retrieval task with the goal of finding videos of a particular event in a large-scale Internet video archive, given example videos and text descriptions. In this paper, we mainly focus on an 'ad-hoc' scenario in MED where we do not use any example video. We aim to retrieve test videos based on their visual semantics using a Visual Concept Signature (VCS) generated for each event only derived from the event description provided as the query. Visual semantics are described using the Semantic INdexing (SIN) feature which represents the likelihood of predefined visual concepts in a video. To generate a VCS for an event, we project the given event description to a visual concept list using the proposed textual semantic similarity. Exploring SIN feature properties, we harmonize the generated visual concept signature and the SIN feature to improve retrieval performance. We conduct different experiments to assess the quality of generated visual concept signatures with respect to human expectation, and in the context of the MED task to retrieve the SIN feature of videos in the test dataset when we have no or only very few training videos.

  8. Detection and recognition of indoor smoking events

    NASA Astrophysics Data System (ADS)

    Bien, Tse-Lun; Lin, Chang Hong

    2013-03-01

    Smoking in public indoor spaces has become prohibited in many countries since it not only affects the health of the people around you, but also increases the risk of fire outbreaks. This paper proposes a novel scheme to automatically detect and recognize smoking events by using exsiting surveillance cameras. The main idea of our proposed method is to detect human smoking events by recognizing their actions. In this scheme, the human pose estimation is introduced to analyze human actions from their poses. The human pose estimation method segments head and both hands from human body parts by using a skin color detection method. However, the skin color methods may fail in insufficient light conditions. Therefore, the lighting compensation is applied to help the skin color detection method become more accurate. Due to the human body parts may be covered by shadows, which may cause the human pose estimation to fail, the Kalman filter is applied to track the missed body parts. After that, we evaluate the probability features of hands approaching the head. The support vector machine (SVM) is applied to learn and recognize the smoking events by the probability features. To analysis the performance of proposed method, the datasets established in the survillance camera view under indoor enviroment are tested. The experimental results show the effectiveness of our proposed method with accuracy rate of 83.33%.

  9. Phase-Space Detection of Cyber Events

    SciTech Connect

    Hernandez Jimenez, Jarilyn M; Ferber, Aaron E; Prowell, Stacy J; Hively, Lee M

    2015-01-01

    Energy Delivery Systems (EDS) are a network of processes that produce, transfer and distribute energy. EDS are increasingly dependent on networked computing assets, as are many Industrial Control Systems. Consequently, cyber-attacks pose a real and pertinent threat, as evidenced by Stuxnet, Shamoon and Dragonfly. Hence, there is a critical need for novel methods to detect, prevent, and mitigate effects of such attacks. To detect cyber-attacks in EDS, we developed a framework for gathering and analyzing timing data that involves establishing a baseline execution profile and then capturing the effect of perturbations in the state from injecting various malware. The data analysis was based on nonlinear dynamics and graph theory to improve detection of anomalous events in cyber applications. The goal was the extraction of changing dynamics or anomalous activity in the underlying computer system. Takens' theorem in nonlinear dynamics allows reconstruction of topologically invariant, time-delay-embedding states from the computer data in a sufficiently high-dimensional space. The resultant dynamical states were nodes, and the state-to-state transitions were links in a mathematical graph. Alternatively, sequential tabulation of executing instructions provides the nodes with corresponding instruction-to-instruction links. Graph theorems guarantee graph-invariant measures to quantify the dynamical changes in the running applications. Results showed a successful detection of cyber events.

  10. LAN attack detection using Discrete Event Systems.

    PubMed

    Hubballi, Neminath; Biswas, Santosh; Roopa, S; Ratti, Ritesh; Nandi, Sukumar

    2011-01-01

    Address Resolution Protocol (ARP) is used for determining the link layer or Medium Access Control (MAC) address of a network host, given its Internet Layer (IP) or Network Layer address. ARP is a stateless protocol and any IP-MAC pairing sent by a host is accepted without verification. This weakness in the ARP may be exploited by malicious hosts in a Local Area Network (LAN) by spoofing IP-MAC pairs. Several schemes have been proposed in the literature to circumvent these attacks; however, these techniques either make IP-MAC pairing static, modify the existing ARP, patch operating systems of all the hosts etc. In this paper we propose a Discrete Event System (DES) approach for Intrusion Detection System (IDS) for LAN specific attacks which do not require any extra constraint like static IP-MAC, changing the ARP etc. A DES model is built for the LAN under both a normal and compromised (i.e., spoofed request/response) situation based on the sequences of ARP related packets. Sequences of ARP events in normal and spoofed scenarios are similar thereby rendering the same DES models for both the cases. To create different ARP events under normal and spoofed conditions the proposed technique uses active ARP probing. However, this probing adds extra ARP traffic in the LAN. Following that a DES detector is built to determine from observed ARP related events, whether the LAN is operating under a normal or compromised situation. The scheme also minimizes extra ARP traffic by probing the source IP-MAC pair of only those ARP packets which are yet to be determined as genuine/spoofed by the detector. Also, spoofed IP-MAC pairs determined by the detector are stored in tables to detect other LAN attacks triggered by spoofing namely, man-in-the-middle (MiTM), denial of service etc. The scheme is successfully validated in a test bed. PMID:20804980

  11. LAN attack detection using Discrete Event Systems.

    PubMed

    Hubballi, Neminath; Biswas, Santosh; Roopa, S; Ratti, Ritesh; Nandi, Sukumar

    2011-01-01

    Address Resolution Protocol (ARP) is used for determining the link layer or Medium Access Control (MAC) address of a network host, given its Internet Layer (IP) or Network Layer address. ARP is a stateless protocol and any IP-MAC pairing sent by a host is accepted without verification. This weakness in the ARP may be exploited by malicious hosts in a Local Area Network (LAN) by spoofing IP-MAC pairs. Several schemes have been proposed in the literature to circumvent these attacks; however, these techniques either make IP-MAC pairing static, modify the existing ARP, patch operating systems of all the hosts etc. In this paper we propose a Discrete Event System (DES) approach for Intrusion Detection System (IDS) for LAN specific attacks which do not require any extra constraint like static IP-MAC, changing the ARP etc. A DES model is built for the LAN under both a normal and compromised (i.e., spoofed request/response) situation based on the sequences of ARP related packets. Sequences of ARP events in normal and spoofed scenarios are similar thereby rendering the same DES models for both the cases. To create different ARP events under normal and spoofed conditions the proposed technique uses active ARP probing. However, this probing adds extra ARP traffic in the LAN. Following that a DES detector is built to determine from observed ARP related events, whether the LAN is operating under a normal or compromised situation. The scheme also minimizes extra ARP traffic by probing the source IP-MAC pair of only those ARP packets which are yet to be determined as genuine/spoofed by the detector. Also, spoofed IP-MAC pairs determined by the detector are stored in tables to detect other LAN attacks triggered by spoofing namely, man-in-the-middle (MiTM), denial of service etc. The scheme is successfully validated in a test bed.

  12. Pickless event detection and location: The waveform correlation event detection system (WCEDS) revisited

    DOE PAGES

    Arrowsmith, Stephen John; Young, Christopher J.; Ballard, Sanford; Slinkard, Megan Elizabeth

    2016-01-01

    The standard paradigm for seismic event monitoring breaks the event detection problem down into a series of processing stages that can be categorized at the highest level into station-level processing and network-level processing algorithms (e.g., Le Bras and Wuster (2002)). At the station-level, waveforms are typically processed to detect signals and identify phases, which may subsequently be updated based on network processing. At the network-level, phase picks are associated to form events, which are subsequently located. Furthermore, waveforms are typically directly exploited only at the station-level, while network-level operations rely on earth models to associate and locate the events thatmore » generated the phase picks.« less

  13. Pickless event detection and location: The waveform correlation event detection system (WCEDS) revisited

    SciTech Connect

    Arrowsmith, Stephen John; Young, Christopher J.; Ballard, Sanford; Slinkard, Megan Elizabeth

    2016-01-01

    The standard paradigm for seismic event monitoring breaks the event detection problem down into a series of processing stages that can be categorized at the highest level into station-level processing and network-level processing algorithms (e.g., Le Bras and Wuster (2002)). At the station-level, waveforms are typically processed to detect signals and identify phases, which may subsequently be updated based on network processing. At the network-level, phase picks are associated to form events, which are subsequently located. Furthermore, waveforms are typically directly exploited only at the station-level, while network-level operations rely on earth models to associate and locate the events that generated the phase picks.

  14. Using State Estimation Residuals to Detect Abnormal SCADA Data

    SciTech Connect

    Ma, Jian; Chen, Yousu; Huang, Zhenyu; Wong, Pak C.

    2010-06-14

    Detection of manipulated supervisory control and data acquisition (SCADA) data is critically important for the safe and secure operation of modern power systems. In this paper, a methodology of detecting manipulated SCADA data based on state estimation residuals is presented. A framework of the proposed methodology is described. Instead of using original SCADA measurements as the bad data sources, the residuals calculated based on the results of the state estimator are used as the input for the outlier detection process. The BACON algorithm is applied to detect outliers in the state estimation residuals. The IEEE 118-bus system is used as a test case to evaluate the effectiveness of the proposed methodology. The accuracy of the BACON method is compared with that of the 3-σ method for the simulated SCADA measurements and residuals.

  15. Object-Oriented Query Language For Events Detection From Images Sequences

    NASA Astrophysics Data System (ADS)

    Ganea, Ion Eugen

    2015-09-01

    In this paper is presented a method to represent the events extracted from images sequences and the query language used for events detection. Using an object oriented model the spatial and temporal relationships between salient objects and also between events are stored and queried. This works aims to unify the storing and querying phases for video events processing. The object oriented language syntax used for events processing allow the instantiation of the indexes classes in order to improve the accuracy of the query results. The experiments were performed on images sequences provided from sport domain and it shows the reliability and the robustness of the proposed language. To extend the language will be added a specific syntax for constructing the templates for abnormal events and for detection of the incidents as the final goal of the research.

  16. Method of detecting genetic translocations identified with chromosomal abnormalities

    DOEpatents

    Gray, Joe W.; Pinkel, Daniel; Tkachuk, Douglas

    2001-01-01

    Methods and compositions for staining based upon nucleic acid sequence that employ nucleic acid probes are provided. Said methods produce staining patterns that can be tailored for specific cytogenetic analyses. Said probes are appropriate for in situ hybridization and stain both interphase and metaphase chromosomal material with reliable signals. The nucleic acid probes are typically of a complexity greater than 50 kb, the complexity depending upon the cytogenetic application. Methods and reagents are provided for the detection of genetic rearrangements. Probes and test kits are provided for use in detecting genetic rearrangements, particularly for use in tumor cytogenetics, in the detection of disease related loci, specifically cancer, such as chronic myelogenous leukemia (CML) and for biological dosimetry. Methods and reagents are described for cytogenetic research, for the differentiation of cytogenetically similar but genetically different diseases, and for many prognostic and diagnostic applications.

  17. Method of detecting genetic deletions identified with chromosomal abnormalities

    DOEpatents

    Gray, Joe W; Pinkel, Daniel; Tkachuk, Douglas

    2013-11-26

    Methods and compositions for staining based upon nucleic acid sequence that employ nucleic acid probes are provided. Said methods produce staining patterns that can be tailored for specific cytogenetic analyzes. Said probes are appropriate for in situ hybridization and stain both interphase and metaphase chromosomal material with reliable signals. The nucleic acids probes are typically of a complexity greater tha 50 kb, the complexity depending upon the cytogenetic application. Methods and reagents are provided for the detection of genetic rearrangements. Probes and test kits are provided for use in detecting genetic rearrangements, particlularly for use in tumor cytogenetics, in the detection of disease related loci, specifically cancer, such as chronic myelogenous leukemia (CML) and for biological dosimetry. Methods and reagents are described for cytogenetic research, for the differentiation of cytogenetically similar ut genetically different diseases, and for many prognostic and diagnostic applications.

  18. Noninvasive detection of fetal subchromosomal abnormalities by semiconductor sequencing of maternal plasma DNA.

    PubMed

    Yin, Ai-hua; Peng, Chun-fang; Zhao, Xin; Caughey, Bennett A; Yang, Jie-xia; Liu, Jian; Huang, Wei-wei; Liu, Chang; Luo, Dong-hong; Liu, Hai-liang; Chen, Yang-yi; Wu, Jing; Hou, Rui; Zhang, Mindy; Ai, Michael; Zheng, Lianghong; Xue, Rachel Q; Mai, Ming-qin; Guo, Fang-fang; Qi, Yi-ming; Wang, Dong-mei; Krawczyk, Michal; Zhang, Daniel; Wang, Yu-nan; Huang, Quan-fei; Karin, Michael; Zhang, Kang

    2015-11-24

    Noninvasive prenatal testing (NIPT) using sequencing of fetal cell-free DNA from maternal plasma has enabled accurate prenatal diagnosis of aneuploidy and become increasingly accepted in clinical practice. We investigated whether NIPT using semiconductor sequencing platform (SSP) could reliably detect subchromosomal deletions/duplications in women carrying high-risk fetuses. We first showed that increasing concentration of abnormal DNA and sequencing depth improved detection. Subsequently, we analyzed plasma from 1,456 pregnant women to develop a method for estimating fetal DNA concentration based on the size distribution of DNA fragments. Finally, we collected plasma from 1,476 pregnant women with fetal structural abnormalities detected on ultrasound who also underwent an invasive diagnostic procedure. We used SSP of maternal plasma DNA to detect subchromosomal abnormalities and validated our results with array comparative genomic hybridization (aCGH). With 3.5 million reads, SSP detected 56 of 78 (71.8%) subchromosomal abnormalities detected by aCGH. With increased sequencing depth up to 10 million reads and restriction of the size of abnormalities to more than 1 Mb, sensitivity improved to 69 of 73 (94.5%). Of 55 false-positive samples, 35 were caused by deletions/duplications present in maternal DNA, indicating the necessity of a validation test to exclude maternal karyotype abnormalities. This study shows that detection of fetal subchromosomal abnormalities is a viable extension of NIPT based on SSP. Although we focused on the application of cell-free DNA sequencing for NIPT, we believe that this method has broader applications for genetic diagnosis, such as analysis of circulating tumor DNA for detection of cancer. PMID:26554006

  19. Noninvasive detection of fetal subchromosomal abnormalities by semiconductor sequencing of maternal plasma DNA.

    PubMed

    Yin, Ai-hua; Peng, Chun-fang; Zhao, Xin; Caughey, Bennett A; Yang, Jie-xia; Liu, Jian; Huang, Wei-wei; Liu, Chang; Luo, Dong-hong; Liu, Hai-liang; Chen, Yang-yi; Wu, Jing; Hou, Rui; Zhang, Mindy; Ai, Michael; Zheng, Lianghong; Xue, Rachel Q; Mai, Ming-qin; Guo, Fang-fang; Qi, Yi-ming; Wang, Dong-mei; Krawczyk, Michal; Zhang, Daniel; Wang, Yu-nan; Huang, Quan-fei; Karin, Michael; Zhang, Kang

    2015-11-24

    Noninvasive prenatal testing (NIPT) using sequencing of fetal cell-free DNA from maternal plasma has enabled accurate prenatal diagnosis of aneuploidy and become increasingly accepted in clinical practice. We investigated whether NIPT using semiconductor sequencing platform (SSP) could reliably detect subchromosomal deletions/duplications in women carrying high-risk fetuses. We first showed that increasing concentration of abnormal DNA and sequencing depth improved detection. Subsequently, we analyzed plasma from 1,456 pregnant women to develop a method for estimating fetal DNA concentration based on the size distribution of DNA fragments. Finally, we collected plasma from 1,476 pregnant women with fetal structural abnormalities detected on ultrasound who also underwent an invasive diagnostic procedure. We used SSP of maternal plasma DNA to detect subchromosomal abnormalities and validated our results with array comparative genomic hybridization (aCGH). With 3.5 million reads, SSP detected 56 of 78 (71.8%) subchromosomal abnormalities detected by aCGH. With increased sequencing depth up to 10 million reads and restriction of the size of abnormalities to more than 1 Mb, sensitivity improved to 69 of 73 (94.5%). Of 55 false-positive samples, 35 were caused by deletions/duplications present in maternal DNA, indicating the necessity of a validation test to exclude maternal karyotype abnormalities. This study shows that detection of fetal subchromosomal abnormalities is a viable extension of NIPT based on SSP. Although we focused on the application of cell-free DNA sequencing for NIPT, we believe that this method has broader applications for genetic diagnosis, such as analysis of circulating tumor DNA for detection of cancer.

  20. Noninvasive detection of fetal subchromosomal abnormalities by semiconductor sequencing of maternal plasma DNA

    PubMed Central

    Yin, Ai-hua; Peng, Chun-fang; Zhao, Xin; Caughey, Bennett A.; Yang, Jie-xia; Liu, Jian; Huang, Wei-wei; Liu, Chang; Luo, Dong-hong; Liu, Hai-liang; Chen, Yang-yi; Wu, Jing; Hou, Rui; Zhang, Mindy; Ai, Michael; Zheng, Lianghong; Xue, Rachel Q.; Mai, Ming-qin; Guo, Fang-fang; Qi, Yi-ming; Wang, Dong-mei; Krawczyk, Michal; Zhang, Daniel; Wang, Yu-nan; Huang, Quan-fei; Karin, Michael; Zhang, Kang

    2015-01-01

    Noninvasive prenatal testing (NIPT) using sequencing of fetal cell-free DNA from maternal plasma has enabled accurate prenatal diagnosis of aneuploidy and become increasingly accepted in clinical practice. We investigated whether NIPT using semiconductor sequencing platform (SSP) could reliably detect subchromosomal deletions/duplications in women carrying high-risk fetuses. We first showed that increasing concentration of abnormal DNA and sequencing depth improved detection. Subsequently, we analyzed plasma from 1,456 pregnant women to develop a method for estimating fetal DNA concentration based on the size distribution of DNA fragments. Finally, we collected plasma from 1,476 pregnant women with fetal structural abnormalities detected on ultrasound who also underwent an invasive diagnostic procedure. We used SSP of maternal plasma DNA to detect subchromosomal abnormalities and validated our results with array comparative genomic hybridization (aCGH). With 3.5 million reads, SSP detected 56 of 78 (71.8%) subchromosomal abnormalities detected by aCGH. With increased sequencing depth up to 10 million reads and restriction of the size of abnormalities to more than 1 Mb, sensitivity improved to 69 of 73 (94.5%). Of 55 false-positive samples, 35 were caused by deletions/duplications present in maternal DNA, indicating the necessity of a validation test to exclude maternal karyotype abnormalities. This study shows that detection of fetal subchromosomal abnormalities is a viable extension of NIPT based on SSP. Although we focused on the application of cell-free DNA sequencing for NIPT, we believe that this method has broader applications for genetic diagnosis, such as analysis of circulating tumor DNA for detection of cancer. PMID:26554006

  1. Prevalence of pre-transplant electrocardiographic abnormalities and post-transplant cardiac events in patients with liver cirrhosis

    PubMed Central

    2014-01-01

    Background Although cardiovascular disease is thouht to be common in cirrhosis, there are no systematic investigations on the prevalence of electrocardiographic (ECG) abnormalities in these patients and data on the occurrence of post-transplant cardiac events in comparison with the general population are lacking. We aimed to study the prevalence and predictors of ECG abnormalities in patients with cirrhosis undergoing liver transplantation and to define the risk of cardiac events post-transplant compared to the general population. Methods Cirrhotic patients undergoing first-time liver transplantation between 1999–2007 were retrospectively enrolled. ECGs at pre-transplant evaluation were reviewed using the Minnesota classification and compared to healthy controls. Standardized incidence ratios for post-transplant cardiac events were calculated. Results 234 patients with cirrhosis were included, 186 with an available ECG (36% with alcoholic and 24% with viral cirrhosis; mean follow-up 4 years). Cirrhotics had a prolonged QTc interval, a Q wave, abnormal QRS axis deviation, ST segment depression and a pathologic T wave more frequently compared to controls (p < 0.05 for all). Arterial hypertension, older age, cirrhosis severity and etiology were related to ECG abnormalities. Compared to the general Swedish population, patients were 14 times more likely to suffer a cardiac event post-transplant (p < 0.001). A prolonged QTc interval and Q wave were related to post-transplant cardiac events (p < 0.05 for all). Conclusions Pre-transplant ECG abnormalities are common in cirrhosis and are associated with cardiovascular risk factors and cirrhosis severity and etiology. Post-transplant cardiac events are more common than in the general population. PMID:24708568

  2. Aircraft Abnormal Conditions Detection, Identification, and Evaluation Using Innate and Adaptive Immune Systems Interaction

    NASA Astrophysics Data System (ADS)

    Al Azzawi, Dia

    Abnormal flight conditions play a major role in aircraft accidents frequently causing loss of control. To ensure aircraft operation safety in all situations, intelligent system monitoring and adaptation must rely on accurately detecting the presence of abnormal conditions as soon as they take place, identifying their root cause(s), estimating their nature and severity, and predicting their impact on the flight envelope. Due to the complexity and multidimensionality of the aircraft system under abnormal conditions, these requirements are extremely difficult to satisfy using existing analytical and/or statistical approaches. Moreover, current methodologies have addressed only isolated classes of abnormal conditions and a reduced number of aircraft dynamic parameters within a limited region of the flight envelope. This research effort aims at developing an integrated and comprehensive framework for the aircraft abnormal conditions detection, identification, and evaluation based on the artificial immune systems paradigm, which has the capability to address the complexity and multidimensionality issues related to aircraft systems. Within the proposed framework, a novel algorithm was developed for the abnormal conditions detection problem and extended to the abnormal conditions identification and evaluation. The algorithm and its extensions were inspired from the functionality of the biological dendritic cells (an important part of the innate immune system) and their interaction with the different components of the adaptive immune system. Immunity-based methodologies for re-assessing the flight envelope at post-failure and predicting the impact of the abnormal conditions on the performance and handling qualities are also proposed and investigated in this study. The generality of the approach makes it applicable to any system. Data for artificial immune system development were collected from flight tests of a supersonic research aircraft within a motion-based flight

  3. GABAergic influences on ORX receptor-dependent abnormal motor behaviors and neurodegenerative events in fish

    SciTech Connect

    Facciolo, Rosa Maria; Crudo, Michele; Giusi, Giuseppina; Canonaco, Marcello

    2010-02-15

    At date the major neuroreceptors i.e. gamma-aminobutyric acid{sub A} (GABA{sub A}R) and orexin (ORXR) systems are beginning to be linked to homeostasis, neuroendocrine and emotional states. In this study, intraperitoneal treatment of the marine teleost Thalassoma pavo with the highly selective GABA{sub A}R agonist (muscimol, MUS; 0,1 mug/g body weight) and/or its antagonist bicuculline (BIC; 1 mug/g body weight) have corroborated a GABA{sub A}ergic role on motor behaviors. In particular, MUS induced moderate (p < 0.05) and great (p < 0.01) increases of swimming towards food sources and resting states after 24 (1 dose) and 96 (4 doses) h treatment sessions, respectively, when compared to controls. Conversely, BIC caused a very strong (p < 0.001) reduction of the former behavior and in some cases convulsive swimming. From the correlation of BIC-dependent behavioral changes to neuronal morphological and ORXR transcriptional variations, it appeared that the disinhibitory action of GABA{sub A}R was very likely responsible for very strong and strong ORXR mRNA reductions in cerebellum valvula and torus longitudinalis, respectively. Moreover these effects were linked to evident ultra-structural changes such as shrunken cell membranes and loss of cytoplasmic architecture. In contrast, MUS supplied a very low, if any, argyrophilic reaction in hypothalamic and mesencephalic regions plus a scarce level of ultra-structural damages. Interestingly, combined administrations of MUS + BIC were not related to consistent damages, aside mild neuronal alterations in motor-related areas such as optic tectum. Overall it is tempting to suggest, for the first time, a neuroprotective role of GABA{sub A}R inhibitory actions against the overexcitatory ORXR-dependent neurodegeneration and consequently abnormal swimming events in fish.

  4. Video event detection: from subvolume localization to spatiotemporal path search.

    PubMed

    Tran, Du; Yuan, Junsong; Forsyth, David

    2014-02-01

    Although sliding window-based approaches have been quite successful in detecting objects in images, it is not a trivial problem to extend them to detecting events in videos. We propose to search for spatiotemporal paths for video event detection. This new formulation can accurately detect and locate video events in cluttered and crowded scenes, and is robust to camera motions. It can also well handle the scale, shape, and intraclass variations of the event. Compared to event detection using spatiotemporal sliding windows, the spatiotemporal paths correspond to the event trajectories in the video space, thus can better handle events composed by moving objects. We prove that the proposed search algorithm can achieve the global optimal solution with the lowest complexity. Experiments are conducted on realistic video data sets with different event detection tasks, such as anomaly event detection, walking person detection, and running detection. Our proposed method is compatible with different types of video features or object detectors and robust to false and missed local detections. It significantly improves the overall detection and localization accuracy over the state-of-the-art methods. PMID:24356358

  5. Detecting seismic events using Benford's Law

    NASA Astrophysics Data System (ADS)

    Diaz, Jordi; Gallart, Josep; Ruiz, Mario

    2015-04-01

    The Benford's Law (BL) states that the distribution of first significant digits is not uniform but follows a logarithmic frequency distribution. Even if a remarkable wide range of natural and socioeconomical data sets, from stock market values to quantum phase transitions, fit this peculiar law, the conformity to it has deserved few scientific applications, being used mainly as a test to pinpoint anomalous or fraudulent data. We developed a procedure to detect the arrival of seismic waves based on the degree of conformity of the amplitude values in the raw seismic trace to the BL. The signal is divided in time windows of appropriate length and the fitting of the first digits distribution to BL is checked in each time window using a conformity estimator. We document that both teleseismic and local earthquakes can be clearly identified in this procedure and we compare its performance with respect to the classical STA/LTA approach. Moreover, we show that the conformity of the seismic record to the BL does not depend on the amplitude of the incoming series, as the occurrence of events with very different amplitudes result in quite similar degree of BL fitting. On the other hand, we show that natural or man-made quasi-monochromatic seismic signals, surface wave trains or engine-generated vibrations can be identified through their very low BL estimator values, when appropriate interval lengths are used. Therefore, we conclude that the degree of conformity of a seismic signal with the BL is primarily dependent on the frequency content of that signal.

  6. AESOP: Adaptive Event detection SOftware using Programming by example

    NASA Astrophysics Data System (ADS)

    Thangali, Ashwin; Prasad, Harsha; Kethamakka, Sai; Demirdjian, David; Checka, Neal

    2015-05-01

    This paper presents AESOP, a software tool for automatic event detection in video. AESOP employs a super- vised learning approach for constructing event models, given training examples from different event classes. A trajectory-based formulation is used for modeling events with an aim towards incorporating invariance to changes in the camera location and orientation parameters. The proposed formulation is designed to accommodate events that involve interactions between two or more entities over an extended period of time. AESOP's event models are formulated as HMMs to improve the event detection algorithm's robustness to noise in input data and to achieve computationally efficient algorithms for event model training and event detection. AESOP's performance is demonstrated on a wide range of different scenarios, including stationary camera surveillance and aerial video footage captured in land and maritime environments.

  7. Preliminary research on abnormal brain detection by wavelet-energy and quantum- behaved PSO.

    PubMed

    Zhang, Yudong; Ji, Genlin; Yang, Jiquan; Wang, Shuihua; Dong, Zhengchao; Phillips, Preetha; Sun, Ping

    2016-04-29

    It is important to detect abnormal brains accurately and early. The wavelet-energy (WE) was a successful feature descriptor that achieved excellent performance in various applications; hence, we proposed a WE based new approach for automated abnormal detection, and reported its preliminary results in this study. The kernel support vector machine (KSVM) was used as the classifier, and quantum-behaved particle swarm optimization (QPSO) was introduced to optimize the weights of the SVM. The results based on a 5 × 5-fold cross validation showed the performance of the proposed WE + QPSO-KSVM was superior to ``DWT + PCA + BP-NN'', ``DWT + PCA + RBF-NN'', ``DWT + PCA + PSO-KSVM'', ``WE + BPNN'', ``WE +$ KSVM'', and ``DWT $+$ PCA $+$ GA-KSVM'' w.r.t. sensitivity, specificity, and accuracy. The work provides a novel means to detect abnormal brains with excellent performance. PMID:27163327

  8. Preliminary research on abnormal brain detection by wavelet-energy and quantum- behaved PSO.

    PubMed

    Zhang, Yudong; Ji, Genlin; Yang, Jiquan; Wang, Shuihua; Dong, Zhengchao; Phillips, Preetha; Sun, Ping

    2016-04-29

    It is important to detect abnormal brains accurately and early. The wavelet-energy (WE) was a successful feature descriptor that achieved excellent performance in various applications; hence, we proposed a WE based new approach for automated abnormal detection, and reported its preliminary results in this study. The kernel support vector machine (KSVM) was used as the classifier, and quantum-behaved particle swarm optimization (QPSO) was introduced to optimize the weights of the SVM. The results based on a 5 × 5-fold cross validation showed the performance of the proposed WE + QPSO-KSVM was superior to ``DWT + PCA + BP-NN'', ``DWT + PCA + RBF-NN'', ``DWT + PCA + PSO-KSVM'', ``WE + BPNN'', ``WE +$ KSVM'', and ``DWT $+$ PCA $+$ GA-KSVM'' w.r.t. sensitivity, specificity, and accuracy. The work provides a novel means to detect abnormal brains with excellent performance.

  9. Detection of chromosomal abnormalities and the 22q11 microdeletion in fetuses with congenital heart defects.

    PubMed

    Lv, Wei; Wang, Shuyu

    2014-11-01

    Chromosomal abnormalities and the 22q11 microdeletion are implicated in congenital heart defects (CHDs). This study was designed to detect these abnormalities in fetuses and determine the effect of genetic factors on CHD etiology. Between January 2010 and December 2011, 113 fetuses with CHD treated at the Beijing Obstetrics and Gynecology Hospital were investigated, using chromosome karyotyping of either amniotic fluid cell or umbilical cord blood cell samples. Fetuses with a normal result were then investigated for the 22q11 microdeletion by fluorescence in situ hybridization. Of the 113 patients, 12 (10.6%) exhibited chromosomal abnormalities, while 6 (5.3%) of the remaining 101 cases presented with a 22q11 microdeletion. The incidence of chromosomal abnormalities was significantly higher in the group of fetuses presenting with extracardiac malformations in addition to CHD (P<0.001), although the detection of the 22q11 microdeletion was not significantly different between the two groups (P=0.583). In addition, all fetuses with the 22q11 microdeletion occurred de novo. In conclusion, genetic factors are important in the etiology of CHD. Where fetuses present with cardiac defects, additional chromosomal analysis is required to detect extracardiac abnormalities. Fetuses with heart defects should also be considered for 22q11 microdeletion detection to evaluate fetal prognosis, particularly prior to surgery.

  10. Optimizing Detection Rate and Characterization of Subtle Paroxysmal Neonatal Abnormal Facial Movements with Multi-Camera Video-Electroencephalogram Recordings.

    PubMed

    Pisani, Francesco; Pavlidis, Elena; Cattani, Luca; Ferrari, Gianluigi; Raheli, Riccardo; Spagnoli, Carlotta

    2016-06-01

    Objectives We retrospectively analyze the diagnostic accuracy for paroxysmal abnormal facial movements, comparing one camera versus multi-camera approach. Background Polygraphic video-electroencephalogram (vEEG) recording is the current gold standard for brain monitoring in high-risk newborns, especially when neonatal seizures are suspected. One camera synchronized with the EEG is commonly used. Methods Since mid-June 2012, we have started using multiple cameras, one of which point toward newborns' faces. We evaluated vEEGs recorded in newborns in the study period between mid-June 2012 and the end of September 2014 and compared, for each recording, the diagnostic accuracies obtained with one-camera and multi-camera approaches. Results We recorded 147 vEEGs from 87 newborns and found 73 episodes of paroxysmal facial abnormal movements in 18 vEEGs of 11 newborns with the multi-camera approach. By using the single-camera approach, only 28.8% of these events were identified (21/73). Ten positive vEEGs with multicamera with 52 paroxysmal facial abnormal movements (52/73, 71.2%) would have been considered as negative with the single-camera approach. Conclusions The use of one additional facial camera can significantly increase the diagnostic accuracy of vEEGs in the detection of paroxysmal abnormal facial movements in the newborns.

  11. Test and analysis on the abnormal noise of the ultrasonic detection device

    NASA Astrophysics Data System (ADS)

    Li, Guangya; Yang, Mingliang; Wang, Mingquan; Tan, Qiulin; Duan, Nengquan

    2014-03-01

    For the phenomenon that the abnormal noise appear suddenly when the ultrasonic detection device works at the rate of 800mm/min, a vibration testing for this detection device is designed and investigated in this paper. Deep analysis are carried out based on the experimental modal analysis method of point excitation with multiple point three vectors in response and spectrum analysis method. The analysis results demonstrate the main reasons of the abnormal noise, which is due to the resonance between the motor and the ultrasonic station.

  12. Multi-complexity measures for early detection and monitoring of neurological abnormalities from gait time series

    NASA Astrophysics Data System (ADS)

    Gavrishchaka, Valeriy; Davis, Kristina; Senyukova, Olga

    2013-10-01

    Recently, we have proposed to use complementary complexity measures discovered by boosting-like ensemble learning for the enhancement of quantitative indicators dealing with necessarily short physiological time series. We have confirmed robustness of such multi-complexity measures for heart rate variability analysis with the emphasis on detection of emerging and intermittent cardiac abnormalities. Here we demonstrate that such ensemble-based approach could be also effective in discovering universal meta-indicators for early detection and convenient monitoring of neurological abnormalities using gait time series.

  13. Abnormal contextual modulation of visual contour detection in patients with schizophrenia.

    PubMed

    Schallmo, Michael-Paul; Sponheim, Scott R; Olman, Cheryl A

    2013-01-01

    Schizophrenia patients demonstrate perceptual deficits consistent with broad dysfunction in visual context processing. These include poor integration of segments forming visual contours, and reduced visual contrast effects (e.g. weaker orientation-dependent surround suppression, ODSS). Background image context can influence contour perception, as stimuli near the contour affect detection accuracy. Because of ODSS, this contextual modulation depends on the relative orientation between the contour and flanking elements, with parallel flankers impairing contour perception. However in schizophrenia, the impact of abnormal ODSS during contour perception is not clear. It is also unknown whether deficient contour perception marks genetic liability for schizophrenia, or is strictly associated with clinical expression of this disorder. We examined contour detection in 25 adults with schizophrenia, 13 unaffected first-degree biological relatives of schizophrenia patients, and 28 healthy controls. Subjects performed a psychophysics experiment designed to quantify the effect of flanker orientation during contour detection. Overall, patients with schizophrenia showed poorer contour detection performance than relatives or controls. Parallel flankers suppressed and orthogonal flankers enhanced contour detection performance for all groups, but parallel suppression was relatively weaker for schizophrenia patients than healthy controls. Relatives of patients showed equivalent performance with controls. Computational modeling suggested that abnormal contextual modulation in schizophrenia may be explained by suppression that is more broadly tuned for orientation. Abnormal flanker suppression in schizophrenia is consistent with weaker ODSS and/or broader orientation tuning. This work provides the first evidence that such perceptual abnormalities may not be associated with a genetic liability for schizophrenia.

  14. Abnormal Image Detection in Endoscopy Videos Using a Filter Bank and Local Binary Patterns

    PubMed Central

    Nawarathna, Ruwan; Oh, JungHwan; Muthukudage, Jayantha; Tavanapong, Wallapak; Wong, Johnny; de Groen, Piet C.; Tang, Shou Jiang

    2014-01-01

    Finding mucosal abnormalities (e.g., erythema, blood, ulcer, erosion, and polyp) is one of the most essential tasks during endoscopy video review. Since these abnormalities typically appear in a small number of frames (around 5% of the total frame number), automated detection of frames with an abnormality can save physician’s time significantly. In this paper, we propose a new multi-texture analysis method that effectively discerns images showing mucosal abnormalities from the ones without any abnormality since most abnormalities in endoscopy images have textures that are clearly distinguishable from normal textures using an advanced image texture analysis method. The method uses a “texton histogram” of an image block as features. The histogram captures the distribution of different “textons” representing various textures in an endoscopy image. The textons are representative response vectors of an application of a combination of Leung and Malik (LM) filter bank (i.e., a set of image filters) and a set of Local Binary Patterns on the image. Our experimental results indicate that the proposed method achieves 92% recall and 91.8% specificity on wireless capsule endoscopy (WCE) images and 91% recall and 90.8% specificity on colonoscopy images. PMID:25132723

  15. System for detection of hazardous events

    DOEpatents

    Kulesz, James J.; Worley, Brian A.

    2006-05-23

    A system for detecting the occurrence of anomalies, includes a plurality of spaced apart nodes, with each node having adjacent nodes, each of the nodes having one or more sensors associated with the node and capable of detecting anomalies, and each of the nodes having a controller connected to the sensors associated with the node. The system also includes communication links between adjacent nodes, whereby the nodes form a network. Each controller is programmed to query its adjacent nodes to assess the status of the adjacent nodes and the communication links.

  16. System For Detection Of Hazardous Events

    DOEpatents

    Kulesz, James J [Oak Ridge, TN; Worley, Brian A [Knoxville, TN

    2005-08-16

    A system for detecting the occurrence of anomalies, includes a plurality of spaced apart nodes, with each node having adjacent nodes, each of the nodes having one or more sensors associated with the node and capable of detecting anomalies, and each of the nodes having a controller connected to the sensors associated with the node. The system also includes communication links between adjacent nodes, whereby the nodes form a network. Each controller is programmed to query its adjacent nodes to assess the status of the adjacent nodes and the communication links.

  17. A method for in vivo detection of abnormal subepidermal tissues based on dielectric properties.

    PubMed

    Zhang, Liang; Liu, Peiguo; Dong, Xiuzhen; Zhou, Dongming; Shi, Xuetao

    2014-01-01

    In this paper, a convenient and noninvasive scanning imaging method using microwave frequency band for abnormal subepidermal tissues detection is proposed in the aim to improve diagnosis and prognosis in clinical environments. This method is based on the reflective detection technology with coaxial probe that is used to measure the dielectric properties of tissues. An improved equivalent circuit and simulated annealing algorithm (SA) were used in this work to analyze the dielectric properties of tissues. Computational simulations incorporating a simplified model of subcutaneous hemorrhage described in this work were used to evaluate this method. The dielectric properties data of tissues in the model of simulation is derived from the literature. The simulation results demonstrated the potential of this method to detect abnormal subepidermal tissues conveniently and expose them in the image accurately. PMID:25227057

  18. Frequency and patterns of abnormality detected by iodine-123 amine emission CT after cerebral infarction

    SciTech Connect

    Brott, T.G.; Gelfand, M.J.; Williams, C.C.; Spilker, J.A.; Hertzberg, V.S.

    1986-03-01

    Single photon emission computed tomography (SPECT) was performed in 31 patients with cerebral infarction and 13 who had had transient ischemic attacks, using iodine-123-labeled N,N,N'-trimethyl-N'-(2-hydroxyl-3-methyl-5-iodobenzyl)-1,3-propanediamin e (I-123-HIPDM) as the radiopharmaceutical. SPECT scans were compared with computed tomographic (CT) scans. SPECT was as sensitive as CT in detecting cerebral infarction (94% vs. 84%). The abnormalities were larger on the SPECT scans than on the CT scans in 19 cases, equal in seven, and smaller in five (SPECT abnormalities greater than or equal to CT abnormalities in 86% of cases). Fifteen of 30 patients with hemispheric infarction had decreased perfusion (decreased uptake of I-123-HIPDM) to the cerebellar hemisphere contralateral to the cerebral hemisphere involved by the infarction (crossed cerebellar diaschisis). Nine of these 15 patients had major motor deficits, while only one of the 15 without crossed cerebellar diaschisis had a major motor deficit.

  19. Abnormality Detection via Iterative Deformable Registration and Basis-Pursuit Decomposition.

    PubMed

    Zeng, Ke; Erus, Guray; Sotiras, Aristeidis; Shinohara, Russell T; Davatzikos, Christos

    2016-08-01

    We present a generic method for automatic detection of abnormal regions in medical images as deviations from a normative data base. The algorithm decomposes an image, or more broadly a function defined on the image grid, into the superposition of a normal part and a residual term. A statistical model is constructed with regional sparse learning to represent normative anatomical variations among a reference population (e.g., healthy controls), in conjunction with a Markov random field regularization that ensures mutual consistency of the regional learning among partially overlapping image blocks. The decomposition is performed in a principled way so that the normal part fits well with the learned normative model, while the residual term absorbs pathological patterns, which may then be detected through a statistical significance test. The decomposition is applied to multiple image features from an individual scan, detecting abnormalities using both intensity and shape information. We form an iterative scheme that interleaves abnormality detection with deformable registration, gradually improving robustness of the spatial normalization and precision of the detection. The algorithm is evaluated with simulated images and clinical data of brain lesions, and is shown to achieve robust deformable registration and localize pathological regions simultaneously. The algorithm is also applied on images from Alzheimer's disease patients to demonstrate the generality of the method. PMID:27046847

  20. Method of detecting abnormality in a reference crank angle position detection system of an internal combustion engine

    SciTech Connect

    Suzuki, Y.

    1987-05-12

    A method is described of detecting abnormality in a reference crank angle position detection system of a control system for controlling an internal combustion engine. The method comprises a crankshaft, the control system using at least reference pulses generated, respectively, at predetermined crank angles of the crankshaft and detected by the reference crank angle position detection system. Crank angle pulses are generated, respectively, at other predetermined angles of the crankshaft and with a pulse repetition period shorter than that of the reference pulses, for controlling the engine.

  1. Subsurface Event Detection and Classification Using Wireless Signal Networks

    PubMed Central

    Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T.

    2012-01-01

    Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events. PMID:23202191

  2. Subsurface event detection and classification using Wireless Signal Networks.

    PubMed

    Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T

    2012-01-01

    Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events. PMID:23202191

  3. Global Seismic Event Detection Using Surface Waves: 15 Possible Antarctic Glacial Sliding Events

    NASA Astrophysics Data System (ADS)

    Chen, X.; Shearer, P. M.; Walker, K. T.; Fricker, H. A.

    2008-12-01

    To identify overlooked or anomalous seismic events not listed in standard catalogs, we have developed an algorithm to detect and locate global seismic events using intermediate-period (35-70s) surface waves. We apply our method to continuous vertical-component seismograms from the global seismic networks as archived in the IRIS UV FARM database from 1997 to 2007. We first bandpass filter the seismograms, apply automatic gain control, and compute envelope functions. We then examine 1654 target event locations defined at 5 degree intervals and stack the seismogram envelopes along the predicted Rayleigh-wave travel times. The resulting function has spatial and temporal peaks that indicate possible seismic events. We visually check these peaks using a graphical user interface to eliminate artifacts and assign an overall reliability grade (A, B or C) to the new events. We detect 78% of events in the Global Centroid Moment Tensor (CMT) catalog. However, we also find 840 new events not listed in the PDE, ISC and REB catalogs. Many of these new events were previously identified by Ekstrom (2006) using a different Rayleigh-wave detection scheme. Most of these new events are located along oceanic ridges and transform faults. Some new events can be associated with volcanic eruptions such as the 2000 Miyakejima sequence near Japan and others with apparent glacial sliding events in Greenland (Ekstrom et al., 2003). We focus our attention on 15 events detected from near the Antarctic coastline and relocate them using a cross-correlation approach. The events occur in 3 groups which are well-separated from areas of cataloged earthquake activity. We speculate that these are iceberg calving and/or glacial sliding events, and hope to test this by inverting for their source mechanisms and examining remote sensing data from their source regions.

  4. Event Detection using Twitter: A Spatio-Temporal Approach

    PubMed Central

    Cheng, Tao; Wicks, Thomas

    2014-01-01

    Background Every day, around 400 million tweets are sent worldwide, which has become a rich source for detecting, monitoring and analysing news stories and special (disaster) events. Existing research within this field follows key words attributed to an event, monitoring temporal changes in word usage. However, this method requires prior knowledge of the event in order to know which words to follow, and does not guarantee that the words chosen will be the most appropriate to monitor. Methods This paper suggests an alternative methodology for event detection using space-time scan statistics (STSS). This technique looks for clusters within the dataset across both space and time, regardless of tweet content. It is expected that clusters of tweets will emerge during spatio-temporally relevant events, as people will tweet more than expected in order to describe the event and spread information. The special event used as a case study is the 2013 London helicopter crash. Results and Conclusion A spatio-temporally significant cluster is found relating to the London helicopter crash. Although the cluster only remains significant for a relatively short time, it is rich in information, such as important key words and photographs. The method also detects other special events such as football matches, as well as train and flight delays from Twitter data. These findings demonstrate that STSS is an effective approach to analysing Twitter data for event detection. PMID:24893168

  5. Efficient method for events detection in phonocardiographic signals

    NASA Astrophysics Data System (ADS)

    Martinez-Alajarin, Juan; Ruiz-Merino, Ramon

    2005-06-01

    The auscultation of the heart is still the first basic analysis tool used to evaluate the functional state of the heart, as well as the first indicator used to submit the patient to a cardiologist. In order to improve the diagnosis capabilities of auscultation, signal processing algorithms are currently being developed to assist the physician at primary care centers for adult and pediatric population. A basic task for the diagnosis from the phonocardiogram is to detect the events (main and additional sounds, murmurs and clicks) present in the cardiac cycle. This is usually made by applying a threshold and detecting the events that are bigger than the threshold. However, this method usually does not allow the detection of the main sounds when additional sounds and murmurs exist, or it may join several events into a unique one. In this paper we present a reliable method to detect the events present in the phonocardiogram, even in the presence of heart murmurs or additional sounds. The method detects relative maxima peaks in the amplitude envelope of the phonocardiogram, and computes a set of parameters associated with each event. Finally, a set of characteristics is extracted from each event to aid in the identification of the events. Besides, the morphology of the murmurs is also detected, which aids in the differentiation of different diseases that can occur in the same temporal localization. The algorithms have been applied to real normal heart sounds and murmurs, achieving satisfactory results.

  6. Jaw and tooth abnormalities detected on panoramic radiographs in New Zealand children aged 10-15 years.

    PubMed

    Cholitgul, W; Drummond, B K

    2000-03-01

    Panoramic radiographs of 1,608 children and adolescents aged 10 to 15 years (797 males and 811 females) were reviewed to determine the prevalence of tooth and jaw abnormalities. Abnormalities were detected on 21 percent of the radiographs (23 percent females and 17.3 percent males); 879 teeth were diagnosed with abnormalities on 331 radiographs. The more common abnormalities were malpositioned teeth, missing teeth, misshaped teeth, and teeth with hypoplastic appearance. Bony abnormalities and growth problems were detected in a few radiographs. This study demonstrates the value of panoramic radiography in detecting or confirming dental abnormalities, and supports recommendations on the use of panoramic radiography to aid in the assessment of dental development. PMID:10860374

  7. Video Event Detection Framework on Large-Scale Video Data

    ERIC Educational Resources Information Center

    Park, Dong-Jun

    2011-01-01

    Detection of events and actions in video entails substantial processing of very large, even open-ended, video streams. Video data present a unique challenge for the information retrieval community because properly representing video events is challenging. We propose a novel approach to analyze temporal aspects of video data. We consider video data…

  8. Detection of Cardiac Abnormalities from Multilead ECG using Multiscale Phase Alternation Features.

    PubMed

    Tripathy, R K; Dandapat, S

    2016-06-01

    The cardiac activities such as the depolarization and the relaxation of atria and ventricles are observed in electrocardiogram (ECG). The changes in the morphological features of ECG are the symptoms of particular heart pathology. It is a cumbersome task for medical experts to visually identify any subtle changes in the morphological features during 24 hours of ECG recording. Therefore, the automated analysis of ECG signal is a need for accurate detection of cardiac abnormalities. In this paper, a novel method for automated detection of cardiac abnormalities from multilead ECG is proposed. The method uses multiscale phase alternation (PA) features of multilead ECG and two classifiers, k-nearest neighbor (KNN) and fuzzy KNN for classification of bundle branch block (BBB), myocardial infarction (MI), heart muscle defect (HMD) and healthy control (HC). The dual tree complex wavelet transform (DTCWT) is used to decompose the ECG signal of each lead into complex wavelet coefficients at different scales. The phase of the complex wavelet coefficients is computed and the PA values at each wavelet scale are used as features for detection and classification of cardiac abnormalities. A publicly available multilead ECG database (PTB database) is used for testing of the proposed method. The experimental results show that, the proposed multiscale PA features and the fuzzy KNN classifier have better performance for detection of cardiac abnormalities with sensitivity values of 78.12 %, 80.90 % and 94.31 % for BBB, HMD and MI classes. The sensitivity value of proposed method for MI class is compared with the state-of-art techniques from multilead ECG. PMID:27118009

  9. Contralateral subtraction technique for detection of asymmetric abnormalities on whole-body bone scintigrams

    NASA Astrophysics Data System (ADS)

    Shiraishi, Junji; Li, Qiang; Appelbaum, Daniel; Pu, Yonglin; Doi, Kunio

    2007-03-01

    We developed a computer-aided diagnostic (CAD) scheme for assisting radiologists in the detection of asymmetric abnormalities on a single whole-body bone scintigram by applying a contralateral subtraction (CS) technique. Twenty whole-body bone scans including 107 abnormal lesions in anterior and/or posterior images (the number of lesions per case ranged from 1 to 16, mean 5.4) were used in this study. In our scheme, the original bone scan image was flipped horizontally to provide a mirror image. The mirror image was first rotated and shifted globally to match the original image approximately, and then was nonlinearly warped by use of an elastic matching technique in order to match the original image accurately. We applied a nonlinear lookup table to convert the difference in pixel values between the original and the warped images to new pixel values for a CS image, in order to enhance dark shadows at the locations of abnormal lesions where uptake of radioisotope was asymmetrically high, and to suppress light shadows of the lesions on the contralateral side. In addition, we applied a CAD scheme for the detection of asymmetric abnormalities by use of rule-based tests and sequential application of artificial neural networks with 25 image features extracted from the original and CS images. The performance of the CAD scheme, which was evaluated by a leave-one-case-out method, indicated an average sensitivity of 80.4 % with 3.8 false positives per case. This CAD scheme with the contralateral subtraction technique has the potential to improve radiologists' diagnostic accuracy and could be used for computerized identification of asymmetric abnormalities on whole-body bone scans.

  10. Comparison of Efficacy in Abnormal Cervical Cell Detection between Liquid-based Cytology and Conventional Cytology.

    PubMed

    Tanabodee, Jitraporn; Thepsuwan, Kitisak; Karalak, Anant; Laoaree, Orawan; Krachang, Anong; Manmatt, Kittipong; Anontwatanawong, Nualpan

    2015-01-01

    This study was conducted to 1206 women who had cervical cancer screening at Chonburi Cancer Hospital. The spilt-sample study aimed to compare the efficacy of abnormal cervical cells detection between liquid-based cytology (LBC) and conventional cytology (CC). The collection of cervical cells was performed by broom and directly smeared on a glass slide for CC then the rest of specimen was prepared for LBC. All slides were evaluated and classified by The Bethesda System. The results of the two cytological tests were compared to the gold standard. The LBC smear significantly decreased inflammatory cell and thick smear on slides. These two techniques were not difference in detection rate of abnormal cytology and had high cytological diagnostic agreement of 95.7%. The histologic diagnosis of cervical tissue was used as the gold standard in 103 cases. Sensitivity, specificity, positive predictive value, negative predictive value, false positive, false negative and accuracy of LBC at ASC-US cut off were 81.4, 75.0, 70.0, 84.9, 25.0, 18.6 and 77.7%, respectively. CC had higher false positive and false negative than LBC. LBC had shown higher sensitivity, specificity, PPV, NPV and accuracy than CC but no statistical significance. In conclusion, LBC method can improve specimen quality, more sensitive, specific and accurate at ASC-US cut off and as effective as CC in detecting cervical epithelial cell abnormalities. PMID:26514540

  11. Automated contralateral subtraction of dental panoramic radiographs for detecting abnormalities in paranasal sinus

    NASA Astrophysics Data System (ADS)

    Hara, Takeshi; Mori, Shintaro; Kaneda, Takashi; Hayashi, Tatsuro; Katsumata, Akitoshi; Fujita, Hiroshi

    2011-03-01

    Inflammation in the paranasal sinus is often observed in seasonal allergic rhinitis or with colds, but is also an indication for odontogenic tumors, carcinoma of the maxillary sinus or a maxillary cyst. The detection of those findings in dental panoramic radiographs is not difficult for radiologists, but general dentists may miss the findings since they focus on treatments of teeth. The purpose of this work is to develop a contralateral subtraction method for detecting the odontogenic sinusitis region on dental panoramic radiographs. We developed a contralateral subtraction technique in paranasal sinus region, consisting of 1) image filtering of the smoothing and sobel operation for noise reduction and edge extraction, 2) image registration of mirrored image by using mutual information, and 3) image display method of subtracted pixel data. We employed 56 cases (24 normal and 32 abnormal). The abnormal regions and the normal cases were verified by a board-certified radiologist using CT scans. Observer studies with and without subtraction images were performed for 9 readers. The true-positive rate at a 50% confidence level in 7 out of 9 readers was improved, but there was no statistical significance in the difference of area-under-curve (AUC) in each radiologist. In conclusion, the contralateral subtraction images of dental panoramic radiographs may improve the detection rate of abnormal regions in paranasal sinus.

  12. Automatic detection of iceberg calving events using seismic observations

    NASA Astrophysics Data System (ADS)

    Andersen, M. L.; Larsen, T.; Hamilton, G. S.; Nettles, M.

    2014-12-01

    Iceberg calving at large, marine-terminating glaciers has been shown to be seismogenic. Seismic energy from these events is released slowly, resulting in characteristic low-frequency signals. The events therefore typically escape detection by traditional systematic methods. Here we show the results of a detection algorithm applied to data observed at two stations, both ~100 km from Helheim Glacier, South East Greenland, in 2007 and 2008 for the purpose of detecting calving-related seismic signals. The detector entails sliding a 150 s wide window over the observed vertical displacement seismograms at steps of one second. Relative power in the 1.1-3.3 s band is monitored, and the detector is activated when a pre-defined threshold is exceeded. We determine the threshold by calibrating the detector with a record of known events observed by time lapse cameras at Helheim Glacier and automatic detections of glacial earthquakes from the GSN (Global Seismic Network) stations. The resulting list of detections is then filtered for events overlapping with tectonic events, both local and global. We observe a clear periodicity in the detections, with most events occurring during the late summer and early fall, roughly coinciding with the end of the melt season. This apparent offset from peak melt intensity leads us to speculate that the pattern in calving is the result of a combination of the seasonal development of multiple physical properties of the glacier, i.e., surface crevassing, subglacial melt and crevassing, and the subglacial drainage system.

  13. Detection of flood events in hydrological discharge time series

    NASA Astrophysics Data System (ADS)

    Seibert, S. P.; Ehret, U.

    2012-04-01

    The shortcomings of mean-squared-error (MSE) based distance metrics are well known (Beran 1999, Schaeffli & Gupta 2007) and the development of novel distance metrics (Pappenberger & Beven 2004, Ehret & Zehe 2011) and multi-criteria-approaches enjoy increasing popularity (Reusser 2009, Gupta et al. 2009). Nevertheless, the hydrological community still lacks metrics which identify and thus, allow signature based evaluations of hydrological discharge time series. Signature based information/evaluations are required wherever specific time series features, such as flood events, are of special concern. Calculation of event based runoff coefficients or precise knowledge on flood event characteristics (like onset or duration of rising limp or the volume of falling limp, etc.) are possible applications. The same applies for flood forecasting/simulation models. Directly comparing simulated and observed flood event features may reveal thorough insights into model dynamics. Compared to continuous space-and-time-aggregated distance metrics, event based evaluations may provide answers like the distributions of event characteristics or the percentage of the events which were actually reproduced by a hydrological model. It also may help to provide information on the simulation accuracy of small, medium and/or large events in terms of timing and magnitude. However, the number of approaches which expose time series features is small and their usage is limited to very specific questions (Merz & Blöschl 2009, Norbiato et al. 2009). We believe this is due to the following reasons: i) a generally accepted definition of the signature of interest is missing or difficult to obtain (in our case: what makes a flood event a flood event?) and/or ii) it is difficult to translate such a definition into a equation or (graphical) procedure which exposes the feature of interest in the discharge time series. We reviewed approaches which detect event starts and/or ends in hydrological discharge time

  14. Structuring an event ontology for disease outbreak detection

    PubMed Central

    Kawazoe, Ai; Chanlekha, Hutchatai; Shigematsu, Mika; Collier, Nigel

    2008-01-01

    Background This paper describes the design of an event ontology being developed for application in the machine understanding of infectious disease-related events reported in natural language text. This event ontology is designed to support timely detection of disease outbreaks and rapid judgment of their alerting status by 1) bridging a gap between layman's language used in disease outbreak reports and public health experts' deep knowledge, and 2) making multi-lingual information available. Construction and content This event ontology integrates a model of experts' knowledge for disease surveillance, and at the same time sets of linguistic expressions which denote disease-related events, and formal definitions of events. In this ontology, rather general event classes, which are suitable for application to language-oriented tasks such as recognition of event expressions, are placed on the upper-level, and more specific events of the experts' interest are in the lower level. Each class is related to other classes which represent participants of events, and linked with multi-lingual synonym sets and axioms. Conclusions We consider that the design of the event ontology and the methodology introduced in this paper are applicable to other domains which require integration of natural language information and machine support for experts to assess them. The first version of the ontology, with about 40 concepts, will be available in March 2008. PMID:18426553

  15. Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks

    PubMed Central

    Zhou, Zhangbing; Xing, Riliang; Duan, Yucong; Zhu, Yueqin; Xiang, Jianming

    2015-01-01

    With the advent of the Internet of Underwater Things, smart things are deployed in the ocean space and establish underwater wireless sensor networks for the monitoring of vast and dynamic underwater environments. When events are found to have possibly occurred, accurate event coverage should be detected, and potential event sources should be determined for the enactment of prompt and proper responses. To address this challenge, a technique that detects event coverage and determines event sources is developed in this article. Specifically, the occurrence of possible events corresponds to a set of neighboring sensor nodes whose sensory data may deviate from a normal sensing range in a collective fashion. An appropriate sensor node is selected as the relay node for gathering and routing sensory data to sink node(s). When sensory data are collected at sink node(s), the event coverage is detected and represented as a weighted graph, where the vertices in this graph correspond to sensor nodes and the weight specified upon the edges reflects the extent of sensory data deviating from a normal sensing range. Event sources are determined, which correspond to the barycenters in this graph. The results of the experiments show that our technique is more energy efficient, especially when the network topology is relatively steady. PMID:26694394

  16. Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks.

    PubMed

    Zhou, Zhangbing; Xing, Riliang; Duan, Yucong; Zhu, Yueqin; Xiang, Jianming

    2015-01-01

    With the advent of the Internet of Underwater Things, smart things are deployed in the ocean space and establish underwater wireless sensor networks for the monitoring of vast and dynamic underwater environments. When events are found to have possibly occurred, accurate event coverage should be detected, and potential event sources should be determined for the enactment of prompt and proper responses. To address this challenge, a technique that detects event coverage and determines event sources is developed in this article. Specifically, the occurrence of possible events corresponds to a set of neighboring sensor nodes whose sensory data may deviate from a normal sensing range in a collective fashion. An appropriate sensor node is selected as the relay node for gathering and routing sensory data to sink node(s). When sensory data are collected at sink node(s), the event coverage is detected and represented as a weighted graph, where the vertices in this graph correspond to sensor nodes and the weight specified upon the edges reflects the extent of sensory data deviating from a normal sensing range. Event sources are determined, which correspond to the barycenters in this graph. The results of the experiments show that our technique is more energy efficient, especially when the network topology is relatively steady. PMID:26694394

  17. Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks.

    PubMed

    Zhou, Zhangbing; Xing, Riliang; Duan, Yucong; Zhu, Yueqin; Xiang, Jianming

    2015-12-15

    With the advent of the Internet of Underwater Things, smart things are deployed in the ocean space and establish underwater wireless sensor networks for the monitoring of vast and dynamic underwater environments. When events are found to have possibly occurred, accurate event coverage should be detected, and potential event sources should be determined for the enactment of prompt and proper responses. To address this challenge, a technique that detects event coverage and determines event sources is developed in this article. Specifically, the occurrence of possible events corresponds to a set of neighboring sensor nodes whose sensory data may deviate from a normal sensing range in a collective fashion. An appropriate sensor node is selected as the relay node for gathering and routing sensory data to sink node(s). When sensory data are collected at sink node(s), the event coverage is detected and represented as a weighted graph, where the vertices in this graph correspond to sensor nodes and the weight specified upon the edges reflects the extent of sensory data deviating from a normal sensing range. Event sources are determined, which correspond to the barycenters in this graph. The results of the experiments show that our technique is more energy efficient, especially when the network topology is relatively steady.

  18. Detecting Abnormal Vehicular Dynamics at Intersections Based on an Unsupervised Learning Approach and a Stochastic Model

    PubMed Central

    Jiménez-Hernández, Hugo; González-Barbosa, Jose-Joel; Garcia-Ramírez, Teresa

    2010-01-01

    This investigation demonstrates an unsupervised approach for modeling traffic flow and detecting abnormal vehicle behaviors at intersections. In the first stage, the approach reveals and records the different states of the system. These states are the result of coding and grouping the historical motion of vehicles as long binary strings. In the second stage, using sequences of the recorded states, a stochastic graph model based on a Markovian approach is built. A behavior is labeled abnormal when current motion pattern cannot be recognized as any state of the system or a particular sequence of states cannot be parsed with the stochastic model. The approach is tested with several sequences of images acquired from a vehicular intersection where the traffic flow and duration used in connection with the traffic lights are continuously changed throughout the day. Finally, the low complexity and the flexibility of the approach make it reliable for use in real time systems. PMID:22163616

  19. Detecting abnormal vehicular dynamics at intersections based on an unsupervised learning approach and a stochastic model.

    PubMed

    Jiménez-Hernández, Hugo; González-Barbosa, Jose-Joel; Garcia-Ramírez, Teresa

    2010-01-01

    This investigation demonstrates an unsupervised approach for modeling traffic flow and detecting abnormal vehicle behaviors at intersections. In the first stage, the approach reveals and records the different states of the system. These states are the result of coding and grouping the historical motion of vehicles as long binary strings. In the second stage, using sequences of the recorded states, a stochastic graph model based on a Markovian approach is built. A behavior is labeled abnormal when current motion pattern cannot be recognized as any state of the system or a particular sequence of states cannot be parsed with the stochastic model. The approach is tested with several sequences of images acquired from a vehicular intersection where the traffic flow and duration used in connection with the traffic lights are continuously changed throughout the day. Finally, the low complexity and the flexibility of the approach make it reliable for use in real time systems. PMID:22163616

  20. Detecting abnormal vehicular dynamics at intersections based on an unsupervised learning approach and a stochastic model.

    PubMed

    Jiménez-Hernández, Hugo; González-Barbosa, Jose-Joel; Garcia-Ramírez, Teresa

    2010-01-01

    This investigation demonstrates an unsupervised approach for modeling traffic flow and detecting abnormal vehicle behaviors at intersections. In the first stage, the approach reveals and records the different states of the system. These states are the result of coding and grouping the historical motion of vehicles as long binary strings. In the second stage, using sequences of the recorded states, a stochastic graph model based on a Markovian approach is built. A behavior is labeled abnormal when current motion pattern cannot be recognized as any state of the system or a particular sequence of states cannot be parsed with the stochastic model. The approach is tested with several sequences of images acquired from a vehicular intersection where the traffic flow and duration used in connection with the traffic lights are continuously changed throughout the day. Finally, the low complexity and the flexibility of the approach make it reliable for use in real time systems.

  1. An observer study methodology for evaluating detection of motion abnormalities in gated myocardial perfusion SPECT.

    PubMed

    Lalush, David S; Jatko, Megan K; Segars, W Paul

    2005-03-01

    To address the task of detecting nonischemic motion abnormalities from animated displays of gated myocardial perfusion single photon emission computed tomography data, we performed an observer study to evaluate the difference in detection performance between gating to 8 and 16 frames. Images were created from the NCAT mathematical phantom with a realistic heart simulating hypokinetic motion in the left lateral wall. Realistic noise-free projection data were simulated for both normal and defective hearts to obtain 16 frames for the cardiac cycle. Poisson noise was then simulated for each frame to create 50 realizations of each heart, All datasets were processed in two ways: reconstructed as a 16-frame set, and collapsed to 8 frames and reconstructed. Ten observers viewed the cardiac images animated with a realistic real-time frame rate. Observers trained on 100 images and tested on 100 images, rating their confidence on the presence of a motion defect on a continuous scale. None of the observers showed a significant difference in performance between the two gating methods. The 95% confidence interval on the difference in areas under the ROC curve (Az8 - Az16) was -0.029-0.085. Our test did not find a significant difference in detection performance between 8-frame gating and 16-frame gating. We conclude that, for the task of detecting abnormal motion, increasing the number of gated frames from 8 to 16 offers no apparent advantage.

  2. Bayesian-network-based soccer video event detection and retrieval

    NASA Astrophysics Data System (ADS)

    Sun, Xinghua; Jin, Guoying; Huang, Mei; Xu, Guangyou

    2003-09-01

    This paper presents an event based soccer video retrieval method, where the scoring even is detected based on Bayesian network from six kinds of cue information including gate, face, audio, texture, caption and text. The topology within the Bayesian network is predefined by hand according to the domain knowledge and the probability distributions are learned in the case of the known structure and full observability. The resulting event probability from the Bayesian network is used as the feature vector to perform the video retrieval. Experiments show that the true and false detection rations for the scoring event are about 90% and 16.67% respectively, and that the video retrieval result based on event is superior to that based on low-level features in the human visual perception.

  3. Detection of Energetic Particle Events with SOHO Space Observatory

    NASA Astrophysics Data System (ADS)

    Rodríguez Frías, D.; Gómez Herrero, R.; Gutiérrez, J.; Del Peral, L.

    2004-09-01

    An analysis of eighteen solar energetic particle (SEP) events measured with the EPHIN instrument on board the SOHO spacecraft has been performed. Via parametrization of temporal profiles, differences among events have been shown by the temporal profile parameters obtained. The detected differences are found to depend on the particle acceleration, the magnetic connection with the acceleration zone and the interplanetary physical characteristics transport to the observing point.

  4. Adaptive noise estimation and suppression for improving microseismic event detection

    NASA Astrophysics Data System (ADS)

    Mousavi, S. Mostafa; Langston, Charles A.

    2016-09-01

    Microseismic data recorded by surface arrays are often strongly contaminated by unwanted noise. This background noise makes the detection of small magnitude events difficult. A noise level estimation and noise reduction algorithm is presented for microseismic data analysis based upon minimally controlled recursive averaging and neighborhood shrinkage estimators. The method might not be compared with more sophisticated and computationally expensive denoising algorithm in terms of preserving detailed features of seismic signal. However, it is fast and data-driven and can be applied in real-time processing of continuous data for event detection purposes. Results from application of this algorithm to synthetic and real seismic data show that it holds a great promise for improving microseismic event detection.

  5. White Matter Abnormalities in Post-traumatic Stress Disorder Following a Specific Traumatic Event

    PubMed Central

    Li, Lei; Lei, Du; Li, Lingjiang; Huang, Xiaoqi; Suo, Xueling; Xiao, Fenglai; Kuang, Weihong; Li, Jin; Bi, Feng; Lui, Su; Kemp, Graham J.; Sweeney, John A.; Gong, Qiyong

    2016-01-01

    Studies of posttraumatic stress disorder (PTSD) are complicated by wide variability in the intensity and duration of prior stressors in patient participants, secondary effects of chronic psychiatric illness, and a variable history of treatment with psychiatric medications. In magnetic resonance imaging (MRI) studies, patient samples have often been small, and they were not often compared to similarly stressed patients without PTSD in order to control for general stress effects. Findings from these studies have been inconsistent. The present study investigated whole-brain microstructural alterations of white matter in a large drug-naive population who survived a specific, severe traumatic event (a major 8.0-magnitude earthquake). Using diffusion tensor imaging (DTI), we explored group differences between 88 PTSD patients and 91 matched traumatized non-PTSD controls in fractional anisotropy (FA), as well as its component elements axial diffusivity (AD) and radial diffusivity (RD), and examined these findings in relation to findings from deterministic DTI tractography. Relations between white matter alterations and psychiatric symptom severity were examined. PTSD patients, relative to similarly stressed controls, showed an FA increase as well as AD and RD changes in the white matter beneath left dorsolateral prefrontal cortex and forceps major. The observation of increased FA in the PTSD group suggests that the pathophysiology of PTSD after a specific acute traumatic event is distinct from what has been reported in patients with several years duration of illness. Alterations in dorsolateral prefrontal cortex may be an important aspect of illness pathophysiology, possibly via the region's established role in fear extinction circuitry. Use-dependent myelination or other secondary compensatory changes in response to heightened demands for threat appraisal and emotion regulation may be involved. PMID:26981581

  6. White Matter Abnormalities in Post-traumatic Stress Disorder Following a Specific Traumatic Event.

    PubMed

    Li, Lei; Lei, Du; Li, Lingjiang; Huang, Xiaoqi; Suo, Xueling; Xiao, Fenglai; Kuang, Weihong; Li, Jin; Bi, Feng; Lui, Su; Kemp, Graham J; Sweeney, John A; Gong, Qiyong

    2016-02-01

    Studies of posttraumatic stress disorder (PTSD) are complicated by wide variability in the intensity and duration of prior stressors in patient participants, secondary effects of chronic psychiatric illness, and a variable history of treatment with psychiatric medications. In magnetic resonance imaging (MRI) studies, patient samples have often been small, and they were not often compared to similarly stressed patients without PTSD in order to control for general stress effects. Findings from these studies have been inconsistent. The present study investigated whole-brain microstructural alterations of white matter in a large drug-naive population who survived a specific, severe traumatic event (a major 8.0-magnitude earthquake). Using diffusion tensor imaging (DTI), we explored group differences between 88 PTSD patients and 91 matched traumatized non-PTSD controls in fractional anisotropy (FA), as well as its component elements axial diffusivity (AD) and radial diffusivity (RD), and examined these findings in relation to findings from deterministic DTI tractography. Relations between white matter alterations and psychiatric symptom severity were examined. PTSD patients, relative to similarly stressed controls, showed an FA increase as well as AD and RD changes in the white matter beneath left dorsolateral prefrontal cortex and forceps major. The observation of increased FA in the PTSD group suggests that the pathophysiology of PTSD after a specific acute traumatic event is distinct from what has been reported in patients with several years duration of illness. Alterations in dorsolateral prefrontal cortex may be an important aspect of illness pathophysiology, possibly via the region's established role in fear extinction circuitry. Use-dependent myelination or other secondary compensatory changes in response to heightened demands for threat appraisal and emotion regulation may be involved. PMID:26981581

  7. Spectral Cytopathology of Cervical Samples: Detecting Cellular Abnormalities in Cytologically Normal Cells

    PubMed Central

    Schubert, Jennifer M.; Bird, Benjamin; Papamarkakis, Kostas; Miljković, Miloš; Bedrossian, Kristi; Laver, Nora; Diem, Max

    2010-01-01

    Aim Spectral Cytopathology (SCP) is a novel spectroscopic method for objective and unsupervised classification of individual exfoliated cells. The limitations of conventional cytopathology are well-recognized within the pathology community. In SCP, cellular differentiation is made by observing molecular changes in the nucleus and the cytoplasm, which may or may not produce morphological changes detectable by conventional cytopathology. This proof of concept study demonstrates SCP’s potential as an enhancing tool for cytopathologists by aiding in the accurate and reproducible diagnosis of cells in all states of disease. Method Infrared spectra are collected from cervical cells deposited onto reflectively coated glass slides. Each cell has a corresponding infrared spectrum that describes its unique biochemical composition. Spectral data are processed and analyzed by an unsupervised chemometric algorithm, Principal Component Analysis (PCA). Results In this blind study, cervical samples are classified by analyzing the spectra of morphologically normal looking squamous cells from normal samples and samples diagnosed by conventional cytopathology with low grade squamous intraepithelial lesions (LSIL). SCP discriminated cytopathological diagnoses amongst twelve different cervical samples with a high degree of specificity and sensitivity. SCP also correlated two samples with abnormal spectral changes: these samples had a normal cytopathological diagnosis but had a history of abnormal cervical cytology. The spectral changes observed in the morphologically normal looking cells are most likely due to an infection with human papillomavirus, HPV. HPV DNA testing was conducted on five additional samples, and SCP accurately differentiated these samples by their HPV status. Conclusions SCP tracks biochemical variations in cells that are consistent with the onset of disease. HPV has been implicated as the cause of these changes detected spectroscopically. SCP does not depend on

  8. Detection of a second ντ event

    NASA Astrophysics Data System (ADS)

    Ishiguro, Katsumi

    2014-08-01

    OPERA is a neutrino oscillation experiment aiming to prove the tau neutrino appearance for the first time. A tau decay is identified by the detection of its characteristic decay topologies in nuclear emulsion films. OPERA reported the detection of a first tau neutrino event in 2010. We recently detected a second tau neutrino event in the 2011 run sample. The primary vertex has two charged particles of which one exhibits a three-prong vertex in the plastic base of a film after a flight length of 1.54 mm. It satisfies all the selection criteria to be a tau neutrino interaction. Especially the azimuthal angle in the transverse plane between the tau candidate track and the primary track is almost 180 degrees. The number of tau to 3π signal events expected in the analyzed sample is 0.18, the number of background events is 0.05. Considering all modes, the signal expectation is 1.91 events and the background 0.18 events.

  9. Abnormality detection in retinal images using ant colony optimization and artificial neural networks - biomed 2010.

    PubMed

    Kavitha, Ganesan; Ramakrishnan, Swaminathan

    2010-01-01

    Optic disc and retinal vasculature are important anatomical structures in the retina of the eye and any changes observed in these structures provide vital information on severity of various diseases. Digital retinal images are shown to provide a meaningful way of documenting and assessing some of the key elements inside the eye including the optic nerve and the tiny retinal blood vessels. In this work, an attempt has been made to detect and differentiate abnormalities of the retina using Digital image processing together with Optimization based segmentation and Artificial Neural Network methods. The retinal fundus images were recorded using standard protocols. Ant Colony Optimization is employed to extract the most significant objects namely the optic disc and blood vessel. The features related to these objects are obtained and corresponding indices are also derived. Further, these features are subjected to classification using Radial Basis Function Neural Networks and compared with conventional training algorithms. Results show that the Ant Colony Optimization is efficient in extracting useful information from retinal images. The features derived are effective for classification of normal and abnormal images using Radial basis function networks compared to other methods. As Optic disc and blood vessels are significant markers of abnormality in retinal images, the method proposed appears to be useful for mass screening. In this paper, the objectives of the study, methodology and significant observations are presented. PMID:20467104

  10. Abnormality detection in retinal images using ant colony optimization and artificial neural networks - biomed 2010.

    PubMed

    Kavitha, Ganesan; Ramakrishnan, Swaminathan

    2010-01-01

    Optic disc and retinal vasculature are important anatomical structures in the retina of the eye and any changes observed in these structures provide vital information on severity of various diseases. Digital retinal images are shown to provide a meaningful way of documenting and assessing some of the key elements inside the eye including the optic nerve and the tiny retinal blood vessels. In this work, an attempt has been made to detect and differentiate abnormalities of the retina using Digital image processing together with Optimization based segmentation and Artificial Neural Network methods. The retinal fundus images were recorded using standard protocols. Ant Colony Optimization is employed to extract the most significant objects namely the optic disc and blood vessel. The features related to these objects are obtained and corresponding indices are also derived. Further, these features are subjected to classification using Radial Basis Function Neural Networks and compared with conventional training algorithms. Results show that the Ant Colony Optimization is efficient in extracting useful information from retinal images. The features derived are effective for classification of normal and abnormal images using Radial basis function networks compared to other methods. As Optic disc and blood vessels are significant markers of abnormality in retinal images, the method proposed appears to be useful for mass screening. In this paper, the objectives of the study, methodology and significant observations are presented.

  11. Method for early detection of cooling-loss events

    DOEpatents

    Bermudez, Sergio A.; Hamann, Hendrik F.; Marianno, Fernando J.

    2015-12-22

    A method of detecting cooling-loss event early is provided. The method includes defining a relative humidity limit and change threshold for a given space, measuring relative humidity in the given space, determining, with a processing unit, whether the measured relative humidity is within the defined relative humidity limit, generating a warning in an event the measured relative humidity is outside the defined relative humidity limit and determining whether a change in the measured relative humidity is less than the defined change threshold for the given space and generating an alarm in an event the change is greater than the defined change threshold.

  12. Method for early detection of cooling-loss events

    DOEpatents

    Bermudez, Sergio A.; Hamann, Hendrik; Marianno, Fernando J.

    2015-06-30

    A method of detecting cooling-loss event early is provided. The method includes defining a relative humidity limit and change threshold for a given space, measuring relative humidity in the given space, determining, with a processing unit, whether the measured relative humidity is within the defined relative humidity limit, generating a warning in an event the measured relative humidity is outside the defined relative humidity limit and determining whether a change in the measured relative humidity is less than the defined change threshold for the given space and generating an alarm in an event the change is greater than the defined change threshold.

  13. Detection of atypical seismic events on a regional scale

    NASA Astrophysics Data System (ADS)

    Solano-Hernandez, E. A.; Hjorleifsdottir, V.; Perez-Campos, X.; Iglesias, A.

    2013-12-01

    We propose an event-detection algorithm to locate seismic events on a regional scale. Our goal is to identify non-impulsive or 'atypical' events which are not detected by regional or global networks, due to their low P-wave amplitude. Ekstrom (2006) has developed and implemented a method to detect and locate sources of long-period seismic surface waves on a global scale. Atypical events are generated by, for example, rapid glacial movements (Ekstrom, et al., 2003; Ekstrom, et al., 2006), volcanic events (Schuler and Ekstrom, 2009) and landslides (Ekstrom and Stark, 2013). Furthermore, non-impulsive earthquakes have been located on oceanic transform faults (Abercrombie and Ekstrom, 2001). The current method (Ekstrom, 2006), that is applied on the scale of the globe, routinely detects events with magnitudes around Mw 5 and larger. In this work we wish to lower the detection threshold by using shorter period records registered by regional networks. The difficulty lies in that the shorter period records are strongly influenced by the heterogeneous crust and upper mantle, which need to be accounted for in the modeling process. Our proposed method involves first computing full waveforms, Green's functions or moment tensor responses, between a grid of test locations and existing seismic stations in a 3D medium. We then effectively back propagate observed data through cross correlation with the responses, obtaining a function that localizes in time and space at the source. Our method is a variant of the timereversal method presented by, for example, McMechan (1982), Tromp et al. (2005), Larmat et al. (2006), Gajewski and Tessmer (2005) and Kim et al. (2010). To calibrate the various parameters used by the detection method, we use the aftershocks sequence of the March 20, 2012 Ometepec, Guerrero, Mexico earthquake, recorded by the SSN (Mexican National Network). The lively aftershock sequence provided us with many events of different magnitudes, all occurring approximately

  14. Diagnostic Accuracy of Transvaginal Sonography in the Detection of Uterine Abnormalities in Infertile Women

    PubMed Central

    Niknejadi, Maryam; Haghighi, Hadieh; Ahmadi, Firoozeh; Niknejad, Fatemeh; Chehrazi, Mohammad; Vosough, Ahmad; Moenian, Deena

    2012-01-01

    Background Accurate diagnosis of uterine abnormalities has become a core part of the fertility work-up. A variety of modalities can be used for the diagnosis of uterine abnormalities. Objectives This study was designed to assess the diagnostic accuracy of transvaginal ultrasonography (TVS) in uterine pathologies of infertile patients using hysteroscopy as the gold standard. Patients and Methods This was a cross-sectional study carried out in the Department of Reproductive Imaging at Royan Institute from October 2007 to October 2008. In this study, the medical documents of 719 infertile women who were investigated with transvaginal ultrasound (TVS) and then hysteroscopy were reviewed. All women underwent hysteroscopy in the same cycle time after TVS. Seventy-six out of 719 patients were excluded from the study and 643 patients were studied. TVS was performed in the follicular phase after cessation of bleeding. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated for TVS. Hysteroscopy served as the gold standard. Results The overall sensitivity, specificity, positive and negative predictive values for TVS in the diagnosis of uterine abnormality was 79%, 82%, 84% and 71%, respectively. The sensitivity and PPV of TVS in detection of polyp were 88.3% and 81.6%, respectively. These indices were 89.2% and 92.5%, respectively for fibroma, 67% and 98.3%, respectively for subseptated uterus and 90.9% and 100%, respectively for septated uterus. Adhesion and unicornuated uterus have the lowest sensitivity with a sensitivity of 35% and PPV of 57.1%. Conclusion TVS is a cost-effective and non-invasive method for diagnosis of intrauterine lesions such as polyps, submucosal fibroids and septum. It is a valuable adjunctive to hysteroscopy with high accuracy for identification and characterization of intrauterine abnormalities. This may lead to a more precise surgery plan and performance. PMID:23329979

  15. Human Rights Event Detection from Heterogeneous Social Media Graphs.

    PubMed

    Chen, Feng; Neill, Daniel B

    2015-03-01

    Human rights organizations are increasingly monitoring social media for identification, verification, and documentation of human rights violations. Since manual extraction of events from the massive amount of online social network data is difficult and time-consuming, we propose an approach for automated, large-scale discovery and analysis of human rights-related events. We apply our recently developed Non-Parametric Heterogeneous Graph Scan (NPHGS), which models social media data such as Twitter as a heterogeneous network (with multiple different node types, features, and relationships) and detects emerging patterns in the network, to identify and characterize human rights events. NPHGS efficiently maximizes a nonparametric scan statistic (an aggregate measure of anomalousness) over connected subgraphs of the heterogeneous network to identify the most anomalous network clusters. It summarizes each event with information such as type of event, geographical locations, time, and participants, and provides documentation such as links to videos and news reports. Building on our previous work that demonstrates the utility of NPHGS for civil unrest prediction and rare disease outbreak detection, we present an analysis of human rights events detected by NPHGS using two years of Twitter data from Mexico. NPHGS was able to accurately detect relevant clusters of human rights-related tweets prior to international news sources, and in some cases, prior to local news reports. Analysis of social media using NPHGS could enhance the information-gathering missions of human rights organizations by pinpointing specific abuses, revealing events and details that may be blocked from traditional media sources, and providing evidence of emerging patterns of human rights violations. This could lead to more timely, targeted, and effective advocacy, as well as other potential interventions. PMID:27442843

  16. Human Rights Event Detection from Heterogeneous Social Media Graphs.

    PubMed

    Chen, Feng; Neill, Daniel B

    2015-03-01

    Human rights organizations are increasingly monitoring social media for identification, verification, and documentation of human rights violations. Since manual extraction of events from the massive amount of online social network data is difficult and time-consuming, we propose an approach for automated, large-scale discovery and analysis of human rights-related events. We apply our recently developed Non-Parametric Heterogeneous Graph Scan (NPHGS), which models social media data such as Twitter as a heterogeneous network (with multiple different node types, features, and relationships) and detects emerging patterns in the network, to identify and characterize human rights events. NPHGS efficiently maximizes a nonparametric scan statistic (an aggregate measure of anomalousness) over connected subgraphs of the heterogeneous network to identify the most anomalous network clusters. It summarizes each event with information such as type of event, geographical locations, time, and participants, and provides documentation such as links to videos and news reports. Building on our previous work that demonstrates the utility of NPHGS for civil unrest prediction and rare disease outbreak detection, we present an analysis of human rights events detected by NPHGS using two years of Twitter data from Mexico. NPHGS was able to accurately detect relevant clusters of human rights-related tweets prior to international news sources, and in some cases, prior to local news reports. Analysis of social media using NPHGS could enhance the information-gathering missions of human rights organizations by pinpointing specific abuses, revealing events and details that may be blocked from traditional media sources, and providing evidence of emerging patterns of human rights violations. This could lead to more timely, targeted, and effective advocacy, as well as other potential interventions.

  17. Abnormal verbal event related potentials in mild cognitive impairment and incipient Alzheimer's disease

    PubMed Central

    Olichney, J; Morris, S; Ochoa, C; Salmon, D; Thal, L; Kutas, M; Iragui, V

    2002-01-01

    Background: It has been reported that patients with amnesia have a reduced effect of word repetition upon the late positive component of the event related potential (ERP), which peaks at around 600 ms after word onset. Objective: To study a word repetition ERP paradigm in subjects with mild cognitive impairment. Subjects: 14 patients with mild cognitive impairment (mean mini-mental state examination score = 27); 14 normal elderly controls. Methods: Auditory category statements were each followed by a single visual target word (50% "congruous" category exemplars, 50% "incongruous") while ERPs were recorded. N400 (an ERP component elicited by semantically "incongruous" words) and LPC amplitude data were submitted to analysis of variance. Results: The latency of the N400 was slower in mild cognitive impairment. In normal controls, the ERPs to "congruous" targets showed a late positive component to new words, which was greatly diminished with repetition. This repetition effect in normal subjects started before 300 ms at right frontal sites, and peaked at ∼600 ms post-stimulus over posterior sites. In contrast, the group with mild cognitive impairment had a reduced repetition effect (p < 0.02), which started around 500 ms, with a more central distribution. Further comparisons within the cognitive impairment group showed no appreciable congruous word repetition effect among seven individuals who subsequently converted to probable Alzheimer's disease. The congruous word repetition effect in the group with mild cognitive impairment was almost entirely accounted for by the non-converters. The amplitude of the congruous late positive component word repetition effect was significantly correlated (0.38 ≤ r ≤ 0.73) with several verbal memory measures. Conclusions: The congruous word repetition ERP effect appears sensitive to the memory impairment in mild cognitive impairment and could have value in predicting incipient Alzheimer's disease. PMID:12235303

  18. Context-aware event detection smartphone application for first responders

    NASA Astrophysics Data System (ADS)

    Boddhu, Sanjay K.; Dave, Rakesh P.; McCartney, Matt; West, James A.; Williams, Robert L.

    2013-05-01

    The rise of social networking platforms like Twitter, Facebook, etc…, have provided seamless sharing of information (as chat, video and other media) among its user community on a global scale. Further, the proliferation of the smartphones and their connectivity networks has powered the ordinary individuals to share and acquire information regarding the events happening in his/her immediate vicinity in a real-time fashion. This human-centric sensed data being generated in "human-as-sensor" approach is tremendously valuable as it delivered mostly with apt annotations and ground truth that would be missing in traditional machine-centric sensors, besides high redundancy factor (same data thru multiple users). Further, when appropriately employed this real-time data can support in detecting localized events like fire, accidents, shooting, etc…, as they unfold and pin-point individuals being affected by those events. This spatiotemporal information, when made available for first responders in the event vicinity (or approaching it) can greatly assist them to make effective decisions to protect property and life in a timely fashion. In this vein, under SATE and YATE programs, the research team at AFRL Tec^Edge Discovery labs had demonstrated the feasibility of developing Smartphone applications, that can provide a augmented reality view of the appropriate detected events in a given geographical location (localized) and also provide an event search capability over a large geographic extent. In its current state, the application thru its backend connectivity utilizes a data (Text & Image) processing framework, which deals with data challenges like; identifying and aggregating important events, analyzing and correlating the events temporally and spatially and building a search enabled event database. Further, the smartphone application with its backend data processing workflow has been successfully field tested with live user generated feeds.

  19. Signal Detection of Adverse Drug Reaction of Amoxicillin Using the Korea Adverse Event Reporting System Database

    PubMed Central

    2016-01-01

    We conducted pharmacovigilance data mining for a β-lactam antibiotics, amoxicillin, and compare the adverse events (AEs) with the drug labels of 9 countries including Korea, USA, UK, Japan, Germany, Swiss, Italy, France, and Laos. We used the Korea Adverse Event Reporting System (KAERS) database, a nationwide database of AE reports, between December 1988 and June 2014. Frequentist and Bayesian methods were used to calculate disproportionality distribution of drug-AE pairs. The AE which was detected by all the three indices of proportional reporting ratio (PRR), reporting odds ratio (ROR), and information component (IC) was defined as a signal. The KAERS database contained a total of 807,582 AE reports, among which 1,722 reports were attributed to amoxicillin. Among the 192,510 antibiotics-AE pairs, the number of amoxicillin-AE pairs was 2,913. Among 241 AEs, 52 adverse events were detected as amoxicillin signals. Comparing the drug labels of 9 countries, 12 adverse events including ineffective medicine, bronchitis, rhinitis, sinusitis, dry mouth, gastroesophageal reflux, hypercholesterolemia, gastric carcinoma, abnormal crying, induration, pulmonary carcinoma, and influenza-like symptoms were not listed on any of the labels of nine countries. In conclusion, we detected 12 new signals of amoxicillin which were not listed on the labels of 9 countries. Therefore, it should be followed by signal evaluation including causal association, clinical significance, and preventability. PMID:27510377

  20. Automated Detection of Vessel Abnormalities on Fluorescein Angiogram in Malarial Retinopathy

    PubMed Central

    Zhao, Yitian; MacCormick, Ian J. C.; Parry, David G.; Beare, Nicholas A. V.; Harding, Simon P.; Zheng, Yalin

    2015-01-01

    The detection and assessment of intravascular filling defects is important, because they may represent a process central to cerebral malaria pathogenesis: neurovascular sequestration. We have developed and validated a framework that can automatically detect intravascular filling defects in fluorescein angiogram images. It first employs a state-of-the-art segmentation approach to extract the vessels from images and then divide them into individual segments by geometrical analysis. A feature vector based on the intensity and shape of saliency maps is generated to represent the level of abnormality of each vessel segment. An AdaBoost classifier with weighted cost coefficient is trained to classify the vessel segments into normal and abnormal categories. To demonstrate its effectiveness, we apply this framework to 6,358 vessel segments in images from 10 patients with malarial retinopathy. The test sensitivity, specificity, accuracy, and area under curve (AUC) are 74.7%, 73.5%, 74.1% and 74.2% respectively when compared to the reference standard of human expert manual annotations. This performance is comparable to the agreement that we find between human observers of intravascular filling defects. Our method will be a powerful new tool for studying malarial retinopathy. PMID:26053690

  1. Automated Detection of Vessel Abnormalities on Fluorescein Angiogram in Malarial Retinopathy.

    PubMed

    Zhao, Yitian; MacCormick, Ian J C; Parry, David G; Beare, Nicholas A V; Harding, Simon P; Zheng, Yalin

    2015-06-08

    The detection and assessment of intravascular filling defects is important, because they may represent a process central to cerebral malaria pathogenesis: neurovascular sequestration. We have developed and validated a framework that can automatically detect intravascular filling defects in fluorescein angiogram images. It first employs a state-of-the-art segmentation approach to extract the vessels from images and then divide them into individual segments by geometrical analysis. A feature vector based on the intensity and shape of saliency maps is generated to represent the level of abnormality of each vessel segment. An AdaBoost classifier with weighted cost coefficient is trained to classify the vessel segments into normal and abnormal categories. To demonstrate its effectiveness, we apply this framework to 6,358 vessel segments in images from 10 patients with malarial retinopathy. The test sensitivity, specificity, accuracy, and area under curve (AUC) are 74.7%, 73.5%, 74.1% and 74.2% respectively when compared to the reference standard of human expert manual annotations. This performance is comparable to the agreement that we find between human observers of intravascular filling defects. Our method will be a powerful new tool for studying malarial retinopathy.

  2. Automatic computer aided detection of abnormalities in multi-parametric prostate MRI

    NASA Astrophysics Data System (ADS)

    Litjens, G. J. S.; Vos, P. C.; Barentsz, J. O.; Karssemeijer, N.; Huisman, H. J.

    2011-03-01

    Development of CAD systems for detection of prostate cancer has been a recent topic of research. A multi-stage computer aided detection scheme is proposed to help reduce perception and oversight errors in multi-parametric prostate cancer screening MRI. In addition, important features for development of computer aided detection systems for prostate cancer screening MRI are identified. A fast, robust prostate segmentation routine is used to segment the prostate, based on coupled appearance and anatomy models. Subsequently a voxel classification is performed using a support vector machine to compute an abnormality likelihood map of the prostate. This classification step is based on quantitative voxel features like the apparent diffusion coefficient (ADC) and pharmacokinetic parameters. Local maxima in the likelihood map are found using a local maxima detector, after which regions around the local maxima are segmented. Region features are computed to represent statistical properties of the voxel features within the regions. Region classification is performed using these features, which results in a likelihood of abnormality per region. Performance was validated using a 188 patient dataset in a leave-one-patient-out manner. Ground truth was annotated by two expert radiologists. The results were evaluated using FROC analysis. The FROC curves show that inclusion of ADC and pharmacokinetic parameter features increases the performance of an automatic detection system. In addition it shows the potential of such an automated system in aiding radiologists diagnosing prostate MR, obtaining a sensitivity of respectively 74.7% and 83.4% at 7 and 9 false positives per patient.

  3. Detection of abnormal item based on time intervals for recommender systems.

    PubMed

    Gao, Min; Yuan, Quan; Ling, Bin; Xiong, Qingyu

    2014-01-01

    With the rapid development of e-business, personalized recommendation has become core competence for enterprises to gain profits and improve customer satisfaction. Although collaborative filtering is the most successful approach for building a recommender system, it suffers from "shilling" attacks. In recent years, the research on shilling attacks has been greatly improved. However, the approaches suffer from serious problem in attack model dependency and high computational cost. To solve the problem, an approach for the detection of abnormal item is proposed in this paper. In the paper, two common features of all attack models are analyzed at first. A revised bottom-up discretized approach is then proposed based on time intervals and the features for the detection. The distributions of ratings in different time intervals are compared to detect anomaly based on the calculation of chi square distribution (χ(2)). We evaluated our approach on four types of items which are defined according to the life cycles of these items. The experimental results show that the proposed approach achieves a high detection rate with low computational cost when the number of attack profiles is more than 15. It improves the efficiency in shilling attacks detection by narrowing down the suspicious users.

  4. Detection of Abnormal Item Based on Time Intervals for Recommender Systems

    PubMed Central

    Yuan, Quan; Ling, Bin; Xiong, Qingyu

    2014-01-01

    With the rapid development of e-business, personalized recommendation has become core competence for enterprises to gain profits and improve customer satisfaction. Although collaborative filtering is the most successful approach for building a recommender system, it suffers from “shilling” attacks. In recent years, the research on shilling attacks has been greatly improved. However, the approaches suffer from serious problem in attack model dependency and high computational cost. To solve the problem, an approach for the detection of abnormal item is proposed in this paper. In the paper, two common features of all attack models are analyzed at first. A revised bottom-up discretized approach is then proposed based on time intervals and the features for the detection. The distributions of ratings in different time intervals are compared to detect anomaly based on the calculation of chi square distribution (χ2). We evaluated our approach on four types of items which are defined according to the life cycles of these items. The experimental results show that the proposed approach achieves a high detection rate with low computational cost when the number of attack profiles is more than 15. It improves the efficiency in shilling attacks detection by narrowing down the suspicious users. PMID:24693248

  5. Detection of abnormal item based on time intervals for recommender systems.

    PubMed

    Gao, Min; Yuan, Quan; Ling, Bin; Xiong, Qingyu

    2014-01-01

    With the rapid development of e-business, personalized recommendation has become core competence for enterprises to gain profits and improve customer satisfaction. Although collaborative filtering is the most successful approach for building a recommender system, it suffers from "shilling" attacks. In recent years, the research on shilling attacks has been greatly improved. However, the approaches suffer from serious problem in attack model dependency and high computational cost. To solve the problem, an approach for the detection of abnormal item is proposed in this paper. In the paper, two common features of all attack models are analyzed at first. A revised bottom-up discretized approach is then proposed based on time intervals and the features for the detection. The distributions of ratings in different time intervals are compared to detect anomaly based on the calculation of chi square distribution (χ(2)). We evaluated our approach on four types of items which are defined according to the life cycles of these items. The experimental results show that the proposed approach achieves a high detection rate with low computational cost when the number of attack profiles is more than 15. It improves the efficiency in shilling attacks detection by narrowing down the suspicious users. PMID:24693248

  6. Human visual system-based smoking event detection

    NASA Astrophysics Data System (ADS)

    Odetallah, Amjad D.; Agaian, Sos S.

    2012-06-01

    Human action (e.g. smoking, eating, and phoning) analysis is an important task in various application domains like video surveillance, video retrieval, human-computer interaction systems, and so on. Smoke detection is a crucial task in many video surveillance applications and could have a great impact to raise the level of safety of urban areas, public parks, airplanes, hospitals, schools and others. The detection task is challenging since there is no prior knowledge about the object's shape, texture and color. In addition, its visual features will change under different lighting and weather conditions. This paper presents a new scheme of a system for detecting human smoking events, or small smoke, in a sequence of images. In developed system, motion detection and background subtraction are combined with motion-region-saving, skin-based image segmentation, and smoke-based image segmentation to capture potential smoke regions which are further analyzed to decide on the occurrence of smoking events. Experimental results show the effectiveness of the proposed approach. As well, the developed method is capable of detecting the small smoking events of uncertain actions with various cigarette sizes, colors, and shapes.

  7. The effects of anatomical information and observer expertise on abnormality detection task

    NASA Astrophysics Data System (ADS)

    Zhang, L.; Cavaro-Ménard, C.; Le Callet, P.; Cooper, L. H. K.; Hunault, G.; Tanguy, J.-Y.

    2011-03-01

    This paper presents a novel study investigating the influences of Magnetic Resonance (MR) image anatomical information and observer expertise on an abnormality detection task. MRI is exquisitely sensitive for detecting brain abnormalities, particularly in the evaluation of white matter diseases, e.g. multiple sclerosis (MS). For this reason, MS lesions are simulated as the target stimuli for detection in the present study. Two different image backgrounds are used in the following experiments: a) homogeneous region of white matter tissue, and b) one slice of a healthy brain MR image. One expert radiologist (more than 10 years' experience), three radiologists (less than 5 years' experience) and eight naïve observers (without any prior medical knowledge) have performed these experiments, during which they have been asked different questions dependent upon level of experience; the three radiologists and eight naïve observers were asked if they were aware of any hyper-signal, likely to represent an MS lesion, while the most experienced consultant was asked if a clinically significant sign was present. With the percentages of response "yes" displayed on the y-axis and the lesion intensity contrasts on the x-axis, psychometric function is generated from the observer' responses. Results of psychometric functions and calculated thresholds indicate that radiologists have better hyper-signal detection ability than naïve observers, which is intuitively shown by the lower simple visibility thresholds of radiologists. However, when radiologists perform a task with clinical implications, e.g. to detect a clinically significant sign, their detection thresholds are elevated. Moreover, the study indicates that for the radiologists, the simple visibility thresholds remain the same with and without the anatomical information, which reduces the threshold for the clinically significant sign detection task. Findings provide further insight into human visual system processing for this

  8. Automatic event detection based on artificial neural networks

    NASA Astrophysics Data System (ADS)

    Doubravová, Jana; Wiszniowski, Jan; Horálek, Josef

    2015-04-01

    The proposed algorithm was developed to be used for Webnet, a local seismic network in West Bohemia. The Webnet network was built to monitor West Bohemia/Vogtland swarm area. During the earthquake swarms there is a large number of events which must be evaluated automatically to get a quick estimate of the current earthquake activity. Our focus is to get good automatic results prior to precise manual processing. With automatic data processing we may also reach a lower completeness magnitude. The first step of automatic seismic data processing is the detection of events. To get a good detection performance we require low number of false detections as well as high number of correctly detected events. We used a single layer recurrent neural network (SLRNN) trained by manual detections from swarms in West Bohemia in the past years. As inputs of the SLRNN we use STA/LTA of half-octave filter bank fed by vertical and horizontal components of seismograms. All stations were trained together to obtain the same network with the same neuron weights. We tried several architectures - different number of neurons - and different starting points for training. Networks giving the best results for training set must not be the optimal ones for unknown waveforms. Therefore we test each network on test set from different swarm (but still with similar characteristics, i.e. location, focal mechanisms, magnitude range). We also apply a coincidence verification for each event. It means that we can lower the number of false detections by rejecting events on one station only and force to declare an event on all stations in the network by coincidence on two or more stations. In further work we would like to retrain the network for each station individually so each station will have its own coefficients (neural weights) set. We would also like to apply this method to data from Reykjanet network located in Reykjanes peninsula, Iceland. As soon as we have a reliable detection, we can proceed to

  9. Detecting rare gene transfer events in bacterial populations

    PubMed Central

    Nielsen, Kaare M.; Bøhn, Thomas; Townsend, Jeffrey P.

    2014-01-01

    Horizontal gene transfer (HGT) enables bacteria to access, share, and recombine genetic variation, resulting in genetic diversity that cannot be obtained through mutational processes alone. In most cases, the observation of evolutionary successful HGT events relies on the outcome of initially rare events that lead to novel functions in the new host, and that exhibit a positive effect on host fitness. Conversely, the large majority of HGT events occurring in bacterial populations will go undetected due to lack of replication success of transformants. Moreover, other HGT events that would be highly beneficial to new hosts can fail to ensue due to lack of physical proximity to the donor organism, lack of a suitable gene transfer mechanism, genetic compatibility, and stochasticity in tempo-spatial occurrence. Experimental attempts to detect HGT events in bacterial populations have typically focused on the transformed cells or their immediate offspring. However, rare HGT events occurring in large and structured populations are unlikely to reach relative population sizes that will allow their immediate identification; the exception being the unusually strong positive selection conferred by antibiotics. Most HGT events are not expected to alter the likelihood of host survival to such an extreme extent, and will confer only minor changes in host fitness. Due to the large population sizes of bacteria and the time scales involved, the process and outcome of HGT are often not amenable to experimental investigation. Population genetic modeling of the growth dynamics of bacteria with differing HGT rates and resulting fitness changes is therefore necessary to guide sampling design and predict realistic time frames for detection of HGT, as it occurs in laboratory or natural settings. Here we review the key population genetic parameters, consider their complexity and highlight knowledge gaps for further research. PMID:24432015

  10. Detecting rare gene transfer events in bacterial populations.

    PubMed

    Nielsen, Kaare M; Bøhn, Thomas; Townsend, Jeffrey P

    2014-01-01

    Horizontal gene transfer (HGT) enables bacteria to access, share, and recombine genetic variation, resulting in genetic diversity that cannot be obtained through mutational processes alone. In most cases, the observation of evolutionary successful HGT events relies on the outcome of initially rare events that lead to novel functions in the new host, and that exhibit a positive effect on host fitness. Conversely, the large majority of HGT events occurring in bacterial populations will go undetected due to lack of replication success of transformants. Moreover, other HGT events that would be highly beneficial to new hosts can fail to ensue due to lack of physical proximity to the donor organism, lack of a suitable gene transfer mechanism, genetic compatibility, and stochasticity in tempo-spatial occurrence. Experimental attempts to detect HGT events in bacterial populations have typically focused on the transformed cells or their immediate offspring. However, rare HGT events occurring in large and structured populations are unlikely to reach relative population sizes that will allow their immediate identification; the exception being the unusually strong positive selection conferred by antibiotics. Most HGT events are not expected to alter the likelihood of host survival to such an extreme extent, and will confer only minor changes in host fitness. Due to the large population sizes of bacteria and the time scales involved, the process and outcome of HGT are often not amenable to experimental investigation. Population genetic modeling of the growth dynamics of bacteria with differing HGT rates and resulting fitness changes is therefore necessary to guide sampling design and predict realistic time frames for detection of HGT, as it occurs in laboratory or natural settings. Here we review the key population genetic parameters, consider their complexity and highlight knowledge gaps for further research.

  11. Comparison of Event Detection Methods for Centralized Sensor Networks

    NASA Technical Reports Server (NTRS)

    Sauvageon, Julien; Agogiono, Alice M.; Farhang, Ali; Tumer, Irem Y.

    2006-01-01

    The development of an Integrated Vehicle Health Management (IVHM) for space vehicles has become a great concern. Smart Sensor Networks is one of the promising technologies that are catching a lot of attention. In this paper, we propose to a qualitative comparison of several local event (hot spot) detection algorithms in centralized redundant sensor networks. The algorithms are compared regarding their ability to locate and evaluate the event under noise and sensor failures. The purpose of this study is to check if the ratio performance/computational power of the Mote Fuzzy Validation and Fusion algorithm is relevant compare to simpler methods.

  12. Detection of abnormalities in febrile AIDS patients with In-111-labeled leukocyte and Ga-67 scintigraphy

    SciTech Connect

    Fineman, D.S.; Palestro, C.J.; Kim, C.K.; Needle, L.B.; Vallabhajosula, S.; Solomon, R.W.; Goldsmith, S.J.

    1989-03-01

    Thirty-six patients with acquired immunodeficiency syndrome (AIDS), who were febrile but without localizing signs, underwent indium-111 leukocyte scintigraphy 24 hours after injection of labeled white blood cells (WBCs) and were restudied 48 hours after injection of gallium-67 citrate. Fifty-six abnormalities were identified as possible sources of the fever; 27 were confirmed with biopsy. Of these 27, 15 were identified only on In-111 WBC scans (including colitis, sinusitis, and focal bacterial pneumonia); six, only on Ga-67 scans (predominantly Pneumocystis carinii pneumonia and lymphadenopathy); and six, on both studies (predominantly pulmonary lesions). In-111 WBC scanning revealed 21 of 27 abnormalities (78%) and gallium scanning, 12 of 27 (44%). If only one scintigraphic study has been performed, particularly with Ga-67, a significant number of lesions would not have been detected. The authors believe radionuclide evaluation of the febrile AIDS patient without localizing signs should begin with In-111 WBC scintigraphy. Gallium scanning may be used depending on results of In-111 WBC scans or if there is a high index of suspicion for P carinii pneumonia.

  13. Detection and interpretation of seismoacoustic events at German infrasound stations

    NASA Astrophysics Data System (ADS)

    Pilger, Christoph; Koch, Karl; Ceranna, Lars

    2016-04-01

    Three infrasound arrays with collocated or nearby installed seismometers are operated by the Federal Institute for Geosciences and Natural Resources (BGR) as the German National Data Center (NDC) for the verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). Infrasound generated by seismoacoustic events is routinely detected at these infrasound arrays, but air-to-ground coupled acoustic waves occasionally show up in seismometer recordings as well. Different natural and artificial sources like meteoroids as well as industrial and mining activity generate infrasonic signatures that are simultaneously detected at microbarometers and seismometers. Furthermore, many near-surface sources like earthquakes and explosions generate both seismic and infrasonic waves that can be detected successively with both technologies. The combined interpretation of seismic and acoustic signatures provides additional information about the origin time and location of remote infrasound events or about the characterization of seismic events distinguishing man-made and natural origins. Furthermore, seismoacoustic studies help to improve the modelling of infrasound propagation and ducting in the atmosphere and allow quantifying the portion of energy coupled into ground and into air by seismoacoustic sources. An overview of different seismoacoustic sources and their detection by German infrasound stations as well as some conclusions on the benefit of a combined seismoacoustic analysis are presented within this study.

  14. Early Lung Cancer Detection in Uranium Miners with Abnormal Sputum Cytology

    SciTech Connect

    Saccomanno, G.

    2000-06-30

    ''Early Lung Cancer Detection in Uranium Miners with Abnormal Sputum Cytology'' was funded by the Department of Energy to monitor the health effects of radon exposure and/or cigarette smoke on uranium workers from the Colorado Plateau. The resulting Saccomanno Uranium Workers Archive and data base has been used as a source of information to prove eligibility for compensation under the Radiation Exposure Compensation Act and as the source of primary data tissue for a subcontract and other collaborations with outside investigators. The latter includes a study of radon exposure and lung cancer risk in a non-smoking cohort of uranium miners (subcontract); a study of genetic markers for lung cancer susceptibility; and a study of {sup 210}Pb accumulation in the skull as a biomarker of radon exposure.

  15. PMU Data Event Detection: A User Guide for Power Engineers

    SciTech Connect

    Allen, A.; Singh, M.; Muljadi, E.; Santoso, S.

    2014-10-01

    This user guide is intended to accompany a software package containing a Matrix Laboratory (MATLAB) script and related functions for processing phasor measurement unit (PMU) data. This package and guide have been developed by the National Renewable Energy Laboratory and the University of Texas at Austin. The objective of this data processing exercise is to discover events in the vast quantities of data collected by PMUs. This document attempts to cover some of the theory behind processing the data to isolate events as well as the functioning of the MATLAB scripts. The report describes (1) the algorithms and mathematical background that the accompanying MATLAB codes use to detect events in PMU data and (2) the inputs required from the user and the outputs generated by the scripts.

  16. Array-Based Comparative Genomic Hybridization for the Genomewide Detection of Submicroscopic Chromosomal Abnormalities

    PubMed Central

    Vissers, Lisenka E. L. M. ; de Vries, Bert B. A. ; Osoegawa, Kazutoyo ; Janssen, Irene M. ; Feuth, Ton ; Choy, Chik On ; Straatman, Huub ; van der Vliet, Walter ; Huys, Erik H. L. P. G. ; van Rijk, Anke ; Smeets, Dominique ; van Ravenswaaij-Arts, Conny M. A. ; Knoers, Nine V. ; van der Burgt, Ineke ; de Jong, Pieter J. ; Brunner, Han G. ; van Kessel, Ad Geurts ; Schoenmakers, Eric F. P. M. ; Veltman, Joris A. 

    2003-01-01

    Microdeletions and microduplications, not visible by routine chromosome analysis, are a major cause of human malformation and mental retardation. Novel high-resolution, whole-genome technologies can improve the diagnostic detection rate of these small chromosomal abnormalities. Array-based comparative genomic hybridization allows such a high-resolution screening by hybridizing differentially labeled test and reference DNAs to arrays consisting of thousands of genomic clones. In this study, we tested the diagnostic capacity of this technology using ∼3,500 flourescent in situ hybridization–verified clones selected to cover the genome with an average of 1 clone per megabase (Mb). The sensitivity and specificity of the technology were tested in normal-versus-normal control experiments and through the screening of patients with known microdeletion syndromes. Subsequently, a series of 20 cytogenetically normal patients with mental retardation and dysmorphisms suggestive of a chromosomal abnormality were analyzed. In this series, three microdeletions and two microduplications were identified and validated. Two of these genomic changes were identified also in one of the parents, indicating that these are large-scale genomic polymorphisms. Deletions and duplications as small as 1 Mb could be reliably detected by our approach. The percentage of false-positive results was reduced to a minimum by use of a dye-swap-replicate analysis, all but eliminating the need for laborious validation experiments and facilitating implementation in a routine diagnostic setting. This high-resolution assay will facilitate the identification of novel genes involved in human mental retardation and/or malformation syndromes and will provide insight into the flexibility and plasticity of the human genome. PMID:14628292

  17. Weakly supervised learning of a classifier for unusual event detection.

    PubMed

    Jäger, Mark; Knoll, Christian; Hamprecht, Fred A

    2008-09-01

    In this paper, we present an automatic classification framework combining appearance based features and hidden Markov models (HMM) to detect unusual events in image sequences. One characteristic of the classification task is that anomalies are rare. This reflects the situation in the quality control of industrial processes, where error events are scarce by nature. As an additional restriction, class labels are only available for the complete image sequence, since frame-wise manual scanning of the recorded sequences for anomalies is too expensive and should, therefore, be avoided. The proposed framework reduces the feature space dimension of the image sequences by employing subspace methods and encodes characteristic temporal dynamics using continuous hidden Markov models (CHMMs). The applied learning procedure is as follows. 1) A generative model for the regular sequences is trained (one-class learning). 2) The regular sequence model (RSM) is used to locate potentially unusual segments within error sequences by means of a change detection algorithm (outlier detection). 3) Unusual segments are used to expand the RSM to an error sequence model (ESM). The complexity of the ESM is controlled by means of the Bayesian Information Criterion (BIC). The likelihood ratio of the data given the ESM and the RSM is used for the classification decision. This ratio is close to one for sequences without error events and increases for sequences containing error events. Experimental results are presented for image sequences recorded from industrial laser welding processes. We demonstrate that the learning procedure can significantly reduce the user interaction and that sequences with error events can be found with a small false positive rate. It has also been shown that a modeling of the temporal dynamics is necessary to reach these low error rates.

  18. Gait event detection during stair walking using a rate gyroscope.

    PubMed

    Formento, Paola Catalfamo; Acevedo, Ruben; Ghoussayni, Salim; Ewins, David

    2014-03-19

    Gyroscopes have been proposed as sensors for ambulatory gait analysis and functional electrical stimulation systems. These applications often require detection of the initial contact (IC) of the foot with the floor and/or final contact or foot off (FO) from the floor during outdoor walking. Previous investigations have reported the use of a single gyroscope placed on the shank for detection of IC and FO on level ground and incline walking. This paper describes the evaluation of a gyroscope placed on the shank for determination of IC and FO in subjects ascending and descending a set of stairs. Performance was compared with a reference pressure measurement system. The absolute mean difference between the gyroscope and the reference was less than 45 ms for IC and better than 135 ms for FO for both activities. Detection success was over 93%. These results provide preliminary evidence supporting the use of a gyroscope for gait event detection when walking up and down stairs.

  19. Gait Event Detection during Stair Walking Using a Rate Gyroscope

    PubMed Central

    Formento, Paola Catalfamo; Acevedo, Ruben; Ghoussayni, Salim; Ewins, David

    2014-01-01

    Gyroscopes have been proposed as sensors for ambulatory gait analysis and functional electrical stimulation systems. These applications often require detection of the initial contact (IC) of the foot with the floor and/or final contact or foot off (FO) from the floor during outdoor walking. Previous investigations have reported the use of a single gyroscope placed on the shank for detection of IC and FO on level ground and incline walking. This paper describes the evaluation of a gyroscope placed on the shank for determination of IC and FO in subjects ascending and descending a set of stairs. Performance was compared with a reference pressure measurement system. The absolute mean difference between the gyroscope and the reference was less than 45 ms for IC and better than 135 ms for FO for both activities. Detection success was over 93%. These results provide preliminary evidence supporting the use of a gyroscope for gait event detection when walking up and down stairs. PMID:24651724

  20. Integrated Seismic Event Detection and Location by Advanced Array Processing

    SciTech Connect

    Kvaerna, T; Gibbons, S J; Ringdal, F; Harris, D B

    2007-02-09

    The principal objective of this two-year study is to develop and test a new advanced, automatic approach to seismic detection/location using array processing. We address a strategy to obtain significantly improved precision in the location of low-magnitude events compared with current fully-automatic approaches, combined with a low false alarm rate. We have developed and evaluated a prototype automatic system which uses as a basis regional array processing with fixed, carefully calibrated, site-specific parameters in conjuction with improved automatic phase onset time estimation. We have in parallel developed tools for Matched Field Processing for optimized detection and source-region identification of seismic signals. This narrow-band procedure aims to mitigate some of the causes of difficulty encountered using the standard array processing system, specifically complicated source-time histories of seismic events and shortcomings in the plane-wave approximation for seismic phase arrivals at regional arrays.

  1. Polygraph lie detection on real events in a laboratory setting.

    PubMed

    Bradley, M T; Cullen, M C

    1993-06-01

    This laboratory study dealt with real-life intense emotional events. Subjects generated embarrassing stories from their experience, then submitted to polygraph testing and, by lying, denied their stories and, by telling the truth, denied a randomly assigned story. Money was given as an incentive to be judged innocent on each story. An interrogator, blind to the stories, used Control Question Tests and found subjects more deceptive when lying than when truthful. Stories interacted with order such that lying on the second story was more easily detected than lying on the first. Embarrassing stories provide an alternative to the use of mock crimes to study lie detection in the laboratory.

  2. Real-Time Plasma Process Condition Sensing and Abnormal Process Detection

    PubMed Central

    Yang, Ryan; Chen, Rongshun

    2010-01-01

    The plasma process is often used in the fabrication of semiconductor wafers. However, due to the lack of real-time etching control, this may result in some unacceptable process performances and thus leads to significant waste and lower wafer yield. In order to maximize the product wafer yield, a timely and accurately process fault or abnormal detection in a plasma reactor is needed. Optical emission spectroscopy (OES) is one of the most frequently used metrologies in in-situ process monitoring. Even though OES has the advantage of non-invasiveness, it is required to provide a huge amount of information. As a result, the data analysis of OES becomes a big challenge. To accomplish real-time detection, this work employed the sigma matching method technique, which is the time series of OES full spectrum intensity. First, the response model of a healthy plasma spectrum was developed. Then, we defined a matching rate as an indictor for comparing the difference between the tested wafers response and the health sigma model. The experimental results showed that this proposal method can detect process faults in real-time, even in plasma etching tools. PMID:22219683

  3. Statistical language analysis for automatic exfiltration event detection.

    SciTech Connect

    Robinson, David Gerald

    2010-04-01

    This paper discusses the recent development a statistical approach for the automatic identification of anomalous network activity that is characteristic of exfiltration events. This approach is based on the language processing method eferred to as latent dirichlet allocation (LDA). Cyber security experts currently depend heavily on a rule-based framework for initial detection of suspect network events. The application of the rule set typically results in an extensive list of uspect network events that are then further explored manually for suspicious activity. The ability to identify anomalous network events is heavily dependent on the experience of the security personnel wading through the network log. Limitations f this approach are clear: rule-based systems only apply to exfiltration behavior that has previously been observed, and experienced cyber security personnel are rare commodities. Since the new methodology is not a discrete rule-based pproach, it is more difficult for an insider to disguise the exfiltration events. A further benefit is that the methodology provides a risk-based approach that can be implemented in a continuous, dynamic or evolutionary fashion. This permits uspect network activity to be identified early with a quantifiable risk associated with decision making when responding to suspicious activity.

  4. Hidden Markov Models for Detecting Aseismic Events in Southern California

    NASA Astrophysics Data System (ADS)

    Granat, R.

    2004-12-01

    We employ a hidden Markov model (HMM) to segment surface displacement time series collection by the Southern California Integrated Geodetic Network (SCIGN). These segmented time series are then used to detect regional events by observing the number of simultaneous mode changes across the network; if a large number of stations change at the same time, that indicates an event. The hidden Markov model (HMM) approach assumes that the observed data has been generated by an unobservable dynamical statistical process. The process is of a particular form such that each observation is coincident with the system being in a particular discrete state, which is interpreted as a behavioral mode. The dynamics are the model are constructed so that the next state is directly dependent only on the current state -- it is a first order Markov process. The model is completely described by a set of parameters: the initial state probabilities, the first order Markov chain state-to-state transition probabilities, and the probability distribution of observable outputs associated with each state. The result of this approach is that our segmentation decisions are based entirely on statistical changes in the behavior of the observed daily displacements. In general, finding the optimal model parameters to fit the data is a difficult problem. We present an innovative model fitting method that is unsupervised (i.e., it requires no labeled training data) and uses a regularized version of the expectation-maximization (EM) algorithm to ensure that model solutions are both robust with respect to initial conditions and of high quality. We demonstrate the reliability of the method as compared to standard model fitting methods and show that it results in lower noise in the mode change correlation signal used to detect regional events. We compare candidate events detected by this method to the seismic record and observe that most are not correlated with a significant seismic event. Our analysis

  5. Prenatal aneupioidy detection by fluorencence in situ hybridization (FISH) in 1,068 second trimester pregnancies with fetal ultrasound abnormalities

    SciTech Connect

    Ward, B.E.; Wright, M.; Lytle, C. |

    1994-09-01

    One indication for rapid prenatal aneuploidy detection in uncultured amniocytes by FISH is the identification of fetal abnormalities by ultrasound. We analyzed 1,068 consecutive specimens from second trimester pregnancies with fetal ultrasound abnormalities referred for FISH plus cytogenetics. These specimens are a subset (14.7%) of the most recent 7,240 clinical referrals for these combined analyses. Hybridization with specific probes for chromosomes 21, 18, 13, X and Y were used to detect common aneuploidies. As defined by previously described criteria, specimens were reported as informative disomic, informative trisomic, or uninformative within two days of receipt. The rate of informative results from acceptable specimens was 90.1%. The vast majority of uninformative results was due to maternal cell contamination which precluded analysis. Within the informative group there were no false positives, false negatives nor reports of incorrect gender. Of the 1,068 tested specimens with ultrasound abnormalities, 135 (12.5%) were cytogenetically diagnosed as aneuploid. Prior to the cytogenetic analysis, a total of 107 aneuploidies were correctly identified by FISH. The remaining 26 aneuploidies generated an uninformative FISH result. The overall FISH detection rate for aneuploidy (including informative and uninformative results) was 79%. Other unbalanced chromosome abnormalities were present in 2.1% of specimens and 0.7% had balanced chromosome abnormalities. The inclusive total cytogenetic abnormality rate was 15.4%, of which 85% were potentially detectable by our FISH protocol. This clinical experience demonstrates that aneuploidy detection by FISH on uncultured amniocytes can provide accurate and rapid identification of aneuploidies, especially when such abnormalities are suspected following the diagnosis of fetal anomalies by ultrasound examination.

  6. Accurate means of detecting and characterizing abnormal patterns of ventricular activation by phase image analysis

    SciTech Connect

    Botvinick, E.H.; Frais, M.A.; Shosa, D.W.; O'Connell, J.W.; Pacheco-Alvarez, J.A.; Scheinman, M.; Hattner, R.S.; Morady, F.; Faulkner, D.B.

    1982-08-01

    The ability of scintigraphic phase image analysis to characterize patterns of abnormal ventricular activation was investigated. The pattern of phase distribution and sequential phase changes over both right and left ventricular regions of interest were evaluated in 16 patients with normal electrical activation and wall motion and compared with those in 8 patients with an artificial pacemaker and 4 patients with sinus rhythm with the Wolff-Parkinson-White syndrome and delta waves. Normally, the site of earliest phase angle was seen at the base of the interventricular septum, with sequential change affecting the body of the septum and the cardiac apex and then spreading laterally to involve the body of both ventricles. The site of earliest phase angle was located at the apex of the right ventricle in seven patients with a right ventricular endocardial pacemaker and on the lateral left ventricular wall in one patient with a left ventricular epicardial pacemaker. In each case the site corresponded exactly to the position of the pacing electrode as seen on posteroanterior and left lateral chest X-ray films, and sequential phase changes spread from the initial focus to affect both ventricles. In each of the patients with the Wolff-Parkinson-White syndrome, the site of earliest ventricular phase angle was located, and it corresponded exactly to the site of the bypass tract as determined by endocardial mapping. In this way, four bypass pathways, two posterior left paraseptal, one left lateral and one right lateral, were correctly localized scintigraphically. On the basis of the sequence of mechanical contraction, phase image analysis provides an accurate noninvasive method of detecting abnormal foci of ventricular activation.

  7. Basic Characteristics of a Macroscopic Measure for Detecting Abnormal Changes in a Multiagent System

    PubMed Central

    Kinoshita, Tetsuo

    2015-01-01

    Multiagent application systems must deal with various changes in both the system and the system environment at runtime. Generally, such changes have undesirable negative effects on the system. To manage and control the system, it is important to observe and detect negative effects using an appropriate observation function of the system’s behavior. This paper focuses on the design of this function and proposes a new macroscopic measure with which to observe behavioral characteristics of a runtime multiagent system. The proposed measure is designed as the variance of fluctuation of a macroscopic activity factor of the whole system, based on theoretical analysis of the macroscopic behavioral model of a multiagent system. Experiments are conducted to investigate basic characteristics of the proposed measure, using a test bed system. The results of experiments show that the proposed measure reacts quickly and increases drastically in response to abnormal changes in the system. Hence, the proposed measure is considered a measure that can be used to detect undesirable changes in a multiagent system. PMID:25897499

  8. Abnormal Ventral and Dorsal Attention Network Activity during Single and Dual Target Detection in Schizophrenia

    PubMed Central

    Jimenez, Amy M.; Lee, Junghee; Wynn, Jonathan K.; Cohen, Mark S.; Engel, Stephen A.; Glahn, David C.; Nuechterlein, Keith H.; Reavis, Eric A.; Green, Michael F.

    2016-01-01

    Early visual perception and attention are impaired in schizophrenia, and these deficits can be observed on target detection tasks. These tasks activate distinct ventral and dorsal brain networks which support stimulus-driven and goal-directed attention, respectively. We used single and dual target rapid serial visual presentation (RSVP) tasks during fMRI with an ROI approach to examine regions within these networks associated with target detection and the attentional blink (AB) in 21 schizophrenia outpatients and 25 healthy controls. In both tasks, letters were targets and numbers were distractors. For the dual target task, the second target (T2) was presented at three different lags after the first target (T1) (lag1 = 100 ms, lag3 = 300 ms, lag7 = 700ms). For both single and dual target tasks, patients identified fewer targets than controls. For the dual target task, both groups showed the expected AB effect with poorer performance at lag 3 than at lags 1 or 7, and there was no group by lag interaction. During the single target task, patients showed abnormally increased deactivation of the temporo-parietal junction (TPJ), a key region of the ventral network. When attention demands were increased during the dual target task, patients showed overactivation of the posterior intraparietal cortex, a key dorsal network region, along with failure to deactivate TPJ. Results suggest inefficient and faulty suppression of salience-oriented processing regions, resulting in increased sensitivity to stimuli in general, and difficulty distinguishing targets from non-targets. PMID:27014135

  9. Towards perception awareness: Perceptual event detection for Brain computer interfaces.

    PubMed

    Nejati, Hossein; Tsourides, Kleovoulos; Pomponiu, Victor; Ehrenberg, Evan C; Ngai-Man Cheung; Sinha, Pawan

    2015-08-01

    Brain computer interface (BCI) technology is becoming increasingly popular in many domains such as entertainment, mental state analysis, and rehabilitation. For robust performance in these domains, detecting perceptual events would be a vital ability, enabling adaptation to and act on the basis of user's perception of the environment. Here we present a framework to automatically mine spatiotemporal characteristics of a given perceptual event. As this "signature" is derived directly from subject's neural behavior, it can serve as a representation of the subject's perception of the targeted scenario, which in turn allows a BCI system to gain a new level of context awareness: perception awareness. As a proof of concept, we show the application of the proposed framework on MEG signal recordings from a face perception study, and the resulting temporal and spatial characteristics of the derived neural signature, as well as it's compatibility with the neuroscientific literature on face perception.

  10. Endmember detection in marine environment with oil spill event

    NASA Astrophysics Data System (ADS)

    Andreou, Charoula; Karathanassi, Vassilia

    2011-11-01

    Oil spill events are a crucial environmental issue. Detection of oil spills is important for both oil exploration and environmental protection. In this paper, investigation of hyperspectral remote sensing is performed for the detection of oil spills and the discrimination of different oil types. Spectral signatures of different oil types are very useful, since they may serve as endmembers in unmixing and classification models. Towards this direction, an oil spectral library, resulting from spectral measurements of artificial oil spills as well as of look-alikes in marine environment was compiled. Samples of four different oil types were used; two crude oils, one marine residual fuel oil, and one light petroleum product. Lookalikes comprise sea water, river discharges, shallow water and water with algae. Spectral measurements were acquired with spectro-radiometer GER1500. Moreover, oil and look-alikes spectral signatures have been examined whether they can be served as endmembers. This was accomplished by testifying their linear independence. After that, synthetic hyperspectral images based on the relevant oil spectral library were created. Several simplex-based endmember algorithms such as sequential maximum angle convex cone (SMACC), vertex component analysis (VCA), n-finder algorithm (N-FINDR), and automatic target generation process (ATGP) were applied on the synthetic images in order to evaluate their effectiveness for detecting oil spill events occurred from different oil types. Results showed that different types of oil spills with various thicknesses can be extracted as endmembers.

  11. Model observer design for detecting multiple abnormalities in anatomical background images

    NASA Astrophysics Data System (ADS)

    Wen, Gezheng; Markey, Mia K.; Park, Subok

    2016-03-01

    As psychophysical studies are resource-intensive to conduct, model observers are commonly used to assess and optimize medical imaging quality. Existing model observers were typically designed to detect at most one signal. However, in clinical practice, there may be multiple abnormalities in a single image set (e.g., multifocal and multicentric breast cancers (MMBC)), which can impact treatment planning. Prevalence of signals can be different across anatomical regions, and human observers do not know the number or location of signals a priori. As new imaging techniques have the potential to improve multiple-signal detection (e.g., digital breast tomosynthesis may be more effective for diagnosis of MMBC than planar mammography), image quality assessment approaches addressing such tasks are needed. In this study, we present a model-observer mechanism to detect multiple signals in the same image dataset. To handle the high dimensionality of images, a novel implementation of partial least squares (PLS) was developed to estimate different sets of efficient channels directly from the images. Without any prior knowledge of the background or the signals, the PLS channels capture interactions between signals and the background which provide discriminant image information. Corresponding linear decision templates are employed to generate both image-level and location-specific scores on the presence of signals. Our preliminary results show that the model observer using PLS channels, compared to our first attempts with Laguerre-Gauss channels, can achieve high performance with a reasonably small number of channels, and the optimal design of the model observer may vary as the tasks of clinical interest change.

  12. Robust cardiac event change detection method for long-term healthcare monitoring applications.

    PubMed

    Satija, Udit; Ramkumar, Barathram; Manikandan, M Sabarimalai

    2016-06-01

    A long-term continuous cardiac health monitoring system highly demands more battery power for real-time transmission of electrocardiogram (ECG) signals and increases bandwidth, treatment costs and traffic load of the diagnostic server. In this Letter, the authors present an automated low-complexity robust cardiac event change detection (CECD) method that can continuously detect specific changes in PQRST morphological patterns and heart rhythms and then enable transmission/storing of the recorded ECG signals. The proposed CECD method consists of four stages: ECG signal quality assessment, R-peak detection and beat waveform extraction, temporal and RR interval feature extraction and cardiac event change decision. The proposed method is tested and validated using both normal and abnormal ECG signals including different types of arrhythmia beats, heart rates and signal quality. Results show that the method achieves an average sensitivity of 99.76%, positive predictivity of 94.58% and overall accuracy of 94.32% in determining the changes in heartbeat waveforms of the ECG signals.

  13. An Automated Visual Event Detection System for Cabled Observatory Video

    NASA Astrophysics Data System (ADS)

    Edgington, D. R.; Cline, D. E.; Mariette, J.

    2007-12-01

    The permanent presence of underwater cameras on oceanic cabled observatories, such as the Victoria Experimental Network Under the Sea (VENUS) and Eye-In-The-Sea (EITS) on Monterey Accelerated Research System (MARS), will generate valuable data that can move forward the boundaries of understanding the underwater world. However, sightings of underwater animal activities are rare, resulting in the recording of many hours of video with relatively few events of interest. The burden of video management and analysis often requires reducing the amount of video recorded and later analyzed. Sometimes enough human resources do not exist to analyze the video; the strains on human attention needed to analyze video demand an automated way to assist in video analysis. Towards this end, an Automated Visual Event Detection System (AVED) is in development at the Monterey Bay Aquarium Research Institute (MBARI) to address the problem of analyzing cabled observatory video. Here we describe the overall design of the system to process video data and enable science users to analyze the results. We present our results analyzing video from the VENUS observatory and test data from EITS deployments. This automated system for detecting visual events includes a collection of custom and open source software that can be run three ways: through a Web Service, through a Condor managed pool of AVED enabled compute servers, or locally on a single computer. The collection of software also includes a graphical user interface to preview or edit detected results and to setup processing options. To optimize the compute-intensive AVED algorithms, a parallel program has been implemented for high-data rate applications like the EITS instrument on MARS.

  14. Detection of abnormalities in tissues equivalent phantoms by multi-probe laser reflectometry

    NASA Astrophysics Data System (ADS)

    Pandian, P. S.; Kumaravel, M.; Singh, Megha

    2007-07-01

    The optical parameters of tissue-equivalent phantoms are determined by matching the normalized backscattering intensity (NBI) profiles iteratively with that obtained by Monte Carlo simulation procedure. Tissue equivalent optical phantoms (control and with abnormality) were prepared by mixing measured quantities of paraffin wax with wax colors. Abnormalities to be placed in the phantoms were prepared by controlling the absorption and scattering coefficients. The NBI profiles of the phantoms are obtained by an automatic non-contact scanning multi-probe laser reflectometer and are displayed as gray level images after processing. The NBI variations from the abnormality phantoms have distinct variations based on the optical characteristics of the abnormality embedded at various locations and depths. There is a considerable decrease or increase in the NBI variations for different detector probes based on the increase or decrease in absorption and scattering coefficients of abnormalities, respectively. From the profile of subtracted image the peak corresponds to the location of the abnormality and from the full width at half maximum the size of the abnormality is obtained. By further scanning of the image of the phantom with abnormality the depth of the embedded abnormality is obtained.

  15. The waveform correlation event detection system global prototype software design

    SciTech Connect

    Beiriger, J.I.; Moore, S.G.; Trujillo, J.R.; Young, C.J.

    1997-12-01

    The WCEDS prototype software system was developed to investigate the usefulness of waveform correlation methods for CTBT monitoring. The WCEDS prototype performs global seismic event detection and has been used in numerous experiments. This report documents the software system design, presenting an overview of the system operation, describing the system functions, tracing the information flow through the system, discussing the software structures, and describing the subsystem services and interactions. The effectiveness of the software design in meeting project objectives is considered, as well as opportunities for code refuse and lessons learned from the development process. The report concludes with recommendations for modifications and additions envisioned for regional waveform-correlation-based detector.

  16. Multidimensional morphometric 3D MRI analyses for detecting brain abnormalities in children: impact of control population.

    PubMed

    Wilke, Marko; Rose, Douglas F; Holland, Scott K; Leach, James L

    2014-07-01

    Automated morphometric approaches are used to detect epileptogenic structural abnormalities in 3D MR images in adults, using the variance of a control population to obtain z-score maps in an individual patient. Due to the substantial changes the developing human brain undergoes, performing such analyses in children is challenging. This study investigated six features derived from high-resolution T1 datasets in four groups: normal children (1.5T or 3T data), normal clinical scans (3T data), and patients with structural brain lesions (3T data), with each n = 10. Normative control data were obtained from the NIH study on normal brain development (n = 401). We show that control group size substantially influences the captured variance, directly impacting the patient's z-scores. Interestingly, matching on gender does not seem to be beneficial, which was unexpected. Using data obtained at higher field scanners produces slightly different base rates of suprathreshold voxels, as does using clinically derived normal studies, suggesting a subtle but systematic effect of both factors. Two approaches for controlling suprathreshold voxels in a multidimensional approach (combining features and requiring a minimum cluster size) were shown to be substantial and effective in reducing this number. Finally, specific strengths and limitations of such an approach could be demonstrated in individual cases. PMID:25050423

  17. NHANES III: influence of race on GFR thresholds and detection of metabolic abnormalities.

    PubMed

    Foley, Robert N; Wang, Changchun; Ishani, Areef; Collins, Allan J

    2007-09-01

    Whether the creatinine-based glomerular filtration rate (GFR) thresholds used to define chronic kidney disease (CKD) identify metabolic abnormalities similarly in minority and nonminority populations is unknown. We addressed this question among adult participants in the Third National Health and Nutrition Examination Survey (NHANES III) (n = 15,837). GFR was estimated from serum creatinine values and metabolic abnormalities were defined by 5th or 95th percentile values. After adjustment for age, demographic characteristics, and GFR, black participants were significantly more likely than white participants to have abnormal levels of systolic and diastolic blood pressure, hemoglobin, phosphorus, and uric acid. Hispanic subjects were significantly more likely to have abnormal levels of systolic blood pressure, hemoglobin, bicarbonate, and phosphorus. Among participants with GFR < 60 mL/min per 1.73 m(2), black participants were significantly more likely to have abnormal levels of systolic and diastolic blood pressure, hemoglobin, and uric acid; Hispanic subjects were significantly more likely to have abnormal systolic blood pressure levels. Metabolic abnormalities were more common in minority populations, and low GFR appeared to have a multiplicative effect. Defining CKD using a single GFR threshold may be disadvantageous for minority populations because metabolic abnormalities are present at higher levels of GFR.

  18. Fluorescence in situ hybridization of TP53 for the detection of chromosome 17 abnormalities in myelodysplastic syndromes.

    PubMed

    Sánchez-Castro, Judit; Marco-Betés, Víctor; Gómez-Arbonés, Xavier; García-Cerecedo, Tomás; López, Ricard; Talavera, Elisabeth; Fernández-Ruiz, Sara; Ademà, Vera; Marugan, Isabel; Luño, Elisa; Sanzo, Carmen; Vallespí, Teresa; Arenillas, Leonor; Marco Buades, Josefa; Batlle, Ana; Buño, Ismael; Martín Ramos, María Luisa; Blázquez Rios, Beatriz; Collado Nieto, Rosa; Vargas, Ma Teresa; González Martínez, Teresa; Sanz, Guillermo; Solé, Francesc

    2015-01-01

    Conventional G-banding cytogenetics (CC) detects chromosome 17 (chr17) abnormalities in 2% of patients with de novo myelodysplastic syndromes (MDS). We used CC and fluorescence in situ hybridization (FISH) (LSI p53/17p13.1) to assess deletion of 17p in 531 patients with de novo MDS from the Spanish Group of Hematological Cytogenetics. FISH detected - 17 or 17p abnormalities in 13 cases (2.6%) in whom no 17p abnormalities were revealed by CC: 0.9% of patients with a normal karyotype, 0% in non-informative cytogenetics, 50% of patients with a chr17 abnormality without loss of 17p and 4.7% of cases with an abnormal karyotype not involving chr17. Our results suggest that applying FISH of 17p13 to identify the number of copies of the TP53 gene could be beneficial in patients with a complex karyotype. We recommend using FISH of 17p13 in young patients with a normal karyotype or non-informative cytogenetics, and always in isolated del(17p). PMID:25754580

  19. DASAF: An R Package for Deep Sequencing-Based Detection of Fetal Autosomal Abnormalities from Maternal Cell-Free DNA.

    PubMed

    Liu, Baohong; Tang, Xiaoyan; Qiu, Feng; Tao, Chunmei; Gao, Junhui; Ma, Mengmeng; Zhong, Tingyan; Cai, JianPing; Li, Yixue; Ding, Guohui

    2016-01-01

    Background. With the development of massively parallel sequencing (MPS), noninvasive prenatal diagnosis using maternal cell-free DNA is fast becoming the preferred method of fetal chromosomal abnormality detection, due to its inherent high accuracy and low risk. Typically, MPS data is parsed to calculate a risk score, which is used to predict whether a fetal chromosome is normal or not. Although there are several highly sensitive and specific MPS data-parsing algorithms, there are currently no tools that implement these methods. Results. We developed an R package, detection of autosomal abnormalities for fetus (DASAF), that implements the three most popular trisomy detection methods-the standard Z-score (STDZ) method, the GC correction Z-score (GCCZ) method, and the internal reference Z-score (IRZ) method-together with one subchromosome abnormality identification method (SCAZ). Conclusions. With the cost of DNA sequencing declining and with advances in personalized medicine, the demand for noninvasive prenatal testing will undoubtedly increase, which will in turn trigger an increase in the tools available for subsequent analysis. DASAF is a user-friendly tool, implemented in R, that supports identification of whole-chromosome as well as subchromosome abnormalities, based on maternal cell-free DNA sequencing data after genome mapping. PMID:27437397

  20. DASAF: An R Package for Deep Sequencing-Based Detection of Fetal Autosomal Abnormalities from Maternal Cell-Free DNA

    PubMed Central

    Tang, Xiaoyan; Qiu, Feng; Tao, Chunmei; Gao, Junhui; Ma, Mengmeng; Zhong, Tingyan; Cai, JianPing; Li, Yixue

    2016-01-01

    Background. With the development of massively parallel sequencing (MPS), noninvasive prenatal diagnosis using maternal cell-free DNA is fast becoming the preferred method of fetal chromosomal abnormality detection, due to its inherent high accuracy and low risk. Typically, MPS data is parsed to calculate a risk score, which is used to predict whether a fetal chromosome is normal or not. Although there are several highly sensitive and specific MPS data-parsing algorithms, there are currently no tools that implement these methods. Results. We developed an R package, detection of autosomal abnormalities for fetus (DASAF), that implements the three most popular trisomy detection methods—the standard Z-score (STDZ) method, the GC correction Z-score (GCCZ) method, and the internal reference Z-score (IRZ) method—together with one subchromosome abnormality identification method (SCAZ). Conclusions. With the cost of DNA sequencing declining and with advances in personalized medicine, the demand for noninvasive prenatal testing will undoubtedly increase, which will in turn trigger an increase in the tools available for subsequent analysis. DASAF is a user-friendly tool, implemented in R, that supports identification of whole-chromosome as well as subchromosome abnormalities, based on maternal cell-free DNA sequencing data after genome mapping. PMID:27437397

  1. Detecting and mitigating abnormal events in large scale networks: budget constrained placement on smart grids

    SciTech Connect

    Santhi, Nandakishore; Pan, Feng

    2010-10-19

    Several scenarios exist in the modern interconnected world which call for an efficient network interdiction algorithm. Applications are varied, including various monitoring and load shedding applications on large smart energy grids, computer network security, preventing the spread of Internet worms and malware, policing international smuggling networks, and controlling the spread of diseases. In this paper we consider some natural network optimization questions related to the budget constrained interdiction problem over general graphs, specifically focusing on the sensor/switch placement problem for large-scale energy grids. Many of these questions turn out to be computationally hard to tackle. We present a particular form of the interdiction question which is practically relevant and which we show as computationally tractable. A polynomial-time algorithm will be presented for solving this problem.

  2. Prediction models for early risk detection of cardiovascular event.

    PubMed

    Purwanto; Eswaran, Chikkannan; Logeswaran, Rajasvaran; Abdul Rahman, Abdul Rashid

    2012-04-01

    Cardiovascular disease (CVD) is the major cause of death globally. More people die of CVDs each year than from any other disease. Over 80% of CVD deaths occur in low and middle income countries and occur almost equally in male and female. In this paper, different computational models based on Bayesian Networks, Multilayer Perceptron,Radial Basis Function and Logistic Regression methods are presented to predict early risk detection of the cardiovascular event. A total of 929 (626 male and 303 female) heart attack data are used to construct the models.The models are tested using combined as well as separate male and female data. Among the models used, it is found that the Multilayer Perceptron model yields the best accuracy result.

  3. Detecting Rare Events in the Time-Domain

    SciTech Connect

    Rest, A; Garg, A

    2008-10-31

    One of the biggest challenges in current and future time-domain surveys is to extract the objects of interest from the immense data stream. There are two aspects to achieving this goal: detecting variable sources and classifying them. Difference imaging provides an elegant technique for identifying new transients or changes in source brightness. Much progress has been made in recent years toward refining the process. We discuss a selection of pitfalls that can afflict an automated difference imagine pipeline and describe some solutions. After identifying true astrophysical variables, we are faced with the challenge of classifying them. For rare events, such as supernovae and microlensing, this challenge is magnified because we must balance having selection criteria that select for the largest number of objects of interest against a high contamination rate. We discuss considerations and techniques for developing classification schemes.

  4. Efficient hemodynamic event detection utilizing relational databases and wavelet analysis

    NASA Technical Reports Server (NTRS)

    Saeed, M.; Mark, R. G.

    2001-01-01

    Development of a temporal query framework for time-oriented medical databases has hitherto been a challenging problem. We describe a novel method for the detection of hemodynamic events in multiparameter trends utilizing wavelet coefficients in a MySQL relational database. Storage of the wavelet coefficients allowed for a compact representation of the trends, and provided robust descriptors for the dynamics of the parameter time series. A data model was developed to allow for simplified queries along several dimensions and time scales. Of particular importance, the data model and wavelet framework allowed for queries to be processed with minimal table-join operations. A web-based search engine was developed to allow for user-defined queries. Typical queries required between 0.01 and 0.02 seconds, with at least two orders of magnitude improvement in speed over conventional queries. This powerful and innovative structure will facilitate research on large-scale time-oriented medical databases.

  5. Identification of new events in Apollo 16 lunar seismic data by Hidden Markov Model-based event detection and classification

    NASA Astrophysics Data System (ADS)

    Knapmeyer-Endrun, Brigitte; Hammer, Conny

    2015-10-01

    Detection and identification of interesting events in single-station seismic data with little prior knowledge and under tight time constraints is a typical scenario in planetary seismology. The Apollo lunar seismic data, with the only confirmed events recorded on any extraterrestrial body yet, provide a valuable test case. Here we present the application of a stochastic event detector and classifier to the data of station Apollo 16. Based on a single-waveform example for each event class and some hours of background noise, the system is trained to recognize deep moonquakes, impacts, and shallow moonquakes and performs reliably over 3 years of data. The algorithm's demonstrated ability to detect rare events and flag previously undefined signal classes as new event types is of particular interest in the analysis of the first seismic recordings from a completely new environment. We are able to classify more than 50% of previously unclassified lunar events, and additionally find over 200 new events not listed in the current lunar event catalog. These events include deep moonquakes as well as impacts and could be used to update studies on temporal variations in event rate or deep moonquakes stacks used in phase picking for localization. No unambiguous new shallow moonquake was detected, but application to data of the other Apollo stations has the potential for additional new discoveries 40 years after the data were recorded. Besides, the classification system could be useful for future seismometer missions to other planets, e.g., the InSight mission to Mars.

  6. Barometric pressure and triaxial accelerometry-based falls event detection.

    PubMed

    Bianchi, Federico; Redmond, Stephen J; Narayanan, Michael R; Cerutti, Sergio; Lovell, Nigel H

    2010-12-01

    Falls and fall related injuries are a significant cause of morbidity, disability, and health care utilization, particularly among the age group of 65 years and over. The ability to detect falls events in an unsupervised manner would lead to improved prognoses for falls victims. Several wearable accelerometry and gyroscope-based falls detection devices have been described in the literature; however, they all suffer from unacceptable false positive rates. This paper investigates the augmentation of such systems with a barometric pressure sensor, as a surrogate measure of altitude, to assist in discriminating real fall events from normal activities of daily living. The acceleration and air pressure data are recorded using a wearable device attached to the subject's waist and analyzed offline. The study incorporates several protocols including simulated falls onto a mattress and simulated activities of daily living, in a cohort of 20 young healthy volunteers (12 male and 8 female; age: 23.7 ±3.0 years). A heuristically trained decision tree classifier is used to label suspected falls. The proposed system demonstrated considerable improvements in comparison to an existing accelerometry-based technique; showing an accuracy, sensitivity and specificity of 96.9%, 97.5%, and 96.5%, respectively, in the indoor environment, with no false positives generated during extended testing during activities of daily living. This is compared to 85.3%, 75%, and 91.5% for the same measures, respectively, when using accelerometry alone. The increased specificity of this system may enhance the usage of falls detectors among the elderly population.

  7. Event Detection and Spatial Analysis for Characterizing Extreme Precipitation

    NASA Astrophysics Data System (ADS)

    Jeon, S.; Prabhat, M.; Byna, S.; Collins, W.; Wehner, M. F.

    2013-12-01

    Atmospheric Rivers (ARs) are large spatially coherent weather systems with high concentrations of elevated water vapor that often cause severe downpours and flooding over western coastal United States. With the availability of more atmospheric moisture in the future under global warming, we expect ARs to play an important role as a potential cause of extreme precipitation. We have recently developed TECA software for automatically identifying and tracking features in climate datasets. In particular, we are able to identify ARs that make landfall on the western coast of North America. This detection tool examines integrated water vapor field above a certain threshold and performs geometric analysis. Based on the detection procedure, we investigate impacts of ARs by exploring spatial extent of AR precipitation for CMIP5 simulations, and characterize spatial pattern of dependence for future projections under climate change within the framework of extreme value theory. The results show that AR events in RCP8.5 scenario (2076-2100) tend to produce heavier rainfall with higher frequency and longer duration than the events from historical run (1981-2005). Range of spatial dependence between extreme precipitations is concentrated on smaller localized area in California under the highest emission scenario than present day. Preliminary results are illustrated in Figure 1 and 2. Fig 1: Boxplot of annual max precipitation (left two) and max AR precipitation (right two) from GFDL-ESM2M during 25-year time period by station in California, US. Fig 2: Spatial dependence of max AR precipitation calculated from Station 4 (triangle) for historical run (left) and for future projections of RCP8.5 (right) from GFDL-ESM2M. Green and orange colors represent complete dependence and independence between two stations respectively.

  8. Barometric pressure and triaxial accelerometry-based falls event detection.

    PubMed

    Bianchi, Federico; Redmond, Stephen J; Narayanan, Michael R; Cerutti, Sergio; Lovell, Nigel H

    2010-12-01

    Falls and fall related injuries are a significant cause of morbidity, disability, and health care utilization, particularly among the age group of 65 years and over. The ability to detect falls events in an unsupervised manner would lead to improved prognoses for falls victims. Several wearable accelerometry and gyroscope-based falls detection devices have been described in the literature; however, they all suffer from unacceptable false positive rates. This paper investigates the augmentation of such systems with a barometric pressure sensor, as a surrogate measure of altitude, to assist in discriminating real fall events from normal activities of daily living. The acceleration and air pressure data are recorded using a wearable device attached to the subject's waist and analyzed offline. The study incorporates several protocols including simulated falls onto a mattress and simulated activities of daily living, in a cohort of 20 young healthy volunteers (12 male and 8 female; age: 23.7 ±3.0 years). A heuristically trained decision tree classifier is used to label suspected falls. The proposed system demonstrated considerable improvements in comparison to an existing accelerometry-based technique; showing an accuracy, sensitivity and specificity of 96.9%, 97.5%, and 96.5%, respectively, in the indoor environment, with no false positives generated during extended testing during activities of daily living. This is compared to 85.3%, 75%, and 91.5% for the same measures, respectively, when using accelerometry alone. The increased specificity of this system may enhance the usage of falls detectors among the elderly population. PMID:20805056

  9. Detecting Tidal Disruption Events (TDEs) with the Einstein Probe

    NASA Astrophysics Data System (ADS)

    Yuan, W.; Komossa, S.; Zhang, C.; Feng, H.; Zhang, S.; Osborne, J.; O'Brien, P.; Watson, M.; Fraser, G.

    2014-07-01

    Stars are tidally disrupted and accreted when they approach supermassive black holes (SMBHs) closely, producing a flare of electromagnetic radiation. The majority of the (approximately two dozen) tidal disruption events (TDEs) identified so far have been discovered by their luminous, transient X-ray emission. Once TDEs are detected in much larger numbers, in future dedicated transient surveys, a wealth of new applications will become possible. Including (1) TDE rate measurements in dependence of host galaxy types, (2) an assessment of the population of IMBHs, and (3) new probes of general relativity and accretion processes. Here, we present the proposed X-ray mission Einstein Probe}, which aims at detecting TDEs in large numbers. The mission consists of a wide-field micro-pore Lobster-eye imager (60deg x 60deg, or ˜1 ster), and is designed to carry out an all-sky transient survey at energies of 0.5-4 keV. It will also carry an X-ray telescope of the same micro-pore optics for follow-ups, with a smaller field-of-view. It will be capable of issuing public transient alerts rapidly.

  10. Communication of ALS Patients by Detecting Event-Related Potential

    NASA Astrophysics Data System (ADS)

    Kanou, Naoyuki; Sakuma, Kenji; Nakashima, Kenji

    Amyotrophic Lateral Sclerosis(ALS) patients are unable to successfully communicate their desires, although their mental capacity is the same as non-affected persons. Therefore, the authors put emphasis on Event-Related Potential(ERP) which elicits the highest outcome for the target visual and hearing stimuli. P300 is one component of ERP. It is positive potential that is elicited when the subject focuses attention on stimuli that appears infrequently. In this paper, the authors focused on P200 and N200 components, in addition to P300, for their great improvement in the rate of correct judgment in the target word-specific experiment. Hence the authors propose the algorithm that specifies target words by detecting these three components. Ten healthy subjects and ALS patient underwent the experiment in which a target word out of five words, was specified by this algorithm. The rates of correct judgment in nine of ten healthy subjects were more than 90.0%. The highest rate was 99.7%. The highest rate of ALS patient was 100.0%. Through these results, the authors found the possibility that ALS patients could communicate with surrounding persons by detecting ERP(P200, N200 and P300) as their desire.

  11. Treadmill exercise tests predischarge and six weeks post-myocardial infarction to detect abnormalities of known prognostic value.

    PubMed

    Starling, M R; Crawford, M H; Kennedy, G T; O'Rourke, R A

    1981-06-01

    We evaluated 89 patients with predischarge and 6-week post-myocardial infarction treadmill exercise tests to determine the importance of doing repeat tests to identify abnormalities of known prognostic value, and assess the individual variability of treadmill abnormality responses. Nineteen patients (21%) completed only a predischarge exercise test, nine of whom experienced an early cardiac event precluding repeat testing. All nine had a prognostically important treadmill abnormality during the predischarge test. Electrocardiographic ST segment depression was highly reproducible between the early and 6-week tests (k = 0.968). However, angina, inadequate blood pressure response, and ventricular arrhythmias showed limited reproducibility (k = 0.344, 0.50, and 0.166, respectively) and substantial individual variability. Thus, we concluded that: a predischarge treadmill exercise test is important for determining the immediate short-term prognosis of patients after myocardial infarction; and ST segment depression is highly reproducible, whereas other treadmill abnormality responses show substantial variability between the predischarge and 6-week tests.

  12. Rare-event detection and process control for a biomedical application

    NASA Astrophysics Data System (ADS)

    Kegelmeyer, Laura N.

    1990-05-01

    Medical researchers are seeking a method for detecting chromosomal abnormalities in unborn children without requiring invasive procedures such as anmiocentesis. Software has been developed to utilize a light microscope to detect fetal cells that occur with very low frequency in a sample of maternal blood. This rare event detection involves dividing a microscope slide containing a maternal blood sample into as many as 40,000 fields, automatically focusing on each field-of-view, and searching for fetal cells. Size and shape information is obtained by calculating a figure of merit through various binary operations and is used to discriminate fetal cells from noise and artifacts. Once the rare fetal cells are located, the slide is automatically rescanned to count the total number of cells on the slide. Binary operations and image processing hardware are used as much as possible to reduce the total amount of time to analyze one slide. Current runtime for scoring one full slide is about four hours, with motorized stage movement and focusing being the speed-limiting factors. Fetal cells occurring with a frequency of less than 1 in 200,000 maternal cells have been consistently found with this system.

  13. Apparatus and method for detecting full-capture radiation events

    DOEpatents

    Odell, Daniel M. C.

    1994-01-01

    An apparatus and method for sampling the output signal of a radiation detector and distinguishing full-capture radiation events from Compton scattering events. The output signal of a radiation detector is continuously sampled. The samples are converted to digital values and input to a discriminator where samples that are representative of events are identified. The discriminator transfers only event samples, that is, samples representing full-capture events and Compton events, to a signal processor where the samples are saved in a three-dimensional count matrix with time (from the time of onset of the pulse) on the first axis, sample pulse current amplitude on the second axis, and number of samples on the third axis. The stored data are analyzed to separate the Compton events from full-capture events, and the energy of the full-capture events is determined without having determined the energies of any of the individual radiation detector events.

  14. Apparatus and method for detecting full-capture radiation events

    DOEpatents

    Odell, D.M.C.

    1994-10-11

    An apparatus and method are disclosed for sampling the output signal of a radiation detector and distinguishing full-capture radiation events from Compton scattering events. The output signal of a radiation detector is continuously sampled. The samples are converted to digital values and input to a discriminator where samples that are representative of events are identified. The discriminator transfers only event samples, that is, samples representing full-capture events and Compton events, to a signal processor where the samples are saved in a three-dimensional count matrix with time (from the time of onset of the pulse) on the first axis, sample pulse current amplitude on the second axis, and number of samples on the third axis. The stored data are analyzed to separate the Compton events from full-capture events, and the energy of the full-capture events is determined without having determined the energies of any of the individual radiation detector events. 4 figs.

  15. Balloon-Borne Infrasound Detection of Energetic Bolide Events

    NASA Astrophysics Data System (ADS)

    Young, Eliot F.; Ballard, Courtney; Klein, Viliam; Bowman, Daniel; Boslough, Mark

    2016-10-01

    Infrasound is usually defined as sound waves below 20 Hz, the nominal limit of human hearing. Infrasound waves propagate over vast distances through the Earth's atmosphere: the CTBTO (Comprehensive Nuclear-Test-Ban Treaty Organization) has 48 installed infrasound-sensing stations around the world to detect nuclear detonations and other disturbances. In February 2013, several CTBTO infrasound stations detected infrasound signals from a large bolide that exploded over Chelyabinsk, Russia. Some stations recorded signals that had circumnavigated the Earth, over a day after the original event. The goal of this project is to improve upon the sensitivity of the CTBTO network by putting microphones on small, long-duration super-pressure balloons, with the overarching goal of studying the small end of the NEO population by using the Earth's atmosphere as a witness plate.A balloon-borne infrasound sensor is expected to have two advantages over ground-based stations: a lack of wind noise and a concentration of infrasound energy in the "stratospheric duct" between roughly 5 - 50 km altitude. To test these advantages, we have built a small balloon payload with five calibrated microphones. We plan to fly this payload on a NASA high-altitude balloon from Ft Sumner, NM in August 2016. We have arranged for three large explosions to take place in Socorro, NM while the balloon is aloft to assess the sensitivity of balloon-borne vs. ground-based infrasound sensors. We will report on the results from this test flight and the prospects for detecting/characterizing small bolides in the stratosphere.

  16. Automatic detection of volcano-seismic events by modeling state and event duration in hidden Markov models

    NASA Astrophysics Data System (ADS)

    Bhatti, Sohail Masood; Khan, Muhammad Salman; Wuth, Jorge; Huenupan, Fernando; Curilem, Millaray; Franco, Luis; Yoma, Nestor Becerra

    2016-09-01

    In this paper we propose an automatic volcano event detection system based on Hidden Markov Model (HMM) with state and event duration models. Since different volcanic events have different durations, therefore the state and whole event durations learnt from the training data are enforced on the corresponding state and event duration models within the HMM. Seismic signals from the Llaima volcano are used to train the system. Two types of events are employed in this study, Long Period (LP) and Volcano-Tectonic (VT). Experiments show that the standard HMMs can detect the volcano events with high accuracy but generates false positives. The results presented in this paper show that the incorporation of duration modeling can lead to reductions in false positive rate in event detection as high as 31% with a true positive accuracy equal to 94%. Further evaluation of the false positives indicate that the false alarms generated by the system were mostly potential events based on the signal-to-noise ratio criteria recommended by a volcano expert.

  17. Sonic Hedgehog: A Good Gene Gone Bad? Detection and Treatment of Genetic Abnormalities.

    ERIC Educational Resources Information Center

    Yaich, Lauren E.

    2001-01-01

    Presents a case of a baby born with the genetic condition holoprosencephaly in which students explore the "Sonic hedgehog" gene, signal transduction, and the ethics of body and tissue donation. Presents a two-part assignment that features students writing an informed consent document that explains the science behind this congenital abnormality,…

  18. Detection of Local/Regional Events in Kuwait Using Next-Generation Detection Algorithms

    SciTech Connect

    Gok, M. Rengin; Al-Jerri, Farra; Dodge, Douglas; Al-Enezi, Abdullah; Hauk, Terri; Mellors, R.

    2014-12-10

    Seismic networks around the world use conventional triggering algorithms to detect seismic signals in order to locate local/regional seismic events. Kuwait National Seismological Network (KNSN) of Kuwait Institute of Scientific Research (KISR) is operating seven broad-band and short-period three-component stations in Kuwait. The network is equipped with Nanometrics digitizers and uses Antelope and Guralp acquisition software for processing and archiving the data. In this study, we selected 10 days of archived hourly-segmented continuous data of five stations (Figure 1) and 250 days of continuous recording at MIB. For the temporary deployment our selection criteria was based on KNSN catalog intensity for the period of time we test the method. An autonomous event detection and clustering framework is employed to test a more complete catalog of this short period of time. The goal is to illustrate the effectiveness of the technique and pursue the framework for longer period of time.

  19. Using REDItools to Detect RNA Editing Events in NGS Datasets.

    PubMed

    Picardi, Ernesto; D'Erchia, Anna Maria; Montalvo, Antonio; Pesole, Graziano

    2015-03-09

    RNA editing is a post-transcriptional/co-transcriptional molecular phenomenon whereby a genetic message is modified from the corresponding DNA template by means of substitutions, insertions, and/or deletions. It occurs in a variety of organisms and different cellular locations through evolutionally and biochemically unrelated proteins. RNA editing has a plethora of biological effects including the modulation of alternative splicing and fine-tuning of gene expression. RNA editing events by base substitutions can be detected on a genomic scale by NGS technologies through the REDItools package, an ad hoc suite of Python scripts to study RNA editing using RNA-Seq and DNA-Seq data or RNA-Seq data alone. REDItools implement effective filters to minimize biases due to sequencing errors, mapping errors, and SNPs. The package is freely available at Google Code repository (http://code.google.com/p/reditools/) and released under the MIT license. In the present unit we show three basic protocols corresponding to three main REDItools scripts.

  20. Solar activity cycle and the incidence of foetal chromosome abnormalities detected at prenatal diagnosis

    NASA Astrophysics Data System (ADS)

    Halpern, Gabrielle J.; Stoupel, Eliahu G.; Barkai, Gad; Chaki, Rina; Legum, Cyril; Fejgin, Moshe D.; Shohat, Mordechai

    1995-06-01

    We studied 2001 foetuses during the period of minimal solar activity of solar cycle 21 and 2265 foetuses during the period of maximal solar activity of solar cycle 22, in all women aged 37 years and over who underwent free prenatal diagnosis in four hospitals in the greater Tel Aviv area. There were no significant differences in the total incidence of chromosomal abnormalities or of trisomy between the two periods (2.15% and 1.8% versus 2.34% and 2.12%, respectively). However, the trend of excessive incidence of chromosomal abnormalities in the period of maximal solar activity suggests that a prospective study in a large population would be required to rule out any possible effect of extreme solar activity.

  1. Video Event Detection: From Subvolume Localization To Spatio-Temporal Path Search.

    PubMed

    Tran, Du; Yuan, Junsong; Forsyth, David

    2013-07-23

    Although sliding window-based approaches have been quite successful in detecting objects in images, it is not a trivial problem to extend them to detecting events in videos. We propose to search for spatio-temporal paths for video event detection. This new formulation can accurately detect and locate video events in cluttered and crowded scenes, and is robust to camera motions. It can also well handle the scale, shape, and intra-class variations of the event. Compared to event detection using spatio-temporal sliding windows, the spatio-temporal paths correspond to the event trajectories in the video space, thus can better handle events composed by moving objects. We prove that the proposed search algorithm can achieve the global optimal solution with the lowest complexity. Experiments are conducted on realistic video datasets with different event detection tasks, such as anomaly event detection, walking person detection, and running detection. Our proposed method is compatible to different types of video features or object detectors and robust to false and missed local detections. It significantly improves the overall detection and localization accuracy over the state-of-the-art methods. PMID:23898011

  2. Usefulness of noninvasive detection of left ventricular diastolic abnormalities during isometric stress in hypertrophic cardiomyopathy and in athletes.

    PubMed

    Manolas, J; Kyriakidis, M; Anastasakis, A; Pegas, P; Rigopoulos, A; Theopistou, A; Toutouzas, P

    1998-02-01

    We showed previously that the handgrip apexcardiographic test (HAT) is a useful method for detecting left ventricular (LV) diastolic abnormalities in patients with coronary artery disease and systemic hypertension. This study evaluates the use of HAT for assessing the prevalence and types of exercise-induced diastolic abnormalities in patients with obstructive (n = 31) and nonobstructive (n = 35) hypertrophic cardiomyopathy (HC) as well as its potential value for separating healthy subjects and athletes from patients with HC. We obtained a HAT in 66 consecutive patients with HC and in 72 controls (52 healthy volunteers and 20 athletes). A positive HAT was defined by the presence of one of the following: (1) relative A wave to total height (A/H) during or after handgrip > 21% (compliance type), (2) total apexcardiographic relaxation time (TART) > 143 ms or the heart rate corrected TART (TARTI) during handgrip < 0.14, (relaxation type), (3) both types present (mixed type), and (4) diastolic amplitude time index (DATI = TARTI/[A/D]) during handgrip < 0.27. Of the controls, only 1 of 52 healthy subjects and 1 of 20 athletes showed a positive HAT, whereas of the total HC cohort 63 of 66 patients (95%) had a positive result. There was no significant difference in the distribution of these types between obstructive and nonobstructive HC. Further, no LV diastolic abnormalities were present in 10 of 35 patients (29%) with nonobstructive HC at rest and in 3 of 35 patients (9%) during handgrip, whereas of the patients with obstructive HC only 1 of 31 (3%) had no LV diastolic abnormalities at rest and none during handgrip. Based on HAT data, our study demonstrates that in HC (1) LV diastolic abnormalities are very frequent during handgrip; (2) patients with nonobstructive HC show significantly fewer LV diastolic abnormalities at rest than those with obstructive HC; and (3) no significant difference exists between obstructive and nonobstructive HC in the prevalence of types of

  3. Large Time Projection Chambers for Rare Event Detection

    SciTech Connect

    Heffner, M

    2009-11-03

    The Time Projection Chamber (TPC) concept [add ref to TPC section] has been applied to many projects outside of particle physics and the accelerator based experiments where it was initially developed. TPCs in non-accelerator particle physics experiments are principally focused on rare event detection (e.g. neutrino and darkmater experiments) and the physics of these experiments can place dramatically different constraints on the TPC design (only extensions to the traditional TPCs are discussed here). The drift gas, or liquid, is usually the target or matter under observation and due to very low signal rates a TPC with the largest active mass is desired. The large mass complicates particle tracking of short and sometimes very low energy particles. Other special design issues include, efficient light collection, background rejection, internal triggering and optimal energy resolution. Backgrounds from gamma-rays and neutrons are significant design issues in the construction of these TPCs. They are generally placed deep underground to shield from cosmogenic particles and surrounded with shielding to reduce radiation from the local surroundings. The construction materials have to be carefully screened for radiopurity as they are in close contact with the active mass and can be a signification source of background events. The TPC excels in reducing this internal background because the mass inside the fieldcage forms one monolithic volume from which fiducial cuts can be made ex post facto to isolate quiet drift mass, and can be circulated and purified to a very high level. Self shielding in these large mass systems can be significant and the effect improves with density. The liquid phase TPC can obtain a high density at low pressure which results in very good self-shielding and compact installation with a lightweight containment. The down sides are the need for cryogenics, slower charge drift, tracks shorter than the typical electron diffusion, lower energy resolution (e

  4. Wavelet analysis applied to the detection of abnormal ICE exhaust noise

    NASA Astrophysics Data System (ADS)

    Ayadi, M.; Frikha, S.; Hennion, P. Y.

    2000-07-01

    The "Rasping Noise" is an abnormal exhaust noise that occurs in small cars equipped with two boxes exhaust systems. It is an intermittent metallic noise that irritates the ear because of its high frequency components. It occurs during rapid acceleration or deceleration in cold conditions. Pressure signals are picked up in a critical exhaust line at Rasping conditions. Order and wavelet analysis are found to be efficient and completing tools in studying an eventual occurrence of discontinuities or shock waves in such a critical exhaust line.

  5. Detection of structural and numerical chomosomal abnormalities by ACM-FISH analysis in sperm of oligozoospermic infertility patients

    SciTech Connect

    Schmid, T E; Brinkworth, M H; Hill, F; Sloter, E; Kamischke, A; Marchetti, F; Nieschlag, E; Wyrobek, A J

    2003-11-10

    Modern reproductive technologies are enabling the treatment of infertile men with severe disturbances of spermatogenesis. The possibility of elevated frequencies of genetically and chromosomally defective sperm has become an issue of concern with the increased usage of intracytoplasmic sperm injection (ICSI), which can enable men with severely impaired sperm production to father children. Several papers have been published about aneuploidy in oligozoospermic patients, but relatively little is known about chromosome structural aberrations in the sperm of these patients. We examined sperm from infertile, oligozoospermic individuals for structural and numerical chromosomal abnormalities using a multicolor ACM FISH assay that utilizes DNA probes specific for three regions of chromosome 1 to detect human sperm that carry numerical chromosomal abnormalities plus two categories of structural aberrations: duplications and deletions of 1pter and 1cen, and chromosomal breaks within the 1cen-1q12 region. There was a significant increase in the average frequencies of sperm with duplications and deletions in the infertility patients compared with the healthy concurrent controls. There was also a significantly elevated level of breaks within the 1cen-1q12 region. There was no evidence for an increase in chromosome-1 disomy, or in diploidy. Our data reveal that oligozoospermia is associated with chromosomal structural abnormalities suggesting that, oligozoospermic men carry a higher burden of transmissible, chromosome damage. The findings raise the possibility of elevated levels of transmissible chromosomal defects following ICSI treatment.

  6. Usefulness of screening cardiovascular magnetic resonance imaging to detect aortic abnormalities after repair of coarctation of the aorta.

    PubMed

    Tsai, Shane F; Trivedi, Mira; Boettner, Bethany; Daniels, Curt J

    2011-01-15

    Guidelines recommend screening cardiovascular magnetic resonance (Sc-CMR) imaging for all patients after coarctation of the aorta repair, although there are limited data verifying its clinical utility. Therefore, we sought to assess the value of Sc-CMR in detecting aortic complications and at-risk abnormalities after coarctation of the aorta repair and to identify significant risk factors. We reviewed 76 patients (mean age 31 ± 10 years), including 40 with symptomatically indicated CMR (Sx-CMR) and 36 with Sc-CMR studies. CMR angiograms were evaluated for aortic abnormalities. Recoarctation was defined as residual narrowing/descending aorta at the diaphragm ≤0.5 (at risk ≤0.75), ascending aorta aneurysm as maximum ascending cross-sectional area/height ≥10 (at risk ≥5), and descending aorta aneurysm as maximum descending diameter/descending aorta at the diaphragm ≥1.5 (at risk ≥1.25). Aortic complications or abnormalities were found in 45 patients (59%). No patient met criteria for recoarctation (at risk 10 Sx-CMR vs 5 Sc-CMR). Significant risk factors included heart failure symptoms and female gender (p <0.05). One patient (Sc-CMR) had ascending aneurysm (at risk 17 Sx-CMR vs 8 Sc-CMR). Time from repair was a significant predictor (p <0.05). There were 10 patients (6 Sx-CMR vs 4 Sc-CMR) with descending aneurysm (at risk 8 Sx-CMR vs 7 Sc-CMR). Cardiovascular symptoms, hypertension, and echocardiogram were not predictive. In conclusion, >50% of patients undergoing Sc-CMR had aortic abnormalities, which was not significantly different from those undergoing Sx-CMR. In particular, Sc-CMR identified descending aorta aneurysms that were not predicted by clinical parameters or echocardiogram.

  7. A neural network learned information measures for heart motion abnormality detection

    NASA Astrophysics Data System (ADS)

    Nambakhsh, M. S.; Punithakumar, Kumaradevan; Ben Ayed, Ismail; Goela, Aashish; Islam, Ali; Peters, Terry; Li, Shuo

    2011-03-01

    In this study, we propose an information theoretic neural network for normal/abnormal left ventricular motion classification which outperforms significantly other recent methods in the literature. The proposed framework consists of a supervised 3-layer artificial neural network (ANN) which uses hyperbolic tangent sigmoid and linear transfer functions for hidden and output layers, respectively. The ANN is fed by information theoretic measures of left ventricular wall motion such as Shannon's differential entropy (SDE), Rényi entropy and Fisher information, which measure global information of subjects distribution. Using 395×20 segmented LV cavities of short-axis magnetic resonance images (MRI) acquired from 48 subjects, the experimental results show that the proposed method outperforms Support Vector Machine (SVM) and thresholding based information theoretic classifiers. It yields a specificity equal to 90%, a sensitivity of 91%, and a remarkable Area Under Curve (AUC) for Receiver Operating Characteristic (ROC), equal to 93.2%.

  8. Functional brain abnormalities in psychiatric disorders: neural mechanisms to detect and resolve cognitive conflict and interference.

    PubMed

    Melcher, Tobias; Falkai, Peter; Gruber, Oliver

    2008-11-01

    In the present article, we review functional neuroimaging studies on interference processing and performance monitoring in three groups of psychiatric disorders, (1) mood disorders, (2) schizophrenia, and (3) obsessive-compulsive disorder (OCD). Ad (1) Behavioral performance measures suggest an impaired interference resolution capability in symptomatic bipolar disorder patients. A series of neuroimaging analyses found alterations in the ACC-DLPFC system in mood disorder (unipolar depressed and bipolar) patients, putatively reflective of an abnormal interplay of monitoring and executive neurocognitive functions. Other studies of euthymic bipolar patients showed relatively decreased interference-related activation in rostroventral PFC which conceivably underlies defective inhibitory control. Ad (2) Behavioral Stroop studies revealed a specific performance pattern of schizophrenia patients (normal RT interference but increased error interference and RT facilitation) suggestive of a deficit in ignoring irrelevant (word) information. Moreover, reduced/absent behavioral post-error and post-conflict adaptation effects suggest alterations in performance monitoring and/or adjustment capability in these patients. Neuroimaging findings converge to suggest a disorder-related abnormal neurophysiology in ACC which consistently showed conflict- and error-related hypoactivation that, however, appeared to be modulated by different factors. Moreover, studies suggest a specific deficit in context processing in schizophrenia, evidently related to activation reduction in DLPFC. Ad (3) Behavioral findings provide evidence for impaired interference resolution in OCD. Neuroimaging results consistently showed conflict- and error-related ACC hyperactivation which--conforming OCD pathogenesis models--can be conclusively interpreted as reflecting overactive performance monitoring. Taken together, interference resolution and performance monitoring appeared to be fruitful concepts in the

  9. Interrelationships between postpartum events, hormonal therapy, reproductive abnormalities and reproductive performance in dairy cows: a path analysis.

    PubMed Central

    Etherington, W G; Martin, S W; Dohoo, I R; Bosu, W T

    1985-01-01

    Path analysis was used to determine the interrelationships between postpartum administration of gonadotrophin releasing hormone and cloprostenol and the occurrence of reproductive disease and reproductive performance in dairy cows. The data analysed were those collected on 226 Holstein-Friesian cows calving in a commercial dairy herd during a 17 month period (May 1, 1981 to October 1, 1982). Cows administered gonadotrophin releasing hormone at day 15 postpartum experienced an improved rate of uterine involution as determined by rectal palpation nine days later. Although this improved rate of uterine involution reduced the risk of pyometritis, it actually directly delayed conception. Also, gonadotrophin releasing hormone therapy directly resulted in an increased incidence of pyometritis which in turn resulted in an increase incidence of cystic ovarian disease and anestrus. The occurrence of these abnormalities resulted in increased intervals from calving to first observed estrus, first service and conception. In addition to this effect, the administration of gonadotrophin releasing hormone was also associated with increased plasma progesterone concentrations at days 24 and 28 postpartum which delayed conception. Cloprostenol therapy at day 24 postpartum resulted in a decreased plasma progesterone concentration at day 28 postpartum which was directly and indirectly associated with a decrease in the calving to conception interval. The indirect effects were mediated by a reduction in days to first estrus. Cloprostenol therapy also directly resulted in a decreased calving to first observed estrus interval for reasons not attributable to the level of progesterone at day 28. PMID:3899335

  10. Robust algorithmic detection of the developed cardiac pathologies and emerging or transient abnormalities from short periods of RR data

    NASA Astrophysics Data System (ADS)

    Gavrishchaka, Valeriy V.; Senyukova, Olga

    2011-06-01

    Numerous research efforts and clinical testing have confirmed validity of heart rate variability (HRV) analysis as one of the cardiac diagnostics modalities. The majority of HRV analysis tools currently used in practice are based on linear indicators. Methods from nonlinear dynamics (NLD) provide more natural modeling framework for adaptive biological systems with multiple feedback loops. Compared to linear indicators, many NLD-based measures are much less sensitive to data artifacts and non-stationarity. However, majority of NLD measures require long time series for stable calculation. Similar restrictions also apply for linear indicators. Such requirements could drastically limit practical usability of HRV analysis in many applications, including express diagnostics, early indication of subtle directional changes during personalization of medical treatment, and robust detection of emerging or transient abnormalities. Recently we have illustrated that these challenges could be overcome by using classification framework based on boosting-like ensemble learning techniques that are capable of discovering robust meta-indicators from existing HRV measures and other incomplete empirical knowledge. In this paper we demonstrate universality of such meta-indicators and discuss operational details of their practical usage. Using such pathology examples as congestive heart failure (CHF) and arrhythmias, we show that classifiers trained on short RR segments (down to several minutes) could achieve reasonable classification accuracy (˜80-85% and higher). These indicators calculated from longer RR segments could be applicable for accurate diagnostics with classification accuracy approaching 100%. In addition, it is feasible to discover single "normal-abnormal" meta-classifier capable of detecting multiple abnormalities.

  11. A model of human event detection in multiple process monitoring situations

    NASA Technical Reports Server (NTRS)

    Greenstein, J. S.; Rouse, W. B.

    1978-01-01

    It is proposed that human decision making in many multi-task situations might be modeled in terms of the manner in which the human detects events related to his tasks and the manner in which he allocates his attention among his tasks once he feels events have occurred. A model of human event detection performance in such a situation is presented. An assumption of the model is that, in attempting to detect events, the human generates the probability that events have occurred. Discriminant analysis is used to model the human's generation of these probabilities. An experimental study of human event detection performance in a multiple process monitoring situation is described and the application of the event detection model to this situation is addressed. The experimental study employed a situation in which subjects simulataneously monitored several dynamic processes for the occurrence of events and made yes/no decisions on the presence of events in each process. Input to the event detection model of the information displayed to the experimental subjects allows comparison of the model's performance with the performance of the subjects.

  12. Method and apparatus for detecting and determining event characteristics with reduced data collection

    NASA Technical Reports Server (NTRS)

    Totman, Peter D. (Inventor); Everton, Randy L. (Inventor); Egget, Mark R. (Inventor); Macon, David J. (Inventor)

    2007-01-01

    A method and apparatus for detecting and determining event characteristics such as, for example, the material failure of a component, in a manner which significantly reduces the amount of data collected. A sensor array, including a plurality of individual sensor elements, is coupled to a programmable logic device (PLD) configured to operate in a passive state and an active state. A triggering event is established such that the PLD records information only upon detection of the occurrence of the triggering event which causes a change in state within one or more of the plurality of sensor elements. Upon the occurrence of the triggering event, the change in state of the one or more sensor elements causes the PLD to record in memory which sensor element detected the event and at what time the event was detected. The PLD may be coupled with a computer for subsequent downloading and analysis of the acquired data.

  13. The photodynamic detection of mucosal abnormality in oral cancer patients: a pilot study

    NASA Astrophysics Data System (ADS)

    O'Dwyer, Martin; Ogden, Graham; McLaren, Stuart; Padgett, Miles

    2005-03-01

    Patients who have had one oral cancer are at increased risk of developing a semi-malignant tumour. The detecting of oral cancer is made difficult (and is often delayed) by the unknown appearance of the early oral lesion. A technique that could reliably detect early cancers would be useful to the oral and dental health specialist. One possible technique is the use of a photosensitiser that may be preferentially taken up by cancerous cells. 5-aminolaevulinic acid (ALA) is one such drug that is converted to Protoporphyrin IX (PpIX) and fluoresces at 636nm when illuminated with light of wavelength 405nm. It has been hypothesized that cell inclined towards malignant change would have a higher metabolic rate, and thus convert more ALA into its metabolite PpIX. These drugs can then be detected using a technique called Photodynamic detection, through the analysis of their fluorescence spectra. We describe a pilot study that used a compact spectroscopic instrument designed to excite and measure fluorescence in the oral cavity. Some Inter-subject variation in PpIX time course characteristics may be evident in our volunteers, as has been reported by other researchers. The obtained data would suggest that this instrument may be a valuable tool for detecting early oral cancers. However, further studies are required, not least to ensure that these data are due to detection of ALA metabolite in cancer and not some other systemic effect.

  14. Unsupervised Event Characterization and Detection in Multichannel Signals: An EEG application

    PubMed Central

    Mur, Angel; Dormido, Raquel; Vega, Jesús; Duro, Natividad; Dormido-Canto, Sebastian

    2016-01-01

    In this paper, we propose a new unsupervised method to automatically characterize and detect events in multichannel signals. This method is used to identify artifacts in electroencephalogram (EEG) recordings of brain activity. The proposed algorithm has been evaluated and compared with a supervised method. To this end an example of the performance of the algorithm to detect artifacts is shown. The results show that although both methods obtain similar classification, the proposed method allows detecting events without training data and can also be applied in signals whose events are unknown a priori. Furthermore, the proposed method provides an optimal window whereby an optimal detection and characterization of events is found. The detection of events can be applied in real-time. PMID:27120605

  15. [Methods for early detection of predisposition to abnormal increases in body weight of children and adolescents].

    PubMed

    Ivashchenko, S N

    2014-01-01

    This article presents the results of a special method designed for the early identification of children's and adolescents' propensity for abnormal weight gain. The basis of this technique is the principle of monitoring the actual values of body mass index for each child or young person at the age of dynamic changes in the index of the normal range. The weekly body weight of each child or adolescent who participates in the study is measured and the results are included in a special registry. Measurement of the body weight of the children and adolescents occurs in the morning at the same hour on an empty stomach after use of the toilet and performance of necessary hygiene. Afterwards, the obtained values of their body mass indices are compared with those considered normal for age, according to official data. In cases when the resulting body mass index of a child or young person exceeds the range of normal-for-age values, an in-depth medical examination of the child or adolescent is conducted together with the nature of their food intake and mode of physical activity, which may then be corrected.

  16. Spectroscopic detection of abnormality in chicken liver as an inspection tool

    NASA Astrophysics Data System (ADS)

    Dey, Bhabani P.; Chan, Diane E.; Chen, Yud-Ren; Gwozdz, Frank B.

    2004-03-01

    Successful differentiation of normal chicken livers from septicemic chicken livers was demonstrated using visible/near-infrared (Vis/NIR) spectral data subjected to principal component analysis and then fed into a feedforward back-propagation neural network. The study used 300 fresh chicken livers, 150 collected from normal chicken carcasses and 150 collected from chicken carcasses diagnosed with the septicemica/toxemia (septox) condition as defined for condemnation under U.S. Department of Agriculture (USDA) standards for food safety. Using a training set of 200 samples and testing set of 100 samples, the best neural network model demonstrated a classification accuracy of 98% for normal samples and 94% for septicemia/toxemia samples. These results show that Vis/NIR spectral methods have potential for use in chicken liver inspection as part of automated online systems for food safety inspection. Liver abnormalities are identifying characteristics of the septox condition; consequently, liver screening would be extremely useful as part of an automated inspection system to meet USDA food safety requirements for poultry. Automated inspection systems capable of real-time on-line operation are currently being developed, and spectroscopic liver inspection is potential tool that could be implemented as part of such systems to help poultry processors increase production while meeting food safety inspection requirements.

  17. Detection of liver cancer and abnormal liver tissue by Raman spectroscopy and fluorescence

    NASA Astrophysics Data System (ADS)

    Li, Xiaozhou; Ding, Jianhua; Zhang, Xiujun; Lin, Junxiu; Wang, Deli

    2005-01-01

    In this paper, laser induced human serum Raman spectra of liver cancer are measured. The spectra differences in serum from normal people and liver disease patients are analyzed. For the typical spectrum of normal serum, there are three sharp Raman peaks and relative intensity of Raman peaks excited by 514.5nm is higher than that excited by 488.0nm. For the Raman spectrum of liver cancer serum there are no peaks or very weak Raman peaks at the same positions. Results from more than two hundred case measurements show that clinical diagnostic accuracy is 92.86%. And then, the liver fibrosis and liver cirrhosis are studied applying the technology of LIF. To liver cirrhosis, the shape of Raman peak is similar to normal and fluorescence spectrum is similar to that of liver cancer from statistic data. The experiment indicates that there is notable fluorescence difference between the abnormal and normal liver tissue and have blue shift in fluorescence peak. Except for human serum, we use rats serum for researching either. Compared with results of path al examination, we analyze the spectra of normal cases, hepatic fibrosis and hepatocirrhosis respectively in an attempt to find some difference between them. Red shift of fluorescence peak is observed with disease evolution using 514.5nm excitation of an Ar-ion laser. However, no distinct changes happen with 488.0nm excitation. These results have important reference values to explore the method of laser spectrum diagnosis.

  18. Automated Detection of Brain Abnormalities in Neonatal Hypoxia Ischemic Injury from MR Images

    PubMed Central

    Ghosh, Nirmalya; Sun, Yu; Bhanu, Bir; Ashwal, Stephen; Obenaus, Andre

    2014-01-01

    We compared the efficacy of three automated brain injury detection methods, namely symmetry-integrated region growing (SIRG), hierarchical region splitting (HRS) and modified watershed segmentation (MWS) in human and animal magnetic resonance imaging (MRI) datasets for the detection of hypoxic ischemic injuries (HII). Diffusion weighted imaging (DWI, 1.5T) data from neonatal arterial ischemic stroke (AIS) patients, as well as T2-weighted imaging (T2WI, 11.7T, 4.7T) at seven different time-points (1, 4, 7, 10, 17, 24 and 31 days post HII) in rat-pup model of hypoxic ischemic injury were used to check the temporal efficacy of our computational approaches. Sensitivity, specificity, similarity were used as performance metrics based on manual (‘gold standard’) injury detection to quantify comparisons. When compared to the manual gold standard, automated injury location results from SIRG performed the best in 62% of the data, while 29% for HRS and 9% for MWS. Injury severity detection revealed that SIRG performed the best in 67% cases while HRS for 33% data. Prior information is required by HRS and MWS, but not by SIRG. However, SIRG is sensitive to parameter-tuning, while HRS and MWS are not. Among these methods, SIRG performs the best in detecting lesion volumes; HRS is the most robust, while MWS lags behind in both respects. PMID:25000294

  19. Extra structurally abnormal chromosomes (ESAC) detected at amniocentesis: frequency in approximately 75,000 prenatal cytogenetic diagnoses and associations with maternal and paternal age.

    PubMed Central

    Hook, E B; Cross, P K

    1987-01-01

    We analyzed rates of extra structurally abnormal chromosomes (ESAC) detected in prenatal cytogenetic diagnoses of amniotic fluid reported to the New York Chromosome Registry. These karyotypes include both extra unidentified structurally abnormal chromosomes (EUSAC)--often denoted as "markers"--and extra identified structurally abnormal chromosomes (EISAC). The rate of all EUSAC was 0.64/1,000 (0.32-0.40/1,000 mutant and 0.23-0.32 inherited), and that of all EISAC was 0.11/1,000 (0.07/1,000 mutant and 0.04/1,000 inherited). The rate of all ESAC was approximately 0.8/1,000-0.4-0.5/1,000 mutant and 0.3-0.4/1,000 inherited. Mean +/- SD maternal age of mutant cases was 37.5 +/- 2.9, significantly greater than the value of 35.8 years in controls. A regression analysis indicated a rate of change of the log of the rate of about +0.20 with each year of maternal age between 30 and 45 years. When paternal age was introduced, the maternal age coefficient increased to about +0.25--close to that seen for 47, +21--but the paternal age coefficient was -0.06. After being matched for maternal age and year of diagnosis, the case-control difference in paternal age for 24 mutant cases was -2.4 with a 95% confidence interval of -4.6 to -0.1 years. In a regression analysis of the effects of both parental ages on the (log) rate, the maternal age coefficient was +0.25 and the paternal age coefficient was -0.06. These results are consistent with a (weak) negative paternal age effect in the face of a strong maternal age effect. Since ESAC include a heterogeneous group of abnormalities, the maternal age and paternal age trends, if not the result of statistical fluctuation or undetected biases, may involve different types of events. Data in the literature suggest that chromosomes with de novo duplicated inversions of 15p have a strong maternal age effect (but little paternal age effect). Such chromosomes, however, do not account for the active maternal age trends seen in the data analyzed here

  20. [Impact of indirect factors on the growing prevalence of workers with abnormal findings in periodic general health examinations: a survey on the definition and detection of such abnormal workers by occupational health organizations].

    PubMed

    Hoshuyama, T; Takahashi, K; Fujishiro, K; Uchida, K; Okubo, T

    2000-05-01

    The prevalence of workers with abnormal findings in periodic general health examinations (PGHEx) has been growing recently in Japan and reached 41.2% in 1998. To clarify the indirect factors related to such an increase in workers with abnormal findings in the PGHEx, we carried out a questionnaire survey on the content of the statutory notification form of results of the PGHEx among a representative sample of 136 Occupational Health Organizations (OHOs). Questions on how those workers with abnormal findings were defined and detected and when the definition and the reference intervals for total cholesterol became available were included. Of the 107 OHOs which answered the questionnaire, 85 were included in the analyses because they actually calculated the number of workers with abnormal findings in each company and helped the employer fill out the notification form. The results revealed that there was no standardized definition of workers with abnormal findings in the PGHEx. Both reference intervals of items in the PGHEx and algorithm in detecting workers with abnormal findings in the PGHEx varied among the OHOs. When detecting the workers, 13 OHOs (15.3%) selected them taking into consideration medical background factors such as previous results of the PGHEx and current medical treatment. From the late 1980s to the early 1990s, many OHOs modified the definition of workers with abnormal findings, and have tended to reduce the upper limit of the reference interval for serum cholesterol. This is mainly due to amendment of the Industrial Safety and Health Law and a new recommendation for a reference interval/value proposed by the related scientific society. Although the prevalence of workers with abnormal findings in the PGHEx has continuously increased, it is not valid to compare the prevalence over the years because of modification in the definition of such workers. The prevalence of workers with abnormal findings in the PGHEx, which is one of the most important

  1. Motor task event detection using Subthalamic Nucleus Local Field Potentials.

    PubMed

    Niketeghad, Soroush; Hebb, Adam O; Nedrud, Joshua; Hanrahan, Sara J; Mahoor, Mohammad H

    2015-08-01

    Deep Brain Stimulation (DBS) provides significant therapeutic benefit for movement disorders such as Parkinson's disease. Current DBS devices lack real-time feedback (thus are open loop) and stimulation parameters are adjusted during scheduled visits with a clinician. A closed-loop DBS system may reduce power consumption and DBS side effects. In such systems, DBS parameters are adjusted based on patient's behavior, which means that behavior detection is a major step in designing such systems. Various physiological signals can be used to recognize the behaviors. Subthalamic Nucleus (STN) Local Field Potential (LFP) is a great candidate signal for the neural feedback, because it can be recorded from the stimulation lead and does not require additional sensors. A practical behavior detection method should be able to detect behaviors asynchronously meaning that it should not use any prior knowledge of behavior onsets. In this paper, we introduce a behavior detection method that is able to asynchronously detect the finger movements of Parkinson patients. As a result of this study, we learned that there is a motor-modulated inter-hemispheric connectivity between LFP signals recorded bilaterally from STN. We used non-linear regression method to measure this connectivity and use it to detect the finger movements. Performance of this method is evaluated using Receiver Operating Characteristic (ROC). PMID:26737550

  2. Contamination event detection using multiple types of conventional water quality sensors in source water.

    PubMed

    Liu, Shuming; Che, Han; Smith, Kate; Chen, Lei

    2014-08-01

    Early warning systems are often used to detect deliberate and accidental contamination events in a water system. Conventional methods normally detect a contamination event by comparing the predicted and observed water quality values from one sensor. This paper proposes a new method for event detection by exploring the correlative relationships between multiple types of conventional water quality sensors. The performance of the proposed method was evaluated using data from contaminant injection experiments in a laboratory. Results from these experiments demonstrated the correlative responses of multiple types of sensors. It was observed that the proposed method could detect a contamination event 9 minutes after the introduction of lead nitrate solution with a concentration of 0.01 mg L(-1). The proposed method employs three parameters. Their impact on the detection performance was also analyzed. The initial analysis showed that the correlative response is contaminant-specific, which implies that it can be utilized not only for contamination detection, but also for contaminant identification.

  3. Molecular detection of chromosomal abnormalities in germ and somatic cells of aged male mice

    SciTech Connect

    Lowe, X.; Baulch, J.; Quintana, L.; Ramsey, M.; Breneman, J.; Tucker, J.; Wyrobek, A.; Collins, B.; Allen, J.; Holland, N.

    1994-12-31

    Three cytogenetic methods were applied to eight B6C3F1 male mice aged 22.5 - 30.5mo to determine if advanced age was associated with an elevated risk of producing chromosomally defective germinal and somatic cells; sperm aneuploidy analysis by multi-color fluorescence in situ hybridization for three chromosomes, spermatid micronucleus analysis with anti-kinetochore antibodies, and translocation analysis of somatic metaphases by {open_quotes}painting{close_quotes} for two chromosomes. Eight mice aged 2.4mo served as controls. Sperm aneuploidy was measured by multi-color fluorescence in situ co-hybridization with DNA probes specific for chromosomes X, Y and 8, scoring 10,000 cells per animal. The aged group showed significant 1.5 - 2.0 fold increases in the hyperhaploidy phenotypes X-X-8, Y-Y-8, 8-8-Y, and 8-8-X with the greater effects appearing in animals aged >29mo. The aged group also showed significantly increased frequencies of micronucleated spermatids (2.0 vs 0.4 per 1000; all were kinetochore negative). Analysis of metaphase chromosomes from blood by {open_quotes}painting{close_quotes} of chromosomes 2 and 8 yielded 4 translocation per 858 cell-equivalents in the aged group which was a non-significant elevation over 0/202 in controls. Although interpretation must be cautious due to the small number of animals analyzed, these findings suggest that advanced paternal age may be a risk factor for chromosomal abnormalities of reproductive and somatic importance.

  4. Detection of Abnormal Muscle Activations during Walking Following Spinal Cord Injury (SCI)

    ERIC Educational Resources Information Center

    Wang, Ping; Low, K. H.; McGregor, Alison H.; Tow, Adela

    2013-01-01

    In order to identify optimal rehabilitation strategies for spinal cord injury (SCI) participants, assessment of impaired walking is required to detect, monitor and quantify movement disorders. In the proposed assessment, ten healthy and seven SCI participants were recruited to perform an over-ground walking test at slow walking speeds. SCI…

  5. Improved detection of event-related functional MRI signals using probability functions.

    PubMed

    Hagberg, G E; Zito, G; Patria, F; Sanes, J N

    2001-11-01

    Selecting an optimal event distribution for experimental use in event-related fMRI studies can require the generation of large numbers of event sequences with characteristics hard to control. The use of known probability distributions offers the possibility to control event timing and constrain the search space for finding optimal event sequences. We investigated different probability distributions in terms of response estimation (estimation efficiency), detectability (detection power, parameter estimation efficiency, sensitivity to true positives), and false-positive activation. Numerous simulated event sequences were generated selecting interevent intervals (IEI) from the uniform, uniform permuted, Latin square, exponential, binomial, Poisson, chi(2), geometric, and bimodal probability distributions and fixed IEI. Event sequences from the bimodal distribution, like block designs, had the best performance for detection and the poorest for estimation, while high estimation and detectability occurred for the long-decay exponential distribution. The uniform distribution also yielded high estimation efficiency, but probability functions with a long tail toward higher IEI, such as the geometric and the chi(2) distributions, had superior detectability. The distributions with the best detection performance also had a relatively high incidence of false positives, in contrast to the ordered distributions (Latin square and uniform permuted). The predictions of improved sensitivities for distributions with long tails were confirmed with empirical data. Moreover, the Latin square design yielded detection of activated voxels similar to the chi(2) distribution. These results indicate that high detection and suitable behavioral designs have compatibility for application of functional MRI methods to experiments requiring complex designs.

  6. Utility of the Thin Prep Imaging System® in the detection of squamous intraepithelial abnormalities on retrospective evaluation: can we trust the imager?

    PubMed

    Barroeta, Julieta E; Reilly, Mary E; Steinhoff, Margaret M; Lawrence, W Dwayne

    2012-02-01

    Prospective studies analyzing the ThinPrep Imaging System (TIS) have demonstrated a significant decrease in screening time and detection rates comparable or better than manual screening. We retrospectively analyzed the accuracy of the TIS in detecting cervical abnormalities. Our study included all new HSIL diagnoses in 2007 with previous negative (NIL) pap tests screened with TIS. The original 22 fields of view (FOV) were reviewed by 2 blinded screeners followed by manual screening of all slides. Any ASC-US or above was considered "abnormal." Of a total of 111,080 pap tests performed in 2007, 180 were reported as HSIL. Of these, 45 cases had a previous NIL pap diagnosed within the last year, screened with TIS. Following re-examination of the NIL pap, 31 diagnoses remained unchanged and 9 were reclassified as abnormal on the basis of cells present within the original FOV. When manually reviewed, all nine cases were confirmed as abnormal. Four cases were reclassified as abnormal on the basis of the manual screen (abnormal cells absent in the FOV). The sensitivity of TIS for the detection of abnormality was 99.95% (false-negative rate FNR: 0.05%) and the sensitivity for detection of HSIL was 99.07% (FNR: 0.92%). When analyzing the cytotechnologist interpretation of the FOV, the sensitivity for detection of abnormality and HSIL was 99.89% (FNR: 0.1%), and 99.53% (FNR: 0.4%), respectively. On retrospective analysis based on newly diagnosed HSIL cases, the sensitivity of TIS was comparable to that of manual screening with a slightly decreased rate of false negatives.

  7. Nonthreshold-based event detection for 3d environment monitoring in sensor networks

    SciTech Connect

    Li, M.; Liu, Y.H.; Chen, L.

    2008-12-15

    Event detection is a crucial task for wireless sensor network applications, especially environment monitoring. Existing approaches for event detection are mainly based on some predefined threshold values and, thus, are often inaccurate and incapable of capturing complex events. For example, in coal mine monitoring scenarios, gas leakage or water osmosis can hardly be described by the overrun of specified attribute thresholds but some complex pattern in the full-scale view of the environmental data. To address this issue, we propose a nonthreshold-based approach for the real 3D sensor monitoring environment. We employ energy-efficient methods to collect a time series of data maps from the sensor network and detect complex events through matching the gathered data to spatiotemporal data patterns. Finally, we conduct trace-driven simulations to prove the efficacy and efficiency of this approach on detecting events of complex phenomena from real-life records.

  8. Quantitative Gait Analysis Using a Motorized Treadmill System Sensitively Detects Motor Abnormalities in Mice Expressing ATPase Defective Spastin.

    PubMed

    Connell, James W; Allison, Rachel; Reid, Evan

    2016-01-01

    The hereditary spastic paraplegias (HSPs) are genetic conditions in which there is progressive axonal degeneration in the corticospinal tract. Autosomal dominant mutations, including nonsense, frameshift and missense changes, in the gene encoding the microtubule severing ATPase spastin are the most common cause of HSP in North America and northern Europe. In this study we report quantitative gait analysis using a motorized treadmill system, carried out on mice knocked-in for a disease-associated mutation affecting a critical residue in the Walker A motif of the spastin ATPase domain. At 4 months and at one year of age homozygous mutant mice had a number of abnormal gait parameters, including in stride length and stride duration, compared to heterozygous and wild-type littermates. Gait parameters in heterozygous animals did not differ from wild-type littermates. We conclude that quantitative gait analysis using the DigiGait system sensitively detects motor abnormalities in a hereditary spastic paraplegia model, and would be a useful method for analyzing the effects of pharmacological treatments for HSP.

  9. Trends in breast biopsies for abnormalities detected at screening mammography: a population-based study in the Netherlands

    PubMed Central

    van Breest Smallenburg, V; Nederend, J; Voogd, A C; Coebergh, J W W; van Beek, M; Jansen, F H; Louwman, W J; Duijm, L E M

    2013-01-01

    Background: Diagnostic surgical breast biopsies have several disadvantages, therefore, they should be used with hesitation. We determined time trends in types of breast biopsies for the workup of abnormalities detected at screening mammography. We also examined diagnostic delays. Methods: In a Dutch breast cancer screening region 6230 women were referred for an abnormal screening mammogram between 1 January 1997 and 1 January 2011. During two year follow-up clinical data, breast imaging-, biopsy-, surgery- and pathology-reports were collected of these women. Furthermore, breast cancers diagnosed >3 months after referral (delays) were examined, this included review of mammograms and pathology specimens to determine the cause of the delays. Results: In 41.1% (1997–1998) and in 44.8% (2009–2010) of referred women imaging was sufficient for making the diagnosis (P<0.0001). Fine-needle aspiration cytology decreased from 12.7% (1997–1998) to 4.7% (2009–2010) (P<0.0001), percutaneous core-needle biopsies (CBs) increased from 8.0 to 49.1% (P<0.0001) and surgical biopsies decreased from 37.8 to 1.4% (P<0.0001). Delays in breast cancer diagnosis decreased from 6.7 to 1.8% (P=0.003). Conclusion: The use of diagnostic surgical breast biopsies has decreased substantially. They have mostly been replaced by percutaneous CBs and this replacement did not result in an increase of diagnostic delays. PMID:23695018

  10. Power System Extreme Event Detection: The VulnerabilityFrontier

    SciTech Connect

    Lesieutre, Bernard C.; Pinar, Ali; Roy, Sandip

    2007-10-17

    In this work we apply graph theoretic tools to provide aclose bound on a frontier relating the number of line outages in a gridto the power disrupted by the outages. This frontier describes theboundary of a space relating the possible severity of a disturbance interms of power disruption, from zero to some maximum on the boundary, tothe number line outages involved in the event. We present the usefulnessof this analysis with a complete analysis of a 30 bus system, and presentresults for larger systems.

  11. Brain tumour classification and abnormality detection using neuro-fuzzy technique and Otsu thresholding.

    PubMed

    Renjith, Arokia; Manjula, P; Mohan Kumar, P

    2015-01-01

    Brain tumour is one of the main causes for an increase in transience among children and adults. This paper proposes an improved method based on Magnetic Resonance Imaging (MRI) brain image classification and image segmentation approach. Automated classification is encouraged by the need of high accuracy when dealing with a human life. The detection of the brain tumour is a challenging problem, due to high diversity in tumour appearance and ambiguous tumour boundaries. MRI images are chosen for detection of brain tumours, as they are used in soft tissue determinations. First of all, image pre-processing is used to enhance the image quality. Second, dual-tree complex wavelet transform multi-scale decomposition is used to analyse texture of an image. Feature extraction extracts features from an image using gray-level co-occurrence matrix (GLCM). Then, the Neuro-Fuzzy technique is used to classify the stages of brain tumour as benign, malignant or normal based on texture features. Finally, tumour location is detected using Otsu thresholding. The classifier performance is evaluated based on classification accuracies. The simulated results show that the proposed classifier provides better accuracy than previous method.

  12. Falls event detection using triaxial accelerometry and barometric pressure measurement.

    PubMed

    Bianchi, Federico; Redmond, Stephen J; Narayanan, Michael R; Cerutti, Sergio; Celler, Branko G; Lovell, Nigel H

    2009-01-01

    A falls detection system, employing a Bluetooth-based wearable device, containing a triaxial accelerometer and a barometric pressure sensor, is described. The aim of this study is to evaluate the use of barometric pressure measurement, as a surrogate measure of altitude, to augment previously reported accelerometry-based falls detection algorithms. The accelerometry and barometric pressure signals obtained from the waist-mounted device are analyzed by a signal processing and classification algorithm to discriminate falls from activities of daily living. This falls detection algorithm has been compared to two existing algorithms which utilize accelerometry signals alone. A set of laboratory-based simulated falls, along with other tasks associated with activities of daily living (16 tests) were performed by 15 healthy volunteers (9 male and 6 female; age: 23.7 +/- 2.9 years; height: 1.74 +/- 0.11 m). The algorithm incorporating pressure information detected falls with the highest sensitivity (97.8%) and the highest specificity (96.7%).

  13. Neuro-evolutionary event detection technique for downhole microseismic surveys

    NASA Astrophysics Data System (ADS)

    Maity, Debotyam; Salehi, Iraj

    2016-01-01

    Recent years have seen a significant increase in borehole microseismic data acquisition programs associated with unconventional reservoir developments such as hydraulic fracturing programs for shale oil and gas. The data so acquired is used for hydraulic fracture monitoring and diagnostics and therefore, the quality of the data in terms of resolution and accuracy has a significant impact on its value to the industry. Borehole microseismic data acquired in such environments typically suffer from propagation effects due to the presence of thin interbedded shale layers as well as noise and interference effects. Moreover, acquisition geometry has significant impact on detectability across portions of the sensor array. Our work focuses on developing robust first arrival detection and pick selection workflow for both P and S waves specifically designed for such environments. We introduce a novel workflow for refinement of picks with immunity towards significant noise artifacts and applicability over data with very low signal-to-noise ratio provided some accurate picks have already been made. This workflow utilizes multi-step hybrid detection and classification routine which makes use of a neural network based autopicker for initial picking and an evolutionary algorithm for pick refinement. We highlight the results from an actual field case study including multiple examples demonstrating immunity towards noise and compare the effectiveness of the workflow with two contemporary autopicking routines without the application of the shared detection/refinement procedure. Finally, we use a windowed waveform cross-correlation based uncertainty estimation method for potential quality control purposes. While the workflow was developed to work with the neural network based autopicker, it can be used with any other traditional autopicker and provides significant improvements in pick detection across seismic gathers.

  14. A multiscale decomposition approach to detect abnormal vasculature in the optic disc.

    PubMed

    Agurto, Carla; Yu, Honggang; Murray, Victor; Pattichis, Marios S; Nemeth, Sheila; Barriga, Simon; Soliz, Peter

    2015-07-01

    This paper presents a multiscale method to detect neovascularization in the optic disc (NVD) using fundus images. Our method is applied to a manually selected region of interest (ROI) containing the optic disc. All the vessels in the ROI are segmented by adaptively combining contrast enhancement methods with a vessel segmentation technique. Textural features extracted using multiscale amplitude-modulation frequency-modulation, morphological granulometry, and fractal dimension are used. A linear SVM is used to perform the classification, which is tested by means of 10-fold cross-validation. The performance is evaluated using 300 images achieving an AUC of 0.93 with maximum accuracy of 88%. PMID:25698545

  15. A Multiscale Decomposition Approach to Detect Abnormal Vasculature in the Optic Disc

    PubMed Central

    Agurto, Carla; Yu, Honggang; Murray, Victor; Pattichis, Marios S.; Nemeth, Sheila; Barriga, Simon; Soliz, Peter

    2015-01-01

    This paper presents a multiscale method to detect neovascularization in the optic disc (NVD) using fundus images. Our method is applied to a manually selected region of interest (ROI) containing the optic disc. All the vessels in the ROI are segmented by adaptively combining contrast enhancement methods with a vessel segmentation technique. Textural features extracted using multiscale amplitude-modulation frequency-modulation, morphological granulometry, and fractal dimension are used. A linear SVM is used to perform the classification, which is tested by means of 10-fold cross-validation. The performance is evaluated using 300 images achieving an AUC of 0.93 with maximum accuracy of 88%. PMID:25698545

  16. Simulation-Based Evaluation of the Performances of an Algorithm for Detecting Abnormal Disease-Related Features in Cattle Mortality Records

    PubMed Central

    Perrin, Jean-Baptiste; Durand, Benoît; Gay, Emilie; Ducrot, Christian; Hendrikx, Pascal; Calavas, Didier; Hénaux, Viviane

    2015-01-01

    We performed a simulation study to evaluate the performances of an anomaly detection algorithm considered in the frame of an automated surveillance system of cattle mortality. The method consisted in a combination of temporal regression and spatial cluster detection which allows identifying, for a given week, clusters of spatial units showing an excess of deaths in comparison with their own historical fluctuations. First, we simulated 1,000 outbreaks of a disease causing extra deaths in the French cattle population (about 200,000 herds and 20 million cattle) according to a model mimicking the spreading patterns of an infectious disease and injected these disease-related extra deaths in an authentic mortality dataset, spanning from January 2005 to January 2010. Second, we applied our algorithm on each of the 1,000 semi-synthetic datasets to identify clusters of spatial units showing an excess of deaths considering their own historical fluctuations. Third, we verified if the clusters identified by the algorithm did contain simulated extra deaths in order to evaluate the ability of the algorithm to identify unusual mortality clusters caused by an outbreak. Among the 1,000 simulations, the median duration of simulated outbreaks was 8 weeks, with a median number of 5,627 simulated deaths and 441 infected herds. Within the 12-week trial period, 73% of the simulated outbreaks were detected, with a median timeliness of 1 week, and a mean of 1.4 weeks. The proportion of outbreak weeks flagged by an alarm was 61% (i.e. sensitivity) whereas one in three alarms was a true alarm (i.e. positive predictive value). The performances of the detection algorithm were evaluated for alternative combination of epidemiologic parameters. The results of our study confirmed that in certain conditions automated algorithms could help identifying abnormal cattle mortality increases possibly related to unidentified health events. PMID:26536596

  17. Spatial-temporal event detection in climate parameter imagery.

    SciTech Connect

    McKenna, Sean Andrew; Gutierrez, Karen A.

    2011-10-01

    Previously developed techniques that comprise statistical parametric mapping, with applications focused on human brain imaging, are examined and tested here for new applications in anomaly detection within remotely-sensed imagery. Two approaches to analysis are developed: online, regression-based anomaly detection and conditional differences. These approaches are applied to two example spatial-temporal data sets: data simulated with a Gaussian field deformation approach and weekly NDVI images derived from global satellite coverage. Results indicate that anomalies can be identified in spatial temporal data with the regression-based approach. Additionally, la Nina and el Nino climatic conditions are used as different stimuli applied to the earth and this comparison shows that el Nino conditions lead to significant decreases in NDVI in both the Amazon Basin and in Southern India.

  18. Detection of intermittent events in atmospheric time series

    NASA Astrophysics Data System (ADS)

    Paradisi, P.; Cesari, R.; Palatella, L.; Contini, D.; Donateo, A.

    2009-04-01

    The modeling approach in atmospheric sciences is based on the assumption that local fluxes of mass, momentum, heat, etc... can be described as linear functions of the local gradient of some intensive property (concentration, flow strain, temperature,...). This is essentially associated with Gaussian statistics and short range (exponential) correlations. However, the atmosphere is a complex dynamical system displaying a wide range of spatial and temporal scales. A global description of the atmospheric dynamics should include a great number of degrees of freedom, strongly interacting on several temporal and spatial scales, thus generating long range (power-law) correlations and non-Gaussian distribution of fluctuations (Lévy flights, Lévy walks, Continuous Time Random Walks) [1]. This is typically associated with anomalous diffusion and scaling, non-trivial memory features and correlation decays and, especially, with the emergence of flux-gradient relationships that are non-linear and/or non-local in time and/or space. Actually, the local flux-gradient relationship is greatly preferred due to a more clear physical meaning, allowing to perform direct comparisons with experimental data, and, especially, to smaller computational costs in numerical models. In particular, the linearity of this relationship allows to define a transport coefficient (e.g., turbulent diffusivity) and the modeling effort is usually focused on this coefficient. However, the validity of the local (and linear) flux-gradient model is strongly dependent on the range of spatial and temporal scales represented by the model and, consequently, by the sub-grid processes included in the flux-gradient relationship. In this work, in order to check the validity of local and linear flux-gradient relationships, an approach based on the concept of renewal critical events [2] is introduced. In fact, in renewal theory [2], the dynamical origin of anomalous behaviour and non-local flux-gradient relation is

  19. Shape Abnormalities of Subcortical and Ventricular Structures in Mild Cognitive Impairment and Alzheimer’s Disease: Detecting, Quantifying, and Predicting

    PubMed Central

    Tang, Xiaoying; Holland, Dominic; Dale, Anders M.; Younes, Laurent; Miller, Michael I.

    2015-01-01

    This article assesses the feasibility of using shape information to detect and quantify the subcortical and ventricular structural changes in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) patients. We first demonstrate structural shape abnormalities in MCI and AD as compared with healthy controls (HC). Exploring the development to AD, we then divide the MCI participants into two subgroups based on longitudinal clinical information: (1) MCI patients who remained stable; (2) MCI patients who converted to AD over time. We focus on seven structures (amygdala, hippocampus, thalamus, caudate, putamen, globus pallidus, and lateral ventricles) in 754 MR scans (210 HC, 369 MCI of which 151 converted to AD over time, and 175 AD). The hippocampus and amygdala were further subsegmented based on high field 0.8 mm isotropic 7.0T scans for finer exploration. For MCI and AD, prominent ventricular expansions were detected and we found that these patients had strongest hippocampal atrophy occurring at CA1 and strongest amygdala atrophy at the basolateral complex. Mild atrophy in basal ganglia structures was also detected in MCI and AD. Stronger atrophy in the amygdala and hippocampus, and greater expansion in ventricles was observed in MCI converters, relative to those MCI who remained stable. Furthermore, we performed principal component analysis on a linear shape space of each structure. A subsequent linear discriminant analysis on the principal component values of hippocampus, amygdala, and ventricle leads to correct classification of 88% HC subjects and 86% AD subjects. PMID:24443091

  20. A Fuzzy-Decision Based Approach for Composite Event Detection in Wireless Sensor Networks

    PubMed Central

    Zhang, Shukui; Chen, Hao; Zhu, Qiaoming

    2014-01-01

    The event detection is one of the fundamental researches in wireless sensor networks (WSNs). Due to the consideration of various properties that reflect events status, the Composite event is more consistent with the objective world. Thus, the research of the Composite event becomes more realistic. In this paper, we analyze the characteristics of the Composite event; then we propose a criterion to determine the area of the Composite event and put forward a dominating set based network topology construction algorithm under random deployment. For the unreliability of partial data in detection process and fuzziness of the event definitions in nature, we propose a cluster-based two-dimensional τ-GAS algorithm and fuzzy-decision based composite event decision mechanism. In the case that the sensory data of most nodes are normal, the two-dimensional τ-GAS algorithm can filter the fault node data effectively and reduce the influence of erroneous data on the event determination. The Composite event judgment mechanism which is based on fuzzy-decision holds the superiority of the fuzzy-logic based algorithm; moreover, it does not need the support of a huge rule base and its computational complexity is small. Compared to CollECT algorithm and CDS algorithm, this algorithm improves the detection accuracy and reduces the traffic. PMID:25136690

  1. Developing and testing a multi-probe resonance electrical impedance spectroscopy system for detecting breast abnormalities

    NASA Astrophysics Data System (ADS)

    Gur, David; Zheng, Bin; Dhurjaty, Sreeram; Wolfe, Gene; Fradin, Mary; Weil, Richard; Sumkin, Jules; Zuley, Margarita

    2009-02-01

    In our previous study, we reported on the development and preliminary testing of a prototype resonance electrical impedance spectroscopy (REIS) system with a pair of probes. Although our pilot study on 150 young women ranging from 30 to 50 years old indicated the feasibility of using REIS output sweep signals to classify between the women who had negative examinations and those who would ultimately be recommended for biopsy, the detection sensitivity was relatively low. To improve performance when using REIS technology, we recently developed a new multi-probe based REIS system. The system consists of a sensor module box that can be easily lifted along a vertical support device to fit women of different height. Two user selectable breast placement "cups" with different curvatures are included in the system. Seven probes are mounted on each of the cups on opposing sides of the sensor box. By rotating the sensor box, the technologist can select the detection sensor cup that better fits the breast size of the woman being examined. One probe is mounted in the cup center for direct contact with the nipple and the other six probes are uniformly distributed along an outside circle to enable contact with six points on the outer and inner breast skin surfaces. The outer probes are located at a distance of 60mm away from the center (nipple) probe. The system automatically monitors the quality of the contact between the breast surface and each of the seven probes and data acquisition can only be initiated when adequate contact is confirmed. The measurement time for each breast is approximately 15 seconds during which time the system records 121 REIS signal sweep outputs generated from 200 KHz to 800 KHz at 5 KHz increments for all preselected probe pairs. Currently we are measuring 6 pairs between the center probe and each of six probes located on the outer circle as well as two pairs between probe pairs on the outer circle. This new REIS system has been installed in our

  2. Detection of zones of abnormal strains in structures using Gaussian curvature analysis

    SciTech Connect

    Lisle, R.J.

    1994-12-01

    Whereas some folds, such as those produced by flexural slip, do not theoretically entail strain within the folded surfaces, any surface involving double curvature (such as domes and saddles) cannot form without some stretching or contraction of the bedding. Whether straining of the surfaces is required during folding depends on the three-dimensional fold shape and, in particular, on the Gaussian curvature at points on the folded surface. Using this as a basis, I present a method for detecting zones of anomalously high strain in oil-field structures from Gaussian curvature analysis (GCA) of natural structures. The new method of GCA is suitable for analyzing surfaces that have been mapped seismically. A Gaussian curvature map of the structure is a principal outcome of the analysis and can be used to predict the density of strain-related subseismic structures, such as small-scale fracturing. The Goose Egg dome, near Casper, Wyoming, is analyzed and provides an example of GCA. In this structure, a relationship is observed between fracture densities and Gaussian curvature.

  3. Unsupervised Spatial Event Detection in Targeted Domains with Applications to Civil Unrest Modeling

    PubMed Central

    Zhao, Liang; Chen, Feng; Dai, Jing; Hua, Ting; Lu, Chang-Tien; Ramakrishnan, Naren

    2014-01-01

    Twitter has become a popular data source as a surrogate for monitoring and detecting events. Targeted domains such as crime, election, and social unrest require the creation of algorithms capable of detecting events pertinent to these domains. Due to the unstructured language, short-length messages, dynamics, and heterogeneity typical of Twitter data streams, it is technically difficult and labor-intensive to develop and maintain supervised learning systems. We present a novel unsupervised approach for detecting spatial events in targeted domains and illustrate this approach using one specific domain, viz. civil unrest modeling. Given a targeted domain, we propose a dynamic query expansion algorithm to iteratively expand domain-related terms, and generate a tweet homogeneous graph. An anomaly identification method is utilized to detect spatial events over this graph by jointly maximizing local modularity and spatial scan statistics. Extensive experiments conducted in 10 Latin American countries demonstrate the effectiveness of the proposed approach. PMID:25350136

  4. White matter microstructural abnormality in children with hydrocephalus detected by probabilistic diffusion tractography

    PubMed Central

    Rajagopal, Akila; Shimony, Joshua S.; McKinstry, Robert C.; Altaye, Mekibib; Maloney, Tom; Mangano, Francesco T.; Limbrick, David D.; Holland, Scott K.; Jones, Blaise V.; Simpson, Sarah; Mercer, Deanna; Yuan, Weihong

    2014-01-01

    Background and Purpose Hydrocephalus is a severe pathologic condition in which WM damage is a major factor associated with poor outcomes. The goal of the study was to investigate tract-based WM connectivity and DTI measurements in children with hydrocephalus using PDT method. Methods Twelve children with hydrocephalus and 16 age matched controls were included in the study. PDT was conducted to generate tract-based connectivity distribution and DTI measures for the gCC and mCST. Tract-based summary measurements, included connectivity index and DTI measures (FA, MD, AD, and RDs) were calculated and compared between the two study groups. Results Tract-based summary measurement showed that there was a higher percentage of voxels with lower normalized CI values in the WM tracts from children with hydrocephalus. In gCC, left mCST and right mCST, the normalized CI value in children with hydrocephalus was found to be significantly lower (p<0.05, corrected). The tract based DTI measures showed that the children with hydrocephalus had significantly higher MD, AD, and RD in gCC, left mCST, and right mCST, and lower FA in gCC (p<0.05, corrected). Conclusions The analysis of WM connectivity showed that PDT method is a sensitive tool to detect the decreased continuity in WM tracts that are under the direct influence of mechanical distortion and increased intracranial pressure in hydrocephalus. This voxel-based connectivity method can provide quantitative information complementary to the standard DTI summary measures. PMID:24072621

  5. Seismic network detection probability assessment using waveforms and accounting to event association logic

    NASA Astrophysics Data System (ADS)

    Pinsky, Vladimir; Shapira, Avi

    2016-05-01

    The geographical area where a seismic event of magnitude M ≥ M t is detected by a seismic station network, for a defined probability is derived from a station probability of detection estimated as a function of epicentral distance. The latter is determined from both the bulletin data and the waveforms recorded by the station during the occurrence of the event with and without band-pass filtering. For simulating the real detection process, the waveforms are processed using the conventional Carl Johnson detection and association algorithm. The attempt is presented to account for the association time criterion in addition to the conventional approach adopted by the known PMC method.

  6. Find Your Manners: How Do Infants Detect the Invariant Manner of Motion in Dynamic Events?

    ERIC Educational Resources Information Center

    Pruden, Shannon M.; Goksun, Tilbe; Roseberry, Sarah; Hirsh-Pasek, Kathy; Golinkoff, Roberta M.

    2012-01-01

    To learn motion verbs, infants must be sensitive to the specific event features lexicalized in their language. One event feature important for the acquisition of English motion verbs is the manner of motion. This article examines when and how infants detect manners of motion across variations in the figure's path. Experiment 1 shows that 13- to…

  7. A new paradigm of dielectric relaxation spectroscopy for non-invasive detection of breast abnormalities: a preliminary feasibility analysis

    NASA Astrophysics Data System (ADS)

    Dhurjaty, Sreeram; Qiu, Yuchen; Tan, Maxine; Qian, Wei; Zheng, Bin

    2016-03-01

    In order to improve efficacy of screening mammography, in recent years, we have been investigating the feasibility of applying a resonance-frequency based electrical impedance spectroscopy (REIS) technology to noninvasively detect breast abnormalities that may lead to the development of cancer in the near-term. Despite promising study-results, we found that REIS suffered from relatively poor reproducibility due to perturbations in electrode placement, contact pressure variation on the breast, as well as variation of the resonating inductor. To overcome this limitation, in this study, we propose and analyze a new paradigm of Dielectric Relaxation Spectroscopy (DRS) that measures polarization-lag of dielectric signals in breast-capacitance when excited by the pulses or sine waves. Unlike conventional DRS that operates using the signals at very high frequencies (GHz) to examine changes in polarization, our new method detects and characterizes the dielectric properties of tissue at low frequencies (<=10 MHz) due to the advent of inexpensive oscillators that are accurate to 1 pico-second (used in GPS receivers) as well as measurement of amplitudes of 1 ppm or better. From theoretical analysis, we have proved that the sensitivity of new DRS in detecting permittivity of water increased by >=80 times as compared to conventional DRS, which operates at frequencies around 4GHz. By analyzing and comparing the relationship between the new DRS and REIS, we found that this DRS has potential advantages in enhancing repeatability from various readings, including temperature-insensitive detection, and yielding higher resolution or sensitivity (up to 100 Femtofarads).

  8. An integrated logit model for contamination event detection in water distribution systems.

    PubMed

    Housh, Mashor; Ostfeld, Avi

    2015-05-15

    The problem of contamination event detection in water distribution systems has become one of the most challenging research topics in water distribution systems analysis. Current attempts for event detection utilize a variety of approaches including statistical, heuristics, machine learning, and optimization methods. Several existing event detection systems share a common feature in which alarms are obtained separately for each of the water quality indicators. Unifying those single alarms from different indicators is usually performed by means of simple heuristics. A salient feature of the current developed approach is using a statistically oriented model for discrete choice prediction which is estimated using the maximum likelihood method for integrating the single alarms. The discrete choice model is jointly calibrated with other components of the event detection system framework in a training data set using genetic algorithms. The fusing process of each indicator probabilities, which is left out of focus in many existing event detection system models, is confirmed to be a crucial part of the system which could be modelled by exploiting a discrete choice model for improving its performance. The developed methodology is tested on real water quality data, showing improved performances in decreasing the number of false positive alarms and in its ability to detect events with higher probabilities, compared to previous studies.

  9. Comparison of the STA/LTA and power spectral density methods for microseismic event detection

    NASA Astrophysics Data System (ADS)

    Vaezi, Yoones; Van der Baan, Mirko

    2015-12-01

    Robust event detection and picking is a prerequisite for reliable (micro-) seismic interpretations. Detection of weak events is a common challenge among various available event detection algorithms. In this paper we compare the performance of two event detection methods, the short-term average/long-term average (STA/LTA) method, which is the most commonly used technique in industry, and a newly introduced method that is based on the power spectral density (PSD) measurements. We have applied both techniques to a 1-hr long segment of the vertical component of some raw continuous data recorded at a borehole geophone in a hydraulic fracturing experiment. The PSD technique outperforms the STA/LTA technique by detecting a higher number of weak events while keeping the number of false alarms at a reasonable level. The time-frequency representations obtained through the PSD method can also help define a more suitable bandpass filter which is usually required for the STA/LTA method. The method offers thus much promise for automated event detection in industrial, local, regional and global seismological data sets.

  10. Automated identification of abnormal metaphase chromosome cells for the detection of chronic myeloid leukemia using microscopic images

    NASA Astrophysics Data System (ADS)

    Wang, Xingwei; Zheng, Bin; Li, Shibo; Mulvihill, John J.; Chen, Xiaodong; Liu, Hong

    2010-07-01

    Karyotyping is an important process to classify chromosomes into standard classes and the results are routinely used by the clinicians to diagnose cancers and genetic diseases. However, visual karyotyping using microscopic images is time-consuming and tedious, which reduces the diagnostic efficiency and accuracy. Although many efforts have been made to develop computerized schemes for automated karyotyping, no schemes can get be performed without substantial human intervention. Instead of developing a method to classify all chromosome classes, we develop an automatic scheme to detect abnormal metaphase cells by identifying a specific class of chromosomes (class 22) and prescreen for suspicious chronic myeloid leukemia (CML). The scheme includes three steps: (1) iteratively segment randomly distributed individual chromosomes, (2) process segmented chromosomes and compute image features to identify the candidates, and (3) apply an adaptive matching template to identify chromosomes of class 22. An image data set of 451 metaphase cells extracted from bone marrow specimens of 30 positive and 30 negative cases for CML is selected to test the scheme's performance. The overall case-based classification accuracy is 93.3% (100% sensitivity and 86.7% specificity). The results demonstrate the feasibility of applying an automated scheme to detect or prescreen the suspicious cancer cases.

  11. The waveform correlation event detection system project, Phase I: Issues in prototype development and testing

    SciTech Connect

    Young, C.; Harris, M.; Beiriger, J.; Moore, S.; Trujillo, J.; Withers, M.; Aster, R.

    1996-08-01

    A study using long-period seismic data showed that seismic events can be detected and located based on correlations of processed waveform profiles with the profile expected for an event. In this technique both time and space are discretized and events are found by forming profiles and calculating correlations for all time-distance points. events are declared at points with large correlations. In the first phase of the Waveform Correlation Event Detection System (WCEDS) Project at Sandia Labs we have developed a prototype automatic event detection system based on Shearer`s work which shows promise for treaty monitoring applications. Many modifications have been made to meet the requirements of the monitoring environment. A new full matrix multiplication has been developed which can reduce the number of computations needed for the data correlation by as much as two orders of magnitude for large grids. New methodology has also been developed to deal with the problems caused by false correlations (sidelobes) generated during the correlation process. When an event has been detected, masking matrices are set up which will mask all correlation sidelobes due to the event, allowing other events with intermingled phases to be found. This process is repeated until a detection threshold is reached. The system was tested on one hour of Incorporated Research Institutions for Seismology (IRIS) broadband data and built all 4 of the events listed in the National Earthquake Information Center (NEIC) Preliminary Determination of Epicenters (PDE) which were observable by the IRIS network. A continuous execution scheme has been developed for the system but has not yet been implemented. Improvements to the efficiency of the code are in various stages of development. Many refinements would have to be made to the system before it could be used as part of an actual monitoring system, but at this stage we know of no clear barriers which would prevent an eventual implementation of the system.

  12. Supervisory control design based on hybrid systems and fuzzy events detection. Application to an oxichlorination reactor.

    PubMed

    Altamiranda, Edmary; Torres, Horacio; Colina, Eliezer; Chacón, Edgar

    2002-10-01

    This paper presents a supervisory control scheme based on hybrid systems theory and fuzzy events detection. The fuzzy event detector is a linguistic model, which synthesizes complex relations between process variables and process events incorporating experts' knowledge about the process operation. This kind of detection allows the anticipation of appropriate control actions, which depend upon the selected membership functions used to characterize the process under scrutiny. The proposed supervisory control scheme was successfully implemented for an oxichlorination reactor in a vinyl monomer plant. This implementation has allowed improvement of reactor stability and reduction of raw material consumption. PMID:12398279

  13. Qualitative and event-specific real-time PCR detection methods for Bt brinjal event EE-1.

    PubMed

    Randhawa, Gurinder Jit; Sharma, Ruchi; Singh, Monika

    2012-01-01

    Bt brinjal event EE-1 with cry1Ac gene, expressing insecticidal protein against fruit and shoot borer, is the first genetically modified food crop in the pipeline for commercialization in India. Qualitative polymerase chain reaction (PCR) along with event-specific conventional as well as real-time PCR methods to characterize the event EE-1 is reported. A multiplex (pentaplex) PCR system simultaneously amplifying cry1Ac transgene, Cauliflower Mosaic Virus (CaMV) 35S promoter, nopaline synthase (nos) terminator, aminoglycoside adenyltransferase (aadA) marker gene, and a taxon-specific beta-fructosidase gene in event EE-1 has been developed. Furthermore, construct-specific PCR, targeting the approximate 1.8 kb region of inserted gene construct comprising the region of CaMV 35S promoter and cry1Ac gene has also been developed. The LOD of developed EE-1 specific conventional PCR assay is 0.01%. The method performance of the reported real-time PCR assay was consistent with the acceptance criteria of Codex Alimentarius Commission ALINORM 10/33/23, with the LOD and LOQ values of 0.05%. The developed detection methods would not only facilitate effective regulatory compliance for identification of genetic traits, risk assessment, management, and postrelease monitoring, but also address consumer concerns and resolution of legal disputes. PMID:23451391

  14. Qualitative and event-specific real-time PCR detection methods for Bt brinjal event EE-1.

    PubMed

    Randhawa, Gurinder Jit; Sharma, Ruchi; Singh, Monika

    2012-01-01

    Bt brinjal event EE-1 with cry1Ac gene, expressing insecticidal protein against fruit and shoot borer, is the first genetically modified food crop in the pipeline for commercialization in India. Qualitative polymerase chain reaction (PCR) along with event-specific conventional as well as real-time PCR methods to characterize the event EE-1 is reported. A multiplex (pentaplex) PCR system simultaneously amplifying cry1Ac transgene, Cauliflower Mosaic Virus (CaMV) 35S promoter, nopaline synthase (nos) terminator, aminoglycoside adenyltransferase (aadA) marker gene, and a taxon-specific beta-fructosidase gene in event EE-1 has been developed. Furthermore, construct-specific PCR, targeting the approximate 1.8 kb region of inserted gene construct comprising the region of CaMV 35S promoter and cry1Ac gene has also been developed. The LOD of developed EE-1 specific conventional PCR assay is 0.01%. The method performance of the reported real-time PCR assay was consistent with the acceptance criteria of Codex Alimentarius Commission ALINORM 10/33/23, with the LOD and LOQ values of 0.05%. The developed detection methods would not only facilitate effective regulatory compliance for identification of genetic traits, risk assessment, management, and postrelease monitoring, but also address consumer concerns and resolution of legal disputes.

  15. Theta responses are abnormal in mild cognitive impairment: evidence from analysis of theta event-related synchronization during a temporal expectancy task.

    PubMed

    Caravaglios, Giuseppe; Muscoso, Emma Gabriella; Di Maria, Giulia; Costanzo, Erminio

    2013-07-01

    We examined the hypothesis that the attention/executive deficits in mild cognitive impairment (MCI) due to Alzheimer's disease is associated to an abnormal cortical activation, revealed by the method of event-related synchronization/desynchronization (ERS/ERD) in the theta band during a paradigm of temporal orienting of attention. MCI patients (n = 25) and healthy elderly (HE) matched controls (n = 15) performed a task in which periodically omitted tones had to be predicted and their virtual onset time had to be marked by pressing a button. Single-trial theta responses were measured, respectively, before and after the motor response. Then, theta responses were compared to theta power during eyes closed resting state (ERD/ERS method).The temporal course of the task was characterized by two different behavioural conditions: (1) a pre-event epoch, in which the subject awaited the virtual onset of the omitted tone, (2) a post-event (after button pressing) epoch, in which the subject was in a post-motor response condition. The most important findings are summarized as follows: (1) in both groups, the pre-event epoch was characterized by theta ERS on temporal electrodes, but HE had a greater theta ERS compared to that of MCI group; (2) in both groups, during the post-motor condition, there was a theta ERS on prefrontal regions, and, also in this case, HE showed a greater theta enhancement compared to that of MCI patients; (3) HE showed evidence of lateralization: during the waiting epoch, theta ERS was dominant on the right posterior temporal lead (T6), whilst, during the post-motor epoch, theta ERS was greater on the left, as well as the midline prefrontal leads. Compared to the traditional neuropsychological measures for the episodic memory, these theta ERS indicators were less accurate in differentiating MCI patients from healthy elderly. The clinical relevance of these findings is that the weaker theta reactivity in MCI would indicate an early impairment in the

  16. Real-time detection and classification of anomalous events in streaming data

    DOEpatents

    Ferragut, Erik M.; Goodall, John R.; Iannacone, Michael D.; Laska, Jason A.; Harrison, Lane T.

    2016-04-19

    A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The events can be displayed to a user in user-defined groupings in an animated fashion. The system can include a plurality of anomaly detectors that together implement an algorithm to identify low probability events and detect atypical traffic patterns. The atypical traffic patterns can then be classified as being of interest or not. In one particular example, in a network environment, the classification can be whether the network traffic is malicious or not.

  17. Diagnostic accuracy of myocardial deformation indices for detecting high risk coronary artery disease in patients without regional wall motion abnormality

    PubMed Central

    Rostamzadeh, Alireza; Shojaeifard, Maryam; Rezaei, Yousef; Dehghan, Kasra

    2015-01-01

    Background: The prediction of coronary artery disease (CAD) by conventional echocardiographic measurements is principally based on the estimation of ejection fraction and regional wall motion abnormality (RWMA). This study aimed to determine whether strain echocardiography of left ventricle measured by velocity vector imaging (VVI) method could detect patients with a high-risk CAD. Methods: In a prospective study, a total of 119 consecutive patients who were assessed for eligibility were categorized into three groups: (1) without CAD as normal (n=59), (2) 1- or 2-vessel disease as low-risk (n=29), and (3) left main and/or 3-vessel disease as high-risk (n=31). The peaks of systolic strain and strain rate from 18 curves of apical views were averaged as global longitudinal strain and strain rate (GLS and GLSR), respectively; the 6 systolic peaks of strain and strain rate at base- and mid-ventricular of short axis views were averaged as mean radial strain rate (MRSR). Results: GLS, GLSR, and basal MRSR of left ventricle were significantly lower in the high-risk group (P=0.047, P=0.004 and P=0.030, respectively). Receiver operating characteristics curve showed that the optimal values of GLS, GLSR, and basal MRSR for detecting the severe CAD were -17%, -1 s-1, and 1.45 s-1 with the sensitivities of 77%, 71%, and 71% and the specificities of 63%, 67%, and 62%, respectively. Conclusion: Decrements in the GLS, GLSR, and basal MRSR of the left ventricle can detect the high-risk CAD cases among patients without RWMA at rest. PMID:26309603

  18. Event Detection and Visualization of Ocean Eddies based on SSH and Velocity Field

    NASA Astrophysics Data System (ADS)

    Matsuoka, Daisuke; Araki, Fumiaki; Inoue, Yumi; Sasaki, Hideharu

    2016-04-01

    Numerical studies of ocean eddies have been progressed using high-resolution ocean general circulation models. In order to understand ocean eddies from simulation results with large amount of information volume, it is necessary to visualize not only distribution of eddies of each time step, but also events or phenomena of eddies. However, previous methods cannot precisely detect eddies, especially, during the events such as eddies' amalgamation, bifurcation. In the present study, we propose a new approach of eddy's detection, tracking and event visualization based on sea surface height (SSH) and velocity field. The proposed method detects eddies region as well as streams and currents region, and classifies detected eddies into several types. By tracking the time-varying change of classified eddies, it is possible to detect not only eddies event such as amalgamation and bifurcation but also the interaction between eddy and ocean current. As a result of visualizing detected eddies and events, we succeeded in creating the movie which enables us to intuitively understand the region of interest.

  19. Event Detection in Aerospace Systems using Centralized Sensor Networks: A Comparative Study of Several Methodologies

    NASA Technical Reports Server (NTRS)

    Mehr, Ali Farhang; Sauvageon, Julien; Agogino, Alice M.; Tumer, Irem Y.

    2006-01-01

    Recent advances in micro electromechanical systems technology, digital electronics, and wireless communications have enabled development of low-cost, low-power, multifunctional miniature smart sensors. These sensors can be deployed throughout a region in an aerospace vehicle to build a network for measurement, detection and surveillance applications. Event detection using such centralized sensor networks is often regarded as one of the most promising health management technologies in aerospace applications where timely detection of local anomalies has a great impact on the safety of the mission. In this paper, we propose to conduct a qualitative comparison of several local event detection algorithms for centralized redundant sensor networks. The algorithms are compared with respect to their ability to locate and evaluate an event in the presence of noise and sensor failures for various node geometries and densities.

  20. Patients with mild cognitive impairment have an abnormal upper-alpha event-related desynchronization/synchronization (ERD/ERS) during a task of temporal attention.

    PubMed

    Caravaglios, Giuseppe; Muscoso, Emma Gabriella; Di Maria, Giulia; Costanzo, Erminio

    2015-03-01

    There are several evidences indicating that an impairment in attention-executive functions is present in prodromal Alzheimer's disease and predict future global cognitive decline. In particular, the issue of temporal orienting of attention in patients with mild cognitive impairment (MCI) due to Alzheimer's disease has been overlooked. The present research aimed to explore whether subtle deficits of cortical activation are present in these patients early in the course of the disease. We studied the upper-alpha event-related synchronization/desynchronization phenomenon during a paradigm of temporal orientation of attention. MCI patients (n = 27) and healthy elderly controls (n = 15) performed a task in which periodically omitted tones had to be predicted and their virtual onset time had to be marked by pressing a button. Single-trial responses were measured, respectively, before and after the motor response. Then, upper-alpha responses were compared to upper-alpha power during eyes-closed resting state. The time course of the task was characterized by two different behavioral conditions: (1) a pre-event epoch, in which the subject awaited the virtual onset of the omitted tone, (2) a post-event epoch (after button pressing), in which the subject was in a post-motor response condition. The principal findings are: (1) during the waiting epoch, only healthy elderly had an upper-alpha ERD at the level of both temporal and posterior brain regions; (2) during the post-motor epoch, the aMCI patients had a weaker upper-alpha ERS on prefrontal regions; (3) only healthy elderly showed a laterality effect: (a) during the waiting epoch, the upper-alpha ERD was greater at the level of the right posterior-temporal lead; during the post-motor epoch, the upper alpha ERS was greater on the left prefrontal lead. The relevance of these findings is that the weaker upper-alpha response observed in aMCI patients is evident even if the accuracy of the behavioral performance (i.e., button

  1. Cooperative object tracking and composite event detection with wireless embedded smart cameras.

    PubMed

    Wang, Youlu; Velipasalar, Senem; Casares, Mauricio

    2010-10-01

    Embedded smart cameras have limited processing power, memory, energy, and bandwidth. Thus, many system- and algorithm-wise challenges remain to be addressed to have operational, battery-powered wireless smart-camera networks. We present a wireless embedded smart-camera system for cooperative object tracking and detection of composite events spanning multiple camera views. Each camera is a CITRIC mote consisting of a camera board and wireless mote. Lightweight and robust foreground detection and tracking algorithms are implemented on the camera boards. Cameras exchange small-sized data wirelessly in a peer-to-peer manner. Instead of transferring or saving every frame or trajectory, events of interest are detected. Simpler events are combined in a time sequence to define semantically higher-level events. Event complexity can be increased by increasing the number of primitives and/or number of camera views they span. Examples of consistently tracking objects across different cameras, updating location of occluded/lost objects from other cameras, and detecting composite events spanning two or three camera views, are presented. All the processing is performed on camera boards. Operating current plots of smart cameras, obtained when performing different tasks, are also presented. Power consumption is analyzed based upon these measurements. PMID:20551001

  2. Assessing the Probability of Detection of Horizontal Gene Transfer Events in Bacterial Populations

    PubMed Central

    Townsend, Jeffrey P.; Bøhn, Thomas; Nielsen, Kaare Magne

    2012-01-01

    Experimental approaches to identify horizontal gene transfer (HGT) events of non-mobile DNA in bacteria have typically relied on detection of the initial transformants or their immediate offspring. However, rare HGT events occurring in large and structured populations are unlikely to be detected in a short time frame. Population genetic modeling of the growth dynamics of bacterial genotypes is therefore necessary to account for natural selection and genetic drift during the time lag and to predict realistic time frames for detection with a given sampling design. Here we draw on statistical approaches to population genetic theory to construct a cohesive probabilistic framework for investigation of HGT of exogenous DNA into bacteria. In particular, the stochastic timing of rare HGT events is accounted for. Integrating over all possible event timings, we provide an equation for the probability of detection, given that HGT actually occurred. Furthermore, we identify the key variables determining the probability of detecting HGT events in four different case scenarios that are representative of bacterial populations in various environments. Our theoretical analysis provides insight into the temporal aspects of dissemination of genetic material, such as antibiotic resistance genes or transgenes present in genetically modified organisms. Due to the long time scales involved and the exponential growth of bacteria with differing fitness, quantitative analyses incorporating bacterial generation time, and levels of selection, such as the one presented here, will be a necessary component of any future experimental design and analysis of HGT as it occurs in natural settings. PMID:22363321

  3. Assessing the probability of detection of horizontal gene transfer events in bacterial populations.

    PubMed

    Townsend, Jeffrey P; Bøhn, Thomas; Nielsen, Kaare Magne

    2012-01-01

    Experimental approaches to identify horizontal gene transfer (HGT) events of non-mobile DNA in bacteria have typically relied on detection of the initial transformants or their immediate offspring. However, rare HGT events occurring in large and structured populations are unlikely to be detected in a short time frame. Population genetic modeling of the growth dynamics of bacterial genotypes is therefore necessary to account for natural selection and genetic drift during the time lag and to predict realistic time frames for detection with a given sampling design. Here we draw on statistical approaches to population genetic theory to construct a cohesive probabilistic framework for investigation of HGT of exogenous DNA into bacteria. In particular, the stochastic timing of rare HGT events is accounted for. Integrating over all possible event timings, we provide an equation for the probability of detection, given that HGT actually occurred. Furthermore, we identify the key variables determining the probability of detecting HGT events in four different case scenarios that are representative of bacterial populations in various environments. Our theoretical analysis provides insight into the temporal aspects of dissemination of genetic material, such as antibiotic resistance genes or transgenes present in genetically modified organisms. Due to the long time scales involved and the exponential growth of bacteria with differing fitness, quantitative analyses incorporating bacterial generation time, and levels of selection, such as the one presented here, will be a necessary component of any future experimental design and analysis of HGT as it occurs in natural settings.

  4. 3He-Rich SEP Events Detected by EPHIN 1996-2000

    NASA Astrophysics Data System (ADS)

    Gómez-Herrero, R.; Rodríguez-Frías, D.; Del Peral, L.; Sequeiros, J.; Gutiérrez, J.; Müller-Mellin, R.; Kunow, H.

    2003-07-01

    Thirteen 3 He-rich impulsive events have been identified in EPHIN data between 1996 and 2000. Energy spectra, abundance ratios, and association with solar activity have been evaluated. association with radio bursts I I I-type has been observed for all of them, but solar flare association has been found only for 8 of them. No acceleration above 30 MeV/nucleon has been appreciated. No deuterium has been detected for any event under study.

  5. On-line Machine Learning and Event Detection in Petascale Data Streams

    NASA Astrophysics Data System (ADS)

    Thompson, David R.; Wagstaff, K. L.

    2012-01-01

    Traditional statistical data mining involves off-line analysis in which all data are available and equally accessible. However, petascale datasets have challenged this premise since it is often impossible to store, let alone analyze, the relevant observations. This has led the machine learning community to investigate adaptive processing chains where data mining is a continuous process. Here pattern recognition permits triage and followup decisions at multiple stages of a processing pipeline. Such techniques can also benefit new astronomical instruments such as the Large Synoptic Survey Telescope (LSST) and Square Kilometre Array (SKA) that will generate petascale data volumes. We summarize some machine learning perspectives on real time data mining, with representative cases of astronomical applications and event detection in high volume datastreams. The first is a "supervised classification" approach currently used for transient event detection at the Very Long Baseline Array (VLBA). It injects known signals of interest - faint single-pulse anomalies - and tunes system parameters to recover these events. This permits meaningful event detection for diverse instrument configurations and observing conditions whose noise cannot be well-characterized in advance. Second, "semi-supervised novelty detection" finds novel events based on statistical deviations from previous patterns. It detects outlier signals of interest while considering known examples of false alarm interference. Applied to data from the Parkes pulsar survey, the approach identifies anomalous "peryton" phenomena that do not match previous event models. Finally, we consider online light curve classification that can trigger adaptive followup measurements of candidate events. Classifier performance analyses suggest optimal survey strategies, and permit principled followup decisions from incomplete data. These examples trace a broad range of algorithm possibilities available for online astronomical data

  6. A canonical correlation analysis based method for contamination event detection in water sources.

    PubMed

    Li, Ruonan; Liu, Shuming; Smith, Kate; Che, Han

    2016-06-15

    In this study, a general framework integrating a data-driven estimation model is employed for contamination event detection in water sources. Sequential canonical correlation coefficients are updated in the model using multivariate water quality time series. The proposed method utilizes canonical correlation analysis for studying the interplay between two sets of water quality parameters. The model is assessed by precision, recall and F-measure. The proposed method is tested using data from a laboratory contaminant injection experiment. The proposed method could detect a contamination event 1 minute after the introduction of 1.600 mg l(-1) acrylamide solution. With optimized parameter values, the proposed method can correctly detect 97.50% of all contamination events with no false alarms. The robustness of the proposed method can be explained using the Bauer-Fike theorem. PMID:27264637

  7. Detecting deception in children: an experimental study of the effect of event familiarity on CBCA ratings.

    PubMed

    Blandon-Gitlin, Iris; Pezdek, Kathy; Rogers, Martha; Brodie, Laura

    2005-04-01

    The CBCA is the most commonly used deception detection. technique worldwide. Pezdek et al. (2004) used a quasi-experimental design to assess children's accounts of a traumatic medical procedure; CBCA ratings were higher for descriptions of familiar than unfamiliar events. This study tested this effect using an experimental design and assessed the joint effect of familiarity and veracity on CBCA ratings. Children described a true or a fabricated event. Half described a familiar event; half described an unfamiliar event. Two CBCA-trained judges rated transcripts of the descriptions. CBCA scores were more strongly influenced by the familiarity than the actual veracity of the event, and CBCA scores were significantly correlated with age. CBCA results were compared with results from other measures. Together with the results of K. Pezdek et al. (2004) these findings suggest that in its current form, CBCA is of limited utility as a credibility assessment tool. PMID:15912723

  8. Spectrum of brain abnormalities detected on whole body F-18 FDG PET/CT in patients undergoing evaluation for non-CNS malignancies

    PubMed Central

    Tripathi, Madhavi; Jaimini, Abhinav; D’Souza, Maria M; Sharma, Rajnish; Jain, Jyotika; Garg, Gunjan; Singh, Dinesh; Kumar, Nitin; Mishra, Anil K; Grover, Rajesh K; Mondal, Anupam

    2011-01-01

    We present the pattern of metabolic brain abnormalities detected in patients undergoing whole body (WB) F-18 flurodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) examination for non-central nervous system (CNS) malignancies. Knowledge of the PET/CT appearance of various intracranial metabolic abnormalities enables correct interpretation of PET scans in oncological patients where differentiation of metastasis from benign intracranial pathologies is important and improves specificity of the PET study. A complete clinical history and correlation with CT and MRI greatly helps in arriving at a correct imaging diagnosis. PMID:22174526

  9. Anomalous optical events detected by rocket-borne sensor in the WIPP campaign

    NASA Technical Reports Server (NTRS)

    Li, Ya QI; Holzworth, Robert H.; Hu, Hua; Mccarthy, Michael; Massey, R. Dayle

    1991-01-01

    This paper describes the instruments used in the Wave Induced Particle Precipitation campaign in 1987, in which one rocket and four balloons were launched near thunderstorms from the NASA Wallops Flight Facility. Examples of both the lightning events and the anomalous optical events (AOEs) detected on July 31, 1987 are presented. It is shown that the signatures of these AOEs differ from those of well-known optical sources in the atmosphere. It was found that AOEs were sometimes associated with subionospheric VLF signal perturbations (Trimpi events), suggesting a possibility that AOEs might be linked to a disturbance of the electron concentration in the high-altitude atmosphere or lower ionosphere.

  10. Automated detection of apnea/hypopnea events in healthy children polysomnograms: preliminary results.

    PubMed

    Held, Claudio M; Causa, Leonardo; Jaillet, Fabrice; Chamorro, Rodrigo; Garrido, Marcelo; Algarin, Cecilia; Peirano, Patricio

    2013-01-01

    A methodology to detect sleep apnea/hypopnea events in the respiratory signals of polysomnographic recordings is presented. It applies empirical mode decomposition (EMD), Hilbert-Huang transform (HHT), fuzzy logic and signal preprocessing techniques for feature extraction, expert criteria and context analysis. EMD, HHT and fuzzy logic are used for artifact detection and preliminary detection of respiration signal zones with significant variations in the amplitude of the signal; feature extraction, expert criteria and context analysis are used to characterize and validate the respiratory events. An annotated database of 30 all-night polysomnographic recordings, acquired from 30 healthy ten-year-old children, was divided in a training set of 15 recordings (485 sleep apnea/hypopnea events), a validation set of five recordings (109 sleep apnea/hypopnea events), and a testing set of ten recordings (281 sleep apnea/hypopnea events). The overall detection performance on the testing data set was 89.7% sensitivity and 16.3% false-positive rate. The next step is to include discrimination among apneas, hypopneas and respiratory pauses.

  11. Impulsive 3He-rich Solar Energetic Particle Events detected with EPHIN

    NASA Astrophysics Data System (ADS)

    Rodriguez-Frias, M. D.; Gomez-Herrero, R.; del Peral, L.; Sequeiros, J.; Kunow, H.; Mueller-Mellin, R.

    2001-08-01

    We report observation of 3 He-rich solar energetic particles (SEP) events detected by Electron Proton and Helium Instrument (EPHIN) aboard the Solar and Heliospheric Observatory (SOHO) spacecraft. EPHIN has been detecting Helium isotopes in the energy range 4-53 MeV/n since December 1995 using a ˜E-E sensor system with solid-state detectors. In this paper we concentrate on observations of SEP with excess in the 3 He abundance. The abundances 3 He/4 He and 4 He/1 H have been obtained and compared among different events. Energy spectra of protons, 3 He, 4 He have been studied.

  12. Method for detecting binding events using micro-X-ray fluorescence spectrometry

    DOEpatents

    Warner, Benjamin P.; Havrilla, George J.; Mann, Grace

    2010-12-28

    Method for detecting binding events using micro-X-ray fluorescence spectrometry. Receptors are exposed to at least one potential binder and arrayed on a substrate support. Each member of the array is exposed to X-ray radiation. The magnitude of a detectable X-ray fluorescence signal for at least one element can be used to determine whether a binding event between a binder and a receptor has occurred, and can provide information related to the extent of binding between the binder and receptor.

  13. Application of the FICTION technique for the simultaneous detection of immunophenotype and chromosomal abnormalities in routinely fixed, paraffin wax embedded bone marrow trephines.

    PubMed

    Korac, P; Jones, M; Dominis, M; Kusec, R; Mason, D Y; Banham, A H; Ventura, R A

    2005-12-01

    The use of interphase fluorescence in situ hybridisation (FISH) to study cytogenetic abnormalities in routinely fixed paraffin wax embedded tissue has become commonplace over the past decade. However, very few studies have applied FISH to routinely fixed bone marrow trephines (BMTs). This may be because of the acid based decalcification methods that are commonly used during the processing of BMTs, which may adversely affect the suitability of the sample for FISH analysis. For the first time, this report describes the simultaneous application of FISH and immunofluorescent staining (the FICTION technique) to formalin fixed, EDTA decalcified and paraffin wax embedded BMTs. This technique allows the direct correlation of genetic abnormalities to immunophenotype, and therefore will be particularly useful for the identification of genetic abnormalities in specific tumour cells present in BMTs. The application of this to routine clinical practice will assist diagnosis and the detection of minimal residual disease.

  14. Detection of invisible and crucial events: from seismic fluctuations to the war against terrorism

    NASA Astrophysics Data System (ADS)

    Allegrini, Paolo; Fronzoni, Leone; Grigolini, Paolo; Latora, Vito; Mega, Mirko S.; Palatella, Luigi; Rapisarda, Andrea; Vinciguerra, Sergio

    2004-04-01

    We prove the efficiency of a new method for the detection of crucial events that might have useful applications to the war against terrorism. This has to do with the search for rare but significant events, a theme of research that has been made of extreme importance by the tragedy of September 11. This method is applied here to defining the statistics of seismic main-shocks, as done in cond-mat/0212529. The emphasis here is on the conceptual issues behind the results obtained in cond-mat/0212529 than on geophysics. This discussion suggests that the method has a wider range of validity. We support this general discussion with a dynamic model originally proposed in cond-mat/0107597 for purposes different from geophysical applications. However, it is a case where the crucial events to detect are under our control, thereby making it possible for us to check the accuracy of the method of detection of invisible and crucial events that we propose here for a general purpose, including the war against terrorism. For this model an analytical treatment has been recently found [cond-mat/0209038], supporting the claims that we make in this paper for the accuracy of the method of detection. For the reader's convenience, the results on the seismic fluctuations are suitably reviewed, and discussed in the light of the more general perspective of this paper. We also review the model for seismic fluctuations, proposed in the earlier work of cond-mat/0212529. This model shares with the model of cond-mat/0107597 the property that the crucial events are imbedded in a sea of secondary events, but it allows us to reveal with accuracy the statistics of the crucial events for different mathematical reasons.

  15. Can Signal Abnormalities Detected with MR Imaging in Knee Articular Cartilage Be Used to Predict Development of Morphologic Cartilage Defects? 48-Month Data from the Osteoarthritis Initiative.

    PubMed

    Schwaiger, Benedikt J; Gersing, Alexandra S; Mbapte Wamba, John; Nevitt, Michael C; McCulloch, Charles E; Link, Thomas M

    2016-10-01

    more likely in any of the subgrades (P = .98) and was significantly associated with progression of bone marrow abnormalities (P = .002). Conclusion Knee cartilage signal abnormalities detected with MR imaging are precursors of morphologic defects with osteoarthritis and may serve as imaging biomarkers with which to assess risk for cartilage degeneration. (©) RSNA, 2016.

  16. Why conventional detection methods fail in identifying the existence of contamination events.

    PubMed

    Liu, Shuming; Li, Ruonan; Smith, Kate; Che, Han

    2016-04-15

    Early warning systems are widely used to safeguard water security, but their effectiveness has raised many questions. To understand why conventional detection methods fail to identify contamination events, this study evaluates the performance of three contamination detection methods using data from a real contamination accident and two artificial datasets constructed using a widely applied contamination data construction approach. Results show that the Pearson correlation Euclidean distance (PE) based detection method performs better for real contamination incidents, while the Euclidean distance method (MED) and linear prediction filter (LPF) method are more suitable for detecting sudden spike-like variation. This analysis revealed why the conventional MED and LPF methods failed to identify existence of contamination events. The analysis also revealed that the widely used contamination data construction approach is misleading.

  17. Why conventional detection methods fail in identifying the existence of contamination events.

    PubMed

    Liu, Shuming; Li, Ruonan; Smith, Kate; Che, Han

    2016-04-15

    Early warning systems are widely used to safeguard water security, but their effectiveness has raised many questions. To understand why conventional detection methods fail to identify contamination events, this study evaluates the performance of three contamination detection methods using data from a real contamination accident and two artificial datasets constructed using a widely applied contamination data construction approach. Results show that the Pearson correlation Euclidean distance (PE) based detection method performs better for real contamination incidents, while the Euclidean distance method (MED) and linear prediction filter (LPF) method are more suitable for detecting sudden spike-like variation. This analysis revealed why the conventional MED and LPF methods failed to identify existence of contamination events. The analysis also revealed that the widely used contamination data construction approach is misleading. PMID:26905801

  18. Autonomous Detection of Eruptions, Plumes, and Other Transient Events in the Outer Solar System

    NASA Astrophysics Data System (ADS)

    Bunte, M. K.; Lin, Y.; Saripalli, S.; Bell, J. F.

    2012-12-01

    The outer solar system abounds with visually stunning examples of dynamic processes such as eruptive events that jettison materials from satellites and small bodies into space. The most notable examples of such events are the prominent volcanic plumes of Io, the wispy water jets of Enceladus, and the outgassing of comet nuclei. We are investigating techniques that will allow a spacecraft to autonomously detect those events in visible images. This technique will allow future outer planet missions to conduct sustained event monitoring and automate prioritization of data for downlink. Our technique detects plumes by searching for concentrations of large local gradients in images. Applying a Scale Invariant Feature Transform (SIFT) to either raw or calibrated images identifies interest points for further investigation based on the magnitude and orientation of local gradients in pixel values. The interest points are classified as possible transient geophysical events when they share characteristics with similar features in user-classified images. A nearest neighbor classification scheme assesses the similarity of all interest points within a threshold Euclidean distance and classifies each according to the majority classification of other interest points. Thus, features marked by multiple interest points are more likely to be classified positively as events; isolated large plumes or multiple small jets are easily distinguished from a textured background surface due to the higher magnitude gradient of the plume or jet when compared with the small, randomly oriented gradients of the textured surface. We have applied this method to images of Io, Enceladus, and comet Hartley 2 from the Voyager, Galileo, New Horizons, Cassini, and Deep Impact EPOXI missions, where appropriate, and have successfully detected up to 95% of manually identifiable events that our method was able to distinguish from the background surface and surface features of a body. Dozens of distinct features

  19. Wenchuan Event Detection And Localization Using Waveform Correlation Coupled With Double Difference

    NASA Astrophysics Data System (ADS)

    Slinkard, M.; Heck, S.; Schaff, D. P.; Young, C. J.; Richards, P. G.

    2014-12-01

    The well-studied Wenchuan aftershock sequence triggered by the May 12, 2008, Ms 8.0, mainshock offers an ideal test case for evaluating the effectiveness of using waveform correlation coupled with double difference relocation to detect and locate events in a large aftershock sequence. We use Sandia's SeisCorr detector to process 3 months of data recorded by permanent IRIS and temporary ASCENT stations using templates from events listed in a global catalog to find similar events in the raw data stream. Then we take the detections and relocate them using the double difference method. We explore both the performance that can be expected with using just a small number of stations, and, the benefits of reprocessing a well-studied sequence such as this one using waveform correlation to find even more events. We benchmark our results against previously published results describing relocations of regional catalog data. Before starting this project, we had examples where with just a few stations at far-regional distances, waveform correlation combined with double difference did and impressive job of detection and location events with precision at the few hundred and even tens of meters level.

  20. Secure Access Control and Large Scale Robust Representation for Online Multimedia Event Detection

    PubMed Central

    Liu, Changyu; Li, Huiling

    2014-01-01

    We developed an online multimedia event detection (MED) system. However, there are a secure access control issue and a large scale robust representation issue when we want to integrate traditional event detection algorithms into the online environment. For the first issue, we proposed a tree proxy-based and service-oriented access control (TPSAC) model based on the traditional role based access control model. Verification experiments were conducted on the CloudSim simulation platform, and the results showed that the TPSAC model is suitable for the access control of dynamic online environments. For the second issue, inspired by the object-bank scene descriptor, we proposed a 1000-object-bank (1000OBK) event descriptor. Feature vectors of the 1000OBK were extracted from response pyramids of 1000 generic object detectors which were trained on standard annotated image datasets, such as the ImageNet dataset. A spatial bag of words tiling approach was then adopted to encode these feature vectors for bridging the gap between the objects and events. Furthermore, we performed experiments in the context of event classification on the challenging TRECVID MED 2012 dataset, and the results showed that the robust 1000OBK event descriptor outperforms the state-of-the-art approaches. PMID:25147840

  1. Secure access control and large scale robust representation for online multimedia event detection.

    PubMed

    Liu, Changyu; Lu, Bin; Li, Huiling

    2014-01-01

    We developed an online multimedia event detection (MED) system. However, there are a secure access control issue and a large scale robust representation issue when we want to integrate traditional event detection algorithms into the online environment. For the first issue, we proposed a tree proxy-based and service-oriented access control (TPSAC) model based on the traditional role based access control model. Verification experiments were conducted on the CloudSim simulation platform, and the results showed that the TPSAC model is suitable for the access control of dynamic online environments. For the second issue, inspired by the object-bank scene descriptor, we proposed a 1000-object-bank (1000OBK) event descriptor. Feature vectors of the 1000OBK were extracted from response pyramids of 1000 generic object detectors which were trained on standard annotated image datasets, such as the ImageNet dataset. A spatial bag of words tiling approach was then adopted to encode these feature vectors for bridging the gap between the objects and events. Furthermore, we performed experiments in the context of event classification on the challenging TRECVID MED 2012 dataset, and the results showed that the robust 1000OBK event descriptor outperforms the state-of-the-art approaches.

  2. Testing the ability of different seismic detections approaches to monitor aftershocks following a moderate magnitude event.

    NASA Astrophysics Data System (ADS)

    Romero, Paula; Díaz, Jordi; Ruiz, Mario; Cantavella, Juan Vicente; Gomez-García, Clara

    2016-04-01

    The detection and picking of seismic events is a permanent concern for seismic surveying, in particular when dealing with aftershocks of moderate magnitude events. Many efforts have been done to find the balance between computer efficiency and the robustness of the detection methods. In this work, data recorded by a high density seismic network deployed following a 5.2 magnitude event located close to Albacete, SE Spain, is used to test the ability of classical and recently proposed detection methodologies. Two days after the main shock, occurred the 23th February, a network formed by 11 stations from ICTJA-CSIC and 2 stations from IGN were deployed over the region, with inter-station distances ranging between 5 and 10 km. The network remained in operation until April 6th, 2015 and allowed to manually identify up to 552 events with magnitudes from 0.2 to 3.5 located in an area of just 25 km2 inside the network limits. The detection methods here studied applied are the classical STA/LTA, a power spectral method, a detector based in the Benford's law and a waveform similarity method. The STA/LTA method, based in the comparison of background noise and seismic signal amplitudes, is taken as a reference to evaluate the results arising from the other approaches. The power spectral density method is based in the inspection of the characteristic frequency pattern associated to seismic events. The Benford's Law detector analyses the distribution of the first-digit of displacement count in the histogram of a seismic waveform, considering that only the windows containing seismic wave arrivals will match the logarithmic law. Finally, the waveform similarity method is based in the analysis of the normalized waveform amplitude, detecting those events with waveform similar to a previously defined master event. The aim of this contribution is to inspect the ability of the different approaches to accurately detect the aftershocks events for this kind of seismic crisis and to

  3. Detection and identification of multiple genetically modified events using DNA insert fingerprinting.

    PubMed

    Raymond, Philippe; Gendron, Louis; Khalf, Moustafa; Paul, Sylvianne; Dibley, Kim L; Bhat, Somanath; Xie, Vicki R D; Partis, Lina; Moreau, Marie-Eve; Dollard, Cheryl; Coté, Marie-José; Laberge, Serge; Emslie, Kerry R

    2010-03-01

    Current screening and event-specific polymerase chain reaction (PCR) assays for the detection and identification of genetically modified organisms (GMOs) in samples of unknown composition or for the detection of non-regulated GMOs have limitations, and alternative approaches are required. A transgenic DNA fingerprinting methodology using restriction enzyme digestion, adaptor ligation, and nested PCR was developed where individual GMOs are distinguished by the characteristic fingerprint pattern of the fragments generated. The inter-laboratory reproducibility of the amplified fragment sizes using different capillary electrophoresis platforms was compared, and reproducible patterns were obtained with an average difference in fragment size of 2.4 bp. DNA insert fingerprints for 12 different maize events, including two maize hybrids and one soy event, were generated that reflected the composition of the transgenic DNA constructs. Once produced, the fingerprint profiles were added to a database which can be readily exchanged and shared between laboratories. This approach should facilitate the process of GMO identification and characterization.

  4. Detecting Continuity Violations in Infancy: A New Account and New Evidence from Covering and Tube Events

    ERIC Educational Resources Information Center

    Wang, S.h.; Baillargeon, R.; Paterson, S.

    2005-01-01

    Recent research on infants' responses to occlusion and containment events indicates that, although some violations of the continuity principle are detected at an early age e.g. Aguiar, A., & Baillargeon, R. (1999). 2.5-month-old infants' reasoning about when objects should and should not be occluded. Cognitive Psychology 39, 116-157; Hespos, S.…

  5. A novel seizure detection algorithm informed by hidden Markov model event states

    NASA Astrophysics Data System (ADS)

    Baldassano, Steven; Wulsin, Drausin; Ung, Hoameng; Blevins, Tyler; Brown, Mesha-Gay; Fox, Emily; Litt, Brian

    2016-06-01

    Objective. Recently the FDA approved the first responsive, closed-loop intracranial device to treat epilepsy. Because these devices must respond within seconds of seizure onset and not miss events, they are tuned to have high sensitivity, leading to frequent false positive stimulations and decreased battery life. In this work, we propose a more robust seizure detection model. Approach. We use a Bayesian nonparametric Markov switching process to parse intracranial EEG (iEEG) data into distinct dynamic event states. Each event state is then modeled as a multidimensional Gaussian distribution to allow for predictive state assignment. By detecting event states highly specific for seizure onset zones, the method can identify precise regions of iEEG data associated with the transition to seizure activity, reducing false positive detections associated with interictal bursts. The seizure detection algorithm was translated to a real-time application and validated in a small pilot study using 391 days of continuous iEEG data from two dogs with naturally occurring, multifocal epilepsy. A feature-based seizure detector modeled after the NeuroPace RNS System was developed as a control. Main results. Our novel seizure detection method demonstrated an improvement in false negative rate (0/55 seizures missed versus 2/55 seizures missed) as well as a significantly reduced false positive rate (0.0012 h versus 0.058 h‑1). All seizures were detected an average of 12.1 ± 6.9 s before the onset of unequivocal epileptic activity (unequivocal epileptic onset (UEO)). Significance. This algorithm represents a computationally inexpensive, individualized, real-time detection method suitable for implantable antiepileptic devices that may considerably reduce false positive rate relative to current industry standards.

  6. A novel seizure detection algorithm informed by hidden Markov model event states

    NASA Astrophysics Data System (ADS)

    Baldassano, Steven; Wulsin, Drausin; Ung, Hoameng; Blevins, Tyler; Brown, Mesha-Gay; Fox, Emily; Litt, Brian

    2016-06-01

    Objective. Recently the FDA approved the first responsive, closed-loop intracranial device to treat epilepsy. Because these devices must respond within seconds of seizure onset and not miss events, they are tuned to have high sensitivity, leading to frequent false positive stimulations and decreased battery life. In this work, we propose a more robust seizure detection model. Approach. We use a Bayesian nonparametric Markov switching process to parse intracranial EEG (iEEG) data into distinct dynamic event states. Each event state is then modeled as a multidimensional Gaussian distribution to allow for predictive state assignment. By detecting event states highly specific for seizure onset zones, the method can identify precise regions of iEEG data associated with the transition to seizure activity, reducing false positive detections associated with interictal bursts. The seizure detection algorithm was translated to a real-time application and validated in a small pilot study using 391 days of continuous iEEG data from two dogs with naturally occurring, multifocal epilepsy. A feature-based seizure detector modeled after the NeuroPace RNS System was developed as a control. Main results. Our novel seizure detection method demonstrated an improvement in false negative rate (0/55 seizures missed versus 2/55 seizures missed) as well as a significantly reduced false positive rate (0.0012 h versus 0.058 h-1). All seizures were detected an average of 12.1 ± 6.9 s before the onset of unequivocal epileptic activity (unequivocal epileptic onset (UEO)). Significance. This algorithm represents a computationally inexpensive, individualized, real-time detection method suitable for implantable antiepileptic devices that may considerably reduce false positive rate relative to current industry standards.

  7. Low time resolution analysis of polar ice cores cannot detect impulsive nitrate events

    NASA Astrophysics Data System (ADS)

    Smart, D. F.; Shea, M. A.; Melott, A. L.; Laird, C. M.

    2014-12-01

    Ice cores are archives of climate change and possibly large solar proton events (SPEs). Wolff et al. (2012) used a single event, a nitrate peak in the GISP2-H core, which McCracken et al. (2001a) time associated with the poorly quantified 1859 Carrington event, to discredit SPE-produced, impulsive nitrate deposition in polar ice. This is not the ideal test case. We critique the Wolff et al. analysis and demonstrate that the data they used cannot detect impulsive nitrate events because of resolution limitations. We suggest reexamination of the top of the Greenland ice sheet at key intervals over the last two millennia with attention to fine resolution and replicate sampling of multiple species. This will allow further insight into polar depositional processes on a subseasonal scale, including atmospheric sources, transport mechanisms to the ice sheet, postdepositional interactions, and a potential SPE association.

  8. Valvular Abnormalities Detected by Echocardiography in 5-Year Survivors of Childhood Cancer: A Long-Term Follow-Up Study

    SciTech Connect

    Pal, Helena J. van der; Caron, Huib N.; Kremer, Leontien C.; Dalen, Elvira C. van

    2015-01-01

    Purpose: To determine the prevalence of valvular abnormalities after radiation therapy involving the heart region and/or treatment with anthracyclines and to identify associated risk factors in a large cohort of 5-year childhood cancer survivors (CCS). Methods and Materials: The study cohort consisted of all 626 eligible 5-year CCS diagnosed with childhood cancer in the Emma Children's Hospital/Academic Medical Center between 1966 and 1996 and treated with radiation therapy involving the heart region and/or anthracyclines. We determined the presence of valvular abnormalities according to echocardiograms. Physical radiation dose was converted into the equivalent dose in 2-Gy fractions (EQD{sub 2}). Using multivariable logistic regression analyses, we examined the associations between cancer treatment and valvular abnormalities. Results: We identified 225 mainly mild echocardiographic valvular abnormalities in 169 of 545 CCS (31%) with a cardiac assessment (median follow-up time, 14.9 years [range, 5.1-36.8 years]; median attained age 22.0 years [range, 7.0-49.7 years]). Twenty-four CCS (4.4%) had 31 moderate or higher-graded abnormalities. Most common abnormalities were tricuspid valve disorders (n=119; 21.8%) and mitral valve disorders (n=73; 13.4%). The risk of valvular abnormalities was associated with increasing radiation dose (using EQD{sub 2}) involving the heart region (odds ratio 1.33 per 10 Gy) and the presence of congenital heart disease (odds ratio 3.43). We found no statistically significant evidence that anthracyclines increase the risk. Conclusions: Almost one-third of CCS treated with potentially cardiotoxic therapy had 1 or more asymptomatic, mostly mild valvular abnormalities after a median follow-up of nearly 15 years. The most important risk factors are higher EQD{sub 2} to the heart region and congenital heart disease. Studies with longer follow-up are necessary to investigate the clinical course of asymptomatic valvular abnormalities in

  9. Meiotic abnormalities

    SciTech Connect

    1993-12-31

    Chapter 19, describes meiotic abnormalities. These include nondisjunction of autosomes and sex chromosomes, genetic and environmental causes of nondisjunction, misdivision of the centromere, chromosomally abnormal human sperm, male infertility, parental age, and origin of diploid gametes. 57 refs., 2 figs., 1 tab.

  10. Pre-trained D-CNN models for detecting complex events in unconstrained videos

    NASA Astrophysics Data System (ADS)

    Robinson, Joseph P.; Fu, Yun

    2016-05-01

    Rapid event detection faces an emergent need to process large videos collections; whether surveillance videos or unconstrained web videos, the ability to automatically recognize high-level, complex events is a challenging task. Motivated by pre-existing methods being complex, computationally demanding, and often non-replicable, we designed a simple system that is quick, effective and carries minimal overhead in terms of memory and storage. Our system is clearly described, modular in nature, replicable on any Desktop, and demonstrated with extensive experiments, backed by insightful analysis on different Convolutional Neural Networks (CNNs), as stand-alone and fused with others. With a large corpus of unconstrained, real-world video data, we examine the usefulness of different CNN models as features extractors for modeling high-level events, i.e., pre-trained CNNs that differ in architectures, training data, and number of outputs. For each CNN, we use 1-fps from all training exemplar to train one-vs-rest SVMs for each event. To represent videos, frame-level features were fused using a variety of techniques. The best being to max-pool between predetermined shot boundaries, then average-pool to form the final video-level descriptor. Through extensive analysis, several insights were found on using pre-trained CNNs as off-the-shelf feature extractors for the task of event detection. Fusing SVMs of different CNNs revealed some interesting facts, finding some combinations to be complimentary. It was concluded that no single CNN works best for all events, as some events are more object-driven while others are more scene-based. Our top performance resulted from learning event-dependent weights for different CNNs.

  11. Detection and analysis of microseismic events using a Matched Filtering Algorithm (MFA)

    NASA Astrophysics Data System (ADS)

    Caffagni, Enrico; Eaton, David W.; Jones, Joshua P.; van der Baan, Mirko

    2016-07-01

    A new Matched Filtering Algorithm (MFA) is proposed for detecting and analysing microseismic events recorded by downhole monitoring of hydraulic fracturing. This method requires a set of well-located template (`parent') events, which are obtained using conventional microseismic processing and selected on the basis of high signal-to-noise (S/N) ratio and representative spatial distribution of the recorded microseismicity. Detection and extraction of `child' events are based on stacked, multichannel cross-correlation of the continuous waveform data, using the parent events as reference signals. The location of a child event relative to its parent is determined using an automated process, by rotation of the multicomponent waveforms into the ray-centred co-ordinates of the parent and maximizing the energy of the stacked amplitude envelope within a search volume around the parent's hypocentre. After correction for geometrical spreading and attenuation, the relative magnitude of the child event is obtained automatically using the ratio of stacked envelope peak with respect to its parent. Since only a small number of parent events require interactive analysis such as picking P- and S-wave arrivals, the MFA approach offers the potential for significant reduction in effort for downhole microseismic processing. Our algorithm also facilitates the analysis of single-phase child events, that is, microseismic events for which only one of the S- or P-wave arrivals is evident due to unfavourable S/N conditions. A real-data example using microseismic monitoring data from four stages of an open-hole slickwater hydraulic fracture treatment in western Canada demonstrates that a sparse set of parents (in this case, 4.6 per cent of the originally located events) yields a significant (more than fourfold increase) in the number of located events compared with the original catalogue. Moreover, analysis of the new MFA catalogue suggests that this approach leads to more robust interpretation

  12. Remote monitoring of cardiovascular implantable devices in the pediatric population improves detection of adverse events.

    PubMed

    Malloy, Lindsey E; Gingerich, Jean; Olson, Mark D; Atkins, Dianne L

    2014-02-01

    With the exponential growth of cardiovascular implantable electronic devices (CIEDs) in pediatric patients, a new method of long-term surveillance, remote monitoring (RM), has become the standard of care. The purpose of this study was to determine the usefulness of RM as a monitoring tool in the pediatric population. A retrospective review was performed of 198 patients at the University of Iowa Children's Hospital who had CIEDs. Data transmitted by RM were analyzed. The following data were examined: patient demographics; median interval between transmissions; detection of adverse events requiring corrective measures, including detection of lead failure; detection of arrhythmias and device malfunctions independent of symptoms; time gained in the detection of events using RM versus standard practice; the validity of RM; and the impact of RM on data management. Of 198 patients, 162 submitted 615 RM transmissions. The median time between remote transmissions was 91 days. Of 615 total transmissions, 16 % had true adverse events with 11 % prompting clinical intervention. Of those events requiring clinical response, 61 % of patients reported symptoms. The median interval between last follow-up and occurrence of events detected by RM was 46 days, representing a gain of 134 days for patients followed-up at 6-month intervals and 44 days for patients followed-up at 3 month-intervals. The sensitivity and specificity of RM were found to be 99 and 72 %, respectively. The positive and negative predictive values were found to be 41 and 99 %, respectively. RM allows for early identification of arrhythmias and device malfunctions, thus prompting earlier corrective measures and improving care and safety in pediatric patients.

  13. The grain size distribution and the detection of abnormal grain growth of austenite in an eutectoid steel containing niobium

    SciTech Connect

    Bruno, J.C. . Dept. de Engenharia Mecanica e de Materiais); Rios, P.R. . Dept. de Ciencia dos Materiais e Metalurgia)

    1995-02-15

    The abnormal grain growth of austenite was studied in a commercial steel of composition (wt%): 0.70 C, 1.36 Mn, 0.72 Si, 0.015 P, 0.027 S and 0.03 Nb. Specimens were thermocycled at various conditions and then grain size distribution determined. The grain size distribution shape did not change during normal grain growth but this distribution widened and flattened during the abnormal grain growth. The initial smaller mean size of carbonitrides and/or the highest homogeneity of niobium carbonitride size distribution of the samples submitted to thermal cycles, in comparison with the normalized samples, increased the abnormal grain growth temperature from 1,373 K to 1,473 K.

  14. Drivers of Emerging Infectious Disease Events as a Framework for Digital Detection

    PubMed Central

    Olson, Sarah H.; Benedum, Corey M.; Mekaru, Sumiko R.; Preston, Nicholas D.; Mazet, Jonna A.K.; Joly, Damien O.

    2015-01-01

    The growing field of digital disease detection, or epidemic intelligence, attempts to improve timely detection and awareness of infectious disease (ID) events. Early detection remains an important priority; thus, the next frontier for ID surveillance is to improve the recognition and monitoring of drivers (antecedent conditions) of ID emergence for signals that precede disease events. These data could help alert public health officials to indicators of elevated ID risk, thereby triggering targeted active surveillance and interventions. We believe that ID emergence risks can be anticipated through surveillance of their drivers, just as successful warning systems of climate-based, meteorologically sensitive diseases are supported by improved temperature and precipitation data. We present approaches to driver surveillance, gaps in the current literature, and a scientific framework for the creation of a digital warning system. Fulfilling the promise of driver surveillance will require concerted action to expand the collection of appropriate digital driver data. PMID:26196106

  15. Covert Network Analysis for Key Player Detection and Event Prediction Using a Hybrid Classifier

    PubMed Central

    Akram, M. Usman; Khan, Shoab A.; Javed, Muhammad Younus

    2014-01-01

    National security has gained vital importance due to increasing number of suspicious and terrorist events across the globe. Use of different subfields of information technology has also gained much attraction of researchers and practitioners to design systems which can detect main members which are actually responsible for such kind of events. In this paper, we present a novel method to predict key players from a covert network by applying a hybrid framework. The proposed system calculates certain centrality measures for each node in the network and then applies novel hybrid classifier for detection of key players. Our system also applies anomaly detection to predict any terrorist activity in order to help law enforcement agencies to destabilize the involved network. As a proof of concept, the proposed framework has been implemented and tested using different case studies including two publicly available datasets and one local network. PMID:25136674

  16. SU-E-J-122: Detecting Treatment-Induced Metabolic Abnormalities in Craniopharyngioma Patients Undergoing Surgery and Proton Therapy

    SciTech Connect

    Hua, C; Shulkin, B; Li, Y; LI, X; Merchant, T; Indelicato, D; Boop, F

    2014-06-01

    Purpose: To identify treatment-induced defects in the brain of children with craniopharyngioma receiving surgery and proton therapy using fluorodeoxyglucose positron emission tomography (FDG PET). Methods: Forty seven patients were enrolled on a clinical trial for craniopharyngioma with serial imaging and functional evaluations. Proton therapy was delivered using the double-scattered beams with a prescribed dose of 54 Cobalt Gray Equivalent. FDG tracer uptake in each of 63 anatomical regions was computed after warping PET images to a 3D reference template in Talairach coordinates. Regional uptake was deemed significantly low or high if exceeding two standard deviations of normal population from the mean. For establishing the normal ranges, 132 children aged 1–20 years with noncentral nervous system related diseases and normal-appearing cerebral PET scans were analyzed. Age- and gender-dependent regional uptake models were developed by linear regression and confidence intervals were calculated. Results: Most common PET abnormality before proton therapy was significantly low uptake in the frontal lobe, the occipital lobe (particularly in cuneus), the medial and ventral temporal lobe, cingulate gyrus, caudate nuclei, and thalamus. They were related to injury from surgical corridors, tumor mass effect, insertion of a ventricular catheter, and the placement of an Ommaya reservoir. Surprisingly a significantly high uptake was observed in temporal gyri and the parietal lobe. In 13 patients who already completed 18-month PET scans, metabolic abnormalities improved in 11 patients from baseline. One patient had persistent abnormalities. Only one revealed new uptake abnormalities in thalamus, brainstem, cerebellum, and insula. Conclusion: Postoperative FDG PET of craniopharyngioma patients revealed metabolic abnormalities in specific regions of the brain. Proton therapy did not appear to exacerbate these surgery- and tumor-induced defects. In patients with persistent and

  17. Effects of performing two visual tasks on single-trial detection of event-related potentials.

    PubMed

    Cecotti, Hubert; Eckstein, Miguel P; Giesbrecht, Barry

    2012-01-01

    The detection of event-related potentials (ERPs) in brain-computer interface (BCI) depends on the ability of the subject to pay attention to specific stimuli presented during the BCI task. For healthy users, a BCI shall be used as a complement to other existing devices, which involve the response to other tasks. Those tasks may impair selective attention, particularly if the stimuli have the same modality e.g. visual. It is therefore critical to analyze how single-trial detection of brain evoked response is impaired by the addition of tasks concerning the same modality. We tested 10 healthy participants using an application that has two visual target detection tasks. The first one corresponds to a rapid serial visual presentation paradigm where target detection is achieved by brain-evoked single-trial detection in the recorded electroencephalogram (EEG) signal. The second task is the detection of a visual event on a tactical map by a behavioral response. These tasks were tested individually (single task) and in parallel (dual-task). Whereas the performance of single-trial detection was not impaired between single and dual-task conditions, the behavioral performance decreased during the dual-task condition. These results quantify the performance drop that can occur in a dual-task system using both brain-evoked responses and behavioral responses. PMID:23366242

  18. Event Detection and Location of Earthquakes Using the Cascadia Initiative Dataset

    NASA Astrophysics Data System (ADS)

    Morton, E.; Bilek, S. L.; Rowe, C. A.

    2015-12-01

    The Cascadia subduction zone (CSZ) produces a range of slip behavior along the plate boundary megathrust, from great earthquakes to episodic slow slip and tremor (ETS). Unlike other subduction zones that produce great earthquakes and ETS, the CSZ is notable for the lack of small and moderate magnitude earthquakes recorded. The seismogenic zone extent is currently estimated to be primarily offshore, thus the lack of observed small, interplate earthquakes may be partially due to the use of only land seismometers. The Cascadia Initiative (CI) community seismic experiment seeks to address this issue by including ocean bottom seismometers (OBS) deployed directly over the locked seismogenic zone, in addition to land seismometers. We use these seismic data to explore whether small magnitude earthquakes are occurring on the plate interface, but have gone undetected by the land-based seismic networks. We select a subset of small magnitude (M0.1-3.7) earthquakes from existing earthquake catalogs, based on land seismic data, whose preliminary hypocentral locations suggest they may have occurred on the plate interface. We window the waveforms on CI OBS and land seismometers around the phase arrival times for these earthquakes to generate templates for subspace detection, which allows for additional flexibility over traditional matched filter detection methods. Here we present event detections from the first year of CI deployment and preliminary locations for the detected events. Initial results of scanning the first year of the CI deployment using one cluster of template events, located near a previously identified subducted seamount, include 473 detections on OBS station M08A (~61.6 km offshore) and 710 detections on OBS station J25A (~44.8 km northeast of M08A). Ongoing efforts include detection using additional OBS stations along the margin, as well as determining locations of clusters detected in the first year of deployment.

  19. Event-specific quantitative detection of nine genetically modified maizes using one novel standard reference molecule.

    PubMed

    Yang, Litao; Guo, Jinchao; Pan, Aihu; Zhang, Haibo; Zhang, Kewei; Wang, Zhengming; Zhang, Dabing

    2007-01-10

    With the development of genetically modified organism (GMO) detection techniques, the Polymerase Chain Reaction (PCR) technique has been the mainstay for GMO detection, and real-time PCR is the most effective and important method for GMO quantification. An event-specific detection strategy based on the unique and specific integration junction sequences between the host plant genome DNA and the integrated gene is being developed for its high specificity. This study establishes the event-specific detection methods for TC1507 and CBH351 maizes. In addition, the event-specific TaqMan real-time PCR detection methods for another seven GM maize events (Bt11, Bt176, GA21, MON810, MON863, NK603, and T25) were systematically optimized and developed. In these PCR assays, the fluorescent quencher, TAMRA, was dyed on the T-base of the probe at the internal position to improve the intensity of the fluorescent signal. To overcome the difficulties in obtaining the certified reference materials of these GM maizes, one novel standard reference molecule containing all nine specific integration junction sequences of these GM maizes and the maize endogenous reference gene, zSSIIb, was constructed and used for quantitative analysis. The limits of detection of these methods were 20 copies for these different GM maizes, the limits of quantitation were about 20 copies, and the dynamic ranges for quantification were from 0.05 to 100% in 100 ng of DNA template. Furthermore, nine groups of the mixed maize samples of these nine GM maize events were quantitatively analyzed to evaluate the accuracy and precision. The accuracy expressed as bias varied from 0.67 to 28.00% for the nine tested groups of GM maize samples, and the precision expressed as relative standard deviations was from 0.83 to 26.20%. All of these indicated that the established event-specific real-time PCR detection systems and the reference molecule in this study are suitable for the identification and quantification of these GM

  20. Event-specific quantitative detection of nine genetically modified maizes using one novel standard reference molecule.

    PubMed

    Yang, Litao; Guo, Jinchao; Pan, Aihu; Zhang, Haibo; Zhang, Kewei; Wang, Zhengming; Zhang, Dabing

    2007-01-10

    With the development of genetically modified organism (GMO) detection techniques, the Polymerase Chain Reaction (PCR) technique has been the mainstay for GMO detection, and real-time PCR is the most effective and important method for GMO quantification. An event-specific detection strategy based on the unique and specific integration junction sequences between the host plant genome DNA and the integrated gene is being developed for its high specificity. This study establishes the event-specific detection methods for TC1507 and CBH351 maizes. In addition, the event-specific TaqMan real-time PCR detection methods for another seven GM maize events (Bt11, Bt176, GA21, MON810, MON863, NK603, and T25) were systematically optimized and developed. In these PCR assays, the fluorescent quencher, TAMRA, was dyed on the T-base of the probe at the internal position to improve the intensity of the fluorescent signal. To overcome the difficulties in obtaining the certified reference materials of these GM maizes, one novel standard reference molecule containing all nine specific integration junction sequences of these GM maizes and the maize endogenous reference gene, zSSIIb, was constructed and used for quantitative analysis. The limits of detection of these methods were 20 copies for these different GM maizes, the limits of quantitation were about 20 copies, and the dynamic ranges for quantification were from 0.05 to 100% in 100 ng of DNA template. Furthermore, nine groups of the mixed maize samples of these nine GM maize events were quantitatively analyzed to evaluate the accuracy and precision. The accuracy expressed as bias varied from 0.67 to 28.00% for the nine tested groups of GM maize samples, and the precision expressed as relative standard deviations was from 0.83 to 26.20%. All of these indicated that the established event-specific real-time PCR detection systems and the reference molecule in this study are suitable for the identification and quantification of these GM

  1. Long-Duration Neutron Production in Solar Eruptive Events Detected with the MESSENGER Neutron Spectrometer

    NASA Astrophysics Data System (ADS)

    Feldman, W. C.; Lawrence, D. J.; Vestrand, W. T.; Peplowski, P. N.

    2014-12-01

    Nine long-duration neutron solar eruptive events (SEEs) between 31 December 2007 and 16 March 2013 appear to be excellent candidates for detection of fast neutrons from the Sun by the MESSENGER Neutron Spectrometer (NS). One event (on 4 June 2011) is the cleanest example, because it was not accompanied by energetic ions at MESSENGER having energies greater than 50±10 MeV/nuc. The purpose of this study is to assemble a set of conditions common to all events that can help identify the physical conditions at their origin. We classified the nine events into three categories: (1) those having tight magnetic connection to the Sun as well as to spacecraft at 1 AU that can separately measure the energetic proton, alpha particle, and electron flux spectra, (2) those with sufficiently close connection that the energetic flux spectra can be compared, (3) those that have only marginal connections, and (4) those that are also seen at Earth. Four events fall into category (1), three into category (2), two into category (3), and parts of four events overlapped neutron events also seen by the scintillation FIBer solar neutron telescope (FIB) detector placed on the International Space Station in 2009. Seven of the nine events that have either tight or marginal magnetic connection have alpha particle abundances less than 2%. For each event, we modeled expected fast neutron count rates from the 1 AU ion spectrum, a process that accounts for the transport of the neutrons through the spacecraft to the NS. The ratios of measured to predicted fast-neutron counts range between 2.0 and 12.1.

  2. Ontology-based knowledge management for personalized adverse drug events detection.

    PubMed

    Cao, Feng; Sun, Xingzhi; Wang, Xiaoyuan; Li, Bo; Li, Jing; Pan, Yue

    2011-01-01

    Since Adverse Drug Event (ADE) has become a leading cause of death around the world, there arises high demand for helping clinicians or patients to identify possible hazards from drug effects. Motivated by this, we present a personalized ADE detection system, with the focus on applying ontology-based knowledge management techniques to enhance ADE detection services. The development of electronic health records makes it possible to automate the personalized ADE detection, i.e., to take patient clinical conditions into account during ADE detection. Specifically, we define the ADE ontology to uniformly manage the ADE knowledge from multiple sources. We take advantage of the rich semantics from the terminology SNOMED-CT and apply it to ADE detection via the semantic query and reasoning. PMID:21893837

  3. Automated detection of instantaneous gait events using time frequency analysis and manifold embedding.

    PubMed

    Aung, Min S H; Thies, Sibylle B; Kenney, Laurence P J; Howard, David; Selles, Ruud W; Findlow, Andrew H; Goulermas, John Y

    2013-11-01

    Accelerometry is a widely used sensing modality in human biomechanics due to its portability, non-invasiveness, and accuracy. However, difficulties lie in signal variability and interpretation in relation to biomechanical events. In walking, heel strike and toe off are primary gait events where robust and accurate detection is essential for gait-related applications. This paper describes a novel and generic event detection algorithm applicable to signals from tri-axial accelerometers placed on the foot, ankle, shank or waist. Data from healthy subjects undergoing multiple walking trials on flat and inclined, as well as smooth and tactile paving surfaces is acquired for experimentation. The benchmark timings at which heel strike and toe off occur, are determined using kinematic data recorded from a motion capture system. The algorithm extracts features from each of the acceleration signals using a continuous wavelet transform over a wide range of scales. A locality preserving embedding method is then applied to reduce the high dimensionality caused by the multiple scales while preserving salient features for classification. A simple Gaussian mixture model is then trained to classify each of the time samples into heel strike, toe off or no event categories. Results show good detection and temporal accuracies for different sensor locations and different walking terrains. PMID:23322764

  4. A Heuristic Indication and Warning Staging Model for Detection and Assessment of Biological Events

    PubMed Central

    Wilson, James M.; Polyak, Marat G.; Blake, Jane W.; Collmann, Jeff

    2008-01-01

    Objective This paper presents a model designed to enable rapid detection and assessment of biological threats that may require swift intervention by the international public health community. Design We utilized Strauss’ grounded theory to develop an expanded model of social disruption due to biological events based on retrospective and prospective case studies. We then applied this model to the temporal domain and propose a heuristic staging model, the Wilson–Collmann Scale for assessing biological event evolution. Measurements We retrospectively and manually examined hard copy archival local media reports in the native vernacular for three biological events associated with substantial social disruption. The model was then tested prospectively through media harvesting based on keywords corresponding to the model parameters. Results Our heuristic staging model provides valuable information about the features of a biological event that can be used to determine the level of concern warranted, such as whether the pathogen in question is responding to established public health disease control measures, including the use of antimicrobials or vaccines; whether the public health and medical infrastructure of the country involved is adequate to mount the necessary response; whether the country’s officials are providing an appropriate level of information to international public health authorities; and whether the event poses a international threat. The approach is applicable for monitoring open-source (public-domain) media for indications and warnings of such events, and specifically for markers of the social disruption that commonly occur as these events unfold. These indications and warnings can then be used as the basis for staging the biological threat in the same manner that the United States National Weather Service currently uses storm warning models (such as the Saffir-Simpson Hurricane Scale) to detect and assess threatening weather conditions. Conclusion

  5. A method for detecting and locating geophysical events using groups of arrays

    NASA Astrophysics Data System (ADS)

    de Groot-Hedlin, Catherine D.; Hedlin, Michael A. H.

    2015-11-01

    We have developed a novel method to detect and locate geophysical events that makes use of any sufficiently dense sensor network. This method is demonstrated using acoustic sensor data collected in 2013 at the USArray Transportable Array (TA). The algorithm applies Delaunay triangulation to divide the sensor network into a mesh of three-element arrays, called triads. Because infrasound waveforms are incoherent between the sensors within each triad, the data are transformed into envelopes, which are cross-correlated to find signals that satisfy a consistency criterion. The propagation azimuth, phase velocity and signal arrival time are computed for each signal. Triads with signals that are consistent with a single source are bundled as an event group. The ensemble of arrival times and azimuths of detected signals within each group are used to locate a common source in space and time. A total of 513 infrasonic stations that were active for part or all of 2013 were divided into over 2000 triads. Low (0.5-2 Hz) and high (2-8 Hz) catalogues of infrasonic events were created for the eastern USA. The low-frequency catalogue includes over 900 events and reveals several highly active source areas on land that correspond with coal mining regions. The high-frequency catalogue includes over 2000 events, with most occurring offshore. Although their cause is not certain, most events are clearly anthropogenic as almost all occur during regular working hours each week. The regions to which the TA is most sensitive vary seasonally, with the direction of reception dependent on the direction of zonal winds. The catalogue has also revealed large acoustic events that may provide useful insight into the nature of long-range infrasound propagation in the atmosphere.

  6. Automatic Acoustic Events Detection, Classification, and Semantic Annotation for Persistent Surveillance Applications

    NASA Astrophysics Data System (ADS)

    Alkilani, Amjad H. I.

    Acoustic surveillance and human behavior analysis represent some of the ongoing research topics in signal processing. Acoustic sensors offer a promising sensing modality, primarily because they can capture a huge amount of information from the environment. Moreover, they can be rapidly deployed and are low-cost. In the past, significant efforts have been devoted to detecting sounds of individual objects or events. However, the issue of understanding human activities based on sporadic acoustic sound events has received unequal attention in the literature and hence is not well understood. This dissertation presents an extensive literature survey on this topic and discusses existing advanced techniques for acoustic signal processing and pattern recognition. A novel theoretic framework (Acoustic Events Detection, Classification, and Annotation (AEDCA)) is proposed which accommodates sound events ontology for improved human activities recognition. Based on a generalized taxonomy, three sound categories signifying interaction of human with each other, with vehicles, and with other objects are introduced. In order to understand different type of human interactions salient sound events are preliminarily identified and classified based on trained set of data. To interlink salient events representing an ontology-based hypothesis, a Hidden Markov Model-Acoustic Activity Recognizer (HMM-AAR) is modeled to recognize spatiotemporally correlated events. Once such a connection is established, an annotation of perceived sound activity is generated. The performance of the AEDCA system was tested and measured experimentally in both indoor and outdoor environments. Appropriate confusion matrices are developed for the assessment of performance reliability, and computational efficiency of the AEDCA system. The obtained results are very promising and strongly demonstrate the AEDCA is both reliable and effective, and can be extended to future surveillance applications.

  7. Exploring the limits of waveform correlation event detection as applied to three earthquake aftershock sequences.

    SciTech Connect

    Resor, Megan E.; Carr, Dorthe Bame; Young, Christopher John

    2010-05-01

    Swarms of earthquakes and/or aftershock sequences can dramatically increase the level of seismicity in a region for a period of time lasting from days to months, depending on the swarm or sequence. Such occurrences can provide a large amount of useful information to seismologists. For those who monitor seismic events for possible nuclear explosions, however, these swarms/sequences are a nuisance. In an explosion monitoring system, each event must be treated as a possible nuclear test until it can be proven, to a high degree of confidence, not to be. Seismic events recorded by the same station with highly correlated waveforms almost certainly have a similar location and source type, so clusters of events within a swarm can quickly be identified as earthquakes. We have developed a number of tools that can be used to exploit the high degree of waveform similarity expected to be associated with swarms/sequences. Dendro Tool measures correlations between known events. The Waveform Correlation Detector is intended to act as a detector, finding events in raw data which correlate with known events. The Self Scanner is used to find all correlated segments within a raw data steam and does not require an event library. All three techniques together provide an opportunity to study the similarities of events in an aftershock sequence in different ways. To comprehensively characterize the benefits and limits of waveform correlation techniques, we studied 3 aftershock sequences, using our 3 tools, at multiple stations. We explored the effects of station distance and event magnitudes on correlation results. Lastly, we show the reduction in detection threshold and analyst workload offered by waveform correlation techniques compared to STA/LTA based detection. We analyzed 4 days of data from each aftershock sequence using all three methods. Most known events clustered in a similar manner across the toolsets. Up to 25% of catalogued events were found to be a member of a cluster. In

  8. Characterization and Analysis of Networked Array of Sensors for Event Detection (CANARY-EDS)

    2011-05-27

    CANARY -EDS provides probabilistic event detection based on analysis of time-series data from water quality or other sensors. CANARY also can compare patterns against a library of previously seen data to indicate that a certain pattern has reoccurred, suppressing what would otherwise be considered an event. CANARY can be configured to analyze previously recorded data from files or databases, or it can be configured to run in real-time mode directory from a database, or throughmore » the US EPA EDDIES software.« less

  9. Hazardous Traffic Event Detection Using Markov Blanket and Sequential Minimal Optimization (MB-SMO).

    PubMed

    Yan, Lixin; Zhang, Yishi; He, Yi; Gao, Song; Zhu, Dunyao; Ran, Bin; Wu, Qing

    2016-07-13

    The ability to identify hazardous traffic events is already considered as one of the most effective solutions for reducing the occurrence of crashes. Only certain particular hazardous traffic events have been studied in previous studies, which were mainly based on dedicated video stream data and GPS data. The objective of this study is twofold: (1) the Markov blanket (MB) algorithm is employed to extract the main factors associated with hazardous traffic events; (2) a model is developed to identify hazardous traffic event using driving characteristics, vehicle trajectory, and vehicle position data. Twenty-two licensed drivers were recruited to carry out a natural driving experiment in Wuhan, China, and multi-sensor information data were collected for different types of traffic events. The results indicated that a vehicle's speed, the standard deviation of speed, the standard deviation of skin conductance, the standard deviation of brake pressure, turn signal, the acceleration of steering, the standard deviation of acceleration, and the acceleration in Z (G) have significant influences on hazardous traffic events. The sequential minimal optimization (SMO) algorithm was adopted to build the identification model, and the accuracy of prediction was higher than 86%. Moreover, compared with other detection algorithms, the MB-SMO algorithm was ranked best in terms of the prediction accuracy. The conclusions can provide reference evidence for the development of dangerous situation warning products and the design of intelligent vehicles.

  10. Detection of seismic events triggered by P-waves from the 2011 Tohoku-Oki earthquake

    NASA Astrophysics Data System (ADS)

    Miyazawa, Masatoshi

    2012-12-01

    Large-amplitude surface waves from the 2011 Tohoku-Oki earthquake triggered many seismic events across Japan, while the smaller amplitude P-wave triggering remains unclear. A spectral method was used to detect seismic events triggered by the first arriving P-waves over Japan. This method uses a reference event to correct for source and propagation effects, so that the local response near the station can be examined in detail. P-wave triggering was found in the regions where triggered non-volcanic tremor (NVT) has been observed, and some seismic and volcanic regions. The triggering strain due to P-waves is of the order of 10-8 to 10-7, which is 1 to 2 orders of magnitude smaller than the triggering strain necessary for the surface wave triggering. In the regions of NVT, the triggered event was not identified with slow events, but with other seismic events such as tectonic earthquakes. The sequence of triggering in the regions started with P-wave arrivals. The subsequent surface waves contributed to triggering of NVT, possibly together with slow slip, which resulted in the large amplitude of the NVT.

  11. Hazardous Traffic Event Detection Using Markov Blanket and Sequential Minimal Optimization (MB-SMO).

    PubMed

    Yan, Lixin; Zhang, Yishi; He, Yi; Gao, Song; Zhu, Dunyao; Ran, Bin; Wu, Qing

    2016-01-01

    The ability to identify hazardous traffic events is already considered as one of the most effective solutions for reducing the occurrence of crashes. Only certain particular hazardous traffic events have been studied in previous studies, which were mainly based on dedicated video stream data and GPS data. The objective of this study is twofold: (1) the Markov blanket (MB) algorithm is employed to extract the main factors associated with hazardous traffic events; (2) a model is developed to identify hazardous traffic event using driving characteristics, vehicle trajectory, and vehicle position data. Twenty-two licensed drivers were recruited to carry out a natural driving experiment in Wuhan, China, and multi-sensor information data were collected for different types of traffic events. The results indicated that a vehicle's speed, the standard deviation of speed, the standard deviation of skin conductance, the standard deviation of brake pressure, turn signal, the acceleration of steering, the standard deviation of acceleration, and the acceleration in Z (G) have significant influences on hazardous traffic events. The sequential minimal optimization (SMO) algorithm was adopted to build the identification model, and the accuracy of prediction was higher than 86%. Moreover, compared with other detection algorithms, the MB-SMO algorithm was ranked best in terms of the prediction accuracy. The conclusions can provide reference evidence for the development of dangerous situation warning products and the design of intelligent vehicles. PMID:27420073

  12. Hazardous Traffic Event Detection Using Markov Blanket and Sequential Minimal Optimization (MB-SMO)

    PubMed Central

    Yan, Lixin; Zhang, Yishi; He, Yi; Gao, Song; Zhu, Dunyao; Ran, Bin; Wu, Qing

    2016-01-01

    The ability to identify hazardous traffic events is already considered as one of the most effective solutions for reducing the occurrence of crashes. Only certain particular hazardous traffic events have been studied in previous studies, which were mainly based on dedicated video stream data and GPS data. The objective of this study is twofold: (1) the Markov blanket (MB) algorithm is employed to extract the main factors associated with hazardous traffic events; (2) a model is developed to identify hazardous traffic event using driving characteristics, vehicle trajectory, and vehicle position data. Twenty-two licensed drivers were recruited to carry out a natural driving experiment in Wuhan, China, and multi-sensor information data were collected for different types of traffic events. The results indicated that a vehicle’s speed, the standard deviation of speed, the standard deviation of skin conductance, the standard deviation of brake pressure, turn signal, the acceleration of steering, the standard deviation of acceleration, and the acceleration in Z (G) have significant influences on hazardous traffic events. The sequential minimal optimization (SMO) algorithm was adopted to build the identification model, and the accuracy of prediction was higher than 86%. Moreover, compared with other detection algorithms, the MB-SMO algorithm was ranked best in terms of the prediction accuracy. The conclusions can provide reference evidence for the development of dangerous situation warning products and the design of intelligent vehicles. PMID:27420073

  13. CTBT infrasound network performance to detect the 2013 Russian fireball event

    NASA Astrophysics Data System (ADS)

    Pilger, Christoph; Ceranna, Lars; Ross, J. Ole; Le Pichon, Alexis; Mialle, Pierrick; Garcés, Milton A.

    2015-04-01

    The explosive fragmentation of the 2013 Chelyabinsk meteorite generated a large airburst with an equivalent yield of 500 kT TNT. It is the most energetic event recorded by the infrasound component of the Comprehensive Nuclear-Test-Ban Treaty-International Monitoring System (CTBT-IMS), globally detected by 20 out of 42 operational stations. This study performs a station-by-station estimation of the IMS detection capability to explain infrasound detections and nondetections from short to long distances, using the Chelyabinsk meteorite as global reference event. Investigated parameters influencing the detection capability are the directivity of the line source signal, the ducting of acoustic energy, and the individual noise conditions at each station. Findings include a clear detection preference for stations perpendicular to the meteorite trajectory, even over large distances. Only a weak influence of stratospheric ducting is observed for this low-frequency case. Furthermore, a strong dependence on the diurnal variability of background noise levels at each station is observed, favoring nocturnal detections.

  14. Facilitating adverse drug event detection in pharmacovigilance databases using molecular structure similarity: application to rhabdomyolysis

    PubMed Central

    Vilar, Santiago; Harpaz, Rave; Chase, Herbert S; Costanzi, Stefano; Rabadan, Raul

    2011-01-01

    Background Adverse drug events (ADE) cause considerable harm to patients, and consequently their detection is critical for patient safety. The US Food and Drug Administration maintains an adverse event reporting system (AERS) to facilitate the detection of ADE in drugs. Various data mining approaches have been developed that use AERS to detect signals identifying associations between drugs and ADE. The signals must then be monitored further by domain experts, which is a time-consuming task. Objective To develop a new methodology that combines existing data mining algorithms with chemical information by analysis of molecular fingerprints to enhance initial ADE signals generated from AERS, and to provide a decision support mechanism to facilitate the identification of novel adverse events. Results The method achieved a significant improvement in precision in identifying known ADE, and a more than twofold signal enhancement when applied to the ADE rhabdomyolysis. The simplicity of the method assists in highlighting the etiology of the ADE by identifying structurally similar drugs. A set of drugs with strong evidence from both AERS and molecular fingerprint-based modeling is constructed for further analysis. Conclusion The results demonstrate that the proposed methodology could be used as a pharmacovigilance decision support tool to facilitate ADE detection. PMID:21946238

  15. Support Vector Machine Model for Automatic Detection and Classification of Seismic Events

    NASA Astrophysics Data System (ADS)

    Barros, Vesna; Barros, Lucas

    2016-04-01

    The automated processing of multiple seismic signals to detect, localize and classify seismic events is a central tool in both natural hazards monitoring and nuclear treaty verification. However, false detections and missed detections caused by station noise and incorrect classification of arrivals are still an issue and the events are often unclassified or poorly classified. Thus, machine learning techniques can be used in automatic processing for classifying the huge database of seismic recordings and provide more confidence in the final output. Applied in the context of the International Monitoring System (IMS) - a global sensor network developed for the Comprehensive Nuclear-Test-Ban Treaty (CTBT) - we propose a fully automatic method for seismic event detection and classification based on a supervised pattern recognition technique called the Support Vector Machine (SVM). According to Kortström et al., 2015, the advantages of using SVM are handleability of large number of features and effectiveness in high dimensional spaces. Our objective is to detect seismic events from one IMS seismic station located in an area of high seismicity and mining activity and classify them as earthquakes or quarry blasts. It is expected to create a flexible and easily adjustable SVM method that can be applied in different regions and datasets. Taken a step further, accurate results for seismic stations could lead to a modification of the model and its parameters to make it applicable to other waveform technologies used to monitor nuclear explosions such as infrasound and hydroacoustic waveforms. As an authorized user, we have direct access to all IMS data and bulletins through a secure signatory account. A set of significant seismic waveforms containing different types of events (e.g. earthquake, quarry blasts) and noise is being analysed to train the model and learn the typical pattern of the signal from these events. Moreover, comparing the performance of the support

  16. Detection of Abnormal Glucose Tolerance in Africans Is Improved by Combining A1C With Fasting Glucose: The Africans in America Study

    PubMed Central

    Thoreson, Caroline K.; O'Connor, Michelle Y.; Ricks, Madia; Chung, Stephanie T.; Tulloch-Reid, Marshall K.; Lozier, Jay N.; Sacks, David B.

    2015-01-01

    OBJECTIVE Abnormal glucose tolerance is rising in sub-Saharan Africa. Hemoglobin A1c by itself and in combination with fasting plasma glucose (FPG) is used to diagnose abnormal glucose tolerance. The diagnostic ability of A1C in Africans with heterozygous variant hemoglobin, such as sickle cell trait or hemoglobin C trait, has not been rigorously evaluated. In U.S.-based Africans, we determined by hemoglobin status the sensitivities of 1) FPG ≥5.6 mmol/L, 2) A1C ≥ 5.7% (39 mmol/mol), and 3) FPG combined with A1C (FPG ≥5.6 mmol/L and/or A1C ≥5.7% [39 mmol/mol]) for the detection of abnormal glucose tolerance. RESEARCH DESIGN AND METHODS An oral glucose tolerance test (OGTT) was performed in 216 African immigrants (68% male, age 37 ± 10 years [mean ± SD], range 20–64 years). Abnormal glucose tolerance was defined as 2-h glucose ≥7.8 mmol/L. RESULTS Variant hemoglobin was identified in 21% (46 of 216). Abnormal glucose tolerance occurred in 33% (72 of 216). When determining abnormal glucose tolerance from the OGTT (2-h glucose ≥7.8 mmol/L), sensitivities of FPG for the total, normal, and variant hemoglobin groups were 32%, 32%, and 33%, respectively. Sensitivities for A1C were 53%, 54%, and 47%. For FPG and A1C combined, sensitivities were 64%, 63%, and 67%. Sensitivities for FPG and A1C and the combination did not vary by hemoglobin status (all P > 0.6). For the entire cohort, sensitivity was higher for A1C than FPG and for both tests combined than for either test alone (all P values ≤ 0.01). CONCLUSIONS No significant difference in sensitivity of A1C by variant hemoglobin status was detected. For the diagnosis of abnormal glucose tolerance in Africans, the sensitivity of A1C combined with FPG is significantly superior to either test alone. PMID:25338926

  17. Women's perceptions of events impeding or facilitating the detection, investigation and treatment of breast cancer.

    PubMed

    Bairati, I; Fillion, L; Meyer, F A; Héry, C; Larochelle, M

    2006-05-01

    An integrated network is currently being implemented in the province of Quebec in order to improve the cancer care continuum. In this context, formal trajectories for cancer patients through healthcare services are being established. The investigation of patients' perceptions of the healthcare continuum is essential as it allows us to identify the issue of continuity/discontinuity of health services. In addition, patients' perceptions of continuity of cancer care should be documented since they could influence the implementation of optimal trajectories through the healthcare services. An exploratory qualitative study was conducted in order to identify events, based on the perceptions of women with breast cancer, that made the patient progress more rapidly, facilitating events, or more slowly, impeding events, within the cancer care continuum. Two consecutive series of women receiving adjuvant radiation therapy in 2002 and 2003 at the University Hospital of Quebec City were recruited, for a total of 120 participants. A semi-structured interview was administered in order to identify women's perceptions regarding impeding and facilitating events during the detection, investigation and treatment periods of cancer, as well as the actors and reasons involved. Overall, 64% of women reported having at least one impeding event, while 68% reported at least one facilitating event. The periods most frequently affected by impeding or facilitating events were the investigation period, followed by the treatment period. The main stages affected by impeding or facilitating events were the scheduling of an appointment, during the investigation period, and the onset of treatment. Impeding events particularly affected the scheduling of mammography, the initial exam of the investigation for breast cancer, as well as the onset of radiation treatment. On the other hand, facilitating events mainly occurred at the time of the scheduling of medical consultations with specialists, during the

  18. Craniofacial Abnormalities

    MedlinePlus

    ... of the skull and face. Craniofacial abnormalities are birth defects of the face or head. Some, like cleft ... palate, are among the most common of all birth defects. Others are very rare. Most of them affect ...

  19. Chromosome Abnormalities

    MedlinePlus

    ... decade, newer techniques have been developed that allow scientists and doctors to screen for chromosomal abnormalities without using a microscope. These newer methods compare the patient's DNA to a normal DNA ...

  20. Walking abnormalities

    MedlinePlus

    ... include: Arthritis of the leg or foot joints Conversion disorder (a psychological disorder) Foot problems (such as a ... injuries. For an abnormal gait that occurs with conversion disorder, counseling and support from family members are strongly ...

  1. Nail abnormalities

    MedlinePlus

    Beau's lines; Fingernail abnormalities; Spoon nails; Onycholysis; Leukonychia; Koilonychia; Brittle nails ... Just like the skin, the fingernails tell a lot about your health: ... the fingernail. These lines can occur after illness, injury to ...

  2. Detection of Unusual Events and Trends in Complex Non-Stationary Data Streams

    SciTech Connect

    Perez, Rafael B; Protopopescu, Vladimir A; Worley, Brian Addison; Perez, Cristina

    2006-01-01

    The search for unusual events and trends hidden in multi-component, nonlinear, non-stationary, noisy signals is extremely important for a host of different applications, ranging from nuclear power plant and electric grid operation to internet traffic and implementation of non-proliferation protocols. In the context of this work, we define an unusual event as a local signal disturbance and a trend as a continuous carrier of information added to and different from the underlying baseline dynamics. The goal of this paper is to investigate the feasibility of detecting hidden intermittent events inside non-stationary signal data sets corrupted by high levels of noise, by using the Hilbert-Huang empirical mode decomposition method.

  3. Solar Origin of Solar Particle Events Detected by the Standard Radiation Environment Monitor of ESA

    NASA Astrophysics Data System (ADS)

    Tziotziou, K.; Sandberg, I.; Anastasiadis, A.; Daglis, I. A.; Panagopoulos, I.; Mavromichalaki, H.; Papaioannou, A.; Gerontidou, M.; Nieminen, P.; Glover, A.

    2010-07-01

    Solar Particle Events (SPEs) of the 23rd Solar Cycle detected by the ESA Standard Radiation Environment Monitor (SREM) onboard the INTEGRAL satellite have been studied in order to find their connection to solar sources. X-ray, optical and radio data of solar flares that were observed by several space-based instruments during the aforementioned solar cycle have been selected. The data were reduced and thoroughly analyzed in order to establish the corresponding solar origin of the selected SPEs. The extensive scientific analysis has produced clear correlations with X class solar flares for the events of the October-November 2003, January 2005 and December 2006 periods while for the events that occurred during September 2005, correlations with X class flares are possible but not straightforward due to the complexity of the registered solar particle fluxes.

  4. Event Detection: A Clinical Notification Service on a Health Information Exchange Platform

    PubMed Central

    Moore, Thomas; Shapiro, Jason S.; Doles, Luke; Calman, Neil; Camhi, Eli; Check, Thomas; Onyile, Arit; Kuperman, Gilad

    2012-01-01

    Notifying ambulatory providers when their patients visit the hospital is a simple concept but potentially a powerful tool for improving care coordination. A health information exchange (HIE) can provide automatic notifications to its members by building services on top of their existing infrastructure. NYCLIX, Inc., a functioning HIE in New York City, has developed a system that detects hospital admissions, discharges and emergency department visits and notifies their providers. The system has been in use since November 2010. Out of 63,305 patients enrolled 6,913 (11%) had one or more events in the study period and on average there were 238 events per day. While event notifications have a clinical value, their use also involves non-clinical care coordination; new workflows should be designed to incorporate a broader care team in their use. This paper describes the user requirements for the notification system, system design, current status, lessons learned and future directions. PMID:23304336

  5. Detection of Severe Rain on Snow events using passive microwave remote sensing

    NASA Astrophysics Data System (ADS)

    Grenfell, T. C.; Putkonen, J.

    2007-12-01

    Severe wintertime rain-on-snow (ROS) events create a strong ice layer or layers in the snow on arctic tundra that act as a barrier to ungulate grazing. These events are linked with large-scale ungulate herd declines via starvation and reduced calf production rate when the animals are unable to penetrate through the resulting ice layer. ROS events also produce considerable perturbation in the mean wintertime soil temperature beneath the snow pack. ROS is a sporadic but well-known and significant phenomenon that is currently very poorly documented. Characterization of the distribution and occurrence of severe rain-on-snow events is based only on anecdotal evidence, indirect observations of carcasses found adjacent to iced snow packs, and irregular detection by a sparse observational weather network. We have analyzed in detail a particular well-identified ROS event that took place on Banks Island in early October 2003 that resulted in the death of 20,000 musk oxen. We make use of multifrequency passive microwave imagery from the special sensing microwave imager satellite sensor suite (SSM/I) in conjunction with a strong-fluctuation-theory (SFT) emissivity model. We show that a combination of time series analysis and cluster analysis based on microwave spectral gradients and polarization ratios provides a means to detect the stages of the ROS event resulting from the modification of the vertical structure of the snow pack, specifically wetting the snow, the accumulation of liquid water at the base of the snow during the rain event, and the subsequent modification of the snowpack after refreezing. SFT model analysis provides quantitative confirmation of our interpretation of the evolution of the microwave properties of the snowpack as a result of the ROS event. In particular, in addition to the grain coarsening due to destructive metamorphism, we detect the presence of the internal water and ice layers, directly identifying the physical properties producing the

  6. Assessment and validation of a simple automated method for the detection of gait events and intervals.

    PubMed

    Ghoussayni, Salim; Stevens, Christopher; Durham, Sally; Ewins, David

    2004-12-01

    A simple and rapid automatic method for detection of gait events at the foot could speed up and possibly increase the repeatability of gait analysis and evaluations of treatments for pathological gaits. The aim of this study was to compare and validate a kinematic-based algorithm used in the detection of four gait events, heel contact, heel rise, toe contact and toe off. Force platform data is often used to obtain start and end of contact phases, but not usually heel rise and toe contact events. For this purpose synchronised kinematic, kinetic and video data were captured from 12 healthy adult subjects walking both barefoot and shod at slow and normal self-selected speeds. The data were used to determine the gait events using three methods: force, visual inspection and algorithm methods. Ninety percent of all timings given by the algorithm were within one frame (16.7 ms) when compared to visual inspection. There were no statistically significant differences between the visual and algorithm timings. For both heel and toe contact the differences between the three methods were within 1.5 frames, whereas for heel rise and toe off the differences between the force on one side and the visual and algorithm on the other were higher and more varied (up to 175 ms). In addition, the algorithm method provided the duration of three intervals, heel contact to toe contact, toe contact to heel rise and heel rise to toe off, which are not readily available from force platform data. The ability to automatically and reliably detect the timings of these four gait events and three intervals using kinematic data alone is an asset to clinical gait analysis.

  7. Flow detection via sparse frame analysis for suspicious event recognition in infrared imagery

    NASA Astrophysics Data System (ADS)

    Fernandes, Henrique C.; Batista, Marcos A.; Barcelos, Celia A. Z.; Maldague, Xavier P. V.

    2013-05-01

    It is becoming increasingly evident that intelligent systems are very bene¯cial for society and that the further development of such systems is necessary to continue to improve society's quality of life. One area that has drawn the attention of recent research is the development of automatic surveillance systems. In our work we outline a system capable of monitoring an uncontrolled area (an outside parking lot) using infrared imagery and recognizing suspicious events in this area. The ¯rst step is to identify moving objects and segment them from the scene's background. Our approach is based on a dynamic background-subtraction technique which robustly adapts detection to illumination changes. It is analyzed only regions where movement is occurring, ignoring in°uence of pixels from regions where there is no movement, to segment moving objects. Regions where movement is occurring are identi¯ed using °ow detection via sparse frame analysis. During the tracking process the objects are classi¯ed into two categories: Persons and Vehicles, based on features such as size and velocity. The last step is to recognize suspicious events that may occur in the scene. Since the objects are correctly segmented and classi¯ed it is possible to identify those events using features such as velocity and time spent motionless in one spot. In this paper we recognize the suspicious event suspicion of object(s) theft from inside a parked vehicle at spot X by a person" and results show that the use of °ow detection increases the recognition of this suspicious event from 78:57% to 92:85%.

  8. Detection and analysis of high-temperature events in the BIRD mission

    NASA Astrophysics Data System (ADS)

    Zhukov, Boris; Briess, Klaus; Lorenz, Eckehard; Oertel, Dieter; Skrbek, Wolfgang

    2005-01-01

    The primary mission objective of a new small Bi-spectral InfraRed Detection (BIRD) satellite is detection and quantitative analysis of high-temperature events like fires and volcanoes. An absence of saturation in the BIRD infrared channels makes it possible to improve false alarm rejection as well as to retrieve quantitative characteristics of hot targets, including their effective fire temperature, area and the radiative energy release. Examples are given of detection and analysis of wild and coal seam fires, of volcanic activity as well as of oil fires in Iraq. The smallest fires detected by BIRD, which were verified on ground, had an area of 12m2 at daytime and 4m2 at night.

  9. Automatic Event Detection in Noisy Environment for Material Process Monitoring by Laser AE Method

    NASA Astrophysics Data System (ADS)

    Ito, K.; Kuriki, H.; Araki, H.; Kuroda, S.; Enoki, M.

    2014-06-01

    Laser acoustic emission (AE) method is a unique in-situ and non-contact nondestructive evaluation (NDE) method. It has a capability to detect signals generated from crack generation and propagation, friction and other physical phenomena in materials even in high temperature environment. However, laser AE system has lower signal-to-noise ratio compared to the conventional AE system using PZT sensors, so it is difficult to apply this method in noisy environment. A novel AE measurement system to detect events in such difficult environments was developed. This system could continuously record all AE waveforms and enable unrestricted post-analyses. Noise reduction filters in frequency domain coupling with a new AE event extraction using multiple threshold values showed a good potential for AE signal processing. This system was successfully applied for crack monitoring of plasma spray deposition process of ceramic coating.

  10. How unusual are the "unusual events" detected by control chart techniques in healthcare settings?

    PubMed

    Borckardt, Jeffrey J; Nash, Michael R; Hardesty, Susan; Herbert, Joan; Cooney, Harriet; Pelic, Christopher

    2006-01-01

    Statistical process control (SPC) charts have become widely implemented tools for quality monitoring and assurance in healthcare settings across the United States. SPC methods have been successfully used in industrial settings to track the quality of products manufactured by machines and to detect deviations from acceptable Levels of product quality. However, problems may arise when SPC methods are used to evaluate human behavior. Specifically, when human behavior is tracked over time, the data stream generated usually exhibits periodicity and gradualism with respect to behavioral changes over time. These tendencies can be quantified and are recognized in the statistical field as autocorrelation. When autocorrelation is present, conventional SPC methods too often identify events as "unusuaL" when they really should be understood as products of random fluctuation. This article discusses the concept of autocorrelation and demonstrates the negative impact of autocorrelation on traditional SPC methods, with a specific focus on the use of SPC charts to detect unusual events. PMID:16944647

  11. Efficient In Planta Detection and Dissection of De Novo Mutation Events in the Arabidopsis thaliana Disease Resistance Gene UNI.

    PubMed

    Ogawa, Tomohiko; Mori, Akiko; Igari, Kadunari; Morita, Miyo Terao; Tasaka, Masao; Uchida, Naoyuki

    2016-06-01

    Plants possess disease resistance (R) proteins encoded by R genes, and each R protein recognizes a specific pathogen factor(s) for immunity. Interestingly, a remarkably high degree of polymorphisms in R genes, which are traces of past mutation events during evolution, suggest the rapid diversification of R genes. However, little is known about molecular aspects that facilitate the rapid change of R genes because of the lack of tools that enable us to monitor de novo R gene mutations efficiently in an experimentally feasible time scale, especially in living plants. Here we introduce a model assay system that enables efficient in planta detection of de novo mutation events in the Arabidopsis thaliana R gene UNI in one generation. The uni-1D mutant harbors a gain-of-function allele of the UNI gene. uni-1D heterozygous individuals originally exhibit dwarfism with abnormally short stems. However, interestingly, morphologically normal stems sometimes emerge spontaneously from the uni-1D plants, and the morphologically reverted tissues carry additional de novo mutations in the UNI gene. Strikingly, under an extreme condition, almost half of the examined population shows the reversion phenomenon. By taking advantage of this phenomenon, we demonstrate that the reversion frequency is remarkably sensitive to a variety of fluctuations in DNA stability, underlying a mutable tendency of the UNI gene. We also reveal that activities of the salicylic acid pathway and DNA damage sensor pathway are involved in the reversion phenomenon. Thus, we provide an experimentally feasible model tool to explore factors and conditions that significantly affect the R gene mutation phenomenon. PMID:27016096

  12. Automatic Detection and Classification of Unsafe Events During Power Wheelchair Use

    PubMed Central

    Moghaddam, Athena K.; Yuen, Hiu Kim; Archambault, Philippe S.; Routhier, François; Michaud, François; Boissy, Patrick

    2014-01-01

    Using a powered wheelchair (PW) is a complex task requiring advanced perceptual and motor control skills. Unfortunately, PW incidents and accidents are not uncommon and their consequences can be serious. The objective of this paper is to develop technological tools that can be used to characterize a wheelchair user’s driving behavior under various settings. In the experiments conducted, PWs are outfitted with a datalogging platform that records, in real-time, the 3-D acceleration of the PW. Data collection was conducted over 35 different activities, designed to capture a spectrum of PW driving events performed at different speeds (collisions with fixed or moving objects, rolling on incline plane, and rolling across multiple types obstacles). The data was processed using time-series analysis and data mining techniques, to automatically detect and identify the different events. We compared the classification accuracy using four different types of time-series features: 1) time-delay embeddings; 2) time-domain characterization; 3) frequency-domain features; and 4) wavelet transforms. In the analysis, we compared the classification accuracy obtained when distinguishing between safe and unsafe events during each of the 35 different activities. For the purposes of this study, unsafe events were defined as activities containing collisions against objects at different speed, and the remainder were defined as safe events. We were able to accurately detect 98% of unsafe events, with a low (12%) false positive rate, using only five examples of each activity. This proof-of-concept study shows that the proposed approach has the potential of capturing, based on limited input from embedded sensors, contextual information on PW use, and of automatically characterizing a user’s PW driving behavior. PMID:27170879

  13. Automatic Detection and Classification of Unsafe Events During Power Wheelchair Use.

    PubMed

    Pineau, Joelle; Moghaddam, Athena K; Yuen, Hiu Kim; Archambault, Philippe S; Routhier, François; Michaud, François; Boissy, Patrick

    2014-01-01

    Using a powered wheelchair (PW) is a complex task requiring advanced perceptual and motor control skills. Unfortunately, PW incidents and accidents are not uncommon and their consequences can be serious. The objective of this paper is to develop technological tools that can be used to characterize a wheelchair user's driving behavior under various settings. In the experiments conducted, PWs are outfitted with a datalogging platform that records, in real-time, the 3-D acceleration of the PW. Data collection was conducted over 35 different activities, designed to capture a spectrum of PW driving events performed at different speeds (collisions with fixed or moving objects, rolling on incline plane, and rolling across multiple types obstacles). The data was processed using time-series analysis and data mining techniques, to automatically detect and identify the different events. We compared the classification accuracy using four different types of time-series features: 1) time-delay embeddings; 2) time-domain characterization; 3) frequency-domain features; and 4) wavelet transforms. In the analysis, we compared the classification accuracy obtained when distinguishing between safe and unsafe events during each of the 35 different activities. For the purposes of this study, unsafe events were defined as activities containing collisions against objects at different speed, and the remainder were defined as safe events. We were able to accurately detect 98% of unsafe events, with a low (12%) false positive rate, using only five examples of each activity. This proof-of-concept study shows that the proposed approach has the potential of capturing, based on limited input from embedded sensors, contextual information on PW use, and of automatically characterizing a user's PW driving behavior. PMID:27170879

  14. Automatic Detection and Classification of Unsafe Events During Power Wheelchair Use.

    PubMed

    Pineau, Joelle; Moghaddam, Athena K; Yuen, Hiu Kim; Archambault, Philippe S; Routhier, François; Michaud, François; Boissy, Patrick

    2014-01-01

    Using a powered wheelchair (PW) is a complex task requiring advanced perceptual and motor control skills. Unfortunately, PW incidents and accidents are not uncommon and their consequences can be serious. The objective of this paper is to develop technological tools that can be used to characterize a wheelchair user's driving behavior under various settings. In the experiments conducted, PWs are outfitted with a datalogging platform that records, in real-time, the 3-D acceleration of the PW. Data collection was conducted over 35 different activities, designed to capture a spectrum of PW driving events performed at different speeds (collisions with fixed or moving objects, rolling on incline plane, and rolling across multiple types obstacles). The data was processed using time-series analysis and data mining techniques, to automatically detect and identify the different events. We compared the classification accuracy using four different types of time-series features: 1) time-delay embeddings; 2) time-domain characterization; 3) frequency-domain features; and 4) wavelet transforms. In the analysis, we compared the classification accuracy obtained when distinguishing between safe and unsafe events during each of the 35 different activities. For the purposes of this study, unsafe events were defined as activities containing collisions against objects at different speed, and the remainder were defined as safe events. We were able to accurately detect 98% of unsafe events, with a low (12%) false positive rate, using only five examples of each activity. This proof-of-concept study shows that the proposed approach has the potential of capturing, based on limited input from embedded sensors, contextual information on PW use, and of automatically characterizing a user's PW driving behavior.

  15. Nanoporous niobium oxide for label-free detection of DNA hybridization events.

    PubMed

    Choi, Jinsub; Lim, Jae Hoon; Rho, Sangchul; Jahng, Deokjin; Lee, Jaeyoung; Kim, Kyung Ja

    2008-01-15

    We found that DNA probes can be immobilized on anodically prepared porous niobium oxide without a chemical modification of both the DNA probes and the substrate. By using the porous niobium oxide with a positive surface charge, DNA hybridization events are detected on the basis of the blue-shift of a maximum absorption peak in UV-vis-NIR spectroscopy. The blue-shift is ascribed to the change of surface charge upon single- or double-stranded DNA. The method does not require a label and shows high sensitivity with the detection limit of the concentration of 1nM.

  16. A multivariate based event detection method and performance comparison with two baseline methods.

    PubMed

    Liu, Shuming; Smith, Kate; Che, Han

    2015-09-01

    Early warning systems have been widely deployed to protect water systems from accidental and intentional contamination events. Conventional detection algorithms are often criticized for having high false positive rates and low true positive rates. This mainly stems from the inability of these methods to determine whether variation in sensor measurements is caused by equipment noise or the presence of contamination. This paper presents a new detection method that identifies the existence of contamination by comparing Euclidean distances of correlation indicators, which are derived from the correlation coefficients of multiple water quality sensors. The performance of the proposed method was evaluated using data from a contaminant injection experiment and compared with two baseline detection methods. The results show that the proposed method can differentiate between fluctuations caused by equipment noise and those due to the presence of contamination. It yielded higher possibility of detection and a lower false alarm rate than the two baseline methods. With optimized parameter values, the proposed method can correctly detect 95% of all contamination events with a 2% false alarm rate.

  17. Temporal and Spatial Predictability of an Irrelevant Event Differently Affect Detection and Memory of Items in a Visual Sequence

    PubMed Central

    Ohyama, Junji; Watanabe, Katsumi

    2016-01-01

    We examined how the temporal and spatial predictability of a task-irrelevant visual event affects the detection and memory of a visual item embedded in a continuously changing sequence. Participants observed 11 sequentially presented letters, during which a task-irrelevant visual event was either present or absent. Predictabilities of spatial location and temporal position of the event were controlled in 2 × 2 conditions. In the spatially predictable conditions, the event occurred at the same location within the stimulus sequence or at another location, while, in the spatially unpredictable conditions, it occurred at random locations. In the temporally predictable conditions, the event timing was fixed relative to the order of the letters, while in the temporally unpredictable condition; it could not be predicted from the letter order. Participants performed a working memory task and a target detection reaction time (RT) task. Memory accuracy was higher for a letter simultaneously presented at the same location as the event in the temporally unpredictable conditions, irrespective of the spatial predictability of the event. On the other hand, the detection RTs were only faster for a letter simultaneously presented at the same location as the event when the event was both temporally and spatially predictable. Thus, to facilitate ongoing detection processes, an event must be predictable both in space and time, while memory processes are enhanced by temporally unpredictable (i.e., surprising) events. Evidently, temporal predictability has differential effects on detection and memory of a visual item embedded in a sequence of images. PMID:26869966

  18. Event Detection for Hydrothermal Plumes: A case study at Grotto Vent

    NASA Astrophysics Data System (ADS)

    Bemis, K. G.; Ozer, S.; Xu, G.; Rona, P. A.; Silver, D.

    2012-12-01

    Evidence is mounting that geologic events such as volcanic eruptions (and intrusions) and earthquakes (near and far) influence the flow rates and temperatures of hydrothermal systems. Connecting such suppositions to observations of hydrothermal output is challenging, but new ongoing time series have the potential to capture such events. This study explores using activity detection, a technique modified from computer vision, to identify pre-defined events within an extended time series recorded by COVIS (Cabled Observatory Vent Imaging Sonar) and applies it to a time series, with gaps, from Sept 2010 to the present; available measurements include plume orientation, plume rise rate, and diffuse flow area at the NEPTUNE Canada Observatory at Grotto Vent, Main Endeavour Field, Juan de Fuca Ridge. Activity detection is the process of finding a pattern (activity) in a data set containing many different types of patterns. Among many approaches proposed to model and detect activities, we have chosen a graph-based technique, Petri Nets, as they do not require training data to model the activity. They use the domain expert's knowledge to build the activity as a combination of feature states and their transitions (actions). Starting from a conceptual model of how hydrothermal plumes respond to daily tides, we have developed a Petri Net based detection algorithm that identifies deviations from the specified response. Initially we assumed that the orientation of the plume would change smoothly and symmetrically in a consistent daily pattern. However, results indicate that the rate of directional changes varies. The present Petri Net detects unusually large and rapid changes in direction or amount of bending; however inspection of Figure 1 suggests that many of the events detected may be artifacts resulting from gaps in the data or from the large temporal spacing. Still, considerable complexity overlies the "normal" tidal response pattern (the data has a dominant frequency of

  19. Shared clonal cytogenetic abnormalities in aberrant mast cells and leukemic myeloid blasts detected by single nucleotide polymorphism microarray-based whole-genome scanning.

    PubMed

    Frederiksen, John K; Shao, Lina; Bixby, Dale L; Ross, Charles W

    2016-04-01

    Systemic mastocytosis (SM) is characterized by a clonal proliferation of aberrant mast cells within extracutaneous sites. In a subset of SM cases, a second associated hematologic non-mast cell disease (AHNMD) is also present, usually of myeloid origin. Polymerase chain reaction and targeted fluorescence in situ hybridization studies have provided evidence that, in at least some cases, the aberrant mast cells are related clonally to the neoplastic cells of the AHNMD. In this work, a single nucleotide polymorphism microarray (SNP-A) was used to characterize the cytogenetics of the aberrant mast cells from a patient with acute myeloid leukemia and concomitant mast cell leukemia associated with a KIT D816A mutation. The results demonstrate the presence of shared cytogenetic abnormalities between the mast cells and myeloid blasts, as well as additional abnormalities within mast cells (copy-neutral loss of heterozygosity) not detectable by routine karyotypic analysis. To our knowledge, this work represents the first application of SNP-A whole-genome scanning to the detection of shared cytogenetic abnormalities between the two components of a case of SM-AHNMD. The findings provide additional evidence of a frequent clonal link between aberrant mast cells and cells of myeloid AHNMDs, and also highlight the importance of direct sequencing for identifying uncommon activating KIT mutations.

  20. Risk of Newly Detected Infections and Cervical Abnormalities in Women Seropositive for Naturally Acquired Human Papillomavirus Type 16/18 Antibodies: Analysis of the Control Arm of PATRICIA

    PubMed Central

    Castellsagué, Xavier; Naud, Paulo; Chow, Song-Nan; Wheeler, Cosette M.; Germar, Maria Julieta V.; Lehtinen, Matti; Paavonen, Jorma; Jaisamrarn, Unnop; Garland, Suzanne M.; Salmerón, Jorge; Apter, Dan; Kitchener, Henry; Teixeira, Julio C.; Skinner, S. Rachel; Limson, Genara; Szarewski, Anne; Romanowski, Barbara; Aoki, Fred Y.; Schwarz, Tino F.; Poppe, Willy A. J.; Bosch, F. Xavier; de Carvalho, Newton S.; Peters, Klaus; Tjalma, Wiebren A. A.; Safaeian, Mahboobeh; Raillard, Alice; Descamps, Dominique; Struyf, Frank; Dubin, Gary; Rosillon, Dominique; Baril, Laurence

    2014-01-01

    Background. We examined risk of newly detected human papillomavirus (HPV) infection and cervical abnormalities in relation to HPV type 16/18 antibody levels at enrollment in PATRICIA (Papilloma Trial Against Cancer in Young Adults; NCT00122681). Methods. Using Poisson regression, we compared risk of newly detected infection and cervical abnormalities associated with HPV-16/18 between seronegative vs seropositive women (15–25 years) in the control arm (DNA negative at baseline for the corresponding HPV type [HPV-16: n = 8193; HPV-18: n = 8463]). Results. High titers of naturally acquired HPV-16 antibodies and/or linear trend for increasing antibody levels were significantly associated with lower risk of incident and persistent infection, atypical squamous cells of undetermined significance or greater (ASCUS+), and cervical intraepithelial neoplasia grades 1/2 or greater (CIN1+, CIN2+). For HPV-18, although seropositivity was associated with lower risk of ASCUS+ and CIN1+, no association between naturally acquired antibodies and infection was demonstrated. Naturally acquired HPV-16 antibody levels of 371 (95% confidence interval [CI], 242–794), 204 (95% CI, 129–480), and 480 (95% CI, 250–5756) EU/mL were associated with 90% reduction of incident infection, 6-month persistent infection, and ASCUS+, respectively. Conclusions. Naturally acquired antibodies to HPV-16, and to a lesser extent HPV-18, are associated with some reduced risk of subsequent infection and cervical abnormalities associated with the same HPV type. PMID:24610876

  1. Respiratory symptoms in rheumatoid arthritis: relation to pulmonary abnormalities detected by high-resolution CT and pulmonary functional testing.

    PubMed

    Youssef, Amir A; Machaly, Shereen A; El-Dosoky, Mohammed E; El-Maghraby, Nermeen M

    2012-07-01

    Pulmonary disease is the most frequent and among the most severe extra-articular manifestation of rheumatoid arthritis (RA). However, this issue has not been sufficiently studied in Egyptian patients. The objectives of the present study are to investigate the prevalence and types of pulmonary involvement using high-resolution computed tomography scan (HRCT) and pulmonary function tests (PFT) and evaluate the association between respiratory symptoms and RA-lung disease in a group of Egyptian RA patients. Thirty-six RA patients were recruited; 34 females (94.4%) and 2 males (5.6%) with median age of 48.5 years, and none of them was smoker. Detailed medical and drug histories were obtained. PFT, plain X-ray of the chest, and HRCT were performed to all subjects involved. Nearly 64% of RA patients demonstrated abnormalities in PFT and 47% in HRCT. Mixed restrictive and obstructive pattern was the commonest. Nearly two-thirds of our patients reported one or more pulmonary symptom whether dyspnea, cough, wheezing, or phlegm. Dyspnea was the most frequent symptom. Respiratory symptoms were statistically more common in patients with lung disease. The advanced age, high radiological score, and severity of rheumatoid disease were found to be predictive of lung involvement. Among respiratory symptoms, dyspnea and cough were associated with any pulmonary abnormalities. When specific pulmonary abnormalities were considered, only dyspnea was identified as predictor for restriction. For obstructive abnormality, both cough and wheezing provided valid prediction. We conclude that pulmonary involvement is a common manifestation in Egyptian RA patients, and the pattern of involvement is generally consistent with other studies that were performed worldwide. Specific respiratory symptoms could be used as practical, easy, and cost-effective method, especially in older and with more severe RA patients, to discriminate patients in need of subsequent PFT and HRCT imaging.

  2. Adverse event detection (AED) system for continuously monitoring and evaluating structural health status

    NASA Astrophysics Data System (ADS)

    Yun, Jinsik; Ha, Dong Sam; Inman, Daniel J.; Owen, Robert B.

    2011-03-01

    Structural damage for spacecraft is mainly due to impacts such as collision of meteorites or space debris. We present a structural health monitoring (SHM) system for space applications, named Adverse Event Detection (AED), which integrates an acoustic sensor, an impedance-based SHM system, and a Lamb wave SHM system. With these three health-monitoring methods in place, we can determine the presence, location, and severity of damage. An acoustic sensor continuously monitors acoustic events, while the impedance-based and Lamb wave SHM systems are in sleep mode. If an acoustic sensor detects an impact, it activates the impedance-based SHM. The impedance-based system determines if the impact incurred damage. When damage is detected, it activates the Lamb wave SHM system to determine the severity and location of the damage. Further, since an acoustic sensor dissipates much less power than the two SHM systems and the two systems are activated only when there is an acoustic event, our system reduces overall power dissipation significantly. Our prototype system demonstrates the feasibility of the proposed concept.

  3. Real-time gait event detection for transfemoral amputees during ramp ascending and descending.

    PubMed

    Maqbool, H F; Husman, M A B; Awad, M I; Abouhossein, A; Dehghani-Sanij, A A

    2015-01-01

    Events and phases detection of the human gait are vital for controlling prosthesis, orthosis and functional electrical stimulation (FES) systems. Wearable sensors are inexpensive, portable and have fast processing capability. They are frequently used to assess spatio-temporal, kinematic and kinetic parameters of the human gait which in turn provide more details about the human voluntary control and ampute-eprosthesis interaction. This paper presents a reliable real-time gait event detection algorithm based on simple heuristics approach, applicable to signals from tri-axial gyroscope for lower limb amputees during ramp ascending and descending. Experimental validation is done by comparing the results of gyroscope signal with footswitches. For healthy subjects, the mean difference between events detected by gyroscope and footswitches is 14 ms and 10.5 ms for initial contact (IC) whereas for toe off (TO) it is -5 ms and -25 ms for ramp up and down respectively. For transfemoral amputee, the error is slightly higher either due to the placement of footswitches underneath the foot or the lack of proper knee flexion and ankle plantarflexion/dorsiflexion during ramp up and down. Finally, repeatability tests showed promising results.

  4. Real-time gait event detection for transfemoral amputees during ramp ascending and descending.

    PubMed

    Maqbool, H F; Husman, M A B; Awad, M I; Abouhossein, A; Dehghani-Sanij, A A

    2015-01-01

    Events and phases detection of the human gait are vital for controlling prosthesis, orthosis and functional electrical stimulation (FES) systems. Wearable sensors are inexpensive, portable and have fast processing capability. They are frequently used to assess spatio-temporal, kinematic and kinetic parameters of the human gait which in turn provide more details about the human voluntary control and ampute-eprosthesis interaction. This paper presents a reliable real-time gait event detection algorithm based on simple heuristics approach, applicable to signals from tri-axial gyroscope for lower limb amputees during ramp ascending and descending. Experimental validation is done by comparing the results of gyroscope signal with footswitches. For healthy subjects, the mean difference between events detected by gyroscope and footswitches is 14 ms and 10.5 ms for initial contact (IC) whereas for toe off (TO) it is -5 ms and -25 ms for ramp up and down respectively. For transfemoral amputee, the error is slightly higher either due to the placement of footswitches underneath the foot or the lack of proper knee flexion and ankle plantarflexion/dorsiflexion during ramp up and down. Finally, repeatability tests showed promising results. PMID:26737364

  5. Detection of DNA recognition events using multi-well field effect devices.

    PubMed

    Sakata, Toshiya; Miyahara, Yuji

    2005-11-15

    We proposed the multi-well field effect device for detection of charged biomolecules and demonstrated the detection principle for DNA recognition events using quasi-static capacitance-voltage (QSCV) measurement. The multi-well field effect device is based on the electrostatic interaction between molecular charges induced by DNA recognition and surface electrons in silicon through the Si(3)N(4)/SiO(2) thin double-layer. Since DNA molecules and DNA binders such as Hoechst 33258 have intrinsic charges in aqueous solutions, respectively, the charge density changes due to DNA recognition events at the Si(3)N(4) surface were directly translated into electrical signal such as a flat band voltage change in the QSCV measurement. The average flat band shifts were 20.7 mV for hybridization and -13.5 mV for binding of Hoechst 33258. From the results of flat band voltage shifts due to hybridization and binding of Hoechst 33258, the immobilization density of oligonucleotide probes at the Si(3)N(4) surface was estimated to be 10(8) cm(-2). The platform based on the multi-well field effect device is suitable for a simple and arrayed detection system for DNA recognition events.

  6. Data Flow Design for Event Detection and Qualification in TES X-Ray Detectors

    NASA Astrophysics Data System (ADS)

    Ceballos, M. T.; Cobo, B.; Fraga-Encinas, R.; van der Kuur, J.; Schuurmans, J.; Gottardi, L.

    2013-10-01

    The current and forthcoming research lines in X-ray astronomy will require unprecedented spectral resolution with imaging capabilities. The most promising detectors able to provide these capabilities are the calorimeters based on Transition Edge Sensor (TES) technologies, like the one that has been under development for the proposed ATHENA x-ray space mission. We present here the Data Flow designed for one of such instruments covering the detection algorithms to extract the x-ray events (photons) from the noisy signal (as well as to cope with a possible pile-up), the event qualification (event grade) according to the event arrival time and proximity to other events, and finally the filtering process applied to these pulses to get their energy content, and thus the astronomical source spectrum. This development is currently part of a collaboration between IFCA (Spain) and SRON (NL) institutes, as part of a larger project initiated in 2005 and named EURECA (de Korte et al. 2009) involving many other institutes in Europe and the USA. This project was created to design the TES prototype proposed for the XEUS/IXO/ATHENA ESA missions.

  7. Method for the depth corrected detection of ionizing events from a co-planar grids sensor

    DOEpatents

    De Geronimo, Gianluigi; Bolotnikov, Aleksey E.; Carini, Gabriella

    2009-05-12

    A method for the detection of ionizing events utilizing a co-planar grids sensor comprising a semiconductor substrate, cathode electrode, collecting grid and non-collecting grid. The semiconductor substrate is sensitive to ionizing radiation. A voltage less than 0 Volts is applied to the cathode electrode. A voltage greater than the voltage applied to the cathode is applied to the non-collecting grid. A voltage greater than the voltage applied to the non-collecting grid is applied to the collecting grid. The collecting grid and the non-collecting grid are summed and subtracted creating a sum and difference respectively. The difference and sum are divided creating a ratio. A gain coefficient factor for each depth (distance between the ionizing event and the collecting grid) is determined, whereby the difference between the collecting electrode and the non-collecting electrode multiplied by the corresponding gain coefficient is the depth corrected energy of an ionizing event. Therefore, the energy of each ionizing event is the difference between the collecting grid and the non-collecting grid multiplied by the corresponding gain coefficient. The depth of the ionizing event can also be determined from the ratio.

  8. Advanced Geospatial Hydrodynamic Signals Analysis for Tsunami Event Detection and Warning

    NASA Astrophysics Data System (ADS)

    Arbab-Zavar, Banafshe; Sabeur, Zoheir

    2013-04-01

    Current early tsunami warning can be issued upon the detection of a seismic event which may occur at a given location offshore. This also provides an opportunity to predict the tsunami wave propagation and run-ups at potentially affected coastal zones by selecting the best matching seismic event from a database of pre-computed tsunami scenarios. Nevertheless, it remains difficult and challenging to obtain the rupture parameters of the tsunamigenic earthquakes in real time and simulate the tsunami propagation with high accuracy. In this study, we propose a supporting approach, in which the hydrodynamic signal is systematically analysed for traces of a tsunamigenic signal. The combination of relatively low amplitudes of a tsunami signal at deep waters and the frequent occurrence of background signals and noise contributes to a generally low signal to noise ratio for the tsunami signal; which in turn makes the detection of this signal difficult. In order to improve the accuracy and confidence of detection, a re-identification framework in which a tsunamigenic signal is detected via the scan of a network of hydrodynamic stations with water level sensing is performed. The aim is to attempt the re-identification of the same signatures as the tsunami wave spatially propagates through the hydrodynamic stations sensing network. The re-identification of the tsunamigenic signal is technically possible since the tsunami signal at the open ocean itself conserves its birthmarks relating it to the source event. As well as supporting the initial detection and improving the confidence of detection, a re-identified signal is indicative of the spatial range of the signal, and thereby it can be used to facilitate the identification of certain background signals such as wind waves which do not have as large a spatial reach as tsunamis. In this paper, the proposed methodology for the automatic detection of tsunamigenic signals has been achieved using open data from NOAA with a recorded

  9. Group localisation and unsupervised detection and classification of basic crowd behaviour events for surveillance applications

    NASA Astrophysics Data System (ADS)

    Roubtsova, Nadejda S.; de With, Peter H. N.

    2013-02-01

    Technology for monitoring crowd behaviour is in demand for surveillance and security applications. The trend in research is to tackle detection of complex crowd behaviour events (panic, ght, evacuation etc.) directly using machine learning techniques. In this paper, we present a contrary, bottom-up approach seeking basic group information: (1) instantaneous location and (2) the merge, split and lateral slide-by events - the three basic motion patterns comprising any crowd behaviour. The focus on such generic group information makes our algorithm suitable as a building block in a variety of surveillance systems, possibly integrated with static content analysis solutions. Our feature extraction framework has optical ow in its core. The framework is universal being motion-based, rather than object-detection-based and generates a large variety of motion-blob- characterising features useful for an array of classi cation problems. Motion-based characterisation is performed on a group as an atomic whole and not by means of superposition of individual human motions. Within that feature space, our classi cation system makes decisions based on heuristic rules and thresholds, without machine learning. Our system performs well on group localisation, consistently generating contours around both moving and halted groups. The visual output of our periodical group localisation is equivalent to tracking and the group contour accuracy ranges from adequate to exceptionally good. The system successfully detects and classi es within our merge/split/slide-by event space in surveillance-type video sequences, di ering in resolution, scale, quality and motion content. Quantitatively, its performance is characterised by a good recall: 83% on detection and 71% on combined detection and classi cation.

  10. Final Scientific Report, Integrated Seismic Event Detection and Location by Advanced Array Processing

    SciTech Connect

    Kvaerna, T.; Gibbons. S.J.; Ringdal, F; Harris, D.B.

    2007-01-30

    In the field of nuclear explosion monitoring, it has become a priority to detect, locate, and identify seismic events down to increasingly small magnitudes. The consideration of smaller seismic events has implications for a reliable monitoring regime. Firstly, the number of events to be considered increases greatly; an exponential increase in naturally occurring seismicity is compounded by large numbers of seismic signals generated by human activity. Secondly, the signals from smaller events become more difficult to detect above the background noise and estimates of parameters required for locating the events may be subject to greater errors. Thirdly, events are likely to be observed by a far smaller number of seismic stations, and the reliability of event detection and location using a very limited set of observations needs to be quantified. For many key seismic stations, detection lists may be dominated by signals from routine industrial explosions which should be ascribed, automatically and with a high level of confidence, to known sources. This means that expensive analyst time is not spent locating routine events from repeating seismic sources and that events from unknown sources, which could be of concern in an explosion monitoring context, are more easily identified and can be examined with due care. We have obtained extensive lists of confirmed seismic events from mining and other artificial sources which have provided an excellent opportunity to assess the quality of existing fully-automatic event bulletins and to guide the development of new techniques for online seismic processing. Comparing the times and locations of confirmed events from sources in Fennoscandia and NW Russia with the corresponding time and location estimates reported in existing automatic bulletins has revealed substantial mislocation errors which preclude a confident association of detected signals with known industrial sources. The causes of the errors are well understood and are

  11. Single-subject-based whole-brain MEG slow-wave imaging approach for detecting abnormality in patients with mild traumatic brain injury.

    PubMed

    Huang, Ming-Xiong; Nichols, Sharon; Baker, Dewleen G; Robb, Ashley; Angeles, Annemarie; Yurgil, Kate A; Drake, Angela; Levy, Michael; Song, Tao; McLay, Robert; Theilmann, Rebecca J; Diwakar, Mithun; Risbrough, Victoria B; Ji, Zhengwei; Huang, Charles W; Chang, Douglas G; Harrington, Deborah L; Muzzatti, Laura; Canive, Jose M; Christopher Edgar, J; Chen, Yu-Han; Lee, Roland R

    2014-01-01

    Traumatic brain injury (TBI) is a leading cause of sustained impairment in military and civilian populations. However, mild TBI (mTBI) can be difficult to detect using conventional MRI or CT. Injured brain tissues in mTBI patients generate abnormal slow-waves (1-4 Hz) that can be measured and localized by resting-state magnetoencephalography (MEG). In this study, we develop a voxel-based whole-brain MEG slow-wave imaging approach for detecting abnormality in patients with mTBI on a single-subject basis. A normative database of resting-state MEG source magnitude images (1-4 Hz) from 79 healthy control subjects was established for all brain voxels. The high-resolution MEG source magnitude images were obtained by our recent Fast-VESTAL method. In 84 mTBI patients with persistent post-concussive symptoms (36 from blasts, and 48 from non-blast causes), our method detected abnormalities at the positive detection rates of 84.5%, 86.1%, and 83.3% for the combined (blast-induced plus with non-blast causes), blast, and non-blast mTBI groups, respectively. We found that prefrontal, posterior parietal, inferior temporal, hippocampus, and cerebella areas were particularly vulnerable to head trauma. The result also showed that MEG slow-wave generation in prefrontal areas positively correlated with personality change, trouble concentrating, affective lability, and depression symptoms. Discussion is provided regarding the neuronal mechanisms of MEG slow-wave generation due to deafferentation caused by axonal injury and/or blockages/limitations of cholinergic transmission in TBI. This study provides an effective way for using MEG slow-wave source imaging to localize affected areas and supports MEG as a tool for assisting the diagnosis of mTBI. PMID:25009772

  12. A Patch-Based Method for Repetitive and Transient Event Detection in Fluorescence Imaging

    PubMed Central

    Boulanger, Jérôme; Gidon, Alexandre; Kervran, Charles; Salamero, Jean

    2010-01-01

    Automatic detection and characterization of molecular behavior in large data sets obtained by fast imaging in advanced light microscopy become key issues to decipher the dynamic architectures and their coordination in the living cell. Automatic quantification of the number of sudden and transient events observed in fluorescence microscopy is discussed in this paper. We propose a calibrated method based on the comparison of image patches expected to distinguish sudden appearing/vanishing fluorescent spots from other motion behaviors such as lateral movements. We analyze the performances of two statistical control procedures and compare the proposed approach to a frame difference approach using the same controls on a benchmark of synthetic image sequences. We have then selected a molecular model related to membrane trafficking and considered real image sequences obtained in cells stably expressing an endocytic-recycling trans-membrane protein, the Langerin-YFP, for validation. With this model, we targeted the efficient detection of fast and transient local fluorescence concentration arising in image sequences from a data base provided by two different microscopy modalities, wide field (WF) video microscopy using maximum intensity projection along the axial direction and total internal reflection fluorescence microscopy. Finally, the proposed detection method is briefly used to statistically explore the effect of several perturbations on the rate of transient events detected on the pilot biological model. PMID:20976222

  13. EUROarray human papillomavirus (HPV) assay is highly concordant with other commercial assays for detection of high-risk HPV genotypes in women with high grade cervical abnormalities.

    PubMed

    Cornall, A M; Poljak, M; Garland, S M; Phillips, S; Machalek, D A; Tan, J H; Quinn, M A; Tabrizi, S N

    2016-06-01

    The purpose of this study was to evaluate the performance of the EUROIMMUN EUROArray HPV genotyping assay against the Roche Cobas 4800, Roche HPV Amplicor, Roche Linear Array and Qiagen Hybrid Capture 2 assays in the detection of high-risk HPV (HR-HPV) from liquid based cervical cytology samples collected from women undergoing follow-up for abnormal cervical cytology results. Cervical specimens from 404 women undergoing management of high-grade cytological abnormality were evaluated by EUROarray HPV for detection of HR-HPV genotypes and prediction of histologically-confirmed cervical intraepithelial neoplasia grade 2 or higher (≥CIN2). The results were compared to Hybrid Capture 2, Cobas 4800 HPV, Amplicor and Linear Array HPV. Positivity for 14 HR-HPV types was 80.0 % for EUROarray (95 % CI; 75.7-83.8 %). Agreement (κ, 95 % CI) between the EUROarray and other HPV tests for detection of HR-HPV was good to very good [Hybrid Capture κ = 0.62 (0.54-0.71); Cobas κ = 0.81 (0.74-0.88); Amplicor κ = 0.68 (0.60-0.77); Linear Array κ = 0.77 (0.70-0.85)]. For detection of HR-HPV, agreement with EUROarray was 87.90 % (Hybrid Capture), 93.58 % (Cobas), 92.84 % (Amplicor) and 92.59 % (Linear Array). Detection of HR-HPV was not significantly different between EUROarray and any other test (p < 0.001). EUROarray was concordant with other assays evaluated for detection of high-risk HPV and showed sensitivity and specificity for detection of ≥ CIN2 of 86 % and 71 %, respectively. PMID:27048314

  14. Myelodysplastic syndromes: pathogenesis, functional abnormalities, and clinical implications.

    PubMed Central

    Jacobs, A

    1985-01-01

    The myelodysplastic syndromes represent a preleukaemic state in which a clonal abnormality of haemopoietic stem cell is characterised by a variety of phenotypic manifestations with varying degrees of ineffective haemopoiesis. This state probably develops as a sequence of events in which the earliest stages may be difficult to detect by conventional pathological techniques. The process is characterised by genetic changes leading to abnormal control of cell proliferation and differentiation. Expansion of an abnormal clone may be related to independence from normal growth factors, insensitivity to normal inhibitory factors, suppression of normal clonal growth, or changes in the immunological or nutritional condition of the host. The haematological picture is of peripheral blood cytopenias: a cellular bone marrow, and functional abnormalities of erythroid, myeloid, and megakaryocytic cells. In most cases marrow cells have an abnormal DNA content, often with disturbances of the cell cycle: an abnormal karyotype is common in premalignant clones. Growth abnormalities of erythroid or granulocyte-macrophage progenitors are common in marrow cultures, and lineage specific surface membrane markers indicate aberrations of differentiation. Progression of the disorder may occur through clonal expansion or through clonal evolution with a greater degree of malignancy. Current attempts to influence abnormal growth and differentiation have had only limited success. Clinical recognition of the syndrome depends on an acute awareness of the signs combined with the identification of clonal and functional abnormalities. PMID:2999194

  15. Event Detection Using Mobile Phone Mass GPS Data and Their Reliavility Verification by Dmsp/ols Night Light Image

    NASA Astrophysics Data System (ADS)

    Yuki, Akiyama; Satoshi, Ueyama; Ryosuke, Shibasaki; Adachi, Ryuichiro

    2016-06-01

    In this study, we developed a method to detect sudden population concentration on a certain day and area, that is, an "Event," all over Japan in 2012 using mass GPS data provided from mobile phone users. First, stay locations of all phone users were detected using existing methods. Second, areas and days where Events occurred were detected by aggregation of mass stay locations into 1-km-square grid polygons. Finally, the proposed method could detect Events with an especially large number of visitors in the year by removing the influences of Events that occurred continuously throughout the year. In addition, we demonstrated reasonable reliability of the proposed Event detection method by comparing the results of Event detection with light intensities obtained from the night light images from the DMSP/OLS night light images. Our method can detect not only positive events such as festivals but also negative events such as natural disasters and road accidents. These results are expected to support policy development of urban planning, disaster prevention, and transportation management.

  16. Fault detection and isolation in manufacturing systems with an identified discrete event model

    NASA Astrophysics Data System (ADS)

    Roth, Matthias; Schneider, Stefan; Lesage, Jean-Jacques; Litz, Lothar

    2012-10-01

    In this article a generic method for fault detection and isolation (FDI) in manufacturing systems considered as discrete event systems (DES) is presented. The method uses an identified model of the closed-loop of plant and controller built on the basis of observed fault-free system behaviour. An identification algorithm known from literature is used to determine the fault detection model in form of a non-deterministic automaton. New results of how to parameterise this algorithm are reported. To assess the fault detection capability of an identified automaton, probabilistic measures are proposed. For fault isolation, the concept of residuals adapted for DES is used by defining appropriate set operations representing generic fault symptoms. The method is applied to a case study system.

  17. Exupery volcano fast response system - The event detection and waveform classification system

    NASA Astrophysics Data System (ADS)

    Hammer, Conny; Ohrnberger, Matthias

    2010-05-01

    Volcanic eruptions are often preceded by seismic activity which can be used to quantify the volcanic activity since the number and the size of certain types of seismic events usually increase before periods of volcanic crisis. The implementation of an automatic detection and classification system for seismic signals of volcanic origin allows not only for the processing of large amounts of data in short time, but also provides consistent and time-invariant results. Here, we have developed a system based upon a combination of different methods. To enable a first robust event detection in the continuous data stream different modules are implemented in the real time system Earthworm which is widely distributed in active volcano monitoring observatories worldwide. Among those software modules are classical trigger algorithm like STA/LTA and cross-correlation master event matching which is also used to detect different classes of signals. Furthermore an additional module is implemented in the real time system to compute continuous activity parameters which are also used to quantify the volcanic activity. Most automatic classification systems need a sufficiently large pre-classified data set for training the system. However in case of a volcanic crisis we are often confronted with a lack of training data due to insufficient prior observations because prior data acquisition might be carried out with different equipment at a low number of sites and due to the imminent crisis there might be no time for the time-consuming and tedious process of preparing a training data set. For this reason we have developed a novel seismic event spotting technique in order to be less dependent on the existence of previously acquired data bases of event classes. One main goal is therefore to provide observatory staff with a robust event classification based on a minimum number of reference waveforms. By using a "learning-while-recording" approach we are allowing for the fast build-up of a

  18. Gait event detection for use in FES rehabilitation by radial and tangential foot accelerations.

    PubMed

    Rueterbories, Jan; Spaich, Erika G; Andersen, Ole K

    2014-04-01

    Gait rehabilitation by Functional Electrical Stimulations (FESs) requires a reliable trigger signal to start the stimulations. This could be obtained by a simple switch under the heel or by means of an inertial sensor system. This study provides an algorithm to detect gait events in differential acceleration signals of the foot. The key feature of differential measurements is that they compensate the impact of gravity. The real time detection capability of a rule based algorithm in healthy and hemiparetic individuals was investigated. Detection accuracy and precision compared to signals from foot switches were evaluated. The algorithm detected curve features of the vectorial sum of radial and tangential accelerations and mapped those to discrete gait states. The results showed detection rates for healthy and hemiparetic gait ranging form 84.2% to 108.5%. The sensitivity was between 0.81 and 1, and the specificity between 0.85 and 1, depending on gait phase and group of subjects. The algorithm detected gait phase changes earlier than the reference. Differential acceleration signals combined with the proposed algorithm have the potential to be implemented in a future FES system.

  19. Detection and identification of multiple genetically modified events using DNA insert fingerprinting.

    PubMed

    Raymond, Philippe; Gendron, Louis; Khalf, Moustafa; Paul, Sylvianne; Dibley, Kim L; Bhat, Somanath; Xie, Vicki R D; Partis, Lina; Moreau, Marie-Eve; Dollard, Cheryl; Coté, Marie-José; Laberge, Serge; Emslie, Kerry R

    2010-03-01

    Current screening and event-specific polymerase chain reaction (PCR) assays for the detection and identification of genetically modified organisms (GMOs) in samples of unknown composition or for the detection of non-regulated GMOs have limitations, and alternative approaches are required. A transgenic DNA fingerprinting methodology using restriction enzyme digestion, adaptor ligation, and nested PCR was developed where individual GMOs are distinguished by the characteristic fingerprint pattern of the fragments generated. The inter-laboratory reproducibility of the amplified fragment sizes using different capillary electrophoresis platforms was compared, and reproducible patterns were obtained with an average difference in fragment size of 2.4 bp. DNA insert fingerprints for 12 different maize events, including two maize hybrids and one soy event, were generated that reflected the composition of the transgenic DNA constructs. Once produced, the fingerprint profiles were added to a database which can be readily exchanged and shared between laboratories. This approach should facilitate the process of GMO identification and characterization. PMID:19943159

  20. Clinical outcome of subchromosomal events detected by whole‐genome noninvasive prenatal testing

    PubMed Central

    Helgeson, J.; Wardrop, J.; Boomer, T.; Almasri, E.; Paxton, W. B.; Saldivar, J. S.; Dharajiya, N.; Monroe, T. J.; Farkas, D. H.; Grosu, D. S.

    2015-01-01

    Abstract Objective A novel algorithm to identify fetal microdeletion events in maternal plasma has been developed and used in clinical laboratory‐based noninvasive prenatal testing. We used this approach to identify the subchromosomal events 5pdel, 22q11del, 15qdel, 1p36del, 4pdel, 11qdel, and 8qdel in routine testing. We describe the clinical outcomes of those samples identified with these subchromosomal events. Methods Blood samples from high‐risk pregnant women submitted for noninvasive prenatal testing were analyzed using low coverage whole genome massively parallel sequencing. Sequencing data were analyzed using a novel algorithm to detect trisomies and microdeletions. Results In testing 175 393 samples, 55 subchromosomal deletions were reported. The overall positive predictive value for each subchromosomal aberration ranged from 60% to 100% for cases with diagnostic and clinical follow‐up information. The total false positive rate was 0.0017% for confirmed false positives results; false negative rate and sensitivity were not conclusively determined. Conclusion Noninvasive testing can be expanded into the detection of subchromosomal copy number variations, while maintaining overall high test specificity. In the current setting, our results demonstrate high positive predictive values for testing of rare subchromosomal deletions. © 2015 The Authors. Prenatal Diagnosis published by John Wiley & Sons Ltd. PMID:26088833

  1. Piezoelectric energy-harvesting power source and event detection sensors for gun-fired munitions

    NASA Astrophysics Data System (ADS)

    Rastegar, Jahangir; Feng, Dake; Pereira, Carlos M.

    2015-05-01

    This paper presents a review of piezoelectric based energy harvesting devices and their charge collection electronics for use in very harsh environment of gun-fired munitions. A number of novel classes of such energy harvesting power sources have been developed for gun-fired munitions and similar applications, including those with integrated safety and firing setback event detection electronics and logic circuitry. The power sources are designed to harvest energy from firing acceleration and vibratory motions during the flight. As an example, the application of the developed piezoelectric based energy harvesting devices with event detection circuitry for the development of self-powered initiators with full no-fire safety circuitry for protection against accidental drops, transportation vibration, and other similar low amplitude accelerations and/or high amplitude but short duration acceleration events is presented. The design allows the use of a very small piezoelectric element, thereby allowing such devices to be highly miniaturized. These devices can be readily hardened to withstand very high G firing setback accelerations in excess of 100,000 G and the harsh firing environment. The design of prototypes and testing under realistic conditions are presented.

  2. Comprehensive temporal information detection from clinical text: medical events, time, and TLINK identification

    PubMed Central

    Sohn, Sunghwan; Wagholikar, Kavishwar B; Li, Dingcheng; Jonnalagadda, Siddhartha R; Tao, Cui; Komandur Elayavilli, Ravikumar; Liu, Hongfang

    2013-01-01

    Background Temporal information detection systems have been developed by the Mayo Clinic for the 2012 i2b2 Natural Language Processing Challenge. Objective To construct automated systems for EVENT/TIMEX3 extraction and temporal link (TLINK) identification from clinical text. Materials and methods The i2b2 organizers provided 190 annotated discharge summaries as the training set and 120 discharge summaries as the test set. Our Event system used a conditional random field classifier with a variety of features including lexical information, natural language elements, and medical ontology. The TIMEX3 system employed a rule-based method using regular expression pattern match and systematic reasoning to determine normalized values. The TLINK system employed both rule-based reasoning and machine learning. All three systems were built in an Apache Unstructured Information Management Architecture framework. Results Our TIMEX3 system performed the best (F-measure of 0.900, value accuracy 0.731) among the challenge teams. The Event system produced an F-measure of 0.870, and the TLINK system an F-measure of 0.537. Conclusions Our TIMEX3 system demonstrated good capability of regular expression rules to extract and normalize time information. Event and TLINK machine learning systems required well-defined feature sets to perform well. We could also leverage expert knowledge as part of the machine learning features to further improve TLINK identification performance. PMID:23558168

  3. Detecting regular sound changes in linguistics as events of concerted evolution

    SciTech Connect

    Hruschka, Daniel  J.; Branford, Simon; Smith, Eric  D.; Wilkins, Jon; Meade, Andrew; Pagel, Mark; Bhattacharya, Tanmoy

    2014-12-18

    Background: Concerted evolution is normally used to describe parallel changes at different sites in a genome, but it is also observed in languages where a specific phoneme changes to the same other phoneme in many words in the lexicon—a phenomenon known as regular sound change. We develop a general statistical model that can detect concerted changes in aligned sequence data and apply it to study regular sound changes in the Turkic language family. Results: Linguistic evolution, unlike the genetic substitutional process, is dominated by events of concerted evolutionary change. Our model identified more than 70 historical events of regular sound change that occurred throughout the evolution of the Turkic language family, while simultaneously inferring a dated phylogenetic tree. Including regular sound changes yielded an approximately 4-fold improvement in the characterization of linguistic change over a simpler model of sporadic change, improved phylogenetic inference, and returned more reliable and plausible dates for events on the phylogenies. The historical timings of the concerted changes closely follow a Poisson process model, and the sound transition networks derived from our model mirror linguistic expectations. Conclusions: We demonstrate that a model with no prior knowledge of complex concerted or regular changes can nevertheless infer the historical timings and genealogical placements of events of concerted change from the signals left in contemporary data. Our model can be applied wherever discrete elements—such as genes, words, cultural trends, technologies, or morphological traits—can change in parallel within an organism or other evolving group.

  4. Detection of Visual Events in Underwater Video Using a Neuromorphic Saliency-based Attention System

    NASA Astrophysics Data System (ADS)

    Edgington, D. R.; Walther, D.; Cline, D. E.; Sherlock, R.; Salamy, K. A.; Wilson, A.; Koch, C.

    2003-12-01

    The Monterey Bay Aquarium Research Institute (MBARI) uses high-resolution video equipment on remotely operated vehicles (ROV) to obtain quantitative data on the distribution and abundance of oceanic animals. High-quality video data supplants the traditional approach of assessing the kinds and numbers of animals in the oceanic water column through towing collection nets behind ships. Tow nets are limited in spatial resolution, and often destroy abundant gelatinous animals resulting in species undersampling. Video camera-based quantitative video transects (QVT) are taken through the ocean midwater, from 50m to 4000m, and provide high-resolution data at the scale of the individual animals and their natural aggregation patterns. However, the current manual method of analyzing QVT video by trained scientists is labor intensive and poses a serious limitation to the amount of information that can be analyzed from ROV dives. Presented here is an automated system for detecting marine animals (events) visible in the videos. Automated detection is difficult due to the low contrast of many translucent animals and due to debris ("marine snow") cluttering the scene. Video frames are processed with an artificial intelligence attention selection algorithm that has proven a robust means of target detection in a variety of natural terrestrial scenes. The candidate locations identified by the attention selection module are tracked across video frames using linear Kalman filters. Typically, the occurrence of visible animals in the video footage is sparse in space and time. A notion of "boring" video frames is developed by detecting whether or not there is an interesting candidate object for an animal present in a particular sequence of underwater video -- video frames that do not contain any "interesting" events. If objects can be tracked successfully over several frames, they are stored as potentially "interesting" events. Based on low-level properties, interesting events are

  5. Use of a Novel High-Resolution Magnetic Resonance Neurography Protocol to Detect Abnormal Dorsal Root Ganglia in Sjögren Patients With Neuropathic Pain

    PubMed Central

    Birnbaum, Julius; Duncan, Trisha; Owoyemi, Kristie; Wang, Kenneth C.; Carrino, John; Chhabra, Avneesh

    2014-01-01

    whose neuropathic pain resolved with intravenous immunoglobulin (IVIg) therapy had improvement of MRN DRG abnormalities. We have developed a novel MRN protocol that can detect DRG abnormalities in SS patients with neuropathic pain who do not have markers of peripheral neuropathy. We found that SS patients with MRN DRG abnormalities had statistically significant, increased IENFD on skin biopsy studies, which may suggest a relationship between trophic mediators and neuropathic pain. Given that our literature review has demonstrated that many SS neuropathic pain patients do not have a neuropathy, our findings suggest an important niche for this MRN DRG technique in the evaluation of broader subsets of SS neuropathic pain patients who may not have underlying neuropathies. The improvement of MRN DRG abnormalities in patients with IVIg-induced remission of neuropathic pain suggests that our MRN protocol may be capturing reversible, immune-mediated mechanisms targeting the DRG. PMID:24797167

  6. Rapid and reliable detection and identification of GM events using multiplex PCR coupled with oligonucleotide microarray.

    PubMed

    Xu, Xiaodan; Li, Yingcong; Zhao, Heng; Wen, Si-yuan; Wang, Sheng-qi; Huang, Jian; Huang, Kun-lun; Luo, Yun-bo

    2005-05-18

    To devise a rapid and reliable method for the detection and identification of genetically modified (GM) events, we developed a multiplex polymerase chain reaction (PCR) coupled with a DNA microarray system simultaneously aiming at many targets in a single reaction. The system included probes for screening gene, species reference gene, specific gene, construct-specific gene, event-specific gene, and internal and negative control genes. 18S rRNA was combined with species reference genes as internal controls to assess the efficiency of all reactions and to eliminate false negatives. Two sets of the multiplex PCR system were used to amplify four and five targets, respectively. Eight different structure genes could be detected and identified simultaneously for Roundup Ready soybean in a single microarray. The microarray specificity was validated by its ability to discriminate two GM maizes Bt176 and Bt11. The advantages of this method are its high specificity and greatly reduced false-positives and -negatives. The multiplex PCR coupled with microarray technology presented here is a rapid and reliable tool for the simultaneous detection of GM organism ingredients.

  7. Application of Data Cubes for Improving Detection of Water Cycle Extreme Events

    NASA Technical Reports Server (NTRS)

    Albayrak, Arif; Teng, William

    2015-01-01

    As part of an ongoing NASA-funded project to remove a longstanding barrier to accessing NASA data (i.e., accessing archived time-step array data as point-time series), for the hydrology and other point-time series-oriented communities, "data cubes" are created from which time series files (aka "data rods") are generated on-the-fly and made available as Web services from the Goddard Earth Sciences Data and Information Services Center (GES DISC). Data cubes are data as archived rearranged into spatio-temporal matrices, which allow for easy access to the data, both spatially and temporally. A data cube is a specific case of the general optimal strategy of reorganizing data to match the desired means of access. The gain from such reorganization is greater the larger the data set. As a use case of our project, we are leveraging existing software to explore the application of the data cubes concept to machine learning, for the purpose of detecting water cycle extreme events, a specific case of anomaly detection, requiring time series data. We investigate the use of support vector machines (SVM) for anomaly classification. We show an example of detection of water cycle extreme events, using data from the Tropical Rainfall Measuring Mission (TRMM).

  8. Detecting tidal disruption events of massive black holes in normal galaxies with the Einstein Probe

    NASA Astrophysics Data System (ADS)

    Yuan, W.; Komossa, S.; Zhang, C.; Feng, H.; Ling, Z.-X.; Zhao, D. H.; Zhang, S.-N.; Osborne, J. P.; O'Brien, P.; Willingale, R.; Lapington, J.; Lapington

    2016-02-01

    Stars are tidally disrupted and accreted when they approach massive black holes (MBHs) closely, producing a flare of electromagnetic radiation. The majority of the (approximately two dozen) tidal disruption events (TDEs) identified so far have been discovered by their luminous, transient X-ray emission. Once TDEs are detected in much larger numbers, in future dedicated transient surveys, a wealth of new applications will become possible. Here, we present the proposed Einstein Probe mission, which is a dedicated time-domain soft X-ray all-sky monitor aiming at detecting X-ray transients including TDEs in large numbers. The mission consists of a wide-field micro-pore Lobster-eye imager (60° × 60°), and is designed to carry out an all-sky transient survey at energies of 0.5-4 keV. It will also carry a more sensitive telescope for X-ray follow-ups, and will be capable of issuing public transient alerts rapidly. Einstein Probe is expected to revolutionise the field of TDE research by detecting several tens to hundreds of events per year from the early phase of flares, many with long-term, well sampled lightcurves.

  9. Diagnostic value of fasting capillary glucose, fructosamine and glycosylated haemoglobin in detecting diabetes and other glucose tolerance abnormalities compared to oral glucose tolerance test.

    PubMed

    Herdzik, E; Safranow, K; Ciechanowski, K

    2002-04-01

    New diagnostic criteria for diabetes mellitus recommend lowering of the fasting plasma glucose to 7.0 mmol/l. In contrast to recommendations of the American Diabetes Association (ADA), WHO recommends using the oral glucose tolerance test (OGTT) in clinical practice. In this study. based on OGTT results and WHO 1998 criteria, we determined if measuring fasting capillary glycaemia (FCG) along with fructosamine and/or glycosylated haemoglobin allows the detection of glucose tolerance abnormalities better than FCG alone. OGTT was performed in 538 patients. Serum fructosamine was determined in 480 of the patients, and glycosylated haemoglobin in 234 of the patients. According to WHO 1998 criteria, the patients were divided into groups due to glucose tolerance abnormalities. Fructosamine correlated stronger with 2-h post-load glucose concentrations than with FCG. HbAlc correlated stronger with FCG than with 2-h post-load glucose. Combined use of fructosamine and FCG predicted 2-h post-load glucose better than combined use of FCG and HbA1c. Receiver operating characteristic curve analyses showed that FCG was the best criterion in discriminating diabetes. Combined use of FCG and fructosamine slightly improved the ability to discriminate glucose tolerance abnormalities from normal glucose tolerance. FCG is the most effective predictor of 2-h post-load glucose and the best criterion for discriminating diabetes and other glucose tolerance abnormalities from normal glucose tolerance. Fructosamine is a potentially useful post-load glycaemia index. OGTT is irreplaceable in identification of patients with high post-load glycaemia.

  10. Hierarchical modeling for rare event detection and cell subset alignment across flow cytometry samples.

    PubMed

    Cron, Andrew; Gouttefangeas, Cécile; Frelinger, Jacob; Lin, Lin; Singh, Satwinder K; Britten, Cedrik M; Welters, Marij J P; van der Burg, Sjoerd H; West, Mike; Chan, Cliburn

    2013-01-01

    Flow cytometry is the prototypical assay for multi-parameter single cell analysis, and is essential in vaccine and biomarker research for the enumeration of antigen-specific lymphocytes that are often found in extremely low frequencies (0.1% or less). Standard analysis of flow cytometry data relies on visual identification of cell subsets by experts, a process that is subjective and often difficult to reproduce. An alternative and more objective approach is the use of statistical models to identify cell subsets of interest in an automated fashion. Two specific challenges for automated analysis are to detect extremely low frequency event subsets without biasing the estimate by pre-processing enrichment, and the ability to align cell subsets across multiple data samples for comparative analysis. In this manuscript, we develop hierarchical modeling extensions to the Dirichlet Process Gaussian Mixture Model (DPGMM) approach we have previously described for cell subset identification, and show that the hierarchical DPGMM (HDPGMM) naturally generates an aligned data model that captures both commonalities and variations across multiple samples. HDPGMM also increases the sensitivity to extremely low frequency events by sharing information across multiple samples analyzed simultaneously. We validate the accuracy and reproducibility of HDPGMM estimates of antigen-specific T cells on clinically relevant reference peripheral blood mononuclear cell (PBMC) samples with known frequencies of antigen-specific T cells. These cell samples take advantage of retrovirally TCR-transduced T cells spiked into autologous PBMC samples to give a defined number of antigen-specific T cells detectable by HLA-peptide multimer binding. We provide open source software that can take advantage of both multiple processors and GPU-acceleration to perform the numerically-demanding computations. We show that hierarchical modeling is a useful probabilistic approach that can provide a consistent labeling

  11. BIRD detection and analysis of high-temperature events: first results

    NASA Astrophysics Data System (ADS)

    Zhukov, Boris; Briess, Klaus; Lorenz, Eckehard; Oertel, Dieter; Skrbek, Wolfgang

    2003-03-01

    The primary mission objective of a new small Bi-spectral InfraRed Detection (BIRD) satellite, which was put in a 570 km circular sun-synchronous orbit on 22 October 2001, is detection and quantitative analysis of high-temperature events (HTE) like fires and volcanoes. A unique feature of the BIRD mid- and thermal infrared channels is a real-time adjustment of their integration time that allows a HTE observation without sensor saturation, preserving a good radiometric resolution of 0.1-0.2 K for pixels at normal temperatures. This makes it possible: (a) to improve false alarm rejection capability and (b) to estimate HTE temperature, area and radiative energy release. Due to a higher spatial resolution, BIRD can detect an order of magnitude smaller HTE than AVHRR and MODIS. The smallest verified fire that was detected in the BIRD data had an area of ~12 m2. The first BIRD HTE detection and analysis results are presented including bush fires in Australia, forest fires in Russia, coal seam fires in China, and a time-varying thermal activity at Etna.

  12. Gait event detection on level ground and incline walking using a rate gyroscope.

    PubMed

    Catalfamo, Paola; Ghoussayni, Salim; Ewins, David

    2010-01-01

    Gyroscopes have been proposed as sensors for ambulatory gait analysis and functional electrical stimulation systems. Accurate determination of the Initial Contact of the foot with the floor (IC) and the final contact or Foot Off (FO) on different terrains is important. This paper describes the evaluation of a gyroscope placed on the shank for determination of IC and FO in subjects walking outdoors on level ground, and up and down an incline. Performance was compared with a reference pressure measurement system. The mean difference between the gyroscope and the reference was less than -25 ms for IC and less than 75 ms for FO for all terrains. Detection success was over 98%. These results provide preliminary evidence supporting the use of the gyroscope for gait event detection on inclines as well as level walking.

  13. Label-Free Detection of Single Living Bacteria via Electrochemical Collision Event.

    PubMed

    Lee, Ji Young; Kim, Byung-Kwon; Kang, Mijeong; Park, Jun Hui

    2016-01-01

    We detected single living bacterial cells on ultramicroelectrode (UME) using a single-particle collision method and optical microscopic methods. The number of collision events involving the bacterial cells indicated in current-time (i-t) curves corresponds to the number of bacterial cells (i.e., Escherichia coli) on the UME surface, as observed visually. Simulations were performed to determine the theoretical current response (75 pA) and frequency (0.47 pM(-1) s(-1)) of single Escherichia coli collisions. The experimental current response (83 pA) and frequency (0.26 pM(-1) s(-1)) were on the same order of magnitude as the theoretical values. This single-particle collision approach facilitates detecting living bacteria and determining their concentration in solution and could be widely applied to studying other bacteria and biomolecules. PMID:27435527

  14. Detecting event-related recurrences by symbolic analysis: applications to human language processing

    PubMed Central

    beim Graben, Peter; Hutt, Axel

    2015-01-01

    Quasi-stationarity is ubiquitous in complex dynamical systems. In brain dynamics, there is ample evidence that event-related potentials (ERPs) reflect such quasi-stationary states. In order to detect them from time series, several segmentation techniques have been proposed. In this study, we elaborate a recent approach for detecting quasi-stationary states as recurrence domains by means of recurrence analysis and subsequent symbolization methods. We address two pertinent problems of contemporary recurrence analysis: optimizing the size of recurrence neighbourhoods and identifying symbols from different realizations for sequence alignment. As possible solutions for these problems, we suggest a maximum entropy criterion and a Hausdorff clustering algorithm. The resulting recurrence domains for single-subject ERPs are obtained as partition cells reflecting quasi-stationary brain states. PMID:25548270

  15. Label-Free Detection of Single Living Bacteria via Electrochemical Collision Event

    NASA Astrophysics Data System (ADS)

    Lee, Ji Young; Kim, Byung-Kwon; Kang, Mijeong; Park, Jun Hui

    2016-07-01

    We detected single living bacterial cells on ultramicroelectrode (UME) using a single-particle collision method and optical microscopic methods. The number of collision events involving the bacterial cells indicated in current-time (i-t) curves corresponds to the number of bacterial cells (i.e., Escherichia coli) on the UME surface, as observed visually. Simulations were performed to determine the theoretical current response (75 pA) and frequency (0.47 pM‑1 s‑1) of single Escherichia coli collisions. The experimental current response (83 pA) and frequency (0.26 pM‑1 s‑1) were on the same order of magnitude as the theoretical values. This single-particle collision approach facilitates detecting living bacteria and determining their concentration in solution and could be widely applied to studying other bacteria and biomolecules.

  16. Label-Free Detection of Single Living Bacteria via Electrochemical Collision Event

    PubMed Central

    Lee, Ji Young; Kim, Byung-Kwon; Kang, Mijeong; Park, Jun Hui

    2016-01-01

    We detected single living bacterial cells on ultramicroelectrode (UME) using a single-particle collision method and optical microscopic methods. The number of collision events involving the bacterial cells indicated in current-time (i-t) curves corresponds to the number of bacterial cells (i.e., Escherichia coli) on the UME surface, as observed visually. Simulations were performed to determine the theoretical current response (75 pA) and frequency (0.47 pM−1 s−1) of single Escherichia coli collisions. The experimental current response (83 pA) and frequency (0.26 pM−1 s−1) were on the same order of magnitude as the theoretical values. This single-particle collision approach facilitates detecting living bacteria and determining their concentration in solution and could be widely applied to studying other bacteria and biomolecules. PMID:27435527

  17. Optimized Swinging Door Algorithm for Wind Power Ramp Event Detection: Preprint

    SciTech Connect

    Cui, Mingjian; Zhang, Jie; Florita, Anthony R.; Hodge, Bri-Mathias; Ke, Deping; Sun, Yuanzhang

    2015-08-06

    Significant wind power ramp events (WPREs) are those that influence the integration of wind power, and they are a concern to the continued reliable operation of the power grid. As wind power penetration has increased in recent years, so has the importance of wind power ramps. In this paper, an optimized swinging door algorithm (SDA) is developed to improve ramp detection performance. Wind power time series data are segmented by the original SDA, and then all significant ramps are detected and merged through a dynamic programming algorithm. An application of the optimized SDA is provided to ascertain the optimal parameter of the original SDA. Measured wind power data from the Electric Reliability Council of Texas (ERCOT) are used to evaluate the proposed optimized SDA.

  18. Gait Event Detection on Level Ground and Incline Walking Using a Rate Gyroscope

    PubMed Central

    Catalfamo, Paola; Ghoussayni, Salim; Ewins, David

    2010-01-01

    Gyroscopes have been proposed as sensors for ambulatory gait analysis and functional electrical stimulation systems. Accurate determination of the Initial Contact of the foot with the floor (IC) and the final contact or Foot Off (FO) on different terrains is important. This paper describes the evaluation of a gyroscope placed on the shank for determination of IC and FO in subjects walking outdoors on level ground, and up and down an incline. Performance was compared with a reference pressure measurement system. The mean difference between the gyroscope and the reference was less than −25 ms for IC and less than 75 ms for FO for all terrains. Detection success was over 98%. These results provide preliminary evidence supporting the use of the gyroscope for gait event detection on inclines as well as level walking. PMID:22219682

  19. Detection of planets in extremely weak central perturbation microlensing events via next-generation ground-based surveys

    SciTech Connect

    Chung, Sun-Ju; Lee, Chung-Uk; Koo, Jae-Rim E-mail: leecu@kasi.re.kr

    2014-04-20

    Even though the recently discovered high-magnification event MOA-2010-BLG-311 had complete coverage over its peak, confident planet detection did not happen due to extremely weak central perturbations (EWCPs, fractional deviations of ≲ 2%). For confident detection of planets in EWCP events, it is necessary to have both high cadence monitoring and high photometric accuracy better than those of current follow-up observation systems. The next-generation ground-based observation project, Korea Microlensing Telescope Network (KMTNet), satisfies these conditions. We estimate the probability of occurrence of EWCP events with fractional deviations of ≤2% in high-magnification events and the efficiency of detecting planets in the EWCP events using the KMTNet. From this study, we find that the EWCP events occur with a frequency of >50% in the case of ≲ 100 M {sub E} planets with separations of 0.2 AU ≲ d ≲ 20 AU. We find that for main-sequence and sub-giant source stars, ≳ 1 M {sub E} planets in EWCP events with deviations ≤2% can be detected with frequency >50% in a certain range that changes with the planet mass. However, it is difficult to detect planets in EWCP events of bright stars like giant stars because it is easy for KMTNet to be saturated around the peak of the events because of its constant exposure time. EWCP events are caused by close, intermediate, and wide planetary systems with low-mass planets and close and wide planetary systems with massive planets. Therefore, we expect that a much greater variety of planetary systems than those already detected, which are mostly intermediate planetary systems, regardless of the planet mass, will be significantly detected in the near future.

  20. Automatic Detection of Whole Night Snoring Events Using Non-Contact Microphone

    PubMed Central

    Dafna, Eliran; Tarasiuk, Ariel; Zigel, Yaniv

    2013-01-01

    Objective Although awareness of sleep disorders is increasing, limited information is available on whole night detection of snoring. Our study aimed to develop and validate a robust, high performance, and sensitive whole-night snore detector based on non-contact technology. Design Sounds during polysomnography (PSG) were recorded using a directional condenser microphone placed 1 m above the bed. An AdaBoost classifier was trained and validated on manually labeled snoring and non-snoring acoustic events. Patients Sixty-seven subjects (age 52.5±13.5 years, BMI 30.8±4.7 kg/m2, m/f 40/27) referred for PSG for obstructive sleep apnea diagnoses were prospectively and consecutively recruited. Twenty-five subjects were used for the design study; the validation study was blindly performed on the remaining forty-two subjects. Measurements and Results To train the proposed sound detector, >76,600 acoustic episodes collected in the design study were manually classified by three scorers into snore and non-snore episodes (e.g., bedding noise, coughing, environmental). A feature selection process was applied to select the most discriminative features extracted from time and spectral domains. The average snore/non-snore detection rate (accuracy) for the design group was 98.4% based on a ten-fold cross-validation technique. When tested on the validation group, the average detection rate was 98.2% with sensitivity of 98.0% (snore as a snore) and specificity of 98.3% (noise as noise). Conclusions Audio-based features extracted from time and spectral domains can accurately discriminate between snore and non-snore acoustic events. This audio analysis approach enables detection and analysis of snoring sounds from a full night in order to produce quantified measures for objective follow-up of patients. PMID:24391903

  1. Large-Scale Disturbance Events in Terrestrial Ecosystems Detected using Global Satellite Data Sets

    NASA Astrophysics Data System (ADS)

    Potter, C.; Tan, P.; Kumar, V.; Klooster, S.

    2004-12-01

    Studies are being conducted to evaluate patterns in a 19-year record of global satellite observations of vegetation phenology from the Advanced Very High Resolution Radiometer (AVHRR), as a means to characterize large-scale ecosystem disturbance events and regimes. The fraction absorbed of photosynthetically active radiation (FPAR) by vegetation canopies worldwide has been computed at a monthly time interval from 1982 to 2000 and gridded at a spatial resolution of 8-km globally. Potential disturbance events were identified in the FPAR time series by locating anomalously low values (FPAR-LO) that lasted longer than 12 consecutive months at any 8-km pixel. We can find verifiable evidence of numerous disturbance types across North America, including major regional patterns of cold and heat waves, forest fires, tropical storms, and large-scale forest logging. Based on this analysis, an historical picture is emerging of periodic droughts and heat waves, possibly coupled with herbivorous insect outbreaks, as among the most important causes of ecosystem disturbance in North America. In South America, large areas of northeastern Brazil appear to have been impacted in the early 1990s by severe drought. Amazon tropical forest disturbance can be detected at large scales particularly in the mid 1990s. In Asia, large-scale disturbance events appear in the mid 1980s and the late 1990s across boreal and temperate forest zones, as well as in cropland areas of western India. In northern Europe and central Africa, large-scale forest disturbance appears in the mid 1990s.

  2. Endpoint Visual Detection of Three Genetically Modified Rice Events by Loop-Mediated Isothermal Amplification

    PubMed Central

    Chen, Xiaoyun; Wang, Xiaofu; Jin, Nuo; Zhou, Yu; Huang, Sainan; Miao, Qingmei; Zhu, Qing; Xu, Junfeng

    2012-01-01

    Genetically modified (GM) rice KMD1, TT51-1, and KF6 are three of the most well known transgenic Bt rice lines in China. A rapid and sensitive molecular assay for risk assessment of GM rice is needed. Polymerase chain reaction (PCR), currently the most common method for detecting genetically modified organisms, requires temperature cycling and relatively complex procedures. Here we developed a visual and rapid loop-mediated isothermal amplification (LAMP) method to amplify three GM rice event-specific junction sequences. Target DNA was amplified and visualized by two indicators (SYBR green or hydroxy naphthol blue [HNB]) within 60 min at an isothermal temperature of 63 °C. Different kinds of plants were selected to ensure the specificity of detection and the results of the non-target samples were negative, indicating that the primer sets for the three GM rice varieties had good levels of specificity. The sensitivity of LAMP, with detection limits at low concentration levels (0.01%–0.005% GM), was 10- to 100-fold greater than that of conventional PCR. Additionally, the LAMP assay coupled with an indicator (SYBR green or HNB) facilitated analysis. These findings revealed that the rapid detection method was suitable as a simple field-based test to determine the status of GM crops. PMID:23203072

  3. The Waveform Correlation Event Detection System project, Phase II: Testing with the IDC primary network

    SciTech Connect

    Young, C.J.; Beiriger, J.I.; Moore, S.G.

    1998-04-01

    Further improvements to the Waveform Correlation Event Detection System (WCEDS) developed by Sandia Laboratory have made it possible to test the system on the accepted Comprehensive Test Ban Treaty (CTBT) seismic monitoring network. For our test interval we selected a 24-hour period from December 1996, and chose to use the Reviewed Event Bulletin (REB) produced by the Prototype International Data Center (PIDC) as ground truth for evaluating the results. The network is heterogeneous, consisting of array and three-component sites, and as a result requires more flexible waveform processing algorithms than were available in the first version of the system. For simplicity and superior performance, we opted to use the spatial coherency algorithm of Wagner and Owens (1996) for both types of sites. Preliminary tests indicated that the existing version of WCEDS, which ignored directional information, could not achieve satisfactory detection or location performance for many of the smaller events in the REB, particularly those in the south Pacific where the network coverage is unusually sparse. To achieve an acceptable level of performance, we made modifications to include directional consistency checks for the correlations, making the regions of high correlation much less ambiguous. These checks require the production of continuous azimuth and slowness streams for each station, which is accomplished by means of FK processing for the arrays and power polarization processing for the three-component sites. In addition, we added the capability to use multiple frequency-banded data streams for each site to increase sensitivity to phases whose frequency content changes as a function of distance.

  4. Automatic Event Detection and Characterization of solar events with IRIS, SDO/AIA and Hi-C

    NASA Astrophysics Data System (ADS)

    Alexander, Caroline; Fayock, Brian; Winebarger, Amy

    2016-05-01

    Dynamic, low-lying loops with peak temperatures <1 MK are observed throughout the solar transition region. These loops can be observed in SDO/AIA data due to some lower temperature spectral lines in the passbands, but have not been studied in great detail. We have developed a technique to automatically identify events (i.e., brightenings) on a pixel-by-pixel basis applying a set of selection criteria. The pixels are then grouped according to their proximity in space and relative progression of the event. This method allows us to characterize their overall lifetime and the rate at which these events occur. Our current progress includes identification of these groups of events in IRIS data, determination of their existence in AIA data, and characterization based on a comparison between the two. This technique has also been used on Hi-C data in preparation for the rocket re-flight in July 2016. Results on the success of this technique at identifying real structures and sources of heating will be shown.

  5. Detecting regular sound changes in linguistics as events of concerted evolution

    DOE PAGES

    Hruschka, Daniel  J.; Branford, Simon; Smith, Eric  D.; Wilkins, Jon; Meade, Andrew; Pagel, Mark; Bhattacharya, Tanmoy

    2014-12-18

    Background: Concerted evolution is normally used to describe parallel changes at different sites in a genome, but it is also observed in languages where a specific phoneme changes to the same other phoneme in many words in the lexicon—a phenomenon known as regular sound change. We develop a general statistical model that can detect concerted changes in aligned sequence data and apply it to study regular sound changes in the Turkic language family. Results: Linguistic evolution, unlike the genetic substitutional process, is dominated by events of concerted evolutionary change. Our model identified more than 70 historical events of regular soundmore » change that occurred throughout the evolution of the Turkic language family, while simultaneously inferring a dated phylogenetic tree. Including regular sound changes yielded an approximately 4-fold improvement in the characterization of linguistic change over a simpler model of sporadic change, improved phylogenetic inference, and returned more reliable and plausible dates for events on the phylogenies. The historical timings of the concerted changes closely follow a Poisson process model, and the sound transition networks derived from our model mirror linguistic expectations. Conclusions: We demonstrate that a model with no prior knowledge of complex concerted or regular changes can nevertheless infer the historical timings and genealogical placements of events of concerted change from the signals left in contemporary data. Our model can be applied wherever discrete elements—such as genes, words, cultural trends, technologies, or morphological traits—can change in parallel within an organism or other evolving group.« less

  6. Unreported seismic events found far off-shore Mexico using full-waveform, cross-correlation detection method.

    NASA Astrophysics Data System (ADS)

    Solano, ErickaAlinne; Hjorleifsdottir, Vala; Perez-Campos, Xyoli

    2015-04-01

    A large subset of seismic events do not have impulsive arrivals, such as low frequency events in volcanoes, earthquakes in the shallow part of the subduction interface and further down dip from the traditional seismogenic part, glacial events, volcanic and non-volcanic tremors and landslides. A suite of methods can be used to detect these non-impulsive events. One of this methods is the full-waveform detection based on time reversal methods (Solano, et al , submitted to GJI). The method uses continuous observed seismograms, together with Greens functions and moment tensor responses calculated for an arbitrary 3D structure. This method was applied to the 2012 Ometepec-Pinotepa Nacional earthquake sequence in Guerrero, Mexico. During the span time of the study, we encountered three previously unknown events. One of this events was an impulsive earthquake in the Ometepec area, that only has clear arrivals on three stations and was therefore not located and reported by the SSN. The other two events are previously undetected events, very depleted in high frequencies, that occurred far outside the search area. A very rough estimate gives the location of this two events in the portion of the East Pacific Rise around 9 N. These two events are detected despite their distance from the search area, due to favorable move-out on the array of the Mexican National Seismological Service network (SSN). We are expanding the study area to the EPR and to a larger period of time, with the objective of finding more events in that region. We will present an analysis of the newly detected events, as well as any further findings at the meeting.

  7. Validity assessment of the detection method of maize event Bt10 through investigation of its molecular structure.

    PubMed

    Milcamps, Anne; Rabe, Scott; Cade, Rebecca; De Framond, Anic J; Henriksson, Peter; Kramer, Vance; Lisboa, Duarte; Pastor-Benito, Susana; Willits, Michael G; Lawrence, David; Van den Eede, Guy

    2009-04-22

    In March 2005, U.S. authorities informed the European Commission of the inadvertent release of unauthorized maize GM event Bt10 in their market and subsequently the grain channel. In the United States measures were taken to eliminate Bt10 from seed and grain supplies; in the European Union an embargo for maize gluten and brewer's grain import was implemented unless certified of Bt10 absence with a Bt10-specific PCR detection method. With the aim of assessing the validity of the Bt10 detection method, an in-depth analysis of the molecular organization of the genetic modification of this event was carried out by both the company Syngenta, who produced the event, and the European Commission Joint Research Centre, who validated the detection method. Using a variety of molecular analytical tools, both organizations found the genetic modification of event Bt10 to be very complex in structure, with rearrangements, inversions, and multiple copies of the structural elements (cry1Ab, pat, and the amp gene), interspersed with small genomic maize fragments. Southern blot analyses demonstrated that all Bt10 elements were found tightly linked on one large fragment, including the region that would generate the event-specific PCR amplicon of the Bt10 detection method. This study proposes a hypothetical map of the insert of event Bt10 and concludes that the validated detection method for event Bt10 is fit for its purpose.

  8. Validity assessment of the detection method of maize event Bt10 through investigation of its molecular structure.

    PubMed

    Milcamps, Anne; Rabe, Scott; Cade, Rebecca; De Framond, Anic J; Henriksson, Peter; Kramer, Vance; Lisboa, Duarte; Pastor-Benito, Susana; Willits, Michael G; Lawrence, David; Van den Eede, Guy

    2009-04-22

    In March 2005, U.S. authorities informed the European Commission of the inadvertent release of unauthorized maize GM event Bt10 in their market and subsequently the grain channel. In the United States measures were taken to eliminate Bt10 from seed and grain supplies; in the European Union an embargo for maize gluten and brewer's grain import was implemented unless certified of Bt10 absence with a Bt10-specific PCR detection method. With the aim of assessing the validity of the Bt10 detection method, an in-depth analysis of the molecular organization of the genetic modification of this event was carried out by both the company Syngenta, who produced the event, and the European Commission Joint Research Centre, who validated the detection method. Using a variety of molecular analytical tools, both organizations found the genetic modification of event Bt10 to be very complex in structure, with rearrangements, inversions, and multiple copies of the structural elements (cry1Ab, pat, and the amp gene), interspersed with small genomic maize fragments. Southern blot analyses demonstrated that all Bt10 elements were found tightly linked on one large fragment, including the region that would generate the event-specific PCR amplicon of the Bt10 detection method. This study proposes a hypothetical map of the insert of event Bt10 and concludes that the validated detection method for event Bt10 is fit for its purpose. PMID:19368351

  9. Predictors of Arrhythmic Events Detected by Implantable Loop Recorders in Renal Transplant Candidates

    PubMed Central

    Silva, Rodrigo Tavares; Martinelli Filho, Martino; Peixoto, Giselle de Lima; de Lima, José Jayme Galvão; de Siqueira, Sérgio Freitas; Costa, Roberto; Gowdak, Luís Henrique Wolff; de Paula, Flávio Jota; Kalil Filho, Roberto; Ramires, José Antônio Franchini

    2015-01-01

    Background The recording of arrhythmic events (AE) in renal transplant candidates (RTCs) undergoing dialysis is limited by conventional electrocardiography. However, continuous cardiac rhythm monitoring seems to be more appropriate due to automatic detection of arrhythmia, but this method has not been used. Objective We aimed to investigate the incidence and predictors of AE in RTCs using an implantable loop recorder (ILR). Methods A prospective observational study conducted from June 2009 to January 2011 included 100 consecutive ambulatory RTCs who underwent ILR and were followed-up for at least 1 year. Multivariate logistic regression was applied to define predictors of AE. Results During a mean follow-up of 424 ± 127 days, AE could be detected in 98% of patients, and 92% had more than one type of arrhythmia, with most considered potentially not serious. Sustained atrial tachycardia and atrial fibrillation occurred in 7% and 13% of patients, respectively, and bradyarrhythmia and non-sustained or sustained ventricular tachycardia (VT) occurred in 25% and 57%, respectively. There were 18 deaths, of which 7 were sudden cardiac events: 3 bradyarrhythmias, 1 ventricular fibrillation, 1 myocardial infarction, and 2 undetermined. The presence of a long QTc (odds ratio [OR] = 7.28; 95% confidence interval [CI], 2.01–26.35; p = 0.002), and the duration of the PR interval (OR = 1.05; 95% CI, 1.02–1.08; p < 0.001) were independently associated with bradyarrhythmias. Left ventricular dilatation (LVD) was independently associated with non-sustained VT (OR = 2.83; 95% CI, 1.01–7.96; p = 0.041). Conclusions In medium-term follow-up of RTCs, ILR helped detect a high incidence of AE, most of which did not have clinical relevance. The PR interval and presence of long QTc were predictive of bradyarrhythmias, whereas LVD was predictive of non-sustained VT. PMID:26351983

  10. The ADENOMA Study. Accuracy of Detection using Endocuff Vision™ Optimization of Mucosal Abnormalities: study protocol for randomized controlled trial

    PubMed Central

    Bevan, Roisin; Ngu, Wee Sing; Saunders, Brian P.; Tsiamoulos, Zacharias; Bassett, Paul; Hoare, Zoe; Rees, Colin J.

    2016-01-01

    Background: Colonoscopy is the gold standard investigation for the diagnosis of bowel pathology and colorectal cancer screening. Adenoma detection rate is a marker of high quality colonoscopy and a high adenoma detection rate is associated with a lower incidence of interval cancers. Several technological advancements have been explored to improve adenoma detection rate. A new device called Endocuff Vision™ has been shown to improve adenoma detection rate in pilot studies. Methods/Design: This is a prospective, multicenter, randomized controlled trial comparing the adenoma detection rate in patients undergoing Endocuff Vision™-assisted colonoscopy with standard colonoscopy. All patients above 18 years of age referred for screening, surveillance, or diagnostic colonoscopy who are able to consent are invited to the study. Patients with absolute contraindications to colonoscopy, large bowel obstruction or pseudo-obstruction, colon cancer or polyposis syndromes, colonic strictures, severe diverticular segments, active colitis, anticoagulant therapy, or pregnancy are excluded. Patients are randomized according to site, age, sex, and bowel cancer screening status to receive Endocuff Vision™-assisted colonoscopy or standard colonoscopy on the day of procedure. Baseline data, colonoscopy, and polyp data including histology are collected. Nurse assessment of patient comfort and patient comfort questionnaires are completed post procedure. Patients are followed up at 21 days and complete a patient experience questionnaire. This study will take place across seven NHS Hospital Trusts: one in London and six within the Northern Region Endoscopy Group. A maximum of 10 colonoscopists per site will recruit a total of 1772 patients, with a maximum of four bowel screening colonoscopists permitted per site. Discussion: This is the first trial to evaluate the adenoma detection rate of Endocuff Vision™ in all screening, surveillance, and diagnostic patient groups. This timely

  11. Detection of p53 gene abnormality by sequence analysis of archival paraffin tissue. A comparison with fresh-frozen specimens.

    PubMed

    Nadji, M; Meng, L; Lin, L; Nassiri, M; Morales, A R

    1996-12-01

    This parallel study was designed to compare the sensitivity and specificity of detection of point mutations in fresh-frozen and formalin-fixed, paraffin-embedded breast cancer tissue. Sequence analysis of exon 5 of p53 gene was performed on polymerase chain reaction-amplified DNA from 25 infiltrating ductal carcinomas of the breast. Four tumor showed mutations with identical base substitutions in their respective codons of both frozen and paraffin-embedded specimens. We conclude that subtle genetic alterations can be detected in archival paraffin tissue with an accuracy comparable to that of fresh-frozen histologic samples.

  12. Hierarchical representation and machine learning from faulty jet engine behavioral examples to detect real time abnormal conditions

    NASA Technical Reports Server (NTRS)

    Gupta, U. K.; Ali, M.

    1988-01-01

    The theoretical basis and operation of LEBEX, a machine-learning system for jet-engine performance monitoring, are described. The behavior of the engine is modeled in terms of four parameters (the rotational speeds of the high- and low-speed sections and the exhaust and combustion temperatures), and parameter variations indicating malfunction are transformed into structural representations involving instances and events. LEBEX extracts descriptors from a set of training data on normal and faulty engines, represents them hierarchically in a knowledge base, and uses them to diagnose and predict faults on a real-time basis. Diagrams of the system architecture and printouts of typical results are shown.

  13. Validity of acoustic quantification colour kinesis for detection of left ventricular regional wall motion abnormalities: a transoesophageal echocardiographic study.

    PubMed

    Hartmann, T; Kolev, N; Blaicher, A; Spiss, C; Zimpfer, M

    1997-10-01

    Transoesophageal echocardiography is a sensitive monitor for intraoperative myocardial ischaemia. Colour kinesis is a new technology for echocardiographic assessment of regional wall motion based on acoustic quantification. We have examined the feasibility and accuracy of quantitative segmental analysis of colour kinesis images to provide objective evaluation of systolic regional wall motion during the perioperative period using transoesophageal echocardiography (TOE). Two-dimensional echocardiograms were obtained in the transgastric short-axis and long-axis views in 60 patients with coronary artery disease undergoing noncardiac surgery. End-systolic colour overlays superimposed on the grey scale images were obtained with colour kinesis to colour encode left ventricular endocardial motion throughout systole. These colour-encoded images were divided into segments and compared with corresponding conventional two-dimensional images. Six hundred of a potential 720 left ventricular wall segments were of sufficient resolution for grading by experts; they diagnosed wall motion abnormalities in 61 of these segments by a conventional method. In comparing the conventional TOE method with colour kinesis, there were 60 true positives, 482 true negatives, 57 false positives and 1 false negative result. This yielded a sensitivity of 98%, specificity of 89%, positive predictive value of 51% and negative predictive value of 100%. Translational and rotational movement of the heart and papillary muscle interference were common problems accounting for false positive diagnoses. We conclude that colour kinesis provides a basis for objective and on-line evaluation of left ventricular regional wall motion which is a sensitive but non-specific method. It may be a useful aid for the less experienced because it can potentially direct the anaesthetist's attention towards specific segments.

  14. Microcalcifications Detected as an Abnormality on Screening Mammography: Outcomes and Followup over a Five-Year Period.

    PubMed

    Craft, Melissa; Bicknell, Anne M; Hazan, Georges J; Flegg, Karen M

    2013-01-01

    Objectives. This study reviewed the outcome of women attending a breast screening program recalled for assessment of microcalcifications and examined the incidence of a breast carcinoma detected during the following five years in any of the women who were given a benign diagnosis at assessment. Method. A retrospective study consisted of 235 clients attending an Australian BreastScreen program in 2003, who were recalled for investigation of microcalcifications detected on screening mammography. Records for the following five years were available for 168 women in the benign outcome group including those who did not require biopsy at initial assessment. Results. Malignant disease was detected in 26.0% (n = 146) of the women who underwent biopsy. None of the women in the benign outcome group, with available five-year follow-up records, developed a subsequent breast cancer, arising from the calcifications initially recalled in 2003. Conclusions. This study highlights the effectiveness of an Australian screening program in diagnosing malignancy in women with screen detected microcalcification. This has been achieved by correctly determining 38% (n = 235) of the women as benign without the need for biopsy or early recall. A low rate of open surgical biopsies was performed with no cancer diagnoses missed at the time of initial assessment. PMID:24194985

  15. Microcalcifications Detected as an Abnormality on Screening Mammography: Outcomes and Followup over a Five-Year Period

    PubMed Central

    Bicknell, Anne M.; Hazan, Georges J.; Flegg, Karen M.

    2013-01-01

    Objectives. This study reviewed the outcome of women attending a breast screening program recalled for assessment of microcalcifications and examined the incidence of a breast carcinoma detected during the following five years in any of the women who were given a benign diagnosis at assessment. Method. A retrospective study consisted of 235 clients attending an Australian BreastScreen program in 2003, who were recalled for investigation of microcalcifications detected on screening mammography. Records for the following five years were available for 168 women in the benign outcome group including those who did not require biopsy at initial assessment. Results. Malignant disease was detected in 26.0% (n = 146) of the women who underwent biopsy. None of the women in the benign outcome group, with available five-year follow-up records, developed a subsequent breast cancer, arising from the calcifications initially recalled in 2003. Conclusions. This study highlights the effectiveness of an Australian screening program in diagnosing malignancy in women with screen detected microcalcification. This has been achieved by correctly determining 38% (n = 235) of the women as benign without the need for biopsy or early recall. A low rate of open surgical biopsies was performed with no cancer diagnoses missed at the time of initial assessment. PMID:24194985

  16. Plasma abnormal prothrombin (PIVKA-II): a new and reliable marker for the detection of hepatocellular carcinoma.

    PubMed

    Takikawa, Y; Suzuki, K; Yamazaki, K; Goto, T; Madarame, T; Miura, Y; Yoshida, T; Kashiwabara, T; Sato, S

    1992-01-01

    We evaluated the clinical usefulness of a protein induced by vitamin K absence, antagonist-prothrombin (PIVKA-II), in detecting hepatocellular carcinoma (HCC) specifically in patients with liver cirrhosis, and the possible correlation between levels of PIVKA-II and pathological features of HCC. Plasma levels of PIVKA-II and alpha-fetoprotein (AFP) were measured in 628 patients with various diseases, including 253 with liver cirrhosis and 116 with HCC. PIVKA-II was detected (greater than or equal to 0.1 arbitrary unit/mL) in 54.3% of HCC and the concentration showed a positive correlation with the tumour size. As a screening test for the detection of HCC, PIVKA-II produced values comparable with those of AFP with a sensitivity, specificity and validity of 52.8, 98.8 and 51.6% respectively. Sixteen of 45 patients (37%) with HCC who had low AFP (less than 100 ng/mL) levels were positive for PIVKA-II. No apparent relationship, however, could be found between the levels of PIVKA-II and the aetiology or pathological findings of HCC. These results suggest that PIVKA-II can be a reliable marker for detecting HCC in patients with liver cirrhosis.

  17. High-Performance Signal Detection for Adverse Drug Events using MapReduce Paradigm.

    PubMed

    Fan, Kai; Sun, Xingzhi; Tao, Ying; Xu, Linhao; Wang, Chen; Mao, Xianling; Peng, Bo; Pan, Yue

    2010-01-01

    Post-marketing pharmacovigilance is important for public health, as many Adverse Drug Events (ADEs) are unknown when those drugs were approved for marketing. However, due to the large number of reported drugs and drug combinations, detecting ADE signals by mining these reports is becoming a challenging task in terms of computational complexity. Recently, a parallel programming model, MapReduce has been introduced by Google to support large-scale data intensive applications. In this study, we proposed a MapReduce-based algorithm, for common ADE detection approach, Proportional Reporting Ratio (PRR), and tested it in mining spontaneous ADE reports from FDA. The purpose is to investigate the possibility of using MapReduce principle to speed up biomedical data mining tasks using this pharmacovigilance case as one specific example. The results demonstrated that MapReduce programming model could improve the performance of common signal detection algorithm for pharmacovigilance in a distributed computation environment at approximately liner speedup rates. PMID:21347109

  18. The WISE Detection of an Infrared Echo in Tidal Disruption Event ASASSN-14li

    NASA Astrophysics Data System (ADS)

    Jiang, Ning; Dou, Liming; Wang, Tinggui; Yang, Chenwei; Lyu, Jianwei; Zhou, Hongyan

    2016-09-01

    We report the detection of a significant infrared variability of the nearest tidal disruption event (TDE) ASASSN-14li using Wide-field Infrared Survey Explorer and newly released Near-Earth Object WISE Reactivation data. In comparison with the quiescent state, the infrared flux is brightened by 0.12 and 0.16 mag in the W1 (3.4 μm) and W2 (4.6 μm) bands at 36 days after the optical discovery (or ∼110 days after the peak disruption date). The flux excess is still detectable ∼170 days later. Assuming that the flare-like infrared emission is from the dust around the black hole, its blackbody temperature is estimated to be ∼2.1 × 103 K, slightly higher than the dust sublimation temperature, indicating that the dust is likely located close to the dust sublimation radius. The equilibrium between the heating and radiation of the dust claims a bolometric luminosity of ∼1043–1045 erg s‑1, comparable with the observed peak luminosity. This result has for the first time confirmed the detection of infrared emission from the dust echoes of TDEs.

  19. Automatic Detection of Swallowing Events by Acoustical Means for Applications of Monitoring of Ingestive Behavior

    PubMed Central

    Sazonov, Edward S.; Makeyev, Oleksandr; Schuckers, Stephanie; Lopez-Meyer, Paulo; Melanson, Edward L.; Neuman, Michael R.

    2010-01-01

    Our understanding of etiology of obesity and overweight is incomplete due to lack of objective and accurate methods for Monitoring of Ingestive Behavior (MIB) in the free living population. Our research has shown that frequency of swallowing may serve as a predictor for detecting food intake, differentiating liquids and solids, and estimating ingested mass. This paper proposes and compares two methods of acoustical swallowing detection from sounds contaminated by motion artifacts, speech and external noise. Methods based on mel-scale Fourier spectrum, wavelet packets, and support vector machines are studied considering the effects of epoch size, level of decomposition and lagging on classification accuracy. The methodology was tested on a large dataset (64.5 hours with a total of 9,966 swallows) collected from 20 human subjects with various degrees of adiposity. Average weighted epoch recognition accuracy for intra-visit individual models was 96.8% which resulted in 84.7% average weighted accuracy in detection of swallowing events. These results suggest high efficiency of the proposed methodology in separation of swallowing sounds from artifacts that originate from respiration, intrinsic speech, head movements, food ingestion, and ambient noise. The recognition accuracy was not related to body mass index, suggesting that the methodology is suitable for obese individuals. PMID:19789095

  20. Solar Power Ramp Events Detection Using an Optimized Swinging Door Algorithm

    SciTech Connect

    Cui, Mingjian; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Ke, Deping; Sun, Yuanzhang

    2015-08-05

    Solar power ramp events (SPREs) significantly influence the integration of solar power on non-clear days and threaten the reliable and economic operation of power systems. Accurately extracting solar power ramps becomes more important with increasing levels of solar power penetrations in power systems. In this paper, we develop an optimized swinging door algorithm (OpSDA) to enhance the state of the art in SPRE detection. First, the swinging door algorithm (SDA) is utilized to segregate measured solar power generation into consecutive segments in a piecewise linear fashion. Then we use a dynamic programming approach to combine adjacent segments into significant ramps when the decision thresholds are met. In addition, the expected SPREs occurring in clear-sky solar power conditions are removed. Measured solar power data from Tucson Electric Power is used to assess the performance of the proposed methodology. OpSDA is compared to two other ramp detection methods: the SDA and the L1-Ramp Detect with Sliding Window (L1-SW) method. The statistical results show the validity and effectiveness of the proposed method. OpSDA can significantly improve the performance of the SDA, and it can perform as well as or better than L1-SW with substantially less computation time.

  1. Solar Power Ramp Events Detection Using an Optimized Swinging Door Algorithm: Preprint

    SciTech Connect

    Cui, Mingjian; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Ke, Deping; Sun, Yuanzhang

    2015-08-07

    Solar power ramp events (SPREs) are those that significantly influence the integration of solar power on non-clear days and threaten the reliable and economic operation of power systems. Accurately extracting solar power ramps becomes more important with increasing levels of solar power penetrations in power systems. In this paper, we develop an optimized swinging door algorithm (OpSDA) to detection. First, the swinging door algorithm (SDA) is utilized to segregate measured solar power generation into consecutive segments in a piecewise linear fashion. Then we use a dynamic programming approach to combine adjacent segments into significant ramps when the decision thresholds are met. In addition, the expected SPREs occurring in clear-sky solar power conditions are removed. Measured solar power data from Tucson Electric Power is used to assess the performance of the proposed methodology. OpSDA is compared to two other ramp detection methods: the SDA and the L1-Ramp Detect with Sliding Window (L1-SW) method. The statistical results show the validity and effectiveness of the proposed method. OpSDA can significantly improve the performance of the SDA, and it can perform as well as or better than L1-SW with substantially less computation time.

  2. The WISE Detection of an Infrared Echo in Tidal Disruption Event ASASSN-14li

    NASA Astrophysics Data System (ADS)

    Jiang, Ning; Dou, Liming; Wang, Tinggui; Yang, Chenwei; Lyu, Jianwei; Zhou, Hongyan

    2016-09-01

    We report the detection of a significant infrared variability of the nearest tidal disruption event (TDE) ASASSN-14li using Wide-field Infrared Survey Explorer and newly released Near-Earth Object WISE Reactivation data. In comparison with the quiescent state, the infrared flux is brightened by 0.12 and 0.16 mag in the W1 (3.4 μm) and W2 (4.6 μm) bands at 36 days after the optical discovery (or ˜110 days after the peak disruption date). The flux excess is still detectable ˜170 days later. Assuming that the flare-like infrared emission is from the dust around the black hole, its blackbody temperature is estimated to be ˜2.1 × 103 K, slightly higher than the dust sublimation temperature, indicating that the dust is likely located close to the dust sublimation radius. The equilibrium between the heating and radiation of the dust claims a bolometric luminosity of ˜1043-1045 erg s-1, comparable with the observed peak luminosity. This result has for the first time confirmed the detection of infrared emission from the dust echoes of TDEs.

  3. Sonographic cutoff values for detection of abnormalities in small, medium and large joints: a comparative study between patients with rheumatoid arthritis and healthy volunteers.

    PubMed

    Machado, Flávia Soares; Furtado, Rita Nely Vilar; Takahashi, Rogerio Diniz; de Buosi, Ana Leticia Pirosi; Natour, Jamil

    2015-04-01

    To determine ultrasound measurements indicative of abnormalities in small, medium and large joints, we conducted a cross-sectional study comparing 60 patients with rheumatoid arthritis (RA) and 78 healthy volunteers. A MyLab 60 ultrasound machine (Esaote) and a linear multifrequency probe were used. Quantitative measurements of synovial recesses and semiquantitative measurements of synovial hyperplasia, power Doppler and bone erosion (scores = 0-3) were performed. The cutoff values for synovial recesses indicating RA (receiver operating characteristic curve, area under the curve >0.800) were found to be (radiocarpal) 3.78 mm and (ulnocarpal) 3.07 mm. Those measurements with the greatest chance of indicating RA (logistic regression analysis expressed as odds ratios [ORs]) were (p < 0.001) measurements of synovial hyperplasia (ulnocarpal, OR = 100, and radiocarpal, OR = 70); synovial power Doppler (radiocarpal, OR = 66); synovial bone erosion (radiocarpal, OR = 324); fifth metatarsophalangeal joint (OR = 100); and second metacarpophalangeal joint (OR = 92). We concluded that for both quantitative and semiquantitative ultrasound measurements, radiocarpal abnormalities increase the chance of detecting RA.

  4. Using tensor-based morphometry to detect structural brain abnormalities in rats with adolescent intermittent alcohol exposure

    NASA Astrophysics Data System (ADS)

    Paniagua, Beatriz; Ehlers, Cindy; Crews, Fulton; Budin, Francois; Larson, Garrett; Styner, Martin; Oguz, Ipek

    2011-03-01

    Understanding the effects of adolescent binge drinking that persist into adulthood is a crucial public health issue. Adolescent intermittent ethanol exposure (AIE) is an animal model that can be used to investigate these effects in rodents. In this work, we investigate the application of a particular image analysis technique, tensor-based morphometry, for detecting anatomical differences between AIE and control rats using Diffusion Tensor Imaging (DTI). Deformation field analysis is a popular method for detecting volumetric changes analyzing Jacobian determinants calculated on deformation fields. Recent studies showed that computing deformation field metrics on the full deformation tensor, often referred to as tensor-based morphometry (TBM), increases the sensitivity to anatomical differences. In this paper we conduct a comprehensive TBM study for precisely locating differences between control and AIE rats. Using a DTI RARE sequence designed for minimal geometric distortion, 12-directional images were acquired postmortem for control and AIE rats (n=9). After preprocessing, average images for the two groups were constructed using an unbiased atlas building approach. We non-rigidly register the two atlases using Large Deformation Diffeomorphic Metric Mapping, and analyze the resulting deformation field using TBM. In particular, we evaluate the tensor determinant, geodesic anisotropy, and deformation direction vector (DDV) on the deformation field to detect structural differences. This yields data on the local amount of growth, shrinkage and the directionality of deformation between the groups. We show that TBM can thus be used to measure group morphological differences between rat populations, demonstrating the potential of the proposed framework.

  5. Comparing voxel-based iterative sensitivity and voxel-based morphometry to detect abnormalities in T2-weighted MRI.

    PubMed

    Diaz-de-Grenu, Lara Z; Acosta-Cabronero, Julio; Williams, Guy B; Nestor, Peter J

    2014-10-15

    This study aimed to test the superiority proposed by Abbott et al. (2011) of their Voxel based iterative sensitivity (VBIS) method over Voxel Based Morphometry using T2-weighted images (T2-VBM), in detecting intensity changes in Alzheimer's disease (AD). A comparison was made first in simulated intensity lesions and then in AD patients. Intensity changes were evaluated in the whole-brain with VBIS and with a simple intensity-based approach and in specific tissue classes with the conventional VBM method of using tissue probability segments. Results showed that VBIS performed well in the simulated environment though it showed no superiority in detecting the lesion compared to the much simpler VBM approach. The VBIS method, however, failed to detect any meaningful signal intensity reduction in AD patient data. Moreover, its whole brain approach was contaminated by the excess cerebrospinal fluid signal (very bright on T2-weighted scans) in areas of maximal measurable atrophy (mesial temporal lobes); this gave rise to spurious signal intensity increases in these regions in AD. The same artefact was observed for both intensity-based methods but not with the conventional VBM approach of performing statistics on grey matter segments. In conclusion, no evidence was found to indicate that VBIS offers benefits over T2-VBM in AD, nor in simulation intensity lesions. The study highlights the necessity of empirically testing voxel-based analysis techniques rather than merely claiming superiority of one method over another on theoretical grounds.

  6. DADA: Data Assimilation for the Detection and Attribution of Weather and Climate-related Events

    NASA Astrophysics Data System (ADS)

    Hannart, Alexis; Bocquet, Marc; Carrassi, Alberto; Ghil, Michael; Naveau, Philippe; Pulido, Manuel; Ruiz, Juan; Tandeo, Pierre

    2015-04-01

    We describe a new approach allowing for near real time, systematic causal attribution of weather and climate-related events. The method is purposely designed to allow its operability at meteorological centers by synergizing causal attribution with data treatments that are routinely performed when numerically forecasting the weather, thereby taking advantage of their powerful computational and observational capacity. Namely, we show that causal attribution can be obtained as a by-product of the so-called data assimilation procedures that are run on a daily basis to update the meteorological model with new atmospheric observations. We explain the theoretical rationale of this approach and sketch the most prominent features of a "data assimilation-based detection and attribution" (DADA) procedure. The proposal is illustrated in the context of the 3-variables Lorenz model. Several practical and theoretical research questions that need to be addressed to make the proposal readily operational within weather forecasting centers are finally laid out.

  7. Event detection and localization for small mobile robots using reservoir computing.

    PubMed

    Antonelo, E A; Schrauwen, B; Stroobandt, D

    2008-08-01

    Reservoir Computing (RC) techniques use a fixed (usually randomly created) recurrent neural network, or more generally any dynamic system, which operates at the edge of stability, where only a linear static readout output layer is trained by standard linear regression methods. In this work, RC is used for detecting complex events in autonomous robot navigation. This can be extended to robot localization tasks which are solely based on a few low-range, high-noise sensory data. The robot thus builds an implicit map of the environment (after learning) that is used for efficient localization by simply processing the input stream of distance sensors. These techniques are demonstrated in both a simple simulation environment and in the physically realistic Webots simulation of the commercially available e-puck robot, using several complex and even dynamic environments.

  8. The Event Detection and the Apparent Velocity Estimation Based on Computer Vision

    NASA Astrophysics Data System (ADS)

    Shimojo, M.

    2012-08-01

    The high spatial and time resolution data obtained by the telescopes aboard Hinode revealed the new interesting dynamics in solar atmosphere. In order to detect such events and estimate the velocity of dynamics automatically, we examined the estimation methods of the optical flow based on the OpenCV that is the computer vision library. We applied the methods to the prominence eruption observed by NoRH, and the polar X-ray jet observed by XRT. As a result, it is clear that the methods work well for solar images if the images are optimized for the methods. It indicates that the optical flow estimation methods in the OpenCV library are very useful to analyze the solar phenomena.

  9. Detection and Attribution of Simulated Climatic Extreme Events and Impacts: High Sensitivity to Bias Correction

    NASA Astrophysics Data System (ADS)

    Sippel, S.; Otto, F. E. L.; Forkel, M.; Allen, M. R.; Guillod, B. P.; Heimann, M.; Reichstein, M.; Seneviratne, S. I.; Kirsten, T.; Mahecha, M. D.

    2015-12-01

    Understanding, quantifying and attributing the impacts of climatic extreme events and variability is crucial for societal adaptation in a changing climate. However, climate model simulations generated for this purpose typically exhibit pronounced biases in their output that hinders any straightforward assessment of impacts. To overcome this issue, various bias correction strategies are routinely used to alleviate climate model deficiencies most of which have been criticized for physical inconsistency and the non-preservation of the multivariate correlation structure. We assess how biases and their correction affect the quantification and attribution of simulated extremes and variability in i) climatological variables and ii) impacts on ecosystem functioning as simulated by a terrestrial biosphere model. Our study demonstrates that assessments of simulated climatic extreme events and impacts in the terrestrial biosphere are highly sensitive to bias correction schemes with major implications for the detection and attribution of these events. We introduce a novel ensemble-based resampling scheme based on a large regional climate model ensemble generated by the distributed weather@home setup[1], which fully preserves the physical consistency and multivariate correlation structure of the model output. We use extreme value statistics to show that this procedure considerably improves the representation of climatic extremes and variability. Subsequently, biosphere-atmosphere carbon fluxes are simulated using a terrestrial ecosystem model (LPJ-GSI) to further demonstrate the sensitivity of ecosystem impacts to the methodology of bias correcting climate model output. We find that uncertainties arising from bias correction schemes are comparable in magnitude to model structural and parameter uncertainties. The present study consists of a first attempt to alleviate climate model biases in a physically consistent way and demonstrates that this yields improved simulations of

  10. Fusion of waveform events and radionuclide detections with the help of atmospheric transport modelling

    NASA Astrophysics Data System (ADS)

    Krysta, Monika; Kushida, Noriyuki; Kotselko, Yuriy; Carter, Jerry

    2016-04-01

    Possibilities of associating information from four pillars constituting CTBT monitoring and verification regime, namely seismic, infrasound, hydracoustic and radionuclide networks, have been explored by the International Data Centre (IDC) of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) for a long time. Based on a concept of overlying waveform events with the geographical regions constituting possible sources of the detected radionuclides, interactive and non-interactive tools were built in the past. Based on the same concept, a design of a prototype of a Fused Event Bulletin was proposed recently. One of the key design elements of the proposed approach is the ability to access fusion results from either the radionuclide or from the waveform technologies products, which are available on different time scales and through various different automatic and interactive products. To accommodate various time scales a dynamic product evolving while the results of the different technologies are being processed and compiled is envisioned. The product would be available through the Secure Web Portal (SWP). In this presentation we describe implementation of the data fusion functionality in the test framework of the SWP. In addition, we address possible refinements to the already implemented concepts.

  11. Applying a New Event Detection Algorithm to an Ocean Bottom Seismometer Dataset Recorded Offshore Southern California

    NASA Astrophysics Data System (ADS)

    Bishop, J.; Kohler, M. D.; Bunn, J.; Chandy, K. M.

    2015-12-01

    A number of active southern California offshore faults are capable of M>6 earthquakes, and the only permanent Southern California Seismic Network stations that can contribute to ongoing, small-magnitude earthquake detection and location are those located on the coastline and islands. To obtain a more detailed picture of the seismicity of the region, an array of 34 ocean bottom seismometers (OBSs) was deployed to record continuous waveform data off the coast of Southern California for 12 months (2010-2011) as part of the ALBACORE (Asthenospheric and Lithospheric Broadband Architecture from the California Offshore Region Experiment) project. To obtain a local event catalog based on OBS data, we make use of a newly developed data processing platform based on Python. The data processing procedure comprises a multi-step analysis that starts with the identification of significant signals above the time-adjusted noise floor for each sensor. This is followed by a time-dependent statistical estimate of the likelihood of an earthquake based on the aggregated signals in the array. For periods with elevated event likelihood, an adaptive grid-fitting procedure is used that yields candidate earthquake hypocenters with confidence estimates that best match the observed sensor signals. The results are validated with synthetic travel times and manual picks. Using results from ALBACORE, we have created a more complete view of active faulting in the California Borderland.

  12. Using AHRQ patient safety indicators to detect postdischarge adverse events in the Veterans Health Administration.

    PubMed

    Mull, Hillary J; Borzecki, Ann M; Chen, Qi; Shin, Marlena H; Rosen, Amy K

    2014-01-01

    Patient safety indicators (PSIs) use inpatient administrative data to flag cases with potentially preventable adverse events (AEs) attributable to hospital care. This study explored how many AEs the PSIs identified in the 30 days post discharge. PSI software was run on Veterans Health Administration 2003-2007 administrative data for 10 recently validated PSIs. Among PSI-eligible index hospitalizations not flagged with an AE, this study evaluated how many AEs occurred within 1 to 14 and 15 to 30 days post discharge using inpatient and outpatient administrative data. Considering all PSI-eligible index hospitalizations, 11 141 postdischarge AEs were identified, compared with 40 578 inpatient-flagged AEs. More than 60% of postdischarge AEs were detected within 14 days of discharge. The majority of postdischarge AEs were decubitus ulcers and postoperative pulmonary embolisms or deep vein thromboses. Extending PSI algorithms to the postdischarge period may provide a more complete picture of hospital quality. Future work should use chart review to validate postdischarge PSI events. PMID:23939485

  13. Application of remote sensing in coastal change detection after the tsunami event in Indonesia

    NASA Astrophysics Data System (ADS)

    Lim, H. S.; MatJafri, M. Z.; Abdullah, K.; Saleh, N. Mohd.; Surbakti, M. S.

    2008-10-01

    Shoreline mapping and shoreline change detection are critical in many coastal zone applications. This study focuses on applying remote sensing technology to identify and assess coastal changes in the Banda Aceh, Indonesia. Major changes to land cover were found along the coastal line. Using remote sensing data to detect coastal line change requires high spatial resolution data. In this study, two high spatial data with 30 meter resolution of Landsat TM images captured before and after the Tsunami event were acquired for this purpose. The two satellite images was overlain and compared with pre-Tsunami imagery and with after Tsunami. The two Landsat TM images also were used to generate land cover classification maps for the 24 December 2004 and 27 March 2005, before and after the Tsunami event respectively. The standard supervised classifier was performed to the satellite images such as the Maximum Likelihood, Minimum Distance-to-mean and Parallelepiped. High overall accuracy (>80%) and Kappa coefficient (>0.80) was achieved by the Maximum Likelihood classifier in this study. Estimation of the damage areas between the two dated was estimated from the different between the two classified land cover maps. Visible damage could be seen in either before and after image pair. The visible damage land areas were determined and draw out using the polygon tool included in the PCI Geomatica image processing software. The final set of polygons containing the major changes in the coastal line. An overview of the coastal line changes using Landsat TM images is also presented in this study. This study provided useful information that helps local decision makers make better plan and land management choices.

  14. Automated Visual Event Detection, Tracking, and Data Management System for Cabled- Observatory Video

    NASA Astrophysics Data System (ADS)

    Edgington, D. R.; Cline, D. E.; Schlining, B.; Raymond, E.

    2008-12-01

    Ocean observatories and underwater video surveys have the potential to unlock important discoveries with new and existing camera systems. Yet the burden of video management and analysis often requires reducing the amount of video recorded through time-lapse video or similar methods. It's unknown how many digitized video data sets exist in the oceanographic community, but we suspect that many remain under analyzed due to lack of good tools or human resources to analyze the video. To help address this problem, the Automated Visual Event Detection (AVED) software and The Video Annotation and Reference System (VARS) have been under development at MBARI. For detecting interesting events in the video, the AVED software has been developed over the last 5 years. AVED is based on a neuromorphic-selective attention algorithm, modeled on the human vision system. Frames are decomposed into specific feature maps that are combined into a unique saliency map. This saliency map is then scanned to determine the most salient locations. The candidate salient locations are then segmented from the scene using algorithms suitable for the low, non-uniform light and marine snow typical of deep underwater video. For managing the AVED descriptions of the video, the VARS system provides an interface and database for describing, viewing, and cataloging the video. VARS was developed by the MBARI for annotating deep-sea video data and is currently being used to describe over 3000 dives by our remotely operated vehicles (ROV), making it well suited to this deepwater observatory application with only a few modifications. To meet the compute and data intensive job of video processing, a distributed heterogeneous network of computers is managed using the Condor workload management system. This system manages data storage, video transcoding, and AVED processing. Looking to the future, we see high-speed networks and Grid technology as an important element in addressing the problem of processing and

  15. Beat-by-Beat Quantification of Cardiac Cycle Events Detected From Three-Dimensional Precordial Acceleration Signals.

    PubMed

    Paukkunen, Mikko; Parkkila, Petteri; Hurnanen, Tero; Pänkäälä, Mikko; Koivisto, Tero; Nieminen, Tuomo; Kettunen, Raimo; Sepponen, Raimo

    2016-03-01

    The vibrations produced by the cardiovascular system that are coupled to the precordium can be noninvasively detected using accelerometers. This technique is called seismocardiography. Although clinical applications have been proposed for seismocardiography, the physiology underlying the signal is still not clear. The relationship of seismocardiograms of on the back-to-front axis and cardiac events is fairly well known. However, the 3-D seismocardiograms detectable with modern accelerometers have not been quantified in terms of cardiac cycle events. A major reason for this might be the degree of intersubject variability observed in 3-D seismocardiograms. We present a method to quantify 3-D seismocardiography in terms of cardiac cycle events. First, cardiac cycle events are identified from the seismocardiograms, and then, assigned a number based on the location in which the corresponding event was found. 396 cardiac cycle events from 9 healthy subjects and 120 cardiac cycle events from patients suffering from atrial flutter were analyzed. Despite the weak intersubject correlation of the waveforms (0.05, 0.27, and 0.15 for the x-, y-, and z-axes, respectively), the present method managed to find latent similarities in the seismocardiograms of healthy subjects. We observed that in healthy subjects the distribution of cardiac cycle event coordinates was centered on specific locations. These locations were different in patients with atrial flutter. The results suggest that spatial distribution of seismocardiographic cardiac cycle events might be used to discriminate healthy individuals and those with a failing heart.

  16. Using GPS to Rapidly Detect and Model Earthquakes and Transient Deformation Events

    NASA Astrophysics Data System (ADS)

    Crowell, Brendan W.

    The rapid modeling and detection of earthquakes and transient deformation is a problem of extreme societal importance for earthquake early warning and rapid hazard response. To date, GPS data is not used in earthquake early warning or rapid source modeling even in Japan or California where the most extensive geophysical networks exist. This dissertation focuses on creating algorithms for automated modeling of earthquakes and transient slip events using GPS data in the western United States and Japan. First, I focus on the creation and use of high-rate GPS and combined seismogeodetic data for applications in earthquake early warning and rapid slip inversions. Leveraging data from earthquakes in Japan and southern California, I demonstrate that an accurate magnitude estimate can be made within seconds using P wave displacement scaling, and that a heterogeneous static slip model can be generated within 2-3 minutes. The preliminary source characterization is sufficiently robust to independently confirm the extent of fault slip used for rapid assessment of strong ground motions and improved tsunami warning in subduction zone environments. Secondly, I investigate the automated detection of transient slow slip events in Cascadia using daily positional estimates from GPS. Proper geodetic characterization of transient deformation is necessary for studies of regional interseismic, coseismic and postseismic tectonics, and miscalculations can affect our understanding of the regional stress field. I utilize the relative strength index (RSI) from financial forecasting to create a complete record of slow slip from continuous GPS stations in the Cascadia subduction zone between 1996 and 2012. I create a complete history of slow slip across the Cascadia subduction zone, fully characterizing the timing, progression, and magnitude of events. Finally, using a combination of continuous and campaign GPS measurements, I characterize the amount of extension, shear and subsidence in the

  17. Detection of Left Ventricular Regional Dysfunction and Myocardial Abnormalities Using Complementary Cardiac Magnetic Resonance Imaging in Patients with Systemic Sclerosis without Cardiac Symptoms: A Pilot Study.

    PubMed

    Kobayashi, Yasuyuki; Kobayashi, Hitomi; T Giles, Jon; Yokoe, Isamu; Hirano, Masaharu; Nakajima, Yasuo; Takei, Masami

    2016-01-01

    Objective We sought to detect the presence of left ventricular regional dysfunction and myocardial abnormalities in systemic sclerosis (SSc) patients without cardiac symptoms using a complementary cardiac magnetic resonance (CMR) imaging approach. Methods Consecutive patients with SSc without cardiac symptoms and healthy controls underwent CMR on a 1.5 T scanner. The peak systolic regional function in the circumferential and radial strain (Ecc, % and Err, %) were calculated using a feature tracking analysis on the mid-left ventricular slices obtained with cine MRI. In addition, we investigated the myocardial characteristics by contrast MRI. Pharmacological stress and rest perfusion scans were performed to assess perfusion defect (PD) due to micro- or macrovascular impairment, and late gadolinium enhancement (LGE) images were obtained for the assessment of myocarditis and/or fibrosis. Results We compared 15 SSc patients with 10 healthy controls. No statistically significant differences were observed in the baseline characteristics between the patients and healthy controls. The mean peak Err and Ecc of all segments was significantly lower in the patients than the controls (p=0.011 and p=0.003, respectively). Four patients with LGE (28.6%) and seven patients with PD (50.0%) were observed. PD was significantly associated with digital ulcers (p=0.005). Utilizing a linear regression model, the presence of myocardial LGE was significantly associated with the peak Ecc (p=0.024). After adjusting for age, the association between myocardial LGE and the peak Ecc was strengthened. Conclusion A subclinical myocardial involvement, as detected by CMR, was prevalent in the SSc patients without cardiac symptoms. Regional dysfunction might predict the myocardial abnormalities observed in SSc patients without cardiac symptoms.

  18. PREFACE: Fourth Symposium on Large TPCs for Low Energy Rare Event Detection

    NASA Astrophysics Data System (ADS)

    Irastorza, Igor G.; Colas, Paul; Giomataris, Ioannis

    2009-07-01

    The Fourth International Symposium on large TPCs for low-energy rare-event detection was held at the Hermite auditorium of the Insitute Henri Poincaréte, 11 rue Pierre et Marie Curie in Paris on 18-19 December 2008. As in previous instances of the meeting, held always in Paris in 2006, 2004 and 2002, it gathered a significant community of physicists involved in rare event searches and/or development of time projection chambers (TPCs). The purpose of the meeting was to present and discuss the status of current experiments or projects involving the use of large TPCs for the search of rare events, like low-energy neutrinos, double beta decay, dark matter or axion experiments, as well as to discuss new results and ideas in the framework of the last developments of Micro Pattern Gaseous Detectors (MPGD), and how these are being - or could be - applied to the mentioned searches. The rapid evolvement of these devices and the relevance of their latest results need to be efficiently transferred to the rare event community. The creation of this series of meetings followed the motivation of bringing together both know-hows and it is proving to be a fruitful area of collaboration. Once more, the format of the meeting proved to be a success. A short (2 days) and relatively informal program with some recent highlighted results, rather than exhaustive reviews, attracted the interest of the audience. The symposium, fourth of the series, is becoming consolidated as a regular meeting place for the synergic interplay between the fields of rare events and TPC development. Apart from the usual topics central to the conference subject, like the status of some low-energy neutrino physics and double beta decay experiments, dark matter experiments (and in general physics in underground laboratories), axion searches, or development results, every year the conference programme is enriched with original slightly off-topic contributions that trigger the curiosity and stimulate further thought

  19. SNP Array Karyotyping Allows for the Detection of Uniparental Disomy and Cryptic Chromosomal Abnormalities in MDS/MPD-U and MPD

    PubMed Central

    Gondek, Lukasz P.; Dunbar, Andrew J.; Szpurka, Hadrian; McDevitt, Michael A.; Maciejewski, Jaroslaw P.

    2007-01-01

    We applied single nucleotide polymorphism arrays (SNP-A) to study karyotypic abnormalities in patients with atypical myeloproliferative syndromes (MPD), including myeloproliferative/myelodysplastic syndrome overlap both positive and negative for the JAK2 V617F mutation and secondary acute myeloid leukemia (AML). In typical MPD cases (N = 8), which served as a control group, those with a homozygous V617F mutation showed clear uniparental disomy (UPD) of 9p using SNP-A. Consistent with possible genomic instability, in 19/30 MDS/MPD-U patients, we found additional lesions not identified by metaphase cytogenetics. In addition to UPD9p, we also have detected UPD affecting other chromosomes, including 1 (2/30), 11 (4/30), 12 (1/30) and 22 (1/30). Transformation to AML was observed in 8/30 patients. In 5 V617F+ patients who progressed to AML, we show that SNP-A can allow for the detection of two modes of transformation: leukemic blasts evolving from either a wild-type jak2 precursor carrying other acquired chromosomal defects, or from a V617F+ mutant progenitor characterized by UPD9p. SNP-A-based detection of cryptic lesions in MDS/MPD-U may help explain the clinical heterogeneity of this disorder. PMID:18030353

  20. Fully Autonomous Multiplet Event Detection: Application to Local-Distance Monitoring of Blood Falls Seismicity

    SciTech Connect

    Carmichael, Joshua Daniel; Carr, Christina; Pettit, Erin C.

    2015-06-18

    We apply a fully autonomous icequake detection methodology to a single day of high-sample rate (200 Hz) seismic network data recorded from the terminus of Taylor Glacier, ANT that temporally coincided with a brine release episode near Blood Falls (May 13, 2014). We demonstrate a statistically validated procedure to assemble waveforms triggered by icequakes into populations of clusters linked by intra-event waveform similarity. Our processing methodology implements a noise-adaptive power detector coupled with a complete-linkage clustering algorithm and noise-adaptive correlation detector. This detector-chain reveals a population of 20 multiplet sequences that includes ~150 icequakes and produces zero false alarms on the concurrent, diurnally variable noise. Our results are very promising for identifying changes in background seismicity associated with the presence or absence of brine release episodes. We thereby suggest that our methodology could be applied to longer time periods to establish a brine-release monitoring program for Blood Falls that is based on icequake detections.

  1. Detecting concealed information using feedback related event-related brain potentials.

    PubMed

    Sai, Liyang; Lin, Xiaohong; Hu, Xiaoqing; Fu, Genyue

    2014-10-01

    Employing an event-related potential (ERP)-based concealed information test (CIT), the present study investigated (1) the neurocognitive processes when people received feedbacks regarding their deceptive/truthful responses and (2) whether such feedback-related ERP activities can be used to detect concealed information above and beyond the recognition-related P300. During the CIT, participants were presented with rare, meaningful probes (their own names) embedded within a series of frequent yet meaningless irrelevants (others' names). Participants were instructed to deny their recognition of the probes. Critically, following participants' responses, they were provided with feedbacks regarding whether they succeeded or failed in the CIT. Replicating previous ERP-based CITs, we found a larger P300 elicited by probe compared to irrelevant. Regarding feedback-related ERPs, a temporospatial Principle Component Analyses found two ERP components that were not only sensitive to feedback manipulations but also can discriminate probe from irrelevant: an earlier, central-distributed positivity that was elicited by "success" feedbacks peaked around 219ms; and a later, right central-distributed positivity that was also elicited by "success" feedbacks, peaked around 400ms. Importantly, the feedback ERPs were not correlated with P300 that was elicited by probe/irrelevant, suggesting that these two ERPs reflect independent processes underlying memory concealment. These findings illustrate the feasibility and promise of using feedback-related ERPs to detect concealed memory and thus deception. PMID:25058495

  2. Improving single-trial detection of event-related potentials through artificial deformed signals.

    PubMed

    Cecotti, H; Rivet, B

    2014-01-01

    To propose a reliable and robust Brain-Computer Interface (BCI), efficient machine learning and signal processing methods have to be used. However, it is often necessary to have a sufficient number of labeled brain responses to create a model. A large database that would represent all of the possible variabilities of the signal is not always possible to obtain, because calibration sessions have to be short. In the case of BCIs based on the detection of event-related potentials (ERPs), we propose to tackle this problem by including additional deformed patterns in the training database to increase the number of labeled brain responses. The creation of the additional deformed patterns is based on two approaches: (i) smooth deformation fields, and (ii) right and left shifted signals. The evaluation is performed with data from 10 healthy subjects participating in a P300 speller experiment. The results show that small shifts of the signal allow a better estimation of both spatial filters, and a linear classifier. The best performance, AUC=0.828 ± 0.061, is obtained by combining the smooth deformation fields and the shifts, after spatial filtering, compared to AUC=0.543 ± 0.025, without additional deformed patterns. The results support the conclusion that adding signals with small deformations can significantly improve the performance of single-trial detection when the amount of training data is limited.

  3. Abnormal segregation of alleles in CEPH pedigree DNAs arising from allele loss in lymphoblastoid DNA

    SciTech Connect

    Royle, N.J.; Armour, J.A.L.; Crosier, M.; Jeffreys, A.J. )

    1993-01-01

    Somatic events that result in the reduction to hemior homozygosity at all loci affected by the event have been identified in lymphoblastoid DNA from mothers of two CEPH families. Using suitably informative probes, the allele deficiencies were detected by the abnormal transmission of alleles from grandparents to grandchildren, with the apparent absence of the alleles from the parent. Undetected somatic deficiencies in family DNAs could result in misscoring of recombination events and consequently introduce errors into linkage analysis. 15 refs., 2 figs.

  4. Localized Detection of Frozen Precipitation Events and the Rain/Snow Transition

    NASA Astrophysics Data System (ADS)

    Strachan, S.

    2014-12-01

    Frozen precipitation in the mid-latitudes and semi-arid environments frequently serves a crucial role in the annual water budget. Often occurring along elevational gradients, the rain/snow transition (or, "snow line") in mountain systems determines the amount of water which enters the system slowly during melt phases as opposed to rain which immediately infiltrates or runs off to lower elevations. This in turn influences the location and composition of ecological communities such as conifer forests, as well as timing and nature of the entire mountain block annual hydrologic cycle. Characterization of the rain/snow transition is becoming a priority in mountainous semi-arid regions, as increasing human populations and repeated drought episodes combine to create water shortages. Atmospheric conditions (temperature and relative humidity) which signal the rain/snow transition have been described, but variability within the conditions window can create error in estimating true areal cover of frozen versus liquid precipitation. In populated, flood-prone regions, radar installations specifically tuned to the detection of the "bright band" transition elevation can be deployed; however these cannot be permanently installed at remote, solar-power-dependent climate stations or with fine geographical scale. Characterization of current trends in rain/snow transition can be made using automated weather stations placed along the elevational gradient fielding sensors for high-frequency (e.g. 1-10 minute) measurement of air temperature, relative humidity, liquid precipitation, and precipitation mass. Visual validation of precipitation modes detected through automated means is performed using time-series records from digital cameras placed at each station. Refinements of geographically-explicit relationships of atmospheric conditions to precipitation mode can be made over time, as well as detection of seasonally-anomalous but eco-hydrologically-significant frozen precipitation events

  5. Monkeying around with the gorillas in our midst: familiarity with an inattentional-blindness task does not improve the detection of unexpected events.

    PubMed

    Simons, Daniel J

    2010-01-01

    When people know to look for an unexpected event (eg, a gorilla in a basketball game), they tend to notice that event. But does knowledge that an unexpected event might occur improve the detection of other unexpected events in a similar scene? Subjects watched a new video in which, in addition to the gorilla, two other unexpected events occurred: a curtain changed color, and one player left the scene. Subjects who knew about videos like this one consistently spotted the gorilla in the new video, but they were slightly less likely to notice the other events. Foreknowledge that unexpected events might occur does not enhance the ability to detect other such events.

  6. Detection of whole-brain abnormalities in temporal lobe epilepsy using tensor-based morphometry with DARTEL

    NASA Astrophysics Data System (ADS)

    Li, Wenjing; He, Huiguang; Lu, Jingjing; Lv, Bin; Li, Meng; Jin, Zhengyu

    2009-10-01

    Tensor-based morphometry (TBM) is an automated technique for detecting the anatomical differences between populations by examining the gradients of the deformation fields used to nonlinearly warp MR images. The purpose of this study was to investigate the whole-brain volume changes between the patients with unilateral temporal lobe epilepsy (TLE) and the controls using TBM with DARTEL, which could achieve more accurate inter-subject registration of brain images. T1-weighted images were acquired from 21 left-TLE patients, 21 right-TLE patients and 21 healthy controls, which were matched in age and gender. The determinants of the gradient of deformation fields at voxel level were obtained to quantify the expansion or contraction for individual images relative to the template, and then logarithmical transformation was applied on it. A whole brain analysis was performed using general lineal model (GLM), and the multiple comparison was corrected by false discovery rate (FDR) with p<0.05. For left-TLE patients, significant volume reductions were found in hippocampus, cingulate gyrus, precentral gyrus, right temporal lobe and cerebellum. These results potentially support the utility of TBM with DARTEL to study the structural changes between groups.

  7. FOREWORD: 3rd Symposium on Large TPCs for Low Energy Event Detection

    NASA Astrophysics Data System (ADS)

    Irastorza, Igor G.; Colas, Paul; Gorodetzky, Phillippe

    2007-05-01

    The Third International Symposium on large TPCs for low-energy rare-event detection was held at Carré des sciences, Poincaré auditorium, 25 rue de la Montagne Ste Geneviève in Paris on 11 12 December 2006. This prestigious location belonging to the Ministry of Research is hosted in the former Ecole Polytechnique. The meeting, held in Paris every two years, gathers a significant community of physicists involved in rare event detection. Its purpose is an extensive discussion of present and future projects using large TPCs for low energy, low background detection of rare events (low-energy neutrinos, dark matter, solar axions). The use of a new generation of Micro-Pattern Gaseous Detectors (MPGD) appears to be a promising way to reach this goal. The program this year was enriched by a new session devoted to the detection challenge of polarized gamma rays, relevant novel experimental techniques and the impact on particle physics, astrophysics and astronomy. A very particular feature of this conference is the large variety of talks ranging from purely theoretical to purely experimental subjects including novel technological aspects. This allows discussion and exchange of useful information and new ideas that are emerging to address particle physics experimental challenges. The scientific highlights at the Symposium came on many fronts: Status of low-energy neutrino physics and double-beta decay New ideas on double-beta decay experiments Gamma ray polarization measurement combining high-precision TPCs with MPGD read-out Dark Matter challenges in both axion and WIMP search with new emerging ideas for detection improvements Progress in gaseous and liquid TPCs for rare event detection Georges Charpak opened the meeting with a talk on gaseous detectors for applications in the bio-medical field. He also underlined the importance of new MPGD detectors for both physics and applications. There were about 100 registered participants at the symposium. The successful

  8. Detecting Visual Function Abnormality with a Contrast-Dependent Visual Test in Patients with Type 2 Diabetes

    PubMed Central

    Jang, Yuh; Hu, Fu-Chang; Wu, Wei-Chi

    2016-01-01

    In addition to diabetic retinopathy, diabetes also causes early retinal neurodegeneration and other eye problems, which cause various types of visual deficits. This study used a computer-based visual test (Macular Multi-Function Assessment (MMFA)) to assess contrast-dependent macular visual function in patients with type 2 diabetes to collect more visual information than possible with only the visual acuity test. Because the MMFA is a newly developed test, this study first compared the agreement and discriminative ability of the MMFA and the Early Treatment Diabetic Retinopathy Study (ETDRS) contrast acuity charts. Then symbol discrimination performances of diabetic patients and controls were evaluated at 4 contrast levels using the MMFA. Seventy-seven patients and 45 controls participated. The agreement between MMFA and ETDRS scores was examined by fitting three-level linear mixed-effect models to estimate the intraclass correlation coefficients (ICCs). The estimated areas under the receiver operating characteristic (ROC) curve were used to compare the discriminative ability of diseased versus non-diseased participants between the two tests. The MMFA scores of patients and controls were compared with multiple linear regression analysis after adjusting the effects of age, sex, hypertension and cataract. Results showed that the scores of the MMFA and ETDRS tests displayed high levels of agreement and acceptable and similar discriminative ability. The MMFA performance was correlated with the severity of diabetic retinopathy. Most of the MMFA scores differed significantly between the diabetic patients and controls. In the low contrast condition, the MMFA scores were significantly lower for 006Eon-DR patients than for controls. The potential utility of the MMFA as an easy screening tool for contrast-dependent visual function and for detecting early functional visual change in patients with type 2 diabetes is discussed. PMID:27611680

  9. Detecting Visual Function Abnormality with a Contrast-Dependent Visual Test in Patients with Type 2 Diabetes.

    PubMed

    Tsai, Li-Ting; Liao, Kuo-Meng; Jang, Yuh; Hu, Fu-Chang; Wu, Wei-Chi

    2016-01-01

    In addition to diabetic retinopathy, diabetes also causes early retinal neurodegeneration and other eye problems, which cause various types of visual deficits. This study used a computer-based visual test (Macular Multi-Function Assessment (MMFA)) to assess contrast-dependent macular visual function in patients with type 2 diabetes to collect more visual information than possible with only the visual acuity test. Because the MMFA is a newly developed test, this study first compared the agreement and discriminative ability of the MMFA and the Early Treatment Diabetic Retinopathy Study (ETDRS) contrast acuity charts. Then symbol discrimination performances of diabetic patients and controls were evaluated at 4 contrast levels using the MMFA. Seventy-seven patients and 45 controls participated. The agreement between MMFA and ETDRS scores was examined by fitting three-level linear mixed-effect models to estimate the intraclass correlation coefficients (ICCs). The estimated areas under the receiver operating characteristic (ROC) curve were used to compare the discriminative ability of diseased versus non-diseased participants between the two tests. The MMFA scores of patients and controls were compared with multiple linear regression analysis after adjusting the effects of age, sex, hypertension and cataract. Results showed that the scores of the MMFA and ETDRS tests displayed high levels of agreement and acceptable and similar discriminative ability. The MMFA performance was correlated with the severity of diabetic retinopathy. Most of the MMFA scores differed significantly between the diabetic patients and controls. In the low contrast condition, the MMFA scores were significantly lower for 006Eon-DR patients than for controls. The potential utility of the MMFA as an easy screening tool for contrast-dependent visual function and for detecting early functional visual change in patients with type 2 diabetes is discussed. PMID:27611680

  10. Sudden Event Recognition: A Survey

    PubMed Central

    Suriani, Nor Surayahani; Hussain, Aini; Zulkifley, Mohd Asyraf

    2013-01-01

    Event recognition is one of the most active research areas in video surveillance fields. Advancement in event recognition systems mainly aims to provide convenience, safety and an efficient lifestyle for humanity. A precise, accurate and robust approach is necessary to enable event recognition systems to respond to sudden changes in various uncontrolled environments, such as the case of an emergency, physical threat and a fire or bomb alert. The performance of sudden event recognition systems depends heavily on the accuracy of low level processing, like detection, recognition, tracking and machine learning algorithms. This survey aims to detect and characterize a sudden event, which is a subset of an abnormal event in several video surveillance applications. This paper discusses the following in detail: (1) the importance of a sudden event over a general anomalous event; (2) frameworks used in sudden event recognition; (3) the requirements and comparative studies of a sudden event recognition system and (4) various decision-making approaches for sudden event recognition. The advantages and drawbacks of using 3D images from multiple cameras for real-time application are also discussed. The paper concludes with suggestions for future research directions in sudden event recognition. PMID:23921828

  11. Impaired target detection in schizophrenia and the ventral attentional network: Findings from a joint event-related potential-functional MRI analysis.

    PubMed

    Wynn, Jonathan K; Jimenez, Amy M; Roach, Brian J; Korb, Alexander; Lee, Junghee; Horan, William P; Ford, Judith M; Green, Michael F

    2015-01-01

    Schizophrenia patients have abnormal neural responses to salient, infrequent events. We integrated event-related potentials (ERP) and fMRI to examine the contributions of the ventral (salience) and dorsal (sustained) attention networks to this dysfunctional neural activation. Twenty-one schizophrenia patients and 22 healthy controls were assessed in separate sessions with ERP and fMRI during a visual oddball task. Visual P100, N100, and P300 ERP waveforms and fMRI activation were assessed. A joint independent components analysis (jICA) on the ERP and fMRI data were conducted. Patients exhibited reduced P300, but not P100 or N100, amplitudes to targets and reduced fMRI neural activation in both dorsal and ventral attentional networks compared with controls. However, the jICA revealed that the P300 was linked specifically to activation in the ventral (salience) network, including anterior cingulate, anterior insula, and temporal parietal junction, with patients exhibiting significantly lower activation. The P100 and N100 were linked to activation in the dorsal (sustained) network, with no group differences in level of activation. This joint analysis approach revealed the nature of target detection deficits that were not discernable by either imaging methodology alone, highlighting the utility of a multimodal fMRI and ERP approach to understand attentional network deficits in schizophrenia. PMID:26448909

  12. Impaired target detection in schizophrenia and the ventral attentional network: Findings from a joint event-related potential–functional MRI analysis

    PubMed Central

    Wynn, Jonathan K.; Jimenez, Amy M.; Roach, Brian J.; Korb, Alexander; Lee, Junghee; Horan, William P.; Ford, Judith M.; Green, Michael F.

    2015-01-01

    Schizophrenia patients have abnormal neural responses to salient, infrequent events. We integrated event-related potentials (ERP) and fMRI to examine the contributions of the ventral (salience) and dorsal (sustained) attention networks to this dysfunctional neural activation. Twenty-one schizophrenia patients and 22 healthy controls were assessed in separate sessions with ERP and fMRI during a visual oddball task. Visual P100, N100, and P300 ERP waveforms and fMRI activation were assessed. A joint independent components analysis (jICA) on the ERP and fMRI data were conducted. Patients exhibited reduced P300, but not P100 or N100, amplitudes to targets and reduced fMRI neural activation in both dorsal and ventral attentional networks compared with controls. However, the jICA revealed that the P300 was linked specifically to activation in the ventral (salience) network, including anterior cingulate, anterior insula, and temporal parietal junction, with patients exhibiting significantly lower activation. The P100 and N100 were linked to activation in the dorsal (sustained) network, with no group differences in level of activation. This joint analysis approach revealed the nature of target detection deficits that were not discernable by either imaging methodology alone, highlighting the utility of a multimodal fMRI and ERP approach to understand attentional network deficits in schizophrenia. PMID:26448909

  13. Detection of Rapid Events at Mantle Depth by Future Gravity Missions

    NASA Astrophysics Data System (ADS)

    Ivins, Erik; Watkins, Michael

    2015-04-01

    The robust detection of gravity changes associated with relatively shallow subduction zone earthquakes (0-50 km depth co-seismic rupture) has been one of the success stories of the GRACE (e.g., Han et al. 2013, JGR-B, doi:10.1002/jgrb.50116) and GOCE (e.g., Fuchs et al., 2013, JGR-B, doi: 10.1002/jgrb.50381) missions. This surprise is a testament to the sensitivity of the measurement system, for the satellites must map the gravity potential field changes while flying at orbital altitudes exceeding 400 km (in the case of GRACE). It is clear that these observations contribute to advancing our understanding of large subduction zone earthquakes, if for no other reason than they allow comprehensive observation over the ocean covered solid Earth. The observations aid studies of both the mass transport associated with coseismic and post-seismic. Measurement capability for missions proposed to be flown after GRACE-2 are anticipated to be an order of magnitude, or greater, in accuracy and resolution (e.g., Wiese et al., 2012, J. Geodesy, doi: 10.1007/s00190-011-0493-8; Elsaka et al. 2014, J. Geodesy, doi: 10.1007/s00190-013-0665-9). Deep subduction zone earthquakes have not been detected, nor have any other non-seismic solid Earth deformations - with the exception of the glacial isostatic adjustment vertical response to the last glacial age. We examine the possibility that earthquakes occurring at, or near, the major transition zone in the mantle should be detected in the region where mantle phases become unstable and undergoes transition to a stable perovskite phase below 660 km depth. The Mw 8.2 1994 Bolivian Earthquake and the May 24, 2013 Mw 8.3 earthquake beneath the Sea of Okhotsk, Russia, are prototypes of events that can be studied with future gravity missions. Observation of gravity changes associated with deep subduction zone earthquakes could provide new clues on the enigmatic questions currently in debate over faulting mechanism (e.g., Zhan et al., 2014, Science

  14. Detection of air pollution events over Évora-Portugal during 2009

    NASA Astrophysics Data System (ADS)

    Filipa Domingues, Ana; Bortoli, Daniele; Silva, Ana Maria; Kulkarni, Pavan; Antón, Manuel

    2010-05-01

    All over the world pollutant industries, traffic and other natural and anthropogenic sources are responsible for air pollution affecting health and also the climate. At the moment the monitoring of air quality in urban and country regions become an urgent concern in the atmospheric studies due to the impact of global air pollution on climate and on the environment. One of the evidences of the global character of air pollution is that it not only affects industrialized countries but also reaches less developed countries with pollution gases and particles generated for elsewhere. The development and the employment of instruments and techniques for measure the variation of atmospheric trace gases and perform their monitoring are crucial for the improvement of the air quality and the control of pollutants emissions. One of the instruments able to perform the air quality monitoring is the Spectrometer for Atmospheric TRacers Measurements (SPATRAM) and it is installed at the CGÉs Observatory in Évora (38.5° N, 7.9° W, 300 m asl). This UV-VIS Spectrometer is used to carry out measurements of the zenith scattered radiation (290- 900 nm) to retrieve the vertical content of some atmospheric trace gases such as O3 and NO2 in stratosphere, using Differential Optical Absorption Spectroscopy (DOAS) methodology. Although SPATRAM, in its actual geometric and operational configuration - zenith sky looking and passive mode measurements, is not able to detect small variations of tracers in the troposphere it is possible to identify enhancements in the pollution loads due to air masses movements from polluted sites. In spite of the fact that Evora is a quite unpolluted city the deep analysis of the DOAS output, namely the quantity of gas (in this case NO2) present along the optical path of measurements (SCD - Slant Column Density) allows for the detection of unpredicted variations in the diurnal NO2 cycle. The SPATRAḾs data allows the identification of polluting events which

  15. Wavelet based automated postural event detection and activity classification with single imu - biomed 2013.

    PubMed

    Lockhart, Thurmon E; Soangra, Rahul; Zhang, Jian; Wu, Xuefan

    2013-01-01

    Mobility characteristics associated with activity of daily living such as sitting down, lying down, rising up, and walking are considered to be important in maintaining functional independence and healthy life style especially for the growing elderly population. Characteristics of postural transitions such as sit-to-stand are widely used by clinicians as a physical indicator of health, and walking is used as an important mobility assessment tool. Many tools have been developed to assist in the assessment of functional levels and to detect a person’s activities during daily life. These include questionnaires, observation, diaries, kinetic and kinematic systems, and validated functional tests. These measures are costly and time consuming, rely on subjective patient recall and may not accurately reflect functional ability in the patient’s home. In order to provide a low-cost, objective assessment of functional ability, inertial measurement unit (IMU) using MEMS technology has been employed to ascertain ADLs. These measures facilitate long-term monitoring of activity of daily living using wearable sensors. IMU system are desirable in monitoring human postures since they respond to both frequency and the intensity of movements and measure both dc (gravitational acceleration vector) and ac (acceleration due to body movement) components at a low cost. This has enabled the development of a small, lightweight, portable system that can be worn by a free-living subject without motion impediment – TEMPO (Technology Enabled Medical Precision Observation). Using this IMU system, we acquired indirect measures of biomechanical variables that can be used as an assessment of individual mobility characteristics with accuracy and recognition rates that are comparable to the modern motion capture systems. In this study, five subjects performed various ADLs and mobility measures such as posture transitions and gait characteristics were obtained. We developed postural event detection

  16. An automated cross-correlation based event detection technique and its application to surface passive data set

    USGS Publications Warehouse

    Forghani-Arani, Farnoush; Behura, Jyoti; Haines, Seth S.; Batzle, Mike

    2013-01-01

    In studies on heavy oil, shale reservoirs, tight gas and enhanced geothermal systems, the use of surface passive seismic data to monitor induced microseismicity due to the fluid flow in the subsurface is becoming more common. However, in most studies passive seismic records contain days and months of data and manually analysing the data can be expensive and inaccurate. Moreover, in the presence of noise, detecting the arrival of weak microseismic events becomes challenging. Hence, the use of an automated, accurate and computationally fast technique for event detection in passive seismic data is essential. The conventional automatic event identification algorithm computes a running-window energy ratio of the short-term average to the long-term average of the passive seismic data for each trace. We show that for the common case of a low signal-to-noise ratio in surface passive records, the conventional method is not sufficiently effective at event identification. Here, we extend the conventional algorithm by introducing a technique that is based on the cross-correlation of the energy ratios computed by the conventional method. With our technique we can measure the similarities amongst the computed energy ratios at different traces. Our approach is successful at improving the detectability of events with a low signal-to-noise ratio that are not detectable with the conventional algorithm. Also, our algorithm has the advantage to identify if an event is common to all stations (a regional event) or to a limited number of stations (a local event). We provide examples of applying our technique to synthetic data and a field surface passive data set recorded at a geothermal site.

  17. Novel Logistic Regression Model of Chest CT Attenuation Coefficient Distributions for the Automated Detection of Abnormal (Emphysema or ILD) versus Normal Lung

    PubMed Central

    Chan, Kung-Sik; Jiao, Feiran; Mikulski, Marek A.; Gerke, Alicia; Guo, Junfeng; Newell, John D; Hoffman, Eric A.; Thompson, Brad; Lee, Chang Hyun; Fuortes, Laurence J.

    2015-01-01

    Rationale and Objectives We evaluated the role of automated quantitative computed tomography (CT) scan interpretation algorithm in detecting Interstitial Lung Disease (ILD) and/or emphysema in a sample of elderly subjects with mild lung disease.ypothesized that the quantification and distributions of CT attenuation values on lung CT, over a subset of Hounsfield Units (HU) range [−1000 HU, 0 HU], can differentiate early or mild disease from normal lung. Materials and Methods We compared results of quantitative spiral rapid end-exhalation (functional residual capacity; FRC) and end-inhalation (total lung capacity; TLC) CT scan analyses in 52 subjects with radiographic evidence of mild fibrotic lung disease to 17 normal subjects. Several CT value distributions were explored, including (i) that from the peripheral lung taken at TLC (with peels at 15 or 65mm), (ii) the ratio of (i) to that from the core of lung, and (iii) the ratio of (ii) to its FRC counterpart. We developed a fused-lasso logistic regression model that can automatically identify sub-intervals of [−1000 HU, 0 HU] over which a CT value distribution provides optimal discrimination between abnormal and normal scans. Results The fused-lasso logistic regression model based on (ii) with 15 mm peel identified the relative frequency of CT values over [−1000, −900] and that over [−450,−200] HU as a means of discriminating abnormal versus normal, resulting in a zero out-sample false positive rate and 15%false negative rate of that was lowered to 12% by pooling information. Conclusions We demonstrated the potential usefulness of this novel quantitative imaging analysis method in discriminating ILD and/or emphysema from normal lungs. PMID:26776294

  18. Exploiting semantics for scheduling real-time data collection from sensors to maximize event detection

    NASA Astrophysics Data System (ADS)

    Vaisenberg, Ronen; Mehrotra, Sharad; Ramanan, Deva

    2009-01-01

    A distributed camera network allows for many compelling applications such as large-scale tracking or event detection. In most practical systems, resources are constrained. Although one would like to probe every camera at every time instant and store every frame, this is simply not feasible. Constraints arise from network bandwidth restrictions, I/O and disk usage from writing images, and CPU usage needed to extract features from the images. Assume that, due to resource constraints, only a subset of sensors can be probed at any given time unit. This paper examines the problem of selecting the "best" subset of sensors to probe under some user-specified objective - e.g., detecting as much motion as possible. With this objective, we would like to probe a camera when we expect motion, but would not like to waste resources on a non-active camera. The main idea behind our approach is the use of sensor semantics to guide the scheduling of resources. We learn a dynamic probabilistic model of motion correlations between cameras, and use the model to guide resource allocation for our sensor network. Although previous work has leveraged probabilistic models for sensor-scheduling, our work is distinct in its focus on real-time building-monitoring using a camera network. We validate our approach on a sensor network of a dozen cameras spread throughout a university building, recording measurements of unscripted human activity over a two week period. We automatically learnt a semantic model of typical behaviors, and show that one can significantly improve effciency of resource allocation by exploiting this model.

  19. Elastomeric optical fiber sensors and method for detecting and measuring events occurring in elastic materials

    DOEpatents

    Muhs, Jeffrey D.; Capps, Gary J.; Smith, David B.; White, Clifford P.

    1994-01-01

    Fiber optic sensing means for the detection and measurement of events such as dynamic loadings imposed upon elastic materials including cementitious materials, elastomers, and animal body components and/or the attrition of such elastic materials are provided. One or more optical fibers each having a deformable core and cladding formed of an elastomeric material such as silicone rubber are embedded in the elastic material. Changes in light transmission through any of the optical fibers due the deformation of the optical fiber by the application of dynamic loads such as compression, tension, or bending loadings imposed on the elastic material or by the attrition of the elastic material such as by cracking, deterioration, aggregate break-up, and muscle, tendon, or organ atrophy provide a measurement of the dynamic loadings and attrition. The fiber optic sensors can be embedded in elastomers subject to dynamic loadings and attrition such as commonly used automobiles and in shoes for determining the amount and frequency of the dynamic loadings and the extent of attrition. The fiber optic sensors are also useable in cementitious material for determining the maturation thereof.

  20. First Satellite-detected Perturbations of Outgoing Longwave Radiation Associated with Blowing Snow Events over Antarctica

    NASA Technical Reports Server (NTRS)

    Yang, Yuekui; Palm, Stephen P.; Marshak, Alexander; Wu, Dong L.; Yu, Hongbin; Fu, Qiang

    2014-01-01

    We present the first satellite-detected perturbations of the outgoing longwave radiation (OLR) associated with blowing snow events over the Antarctic ice sheet using data from Cloud-Aerosol Lidar with Orthogonal Polarization and Clouds and the Earth's Radiant Energy System. Significant cloud-free OLR differences are observed between the clear and blowing snow sky, with the sign andmagnitude depending on season and time of the day. During nighttime, OLRs are usually larger when blowing snow is present; the average difference in OLRs between without and with blowing snow over the East Antarctic Ice Sheet is about 5.2 W/m2 for the winter months of 2009. During daytime, in contrast, the OLR perturbation is usually smaller or even has the opposite sign. The observed seasonal variations and day-night differences in the OLR perturbation are consistent with theoretical calculations of the influence of blowing snow on OLR. Detailed atmospheric profiles are needed to quantify the radiative effect of blowing snow from the satellite observations.

  1. PREFACE: 7th International Symposium on Large TPCs for Low-Energy Rare Event Detection

    NASA Astrophysics Data System (ADS)

    Colas, P.; Giomataris, I.; Irastorza, I.; Patzak, Th

    2015-11-01

    The seventh "International Symposium on Large TPCs for Low-Energy Rare Event Detection", took place in Paris between the 15th and 17th of December 2014 at the Institute of Astroparticle Physics (APC) campus - Paris Diderot University. As usual the conference was organized during the week before Christmas, which seems to be convenient for most of the people and occurs every two years with almost 120 participants attending. Many people contributed to the success of the conference, but the organizers would particularly like to thank the management of APC for providing the nice Buffon auditorium and infrastructure. We also acknowledge the valuable support of DSM-Irfu and the University of Zaragoza. The scientific program consisted of plenary sessions including the following topics with theoretical and experimental lectures: • Low energy neutrino physics • Neutrinoless double beta decay process • Dark matter searches • Axion and especially solar axion searches • Space experiments and gamma-ray polarimetry • New detector R&D and future experiments

  2. Solar Energetic Particle Events detected by the Standard Radiation Environment Monitor (SREM) onboard INTEGRAL

    NASA Astrophysics Data System (ADS)

    Georgoulis, M.; Daglis, I. A.; Anastasiadis, A.; Sandberg, I.; Balasis, G.; Nieminen, P.

    2012-01-01

    The SREM is a cost-effective instrument mounted onboard multiple ESA missions. The SREM objective is the in-situ measurement of high-energy solar particles at the spacecraft location. Within the previous solar cycle 23, SREM units onboard ESA's INTEGRAL and Rosetta missions detected several tens of SEPEs and accurately pinpointed their onset, rise, and decay times. We have undertaken a detailed study to determine the solar sources and subsequent interplanetary coronal mass ejections (ICMEs) that gave rise to these events, as well as the timing of SEPEs with the onset of possible geomagnetic activity triggered by these ICMEs. We find that virtually all SREM SEPEs may be associated with CME-driven shocks. For a number of well-studied INTEGRAL/SREM SEPEs, moreover, we see an association between the SEPE peak and the shock passage at L1. Shortly (typically within a few hours) after the SEPE peak, the ICME-driven modulation of the magnetosphere kicks in, with either an increase or a dip of the Dst index, indicating stormy conditions in geospace. We conclude that, pending additional investigation, SREM units may prove useful for a short-term prediction of inclement space-weather conditions in Geospace, especially if mounted onboard dayside missions ahead of the magnetospheric bow shock.

  3. Rapid and Highly Sensitive Detection of Variant Creutzfeldt-Jakob Disease Abnormal Prion Protein on Steel Surfaces by Protein Misfolding Cyclic Amplification: Application to Prion Decontamination Studies.

    PubMed

    Belondrade, Maxime; Nicot, Simon; Béringue, Vincent; Coste, Joliette; Lehmann, Sylvain; Bougard, Daisy

    2016-01-01

    The prevalence of variant Creutzfeldt-Jakob disease (vCJD) in the population remains uncertain, although it has been estimated that 1 in 2000 people in the United Kingdom are positive for abnormal prion protein (PrPTSE) by a recent survey of archived appendix tissues. The prominent lymphotropism of vCJD prions raises the possibility that some surgical procedures may be at risk of iatrogenic vCJD transmission in healthcare facilities. It is therefore vital that decontamination procedures applied to medical devices before their reprocessing are thoroughly validated. A current limitation is the lack of a rapid model permissive to human prions. Here, we developed a prion detection assay based on protein misfolding cyclic amplification (PMCA) technology combined with stainless-steel wire surfaces as carriers of prions (Surf-PMCA). This assay allowed the specific detection of minute quantities (10-8 brain dilution) of either human vCJD or ovine scrapie PrPTSE adsorbed onto a single steel wire, within a two week timeframe. Using Surf-PMCA we evaluated the performance of several reference and commercially available prion-specific decontamination procedures. Surprisingly, we found the efficiency of several marketed reagents to remove human vCJD PrPTSE was lower than expected. Overall, our results demonstrate that Surf-PMCA can be used as a rapid and ultrasensitive assay for the detection of human vCJD PrPTSE adsorbed onto a metallic surface, therefore facilitating the development and validation of decontamination procedures against human prions. PMID:26800081

  4. Rapid and Highly Sensitive Detection of Variant Creutzfeldt-Jakob Disease Abnormal Prion Protein on Steel Surfaces by Protein Misfolding Cyclic Amplification: Application to Prion Decontamination Studies.

    PubMed

    Belondrade, Maxime; Nicot, Simon; Béringue, Vincent; Coste, Joliette; Lehmann, Sylvain; Bougard, Daisy

    2016-01-01

    The prevalence of variant Creutzfeldt-Jakob disease (vCJD) in the population remains uncertain, although it has been estimated that 1 in 2000 people in the United Kingdom are positive for abnormal prion protein (PrPTSE) by a recent survey of archived appendix tissues. The prominent lymphotropism of vCJD prions raises the possibility that some surgical procedures may be at risk of iatrogenic vCJD transmission in healthcare facilities. It is therefore vital that decontamination procedures applied to medical devices before their reprocessing are thoroughly validated. A current limitation is the lack of a rapid model permissive to human prions. Here, we developed a prion detection assay based on protein misfolding cyclic amplification (PMCA) technology combined with stainless-steel wire surfaces as carriers of prions (Surf-PMCA). This assay allowed the specific detection of minute quantities (10-8 brain dilution) of either human vCJD or ovine scrapie PrPTSE adsorbed onto a single steel wire, within a two week timeframe. Using Surf-PMCA we evaluated the performance of several reference and commercially available prion-specific decontamination procedures. Surprisingly, we found the efficiency of several marketed reagents to remove human vCJD PrPTSE was lower than expected. Overall, our results demonstrate that Surf-PMCA can be used as a rapid and ultrasensitive assay for the detection of human vCJD PrPTSE adsorbed onto a metallic surface, therefore facilitating the development and validation of decontamination procedures against human prions.

  5. Rapid and Highly Sensitive Detection of Variant Creutzfeldt - Jakob Disease Abnormal Prion Protein on Steel Surfaces by Protein Misfolding Cyclic Amplification: Application to Prion Decontamination Studies

    PubMed Central

    Belondrade, Maxime; Nicot, Simon; Béringue, Vincent; Coste, Joliette; Lehmann, Sylvain; Bougard, Daisy

    2016-01-01

    The prevalence of variant Creutzfeldt-Jakob disease (vCJD) in the population remains uncertain, although it has been estimated that 1 in 2000 people in the United Kingdom are positive for abnormal prion protein (PrPTSE) by a recent survey of archived appendix tissues. The prominent lymphotropism of vCJD prions raises the possibility that some surgical procedures may be at risk of iatrogenic vCJD transmission in healthcare facilities. It is therefore vital that decontamination procedures applied to medical devices before their reprocessing are thoroughly validated. A current limitation is the lack of a rapid model permissive to human prions. Here, we developed a prion detection assay based on protein misfolding cyclic amplification (PMCA) technology combined with stainless-steel wire surfaces as carriers of prions (Surf-PMCA). This assay allowed the specific detection of minute quantities (10−8 brain dilution) of either human vCJD or ovine scrapie PrPTSE adsorbed onto a single steel wire, within a two week timeframe. Using Surf-PMCA we evaluated the performance of several reference and commercially available prion-specific decontamination procedures. Surprisingly, we found the efficiency of several marketed reagents to remove human vCJD PrPTSE was lower than expected. Overall, our results demonstrate that Surf-PMCA can be used as a rapid and ultrasensitive assay for the detection of human vCJD PrPTSE adsorbed onto a metallic surface, therefore facilitating the development and validation of decontamination procedures against human prions. PMID:26800081

  6. Applying a Hidden Markov Model-Based Event Detection and Classification Algorithm to Apollo Lunar Seismic Data

    NASA Astrophysics Data System (ADS)

    Knapmeyer-Endrun, B.; Hammer, C.

    2014-12-01

    The seismometers that the Apollo astronauts deployed on the Moon provide the only recordings of seismic events from any extra-terrestrial body so far. These lunar events are significantly different from ones recorded on Earth, in terms of both signal shape and source processes. Thus they are a valuable test case for any experiment in planetary seismology. In this study, we analyze Apollo 16 data with a single-station event detection and classification algorithm in view of NASA's upcoming InSight mission to Mars. InSight, scheduled for launch in early 2016, has the goal to investigate Mars' internal structure by deploying a seismometer on its surface. As the mission does not feature any orbiter, continuous data will be relayed to Earth at a reduced rate. Full range data will only be available by requesting specific time-windows within a few days after the receipt of the original transmission. We apply a recently introduced algorithm based on hidden Markov models that requires only a single example waveform of each event class for training appropriate models. After constructing the prototypes we detect and classify impacts and deep and shallow moonquakes. Initial results for 1972 (year of station installation with 8 months of data) indicate a high detection rate of over 95% for impacts, of which more than 80% are classified correctly. Deep moonquakes, which occur in large amounts, but often show only very weak signals, are detected with less certainty (~70%). As there is only one weak shallow moonquake covered, results for this event class are not statistically significant. Daily adjustments of the background noise model help to reduce false alarms, which are mainly erroneous deep moonquake detections, by about 25%. The algorithm enables us to classify events that were previously listed in the catalog without classification, and, through the combined use of long period and short period data, identify some unlisted local impacts as well as at least two yet unreported

  7. Effects of rainfall events on the occurrence and detection efficiency of viruses in river water impacted by combined sewer overflows.

    PubMed

    Hata, Akihiko; Katayama, Hiroyuki; Kojima, Keisuke; Sano, Shoichi; Kasuga, Ikuro; Kitajima, Masaaki; Furumai, Hiroaki

    2014-01-15

    Rainfall events can introduce large amount of microbial contaminants including human enteric viruses into surface water by intermittent discharges from combined sewer overflows (CSOs). The present study aimed to investigate the effect of rainfall events on viral loads in surface waters impacted by CSO and the reliability of molecular methods for detection of enteric viruses. The reliability of virus detection in the samples was assessed by using process controls for virus concentration, nucleic acid extraction and reverse transcription (RT)-quantitative PCR (qPCR) steps, which allowed accurate estimation of virus detection efficiencies. Recovery efficiencies of poliovirus in river water samples collected during rainfall events (<10%) were lower than those during dry weather conditions (>10%). The log10-transformed virus concentration efficiency was negatively correlated with suspended solid concentration (r(2)=0.86) that increased significantly during rainfall events. Efficiencies of DNA extraction and qPCR steps determined with adenovirus type 5 and a primer sharing control, respectively, were lower in dry weather. However, no clear relationship was observed between organic water quality parameters and efficiencies of these two steps. Observed concentrations of indigenous enteric adenoviruses, GII-noroviruses, enteroviruses, and Aichi viruses increased during rainfall events even though the virus concentration efficiency was presumed to be lower than in dry weather. The present study highlights the importance of using appropriate process controls to evaluate accurately the concentration of water borne enteric viruses in natural waters impacted by wastewater discharge, stormwater, and CSOs.

  8. Unsupervised spatio-temporal detection of brain functional activation based on hidden Markov multiple event sequence models

    NASA Astrophysics Data System (ADS)

    Faisan, Sylvain; Thoraval, Laurent; Armspach, Jean-Paul; Heitz, Fabrice; Foucher, Jack

    2005-04-01

    This paper presents a novel, completely unsupervised fMRI brain mapping approach that addresses the three problems of hemodynamic response function (HRF) shape variability, neural event timing, and fMRI response linearity. To make it robust, the method takes into account spatial and temporal information directly into the core of the activation detection process. In practice, activation detection is formulated in terms of temporal alignment between the sequence of hemodynamic response onsets (HROs) detected in the fMRI signal at υ and in the spatial neighbourhood of υ, and the sequence of "off-on" transitions observed in the input blocked stimulation paradigm (when considering epoch-related fMRI data), or the sequence of stimuli of the event-based paradigm (when considering event-related fMRI data). This multiple event sequence alignment problem, which comes under multisensor data fusion, is solved within the probabilistic framework of hidden Markov multiple event sequence models (HMMESMs), a special class of hidden Markov models. Results obtained on real and synthetic data compete with those obtained with the popular statistical parametric mapping (SPM) approach, but without necessitating any prior definition of the expected activation patterns, the HMMESM mapping approach being completely unsupervised.

  9. Effects of rainfall events on the occurrence and detection efficiency of viruses in river water impacted by combined sewer overflows.

    PubMed

    Hata, Akihiko; Katayama, Hiroyuki; Kojima, Keisuke; Sano, Shoichi; Kasuga, Ikuro; Kitajima, Masaaki; Furumai, Hiroaki

    2014-01-15

    Rainfall events can introduce large amount of microbial contaminants including human enteric viruses into surface water by intermittent discharges from combined sewer overflows (CSOs). The present study aimed to investigate the effect of rainfall events on viral loads in surface waters impacted by CSO and the reliability of molecular methods for detection of enteric viruses. The reliability of virus detection in the samples was assessed by using process controls for virus concentration, nucleic acid extraction and reverse transcription (RT)-quantitative PCR (qPCR) steps, which allowed accurate estimation of virus detection efficiencies. Recovery efficiencies of poliovirus in river water samples collected during rainfall events (<10%) were lower than those during dry weather conditions (>10%). The log10-transformed virus concentration efficiency was negatively correlated with suspended solid concentration (r(2)=0.86) that increased significantly during rainfall events. Efficiencies of DNA extraction and qPCR steps determined with adenovirus type 5 and a primer sharing control, respectively, were lower in dry weather. However, no clear relationship was observed between organic water quality parameters and efficiencies of these two steps. Observed concentrations of indigenous enteric adenoviruses, GII-noroviruses, enteroviruses, and Aichi viruses increased during rainfall events even though the virus concentration efficiency was presumed to be lower than in dry weather. The present study highlights the importance of using appropriate process controls to evaluate accurately the concentration of water borne enteric viruses in natural waters impacted by wastewater discharge, stormwater, and CSOs. PMID:24064345

  10. Development of a multiplex polymerase chain reaction method for simultaneous detection of eight events of genetically modified maize.

    PubMed

    Onishi, Mari; Matsuoka, Takeshi; Kodama, Takashi; Kashiwaba, Koichi; Futo, Satoshi; Akiyama, Hiroshi; Maitani, Tamio; Furui, Satoshi; Oguchi, Taichi; Hino, Akihiro

    2005-12-14

    In this study, we developed a novel multiplex polymerase chain reaction (PCR) method for simultaneous detection of up to eight events of genetically modified (GM) maize within a single reaction. The eight detection primer pairs designed to be construct specific for eight respective GM events (i.e., Bt11, Event176, GA21, MON810, MON863, NK603, T25, and TC1507) and a primer pair for an endogenous reference gene, ssIIb, were included in the nonaplex(9plex) PCR system, and its amplified products could be distinguished by agarose gel and capillary electrophoreses based on their different lengths. The optimal condition enabled us to reliably amplify two fragments corresponding to a construct specific sequence and a taxon specific ssIIb in each of the eight events of GM maize and all of nine fragments in a simulated GM mixture containing as little as 0.25% (w/w) each of eight events of GM maize. These results indicate that this multiplex PCR method could be an effective qualitative detection method for screening GM maize. PMID:16332120

  11. A robust real-time gait event detection using wireless gyroscope and its application on normal and altered gaits.

    PubMed

    Gouwanda, Darwin; Gopalai, Alpha Agape

    2015-02-01

    Gait events detection allows clinicians and biomechanics researchers to determine timing of gait events, to estimate duration of stance phase and swing phase and to segment gait data. It also aids biomedical engineers to improve the design of orthoses and FES (functional electrical stimulation) systems. In recent years, researchers have resorted to using gyroscopes to determine heel-strike (HS) and toe-off (TO) events in gait cycles. However, these methods are subjected to significant delays when implemented in real-time gait monitoring devices, orthoses, and FES systems. Therefore, the work presented in this paper proposes a method that addresses these delays, to ensure real-time gait event detection. The proposed algorithm combines the use of heuristics and zero-crossing method to identify HS and TO. Experiments involving: (1) normal walking; (2) walking with knee brace; and (3) walking with ankle brace for overground walking and treadmill walking were designed to verify and validate the identified HS and TO. The performance of the proposed method was compared against the established gait detection algorithms. It was observed that the proposed method produced detection rate that was comparable to earlier reported methods and recorded reduced time delays, at an average of 100 ms.

  12. A robust real-time gait event detection using wireless gyroscope and its application on normal and altered gaits.

    PubMed

    Gouwanda, Darwin; Gopalai, Alpha Agape

    2015-02-01

    Gait events detection allows clinicians and biomechanics researchers to determine timing of gait events, to estimate duration of stance phase and swing phase and to segment gait data. It also aids biomedical engineers to improve the design of orthoses and FES (functional electrical stimulation) systems. In recent years, researchers have resorted to using gyroscopes to determine heel-strike (HS) and toe-off (TO) events in gait cycles. However, these methods are subjected to significant delays when implemented in real-time gait monitoring devices, orthoses, and FES systems. Therefore, the work presented in this paper proposes a method that addresses these delays, to ensure real-time gait event detection. The proposed algorithm combines the use of heuristics and zero-crossing method to identify HS and TO. Experiments involving: (1) normal walking; (2) walking with knee brace; and (3) walking with ankle brace for overground walking and treadmill walking were designed to verify and validate the identified HS and TO. The performance of the proposed method was compared against the established gait detection algorithms. It was observed that the proposed method produced detection rate that was comparable to earlier reported methods and recorded reduced time delays, at an average of 100 ms. PMID:25619613

  13. Comparison among solar energetic particle events detected by COSTEP/SOHO experiment

    NASA Astrophysics Data System (ADS)

    Gomez-Herrero, Raul

    A comparative study of three impulsive solar events produced in July 1996 and two gradual-CME associated events produced in November 1997 has been performed using data from EPHIN instrument aboard SOHO spacecraft. Temporal evolution of the differential energy spectra of electrons in the energy range 0.25-10.4 MeV and H & He nuclei in the energy range 4.3-53.0 MeV/n has been determined for these events. Isotopic abundances of H and He have been obtained separately for each event.

  14. A new method to detect anisotropic electron events with SOHO/EPHIN

    NASA Astrophysics Data System (ADS)

    Banjac, Saša; Kühl, Patrick; Heber, Bernd

    2016-07-01

    The EPHIN instrument (Electron Proton Helium INstrument) forms a part of the COSTEP experiment (COmprehensive SupraThermal and Energetic Particle Analyzer) within the CEPAC collaboration on board of the SOHO spacecraft (SOlar and Heliospheric Observatory). The EPHIN sensor is a stack of six solid-state detectors surrounded by an anti-coincidence. It measures energy spectra of electrons in the range 250 keV to >8.7 MeV, and hydrogen and helium isotopes in the range 4~MeV/n to >53~MeV/n. In order to improve the isotopic resolution, the first two detectors have been segmented: 5 segments form a ring enclosing a central segment. This does not only allow to correct the energy-losses in the detectors for the different path-length in the detectors but allows also an estimation of the arrival direction of the particles with respect to the sensor axis. Utilizing an extensive GEANT 4 Monte-Carlo simulation of the sensor head we computed the scattering-induced modifications to the input angular distribution and developed an inversion method that takes into account the poor counting statistics by optimizing the corresponding algorithm. This improvement makes it possible for the first time to detect long lasting anisotropies in the 1~MeV-3~MeV electron flux with a single telescope on a three-axis stabilized spacecraft. We present the method and its application to several events with strong anisotropies. For validation, we compare our data with the WIND-3DP results.

  15. Automated Detection and Predictive Modeling of Flux Transfer Events using CLUSTER Data

    NASA Astrophysics Data System (ADS)

    Sipes, T. B.; Karimabadi, H.; Driscoll, J.; Wang, Y.; Lavraud, B.; Slavin, J. A.

    2006-12-01

    Almost all statistical studies of flux ropes (FTEs) and traveling compression regions (TCRs) have been based on (i) visual inspection of data to compile a list of events and (ii) use of histograms and simple linear correlation analysis to study their properties and potential causes and dependencies. This approach has several major drawbacks including being highly subjective and inefficient. The traditional use of histograms and simple linear correlation analysis is also only useful for analysis of systems that show dominant dependencies on one or two variables at the most. However, if the system has complex dependencies, more sophisticated statistical techniques are required. For example, Wang et al. [2006] showed evidence that FTE occurrence rate are affected by IMF Bygsm, Bzgsm, and magnitude, and the IMF clock, tilt, spiral, and cone angles. If the initial findings were correct that FTEs occur only during periods of southward IMF, one could use the direction of IMF as a predictor of occurrence of FTEs. But in light of Wang et al. result, one cannot draw quantitative conclusions about conditions under which FTEs occur. It may be that a certain combination of these parameters is the true controlling parameter. To uncover this, one needs to deploy more sophisticated techniques. We have developed a new, sophisticated data mining tool called MineTool. MineTool is highly accurate, flexible and capable of handling difficult and even noisy datasets extremely well. It has the ability to outperform standard data mining tools such as artificial neural networks, decision/regression trees and support vector machines. Here we present preliminary results of the application of this tool to the CLUSTER data to perform two tasks: (i) automated detection of FTEs, and (ii) predictive modeling of occurrences of FTEs based on IMF and magnetospheric conditions.

  16. A secure distributed logistic regression protocol for the detection of rare adverse drug events

    PubMed Central

    El Emam, Khaled; Samet, Saeed; Arbuckle, Luk; Tamblyn, Robyn; Earle, Craig; Kantarcioglu, Murat

    2013-01-01

    Background There is limited capacity to assess the comparative risks of medications after they enter the market. For rare adverse events, the pooling of data from multiple sources is necessary to have the power and sufficient population heterogeneity to detect differences in safety and effectiveness in genetic, ethnic and clinically defined subpopulations. However, combining datasets from different data custodians or jurisdictions to perform an analysis on the pooled data creates significant privacy concerns that would need to be addressed. Existing protocols for addressing these concerns can result in reduced analysis accuracy and can allow sensitive information to leak. Objective To develop a secure distributed multi-party computation protocol for logistic regression that provides strong privacy guarantees. Methods We developed a secure distributed logistic regression protocol using a single analysis center with multiple sites providing data. A theoretical security analysis demonstrates that the protocol is robust to plausible collusion attacks and does not allow the parties to gain new information from the data that are exchanged among them. The computational performance and accuracy of the protocol were evaluated on simulated datasets. Results The computational performance scales linearly as the dataset sizes increase. The addition of sites results in an exponential growth in computation time. However, for up to five sites, the time is still short and would not affect practical applications. The model parameters are the same as the results on pooled raw data analyzed in SAS, demonstrating high model accuracy. Conclusion The proposed protocol and prototype system would allow the development of logistic regression models in a secure manner without requiring the sharing of personal health information. This can alleviate one of the key barriers to the establishment of large-scale post-marketing surveillance programs. We extended the secure protocol to account for

  17. A Methodology to Detect Abnormal Relative Wall Shear Stress on the Full Surface of the Thoracic Aorta Using 4D Flow MRI

    PubMed Central

    van Ooij, Pim; Potters, Wouter V.; Nederveen, Aart J.; Allen, Bradley D.; Collins, Jeremy; Carr, James; Malaisrie, S. Chris; Markl, Michael; Barker, Alex J.

    2014-01-01

    Purpose To compute cohort-averaged wall shear stress (WSS) maps in the thoracic aorta of patients with aortic dilatation or valvular stenosis and to detect abnormal regional WSS. Methods Systolic WSS vectors, estimated from 4D flow MRI data, were calculated along the thoracic aorta lumen in 10 controls, 10 patients with dilated aortas and 10 patients with aortic valve stenosis. 3D segmentations of each aorta were co-registered by group and used to create a cohort-specific aortic geometry. The WSS vectors of each subject were interpolated onto the corresponding cohort-specific geometry to create cohort-averaged WSS maps. A Wilcoxon rank sum test was used to generate aortic P-value maps (P<0.05) representing regional relative WSS differences between groups. Results Cohort-averaged systolic WSS maps and P-value maps were successfully created for all cohorts and comparisons. The dilation cohort showed significantly lower WSS on 7% of the ascending aorta surface, whereas the stenosis cohort showed significantly higher WSS aorta on 34% the ascending aorta surface. Conclusions The findings of this study demonstrated the feasibility of generating cohort-averaged WSS maps for the visualization and identification of regionally altered WSS in the presence of disease, as compared to healthy controls. PMID:24753241

  18. Abnormal cortical sensorimotor activity during “Target” sound detection in subjects with acute acoustic trauma sequelae: an fMRI study

    PubMed Central

    Job, Agnès; Pons, Yoann; Lamalle, Laurent; Jaillard, Assia; Buck, Karl; Segebarth, Christoph; Delon-Martin, Chantal

    2012-01-01

    The most common consequences of acute acoustic trauma (AAT) are hearing loss at frequencies above 3 kHz and tinnitus. In this study, we have used functional Magnetic Resonance Imaging (fMRI) to visualize neuronal activation patterns in military adults with AAT and various tinnitus sequelae during an auditory “oddball” attention task. AAT subjects displayed overactivities principally during reflex of target sound detection, in sensorimotor areas and in emotion-related areas such as the insula, anterior cingulate and prefrontal cortex, in premotor area, in cross-modal sensory associative areas, and, interestingly, in a region of the Rolandic operculum that has recently been shown to be involved in tympanic movements due to air pressure. We propose further investigations of this brain area and fine middle ear investigations, because our results might suggest a model in which AAT tinnitus may arise as a proprioceptive illusion caused by abnormal excitability of middle-ear muscle spindles possibly link with the acoustic reflex and associated with emotional and sensorimotor disturbances. PMID:22574285

  19. Unified framework for triaxial accelerometer-based fall event detection and classification using cumulants and hierarchical decision tree classifier

    PubMed Central

    Kambhampati, Satya Samyukta; Singh, Vishal; Ramkumar, Barathram

    2015-01-01

    In this Letter, the authors present a unified framework for fall event detection and classification using the cumulants extracted from the acceleration (ACC) signals acquired using a single waist-mounted triaxial accelerometer. The main objective of this Letter is to find suitable representative cumulants and classifiers in effectively detecting and classifying different types of fall and non-fall events. It was discovered that the first level of the proposed hierarchical decision tree algorithm implements fall detection using fifth-order cumulants and support vector machine (SVM) classifier. In the second level, the fall event classification algorithm uses the fifth-order cumulants and SVM. Finally, human activity classification is performed using the second-order cumulants and SVM. The detection and classification results are compared with those of the decision tree, naive Bayes, multilayer perceptron and SVM classifiers with different types of time-domain features including the second-, third-, fourth- and fifth-order cumulants and the signal magnitude vector and signal magnitude area. The experimental results demonstrate that the second- and fifth-order cumulant features and SVM classifier can achieve optimal detection and classification rates of above 95%, as well as the lowest false alarm rate of 1.03%. PMID:26609414

  20. A new method for producing automated seismic bulletins: Probabilistic event detection, association, and location

    SciTech Connect

    Draelos, Timothy J.; Ballard, Sanford; Young, Christopher J.; Brogan, Ronald

    2015-10-01

    Given a set of observations within a specified time window, a fitness value is calculated at each grid node by summing station-specific conditional fitness values. Assuming each observation was generated by a refracted P wave, these values are proportional to the conditional probabilities that each observation was generated by a seismic event at the grid node. The node with highest fitness value is accepted as a hypothetical event location, subject to some minimal fitness value, and all arrivals within a longer time window consistent with that event are associated with it. During the association step, a variety of different phases are considered. In addition, once associated with an event, an arrival is removed from further consideration. While unassociated arrivals remain, the search for other events is repeated until none are identified.

  1. A new method for producing automated seismic bulletins: Probabilistic event detection, association, and location

    DOE PAGES

    Draelos, Timothy J.; Ballard, Sanford; Young, Christopher J.; Brogan, Ronald

    2015-10-01

    Given a set of observations within a specified time window, a fitness value is calculated at each grid node by summing station-specific conditional fitness values. Assuming each observation was generated by a refracted P wave, these values are proportional to the conditional probabilities that each observation was generated by a seismic event at the grid node. The node with highest fitness value is accepted as a hypothetical event location, subject to some minimal fitness value, and all arrivals within a longer time window consistent with that event are associated with it. During the association step, a variety of different phasesmore » are considered. In addition, once associated with an event, an arrival is removed from further consideration. While unassociated arrivals remain, the search for other events is repeated until none are identified.« less

  2. IRcall and IRclassifier: two methods for flexible detection of intron retention events from RNA-Seq data

    PubMed Central

    2015-01-01

    Background The emergence of next-generation RNA sequencing (RNA-Seq) provides tremendous opportunities for researchers to analyze alternative splicing on a genome-wide scale. However, accurate detection of intron retention (IR) events from RNA-Seq data has remained an unresolved challenge in next-generation sequencing (NGS) studies. Results We propose two new methods: IRcall and IRclassifier to detect IR events from RNA-Seq data. Our methods combine together gene expression information, read coverage within an intron, and read counts (within introns, within flanking exons, supporting splice junctions, and overlapping with 5' splice site/ 3' splice site), employing ranking strategy and classifiers to detect IR events. We applied our approaches to one published RNA-Seq data on contrasting skip mutant and wild-type in Arabidopsis thaliana. Compared with three state-of-the-art methods, IRcall and IRclassifier could effectively filter out false positives, and predict more accurate IR events. Availability The data and codes of IRcall and IRclassifier are available at http://mlg.hit.edu.cn/ybai/IR/IRcallAndIRclass.html PMID:25707295

  3. Accuracy and Precision of Equine Gait Event Detection during Walking with Limb and Trunk Mounted Inertial Sensors

    PubMed Central

    Olsen, Emil; Andersen, Pia Haubro; Pfau, Thilo

    2012-01-01

    The increased variations of temporal gait events when pathology is present are good candidate features for objective diagnostic tests. We hypothesised that the gait events hoof-on/off and stance can be detected accurately and precisely using features from trunk and distal limb-mounted Inertial Measurement Units (IMUs). Four IMUs were mounted on the distal limb and five IMUs were attached to the skin over the dorsal spinous processes at the withers, fourth lumbar vertebrae and sacrum as well as left and right tuber coxae. IMU data were synchronised to a force plate array and a motion capture system. Accuracy (bias) and precision (SD of bias) was calculated to compare force plate and IMU timings for gait events. Data were collected from seven horses. One hundred and twenty three (123) front limb steps were analysed; hoof-on was detected with a bias (SD) of −7 (23) ms, hoof-off with 0.7 (37) ms and front limb stance with −0.02 (37) ms. A total of 119 hind limb steps were analysed; hoof-on was found with a bias (SD) of −4 (25) ms, hoof-off with 6 (21) ms and hind limb stance with 0.2 (28) ms. IMUs mounted on the distal limbs and sacrum can detect gait events accurately and precisely. PMID:22969392

  4. Acoustic events semantic detection, classification, and annotation for persistent surveillance applications

    NASA Astrophysics Data System (ADS)

    Alkilani, Amjad; Shirkhodaie, Amir

    2014-06-01

    Understanding of group activity based on analysis of spatiotemporally correlated acoustic sound events has received a minimum attention in the literature and hence is not well understood. Identification of group sub-activities such as: Human-Vehicle Interactions (HVI), Human-Object Interactions (HOI), and Human-Human Interactions (HHI) can significantly improve Situational Awareness (SA) in Persistent Surveillance Systems (PSS). In this paper, salient sound events associated with group activities are preliminary identified and applied for training a Gaussian Mixture Model (GMM) whose features are employed as feature vectors for training of algorithms for acoustic sound recognition. In this paper, discrimination of salient sounds associated with the HVI, HHI, and HOI events is achieved via a Correlation Based Template Matching (CMTM) classifier. To interlinked salient events representing an ontology-based hypothesis, a Hidden Markov Model (HMM) is employed to recognize spatiotemporally correlated events. Once such a connection is established, then, the system generates an annotation of each perceived sound event. This paper discusses the technical aspects of this approach and presents the experimental results for several outdoor group activities monitored by an array of acoustic sensors.

  5. Chronic sensory stroke with and without central pain is associated with bilaterally distributed sensory abnormalities as detected by quantitative sensory testing.

    PubMed

    Krause, Thomas; Asseyer, Susanna; Geisler, Frederik; Fiebach, Jochen B; Oeltjenbruns, Jochen; Kopf, Andreas; Villringer, Kersten; Villringer, Arno; Jungehulsing, Gerhard J

    2016-01-01

    Approximately 20% of patients suffering from stroke with pure or predominant sensory symptoms (referred to as sensory stroke patients) develop central poststroke pain (CPSP). It is largely unknown what distinguishes these patients from those who remain pain free. Using quantitative sensory testing (QST), we analyzed the somatosensory profiles of 50 patients with chronic sensory stroke, of which 25 suffered from CPSP. As compared with reference data from healthy controls, patients with CPSP showed alterations of thermal and mechanical thresholds on the body area contralateral to their stroke (P < 0.01). Patients with sensory stroke but without CPSP (non-pain sensory stroke [NPSS] patients) exhibited similar albeit less pronounced contralesional changes. Paradoxical heat sensation (PHS) and dynamic mechanical allodynia (DMA) showed higher values in CPSP, and an elevated cold detection threshold (CDT) was seen more often in CPSP than in patients with NPSS (P < 0.05). In patients with CPSP, changes in CDT, PHS, dynamic mechanical allodynia, and temporal pain summation (wind-up ratio) each correlated with the presence of pain (P < 0.05). On the homologous ipsilesional body area, both patient groups showed additional significant abnormalities as compared with the reference data, which strongly resembled the contralesional changes. In summary, our analysis reveals that CPSP is associated with impaired temperature perception and positive sensory signs, but differences between patients with CPSP and NPSS are subtle. Both patients with CPSP and NPSS show considerable QST changes on the ipsilesional body side. These results are in part paralleled by recent findings of bilaterally spread cortical atrophy in CPSP and might reflect chronic maladaptive cortical plasticity, particularly in patients with CPSP.

  6. Utility of Clinical Breast Exams in Detecting Local-Regional Breast Events after Breast-Conservation in Women with a Personal History of High-risk Breast Cancer

    PubMed Central

    Neuman, Heather B.; Schumacher, Jessica R.; Francescatti, Amanda B.; Adesoye, Taiwo; SB, Edge; ES, Burnside; DJ, Vanness; M, Yu; Y, Si; D, McKellar; DP, Winchester; Greenberg, Caprice C.

    2016-01-01

    Introduction Although breast cancer follow-up guidelines emphasize the importance of clinical exams, prior studies suggest a small fraction of local-regional events occurring after breast conservation are detected by exam alone. Our objective was to examine how local-regional events are detected in a contemporary, national cohort of high-risk breast cancer survivors. Methods A stage-stratified sample of stage II/III breast cancer patients diagnosed in 2006-2007 (n=11,099) were identified from 1,217 facilities within the National Cancer Data Base. Additional data on local-regional and distant breast events, method of event detection, imaging received, and mortality was collected. We further limited the cohort to patients with breast conservation (n=4,854). Summary statistics describe local-regional event rates and detection method. Results Local-regional events were detected in 5.5% (n=265). 83% were ipsilateral or contralateral in-breast events, and 17% within ipsilateral lymph nodes. 48% of local-regional events were detected on asymptomatic breast imaging, 29% by patients, and 10% on clinical exam. Overall, 0.5% of the 4,854 patients had a local-regional event detected on exam. Exams detected a higher proportion of lymph node (8/45) compared to in-breast events (18/220). No factors were associated with method of event detection. Discussion Clinical exams, as an adjunct to screening mammography, have a modest effect on local-regional event detection. This contradicts current belief that exams are a critical adjunct to mammographic screening. These findings can help to streamline follow-up care, potentially improving follow-up efficiency and quality. PMID:27491784

  7. Inherited structural cytogenetic abnormalities detected incidentally in fetuses diagnosed prenatally: frequency, parental-age associations, sex-ratio trends, and comparisons with rates of mutants.

    PubMed Central

    Hook, E B; Schreinemachers, D M; Willey, A M; Cross, P K

    1984-01-01

    Rates of structural chromosome abnormalities were analyzed in 24,951 fetuses studied prenatally in which there were no grounds to suspect an inherited abnormality. In about one in 200 prenatal cytogenetic diagnoses, an unexpected structural abnormality was found. The observed rate was 5.3 per 1,000, of which 1.7 per 1,000 were unbalanced and 3.6 per 1,000 balanced. The rate of inherited abnormalities was 3.1-3.7 per 1,000 (0.4-0.9 per 1,000 for unbalanced abnormalities and 2.6-2.8 per 1,000 for balanced abnormalities). The rate of mutants in this series was, by contrast, 1.6-2.2 per 1,000 (0.8-1.2 per 1,000 for unbalanced abnormalities and 0.8-1.0 per 1,000 for balanced abnormalities). The rate of balanced Robertsonian translocation carriers was 0.6 per 1,000 (about 0.25 per 1,000 for mutants and 0.35 per 1,000 for inherited abnormalities), and for other balanced abnormalities, 3.0 per 1,000 (about 0.6 per 1,000 for mutants and 2.4 per 1,000 for inherited abnormalities). The rates of unbalanced Robertsonian translocations was about 0.1 per 1,000, almost all of which were mutants. For supernumerary rearrangements, the rate was 0.9 per 1,000 (about 0.4 per 1,000 inherited and 0.5 per 1,000 mutant). The rates of all unbalanced (nonmosaic) inherited abnormalities (4.0-5.2 per 10,000) were intermediate between higher rates estimated in all conceptuses (9.1-15.8 per 10,000) and rates observed in newborns (1.5-2.5 per 10,000). This trend is probably attributable to fetal mortality associated with unbalanced rearrangements. The rates of balanced (nonmosaic) inherited abnormalities (26.0-28.0 per 10,000), however, were considerably higher than the rates in all conceptuses (13-16.7 per 10,000) or in all live births (12.2-16.0 per 10,000). The major difference was in the rate of inversions. The use of "banding" methods in the studies of amniocentesis but not in most of the live births or abortus studies probably contributes to at least some of these differences. One trend in

  8. Detecting Recent Atmospheric River Induced Flood Events over the Russian River Basin

    NASA Astrophysics Data System (ADS)

    Mehran, A.; Lettenmaier, D. P.; Ralph, F. M.; Lavers, D. A.

    2015-12-01

    Almost all major flood events in the coastal Western U.S. occur as a result of multi-day extreme precipitation during the winter and late fall, and most such events are now known to be Atmospheric Rivers (ARs). AR events are defined as having integrated water vapor (IWV) exceeding 2 cm in an area at least 2000 km long and no more than 1000 km wide. The dominant moisture source in many AR events, including those associated with most floods in the Russian River basin in Northern California, is the tropics. We report on a hydrological analysis of selected floods in the Russian River basin using the Distributed Hydrology Soil Vegetation Model (DHSVM), forced alternately by gridded station data, NWS WSR-88D radar data, and output from a regional atmospheric model. We also report results of river state forecasts using a river hydrodynamics model to reconstruct flood inundation from selected AR events. We diagnose errors in both the hydrological and river stage predictions, and discuss alternatives for future error reduction.

  9. Externally Sensitized Deprotection of PPG-Masked Carbonyls as a Spatial Proximity Probe in Photoamplified Detection of Binding Events

    PubMed Central

    Gustafson, Tiffany P.; Metzel, Greg A.

    2013-01-01

    Externally-sensitized electron-transfer fragmentation in dithiane PPG-protected carbonyls is adopted for detection and amplification of molecular recognition events. The new methodology allows for detection of as low as 50 attomoles of avidin utilizing an imager based on a low sensitivity mass-produced consumer CCD camera. Numeric modelling is carried out to demonstrate the intrinsic limitations of 2D amplification on surfaces and the advantages of unconstrained amplification in a compartmentalized volume of spatially addressable 3D solutions. PMID:22252455

  10. Event-specific detection of seven genetically modified soybean and maizes using multiplex-PCR coupled with oligonucleotide microarray.

    PubMed

    Xu, Jia; Zhu, Shuifang; Miao, Haizhen; Huang, Wensheng; Qiu, Minyan; Huang, Yan; Fu, Xuping; Li, Yao

    2007-07-11

    With the increasing development of genetically modified organism (GMO) detection techniques, the polymerase chain reaction (PCR) technique has been the mainstay for GMO detection. An oligonucleotide microarray is a glass chip to the surface of which an array of oligonucleotides was fixed as spots, each containing numerous copies of a sequence-specific probe that is complementary to a gene of interest. So it is used to detect ten or more targets synchronously. In this research, an event-specific detection strategy based on the unique and specific integration junction sequences between the host plant genome DNA and the integrated gene is being developed for its high specificity using multiplex-PCR together with oligonucleotide microarray. A commercial GM soybean (GTS 40-3-2) and six GM maize events (MON810, MON863, Bt176, Bt11, GA21, and T25) were detected by this method. The results indicate that it is a suitable method for the identification of these GM soybean and maizes. PMID:17559227

  11. Event-specific detection of seven genetically modified soybean and maizes using multiplex-PCR coupled with oligonucleotide microarray.

    PubMed

    Xu, Jia; Zhu, Shuifang; Miao, Haizhen; Huang, Wensheng; Qiu, Minyan; Huang, Yan; Fu, Xuping; Li, Yao

    2007-07-11

    With the increasing development of genetically modified organism (GMO) detection techniques, the polymerase chain reaction (PCR) technique has been the mainstay for GMO detection. An oligonucleotide microarray is a glass chip to the surface of which an array of oligonucleotides was fixed as spots, each containing numerous copies of a sequence-specific probe that is complementary to a gene of interest. So it is used to detect ten or more targets synchronously. In this research, an event-specific detection strategy based on the unique and specific integration junction sequences between the host plant genome DNA and the integrated gene is being developed for its high specificity using multiplex-PCR together with oligonucleotide microarray. A commercial GM soybean (GTS 40-3-2) and six GM maize events (MON810, MON863, Bt176, Bt11, GA21, and T25) were detected by this method. The results indicate that it is a suitable method for the identification of these GM soybean and maizes.

  12. Detecting deception in children: event familiarity affects criterion-based content analysis ratings.

    PubMed

    Pezdek, Kathy; Morrow, Anne; Blandon-Gitlin, Iris; Goodman, Gail S; Quas, Jodi A; Saywitz, Karen J; Bidrose, Sue; Pipe, Margaret-Ellen; Rogers, Martha; Brodie, Laura

    2004-02-01

    Statement Validity Assessment (SVA) is a comprehensive credibility assessment system, with the Criterion-Based Content Analysis (CBCA) as a core component. Worldwide, the CBCA is reported to be the most widely used veracity assessment instrument. We tested and confirmed the hypothesis that CBCA scores are affected by event familiarity; descriptions of familiar events are more likely to be judged true than are descriptions of unfamiliar events. CBCA scores were applied to transcripts of 114 children who recalled a routine medical procedure (control) or a traumatic medical procedure that they had experienced one time (relatively unfamiliar) or multiple times (relatively familiar). CBCA scores were higher for children in the relatively familiar than the relatively unfamiliar condition, and CBCA scores were significantly correlated with age. Results raise serious questions regarding the forensic suitability of the CBCA for assessing the veracity of children's accounts.

  13. PortVis: A Tool for Port-Based Detection of Security Events

    SciTech Connect

    McPherson, J; Ma, K; Krystosk, P; Bartoletti, T; Christensen, M

    2004-06-29

    Most visualizations of security-related network data require large amounts of finely detailed, high-dimensional data. However, in some cases, the data available can only be coarsely detailed because of security concerns or other limitations. How can interesting security events still be discovered in data that lacks important details, such as IP addresses, network security alarms, and labels? In this paper, we discuss a system we have designed that takes very coarsely detailed data-basic, summarized information of the activity on each TCP port during each given hour-and uses visualization to help uncover interesting security events.

  14. Wideband acoustic activation and detection of droplet vaporization events using a capacitive micromachined ultrasonic transducer.

    PubMed

    Novell, Anthony; Arena, Christopher B; Oralkan, Omer; Dayton, Paul A

    2016-06-01

    An ongoing challenge exists in understanding and optimizing the acoustic droplet vaporization (ADV) process to enhance contrast agent effectiveness for biomedical applications. Acoustic signatures from vaporization events can be identified and differentiated from microbubble or tissue signals based on their frequency content. The present study exploited the wide bandwidth of a 128-element capacitive micromachined ultrasonic transducer (CMUT) array for activation (8 MHz) and real-time imaging (1 MHz) of ADV events from droplets circulating in a tube. Compared to a commercial piezoelectric probe, the CMUT array provides a substantial increase of the contrast-to-noise ratio. PMID:27369143

  15. Event-specific qualitative and quantitative PCR methods for the detection of genetically modified rapeseed Oxy-235.

    PubMed

    Wu, Gang; Wu, Yuhua; Xiao, Ling; Lu, Changming

    2008-10-01

    Oxy-235 is an oxynil-tolerant genetically modified rapeseed approved for commercialized planting in Canada. The aim of this study was to establish event-specific qualitative and quantitative detection methods for Oxy-235. Both the 5'- and 3'-junction sequences spanning the plant DNA and the integrated gene construct of the Oxy-235 event were isolated, sequenced and analyzed. A 1298-bp deletion of the rapeseed genomic DNA that showed a high similarity to the mRNA sequence of Arabidopsis thaliana was found in the integration site of the insert DNA. Event-specific qualitative PCR methods were established, with one method producing a 105-bp product specific for the 5'-integration junction and the other method producing a 124-bp product specific for the 3'-junction. The absolute detection limits for the qualitative PCR were determined to be 100 initial template copies for the 5'-junction and ten for the 3'-junction. Quantitative methods were also developed that targeted both of the junction fragments. The limit of detection of the quantitative PCR analysis was ten initial template copies for either the 5'- or 3'-junction, while the limit of quantification was determined to be approximately 50 initial template copies. The real-time PCR systems so established were examined with two mixed rapeseed samples with known Oxy-235 contents and found to obtain the expected results.

  16. Compression Algorithm Analysis of In-Situ (S)TEM Video: Towards Automatic Event Detection and Characterization

    SciTech Connect

    Teuton, Jeremy R.; Griswold, Richard L.; Mehdi, Beata L.; Browning, Nigel D.

    2015-09-23

    Precise analysis of both (S)TEM images and video are time and labor intensive processes. As an example, determining when crystal growth and shrinkage occurs during the dynamic process of Li dendrite deposition and stripping involves manually scanning through each frame in the video to extract a specific set of frames/images. For large numbers of images, this process can be very time consuming, so a fast and accurate automated method is desirable. Given this need, we developed software that uses analysis of video compression statistics for detecting and characterizing events in large data sets. This software works by converting the data into a series of images which it compresses into an MPEG-2 video using the open source “avconv” utility [1]. The software does not use the video itself, but rather analyzes the video statistics from the first pass of the video encoding that avconv records in the log file. This file contains statistics for each frame of the video including the frame quality, intra-texture and predicted texture bits, forward and backward motion vector resolution, among others. In all, avconv records 15 statistics for each frame. By combining different statistics, we have been able to detect events in various types of data. We have developed an interactive tool for exploring the data and the statistics that aids the analyst in selecting useful statistics for each analysis. Going forward, an algorithm for detecting and possibly describing events automatically can be written based on statistic(s) for each data type.

  17. Systematic analysis of tropospheric NO2 long-range transport events detected in GOME-2 satellite data

    NASA Astrophysics Data System (ADS)

    Zien, A. W.; Richter, A.; Hilboll, A.; Blechschmidt, A.-M.; Burrows, J. P.

    2014-07-01

    Intercontinental long-range transport (LRT) events of NO2 relocate the effects of air pollution from emission regions to remote, pristine regions. We detect transported plumes in tropospheric NO2 columns measured by the GOME-2/MetOp-A instrument with a specialized algorithm and trace the plumes to their sources using the HYSPLIT Lagrangian transport model. With this algorithm we find 3808 LRT events over the ocean for the period 2007 to 2011. LRT events occur frequently in the mid-latitudes, emerging usually from coastal high-emission regions. In the free troposphere, plumes of NO2 can travel for several days to the polar oceanic atmosphere or to other continents. They travel along characteristic routes and originate from both continuous anthropogenic emission and emission events such as bush fires. Most NO2 LRT events occur during autumn and winter months, when meteorological conditions and emissions are most favorable. The evaluation of meteorological data shows that the observed NO2 LRT is often linked to cyclones passing over an emission region.

  18. Systematic analysis of tropospheric NO2 long-range transport events detected in GOME-2 satellite data

    NASA Astrophysics Data System (ADS)

    Zien, A. W.; Richter, A.; Hilboll, A.; Blechschmidt, A.-M.; Burrows, J. P.

    2013-11-01

    Intercontinental long-range transport (LRT) events of NO2 relocate the effects of air pollution from emission regions to remote, pristine regions. We detect transported plumes in tropospheric NO2 columns measured by the GOME-2/MetOp-A instrument with a specialized algorithm and trace the plumes to their sources using the HYSPLIT lagrangian transport model. With this algorithm we find 3808 LRT events over the ocean for the period 2007 to 2011. LRT events occur frequently in the mid-latitudes, emerging usually from coastal high-emission regions. In the free troposphere, plumes of NO2 can travel for several days to the polar oceanic atmosphere or to other continents. They travel along characteristic routes and originate from both continuous anthropogenic emission and emission events such as bush fires. Most NO2 LRT events occur during autumn and winter months, when meteorological conditions and emissions are most favorable. The evaluation of meteorological data shows that the observed NO2 LRT is often linked to cyclones passing over an emission region.

  19. Dune Detective, Using Ecological Studies to Reconstruct Events Which Shaped a Barrier Island.

    ERIC Educational Resources Information Center

    Godfrey, Paul J.; Hon, Will

    This publication is designed for use as part of a curriculum series developed by the Regional Marine Science Project. Students in grades 11 and 12 are exposed to research methods through a series of field exercises guiding investigators in reconstructing the events which have shaped the natural communities of a barrier beach. Background…

  20. A new PCR-CGE (size and color) method for simultaneous detection of genetically modified maize events.

    PubMed

    Nadal, Anna; Coll, Anna; La Paz, Jose-Luis; Esteve, Teresa; Pla, Maria

    2006-10-01

    We present a novel multiplex PCR assay for simultaneous detection of multiple transgenic events in maize. Initially, five PCR primers pairs specific to events Bt11, GA21, MON810, and NK603, and Zea mays L. (alcohol dehydrogenase) were included. The event specificity was based on amplification of transgene/plant genome flanking regions, i.e., the same targets as for validated real-time PCR assays. These short and similarly sized amplicons were selected to achieve high and similar amplification efficiency for all targets; however, its unambiguous identification was a technical challenge. We achieved a clear distinction by a novel CGE approach that combined the identification by size and color (CGE-SC). In one single step, all five targets were amplified and specifically labeled with three different fluorescent dyes. The assay was specific and displayed an LOD of 0.1% of each genetically modified organism (GMO). Therefore, it was adequate to fulfill legal thresholds established, e.g., in the European Union. Our CGE-SC based strategy in combination with an adequate labeling design has the potential to simultaneously detect higher numbers of targets. As an example, we present the detection of up to eight targets in a single run. Multiplex PCR-CGE-SC only requires a conventional sequencer device and enables automation and high throughput. In addition, it proved to be transferable to a different laboratory. The number of authorized GMO events is rapidly growing; and the acreage of genetically modified (GM) varieties cultivated and commercialized worldwide is rapidly increasing. In this context, our multiplex PCR-CGE-SC can be suitable for screening GM contents in food.

  1. A new PCR-CGE (size and color) method for simultaneous detection of genetically modified maize events.

    PubMed

    Nadal, Anna; Coll, Anna; La Paz, Jose-Luis; Esteve, Teresa; Pla, Maria

    2006-10-01

    We present a novel multiplex PCR assay for simultaneous detection of multiple transgenic events in maize. Initially, five PCR primers pairs specific to events Bt11, GA21, MON810, and NK603, and Zea mays L. (alcohol dehydrogenase) were included. The event specificity was based on amplification of transgene/plant genome flanking regions, i.e., the same targets as for validated real-time PCR assays. These short and similarly sized amplicons were selected to achieve high and similar amplification efficiency for all targets; however, its unambiguous identification was a technical challenge. We achieved a clear distinction by a novel CGE approach that combined the identification by size and color (CGE-SC). In one single step, all five targets were amplified and specifically labeled with three different fluorescent dyes. The assay was specific and displayed an LOD of 0.1% of each genetically modified organism (GMO). Therefore, it was adequate to fulfill legal thresholds established, e.g., in the European Union. Our CGE-SC based strategy in combination with an adequate labeling design has the potential to simultaneously detect higher numbers of targets. As an example, we present the detection of up to eight targets in a single run. Multiplex PCR-CGE-SC only requires a conventional sequencer device and enables automation and high throughput. In addition, it proved to be transferable to a different laboratory. The number of authorized GMO events is rapidly growing; and the acreage of genetically modified (GM) varieties cultivated and commercialized worldwide is rapidly increasing. In this context, our multiplex PCR-CGE-SC can be suitable for screening GM contents in food. PMID:16972302

  2. Data-Driven Multimodal Sleep Apnea Events Detection : Synchrosquezing Transform Processing and Riemannian Geometry Classification Approaches.

    PubMed

    Rutkowski, Tomasz M

    2016-07-01

    A novel multimodal and bio-inspired approach to biomedical signal processing and classification is presented in the paper. This approach allows for an automatic semantic labeling (interpretation) of sleep apnea events based the proposed data-driven biomedical signal processing and classification. The presented signal processing and classification methods have been already successfully applied to real-time unimodal brainwaves (EEG only) decoding in brain-computer interfaces developed by the author. In the current project the very encouraging results are obtained using multimodal biomedical (brainwaves and peripheral physiological) signals in a unified processing approach allowing for the automatic semantic data description. The results thus support a hypothesis of the data-driven and bio-inspired signal processing approach validity for medical data semantic interpretation based on the sleep apnea events machine-learning-related classification. PMID:27194241

  3. Detection and location of multiple events by MARS. Final report. [Multiple Arrival Recognition System

    SciTech Connect

    Wang, J.; Masso, J.F.; Archambeau, C.B.; Savino, J.M.

    1980-09-01

    Seismic data from two explosions was processed using the Systems Science and Software MARS (Multiple Arrival Recognition System) seismic event detector in an effort to determine their relative spatial and temporal separation on the basis of seismic data alone. The explosions were less than 1.0 kilometer apart and were separated by less than 0.5 sec in origin times. The seismic data consisted of nine local accelerograms (r < 1.0 km) and four regional (240 through 400 km) seismograms. The MARS processing clearly indicates the presence of multiple explosions, but the restricted frequency range of the data inhibits accurate time picks and hence limits the precision of the event location.

  4. Event detection and control co-design of sampled-data systems

    NASA Astrophysics Data System (ADS)

    Meng, Xiangyu; Chen, Tongwen

    2014-04-01

    This paper proposes event detector and controller co-design criteria for sampled-data systems in which static or dynamic output feedback controllers are used. The resulting criteria provide sufficient conditions to ensure the asymptotic stability of the closed-loop system with reduced communication rates among sensors, controllers, and actuators. The transmissions are mediated by event detectors at both sensor and controller nodes. For static output feedback control, the sufficient condition is given in terms of the feasibility of bilinear matrix inequalities (BMIs). The BMI feasibility problem is converted into a nonlinear optimisation problem involving linear matrix inequalities (LMIs), which is solved via the complementarity linearisation algorithm. For dynamic output feedback control, the sufficient condition is formulated into an LMI feasibility problem, which is readily solved with existing tools. Numerical examples are included to show the effectiveness of the proposed methods.

  5. Signature Based Detection of User Events for Post-mortem Forensic Analysis

    NASA Astrophysics Data System (ADS)

    James, Joshua Isaac; Gladyshev, Pavel; Zhu, Yuandong

    This paper introduces a novel approach to user event reconstruction by showing the practicality of generating and implementing signature-based analysis methods to reconstruct high-level user actions from a collection of low-level traces found during a post-mortem forensic analysis of a system. Traditional forensic analysis and the inferences an investigator normally makes when given digital evidence, are examined. It is then demonstrated that this natural process of inferring high-level events from low-level traces may be encoded using signature-matching techniques. Simple signatures using the defined method are created and applied for three popular Windows-based programs as a proof of concept.

  6. Detection of numerical chromosomal abnormalities (chr. 1 and 18) before and after photodynamic therapy of human bladder carcinoma cells in vitro

    NASA Astrophysics Data System (ADS)

    Bachor, Ruediger; Reich, Ella D.; Kleinschmidt, Klaus; Hautmann, Richard E.

    1997-12-01

    The application of nonradioactive in situ hybridization with chromosome-specific probes for cytogenetic analysis has increased significantly in recent years. In the field of photodynamic therapy (PDT) the hypothesis is that after PDT the remaining viable malignant cells are potentially metastatic cells. Therefore, we performed in vitro experiments on human bladder carcinoma cells to evaluate numerical chromosomal abnormalities before and after PDT. The possible genotoxic effect of PDT with porphycene (AamTPPn) appears to be small based on criteria such as numerical chromosomal abnormalities for chromosome 1 and 18.

  7. Detecting flood event trends assigned to changes in urbanisation levels using a bivariate copula model

    NASA Astrophysics Data System (ADS)

    Requena, Ana; Prosdocimi, Ilaria; Kjeldsen, Thomas R.; Mediero, Luis

    2014-05-01

    Flood frequency analyses based on stationary assumptions are usually employed for estimating design floods. However, more complex non-stationarity approaches are trying to be incorporated with the aim of improving such estimates. In this study, the effect of changing urbanisation on maximum flood peak (Q) and volume (V) series is analysed. The potential changes in an urbanised catchment and in a nearby hydrologically similar rural catchment in northwest England are investigated. The urbanised catchment is characterised by a noticeable increase of the urbanisation level in time, while the rural catchment has not been altered by anthropogenic actions. Winter, summer and annual maximum flood events are studied. With the aim of analysing changes in time, two non-superimposed time-windows are defined covering the periods 1976-1992 and 1993-2008, respectively. A preliminary analysis of temporal trends in Q, V and Kendall's tau is visually done, being formal tested by a resampling procedure. Differences were found among winter, summer and annual maximum flood events. As annual maximum flood events are commonly used for designing purposes, the corresponding bivariate distribution (margins and copula) was obtained for the different time-windows. Trends regarding both time-windows were analysed by comparing bivariate return period curves in the Q-V space. Different behaviours were found depending on the catchment. As a result, the application of the proposed methodology provides useful information in describing changes in flood events, regarding different flood variables and their relationship. In addition, the methodology can inform practitioners on the potential changes connected with urbanisation for appropriate design flood estimation.

  8. Vy-PER: eliminating false positive detection of virus integration events in next generation sequencing data.

    PubMed

    Forster, Michael; Szymczak, Silke; Ellinghaus, David; Hemmrich, Georg; Rühlemann, Malte; Kraemer, Lars; Mucha, Sören; Wienbrandt, Lars; Stanulla, Martin; Franke, Andre

    2015-01-01

    Several pathogenic viruses such as hepatitis B and human immunodeficiency viruses may integrate into the host genome. These virus/host integrations are detectable using paired-end next generation sequencing. However, the low number of expected true virus integrations may be difficult to distinguish from the noise of many false positive candidates. Here, we propose a novel filtering approach that increases specificity without compromising sensitivity for virus/host chimera detection. Our detection pipeline termed Vy-PER (Virus integration detection bY Paired End Reads) outperforms existing similar tools in speed and accuracy. We analysed whole genome data from childhood acute lymphoblastic leukemia (ALL), which is characterised by genomic rearrangements and usually associated with radiation exposure. This analysis was motivated by the recently reported virus integrations at genomic rearrangement sites and association with chromosomal instability in liver cancer. However, as expected, our analysis of 20 tumour and matched germline genomes from ALL patients finds no significant evidence for integrations by known viruses. Nevertheless, our method eliminates 12,800 false positives per genome (80× coverage) and only our method detects singleton human-phiX174-chimeras caused by optical errors of the Illumina HiSeq platform. This high accuracy is useful for detecting low virus integration levels as well as non-integrated viruses. PMID:26166306

  9. Vy-PER: eliminating false positive detection of virus integration events in next generation sequencing data.

    PubMed

    Forster, Michael; Szymczak, Silke; Ellinghaus, David; Hemmrich, Georg; Rühlemann, Malte; Kraemer, Lars; Mucha, Sören; Wienbrandt, Lars; Stanulla, Martin; Franke, Andre

    2015-07-13

    Several pathogenic viruses such as hepatitis B and human immunodeficiency viruses may integrate into the host genome. These virus/host integrations are detectable using paired-end next generation sequencing. However, the low number of expected true virus integrations may be difficult to distinguish from the noise of many false positive candidates. Here, we propose a novel filtering approach that increases specificity without compromising sensitivity for virus/host chimera detection. Our detection pipeline termed Vy-PER (Virus integration detection bY Paired End Reads) outperforms existing similar tools in speed and accuracy. We analysed whole genome data from childhood acute lymphoblastic leukemia (ALL), which is characterised by genomic rearrangements and usually associated with radiation exposure. This analysis was motivated by the recently reported virus integrations at genomic rearrangement sites and association with chromosomal instability in liver cancer. However, as expected, our analysis of 20 tumour and matched germline genomes from ALL patients finds no significant evidence for integrations by known viruses. Nevertheless, our method eliminates 12,800 false positives per genome (80× coverage) and only our method detects singleton human-phiX174-chimeras caused by optical errors of the Illumina HiSeq platform. This high accuracy is useful for detecting low virus integration levels as well as non-integrated viruses.

  10. Vy-PER: eliminating false positive detection of virus integration events in next generation sequencing data

    PubMed Central

    Forster, Michael; Szymczak, Silke; Ellinghaus, David; Hemmrich, Georg; Rühlemann, Malte; Kraemer, Lars; Mucha, Sören; Wienbrandt, Lars; Stanulla, Martin; Franke, Andre

    2015-01-01

    Several pathogenic viruses such as hepatitis B and human immunodeficiency viruses may integrate into the host genome. These virus/host integrations are detectable using paired-end next generation sequencing. However, the low number of expected true virus integrations may be difficult to distinguish from the noise of many false positive candidates. Here, we propose a novel filtering approach that increases specificity without compromising sensitivity for virus/host chimera detection. Our detection pipeline termed Vy-PER (Virus integration detection bY Paired End Reads) outperforms existing similar tools in speed and accuracy. We analysed whole genome data from childhood acute lymphoblastic leukemia (ALL), which is characterised by genomic rearrangements and usually associated with radiation exposure. This analysis was motivated by the recently reported virus integrations at genomic rearrangement sites and association with chromosomal instability in liver cancer. However, as expected, our analysis of 20 tumour and matched germline genomes from ALL patients finds no significant evidence for integrations by known viruses. Nevertheless, our method eliminates 12,800 false positives per genome (80× coverage) and only our method detects singleton human-phiX174-chimeras caused by optical errors of the Illumina HiSeq platform. This high accuracy is useful for detecting low virus integration levels as well as non-integrated viruses. PMID:26166306

  11. Enriched encoding: reward motivation organizes cortical networks for hippocampal detection of unexpected events.

    PubMed

    Murty, Vishnu P; Adcock, R Alison

    2014-08-01

    Learning how to obtain rewards requires learning about their contexts and likely causes. How do long-term memory mechanisms balance the need to represent potential determinants of reward outcomes with the computational burden of an over-inclusive memory? One solution would be to enhance memory for salient events that occur during reward anticipation, because all such events are potential determinants of reward. We tested whether reward motivation enhances encoding of salient events like expectancy violations. During functional magnetic resonance imaging, participants performed a reaction-time task in which goal-irrelevant expectancy violations were encountered during states of high- or low-reward motivation. Motivation amplified hippocampal activation to and declarative memory for expectancy violations. Connectivity of the ventral tegmental area (VTA) with medial prefrontal, ventrolateral prefrontal, and visual cortices preceded and predicted this increase in hippocampal sensitivity. These findings elucidate a novel mechanism whereby reward motivation can enhance hippocampus-dependent memory: anticipatory VTA-cortical-hippocampal interactions. Further, the findings integrate literatures on dopaminergic neuromodulation of prefrontal function and hippocampus-dependent memory. We conclude that during reward motivation, VTA modulation induces distributed neural changes that amplify hippocampal signals and records of expectancy violations to improve predictions-a potentially unique contribution of the hippocampus to reward learning.

  12. Invariance of exocytotic events detected by amperometry as a function of the carbon fiber microelectrode diameter.