Detection and avoidance of errors in computer software

NASA Technical Reports Server (NTRS)

Kinsler, Les

1989-01-01

The acceptance test errors of a computer software project to determine if the errors could be detected or avoided in earlier phases of development. GROAGSS (Gamma Ray Observatory Attitude Ground Support System) was selected as the software project to be examined. The development of the software followed the standard Flight Dynamics Software Development methods. GROAGSS was developed between August 1985 and April 1989. The project is approximately 250,000 lines of code of which approximately 43,000 lines are reused from previous projects. GROAGSS had a total of 1715 Change Report Forms (CRFs) submitted during the entire development and testing. These changes contained 936 errors. Of these 936 errors, 374 were found during the acceptance testing. These acceptance test errors were first categorized into methods of avoidance including: more clearly written requirements; detail review; code reading; structural unit testing; and functional system integration testing. The errors were later broken down in terms of effort to detect and correct, class of error, and probability that the prescribed detection method would be successful. These determinations were based on Software Engineering Laboratory (SEL) documents and interviews with the project programmers. A summary of the results of the categorizations is presented. The number of programming errors at the beginning of acceptance testing can be significantly reduced. The results of the existing development methodology are examined for ways of improvements. A basis is provided for the definition is a new development/testing paradigm. Monitoring of the new scheme will objectively determine its effectiveness on avoiding and detecting errors.

MPI Runtime Error Detection with MUST: Advances in Deadlock Detection

DOE PAGES

Hilbrich, Tobias; Protze, Joachim; Schulz, Martin; ...

2013-01-01

The widely used Message Passing Interface (MPI) is complex and rich. As a result, application developers require automated tools to avoid and to detect MPI programming errors. We present the Marmot Umpire Scalable Tool (MUST) that detects such errors with significantly increased scalability. We present improvements to our graph-based deadlock detection approach for MPI, which cover future MPI extensions. Our enhancements also check complex MPI constructs that no previous graph-based detection approach handled correctly. Finally, we present optimizations for the processing of MPI operations that reduce runtime deadlock detection overheads. Existing approaches often require ( p ) analysis time permore » MPI operation, for p processes. We empirically observe that our improvements lead to sub-linear or better analysis time per operation for a wide range of real world applications.« less

An advanced SEU tolerant latch based on error detection

NASA Astrophysics Data System (ADS)

Xu, Hui; Zhu, Jianwei; Lu, Xiaoping; Li, Jingzhao

2018-05-01

This paper proposes a latch that can mitigate SEUs via an error detection circuit. The error detection circuit is hardened by a C-element and a stacked PMOS. In the hold state, a particle strikes the latch or the error detection circuit may cause a fault logic state of the circuit. The error detection circuit can detect the upset node in the latch and the fault output will be corrected. The upset node in the error detection circuit can be corrected by the C-element. The power dissipation and propagation delay of the proposed latch are analyzed by HSPICE simulations. The proposed latch consumes about 77.5% less energy and 33.1% less propagation delay than the triple modular redundancy (TMR) latch. Simulation results demonstrate that the proposed latch can mitigate SEU effectively. Project supported by the National Natural Science Foundation of China (Nos. 61404001, 61306046), the Anhui Province University Natural Science Research Major Project (No. KJ2014ZD12), the Huainan Science and Technology Program (No. 2013A4011), and the National Natural Science Foundation of China (No. 61371025).

A Mechanism for Error Detection in Speeded Response Time Tasks

ERIC Educational Resources Information Center

Holroyd, Clay B.; Yeung, Nick; Coles, Michael G. H.; Cohen, Jonathan D.

2005-01-01

The concept of error detection plays a central role in theories of executive control. In this article, the authors present a mechanism that can rapidly detect errors in speeded response time tasks. This error monitor assigns values to the output of cognitive processes involved in stimulus categorization and response generation and detects errors…

Early math and reading achievement are associated with the error positivity.

PubMed

Kim, Matthew H; Grammer, Jennie K; Marulis, Loren M; Carrasco, Melisa; Morrison, Frederick J; Gehring, William J

2016-12-01

Executive functioning (EF) and motivation are associated with academic achievement and error-related ERPs. The present study explores whether early academic skills predict variability in the error-related negativity (ERN) and error positivity (Pe). Data from 113 three- to seven-year-old children in a Go/No-Go task revealed that stronger early reading and math skills predicted a larger Pe. Closer examination revealed that this relation was quadratic and significant for children performing at or near grade level, but not significant for above-average achievers. Early academics did not predict the ERN. These findings suggest that the Pe - which reflects individual differences in motivational processes as well as attention - may be associated with early academic achievement. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

The Watchdog Task: Concurrent error detection using assertions

NASA Technical Reports Server (NTRS)

Ersoz, A.; Andrews, D. M.; Mccluskey, E. J.

1985-01-01

The Watchdog Task, a software abstraction of the Watchdog-processor, is shown to be a powerful error detection tool with a great deal of flexibility and the advantages of watchdog techniques. A Watchdog Task system in Ada is presented; issues of recovery, latency, efficiency (communication) and preprocessing are discussed. Different applications, one of which is error detection on a single processor, are examined.

Sensitivity and accuracy of high-throughput metabarcoding methods for early detection of invasive fish species

EPA Science Inventory

For early detection biomonitoring of aquatic invasive species, sensitivity to rare individuals and accurate, high-resolution taxonomic classification are critical to minimize detection errors. Given the great expense and effort associated with morphological identification of many...

Automatic detection of MLC relative position errors for VMAT using the EPID-based picket fence test

NASA Astrophysics Data System (ADS)

Christophides, Damianos; Davies, Alex; Fleckney, Mark

2016-12-01

Multi-leaf collimators (MLCs) ensure the accurate delivery of treatments requiring complex beam fluences like intensity modulated radiotherapy and volumetric modulated arc therapy. The purpose of this work is to automate the detection of MLC relative position errors  ⩾0.5 mm using electronic portal imaging device-based picket fence tests and compare the results to the qualitative assessment currently in use. Picket fence tests with and without intentional MLC errors were measured weekly on three Varian linacs. The picket fence images analysed covered a time period ranging between 14-20 months depending on the linac. An algorithm was developed that calculated the MLC error for each leaf-pair present in the picket fence images. The baseline error distributions of each linac were characterised for an initial period of 6 months and compared with the intentional MLC errors using statistical metrics. The distributions of median and one-sample Kolmogorov-Smirnov test p-value exhibited no overlap between baseline and intentional errors and were used retrospectively to automatically detect MLC errors in routine clinical practice. Agreement was found between the MLC errors detected by the automatic method and the fault reports during clinical use, as well as interventions for MLC repair and calibration. In conclusion the method presented provides for full automation of MLC quality assurance, based on individual linac performance characteristics. The use of the automatic method has been shown to provide early warning for MLC errors that resulted in clinical downtime.

Simulating and Detecting Radiation-Induced Errors for Onboard Machine Learning

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; Bornstein, Benjamin; Granat, Robert; Tang, Benyang; Turmon, Michael

2009-01-01

Spacecraft processors and memory are subjected to high radiation doses and therefore employ radiation-hardened components. However, these components are orders of magnitude more expensive than typical desktop components, and they lag years behind in terms of speed and size. We have integrated algorithm-based fault tolerance (ABFT) methods into onboard data analysis algorithms to detect radiation-induced errors, which ultimately may permit the use of spacecraft memory that need not be fully hardened, reducing cost and increasing capability at the same time. We have also developed a lightweight software radiation simulator, BITFLIPS, that permits evaluation of error detection strategies in a controlled fashion, including the specification of the radiation rate and selective exposure of individual data structures. Using BITFLIPS, we evaluated our error detection methods when using a support vector machine to analyze data collected by the Mars Odyssey spacecraft. We found ABFT error detection for matrix multiplication is very successful, while error detection for Gaussian kernel computation still has room for improvement.

Insar Unwrapping Error Correction Based on Quasi-Accurate Detection of Gross Errors (quad)

NASA Astrophysics Data System (ADS)

Kang, Y.; Zhao, C. Y.; Zhang, Q.; Yang, C. S.

2018-04-01

Unwrapping error is a common error in the InSAR processing, which will seriously degrade the accuracy of the monitoring results. Based on a gross error correction method, Quasi-accurate detection (QUAD), the method for unwrapping errors automatic correction is established in this paper. This method identifies and corrects the unwrapping errors by establishing a functional model between the true errors and interferograms. The basic principle and processing steps are presented. Then this method is compared with the L1-norm method with simulated data. Results show that both methods can effectively suppress the unwrapping error when the ratio of the unwrapping errors is low, and the two methods can complement each other when the ratio of the unwrapping errors is relatively high. At last the real SAR data is tested for the phase unwrapping error correction. Results show that this new method can correct the phase unwrapping errors successfully in the practical application.

Prevention of medication errors: detection and audit.

PubMed

Montesi, Germana; Lechi, Alessandro

2009-06-01

1. Medication errors have important implications for patient safety, and their identification is a main target in improving clinical practice errors, in order to prevent adverse events. 2. Error detection is the first crucial step. Approaches to this are likely to be different in research and routine care, and the most suitable must be chosen according to the setting. 3. The major methods for detecting medication errors and associated adverse drug-related events are chart review, computerized monitoring, administrative databases, and claims data, using direct observation, incident reporting, and patient monitoring. All of these methods have both advantages and limitations. 4. Reporting discloses medication errors, can trigger warnings, and encourages the diffusion of a culture of safe practice. Combining and comparing data from various and encourages the diffusion of a culture of safe practice sources increases the reliability of the system. 5. Error prevention can be planned by means of retroactive and proactive tools, such as audit and Failure Mode, Effect, and Criticality Analysis (FMECA). Audit is also an educational activity, which promotes high-quality care; it should be carried out regularly. In an audit cycle we can compare what is actually done against reference standards and put in place corrective actions to improve the performances of individuals and systems. 6. Patient safety must be the first aim in every setting, in order to build safer systems, learning from errors and reducing the human and fiscal costs.

Predicted Errors In Children's Early Sentence Comprehension

PubMed Central

Gertner, Yael; Fisher, Cynthia

2012-01-01

Children use syntax to interpret sentences and learn verbs; this is syntactic bootstrapping. The structure-mapping account of early syntactic bootstrapping proposes that a partial representation of sentence structure, the set of nouns occurring with the verb, guides initial interpretation and provides an abstract format for new learning. This account predicts early successes, but also telltale errors: Toddlers should be unable to tell transitive sentences from other sentences containing two nouns. In testing this prediction, we capitalized on evidence that 21-month-olds use what they have learned about noun order in English sentences to understand new transitive verbs. In two experiments, 21-month-olds applied this noun-order knowledge to two-noun intransitive sentences, mistakenly assigning different interpretations to “The boy and the girl are gorping!” and “The girl and the boy are gorping!”. This suggests that toddlers exploit partial representations of sentence structure to guide sentence interpretation; these sparse representations are useful, but error-prone. PMID:22525312

Sensitivity in error detection of patient specific QA tools for IMRT plans

NASA Astrophysics Data System (ADS)

Lat, S. Z.; Suriyapee, S.; Sanghangthum, T.

2016-03-01

The high complexity of dose calculation in treatment planning and accurate delivery of IMRT plan need high precision of verification method. The purpose of this study is to investigate error detection capability of patient specific QA tools for IMRT plans. The two H&N and two prostate IMRT plans with MapCHECK2 and portal dosimetry QA tools were studied. Measurements were undertaken for original and modified plans with errors introduced. The intentional errors composed of prescribed dose (±2 to ±6%) and position shifting in X-axis and Y-axis (±1 to ±5mm). After measurement, gamma pass between original and modified plans were compared. The average gamma pass for original H&N and prostate plans were 98.3% and 100% for MapCHECK2 and 95.9% and 99.8% for portal dosimetry, respectively. In H&N plan, MapCHECK2 can detect position shift errors starting from 3mm while portal dosimetry can detect errors started from 2mm. Both devices showed similar sensitivity in detection of position shift error in prostate plan. For H&N plan, MapCHECK2 can detect dose errors starting at ±4%, whereas portal dosimetry can detect from ±2%. For prostate plan, both devices can identify dose errors starting from ±4%. Sensitivity of error detection depends on type of errors and plan complexity.

Computer-Assisted Detection of 90% of EFL Student Errors

ERIC Educational Resources Information Center

Harvey-Scholes, Calum

2018-01-01

Software can facilitate English as a Foreign Language (EFL) students' self-correction of their free-form writing by detecting errors; this article examines the proportion of errors which software can detect. A corpus of 13,644 words of written English was created, comprising 90 compositions written by Spanish-speaking students at levels A2-B2…

Error Detection and Correction in Spelling.

ERIC Educational Resources Information Center

Lydiatt, Steve

1984-01-01

Teachers can discover students' means of dealing with spelling as a problem through investigations of their error detection and correction skills. Approaches for measuring sensitivity and bias are described, as are means of developing appropriate instructional activities. (CL)

[Detection and classification of medication errors at Joan XXIII University Hospital].

PubMed

Jornet Montaña, S; Canadell Vilarrasa, L; Calabuig Mũoz, M; Riera Sendra, G; Vuelta Arce, M; Bardají Ruiz, A; Gallart Mora, M J

2004-01-01

Medication errors are multifactorial and multidisciplinary, and may originate in processes such as drug prescription, transcription, dispensation, preparation and administration. The goal of this work was to measure the incidence of detectable medication errors that arise within a unit dose drug distribution and control system, from drug prescription to drug administration, by means of an observational method confined to the Pharmacy Department, as well as a voluntary, anonymous report system. The acceptance of this voluntary report system's implementation was also assessed. A prospective descriptive study was conducted. Data collection was performed at the Pharmacy Department from a review of prescribed medical orders, a review of pharmaceutical transcriptions, a review of dispensed medication and a review of medication returned in unit dose medication carts. A voluntary, anonymous report system centralized in the Pharmacy Department was also set up to detect medication errors. Prescription errors were the most frequent (1.12%), closely followed by dispensation errors (1.04%). Transcription errors (0.42%) and administration errors (0.69%) had the lowest overall incidence. Voluntary report involved only 4.25% of all detected errors, whereas unit dose medication cart review contributed the most to error detection. Recognizing the incidence and types of medication errors that occur in a health-care setting allows us to analyze their causes and effect changes in different stages of the process in order to ensure maximal patient safety.

Patient identification errors: the detective in the laboratory.

PubMed

Salinas, Maria; López-Garrigós, Maite; Lillo, Rosa; Gutiérrez, Mercedes; Lugo, Javier; Leiva-Salinas, Carlos

2013-11-01

The eradication of errors regarding patients' identification is one of the main goals for safety improvement. As clinical laboratory intervenes in 70% of clinical decisions, laboratory safety is crucial in patient safety. We studied the number of Laboratory Information System (LIS) demographic data errors registered in our laboratory during one year. The laboratory attends a variety of inpatients and outpatients. The demographic data of outpatients is registered in the LIS, when they present to the laboratory front desk. The requests from the primary care centers (PCC) are made electronically by the general practitioner. A manual step is always done at the PCC to conciliate the patient identification number in the electronic request with the one in the LIS. Manual registration is done through hospital information system demographic data capture when patient's medical record number is registered in LIS. Laboratory report is always sent out electronically to the patient's electronic medical record. Daily, every demographic data in LIS is manually compared to the request form to detect potential errors. Fewer errors were committed when electronic order was used. There was great error variability between PCC when using the electronic order. LIS demographic data manual registration errors depended on patient origin and test requesting method. Even when using the electronic approach, errors were detected. There was a great variability between PCC even when using this electronic modality; this suggests that the number of errors is still dependent on the personnel in charge of the technology. © 2013.

Multi-bits error detection and fast recovery in RISC cores

NASA Astrophysics Data System (ADS)

Jing, Wang; Xing, Yang; Yuanfu, Zhao; Weigong, Zhang; Jiao, Shen; Keni, Qiu

2015-11-01

The particles-induced soft errors are a major threat to the reliability of microprocessors. Even worse, multi-bits upsets (MBUs) are ever-increased due to the rapidly shrinking feature size of the IC on a chip. Several architecture-level mechanisms have been proposed to protect microprocessors from soft errors, such as dual and triple modular redundancies (DMR and TMR). However, most of them are inefficient to combat the growing multi-bits errors or cannot well balance the critical paths delay, area and power penalty. This paper proposes a novel architecture, self-recovery dual-pipeline (SRDP), to effectively provide soft error detection and recovery with low cost for general RISC structures. We focus on the following three aspects. First, an advanced DMR pipeline is devised to detect soft error, especially MBU. Second, SEU/MBU errors can be located by enhancing self-checking logic into pipelines stage registers. Third, a recovery scheme is proposed with a recovery cost of 1 or 5 clock cycles. Our evaluation of a prototype implementation exhibits that the SRDP can successfully detect particle-induced soft errors up to 100% and recovery is nearly 95%, the other 5% will inter a specific trap.

Oral precancerous lesions: Problems of early detection and oral cancer prevention

NASA Astrophysics Data System (ADS)

Gileva, Olga S.; Libik, Tatiana V.; Danilov, Konstantin V.

2016-08-01

The study presents the results of the research in the structure, local and systemic risk factors, peculiarities of the clinical manifestation, and quality of primary diagnosis of precancerous oral mucosa lesions (OMLs). In the study a wide range of OMLs and high (25.4%) proportion of oral precancerous lesions (OPLs) in their structure was indicated. The high percentage of different diagnostic errors and the lack of oncological awareness of dental practitioners, as well as the sharp necessity of inclusion of precancer/cancer early detection techniques into their daily practice were noted. The effectiveness of chemilumenescence system of early OPLs and oral cancer detection was demonstrated, the prospects of infrared thermography as a diagnostic tool were also discussed.

Detection of Error Related Neuronal Responses Recorded by Electrocorticography in Humans during Continuous Movements

PubMed Central

Milekovic, Tomislav; Ball, Tonio; Schulze-Bonhage, Andreas; Aertsen, Ad; Mehring, Carsten

2013-01-01

Background Brain-machine interfaces (BMIs) can translate the neuronal activity underlying a user’s movement intention into movements of an artificial effector. In spite of continuous improvements, errors in movement decoding are still a major problem of current BMI systems. If the difference between the decoded and intended movements becomes noticeable, it may lead to an execution error. Outcome errors, where subjects fail to reach a certain movement goal, are also present during online BMI operation. Detecting such errors can be beneficial for BMI operation: (i) errors can be corrected online after being detected and (ii) adaptive BMI decoding algorithm can be updated to make fewer errors in the future. Methodology/Principal Findings Here, we show that error events can be detected from human electrocorticography (ECoG) during a continuous task with high precision, given a temporal tolerance of 300–400 milliseconds. We quantified the error detection accuracy and showed that, using only a small subset of 2×2 ECoG electrodes, 82% of detection information for outcome error and 74% of detection information for execution error available from all ECoG electrodes could be retained. Conclusions/Significance The error detection method presented here could be used to correct errors made during BMI operation or to adapt a BMI algorithm to make fewer errors in the future. Furthermore, our results indicate that smaller ECoG implant could be used for error detection. Reducing the size of an ECoG electrode implant used for BMI decoding and error detection could significantly reduce the medical risk of implantation. PMID:23383315

Activity Tracking for Pilot Error Detection from Flight Data

NASA Technical Reports Server (NTRS)

Callantine, Todd J.; Ashford, Rose (Technical Monitor)

2002-01-01

This report presents an application of activity tracking for pilot error detection from flight data, and describes issues surrounding such an application. It first describes the Crew Activity Tracking System (CATS), in-flight data collected from the NASA Langley Boeing 757 Airborne Research Integrated Experiment System aircraft, and a model of B757 flight crew activities. It then presents an example of CATS detecting actual in-flight crew errors.

Sensitivity and accuracy of DNA based methods used to describe aquatic communities for early detection of invasive fish species

EPA Science Inventory

For biomonitoring efforts aimed at early detection of aquatic invasive species (AIS), the ability to detect rare individuals is key and requires accurate species level identification to maintain a low occurrence probability of non-detection errors (failure to detect a present spe...

The Effect of Error Correction vs. Error Detection on Iranian Pre-Intermediate EFL Learners' Writing Achievement

ERIC Educational Resources Information Center

Abedi, Razie; Latifi, Mehdi; Moinzadeh, Ahmad

2010-01-01

This study tries to answer some ever-existent questions in writing fields regarding approaching the most effective ways to give feedback to students' errors in writing by comparing the effect of error correction and error detection on the improvement of students' writing ability. In order to achieve this goal, 60 pre-intermediate English learners…

Monitoring others' errors: The role of the motor system in early childhood and adulthood.

PubMed

Meyer, Marlene; Braukmann, Ricarda; Stapel, Janny C; Bekkering, Harold; Hunnius, Sabine

2016-03-01

Previous research demonstrates that from early in life, our cortical sensorimotor areas are activated both when performing and when observing actions (mirroring). Recent findings suggest that the adult motor system is also involved in detecting others' rule violations. Yet, how this translates to everyday action errors (e.g., accidentally dropping something) and how error-sensitive motor activity for others' actions emerges are still unknown. In this study, we examined the role of the motor system in error monitoring. Participants observed successful and unsuccessful pincer grasp actions while their electroencephalography was registered. We tested infants (8- and 14-month-olds) at different stages of learning the pincer grasp and adults as advanced graspers. Power in Alpha- and Beta-frequencies was analysed to assess motor and visual processing. Adults showed enhanced motor activity when observing erroneous actions. However, neither 8- nor 14-month-olds displayed this error sensitivity, despite showing motor activity for both actions. All groups did show similar visual activity, that is more Alpha-suppression, when observing correct actions. Thus, while correct and erroneous actions were processed as visually distinct in all age groups, only the adults' motor system was sensitive to action correctness. Functionality of different brain oscillations in the development of error monitoring and mirroring is discussed. © 2015 The British Psychological Society.

Local concurrent error detection and correction in data structures using virtual backpointers

NASA Technical Reports Server (NTRS)

Li, C. C.; Chen, P. P.; Fuchs, W. K.

1987-01-01

A new technique, based on virtual backpointers, for local concurrent error detection and correction in linked data structures is presented. Two new data structures, the Virtual Double Linked List, and the B-tree with Virtual Backpointers, are described. For these structures, double errors can be detected in 0(1) time and errors detected during forward moves can be corrected in 0(1) time. The application of a concurrent auditor process to data structure error detection and correction is analyzed, and an implementation is described, to determine the effect on mean time to failure of a multi-user shared database system. The implementation utilizes a Sequent shared memory multiprocessor system operating on a shared databased of Virtual Double Linked Lists.

Local concurrent error detection and correction in data structures using virtual backpointers

NASA Technical Reports Server (NTRS)

Li, Chung-Chi Jim; Chen, Paul Peichuan; Fuchs, W. Kent

1989-01-01

A new technique, based on virtual backpointers, for local concurrent error detection and correction in linked data strutures is presented. Two new data structures, the Virtual Double Linked List, and the B-tree with Virtual Backpointers, are described. For these structures, double errors can be detected in 0(1) time and errors detected during forward moves can be corrected in 0(1) time. The application of a concurrent auditor process to data structure error detection and correction is analyzed, and an implementation is described, to determine the effect on mean time to failure of a multi-user shared database system. The implementation utilizes a Sequent shared memory multiprocessor system operating on a shared database of Virtual Double Linked Lists.

Local concurrent error detection and correction in data structures using virtual backpointers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, C.C.J.; Chen, P.P.; Fuchs, W.K.

1989-11-01

A new technique, based on virtual backpointers, is presented in this paper for local concurrent error detection and correction in linked data structures. Two new data structures utilizing virtual backpointers, the Virtual Double-Linked List and the B-Tree and Virtual Backpointers, are described. For these structures, double errors within a fixed-size checking window can be detected in constant time and single errors detected during forward moves can be corrected in constant time.

Error Detection Processes during Observational Learning

ERIC Educational Resources Information Center

Badets, Arnaud; Blandin, Yannick; Wright, David L.; Shea, Charles H.

2006-01-01

The purpose of this experiment was to determine whether a faded knowledge of results (KR) frequency during observation of a model's performance enhanced error detection capabilities. During the observation phase, participants observed a model performing a timing task and received KR about the model's performance on each trial or on one of two…

Coherent detection of position errors in inter-satellite laser communications

NASA Astrophysics Data System (ADS)

Xu, Nan; Liu, Liren; Liu, De'an; Sun, Jianfeng; Luan, Zhu

2007-09-01

Due to the improved receiver sensitivity and wavelength selectivity, coherent detection became an attractive alternative to direct detection in inter-satellite laser communications. A novel method to coherent detection of position errors information is proposed. Coherent communication system generally consists of receive telescope, local oscillator, optical hybrid, photoelectric detector and optical phase lock loop (OPLL). Based on the system composing, this method adds CCD and computer as position error detector. CCD captures interference pattern while detection of transmission data from the transmitter laser. After processed and analyzed by computer, target position information is obtained from characteristic parameter of the interference pattern. The position errors as the control signal of PAT subsystem drive the receiver telescope to keep tracking to the target. Theoretical deviation and analysis is presented. The application extends to coherent laser rang finder, in which object distance and position information can be obtained simultaneously.

Decoding of DBEC-TBED Reed-Solomon codes. [Double-Byte-Error-Correcting, Triple-Byte-Error-Detecting

NASA Technical Reports Server (NTRS)

Deng, Robert H.; Costello, Daniel J., Jr.

1987-01-01

A problem in designing semiconductor memories is to provide some measure of error control without requiring excessive coding overhead or decoding time. In LSI and VLSI technology, memories are often organized on a multiple bit (or byte) per chip basis. For example, some 256 K bit DRAM's are organized in 32 K x 8 bit-bytes. Byte-oriented codes such as Reed-Solomon (RS) codes can provide efficient low overhead error control for such memories. However, the standard iterative algorithm for decoding RS codes is too slow for these applications. The paper presents a special decoding technique for double-byte-error-correcting, triple-byte-error-detecting RS codes which is capable of high-speed operation. This technique is designed to find the error locations and the error values directly from the syndrome without having to use the iterative algorithm to find the error locator polynomial.

Detecting and correcting hard errors in a memory array

DOEpatents

Kalamatianos, John; John, Johnsy Kanjirapallil; Gelinas, Robert; Sridharan, Vilas K.; Nevius, Phillip E.

2015-11-19

Hard errors in the memory array can be detected and corrected in real-time using reusable entries in an error status buffer. Data may be rewritten to a portion of a memory array and a register in response to a first error in data read from the portion of the memory array. The rewritten data may then be written from the register to an entry of an error status buffer in response to the rewritten data read from the register differing from the rewritten data read from the portion of the memory array.

Error-Detecting Identification Codes for Algebra Students.

ERIC Educational Resources Information Center

Sutherland, David C.

1990-01-01

Discusses common error-detecting identification codes using linear algebra terminology to provide an interesting application of algebra. Presents examples from the International Standard Book Number, the Universal Product Code, bank identification numbers, and the ZIP code bar code. (YP)

Is comprehension necessary for error detection? A conflict-based account of monitoring in speech production

PubMed Central

Nozari, Nazbanou; Dell, Gary S.; Schwartz, Myrna F.

2011-01-01

Despite the existence of speech errors, verbal communication is successful because speakers can detect (and correct) their errors. The standard theory of speech-error detection, the perceptual-loop account, posits that the comprehension system monitors production output for errors. Such a comprehension-based monitor, however, cannot explain the double dissociation between comprehension and error-detection ability observed in the aphasic patients. We propose a new theory of speech-error detection which is instead based on the production process itself. The theory borrows from studies of forced-choice-response tasks the notion that error detection is accomplished by monitoring response conflict via a frontal brain structure, such as the anterior cingulate cortex. We adapt this idea to the two-step model of word production, and test the model-derived predictions on a sample of aphasic patients. Our results show a strong correlation between patients’ error-detection ability and the model’s characterization of their production skills, and no significant correlation between error detection and comprehension measures, thus supporting a production-based monitor, generally, and the implemented conflict-based monitor in particular. The successful application of the conflict-based theory to error-detection in linguistic, as well as non-linguistic domains points to a domain-general monitoring system. PMID:21652015

Effects of Contextual Sight-Singing and Aural Skills Training on Error-Detection Abilities.

ERIC Educational Resources Information Center

Sheldon, Deborah A.

1998-01-01

Examines the effects of contextual sight-singing and ear training on pitch and rhythm error detection abilities among undergraduate instrumental music education majors. Shows that additional training produced better error detection, particularly with rhythm errors and in one-part examples. Maintains that differences attributable to texture were…

Bayesian network models for error detection in radiotherapy plans

NASA Astrophysics Data System (ADS)

Kalet, Alan M.; Gennari, John H.; Ford, Eric C.; Phillips, Mark H.

2015-04-01

The purpose of this study is to design and develop a probabilistic network for detecting errors in radiotherapy plans for use at the time of initial plan verification. Our group has initiated a multi-pronged approach to reduce these errors. We report on our development of Bayesian models of radiotherapy plans. Bayesian networks consist of joint probability distributions that define the probability of one event, given some set of other known information. Using the networks, we find the probability of obtaining certain radiotherapy parameters, given a set of initial clinical information. A low probability in a propagated network then corresponds to potential errors to be flagged for investigation. To build our networks we first interviewed medical physicists and other domain experts to identify the relevant radiotherapy concepts and their associated interdependencies and to construct a network topology. Next, to populate the network’s conditional probability tables, we used the Hugin Expert software to learn parameter distributions from a subset of de-identified data derived from a radiation oncology based clinical information database system. These data represent 4990 unique prescription cases over a 5 year period. Under test case scenarios with approximately 1.5% introduced error rates, network performance produced areas under the ROC curve of 0.88, 0.98, and 0.89 for the lung, brain and female breast cancer error detection networks, respectively. Comparison of the brain network to human experts performance (AUC of 0.90 ± 0.01) shows the Bayes network model performs better than domain experts under the same test conditions. Our results demonstrate the feasibility and effectiveness of comprehensive probabilistic models as part of decision support systems for improved detection of errors in initial radiotherapy plan verification procedures.

A Review of Research on Error Detection. Technical Report No. 540.

ERIC Educational Resources Information Center

Meyer, Linda A.

A review was conducted of the research on error detection studies completed with children, adolescents, and young adults to determine at what age children begin to detect errors in texts. The studies were grouped according to the subjects' ages. The focus of the review was on the following aspects of each study: the hypothesis that guided the…

Sensitivity and accuracy of high-throughput metabarcoding methods used to describe aquatic communities for early detection of invasve fish species

EPA Science Inventory

For early detection biomonitoring of aquatic invasive species, sensitivity to rare individuals and accurate, high-resolution taxonomic classification are critical to minimize Type I and II detection errors. Given the great expense and effort associated with morphological identifi...

Efficient detection of dangling pointer error for C/C++ programs

NASA Astrophysics Data System (ADS)

Zhang, Wenzhe

2017-08-01

Dangling pointer error is pervasive in C/C++ programs and it is very hard to detect. This paper introduces an efficient detector to detect dangling pointer error in C/C++ programs. By selectively leave some memory accesses unmonitored, our method could reduce the memory monitoring overhead and thus achieves better performance over previous methods. Experiments show that our method could achieve an average speed up of 9% over previous compiler instrumentation based method and more than 50% over previous page protection based method.

Crowdsourcing for error detection in cortical surface delineations.

PubMed

Ganz, Melanie; Kondermann, Daniel; Andrulis, Jonas; Knudsen, Gitte Moos; Maier-Hein, Lena

2017-01-01

With the recent trend toward big data analysis, neuroimaging datasets have grown substantially in the past years. While larger datasets potentially offer important insights for medical research, one major bottleneck is the requirement for resources of medical experts needed to validate automatic processing results. To address this issue, the goal of this paper was to assess whether anonymous nonexperts from an online community can perform quality control of MR-based cortical surface delineations derived by an automatic algorithm. So-called knowledge workers from an online crowdsourcing platform were asked to annotate errors in automatic cortical surface delineations on 100 central, coronal slices of MR images. On average, annotations for 100 images were obtained in less than an hour. When using expert annotations as reference, the crowd on average achieves a sensitivity of 82 % and a precision of 42 %. Merging multiple annotations per image significantly improves the sensitivity of the crowd (up to 95 %), but leads to a decrease in precision (as low as 22 %). Our experiments show that the detection of errors in automatic cortical surface delineations generated by anonymous untrained workers is feasible. Future work will focus on increasing the sensitivity of our method further, such that the error detection tasks can be handled exclusively by the crowd and expert resources can be focused on error correction.

Demonstration of a quantum error detection code using a square lattice of four superconducting qubits.

PubMed

Córcoles, A D; Magesan, Easwar; Srinivasan, Srikanth J; Cross, Andrew W; Steffen, M; Gambetta, Jay M; Chow, Jerry M

2015-04-29

The ability to detect and deal with errors when manipulating quantum systems is a fundamental requirement for fault-tolerant quantum computing. Unlike classical bits that are subject to only digital bit-flip errors, quantum bits are susceptible to a much larger spectrum of errors, for which any complete quantum error-correcting code must account. Whilst classical bit-flip detection can be realized via a linear array of qubits, a general fault-tolerant quantum error-correcting code requires extending into a higher-dimensional lattice. Here we present a quantum error detection protocol on a two-by-two planar lattice of superconducting qubits. The protocol detects an arbitrary quantum error on an encoded two-qubit entangled state via quantum non-demolition parity measurements on another pair of error syndrome qubits. This result represents a building block towards larger lattices amenable to fault-tolerant quantum error correction architectures such as the surface code.

Error-related brain activity and error awareness in an error classification paradigm.

PubMed

Di Gregorio, Francesco; Steinhauser, Marco; Maier, Martin E

2016-10-01

Error-related brain activity has been linked to error detection enabling adaptive behavioral adjustments. However, it is still unclear which role error awareness plays in this process. Here, we show that the error-related negativity (Ne/ERN), an event-related potential reflecting early error monitoring, is dissociable from the degree of error awareness. Participants responded to a target while ignoring two different incongruent distractors. After responding, they indicated whether they had committed an error, and if so, whether they had responded to one or to the other distractor. This error classification paradigm allowed distinguishing partially aware errors, (i.e., errors that were noticed but misclassified) and fully aware errors (i.e., errors that were correctly classified). The Ne/ERN was larger for partially aware errors than for fully aware errors. Whereas this speaks against the idea that the Ne/ERN foreshadows the degree of error awareness, it confirms the prediction of a computational model, which relates the Ne/ERN to post-response conflict. This model predicts that stronger distractor processing - a prerequisite of error classification in our paradigm - leads to lower post-response conflict and thus a smaller Ne/ERN. This implies that the relationship between Ne/ERN and error awareness depends on how error awareness is related to response conflict in a specific task. Our results further indicate that the Ne/ERN but not the degree of error awareness determines adaptive performance adjustments. Taken together, we conclude that the Ne/ERN is dissociable from error awareness and foreshadows adaptive performance adjustments. Our results suggest that the relationship between the Ne/ERN and error awareness is correlative and mediated by response conflict. Copyright © 2016 Elsevier Inc. All rights reserved.

Demonstration of a quantum error detection code using a square lattice of four superconducting qubits

PubMed Central

Córcoles, A.D.; Magesan, Easwar; Srinivasan, Srikanth J.; Cross, Andrew W.; Steffen, M.; Gambetta, Jay M.; Chow, Jerry M.

2015-01-01

The ability to detect and deal with errors when manipulating quantum systems is a fundamental requirement for fault-tolerant quantum computing. Unlike classical bits that are subject to only digital bit-flip errors, quantum bits are susceptible to a much larger spectrum of errors, for which any complete quantum error-correcting code must account. Whilst classical bit-flip detection can be realized via a linear array of qubits, a general fault-tolerant quantum error-correcting code requires extending into a higher-dimensional lattice. Here we present a quantum error detection protocol on a two-by-two planar lattice of superconducting qubits. The protocol detects an arbitrary quantum error on an encoded two-qubit entangled state via quantum non-demolition parity measurements on another pair of error syndrome qubits. This result represents a building block towards larger lattices amenable to fault-tolerant quantum error correction architectures such as the surface code. PMID:25923200

Monitoring robot actions for error detection and recovery

NASA Technical Reports Server (NTRS)

Gini, M.; Smith, R.

1987-01-01

Reliability is a serious problem in computer controlled robot systems. Although robots serve successfully in relatively simple applications such as painting and spot welding, their potential in areas such as automated assembly is hampered by programming problems. A program for assembling parts may be logically correct, execute correctly on a simulator, and even execute correctly on a robot most of the time, yet still fail unexpectedly in the face of real world uncertainties. Recovery from such errors is far more complicated than recovery from simple controller errors, since even expected errors can often manifest themselves in unexpected ways. Here, a novel approach is presented for improving robot reliability. Instead of anticipating errors, researchers use knowledge-based programming techniques so that the robot can autonomously exploit knowledge about its task and environment to detect and recover from failures. They describe preliminary experiment of a system that they designed and constructed.

Dynamic linear models using the Kalman filter for early detection and early warning of malaria outbreaks

NASA Astrophysics Data System (ADS)

Merkord, C. L.; Liu, Y.; DeVos, M.; Wimberly, M. C.

2015-12-01

Malaria early detection and early warning systems are important tools for public health decision makers in regions where malaria transmission is seasonal and varies from year to year with fluctuations in rainfall and temperature. Here we present a new data-driven dynamic linear model based on the Kalman filter with time-varying coefficients that are used to identify malaria outbreaks as they occur (early detection) and predict the location and timing of future outbreaks (early warning). We fit linear models of malaria incidence with trend and Fourier form seasonal components using three years of weekly malaria case data from 30 districts in the Amhara Region of Ethiopia. We identified past outbreaks by comparing the modeled prediction envelopes with observed case data. Preliminary results demonstrated the potential for improved accuracy and timeliness over commonly-used methods in which thresholds are based on simpler summary statistics of historical data. Other benefits of the dynamic linear modeling approach include robustness to missing data and the ability to fit models with relatively few years of training data. To predict future outbreaks, we started with the early detection model for each district and added a regression component based on satellite-derived environmental predictor variables including precipitation data from the Tropical Rainfall Measuring Mission (TRMM) and land surface temperature (LST) and spectral indices from the Moderate Resolution Imaging Spectroradiometer (MODIS). We included lagged environmental predictors in the regression component of the model, with lags chosen based on cross-correlation of the one-step-ahead forecast errors from the first model. Our results suggest that predictions of future malaria outbreaks can be improved by incorporating lagged environmental predictors.

Methods and apparatus using commutative error detection values for fault isolation in multiple node computers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Almasi, Gheorghe; Blumrich, Matthias Augustin; Chen, Dong

Methods and apparatus perform fault isolation in multiple node computing systems using commutative error detection values for--example, checksums--to identify and to isolate faulty nodes. When information associated with a reproducible portion of a computer program is injected into a network by a node, a commutative error detection value is calculated. At intervals, node fault detection apparatus associated with the multiple node computer system retrieve commutative error detection values associated with the node and stores them in memory. When the computer program is executed again by the multiple node computer system, new commutative error detection values are created and stored inmore » memory. The node fault detection apparatus identifies faulty nodes by comparing commutative error detection values associated with reproducible portions of the application program generated by a particular node from different runs of the application program. Differences in values indicate a possible faulty node.« less

Improvement of the Error-detection Mechanism in Adults with Dyslexia Following Reading Acceleration Training.

PubMed

Horowitz-Kraus, Tzipi

2016-05-01

The error-detection mechanism aids in preventing error repetition during a given task. Electroencephalography demonstrates that error detection involves two event-related potential components: error-related and correct-response negativities (ERN and CRN, respectively). Dyslexia is characterized by slow, inaccurate reading. In particular, individuals with dyslexia have a less active error-detection mechanism during reading than typical readers. In the current study, we examined whether a reading training programme could improve the ability to recognize words automatically (lexical representations) in adults with dyslexia, thereby resulting in more efficient error detection during reading. Behavioural and electrophysiological measures were obtained using a lexical decision task before and after participants trained with the reading acceleration programme. ERN amplitudes were smaller in individuals with dyslexia than in typical readers before training but increased following training, as did behavioural reading scores. Differences between the pre-training and post-training ERN and CRN components were larger in individuals with dyslexia than in typical readers. Also, the error-detection mechanism as represented by the ERN/CRN complex might serve as a biomarker for dyslexia and be used to evaluate the effectiveness of reading intervention programmes. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Is Comprehension Necessary for Error Detection? A Conflict-Based Account of Monitoring in Speech Production

ERIC Educational Resources Information Center

Nozari, Nazbanou; Dell, Gary S.; Schwartz, Myrna F.

2011-01-01

Despite the existence of speech errors, verbal communication is successful because speakers can detect (and correct) their errors. The standard theory of speech-error detection, the perceptual-loop account, posits that the comprehension system monitors production output for errors. Such a comprehension-based monitor, however, cannot explain the…

Double ErrP Detection for Automatic Error Correction in an ERP-Based BCI Speller.

PubMed

Cruz, Aniana; Pires, Gabriel; Nunes, Urbano J

2018-01-01

Brain-computer interface (BCI) is a useful device for people with severe motor disabilities. However, due to its low speed and low reliability, BCI still has a very limited application in daily real-world tasks. This paper proposes a P300-based BCI speller combined with a double error-related potential (ErrP) detection to automatically correct erroneous decisions. This novel approach introduces a second error detection to infer whether wrong automatic correction also elicits a second ErrP. Thus, two single-trial responses, instead of one, contribute to the final selection, improving the reliability of error detection. Moreover, to increase error detection, the evoked potential detected as target by the P300 classifier is combined with the evoked error potential at a feature-level. Discriminable error and positive potentials (response to correct feedback) were clearly identified. The proposed approach was tested on nine healthy participants and one tetraplegic participant. The online average accuracy for the first and second ErrPs were 88.4% and 84.8%, respectively. With automatic correction, we achieved an improvement around 5% achieving 89.9% in spelling accuracy for an effective 2.92 symbols/min. The proposed approach revealed that double ErrP detection can improve the reliability and speed of BCI systems.

Increased error-related thalamic activity during early compared to late cocaine abstinence.

PubMed

Li, Chiang-Shan R; Luo, Xi; Sinha, Rajita; Rounsaville, Bruce J; Carroll, Kathleen M; Malison, Robert T; Ding, Yu-Shin; Zhang, Sheng; Ide, Jaime S

2010-06-01

Altered cognitive control is implicated in the shaping of cocaine dependence. One of the key component processes of cognitive control is error monitoring. Our previous imaging work highlighted greater activity in distinct cortical and subcortical regions including the dorsal anterior cingulate cortex (dACC), thalamus and insula when participants committed an error during the stop signal task (Li et al., 2008b). Importantly, dACC, thalamic and insular activity has been associated with drug craving. One hypothesis is that the intense interoceptive activity during craving prevents these cerebral structures from adequately registering error and/or monitoring performance. Alternatively, the dACC, thalamus and insula show abnormally heightened responses to performance errors, suggesting that excessive responses to salient stimuli such as drug cues could precipitate craving. The two hypotheses would each predict decreased and increased activity during stop error (SE) as compared to stop success (SS) trials in the SST. Here we showed that cocaine dependent patients (PCD) experienced greater subjective feeling of loss of control and cocaine craving during early (average of day 6) compared to late (average of day 18) abstinence. Furthermore, compared to PCD during late abstinence, PCD scanned during early abstinence showed increased thalamic as well as insular but not dACC responses to errors (SE>SS). These findings support the hypothesis that heightened thalamic reactivity to salient stimuli co-occur with cocaine craving and loss of self control. Copyright (c) 2010 Elsevier Ireland Ltd. All rights reserved.

Early Detection of Sporadic Pancreatic Cancer

PubMed Central

Chari, Suresh T.; Kelly, Kimberly; Hollingsworth, Michael A.; Thayer, Sarah P.; Ahlquist, David A.; Andersen, Dana K.; Batra, Surinder K.; Brentnall, Teresa A.; Canto, Marcia; Cleeter, Deborah F.; Firpo, Matthew A.; Gambhir, Sanjiv Sam; Go, Vay Liang W.; Hines, O. Joe; Kenner, Barbara J.; Klimstra, David S.; Lerch, Markus M.; Levy, Michael J.; Maitra, Anirban; Mulvihill, Sean J.; Petersen, Gloria M.; Rhim, Andrew D.; Simeone, Diane M.; Srivastava, Sudhir; Tanaka, Masao; Vinik, Aaron I.; Wong, David

2015-01-01

Abstract Pancreatic cancer (PC) is estimated to become the second leading cause of cancer death in the United States by 2020. Early detection is the key to improving survival in PC. Addressing this urgent need, the Kenner Family Research Fund conducted the inaugural Early Detection of Sporadic Pancreatic Cancer Summit Conference in 2014 in conjunction with the 45th Anniversary Meeting of the American Pancreatic Association and Japan Pancreas Society. This seminal convening of international representatives from science, practice, and clinical research was designed to facilitate challenging interdisciplinary conversations to generate innovative ideas leading to the creation of a defined collaborative strategic pathway for the future of the field. An in-depth summary of current efforts in the field, analysis of gaps in specific areas of expertise, and challenges that exist in early detection is presented within distinct areas of inquiry: Case for Early Detection: Definitions, Detection, Survival, and Challenges; Biomarkers for Early Detection; Imaging; and Collaborative Studies. In addition, an overview of efforts in familial PC is presented in an addendum to this article. It is clear from the summit deliberations that only strategically designed collaboration among investigators, institutions, and funders will lead to significant progress in early detection of sporadic PC. PMID:25931254

Errors detected in pediatric oral liquid medication doses prepared in an automated workflow management system.

PubMed

Bledsoe, Sarah; Van Buskirk, Alex; Falconer, R James; Hollon, Andrew; Hoebing, Wendy; Jokic, Sladan

2018-02-01

The effectiveness of barcode-assisted medication preparation (BCMP) technology on detecting oral liquid dose preparation errors. From June 1, 2013, through May 31, 2014, a total of 178,344 oral doses were processed at Children's Mercy, a 301-bed pediatric hospital, through an automated workflow management system. Doses containing errors detected by the system's barcode scanning system or classified as rejected by the pharmacist were further reviewed. Errors intercepted by the barcode-scanning system were classified as (1) expired product, (2) incorrect drug, (3) incorrect concentration, and (4) technological error. Pharmacist-rejected doses were categorized into 6 categories based on the root cause of the preparation error: (1) expired product, (2) incorrect concentration, (3) incorrect drug, (4) incorrect volume, (5) preparation error, and (6) other. Of the 178,344 doses examined, 3,812 (2.1%) errors were detected by either the barcode-assisted scanning system (1.8%, n = 3,291) or a pharmacist (0.3%, n = 521). The 3,291 errors prevented by the barcode-assisted system were classified most commonly as technological error and incorrect drug, followed by incorrect concentration and expired product. Errors detected by pharmacists were also analyzed. These 521 errors were most often classified as incorrect volume, preparation error, expired product, other, incorrect drug, and incorrect concentration. BCMP technology detected errors in 1.8% of pediatric oral liquid medication doses prepared in an automated workflow management system, with errors being most commonly attributed to technological problems or incorrect drugs. Pharmacists rejected an additional 0.3% of studied doses. Copyright © 2018 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

Improved Conflict Detection for Reducing Operational Errors in Air Traffic Control

NASA Technical Reports Server (NTRS)

Paielli, Russell A.; Erzberger, Hainz

2003-01-01

An operational error is an incident in which an air traffic controller allows the separation between two aircraft to fall below the minimum separation standard. The rates of such errors in the US have increased significantly over the past few years. This paper proposes new detection methods that can help correct this trend by improving on the performance of Conflict Alert, the existing software in the Host Computer System that is intended to detect and warn controllers of imminent conflicts. In addition to the usual trajectory based on the flight plan, a "dead-reckoning" trajectory (current velocity projection) is also generated for each aircraft and checked for conflicts. Filters for reducing common types of false alerts were implemented. The new detection methods were tested in three different ways. First, a simple flightpath command language was developed t o generate precisely controlled encounters for the purpose of testing the detection software. Second, written reports and tracking data were obtained for actual operational errors that occurred in the field, and these were "replayed" to test the new detection algorithms. Finally, the detection methods were used to shadow live traffic, and performance was analysed, particularly with regard to the false-alert rate. The results indicate that the new detection methods can provide timely warnings of imminent conflicts more consistently than Conflict Alert.

Detection of other inborn errors of metabolism in hyperphenylalaninemic babies picked up on narrow-spectrum screening programs.

PubMed

Unal, Ozlem; Oztürk-Hişmi, Burcu; Coşkun, Turgay; Tokatlı, Ayşegül; Dursun, Ali; Sivri, Hatice Serap

2012-01-01

In many countries, neonatal screening programs have been unable to expand and have been limited to a few diseases. We highlight herein the opportunity available for the early detection of some inborn errors of metabolism (IEMs) in those countries in which newborn screening programs are limited. All the newborns that are referred to us for hyperphenylalaninemia are examined physically and their blood samples are checked by both high-performance liquid chromatography (HPLC) for blood phenylalanine levels and by amino acid analyzer for the measurement of blood amino acid concentrations. Seven patients who had been referred to our unit for hyperphenylalaninemia were eventually diagnosed with another IEM. A careful physical examination of the babies sent for positive screening test result combined with the utilization of low expense screening techniques at the experienced referring centers might facilitate otherwise missed opportunities for the early detection of some IEMs.

Error detection and correction unit with built-in self-test capability for spacecraft applications

NASA Technical Reports Server (NTRS)

Timoc, Constantin

1990-01-01

The objective of this project was to research and develop a 32-bit single chip Error Detection and Correction unit capable of correcting all single bit errors and detecting all double bit errors in the memory systems of a spacecraft. We designed the 32-bit EDAC (Error Detection and Correction unit) based on a modified Hamming code and according to the design specifications and performance requirements. We constructed a laboratory prototype (breadboard) which was converted into a fault simulator. The correctness of the design was verified on the breadboard using an exhaustive set of test cases. A logic diagram of the EDAC was delivered to JPL Section 514 on 4 Oct. 1988.

Method and apparatus for detecting timing errors in a system oscillator

DOEpatents

Gliebe, Ronald J.; Kramer, William R.

1993-01-01

A method of detecting timing errors in a system oscillator for an electronic device, such as a power supply, includes the step of comparing a system oscillator signal with a delayed generated signal and generating a signal representative of the timing error when the system oscillator signal is not identical to the delayed signal. An LED indicates to an operator that a timing error has occurred. A hardware circuit implements the above-identified method.

IMRT QA: Selecting gamma criteria based on error detection sensitivity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steers, Jennifer M.; Fraass, Benedick A., E-mail: benedick.fraass@cshs.org

Purpose: The gamma comparison is widely used to evaluate the agreement between measurements and treatment planning system calculations in patient-specific intensity modulated radiation therapy (IMRT) quality assurance (QA). However, recent publications have raised concerns about the lack of sensitivity when employing commonly used gamma criteria. Understanding the actual sensitivity of a wide range of different gamma criteria may allow the definition of more meaningful gamma criteria and tolerance limits in IMRT QA. We present a method that allows the quantitative determination of gamma criteria sensitivity to induced errors which can be applied to any unique combination of device, delivery technique,more » and software utilized in a specific clinic. Methods: A total of 21 DMLC IMRT QA measurements (ArcCHECK®, Sun Nuclear) were compared to QA plan calculations with induced errors. Three scenarios were studied: MU errors, multi-leaf collimator (MLC) errors, and the sensitivity of the gamma comparison to changes in penumbra width. Gamma comparisons were performed between measurements and error-induced calculations using a wide range of gamma criteria, resulting in a total of over 20 000 gamma comparisons. Gamma passing rates for each error class and case were graphed against error magnitude to create error curves in order to represent the range of missed errors in routine IMRT QA using 36 different gamma criteria. Results: This study demonstrates that systematic errors and case-specific errors can be detected by the error curve analysis. Depending on the location of the error curve peak (e.g., not centered about zero), 3%/3 mm threshold = 10% at 90% pixels passing may miss errors as large as 15% MU errors and ±1 cm random MLC errors for some cases. As the dose threshold parameter was increased for a given %Diff/distance-to-agreement (DTA) setting, error sensitivity was increased by up to a factor of two for select cases. This increased sensitivity with increasing

IMRT QA: Selecting gamma criteria based on error detection sensitivity.

PubMed

Steers, Jennifer M; Fraass, Benedick A

2016-04-01

The gamma comparison is widely used to evaluate the agreement between measurements and treatment planning system calculations in patient-specific intensity modulated radiation therapy (IMRT) quality assurance (QA). However, recent publications have raised concerns about the lack of sensitivity when employing commonly used gamma criteria. Understanding the actual sensitivity of a wide range of different gamma criteria may allow the definition of more meaningful gamma criteria and tolerance limits in IMRT QA. We present a method that allows the quantitative determination of gamma criteria sensitivity to induced errors which can be applied to any unique combination of device, delivery technique, and software utilized in a specific clinic. A total of 21 DMLC IMRT QA measurements (ArcCHECK®, Sun Nuclear) were compared to QA plan calculations with induced errors. Three scenarios were studied: MU errors, multi-leaf collimator (MLC) errors, and the sensitivity of the gamma comparison to changes in penumbra width. Gamma comparisons were performed between measurements and error-induced calculations using a wide range of gamma criteria, resulting in a total of over 20 000 gamma comparisons. Gamma passing rates for each error class and case were graphed against error magnitude to create error curves in order to represent the range of missed errors in routine IMRT QA using 36 different gamma criteria. This study demonstrates that systematic errors and case-specific errors can be detected by the error curve analysis. Depending on the location of the error curve peak (e.g., not centered about zero), 3%/3 mm threshold = 10% at 90% pixels passing may miss errors as large as 15% MU errors and ±1 cm random MLC errors for some cases. As the dose threshold parameter was increased for a given %Diff/distance-to-agreement (DTA) setting, error sensitivity was increased by up to a factor of two for select cases. This increased sensitivity with increasing dose threshold was consistent

Magnetic-field sensing with quantum error detection under the effect of energy relaxation

NASA Astrophysics Data System (ADS)

Matsuzaki, Yuichiro; Benjamin, Simon

2017-03-01

A solid state spin is an attractive system with which to realize an ultrasensitive magnetic field sensor. A spin superposition state will acquire a phase induced by the target field, and we can estimate the field strength from this phase. Recent studies have aimed at improving sensitivity through the use of quantum error correction (QEC) to detect and correct any bit-flip errors that may occur during the sensing period. Here we investigate the performance of a two-qubit sensor employing QEC and under the effect of energy relaxation. Surprisingly, we find that the standard QEC technique to detect and recover from an error does not improve the sensitivity compared with the single-qubit sensors. This is a consequence of the fact that the energy relaxation induces both a phase-flip and a bit-flip noise where the former noise cannot be distinguished from the relative phase induced from the target fields. However, we have found that we can improve the sensitivity if we adopt postselection to discard the state when error is detected. Even when quantum error detection is moderately noisy, and allowing for the cost of the postselection technique, we find that this two-qubit system shows an advantage in sensing over a single qubit in the same conditions.

Early Detection | Division of Cancer Prevention

Cancer.gov

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Early error detection: an action-research experience teaching vector calculus

NASA Astrophysics Data System (ADS)

Magdalena Añino, María; Merino, Gabriela; Miyara, Alberto; Perassi, Marisol; Ravera, Emiliano; Pita, Gustavo; Waigandt, Diana

2014-04-01

This paper describes an action-research experience carried out with second year students at the School of Engineering of the National University of Entre Ríos, Argentina. Vector calculus students played an active role in their own learning process. They were required to present weekly reports, in both oral and written forms, on the topics studied, instead of merely sitting and watching as the teacher solved problems on the blackboard. The students were also asked to perform computer assignments, and their learning process was continuously monitored. Among many benefits, this methodology has allowed students and teachers to identify errors and misconceptions that might have gone unnoticed under a more passive approach.

Unavoidable Errors: A Spatio-Temporal Analysis of Time-Course and Neural Sources of Evoked Potentials Associated with Error Processing in a Speeded Task

ERIC Educational Resources Information Center

Vocat, Roland; Pourtois, Gilles; Vuilleumier, Patrik

2008-01-01

The detection of errors is known to be associated with two successive neurophysiological components in EEG, with an early time-course following motor execution: the error-related negativity (ERN/Ne) and late positivity (Pe). The exact cognitive and physiological processes contributing to these two EEG components, as well as their functional…

Spatial heterogeneity of type I error for local cluster detection tests

PubMed Central

2014-01-01

Background Just as power, type I error of cluster detection tests (CDTs) should be spatially assessed. Indeed, CDTs’ type I error and power have both a spatial component as CDTs both detect and locate clusters. In the case of type I error, the spatial distribution of wrongly detected clusters (WDCs) can be particularly affected by edge effect. This simulation study aims to describe the spatial distribution of WDCs and to confirm and quantify the presence of edge effect. Methods A simulation of 40 000 datasets has been performed under the null hypothesis of risk homogeneity. The simulation design used realistic parameters from survey data on birth defects, and in particular, two baseline risks. The simulated datasets were analyzed using the Kulldorff’s spatial scan as a commonly used test whose behavior is otherwise well known. To describe the spatial distribution of type I error, we defined the participation rate for each spatial unit of the region. We used this indicator in a new statistical test proposed to confirm, as well as quantify, the edge effect. Results The predefined type I error of 5% was respected for both baseline risks. Results showed strong edge effect in participation rates, with a descending gradient from center to edge, and WDCs more often centrally situated. Conclusions In routine analysis of real data, clusters on the edge of the region should be carefully considered as they rarely occur when there is no cluster. Further work is needed to combine results from power studies with this work in order to optimize CDTs performance. PMID:24885343

Hybrid online sensor error detection and functional redundancy for systems with time-varying parameters.

PubMed

Feng, Jianyuan; Turksoy, Kamuran; Samadi, Sediqeh; Hajizadeh, Iman; Littlejohn, Elizabeth; Cinar, Ali

2017-12-01

Supervision and control systems rely on signals from sensors to receive information to monitor the operation of a system and adjust manipulated variables to achieve the control objective. However, sensor performance is often limited by their working conditions and sensors may also be subjected to interference by other devices. Many different types of sensor errors such as outliers, missing values, drifts and corruption with noise may occur during process operation. A hybrid online sensor error detection and functional redundancy system is developed to detect errors in online signals, and replace erroneous or missing values detected with model-based estimates. The proposed hybrid system relies on two techniques, an outlier-robust Kalman filter (ORKF) and a locally-weighted partial least squares (LW-PLS) regression model, which leverage the advantages of automatic measurement error elimination with ORKF and data-driven prediction with LW-PLS. The system includes a nominal angle analysis (NAA) method to distinguish between signal faults and large changes in sensor values caused by real dynamic changes in process operation. The performance of the system is illustrated with clinical data continuous glucose monitoring (CGM) sensors from people with type 1 diabetes. More than 50,000 CGM sensor errors were added to original CGM signals from 25 clinical experiments, then the performance of error detection and functional redundancy algorithms were analyzed. The results indicate that the proposed system can successfully detect most of the erroneous signals and substitute them with reasonable estimated values computed by functional redundancy system.

Detecting genotyping errors and describing black bear movement in northern Idaho

Treesearch

Michael K. Schwartz; Samuel A. Cushman; Kevin S. McKelvey; Jim Hayden; Cory Engkjer

2006-01-01

Non-invasive genetic sampling has become a favored tool to enumerate wildlife. Genetic errors, caused by poor quality samples, can lead to substantial biases in numerical estimates of individuals. We demonstrate how the computer program DROPOUT can detect amplification errors (false alleles and allelic dropout) in a black bear (Ursus americanus) dataset collected in...

Unmodeled observation error induces bias when inferring patterns and dynamics of species occurrence via aural detections

USGS Publications Warehouse

McClintock, Brett T.; Bailey, Larissa L.; Pollock, Kenneth H.; Simons, Theodore R.

2010-01-01

The recent surge in the development and application of species occurrence models has been associated with an acknowledgment among ecologists that species are detected imperfectly due to observation error. Standard models now allow unbiased estimation of occupancy probability when false negative detections occur, but this is conditional on no false positive detections and sufficient incorporation of explanatory variables for the false negative detection process. These assumptions are likely reasonable in many circumstances, but there is mounting evidence that false positive errors and detection probability heterogeneity may be much more prevalent in studies relying on auditory cues for species detection (e.g., songbird or calling amphibian surveys). We used field survey data from a simulated calling anuran system of known occupancy state to investigate the biases induced by these errors in dynamic models of species occurrence. Despite the participation of expert observers in simplified field conditions, both false positive errors and site detection probability heterogeneity were extensive for most species in the survey. We found that even low levels of false positive errors, constituting as little as 1% of all detections, can cause severe overestimation of site occupancy, colonization, and local extinction probabilities. Further, unmodeled detection probability heterogeneity induced substantial underestimation of occupancy and overestimation of colonization and local extinction probabilities. Completely spurious relationships between species occurrence and explanatory variables were also found. Such misleading inferences would likely have deleterious implications for conservation and management programs. We contend that all forms of observation error, including false positive errors and heterogeneous detection probabilities, must be incorporated into the estimation framework to facilitate reliable inferences about occupancy and its associated vital rate parameters.

Error field detection in DIII-D by magnetic steering of locked modes

DOE PAGES

Shiraki, Daisuke; La Haye, Robert J.; Logan, Nikolas C.; ...

2014-02-20

Optimal correction coil currents for the n = 1 intrinsic error field of the DIII-D tokamak are inferred by applying a rotating external magnetic perturbation to steer the phase of a saturated locked mode with poloidal/toroidal mode number m/n = 2/1. The error field is detected non-disruptively in a single discharge, based on the toroidal torque balance of the resonant surface, which is assumed to be dominated by the balance of resonant electromagnetic torques. This is equivalent to the island being locked at all times to the resonant 2/1 component of the total of the applied and intrinsic error fields,more » such that the deviation of the locked mode phase from the applied field phase depends on the existing error field. The optimal set of correction coil currents is determined to be those currents which best cancels the torque from the error field, based on fitting of the torque balance model. The toroidal electromagnetic torques are calculated from experimental data using a simplified approach incorporating realistic DIII-D geometry, and including the effect of the plasma response on island torque balance based on the ideal plasma response to external fields. This method of error field detection is demonstrated in DIII-D discharges, and the results are compared with those based on the onset of low-density locked modes in ohmic plasmas. Furthermore, this magnetic steering technique presents an efficient approach to error field detection and is a promising method for ITER, particularly during initial operation when the lack of auxiliary heating systems makes established techniques based on rotation or plasma amplification unsuitable.« less

Early Detection of Sporadic Pancreatic Cancer

PubMed Central

Kenner, Barbara J.; Chari, Suresh T.; Cleeter, Deborah F.; Go, Vay Liang W.

2015-01-01

Abstract Innovation leading to significant advances in research and subsequent translation to clinical practice is urgently necessary in early detection of sporadic pancreatic cancer. Addressing this need, the Early Detection of Sporadic Pancreatic Cancer Summit Conference was conducted by Kenner Family Research Fund in conjunction with the 2014 American Pancreatic Association and Japan Pancreas Society Meeting. International interdisciplinary scientific representatives engaged in strategic facilitated conversations based on distinct areas of inquiry: Case for Early Detection: Definitions, Detection, Survival, and Challenges; Biomarkers for Early Detection; Imaging; and Collaborative Studies. Ideas generated from the summit have led to the development of a Strategic Map for Innovation built upon 3 components: formation of an international collaborative effort, design of an actionable strategic plan, and implementation of operational standards, research priorities, and first-phase initiatives. Through invested and committed efforts of leading researchers and institutions, philanthropic partners, government agencies, and supportive business entities, this endeavor will change the future of the field and consequently the survival rate of those diagnosed with pancreatic cancer. PMID:25938853

SU-F-T-310: Does a Head-Mounted Ionization Chamber Detect IMRT Errors?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wegener, S; Herzog, B; Sauer, O

2016-06-15

Purpose: The conventional plan verification strategy is delivering a plan to a QA-phantom before the first treatment. Monitoring each fraction of the patient treatment in real-time would improve patient safety. We evaluated how well a new detector, the IQM (iRT Systems, Germany), is capable of detecting errors we induced into IMRT plans of three different treatment regions. Results were compared to an established phantom. Methods: Clinical plans of a brain, prostate and head-and-neck patient were modified in the Pinnacle planning system, such that they resulted in either several percent lower prescribed doses to the target volume or several percent highermore » doses to relevant organs at risk. Unaltered plans were measured on three days, modified plans once, each with the IQM at an Elekta Synergy with an Agility MLC. All plans were also measured with the ArcCHECK with the cavity plug and a PTW semiflex 31010 ionization chamber inserted. Measurements were evaluated with SNC patient software. Results: Repeated IQM measurements of the original plans were reproducible, such that a 1% deviation from the mean as warning and 3% as action level as suggested by the manufacturer seemed reasonable. The IQM detected most of the simulated errors including wrong energy, a faulty leaf, wrong trial exported and a 2 mm shift of one leaf bank. Detection limits were reached for two plans - a 2 mm field position error and a leaf bank offset combined with an MU change. ArcCHECK evaluation according to our current standards also left undetected errors. Ionization chamber evaluation alone would leave most errors undetected. Conclusion: The IQM detected most errors and performed as well as currently established phantoms with the advantage that it can be used throughout the whole treatment. Drawback is that it does not indicate the source of the error.« less

The use of self checks and voting in software error detection - An empirical study

NASA Technical Reports Server (NTRS)

Leveson, Nancy G.; Cha, Stephen S.; Knight, John C.; Shimeall, Timothy J.

1990-01-01

The results of an empirical study of software error detection using self checks and N-version voting are presented. Working independently, each of 24 programmers first prepared a set of self checks using just the requirements specification of an aerospace application, and then each added self checks to an existing implementation of that specification. The modified programs were executed to measure the error-detection performance of the checks and to compare this with error detection using simple voting among multiple versions. The analysis of the checks revealed that there are great differences in the ability of individual programmers to design effective checks. It was found that some checks that might have been effective failed to detect an error because they were badly placed, and there were numerous instances of checks signaling nonexistent errors. In general, specification-based checks alone were not as effective as specification-based checks combined with code-based checks. Self checks made it possible to identify faults that had not been detected previously by voting 28 versions of the program over a million randomly generated inputs. This appeared to result from the fact that the self checks could examine the internal state of the executing program, whereas voting examines only final results of computations. If internal states had to be identical in N-version voting systems, then there would be no reason to write multiple versions.

TU-G-BRD-08: In-Vivo EPID Dosimetry: Quantifying the Detectability of Four Classes of Errors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ford, E; Phillips, M; Bojechko, C

Purpose: EPID dosimetry is an emerging method for treatment verification and QA. Given that the in-vivo EPID technique is in clinical use at some centers, we investigate the sensitivity and specificity for detecting different classes of errors. We assess the impact of these errors using dose volume histogram endpoints. Though data exist for EPID dosimetry performed pre-treatment, this is the first study quantifying its effectiveness when used during patient treatment (in-vivo). Methods: We analyzed 17 patients; EPID images of the exit dose were acquired and used to reconstruct the planar dose at isocenter. This dose was compared to the TPSmore » dose using a 3%/3mm gamma criteria. To simulate errors, modifications were made to treatment plans using four possible classes of error: 1) patient misalignment, 2) changes in patient body habitus, 3) machine output changes and 4) MLC misalignments. Each error was applied with varying magnitudes. To assess the detectability of the error, the area under a ROC curve (AUC) was analyzed. The AUC was compared to changes in D99 of the PTV introduced by the simulated error. Results: For systematic changes in the MLC leaves, changes in the machine output and patient habitus, the AUC varied from 0.78–0.97 scaling with the magnitude of the error. The optimal gamma threshold as determined by the ROC curve varied between 84–92%. There was little diagnostic power in detecting random MLC leaf errors and patient shifts (AUC 0.52–0.74). Some errors with weak detectability had large changes in D99. Conclusion: These data demonstrate the ability of EPID-based in-vivo dosimetry in detecting variations in patient habitus and errors related to machine parameters such as systematic MLC misalignments and machine output changes. There was no correlation found between the detectability of the error using the gamma pass rate, ROC analysis and the impact on the dose volume histogram. Funded by grant R18HS022244 from AHRQ.« less

Quantum-state anomaly detection for arbitrary errors using a machine-learning technique

NASA Astrophysics Data System (ADS)

Hara, Satoshi; Ono, Takafumi; Okamoto, Ryo; Washio, Takashi; Takeuchi, Shigeki

2016-10-01

The accurate detection of small deviations in given density matrice is important for quantum information processing, which is a difficult task because of the intrinsic fluctuation in density matrices reconstructed using a limited number of experiments. We previously proposed a method for decoherence error detection using a machine-learning technique [S. Hara, T. Ono, R. Okamoto, T. Washio, and S. Takeuchi, Phys. Rev. A 89, 022104 (2014), 10.1103/PhysRevA.89.022104]. However, the previous method is not valid when the errors are just changes in phase. Here, we propose a method that is valid for arbitrary errors in density matrices. The performance of the proposed method is verified using both numerical simulation data and real experimental data.

System of error detection in the manufacture of garments using artificial vision

NASA Astrophysics Data System (ADS)

Moreno, J. J.; Aguila, A.; Partida, E.; Martinez, C. L.; Morales, O.; Tejeida, R.

2017-12-01

A computer vision system is implemented to detect errors in the cutting stage within the manufacturing process of garments in the textile industry. It provides solution to errors within the process that cannot be easily detected by any employee, in addition to significantly increase the speed of quality review. In the textile industry as in many others, quality control is required in manufactured products and this has been carried out manually by means of visual inspection by employees over the years. For this reason, the objective of this project is to design a quality control system using computer vision to identify errors in the cutting stage within the garment manufacturing process to increase the productivity of textile processes by reducing costs.

A Case for Soft Error Detection and Correction in Computational Chemistry.

PubMed

van Dam, Hubertus J J; Vishnu, Abhinav; de Jong, Wibe A

2013-09-10

High performance computing platforms are expected to deliver 10(18) floating operations per second by the year 2022 through the deployment of millions of cores. Even if every core is highly reliable the sheer number of them will mean that the mean time between failures will become so short that most application runs will suffer at least one fault. In particular soft errors caused by intermittent incorrect behavior of the hardware are a concern as they lead to silent data corruption. In this paper we investigate the impact of soft errors on optimization algorithms using Hartree-Fock as a particular example. Optimization algorithms iteratively reduce the error in the initial guess to reach the intended solution. Therefore they may intuitively appear to be resilient to soft errors. Our results show that this is true for soft errors of small magnitudes but not for large errors. We suggest error detection and correction mechanisms for different classes of data structures. The results obtained with these mechanisms indicate that we can correct more than 95% of the soft errors at moderate increases in the computational cost.

A novel approach for pilot error detection using Dynamic Bayesian Networks.

PubMed

Saada, Mohamad; Meng, Qinggang; Huang, Tingwen

2014-06-01

In the last decade Dynamic Bayesian Networks (DBNs) have become one type of the most attractive probabilistic modelling framework extensions of Bayesian Networks (BNs) for working under uncertainties from a temporal perspective. Despite this popularity not many researchers have attempted to study the use of these networks in anomaly detection or the implications of data anomalies on the outcome of such models. An abnormal change in the modelled environment's data at a given time, will cause a trailing chain effect on data of all related environment variables in current and consecutive time slices. Albeit this effect fades with time, it still can have an ill effect on the outcome of such models. In this paper we propose an algorithm for pilot error detection, using DBNs as the modelling framework for learning and detecting anomalous data. We base our experiments on the actions of an aircraft pilot, and a flight simulator is created for running the experiments. The proposed anomaly detection algorithm has achieved good results in detecting pilot errors and effects on the whole system.

Life expectancy and the value of early detection.

PubMed

Howard, David H

2005-09-01

This paper presents a model of the benefits and costs of early detection of asymptomatic disease as they vary by age. The benefits of early detection tend toward zero as the risk of death from competing causes increases. Costs per detected case also decline with age, assuming that disease incidence rises with age, but are always strictly positive. On balance, there is always an age limit beyond which the costs associated with early detection outweigh the benefits. Application of the model to prostate cancer screening suggests that early detection above age 70 or so is not cost-effective.

Early detection: the impact of genomics.

PubMed

van Lanschot, M C J; Bosch, L J W; de Wit, M; Carvalho, B; Meijer, G A

2017-08-01

The field of genomics has shifted our view on disease development by providing insights in the molecular and functional processes encoded in the genome. In the case of cancer, many alterations in the DNA accumulate that enable tumor growth or even metastatic dissemination. Identification of molecular signatures that define different stages of progression towards cancer can enable early tumor detection. In this review, the impact of genomics will be addressed using early detection of colorectal cancer (CRC) as an example. Increased understanding of the adenoma-to-carcinoma progression has led to the discovery of several diagnostic biomarkers. This combined with technical advancements, has facilitated the development of molecular tests for non-invasive early CRC detection in stool and blood samples. Even though several tests have already made it to clinical practice, sensitivity and specificity for the detection of precancerous lesions still need improvement. Besides the diagnostic qualities, also the accuracy of the intermediate endpoint is an important issue on how the effectiveness of a novel test is perceived. Here, progression biomarkers may provide a more precise measure than the currently used morphologically based features. Similar developments in biomarker use for early detection have taken place in other cancer types.

Design and scheduling for periodic concurrent error detection and recovery in processor arrays

NASA Technical Reports Server (NTRS)

Wang, Yi-Min; Chung, Pi-Yu; Fuchs, W. Kent

1992-01-01

Periodic application of time-redundant error checking provides the trade-off between error detection latency and performance degradation. The goal is to achieve high error coverage while satisfying performance requirements. We derive the optimal scheduling of checking patterns in order to uniformly distribute the available checking capability and maximize the error coverage. Synchronous buffering designs using data forwarding and dynamic reconfiguration are described. Efficient single-cycle diagnosis is implemented by error pattern analysis and direct-mapped recovery cache. A rollback recovery scheme using start-up control for local recovery is also presented.

Text familiarity, word frequency, and sentential constraints in error detection.

PubMed

Pilotti, Maura; Chodorow, Martin; Schauss, Frances

2009-12-01

The present study examines whether the frequency of an error-bearing word and its predictability, arising from sentential constraints and text familiarity, either independently or jointly, would impair error detection by making proofreading driven by top-down processes. Prior to a proofreading task, participants were asked to read, copy, memorize, or paraphrase sentences, half of which contained errors. These tasks represented a continuum of progressively more demanding and time-consuming activities, which were thought to lead to comparable increases in text familiarity and thus predictability. Proofreading times were unaffected by whether the sentences had been encountered earlier. Proofreading was slower and less accurate for high-frequency words and for highly constrained sentences. Prior memorization produced divergent effects on accuracy depending on sentential constraints. The latter finding suggested that a substantial level of predictability, such as that produced by memorizing highly constrained sentences, can increase the probability of overlooking errors.

Runtime Verification in Context : Can Optimizing Error Detection Improve Fault Diagnosis

NASA Technical Reports Server (NTRS)

Dwyer, Matthew B.; Purandare, Rahul; Person, Suzette

2010-01-01

Runtime verification has primarily been developed and evaluated as a means of enriching the software testing process. While many researchers have pointed to its potential applicability in online approaches to software fault tolerance, there has been a dearth of work exploring the details of how that might be accomplished. In this paper, we describe how a component-oriented approach to software health management exposes the connections between program execution, error detection, fault diagnosis, and recovery. We identify both research challenges and opportunities in exploiting those connections. Specifically, we describe how recent approaches to reducing the overhead of runtime monitoring aimed at error detection might be adapted to reduce the overhead and improve the effectiveness of fault diagnosis.

Early behavioral inhibition and increased error monitoring predict later social phobia symptoms in childhood

PubMed Central

Lahat, Ayelet; Lamm, Connie; Chronis-Tuscano, Andrea; Pine, Daniel S.; Henderson, Heather A.; Fox, Nathan A.

2014-01-01

Objective Behavioral inhibition (BI) is an early childhood temperament characterized by fearful responses to novelty and avoidance of social interactions. During adolescence, a subset of children with stable childhood BI develop social anxiety disorder and concurrently exhibit increased error monitoring. The current study examines whether increased error monitoring in seven-year-old behaviorally inhibited children prospectively predicts risk for symptoms of social phobia at age 9. Method Two hundred and ninety one children were characterized on BI at 24 and 36 months of age. Children were seen again at 7 years of age, where they performed a Flanker task, and event-related-potential (ERP) indices of response monitoring were generated. At age 9, self- and maternal-report of social phobia symptoms were obtained. Results Children high in BI, compared to those low in BI, displayed increased error monitoring at age 7, as indexed by larger (i.e., more negative) error-related negativity (ERN) amplitudes. Additionally, early BI was related to later childhood social phobia symptoms at age 9 among children with a large difference in amplitude between ERN and correct-response negativity (CRN) at age 7. Conclusions Heightened error monitoring predicts risk for later social phobia symptoms in children with high BI. Research assessing response monitoring in children with BI may refine our understanding of the mechanisms underlying risk for later anxiety disorders and inform prevention efforts. PMID:24655654

SU-F-T-471: Simulated External Beam Delivery Errors Detection with a Large Area Ion Chamber Transmission Detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoffman, D; Dyer, B; Kumaran Nair, C

Purpose: The Integral Quality Monitor (IQM), developed by iRT Systems GmbH (Koblenz, Germany) is a large-area, linac-mounted ion chamber used to monitor photon fluence during patient treatment. Our previous work evaluated the change of the ion chamber’s response to deviations from static 1×1 cm2 and 10×10 cm2 photon beams and other characteristics integral to use in external beam detection. The aim of this work is to simulate two external beam radiation delivery errors, quantify the detection of simulated errors and evaluate the reduction in patient harm resulting from detection. Methods: Two well documented radiation oncology delivery errors were selected formore » simulation. The first error was recreated by modifying a wedged whole breast treatment, removing the physical wedge and calculating the planned dose with Pinnacle TPS (Philips Radiation Oncology Systems, Fitchburg, WI). The second error was recreated by modifying a static-gantry IMRT pharyngeal tonsil plan to be delivered in 3 unmodulated fractions. A radiation oncologist evaluated the dose for simulated errors and predicted morbidity and mortality commiserate with the original reported toxicity, indicating that reported errors were approximately simulated. The ion chamber signal of unmodified treatments was compared to the simulated error signal and evaluated in Pinnacle TPS again with radiation oncologist prediction of simulated patient harm. Results: Previous work established that transmission detector system measurements are stable within 0.5% standard deviation (SD). Errors causing signal change greater than 20 SD (10%) were considered detected. The whole breast and pharyngeal tonsil IMRT simulated error increased signal by 215% and 969%, respectively, indicating error detection after the first fraction and IMRT segment, respectively. Conclusion: The transmission detector system demonstrated utility in detecting clinically significant errors and reducing patient toxicity/harm in simulated

Evaluating suggestibility to additive and contradictory misinformation following explicit error detection in younger and older adults.

PubMed

Huff, Mark J; Umanath, Sharda

2018-06-01

In 2 experiments, we assessed age-related suggestibility to additive and contradictory misinformation (i.e., remembering of false details from an external source). After reading a fictional story, participants answered questions containing misleading details that were either additive (misleading details that supplemented an original event) or contradictory (errors that changed original details). On a final test, suggestibility was greater for additive than contradictory misinformation, and older adults endorsed fewer false contradictory details than younger adults. To mitigate suggestibility in Experiment 2, participants were warned about potential errors, instructed to detect errors, or instructed to detect errors after exposure to examples of additive and contradictory details. Again, suggestibility to additive misinformation was greater than contradictory, and older adults endorsed less contradictory misinformation. Only after detection instructions with misinformation examples were younger adults able to reduce contradictory misinformation effects and reduced these effects to the level of older adults. Additive misinformation however, was immune to all warning and detection instructions. Thus, older adults were less susceptible to contradictory misinformation errors, and younger adults could match this misinformation rate when warning/detection instructions were strong. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Early detection of sporadic pancreatic cancer: summative review.

PubMed

Chari, Suresh T; Kelly, Kimberly; Hollingsworth, Michael A; Thayer, Sarah P; Ahlquist, David A; Andersen, Dana K; Batra, Surinder K; Brentnall, Teresa A; Canto, Marcia; Cleeter, Deborah F; Firpo, Matthew A; Gambhir, Sanjiv Sam; Go, Vay Liang W; Hines, O Joe; Kenner, Barbara J; Klimstra, David S; Lerch, Markus M; Levy, Michael J; Maitra, Anirban; Mulvihill, Sean J; Petersen, Gloria M; Rhim, Andrew D; Simeone, Diane M; Srivastava, Sudhir; Tanaka, Masao; Vinik, Aaron I; Wong, David

2015-07-01

Pancreatic cancer (PC) is estimated to become the second leading cause of cancer death in the United States by 2020. Early detection is the key to improving survival in PC. Addressing this urgent need, the Kenner Family Research Fund conducted the inaugural Early Detection of Sporadic Pancreatic Cancer Summit Conference in 2014 in conjunction with the 45th Anniversary Meeting of the American Pancreatic Association and Japan Pancreas Society. This seminal convening of international representatives from science, practice, and clinical research was designed to facilitate challenging interdisciplinary conversations to generate innovative ideas leading to the creation of a defined collaborative strategic pathway for the future of the field. An in-depth summary of current efforts in the field, analysis of gaps in specific areas of expertise, and challenges that exist in early detection is presented within distinct areas of inquiry: Case for Early Detection: Definitions, Detection, Survival, and Challenges; Biomarkers for Early Detection; Imaging; and Collaborative Studies. In addition, an overview of efforts in familial PC is presented in an addendum to this article. It is clear from the summit deliberations that only strategically designed collaboration among investigators, institutions, and funders will lead to significant progress in early detection of sporadic PC.

Gastrointestinal Cancers: Screening and Early Detection.

PubMed

Griffin-Sobel, Joyce P

2017-05-01

To present an overview of current practices in the screening and early detection of gastrointestinal cancers. Literature reviews. Screening for gastrointestinal cancers is less than desirable, particularly in underserved populations. There are inadequate methods of screening for early detection of esophageal and gastric cancers. Education of patients is needed to reinforce the importance of screening for gastrointestinal cancers. Copyright © 2017 Elsevier Inc. All rights reserved.

Single Versus Multiple Events Error Potential Detection in a BCI-Controlled Car Game With Continuous and Discrete Feedback.

PubMed

Kreilinger, Alex; Hiebel, Hannah; Müller-Putz, Gernot R

2016-03-01

This work aimed to find and evaluate a new method for detecting errors in continuous brain-computer interface (BCI) applications. Instead of classifying errors on a single-trial basis, the new method was based on multiple events (MEs) analysis to increase the accuracy of error detection. In a BCI-driven car game, based on motor imagery (MI), discrete events were triggered whenever subjects collided with coins and/or barriers. Coins counted as correct events, whereas barriers were errors. This new method, termed ME method, combined and averaged the classification results of single events (SEs) and determined the correctness of MI trials, which consisted of event sequences instead of SEs. The benefit of this method was evaluated in an offline simulation. In an online experiment, the new method was used to detect erroneous MI trials. Such MI trials were discarded and could be repeated by the users. We found that, even with low SE error potential (ErrP) detection rates, feasible accuracies can be achieved when combining MEs to distinguish erroneous from correct MI trials. Online, all subjects reached higher scores with error detection than without, at the cost of longer times needed for completing the game. Findings suggest that ErrP detection may become a reliable tool for monitoring continuous states in BCI applications when combining MEs. This paper demonstrates a novel technique for detecting errors in online continuous BCI applications, which yields promising results even with low single-trial detection rates.

[New possibilities screening of refractive errors among children].

PubMed

Ondrejková, M; Kyselová, P

2013-06-01

To establish early detection of refractive errors among children in Slovakia. Different screening methods have been evaluated and compared in this work. we have been working on a prospective study. Pre-school children in kindergardens in Central Slovakia were checked up between years 2009-2011. Effectiveness of various screening methods was compared within 2 groups, using test-type and Plusoptix Vision Screener. Parentęs of children positive to refractive errors were recommended to consult a paediatrician ophthalmologist. 3982 children were examined. As a result, 13-14.1% of children who have not been examinated by the specialist, were positive. 53.3% of them went to see the doctor afterwards. establishment of early refractive errors screening is an important method how to prevent strabismus and amblyopia. It is very important to improve parentęs knowledge about the risk of refractive errors and also to improve screening methods with collaboration with kindergarten teachers.

Early behavioral inhibition and increased error monitoring predict later social phobia symptoms in childhood.

PubMed

Lahat, Ayelet; Lamm, Connie; Chronis-Tuscano, Andrea; Pine, Daniel S; Henderson, Heather A; Fox, Nathan A

2014-04-01

Behavioral inhibition (BI) is an early childhood temperament characterized by fearful responses to novelty and avoidance of social interactions. During adolescence, a subset of children with stable childhood BI develop social anxiety disorder and concurrently exhibit increased error monitoring. The current study examines whether increased error monitoring in 7-year-old, behaviorally inhibited children prospectively predicts risk for symptoms of social phobia at age 9 years. A total of 291 children were characterized on BI at 24 and 36 months of age. Children were seen again at 7 years of age, when they performed a Flanker task, and event-related potential (ERP) indices of response monitoring were generated. At age 9, self- and maternal-report of social phobia symptoms were obtained. Children high in BI, compared to those low in BI, displayed increased error monitoring at age 7, as indexed by larger (i.e., more negative) error-related negativity (ERN) amplitudes. In addition, early BI was related to later childhood social phobia symptoms at age 9 among children with a large difference in amplitude between ERN and correct-response negativity (CRN) at age 7. Heightened error monitoring predicts risk for later social phobia symptoms in children with high BI. Research assessing response monitoring in children with BI may refine our understanding of the mechanisms underlying risk for later anxiety disorders and inform prevention efforts. Copyright © 2014 American Academy of Child and Adolescent Psychiatry. All rights reserved.

CUSUM-Logistic Regression analysis for the rapid detection of errors in clinical laboratory test results.

PubMed

Sampson, Maureen L; Gounden, Verena; van Deventer, Hendrik E; Remaley, Alan T

2016-02-01

The main drawback of the periodic analysis of quality control (QC) material is that test performance is not monitored in time periods between QC analyses, potentially leading to the reporting of faulty test results. The objective of this study was to develop a patient based QC procedure for the more timely detection of test errors. Results from a Chem-14 panel measured on the Beckman LX20 analyzer were used to develop the model. Each test result was predicted from the other 13 members of the panel by multiple regression, which resulted in correlation coefficients between the predicted and measured result of >0.7 for 8 of the 14 tests. A logistic regression model, which utilized the measured test result, the predicted test result, the day of the week and time of day, was then developed for predicting test errors. The output of the logistic regression was tallied by a daily CUSUM approach and used to predict test errors, with a fixed specificity of 90%. The mean average run length (ARL) before error detection by CUSUM-Logistic Regression (CSLR) was 20 with a mean sensitivity of 97%, which was considerably shorter than the mean ARL of 53 (sensitivity 87.5%) for a simple prediction model that only used the measured result for error detection. A CUSUM-Logistic Regression analysis of patient laboratory data can be an effective approach for the rapid and sensitive detection of clinical laboratory errors. Published by Elsevier Inc.

Detecting medication errors in the New Zealand pharmacovigilance database: a retrospective analysis.

PubMed

Kunac, Desireé L; Tatley, Michael V

2011-01-01

Despite the traditional focus being adverse drug reactions (ADRs), pharmacovigilance centres have recently been identified as a potentially rich and important source of medication error data. To identify medication errors in the New Zealand Pharmacovigilance database (Centre for Adverse Reactions Monitoring [CARM]), and to describe the frequency and characteristics of these events. A retrospective analysis of the CARM pharmacovigilance database operated by the New Zealand Pharmacovigilance Centre was undertaken for the year 1 January-31 December 2007. All reports, excluding those relating to vaccines, clinical trials and pharmaceutical company reports, underwent a preventability assessment using predetermined criteria. Those events deemed preventable were subsequently classified to identify the degree of patient harm, type of error, stage of medication use process where the error occurred and origin of the error. A total of 1412 reports met the inclusion criteria and were reviewed, of which 4.3% (61/1412) were deemed preventable. Not all errors resulted in patient harm: 29.5% (18/61) were 'no harm' errors but 65.5% (40/61) of errors were deemed to have been associated with some degree of patient harm (preventable adverse drug events [ADEs]). For 5.0% (3/61) of events, the degree of patient harm was unable to be determined as the patient outcome was unknown. The majority of preventable ADEs (62.5% [25/40]) occurred in adults aged 65 years and older. The medication classes most involved in preventable ADEs were antibacterials for systemic use and anti-inflammatory agents, with gastrointestinal and respiratory system disorders the most common adverse events reported. For both preventable ADEs and 'no harm' events, most errors were incorrect dose and drug therapy monitoring problems consisting of failures in detection of significant drug interactions, past allergies or lack of necessary clinical monitoring. Preventable events were mostly related to the prescribing and

Diffraction analysis and evaluation of several focus- and track-error detection schemes for magneto-optical disk systems

NASA Technical Reports Server (NTRS)

Bernacki, Bruce E.; Mansuripur, M.

1992-01-01

A commonly used tracking method on pre-grooved magneto-optical (MO) media is the push-pull technique, and the astigmatic method is a popular focus-error detection approach. These two methods are analyzed using DIFFRACT, a general-purpose scalar diffraction modeling program, to observe the effects on the error signals due to focusing lens misalignment, Seidel aberrations, and optical crosstalk (feedthrough) between the focusing and tracking servos. Using the results of the astigmatic/push-pull system as a basis for comparison, a novel focus/track-error detection technique that utilizes a ring toric lens is evaluated as well as the obscuration method (focus error detection only).

Design of the Detector II: A CMOS Gate Array for the Study of Concurrent Error Detection Techniques.

DTIC Science & Technology

1987-07-01

detection schemes and temporary failures. The circuit consists- or of six different adders with concurrent error detection schemes . The error detection... schemes are - simple duplication, duplication with functional dual implementation, duplication with different &I [] .6implementations, two-rail encoding...THE SYSTEM. .. .... ...... ...... ...... 5 7. DESIGN OF CED SCHEMES .. ... ...... ...... ........ 7 7.1 Simple Duplication

An Efficient Silent Data Corruption Detection Method with Error-Feedback Control and Even Sampling for HPC Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Di, Sheng; Berrocal, Eduardo; Cappello, Franck

The silent data corruption (SDC) problem is attracting more and more attentions because it is expected to have a great impact on exascale HPC applications. SDC faults are hazardous in that they pass unnoticed by hardware and can lead to wrong computation results. In this work, we formulate SDC detection as a runtime one-step-ahead prediction method, leveraging multiple linear prediction methods in order to improve the detection results. The contributions are twofold: (1) we propose an error feedback control model that can reduce the prediction errors for different linear prediction methods, and (2) we propose a spatial-data-based even-sampling method tomore » minimize the detection overheads (including memory and computation cost). We implement our algorithms in the fault tolerance interface, a fault tolerance library with multiple checkpoint levels, such that users can conveniently protect their HPC applications against both SDC errors and fail-stop errors. We evaluate our approach by using large-scale traces from well-known, large-scale HPC applications, as well as by running those HPC applications on a real cluster environment. Experiments show that our error feedback control model can improve detection sensitivity by 34-189% for bit-flip memory errors injected with the bit positions in the range [20,30], without any degradation on detection accuracy. Furthermore, memory size can be reduced by 33% with our spatial-data even-sampling method, with only a slight and graceful degradation in the detection sensitivity.« less

Using EHR Data to Detect Prescribing Errors in Rapidly Discontinued Medication Orders.

PubMed

Burlison, Jonathan D; McDaniel, Robert B; Baker, Donald K; Hasan, Murad; Robertson, Jennifer J; Howard, Scott C; Hoffman, James M

2018-01-01

Previous research developed a new method for locating prescribing errors in rapidly discontinued electronic medication orders. Although effective, the prospective design of that research hinders its feasibility for regular use. Our objectives were to assess a method to retrospectively detect prescribing errors, to characterize the identified errors, and to identify potential improvement opportunities. Electronically submitted medication orders from 28 randomly selected days that were discontinued within 120 minutes of submission were reviewed and categorized as most likely errors, nonerrors, or not enough information to determine status. Identified errors were evaluated by amount of time elapsed from original submission to discontinuation, error type, staff position, and potential clinical significance. Pearson's chi-square test was used to compare rates of errors across prescriber types. In all, 147 errors were identified in 305 medication orders. The method was most effective for orders that were discontinued within 90 minutes. Duplicate orders were most common; physicians in training had the highest error rate ( p  < 0.001), and 24 errors were potentially clinically significant. None of the errors were voluntarily reported. It is possible to identify prescribing errors in rapidly discontinued medication orders by using retrospective methods that do not require interrupting prescribers to discuss order details. Future research could validate our methods in different clinical settings. Regular use of this measure could help determine the causes of prescribing errors, track performance, and identify and evaluate interventions to improve prescribing systems and processes. Schattauer GmbH Stuttgart.

Periodic Application of Concurrent Error Detection in Processor Array Architectures. PhD. Thesis -

NASA Technical Reports Server (NTRS)

Chen, Paul Peichuan

1993-01-01

Processor arrays can provide an attractive architecture for some applications. Featuring modularity, regular interconnection and high parallelism, such arrays are well-suited for VLSI/WSI implementations, and applications with high computational requirements, such as real-time signal processing. Preserving the integrity of results can be of paramount importance for certain applications. In these cases, fault tolerance should be used to ensure reliable delivery of a system's service. One aspect of fault tolerance is the detection of errors caused by faults. Concurrent error detection (CED) techniques offer the advantage that transient and intermittent faults may be detected with greater probability than with off-line diagnostic tests. Applying time-redundant CED techniques can reduce hardware redundancy costs. However, most time-redundant CED techniques degrade a system's performance.

Deep learning classifier with optical coherence tomography images for early dental caries detection

NASA Astrophysics Data System (ADS)

Karimian, Nima; Salehi, Hassan S.; Mahdian, Mina; Alnajjar, Hisham; Tadinada, Aditya

2018-02-01

Dental caries is a microbial disease that results in localized dissolution of the mineral content of dental tissue. Despite considerable decline in the incidence of dental caries, it remains a major health problem in many societies. Early detection of incipient lesions at initial stages of demineralization can result in the implementation of non-surgical preventive approaches to reverse the demineralization process. In this paper, we present a novel approach combining deep convolutional neural networks (CNN) and optical coherence tomography (OCT) imaging modality for classification of human oral tissues to detect early dental caries. OCT images of oral tissues with various densities were input to a CNN classifier to determine variations in tissue densities resembling the demineralization process. The CNN automatically learns a hierarchy of increasingly complex features and a related classifier directly from training data sets. The initial CNN layer parameters were randomly selected. The training set is split into minibatches, with 10 OCT images per batch. Given a batch of training patches, the CNN employs two convolutional and pooling layers to extract features and then classify each patch based on the probabilities from the SoftMax classification layer (output-layer). Afterward, the CNN calculates the error between the classification result and the reference label, and then utilizes the backpropagation process to fine-tune all the layer parameters to minimize this error using batch gradient descent algorithm. We validated our proposed technique on ex-vivo OCT images of human oral tissues (enamel, cortical-bone, trabecular-bone, muscular-tissue, and fatty-tissue), which attested to effectiveness of our proposed method.

Tests for detecting overdispersion in models with measurement error in covariates.

PubMed

Yang, Yingsi; Wong, Man Yu

2015-11-30

Measurement error in covariates can affect the accuracy in count data modeling and analysis. In overdispersion identification, the true mean-variance relationship can be obscured under the influence of measurement error in covariates. In this paper, we propose three tests for detecting overdispersion when covariates are measured with error: a modified score test and two score tests based on the proposed approximate likelihood and quasi-likelihood, respectively. The proposed approximate likelihood is derived under the classical measurement error model, and the resulting approximate maximum likelihood estimator is shown to have superior efficiency. Simulation results also show that the score test based on approximate likelihood outperforms the test based on quasi-likelihood and other alternatives in terms of empirical power. By analyzing a real dataset containing the health-related quality-of-life measurements of a particular group of patients, we demonstrate the importance of the proposed methods by showing that the analyses with and without measurement error correction yield significantly different results. Copyright © 2015 John Wiley & Sons, Ltd.

Advanced Information Processing System - Fault detection and error handling

NASA Technical Reports Server (NTRS)

Lala, J. H.

1985-01-01

The Advanced Information Processing System (AIPS) is designed to provide a fault tolerant and damage tolerant data processing architecture for a broad range of aerospace vehicles, including tactical and transport aircraft, and manned and autonomous spacecraft. A proof-of-concept (POC) system is now in the detailed design and fabrication phase. This paper gives an overview of a preliminary fault detection and error handling philosophy in AIPS.

Effective connectivity associated with auditory error detection in musicians with absolute pitch

PubMed Central

Parkinson, Amy L.; Behroozmand, Roozbeh; Ibrahim, Nadine; Korzyukov, Oleg; Larson, Charles R.; Robin, Donald A.

2014-01-01

It is advantageous to study a wide range of vocal abilities in order to fully understand how vocal control measures vary across the full spectrum. Individuals with absolute pitch (AP) are able to assign a verbal label to musical notes and have enhanced abilities in pitch identification without reliance on an external referent. In this study we used dynamic causal modeling (DCM) to model effective connectivity of ERP responses to pitch perturbation in voice auditory feedback in musicians with relative pitch (RP), AP, and non-musician controls. We identified a network compromising left and right hemisphere superior temporal gyrus (STG), primary motor cortex (M1), and premotor cortex (PM). We specified nine models and compared two main factors examining various combinations of STG involvement in feedback pitch error detection/correction process. Our results suggest that modulation of left to right STG connections are important in the identification of self-voice error and sensory motor integration in AP musicians. We also identify reduced connectivity of left hemisphere PM to STG connections in AP and RP groups during the error detection and corrections process relative to non-musicians. We suggest that this suppression may allow for enhanced connectivity relating to pitch identification in the right hemisphere in those with more precise pitch matching abilities. Musicians with enhanced pitch identification abilities likely have an improved auditory error detection and correction system involving connectivity of STG regions. Our findings here also suggest that individuals with AP are more adept at using feedback related to pitch from the right hemisphere. PMID:24634644

Automated contouring error detection based on supervised geometric attribute distribution models for radiation therapy: A general strategy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Hsin-Chen; Tan, Jun; Dolly, Steven

2015-02-15

Purpose: One of the most critical steps in radiation therapy treatment is accurate tumor and critical organ-at-risk (OAR) contouring. Both manual and automated contouring processes are prone to errors and to a large degree of inter- and intraobserver variability. These are often due to the limitations of imaging techniques in visualizing human anatomy as well as to inherent anatomical variability among individuals. Physicians/physicists have to reverify all the radiation therapy contours of every patient before using them for treatment planning, which is tedious, laborious, and still not an error-free process. In this study, the authors developed a general strategy basedmore » on novel geometric attribute distribution (GAD) models to automatically detect radiation therapy OAR contouring errors and facilitate the current clinical workflow. Methods: Considering the radiation therapy structures’ geometric attributes (centroid, volume, and shape), the spatial relationship of neighboring structures, as well as anatomical similarity of individual contours among patients, the authors established GAD models to characterize the interstructural centroid and volume variations, and the intrastructural shape variations of each individual structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations calculated from training sets with verified OAR contours. A new iterative weighted GAD model-fitting algorithm was developed for contouring error detection. Receiver operating characteristic (ROC) analysis was employed in a unique way to optimize the model parameters to satisfy clinical requirements. A total of forty-four head-and-neck patient cases, each of which includes nine critical OAR contours, were utilized to demonstrate the proposed strategy. Twenty-nine out of these forty-four patient cases were utilized to train the inter- and intrastructural GAD models. These training data and the remaining fifteen testing

Cost-benefit analysis: newborn screening for inborn errors of metabolism in Lebanon.

PubMed

Khneisser, I; Adib, S; Assaad, S; Megarbane, A; Karam, P

2015-12-01

Few countries in the Middle East-North Africa region have adopted national newborn screening for inborn errors of metabolism by tandem mass spectrometry (MS/MS). We aimed to evaluate the cost-benefit of newborn screening for such disorders in Lebanon, as a model for other developing countries in the region. Average costs of expected care for inborn errors of metabolism cases as a group, between ages 0 and 18, early and late diagnosed, were calculated from 2007 to 2013. The monetary value of early detection using MS/MS was compared with that of clinical "late detection", including cost of diagnosis and hospitalizations. During this period, 126000 newborns were screened. Incidence of detected cases was 1/1482, which can be explained by high consanguinity rates in Lebanon. A reduction by half of direct cost of care, reaching on average 31,631 USD per detected case was shown. This difference more than covers the expense of starting a newborn screening programme. Although this model does not take into consideration the indirect benefits of the better quality of life of those screened early, it can be argued that direct and indirect costs saved through early detection of these disorders are important enough to justify universal publicly-funded screening, especially in developing countries with high consanguinity rates, as shown through this data from Lebanon. © The Author(s) 2015.

Detecting and overcoming systematic errors in genome-scale phylogenies.

PubMed

Rodríguez-Ezpeleta, Naiara; Brinkmann, Henner; Roure, Béatrice; Lartillot, Nicolas; Lang, B Franz; Philippe, Hervé

2007-06-01

Genome-scale data sets result in an enhanced resolution of the phylogenetic inference by reducing stochastic errors. However, there is also an increase of systematic errors due to model violations, which can lead to erroneous phylogenies. Here, we explore the impact of systematic errors on the resolution of the eukaryotic phylogeny using a data set of 143 nuclear-encoded proteins from 37 species. The initial observation was that, despite the impressive amount of data, some branches had no significant statistical support. To demonstrate that this lack of resolution is due to a mutual annihilation of phylogenetic and nonphylogenetic signals, we created a series of data sets with slightly different taxon sampling. As expected, these data sets yielded strongly supported but mutually exclusive trees, thus confirming the presence of conflicting phylogenetic and nonphylogenetic signals in the original data set. To decide on the correct tree, we applied several methods expected to reduce the impact of some kinds of systematic error. Briefly, we show that (i) removing fast-evolving positions, (ii) recoding amino acids into functional categories, and (iii) using a site-heterogeneous mixture model (CAT) are three effective means of increasing the ratio of phylogenetic to nonphylogenetic signal. Finally, our results allow us to formulate guidelines for detecting and overcoming phylogenetic artefacts in genome-scale phylogenetic analyses.

Magneto-optical tracking of flexible laparoscopic ultrasound: model-based online detection and correction of magnetic tracking errors.

PubMed

Feuerstein, Marco; Reichl, Tobias; Vogel, Jakob; Traub, Joerg; Navab, Nassir

2009-06-01

Electromagnetic tracking is currently one of the most promising means of localizing flexible endoscopic instruments such as flexible laparoscopic ultrasound transducers. However, electromagnetic tracking is also susceptible to interference from ferromagnetic material, which distorts the magnetic field and leads to tracking errors. This paper presents new methods for real-time online detection and reduction of dynamic electromagnetic tracking errors when localizing a flexible laparoscopic ultrasound transducer. We use a hybrid tracking setup to combine optical tracking of the transducer shaft and electromagnetic tracking of the flexible transducer tip. A novel approach of modeling the poses of the transducer tip in relation to the transducer shaft allows us to reliably detect and significantly reduce electromagnetic tracking errors. For detecting errors of more than 5 mm, we achieved a sensitivity and specificity of 91% and 93%, respectively. Initial 3-D rms error of 6.91 mm were reduced to 3.15 mm.

Early Forest Fire Detection Using Radio-Acoustic Sounding System

PubMed Central

Sahin, Yasar Guneri; Ince, Turker

2009-01-01

Automated early fire detection systems have recently received a significant amount of attention due to their importance in protecting the global environment. Some emergent technologies such as ground-based, satellite-based remote sensing and distributed sensor networks systems have been used to detect forest fires in the early stages. In this study, a radio-acoustic sounding system with fine space and time resolution capabilities for continuous monitoring and early detection of forest fires is proposed. Simulations show that remote thermal mapping of a particular forest region by the proposed system could be a potential solution to the problem of early detection of forest fires. PMID:22573967

Detecting errors and anomalies in computerized materials control and accountability databases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whiteson, R.; Hench, K.; Yarbro, T.

The Automated MC and A Database Assessment project is aimed at improving anomaly and error detection in materials control and accountability (MC and A) databases and increasing confidence in the data that they contain. Anomalous data resulting in poor categorization of nuclear material inventories greatly reduces the value of the database information to users. Therefore it is essential that MC and A data be assessed periodically for anomalies or errors. Anomaly detection can identify errors in databases and thus provide assurance of the integrity of data. An expert system has been developed at Los Alamos National Laboratory that examines thesemore » large databases for anomalous or erroneous data. For several years, MC and A subject matter experts at Los Alamos have been using this automated system to examine the large amounts of accountability data that the Los Alamos Plutonium Facility generates. These data are collected and managed by the Material Accountability and Safeguards System, a near-real-time computerized nuclear material accountability and safeguards system. This year they have expanded the user base, customizing the anomaly detector for the varying requirements of different groups of users. This paper describes the progress in customizing the expert systems to the needs of the users of the data and reports on their results.« less

Quantum error correction for continuously detected errors with any number of error channels per qubit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahn, Charlene; Wiseman, Howard; Jacobs, Kurt

2004-08-01

It was shown by Ahn, Wiseman, and Milburn [Phys. Rev. A 67, 052310 (2003)] that feedback control could be used as a quantum error correction process for errors induced by weak continuous measurement, given one perfectly measured error channel per qubit. Here we point out that this method can be easily extended to an arbitrary number of error channels per qubit. We show that the feedback protocols generated by our method encode n-2 logical qubits in n physical qubits, thus requiring just one more physical qubit than in the previous case.

SU-E-T-310: Targeting Safety Improvements Through Analysis of Near-Miss Error Detection Points in An Incident Learning Database

DOE Office of Scientific and Technical Information (OSTI.GOV)

Novak, A; Nyflot, M; Sponseller, P

2014-06-01

Purpose: Radiation treatment planning involves a complex workflow that can make safety improvement efforts challenging. This study utilizes an incident reporting system to identify detection points of near-miss errors, in order to guide our departmental safety improvement efforts. Previous studies have examined where errors arise, but not where they are detected or their patterns. Methods: 1377 incidents were analyzed from a departmental nearmiss error reporting system from 3/2012–10/2013. All incidents were prospectively reviewed weekly by a multi-disciplinary team, and assigned a near-miss severity score ranging from 0–4 reflecting potential harm (no harm to critical). A 98-step consensus workflow was usedmore » to determine origination and detection points of near-miss errors, categorized into 7 major steps (patient assessment/orders, simulation, contouring/treatment planning, pre-treatment plan checks, therapist/on-treatment review, post-treatment checks, and equipment issues). Categories were compared using ANOVA. Results: In the 7-step workflow, 23% of near-miss errors were detected within the same step in the workflow, while an additional 37% were detected by the next step in the workflow, and 23% were detected two steps downstream. Errors detected further from origination were more severe (p<.001; Figure 1). The most common source of near-miss errors was treatment planning/contouring, with 476 near misses (35%). Of those 476, only 72(15%) were found before leaving treatment planning, 213(45%) were found at physics plan checks, and 191(40%) were caught at the therapist pre-treatment chart review or on portal imaging. Errors that passed through physics plan checks and were detected by therapists were more severe than other errors originating in contouring/treatment planning (1.81 vs 1.33, p<0.001). Conclusion: Errors caught by radiation treatment therapists tend to be more severe than errors caught earlier in the workflow, highlighting the importance of

Spatial Support Vector Regression to Detect Silent Errors in the Exascale Era

DOE Office of Scientific and Technical Information (OSTI.GOV)

Subasi, Omer; Di, Sheng; Bautista-Gomez, Leonardo

As the exascale era approaches, the increasing capacity of high-performance computing (HPC) systems with targeted power and energy budget goals introduces significant challenges in reliability. Silent data corruptions (SDCs) or silent errors are one of the major sources that corrupt the executionresults of HPC applications without being detected. In this work, we explore a low-memory-overhead SDC detector, by leveraging epsilon-insensitive support vector machine regression, to detect SDCs that occur in HPC applications that can be characterized by an impact error bound. The key contributions are three fold. (1) Our design takes spatialfeatures (i.e., neighbouring data values for each data pointmore » in a snapshot) into training data, such that little memory overhead (less than 1%) is introduced. (2) We provide an in-depth study on the detection ability and performance with different parameters, and we optimize the detection range carefully. (3) Experiments with eight real-world HPC applications show thatour detector can achieve the detection sensitivity (i.e., recall) up to 99% yet suffer a less than 1% of false positive rate for most cases. Our detector incurs low performance overhead, 5% on average, for all benchmarks studied in the paper. Compared with other state-of-the-art techniques, our detector exhibits the best tradeoff considering the detection ability and overheads.« less

Hybrid light transport model based bioluminescence tomography reconstruction for early gastric cancer detection

NASA Astrophysics Data System (ADS)

Chen, Xueli; Liang, Jimin; Hu, Hao; Qu, Xiaochao; Yang, Defu; Chen, Duofang; Zhu, Shouping; Tian, Jie

2012-03-01

Gastric cancer is the second cause of cancer-related death in the world, and it remains difficult to cure because it has been in late-stage once that is found. Early gastric cancer detection becomes an effective approach to decrease the gastric cancer mortality. Bioluminescence tomography (BLT) has been applied to detect early liver cancer and prostate cancer metastasis. However, the gastric cancer commonly originates from the gastric mucosa and grows outwards. The bioluminescent light will pass through a non-scattering region constructed by gastric pouch when it transports in tissues. Thus, the current BLT reconstruction algorithms based on the approximation model of radiative transfer equation are not optimal to handle this problem. To address the gastric cancer specific problem, this paper presents a novel reconstruction algorithm that uses a hybrid light transport model to describe the bioluminescent light propagation in tissues. The radiosity theory integrated with the diffusion equation to form the hybrid light transport model is utilized to describe light propagation in the non-scattering region. After the finite element discretization, the hybrid light transport model is converted into a minimization problem which fuses an l1 norm based regularization term to reveal the sparsity of bioluminescent source distribution. The performance of the reconstruction algorithm is first demonstrated with a digital mouse based simulation with the reconstruction error less than 1mm. An in situ gastric cancer-bearing nude mouse based experiment is then conducted. The primary result reveals the ability of the novel BLT reconstruction algorithm in early gastric cancer detection.

Early detection and intervention for attention-deficit/hyperactivity disorder.

PubMed

Sonuga-Barke, Edmund J S; Koerting, Johanna; Smith, Elizabeth; McCann, Donna C; Thompson, Margaret

2011-04-01

Attention-deficit/hyperactivity disorder (ADHD) is a high-cost/high-burden disorder. Early detection and intervention may prevent or ameliorate the development of the disorder and reduce its long-term impact. In this article, we set out a rationale for an early detection and intervention program. First, we highlight the costs of the condition and second, we discuss the limitations of the current treatments. We then outline the potential value of an early detection and intervention program. We review evidence on predictors of poor outcomes for early ADHD signs and discuss how these might allow us to target early intervention more cost-effectively. We then examine potential barriers to engagement with at-risk samples. This leads to a discussion of possible intervention approaches and how these could be improved. Finally, we describe the Program for Early Detection and Intervention for ADHD (PEDIA), a 5-year program of research supported by the UK National Institute for Health Research and conducted at the University of Southampton (Southampton, UK), which aims to develop and evaluate a strategy for early intervention.

Updating of aversive memories after temporal error detection is differentially modulated by mTOR across development

PubMed Central

Tallot, Lucille; Diaz-Mataix, Lorenzo; Perry, Rosemarie E.; Wood, Kira; LeDoux, Joseph E.; Mouly, Anne-Marie; Sullivan, Regina M.; Doyère, Valérie

2017-01-01

The updating of a memory is triggered whenever it is reactivated and a mismatch from what is expected (i.e., prediction error) is detected, a process that can be unraveled through the memory's sensitivity to protein synthesis inhibitors (i.e., reconsolidation). As noted in previous studies, in Pavlovian threat/aversive conditioning in adult rats, prediction error detection and its associated protein synthesis-dependent reconsolidation can be triggered by reactivating the memory with the conditioned stimulus (CS), but without the unconditioned stimulus (US), or by presenting a CS–US pairing with a different CS–US interval than during the initial learning. Whether similar mechanisms underlie memory updating in the young is not known. Using similar paradigms with rapamycin (an mTORC1 inhibitor), we show that preweaning rats (PN18–20) do form a long-term memory of the CS–US interval, and detect a 10-sec versus 30-sec temporal prediction error. However, the resulting updating/reconsolidation processes become adult-like after adolescence (PN30–40). Our results thus show that while temporal prediction error detection exists in preweaning rats, specific infant-type mechanisms are at play for associative learning and memory. PMID:28202715

ADEPT, a dynamic next generation sequencing data error-detection program with trimming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Shihai; Lo, Chien-Chi; Li, Po-E

Illumina is the most widely used next generation sequencing technology and produces millions of short reads that contain errors. These sequencing errors constitute a major problem in applications such as de novo genome assembly, metagenomics analysis and single nucleotide polymorphism discovery. In this study, we present ADEPT, a dynamic error detection method, based on the quality scores of each nucleotide and its neighboring nucleotides, together with their positions within the read and compares this to the position-specific quality score distribution of all bases within the sequencing run. This method greatly improves upon other available methods in terms of the truemore » positive rate of error discovery without affecting the false positive rate, particularly within the middle of reads. We conclude that ADEPT is the only tool to date that dynamically assesses errors within reads by comparing position-specific and neighboring base quality scores with the distribution of quality scores for the dataset being analyzed. The result is a method that is less prone to position-dependent under-prediction, which is one of the most prominent issues in error prediction. The outcome is that ADEPT improves upon prior efforts in identifying true errors, primarily within the middle of reads, while reducing the false positive rate.« less

ADEPT, a dynamic next generation sequencing data error-detection program with trimming

DOE PAGES

Feng, Shihai; Lo, Chien-Chi; Li, Po-E; ...

2016-02-29

Illumina is the most widely used next generation sequencing technology and produces millions of short reads that contain errors. These sequencing errors constitute a major problem in applications such as de novo genome assembly, metagenomics analysis and single nucleotide polymorphism discovery. In this study, we present ADEPT, a dynamic error detection method, based on the quality scores of each nucleotide and its neighboring nucleotides, together with their positions within the read and compares this to the position-specific quality score distribution of all bases within the sequencing run. This method greatly improves upon other available methods in terms of the truemore » positive rate of error discovery without affecting the false positive rate, particularly within the middle of reads. We conclude that ADEPT is the only tool to date that dynamically assesses errors within reads by comparing position-specific and neighboring base quality scores with the distribution of quality scores for the dataset being analyzed. The result is a method that is less prone to position-dependent under-prediction, which is one of the most prominent issues in error prediction. The outcome is that ADEPT improves upon prior efforts in identifying true errors, primarily within the middle of reads, while reducing the false positive rate.« less

Detecting wrong notes in advance: neuronal correlates of error monitoring in pianists.

PubMed

Ruiz, María Herrojo; Jabusch, Hans-Christian; Altenmüller, Eckart

2009-11-01

Music performance is an extremely rapid process with low incidence of errors even at the fast rates of production required. This is possible only due to the fast functioning of the self-monitoring system. Surprisingly, no specific data about error monitoring have been published in the music domain. Consequently, the present study investigated the electrophysiological correlates of executive control mechanisms, in particular error detection, during piano performance. Our target was to extend the previous research efforts on understanding of the human action-monitoring system by selecting a highly skilled multimodal task. Pianists had to retrieve memorized music pieces at a fast tempo in the presence or absence of auditory feedback. Our main interest was to study the interplay between auditory and sensorimotor information in the processes triggered by an erroneous action, considering only wrong pitches as errors. We found that around 70 ms prior to errors a negative component is elicited in the event-related potentials and is generated by the anterior cingulate cortex. Interestingly, this component was independent of the auditory feedback. However, the auditory information did modulate the processing of the errors after their execution, as reflected in a larger error positivity (Pe). Our data are interpreted within the context of feedforward models and the auditory-motor coupling.

Deep Recurrent Neural Networks for seizure detection and early seizure detection systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Talathi, S. S.

Epilepsy is common neurological diseases, affecting about 0.6-0.8 % of world population. Epileptic patients suffer from chronic unprovoked seizures, which can result in broad spectrum of debilitating medical and social consequences. Since seizures, in general, occur infrequently and are unpredictable, automated seizure detection systems are recommended to screen for seizures during long-term electroencephalogram (EEG) recordings. In addition, systems for early seizure detection can lead to the development of new types of intervention systems that are designed to control or shorten the duration of seizure events. In this article, we investigate the utility of recurrent neural networks (RNNs) in designing seizuremore » detection and early seizure detection systems. We propose a deep learning framework via the use of Gated Recurrent Unit (GRU) RNNs for seizure detection. We use publicly available data in order to evaluate our method and demonstrate very promising evaluation results with overall accuracy close to 100 %. We also systematically investigate the application of our method for early seizure warning systems. Our method can detect about 98% of seizure events within the first 5 seconds of the overall epileptic seizure duration.« less

Automated documentation error detection and notification improves anesthesia billing performance.

PubMed

Spring, Stephen F; Sandberg, Warren S; Anupama, Shaji; Walsh, John L; Driscoll, William D; Raines, Douglas E

2007-01-01

Documentation of key times and events is required to obtain reimbursement for anesthesia services. The authors installed an information management system to improve record keeping and billing performance but found that a significant number of their records still could not be billed in a timely manner, and some records were never billed at all because they contained documentation errors. Computer software was developed that automatically examines electronic anesthetic records and alerts clinicians to documentation errors by alphanumeric page and e-mail. The software's efficacy was determined retrospectively by comparing billing performance before and after its implementation. Staff satisfaction with the software was assessed by survey. After implementation of this software, the percentage of anesthetic records that could never be billed declined from 1.31% to 0.04%, and the median time to correct documentation errors decreased from 33 days to 3 days. The average time to release an anesthetic record to the billing service decreased from 3.0+/-0.1 days to 1.1+/-0.2 days. More than 90% of staff found the system to be helpful and easier to use than the previous manual process for error detection and notification. This system allowed the authors to reduce the median time to correct documentation errors and the number of anesthetic records that were never billed by at least an order of magnitude. The authors estimate that these improvements increased their department's revenue by approximately $400,000 per year.

Detection and correction of prescription errors by an emergency department pharmacy service.

PubMed

Stasiak, Philip; Afilalo, Marc; Castelino, Tanya; Xue, Xiaoqing; Colacone, Antoinette; Soucy, Nathalie; Dankoff, Jerrald

2014-05-01

Emergency departments (EDs) are recognized as a high-risk setting for prescription errors. Pharmacist involvement may be important in reviewing prescriptions to identify and correct errors. The objectives of this study were to describe the frequency and type of prescription errors detected by pharmacists in EDs, determine the proportion of errors that could be corrected, and identify factors associated with prescription errors. This prospective observational study was conducted in a tertiary care teaching ED on 25 consecutive weekdays. Pharmacists reviewed all documented prescriptions and flagged and corrected errors for patients in the ED. We collected information on patient demographics, details on prescription errors, and the pharmacists' recommendations. A total of 3,136 ED prescriptions were reviewed. The proportion of prescriptions in which a pharmacist identified an error was 3.2% (99 of 3,136; 95% confidence interval [CI] 2.5-3.8). The types of identified errors were wrong dose (28 of 99, 28.3%), incomplete prescription (27 of 99, 27.3%), wrong frequency (15 of 99, 15.2%), wrong drug (11 of 99, 11.1%), wrong route (1 of 99, 1.0%), and other (17 of 99, 17.2%). The pharmacy service intervened and corrected 78 (78 of 99, 78.8%) errors. Factors associated with prescription errors were patient age over 65 (odds ratio [OR] 2.34; 95% CI 1.32-4.13), prescriptions with more than one medication (OR 5.03; 95% CI 2.54-9.96), and those written by emergency medicine residents compared to attending emergency physicians (OR 2.21, 95% CI 1.18-4.14). Pharmacists in a tertiary ED are able to correct the majority of prescriptions in which they find errors. Errors are more likely to be identified in prescriptions written for older patients, those containing multiple medication orders, and those prescribed by emergency residents.

Improved assessment of multiple sclerosis lesion segmentation agreement via detection and outline error estimates

PubMed Central

2012-01-01

Background Presented is the method “Detection and Outline Error Estimates” (DOEE) for assessing rater agreement in the delineation of multiple sclerosis (MS) lesions. The DOEE method divides operator or rater assessment into two parts: 1) Detection Error (DE) -- rater agreement in detecting the same regions to mark, and 2) Outline Error (OE) -- agreement of the raters in outlining of the same lesion. Methods DE, OE and Similarity Index (SI) values were calculated for two raters tested on a set of 17 fluid-attenuated inversion-recovery (FLAIR) images of patients with MS. DE, OE, and SI values were tested for dependence with mean total area (MTA) of the raters' Region of Interests (ROIs). Results When correlated with MTA, neither DE (ρ = .056, p=.83) nor the ratio of OE to MTA (ρ = .23, p=.37), referred to as Outline Error Rate (OER), exhibited significant correlation. In contrast, SI is found to be strongly correlated with MTA (ρ = .75, p < .001). Furthermore, DE and OER values can be used to model the variation in SI with MTA. Conclusions The DE and OER indices are proposed as a better method than SI for comparing rater agreement of ROIs, which also provide specific information for raters to improve their agreement. PMID:22812697

Estimation for aerial detection effectiveness with cooperation efficiency factors of early-warning aircraft in early-warning detection SoS under BSC framework

NASA Astrophysics Data System (ADS)

Zhu, Feng; Hu, Xiaofeng; He, Xiaoyuan; Guo, Rui; Li, Kaiming; Yang, Lu

2017-11-01

In the military field, the performance evaluation of early-warning aircraft deployment or construction is always an important problem needing to be explored. As an effective approach of enterprise management and performance evaluation, Balanced Score Card (BSC) attracts more and more attentions and is studied more and more widely all over the world. It can also bring feasible ideas and technical approaches for studying the issue of the performance evaluation of the deployment or construction of early-warning aircraft which is the important component in early-warning detection system of systems (SoS). Therefore, the deep explored researches are carried out based on the previously research works. On the basis of the characteristics of space exploration and aerial detection effectiveness of early-warning detection SoS and the cardinal principle of BSC are analyzed simply, and the performance evaluation framework of the deployment or construction of early-warning aircraft is given, under this framework, aimed at the evaluation issue of aerial detection effectiveness of early-warning detection SoS with the cooperation efficiency factors of the early-warning aircraft and other land based radars, the evaluation indexes are further designed and the relative evaluation model is further established, especially the evaluation radar chart being also drawn to obtain the evaluation results from a direct sight angle. Finally, some practical computer simulations are launched to prove the validity and feasibility of the research thinking and technologic approaches which are proposed in the paper.

About the Early Detection Research Group | Division of Cancer Prevention

Cancer.gov

The Early Detection Research Group supports research that seeks to determine the effectiveness, operating characteristics and clinical impact (harms as well as benefits) of cancer early detection technologies and practices, such as imaging and molecular biomarker approaches.   The group ran two large-scale early detection trials for which data and biospecimens are available

Evaluating Fluorscence-Based Metrics for Early Detection of ...

EPA Pesticide Factsheets

Summary: This paper discusses the results of an ongoing Water Research Foundation project on developing a fluorescence sensor system for early detection of distribution system nitrification Summary: This paper discusses the results of an ongoing Water Research Foundation project on developing a fluorescence sensor system for early detection of distribution system nitrification

Characterizing a four-qubit planar lattice for arbitrary error detection

NASA Astrophysics Data System (ADS)

Chow, Jerry M.; Srinivasan, Srikanth J.; Magesan, Easwar; Córcoles, A. D.; Abraham, David W.; Gambetta, Jay M.; Steffen, Matthias

2015-05-01

Quantum error correction will be a necessary component towards realizing scalable quantum computers with physical qubits. Theoretically, it is possible to perform arbitrarily long computations if the error rate is below a threshold value. The two-dimensional surface code permits relatively high fault-tolerant thresholds at the ~1% level, and only requires a latticed network of qubits with nearest-neighbor interactions. Superconducting qubits have continued to steadily improve in coherence, gate, and readout fidelities, to become a leading candidate for implementation into larger quantum networks. Here we describe characterization experiments and calibration of a system of four superconducting qubits arranged in a planar lattice, amenable to the surface code. Insights into the particular qubit design and comparison between simulated parameters and experimentally determined parameters are given. Single- and two-qubit gate tune-up procedures are described and results for simultaneously benchmarking pairs of two-qubit gates are given. All controls are eventually used for an arbitrary error detection protocol described in separate work [Corcoles et al., Nature Communications, 6, 2015].

Structural and Functional Evaluations for the Early Detection of Glaucoma.

PubMed

Lucy, Katie A; Wollstein, Gadi

2016-01-01

The early detection of glaucoma is imperative in order to preserve functional vision. Structural and functional methods are utilized to detect and monitor glaucomatous damage and the vision loss it causes. The relationship between these detection measures is complex and differs between individuals, especially in early glaucoma. Using both measures together is advised in order to ensure the highest probability of glaucoma detection, and new testing methods are continuously developed with the goals of earlier disease detection and improvement of disease monitoring. The purpose of this review is to explore the relationship between structural and functional glaucoma detection and discuss important technological advances for early glaucoma detection.

Structural and Functional Evaluations for the Early Detection of Glaucoma

PubMed Central

Lucy, Katie A.; Wollstein, Gadi

2016-01-01

The early detection of glaucoma is imperative in order to preserve functional vision. Structural and functional methods are utilized to detect and monitor glaucomatous damage and the vision loss it causes. The relationship between these detection measures is complex and differs between individuals, especially in early glaucoma. Using both measures together is advised in order to ensure the highest probability of glaucoma detection, and new testing methods are continuously developed with the goals of earlier disease detection and improvement of disease monitoring. The purpose of this review is to explore the relationship between structural and functional glaucoma detection and discuss important technological advances for early glaucoma detection. PMID:28603546

A Corpus-Based System of Error Detection and Revision Suggestion for Spanish Learners in Taiwan: A Case Study

ERIC Educational Resources Information Center

Lu, Hui-Chuan; Chu, Yu-Hsin; Chang, Cheng-Yu

2013-01-01

Compared with English learners, Spanish learners have fewer resources for automatic error detection and revision and following the current integrative Computer Assisted Language Learning (CALL), we combined corpus-based approach and CALL to create the System of Error Detection and Revision Suggestion (SEDRS) for learning Spanish. Through…

Using Block-local Atomicity to Detect Stale-value Concurrency Errors

NASA Technical Reports Server (NTRS)

Artho, Cyrille; Havelund, Klaus; Biere, Armin

2004-01-01

Data races do not cover all kinds of concurrency errors. This paper presents a data-flow-based technique to find stale-value errors, which are not found by low-level and high-level data race algorithms. Stale values denote copies of shared data where the copy is no longer synchronized. The algorithm to detect such values works as a consistency check that does not require any assumptions or annotations of the program. It has been implemented as a static analysis in JNuke. The analysis is sound and requires only a single execution trace if implemented as a run-time checking algorithm. Being based on an analysis of Java bytecode, it encompasses the full program semantics, including arbitrarily complex expressions. Related techniques are more complex and more prone to over-reporting.

Strategies for early detection of resectable pancreatic cancer

PubMed Central

Okano, Keiichi; Suzuki, Yasuyuki

2014-01-01

Pancreatic cancer is difficult to diagnose at an early stage and generally has a poor prognosis. Surgical resection is the only potentially curative treatment for pancreatic carcinoma. To improve the prognosis of this disease, it is essential to detect tumors at early stages, when they are resectable. The optimal approach to screening for early pancreatic neoplasia has not been established. The International Cancer of the Pancreas Screening Consortium has recently finalized several recommendations regarding the management of patients who are at an increased risk of familial pancreatic cancer. In addition, there have been notable advances in research on serum markers, tissue markers, gene signatures, and genomic targets of pancreatic cancer. To date, however, no biomarkers have been established in the clinical setting. Advancements in imaging modalities touch all aspects of the clinical management of pancreatic diseases, including the early detection of pancreatic masses, their characterization, and evaluations of tumor resectability. This article reviews strategies for screening high-risk groups, biomarkers, and current advances in imaging modalities for the early detection of resectable pancreatic cancer. PMID:25170207

Early detection of non-native fishes using fish larvae

EPA Science Inventory

Our objective was to evaluate the use of fish larvae for early detection of non-native fishes, comparing traditional and molecular taxonomy approaches to investigate potential efficiencies. Fish larvae present an interesting opportunity for non-native fish early detection. First,...

Modelling exoplanet detection with the LUVOIR Coronagraph: aberration sensitivity and error tolerances

NASA Astrophysics Data System (ADS)

Juanola-Parramon, Roser; Zimmerman, Neil; Bolcar, Matthew R.; Rizzo, Maxime; Roberge, Aki

2018-01-01

The Coronagraph is a key instrument on the Large UV-Optical-Infrared (LUVOIR) Surveyor mission concept. The Apodized Pupil Lyot Coronagraph (APLC) is one of the baselined mask technologies to enable 1E10 contrast observations in the habitable zones of nearby stars. Both the LUVOIR architectures A and B present a segmented aperture as input pupil, introducing a set of random tip/tilt and piston errors, among others, that greatly affect the performance of the coronagraph instrument by increasing the wavefront errors hence reducing the instrument sensitivity. In this poster we present the latest results of the simulation of these effects for different working angle regions and discuss the achieved contrast for exoplanet detection and characterization, including simulated observations under these circumstances, setting boundaries for the tolerance of such errors.

Concurrent error detecting codes for arithmetic processors

NASA Technical Reports Server (NTRS)

Lim, R. S.

1979-01-01

A method of concurrent error detection for arithmetic processors is described. Low-cost residue codes with check-length l and checkbase m = 2 to the l power - 1 are described for checking arithmetic operations of addition, subtraction, multiplication, division complement, shift, and rotate. Of the three number representations, the signed-magnitude representation is preferred for residue checking. Two methods of residue generation are described: the standard method of using modulo m adders and the method of using a self-testing residue tree. A simple single-bit parity-check code is described for checking the logical operations of XOR, OR, and AND, and also the arithmetic operations of complement, shift, and rotate. For checking complement, shift, and rotate, the single-bit parity-check code is simpler to implement than the residue codes.

Composite Interval Mapping Based on Lattice Design for Error Control May Increase Power of Quantitative Trait Locus Detection.

PubMed

He, Jianbo; Li, Jijie; Huang, Zhongwen; Zhao, Tuanjie; Xing, Guangnan; Gai, Junyi; Guan, Rongzhan

2015-01-01

Experimental error control is very important in quantitative trait locus (QTL) mapping. Although numerous statistical methods have been developed for QTL mapping, a QTL detection model based on an appropriate experimental design that emphasizes error control has not been developed. Lattice design is very suitable for experiments with large sample sizes, which is usually required for accurate mapping of quantitative traits. However, the lack of a QTL mapping method based on lattice design dictates that the arithmetic mean or adjusted mean of each line of observations in the lattice design had to be used as a response variable, resulting in low QTL detection power. As an improvement, we developed a QTL mapping method termed composite interval mapping based on lattice design (CIMLD). In the lattice design, experimental errors are decomposed into random errors and block-within-replication errors. Four levels of block-within-replication errors were simulated to show the power of QTL detection under different error controls. The simulation results showed that the arithmetic mean method, which is equivalent to a method under random complete block design (RCBD), was very sensitive to the size of the block variance and with the increase of block variance, the power of QTL detection decreased from 51.3% to 9.4%. In contrast to the RCBD method, the power of CIMLD and the adjusted mean method did not change for different block variances. The CIMLD method showed 1.2- to 7.6-fold higher power of QTL detection than the arithmetic or adjusted mean methods. Our proposed method was applied to real soybean (Glycine max) data as an example and 10 QTLs for biomass were identified that explained 65.87% of the phenotypic variation, while only three and two QTLs were identified by arithmetic and adjusted mean methods, respectively.

Runtime Detection of C-Style Errors in UPC Code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pirkelbauer, P; Liao, C; Panas, T

2011-09-29

Unified Parallel C (UPC) extends the C programming language (ISO C 99) with explicit parallel programming support for the partitioned global address space (PGAS), which provides a global memory space with localized partitions to each thread. Like its ancestor C, UPC is a low-level language that emphasizes code efficiency over safety. The absence of dynamic (and static) safety checks allows programmer oversights and software flaws that can be hard to spot. In this paper, we present an extension of a dynamic analysis tool, ROSE-Code Instrumentation and Runtime Monitor (ROSECIRM), for UPC to help programmers find C-style errors involving the globalmore » address space. Built on top of the ROSE source-to-source compiler infrastructure, the tool instruments source files with code that monitors operations and keeps track of changes to the system state. The resulting code is linked to a runtime monitor that observes the program execution and finds software defects. We describe the extensions to ROSE-CIRM that were necessary to support UPC. We discuss complications that arise from parallel code and our solutions. We test ROSE-CIRM against a runtime error detection test suite, and present performance results obtained from running error-free codes. ROSE-CIRM is released as part of the ROSE compiler under a BSD-style open source license.« less

Detecting and Correcting Errors in Rapid Aiming Movements: Effects of Movement Time, Distance, and Velocity

ERIC Educational Resources Information Center

Sherwood, David E.

2010-01-01

According to closed-loop accounts of motor control, movement errors are detected by comparing sensory feedback to an acquired reference state. Differences between the reference state and the movement-produced feedback results in an error signal that serves as a basis for a correction. The main question addressed in the current study was how…

Automatic-repeat-request error control schemes

NASA Technical Reports Server (NTRS)

Lin, S.; Costello, D. J., Jr.; Miller, M. J.

1983-01-01

Error detection incorporated with automatic-repeat-request (ARQ) is widely used for error control in data communication systems. This method of error control is simple and provides high system reliability. If a properly chosen code is used for error detection, virtually error-free data transmission can be attained. Various types of ARQ and hybrid ARQ schemes, and error detection using linear block codes are surveyed.

One-Class Classification-Based Real-Time Activity Error Detection in Smart Homes.

PubMed

Das, Barnan; Cook, Diane J; Krishnan, Narayanan C; Schmitter-Edgecombe, Maureen

2016-08-01

Caring for individuals with dementia is frequently associated with extreme physical and emotional stress, which often leads to depression. Smart home technology and advances in machine learning techniques can provide innovative solutions to reduce caregiver burden. One key service that caregivers provide is prompting individuals with memory limitations to initiate and complete daily activities. We hypothesize that sensor technologies combined with machine learning techniques can automate the process of providing reminder-based interventions. The first step towards automated interventions is to detect when an individual faces difficulty with activities. We propose machine learning approaches based on one-class classification that learn normal activity patterns. When we apply these classifiers to activity patterns that were not seen before, the classifiers are able to detect activity errors, which represent potential prompt situations. We validate our approaches on smart home sensor data obtained from older adult participants, some of whom faced difficulties performing routine activities and thus committed errors.

Strategies for early melanoma detection: approaches to the patient with nevi

PubMed Central

Goodson, Agnessa G.; Grossman, Douglas

2009-01-01

Given its propensity to metastasize, and lack of effective therapies for most patients with advanced disease, early detection of melanoma is a clinical imperative. Although there are no non-invasive techniques for definitive diagnosis of melanoma, and the “gold standard” remains biopsy with histologic examination, a variety of modalities may facilitate early melanoma diagnosis and the detection of new and changing nevi. This article reviews general clinical principles of early melanoma detection, and various modalities that are currently available or on the horizon, providing the clinician with an up-to-date understanding of management strategies for their patients with numerous or atypical nevi. Learning objectives At the conclusion of this learning activity, participants should: 1) understand the clinical importance of early melanoma detection; 2) appreciate the challenges of early melanoma diagnosis and which patients are at highest risk; 3) know general principles of early melanoma detection; 4) be familiar with current and emerging modalities that may facilitate early melanoma diagnosis and the detection of new and changing nevi; 5) know the advantages and limitations of each modality; and 6) be able to practice a combined approach to the patient with numerous or clinically atypical nevi. PMID:19389517

A representation for error detection and recovery in robot task plans

NASA Technical Reports Server (NTRS)

Lyons, D. M.; Vijaykumar, R.; Venkataraman, S. T.

1990-01-01

A general definition is given of the problem of error detection and recovery in robot assembly systems, and a general representation is developed for dealing with the problem. This invariant representation involves a monitoring process which is concurrent, with one monitor per task plan. A plan hierarchy is discussed, showing how diagnosis and recovery can be handled using the representation.

Detecting Role Errors in the Gene Hierarchy of the NCI Thesaurus

PubMed Central

Min, Hua; Cohen, Barry; Halper, Michael; Oren, Marc; Perl, Yehoshua

2008-01-01

Gene terminologies are playing an increasingly important role in the ever-growing field of genomic research. While errors in large, complex terminologies are inevitable, gene terminologies are even more susceptible to them due to the rapid growth of genomic knowledge and the nature of its discovery. It is therefore very important to establish quality-assurance protocols for such genomic-knowledge repositories. Different kinds of terminologies oftentimes require auditing methodologies adapted to their particular structures. In light of this, an auditing methodology tailored to the characteristics of the NCI Thesaurus’s (NCIT’s) Gene hierarchy is presented. The Gene hierarchy is of particular interest to the NCIT’s designers due to the primary role of genomics in current cancer research. This multiphase methodology focuses on detecting role-errors, such as missing roles or roles with incorrect or incomplete target structures, occurring within that hierarchy. The methodology is based on two kinds of abstraction networks, called taxonomies, that highlight the role distribution among concepts within the IS-A (subsumption) hierarchy. These abstract views tend to highlight portions of the hierarchy having a higher concentration of errors. The errors found during an application of the methodology are reported. Hypotheses pertaining to the efficacy of our methodology are investigated. PMID:19221606

Procedural error monitoring and smart checklists

NASA Technical Reports Server (NTRS)

Palmer, Everett

1990-01-01

Human beings make and usually detect errors routinely. The same mental processes that allow humans to cope with novel problems can also lead to error. Bill Rouse has argued that errors are not inherently bad but their consequences may be. He proposes the development of error-tolerant systems that detect errors and take steps to prevent the consequences of the error from occurring. Research should be done on self and automatic detection of random and unanticipated errors. For self detection, displays should be developed that make the consequences of errors immediately apparent. For example, electronic map displays graphically show the consequences of horizontal flight plan entry errors. Vertical profile displays should be developed to make apparent vertical flight planning errors. Other concepts such as energy circles could also help the crew detect gross flight planning errors. For automatic detection, systems should be developed that can track pilot activity, infer pilot intent and inform the crew of potential errors before their consequences are realized. Systems that perform a reasonableness check on flight plan modifications by checking route length and magnitude of course changes are simple examples. Another example would be a system that checked the aircraft's planned altitude against a data base of world terrain elevations. Information is given in viewgraph form.

Red-breasted nuthatches detect early increases in spruce budworm populations

Treesearch

Hewlette S. Crawford; Daniel T. Jennings; Timothy L. Stone

1990-01-01

Early suppression .of increasing spruce budworm populations is essential to prevent epidemics; however, early changes in budworm numbers are difficult to detect. An effective and inexpensive method to detect early increases is needed. Red-breasted nuthatches eat more spruce budworm larvae and pupae as the insect increases in number. We estimated the number of large...

Action errors, error management, and learning in organizations.

PubMed

Frese, Michael; Keith, Nina

2015-01-03

Every organization is confronted with errors. Most errors are corrected easily, but some may lead to negative consequences. Organizations often focus on error prevention as a single strategy for dealing with errors. Our review suggests that error prevention needs to be supplemented by error management--an approach directed at effectively dealing with errors after they have occurred, with the goal of minimizing negative and maximizing positive error consequences (examples of the latter are learning and innovations). After defining errors and related concepts, we review research on error-related processes affected by error management (error detection, damage control). Empirical evidence on positive effects of error management in individuals and organizations is then discussed, along with emotional, motivational, cognitive, and behavioral pathways of these effects. Learning from errors is central, but like other positive consequences, learning occurs under certain circumstances--one being the development of a mind-set of acceptance of human error.

Sweet-spot training for early esophageal cancer detection

NASA Astrophysics Data System (ADS)

van der Sommen, Fons; Zinger, Svitlana; Schoon, Erik J.; de With, Peter H. N.

2016-03-01

Over the past decade, the imaging tools for endoscopists have improved drastically. This has enabled physicians to visually inspect the intestinal tissue for early signs of malignant lesions. Besides this, recent studies show the feasibility of supportive image analysis for endoscopists, but the analysis problem is typically approached as a segmentation task where binary ground truth is employed. In this study, we show that the detection of early cancerous tissue in the gastrointestinal tract cannot be approached as a binary segmentation problem and it is crucial and clinically relevant to involve multiple experts for annotating early lesions. By employing the so-called sweet spot for training purposes as a metric, a much better detection performance can be achieved. Furthermore, a multi-expert-based ground truth, i.e. a golden standard, enables an improved validation of the resulting delineations. For this purpose, besides the sweet spot we also propose another novel metric, the Jaccard Golden Standard (JIGS) that can handle multiple ground-truth annotations. Our experiments involving these new metrics and based on the golden standard show that the performance of a detection algorithm of early neoplastic lesions in Barrett's esophagus can be increased significantly, demonstrating a 10 percent point increase in the resulting F1 detection score.

Error detection and response adjustment in youth with mild spastic cerebral palsy: an event-related brain potential study.

PubMed

Hakkarainen, Elina; Pirilä, Silja; Kaartinen, Jukka; van der Meere, Jaap J

2013-06-01

This study evaluated the brain activation state during error making in youth with mild spastic cerebral palsy and a peer control group while carrying out a stimulus recognition task. The key question was whether patients were detecting their own errors and subsequently improving their performance in a future trial. Findings indicated that error responses of the group with cerebral palsy were associated with weak motor preparation, as indexed by the amplitude of the late contingent negative variation. However, patients were detecting their errors as indexed by the amplitude of the response-locked negativity and thus improved their performance in a future trial. Findings suggest that the consequence of error making on future performance is intact in a sample of youth with mild spastic cerebral palsy. Because the study group is small, the present findings need replication using a larger sample.

SU-E-T-392: Evaluation of Ion Chamber/film and Log File Based QA to Detect Delivery Errors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nelson, C; Mason, B; Kirsner, S

2015-06-15

Purpose: Ion chamber and film (ICAF) is a method used to verify patient dose prior to treatment. More recently, log file based QA has been shown as an alternative for measurement based QA. In this study, we delivered VMAT plans with and without errors to determine if ICAF and/or log file based QA was able to detect the errors. Methods: Using two VMAT patients, the original treatment plan plus 7 additional plans with delivery errors introduced were generated and delivered. The erroneous plans had gantry, collimator, MLC, gantry and collimator, collimator and MLC, MLC and gantry, and gantry, collimator, andmore » MLC errors. The gantry and collimator errors were off by 4{sup 0} for one of the two arcs. The MLC error introduced was one in which the opening aperture didn’t move throughout the delivery of the field. For each delivery, an ICAF measurement was made as well as a dose comparison based upon log files. Passing criteria to evaluate the plans were ion chamber less and 5% and film 90% of pixels pass the 3mm/3% gamma analysis(GA). For log file analysis 90% of voxels pass the 3mm/3% 3D GA and beam parameters match what was in the plan. Results: Two original plans were delivered and passed both ICAF and log file base QA. Both ICAF and log file QA met the dosimetry criteria on 4 of the 12 erroneous cases analyzed (2 cases were not analyzed). For the log file analysis, all 12 erroneous plans alerted a mismatch in delivery versus what was planned. The 8 plans that didn’t meet criteria all had MLC errors. Conclusion: Our study demonstrates that log file based pre-treatment QA was able to detect small errors that may not be detected using an ICAF and both methods of were able to detect larger delivery errors.« less

Adaptive error detection for HDR/PDR brachytherapy: Guidance for decision making during real-time in vivo point dosimetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kertzscher, Gustavo, E-mail: guke@dtu.dk; Andersen, Claus E., E-mail: clan@dtu.dk; Tanderup, Kari, E-mail: karitand@rm.dk

Purpose: This study presents an adaptive error detection algorithm (AEDA) for real-timein vivo point dosimetry during high dose rate (HDR) or pulsed dose rate (PDR) brachytherapy (BT) where the error identification, in contrast to existing approaches, does not depend on an a priori reconstruction of the dosimeter position. Instead, the treatment is judged based on dose rate comparisons between measurements and calculations of the most viable dosimeter position provided by the AEDA in a data driven approach. As a result, the AEDA compensates for false error cases related to systematic effects of the dosimeter position reconstruction. Given its nearly exclusivemore » dependence on stable dosimeter positioning, the AEDA allows for a substantially simplified and time efficient real-time in vivo BT dosimetry implementation. Methods: In the event of a measured potential treatment error, the AEDA proposes the most viable dosimeter position out of alternatives to the original reconstruction by means of a data driven matching procedure between dose rate distributions. If measured dose rates do not differ significantly from the most viable alternative, the initial error indication may be attributed to a mispositioned or misreconstructed dosimeter (false error). However, if the error declaration persists, no viable dosimeter position can be found to explain the error, hence the discrepancy is more likely to originate from a misplaced or misreconstructed source applicator or from erroneously connected source guide tubes (true error). Results: The AEDA applied on twoin vivo dosimetry implementations for pulsed dose rate BT demonstrated that the AEDA correctly described effects responsible for initial error indications. The AEDA was able to correctly identify the major part of all permutations of simulated guide tube swap errors and simulated shifts of individual needles from the original reconstruction. Unidentified errors corresponded to scenarios where the dosimeter

Invariance of the bit error rate in the ancilla-assisted homodyne detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoshida, Yuhsuke; Takeoka, Masahiro; Sasaki, Masahide

2010-11-15

We investigate the minimum achievable bit error rate of the discrimination of binary coherent states with the help of arbitrary ancillary states. We adopt homodyne measurement with a common phase of the local oscillator and classical feedforward control. After one ancillary state is measured, its outcome is referred to the preparation of the next ancillary state and the tuning of the next mixing with the signal. It is shown that the minimum bit error rate of the system is invariant under the following operations: feedforward control, deformations, and introduction of any ancillary state. We also discuss the possible generalization ofmore » the homodyne detection scheme.« less

Masked and unmasked error-related potentials during continuous control and feedback

NASA Astrophysics Data System (ADS)

Lopes Dias, Catarina; Sburlea, Andreea I.; Müller-Putz, Gernot R.

2018-06-01

The detection of error-related potentials (ErrPs) in tasks with discrete feedback is well established in the brain–computer interface (BCI) field. However, the decoding of ErrPs in tasks with continuous feedback is still in its early stages. Objective. We developed a task in which subjects have continuous control of a cursor’s position by means of a joystick. The cursor’s position was shown to the participants in two different modalities of continuous feedback: normal and jittered. The jittered feedback was created to mimic the instability that could exist if participants controlled the trajectory directly with brain signals. Approach. This paper studies the electroencephalographic (EEG)—measurable signatures caused by a loss of control over the cursor’s trajectory, causing a target miss. Main results. In both feedback modalities, time-locked potentials revealed the typical frontal-central components of error-related potentials. Errors occurring during the jittered feedback (masked errors) were delayed in comparison to errors occurring during normal feedback (unmasked errors). Masked errors displayed lower peak amplitudes than unmasked errors. Time-locked classification analysis allowed a good distinction between correct and error classes (average Cohen-, average TPR  =  81.8% and average TNR  =  96.4%). Time-locked classification analysis between masked error and unmasked error classes revealed results at chance level (average Cohen-, average TPR  =  60.9% and average TNR  =  58.3%). Afterwards, we performed asynchronous detection of ErrPs, combining both masked and unmasked trials. The asynchronous detection of ErrPs in a simulated online scenario resulted in an average TNR of 84.0% and in an average TPR of 64.9%. Significance. The time-locked classification results suggest that the masked and unmasked errors were indistinguishable in terms of classification. The asynchronous classification results suggest that the

Liquid biopsy for early detection of lung cancer.

PubMed

Hofman, Paul

2017-01-01

The possibility of complete recovery for a lung cancer patient depends on very early diagnosis, as it allows total surgical resection. Screening for this cancer in a high-risk population can be performed using a radiological approach, but this holds a certain number of limitations. Liquid biopsy could become an alternative and complementary screening approach to chest imaging for early diagnosis of lung cancer. Several circulating biomarkers indicative of lung cancer can be investigated in blood, such as circulating tumor cells, circulating free nucleic acids (RNA and DNA) and proteins. However, none of these biomarkers have yet been adopted in routine clinical practice and studies are ongoing to confirm or not the usefulness and practical interest in routine early diagnosis and screening for lung cancers. Several potential circulating biomarkers for the early detection of lung cancer exist. When coupled to thoracic imaging, these biomarkers must give diagnosis of a totally resectable lung cancer and potentially provide new recommendations for surveillance by imagery of high-risk populations without a detectable nodule. Optimization of the specificity and sensitivity of the detection methods as well as standardization of the techniques is essential before considering for daily practice a liquid biopsy as an early diagnostic tool, or possibly as a predictive test, of lung cancer.

Kidney Disease: Early Detection and Treatment

MedlinePlus

... Bar Home Current Issue Past Issues Special Section Kidney Disease: Early Detection and Treatment Past Issues / Winter ... called a "urine albumin-to-creatinine ratio." Treating Kidney Disease Kidney disease is usually a progressive disease, ...

Predictive error detection in pianists: a combined ERP and motion capture study

PubMed Central

Maidhof, Clemens; Pitkäniemi, Anni; Tervaniemi, Mari

2013-01-01

Performing a piece of music involves the interplay of several cognitive and motor processes and requires extensive training to achieve a high skill level. However, even professional musicians commit errors occasionally. Previous event-related potential (ERP) studies have investigated the neurophysiological correlates of pitch errors during piano performance, and reported pre-error negativity already occurring approximately 70–100 ms before the error had been committed and audible. It was assumed that this pre-error negativity reflects predictive control processes that compare predicted consequences with actual consequences of one's own actions. However, in previous investigations, correct and incorrect pitch events were confounded by their different tempi. In addition, no data about the underlying movements were available. In the present study, we exploratively recorded the ERPs and 3D movement data of pianists' fingers simultaneously while they performed fingering exercises from memory. Results showed a pre-error negativity for incorrect keystrokes when both correct and incorrect keystrokes were performed with comparable tempi. Interestingly, even correct notes immediately preceding erroneous keystrokes elicited a very similar negativity. In addition, we explored the possibility of computing ERPs time-locked to a kinematic landmark in the finger motion trajectories defined by when a finger makes initial contact with the key surface, that is, at the onset of tactile feedback. Results suggest that incorrect notes elicited a small difference after the onset of tactile feedback, whereas correct notes preceding incorrect ones elicited negativity before the onset of tactile feedback. The results tentatively suggest that tactile feedback plays an important role in error-monitoring during piano performance, because the comparison between predicted and actual sensory (tactile) feedback may provide the information necessary for the detection of an upcoming error. PMID

Continuous glucose monitoring in newborn infants: how do errors in calibration measurements affect detected hypoglycemia?

PubMed

Thomas, Felicity; Signal, Mathew; Harris, Deborah L; Weston, Philip J; Harding, Jane E; Shaw, Geoffrey M; Chase, J Geoffrey

2014-05-01

Neonatal hypoglycemia is common and can cause serious brain injury. Continuous glucose monitoring (CGM) could improve hypoglycemia detection, while reducing blood glucose (BG) measurements. Calibration algorithms use BG measurements to convert sensor signals into CGM data. Thus, inaccuracies in calibration BG measurements directly affect CGM values and any metrics calculated from them. The aim was to quantify the effect of timing delays and calibration BG measurement errors on hypoglycemia metrics in newborn infants. Data from 155 babies were used. Two timing and 3 BG meter error models (Abbott Optium Xceed, Roche Accu-Chek Inform II, Nova Statstrip) were created using empirical data. Monte-Carlo methods were employed, and each simulation was run 1000 times. Each set of patient data in each simulation had randomly selected timing and/or measurement error added to BG measurements before CGM data were calibrated. The number of hypoglycemic events, duration of hypoglycemia, and hypoglycemic index were then calculated using the CGM data and compared to baseline values. Timing error alone had little effect on hypoglycemia metrics, but measurement error caused substantial variation. Abbott results underreported the number of hypoglycemic events by up to 8 and Roche overreported by up to 4 where the original number reported was 2. Nova results were closest to baseline. Similar trends were observed in the other hypoglycemia metrics. Errors in blood glucose concentration measurements used for calibration of CGM devices can have a clinically important impact on detection of hypoglycemia. If CGM devices are going to be used for assessing hypoglycemia it is important to understand of the impact of these errors on CGM data. © 2014 Diabetes Technology Society.

The effectiveness of pretreatment physics plan review for detecting errors in radiation therapy.

PubMed

Gopan, Olga; Zeng, Jing; Novak, Avrey; Nyflot, Matthew; Ford, Eric

2016-09-01

The pretreatment physics plan review is a standard tool for ensuring treatment quality. Studies have shown that the majority of errors in radiation oncology originate in treatment planning, which underscores the importance of the pretreatment physics plan review. This quality assurance measure is fundamentally important and central to the safety of patients and the quality of care that they receive. However, little is known about its effectiveness. The purpose of this study was to analyze reported incidents to quantify the effectiveness of the pretreatment physics plan review with the goal of improving it. This study analyzed 522 potentially severe or critical near-miss events within an institutional incident learning system collected over a three-year period. Of these 522 events, 356 originated at a workflow point that was prior to the pretreatment physics plan review. The remaining 166 events originated after the pretreatment physics plan review and were not considered in the study. The applicable 356 events were classified into one of the three categories: (1) events detected by the pretreatment physics plan review, (2) events not detected but "potentially detectable" by the physics review, and (3) events "not detectable" by the physics review. Potentially detectable events were further classified by which specific checks performed during the pretreatment physics plan review detected or could have detected the event. For these events, the associated specific check was also evaluated as to the possibility of automating that check given current data structures. For comparison, a similar analysis was carried out on 81 events from the international SAFRON radiation oncology incident learning system. Of the 356 applicable events from the institutional database, 180/356 (51%) were detected or could have been detected by the pretreatment physics plan review. Of these events, 125 actually passed through the physics review; however, only 38% (47/125) were actually

Early bronchiectasis in cystic fibrosis detected by surveillance CT.

PubMed

Pillarisetti, Naveen; Linnane, Barry; Ranganathan, Sarath

2010-08-01

There is emerging evidence that cystic fibrosis lung disease begins early in infancy. Newborn screening allows early detection and surveillance of pulmonary disease and the possibility of early intervention in this life-shortening condition. We report two children with cystic fibrosis who underwent a comprehensive assessment from diagnosis that included measurement of lung function, limited-slice high-resolution CT and BAL performed annually. Early aggressive surveillance enabled significant lung disease and bronchiectasis to be detected during the first few years of life and led to a change in management, highlighting a clinical role for CT scanning during the preschool years in children with cystic fibrosis.

Note: Focus error detection device for thermal expansion-recovery microscopy (ThERM).

PubMed

Domené, E A; Martínez, O E

2013-01-01

An innovative focus error detection method is presented that is only sensitive to surface curvature variations, canceling both thermoreflectance and photodefelection effects. The detection scheme consists of an astigmatic probe laser and a four-quadrant detector. Nonlinear curve fitting of the defocusing signal allows the retrieval of a cutoff frequency, which only depends on the thermal diffusivity of the sample and the pump beam size. Therefore, a straightforward retrieval of the thermal diffusivity of the sample is possible with microscopic lateral resolution and high axial resolution (~100 pm).

The Limits of Coding with Joint Constraints on Detected and Undetected Error Rates

NASA Technical Reports Server (NTRS)

Dolinar, Sam; Andrews, Kenneth; Pollara, Fabrizio; Divsalar, Dariush

2008-01-01

We develop a remarkably tight upper bound on the performance of a parameterized family of bounded angle maximum-likelihood (BA-ML) incomplete decoders. The new bound for this class of incomplete decoders is calculated from the code's weight enumerator, and is an extension of Poltyrev-type bounds developed for complete ML decoders. This bound can also be applied to bound the average performance of random code ensembles in terms of an ensemble average weight enumerator. We also formulate conditions defining a parameterized family of optimal incomplete decoders, defined to minimize both the total codeword error probability and the undetected error probability for any fixed capability of the decoder to detect errors. We illustrate the gap between optimal and BA-ML incomplete decoding via simulation of a small code.

Automated System for Early Breast Cancer Detection in Mammograms

NASA Technical Reports Server (NTRS)

Bankman, Isaac N.; Kim, Dong W.; Christens-Barry, William A.; Weinberg, Irving N.; Gatewood, Olga B.; Brody, William R.

1993-01-01

The increasing demand on mammographic screening for early breast cancer detection, and the subtlety of early breast cancer signs on mammograms, suggest an automated image processing system that can serve as a diagnostic aid in radiology clinics. We present a fully automated algorithm for detecting clusters of microcalcifications that are the most common signs of early, potentially curable breast cancer. By using the contour map of the mammogram, the algorithm circumvents some of the difficulties encountered with standard image processing methods. The clinical implementation of an automated instrument based on this algorithm is also discussed.

Missed, Misused, or Mismanaged: Improving Early Detection Systems to Optimize Child Outcomes

ERIC Educational Resources Information Center

Macy, Marisa; Marks, Kevin; Towle, Alexander

2014-01-01

Early detection efforts have been shown to vary greatly in practice, and there is a general lack of systematic accountability built into monitoring early detection effort impact. This article reviews current early detection practices and the drawbacks of these practices, with particular attention given to prevalent issues of mismeasurement,…

TH-AB-202-02: Real-Time Verification and Error Detection for MLC Tracking Deliveries Using An Electronic Portal Imaging Device

DOE Office of Scientific and Technical Information (OSTI.GOV)

J Zwan, B; Central Coast Cancer Centre, Gosford, NSW; Colvill, E

2016-06-15

Purpose: The added complexity of the real-time adaptive multi-leaf collimator (MLC) tracking increases the likelihood of undetected MLC delivery errors. In this work we develop and test a system for real-time delivery verification and error detection for MLC tracking radiotherapy using an electronic portal imaging device (EPID). Methods: The delivery verification system relies on acquisition and real-time analysis of transit EPID image frames acquired at 8.41 fps. In-house software was developed to extract the MLC positions from each image frame. Three comparison metrics were used to verify the MLC positions in real-time: (1) field size, (2) field location and, (3)more » field shape. The delivery verification system was tested for 8 VMAT MLC tracking deliveries (4 prostate and 4 lung) where real patient target motion was reproduced using a Hexamotion motion stage and a Calypso system. Sensitivity and detection delay was quantified for various types of MLC and system errors. Results: For both the prostate and lung test deliveries the MLC-defined field size was measured with an accuracy of 1.25 cm{sup 2} (1 SD). The field location was measured with an accuracy of 0.6 mm and 0.8 mm (1 SD) for lung and prostate respectively. Field location errors (i.e. tracking in wrong direction) with a magnitude of 3 mm were detected within 0.4 s of occurrence in the X direction and 0.8 s in the Y direction. Systematic MLC gap errors were detected as small as 3 mm. The method was not found to be sensitive to random MLC errors and individual MLC calibration errors up to 5 mm. Conclusion: EPID imaging may be used for independent real-time verification of MLC trajectories during MLC tracking deliveries. Thresholds have been determined for error detection and the system has been shown to be sensitive to a range of delivery errors.« less

A Simulation-Based Study on the Comparison of Statistical and Time Series Forecasting Methods for Early Detection of Infectious Disease Outbreaks.

PubMed

Yang, Eunjoo; Park, Hyun Woo; Choi, Yeon Hwa; Kim, Jusim; Munkhdalai, Lkhagvadorj; Musa, Ibrahim; Ryu, Keun Ho

2018-05-11

Early detection of infectious disease outbreaks is one of the important and significant issues in syndromic surveillance systems. It helps to provide a rapid epidemiological response and reduce morbidity and mortality. In order to upgrade the current system at the Korea Centers for Disease Control and Prevention (KCDC), a comparative study of state-of-the-art techniques is required. We compared four different temporal outbreak detection algorithms: the CUmulative SUM (CUSUM), the Early Aberration Reporting System (EARS), the autoregressive integrated moving average (ARIMA), and the Holt-Winters algorithm. The comparison was performed based on not only 42 different time series generated taking into account trends, seasonality, and randomly occurring outbreaks, but also real-world daily and weekly data related to diarrhea infection. The algorithms were evaluated using different metrics. These were namely, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), F1 score, symmetric mean absolute percent error (sMAPE), root-mean-square error (RMSE), and mean absolute deviation (MAD). Although the comparison results showed better performance for the EARS C3 method with respect to the other algorithms, despite the characteristics of the underlying time series data, Holt⁻Winters showed better performance when the baseline frequency and the dispersion parameter values were both less than 1.5 and 2, respectively.

Dysfunctional error-related processing in female psychopathy

PubMed Central

Steele, Vaughn R.; Edwards, Bethany G.; Bernat, Edward M.; Calhoun, Vince D.; Kiehl, Kent A.

2016-01-01

Neurocognitive studies of psychopathy have predominantly focused on male samples. Studies have shown that female psychopaths exhibit similar affective deficits as their male counterparts, but results are less consistent across cognitive domains including response modulation. As such, there may be potential gender differences in error-related processing in psychopathic personality. Here we investigate response-locked event-related potential (ERP) components [the error-related negativity (ERN/Ne) related to early error-detection processes and the error-related positivity (Pe) involved in later post-error processing] in a sample of incarcerated adult female offenders (n = 121) who performed a response inhibition Go/NoGo task. Psychopathy was assessed using the Hare Psychopathy Checklist-Revised (PCL-R). The ERN/Ne and Pe were analyzed with classic windowed ERP components and principal component analysis (PCA). Consistent with previous research performed in psychopathic males, female psychopaths exhibited specific deficiencies in the neural correlates of post-error processing (as indexed by reduced Pe amplitude) but not in error monitoring (as indexed by intact ERN/Ne amplitude). Specifically, psychopathic traits reflecting interpersonal and affective dysfunction remained significant predictors of both time-domain and PCA measures reflecting reduced Pe mean amplitude. This is the first evidence to suggest that incarcerated female psychopaths exhibit similar dysfunctional post-error processing as male psychopaths. PMID:26060326

Principal component analysis for the early detection of mastitis and lameness in dairy cows.

PubMed

Miekley, Bettina; Traulsen, Imke; Krieter, Joachim

2013-08-01

This investigation analysed the applicability of principal component analysis (PCA), a latent variable method, for the early detection of mastitis and lameness. Data used were recorded on the Karkendamm dairy research farm between August 2008 and December 2010. For mastitis and lameness detection, data of 338 and 315 cows in their first 200 d in milk were analysed, respectively. Mastitis as well as lameness were specified according to veterinary treatments. Diseases were defined as disease blocks. The different definitions used (two for mastitis, three for lameness) varied solely in the sequence length of the blocks. Only the days before the treatment were included in the blocks. Milk electrical conductivity, milk yield and feeding patterns (feed intake, number of feeding visits and time at the trough) were used for recognition of mastitis. Pedometer activity and feeding patterns were utilised for lameness detection. To develop and verify the PCA model, the mastitis and the lameness datasets were divided into training and test datasets. PCA extracted uncorrelated principle components (PC) by linear transformations of the raw data so that the first few PCs captured most of the variations in the original dataset. For process monitoring and disease detection, these resulting PCs were applied to the Hotelling's T 2 chart and to the residual control chart. The results show that block sensitivity of mastitis detection ranged from 77·4 to 83·3%, whilst specificity was around 76·7%. The error rates were around 98·9%. For lameness detection, the block sensitivity ranged from 73·8 to 87·8% while the obtained specificities were between 54·8 and 61·9%. The error rates varied from 87·8 to 89·2%. In conclusion, PCA seems to be not yet transferable into practical usage. Results could probably be improved if different traits and more informative sensor data are included in the analysis.

Effort and Potential Efficiencies for Aquatic Non-native Species Early Detection

EPA Science Inventory

This manuscript is based on the early aquatic non-native species detection research in the Duluth-Superior harbor. The problem of early detection is essentially that of a "needle in a haystack" - to detect a newly arrived and presumably rare non-native species with a high probabi...

Register file soft error recovery

DOEpatents

Fleischer, Bruce M.; Fox, Thomas W.; Wait, Charles D.; Muff, Adam J.; Watson, III, Alfred T.

2013-10-15

Register file soft error recovery including a system that includes a first register file and a second register file that mirrors the first register file. The system also includes an arithmetic pipeline for receiving data read from the first register file, and error detection circuitry to detect whether the data read from the first register file includes corrupted data. The system further includes error recovery circuitry to insert an error recovery instruction into the arithmetic pipeline in response to detecting the corrupted data. The inserted error recovery instruction replaces the corrupted data in the first register file with a copy of the data from the second register file.

Advances in pancreatic cancer research: moving towards early detection.

PubMed

He, Xiang-Yi; Yuan, Yao-Zong

2014-08-28

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal forms of cancer. Substantial progress has been made in the understanding of the biology of pancreatic cancer, and advances in patient management have been significant. However, most patients (nearly 80%) who present with locally advanced or metastatic disease have an extremely poor prognosis. Survival is better for those with malignant disease localized to the pancreas, because surgical resection at present offers the only chance of cure. Therefore, the early detection of pancreatic cancer may benefit patients with PDAC. However, its low rate of incidence and the limitations of current screening strategies make early detection difficult. Recent advances in the understanding of the pathogenesis of PDAC suggest that it is possible to detect PDAC in early stages and even identify precursor lesions. The presence of new-onset diabetes mellitus in the early phase of pancreatic cancer may provide clues for its early diagnosis. Advances in the identification of novel circulating biomarkers including serological signatures, autoantibodies, epigenetic markers, circulating tumor cells and microRNAs suggest that they can be used as potential tools for the screening of precursors and early stage PDAC in the future. However, proper screening strategies based on effective screening methodologies need to be tested for clinical application.

Automatic detection and notification of "wrong patient-wrong location'' errors in the operating room.

PubMed

Sandberg, Warren S; Häkkinen, Matti; Egan, Marie; Curran, Paige K; Fairbrother, Pamela; Choquette, Ken; Daily, Bethany; Sarkka, Jukka-Pekka; Rattner, David

2005-09-01

When procedures and processes to assure patient location based on human performance do not work as expected, patients are brought incrementally closer to a possible "wrong patient-wrong procedure'' error. We developed a system for automated patient location monitoring and management. Real-time data from an active infrared/radio frequency identification tracking system provides patient location data that are robust and can be compared with an "expected process'' model to automatically flag wrong-location events as soon as they occur. The system also generates messages that are automatically sent to process managers via the hospital paging system, thus creating an active alerting function to annunciate errors. We deployed the system to detect and annunciate "patient-in-wrong-OR'' events. The system detected all "wrong-operating room (OR)'' events, and all "wrong-OR'' locations were correctly assigned within 0.50+/-0.28 minutes (mean+/-SD). This corresponded to the measured latency of the tracking system. All wrong-OR events were correctly annunciated via the paging function. This experiment demonstrates that current technology can automatically collect sufficient data to remotely monitor patient flow through a hospital, provide decision support based on predefined rules, and automatically notify stakeholders of errors.

Multiple Biomarker Panels for Early Detection of Breast Cancer in Peripheral Blood

PubMed Central

Zhang, Fan; Deng, Youping; Drabier, Renee

2013-01-01

Detecting breast cancer at early stages can be challenging. Traditional mammography and tissue microarray that have been studied for early breast cancer detection and prediction have many drawbacks. Therefore, there is a need for more reliable diagnostic tools for early detection of breast cancer due to a number of factors and challenges. In the paper, we presented a five-marker panel approach based on SVM for early detection of breast cancer in peripheral blood and show how to use SVM to model the classification and prediction problem of early detection of breast cancer in peripheral blood. We found that the five-marker panel can improve the prediction performance (area under curve) in the testing data set from 0.5826 to 0.7879. Further pathway analysis showed that the top four five-marker panels are associated with signaling, steroid hormones, metabolism, immune system, and hemostasis, which are consistent with previous findings. Our prediction model can serve as a general model for multibiomarker panel discovery in early detection of other cancers. PMID:24371830

Multiple biomarker panels for early detection of breast cancer in peripheral blood.

PubMed

Zhang, Fan; Deng, Youping; Drabier, Renee

2013-01-01

Detecting breast cancer at early stages can be challenging. Traditional mammography and tissue microarray that have been studied for early breast cancer detection and prediction have many drawbacks. Therefore, there is a need for more reliable diagnostic tools for early detection of breast cancer due to a number of factors and challenges. In the paper, we presented a five-marker panel approach based on SVM for early detection of breast cancer in peripheral blood and show how to use SVM to model the classification and prediction problem of early detection of breast cancer in peripheral blood. We found that the five-marker panel can improve the prediction performance (area under curve) in the testing data set from 0.5826 to 0.7879. Further pathway analysis showed that the top four five-marker panels are associated with signaling, steroid hormones, metabolism, immune system, and hemostasis, which are consistent with previous findings. Our prediction model can serve as a general model for multibiomarker panel discovery in early detection of other cancers.

Minimum Error Bounded Efficient L1 Tracker with Occlusion Detection (PREPRINT)

DTIC Science & Technology

2011-01-01

Minimum Error Bounded Efficient `1 Tracker with Occlusion Detection Xue Mei\\ ∗ Haibin Ling† Yi Wu†[ Erik Blasch‡ Li Bai] \\Assembly Test Technology...proposed BPR-L1 tracker is tested on several challenging benchmark sequences involving chal- lenges such as occlusion and illumination changes. In all...point method de - pends on the value of the regularization parameter λ. In the experiments, we found that the total number of PCG is a few hundred. The

Conflict monitoring in speech processing: An fMRI study of error detection in speech production and perception.

PubMed

Gauvin, Hanna S; De Baene, Wouter; Brass, Marcel; Hartsuiker, Robert J

2016-02-01

To minimize the number of errors in speech, and thereby facilitate communication, speech is monitored before articulation. It is, however, unclear at which level during speech production monitoring takes place, and what mechanisms are used to detect and correct errors. The present study investigated whether internal verbal monitoring takes place through the speech perception system, as proposed by perception-based theories of speech monitoring, or whether mechanisms independent of perception are applied, as proposed by production-based theories of speech monitoring. With the use of fMRI during a tongue twister task we observed that error detection in internal speech during noise-masked overt speech production and error detection in speech perception both recruit the same neural network, which includes pre-supplementary motor area (pre-SMA), dorsal anterior cingulate cortex (dACC), anterior insula (AI), and inferior frontal gyrus (IFG). Although production and perception recruit similar areas, as proposed by perception-based accounts, we did not find activation in superior temporal areas (which are typically associated with speech perception) during internal speech monitoring in speech production as hypothesized by these accounts. On the contrary, results are highly compatible with a domain general approach to speech monitoring, by which internal speech monitoring takes place through detection of conflict between response options, which is subsequently resolved by a domain general executive center (e.g., the ACC). Copyright © 2015 Elsevier Inc. All rights reserved.

Clover: Compiler directed lightweight soft error resilience

DOE PAGES

Liu, Qingrui; Lee, Dongyoon; Jung, Changhee; ...

2015-05-01

This paper presents Clover, a compiler directed soft error detection and recovery scheme for lightweight soft error resilience. The compiler carefully generates soft error tolerant code based on idem-potent processing without explicit checkpoint. During program execution, Clover relies on a small number of acoustic wave detectors deployed in the processor to identify soft errors by sensing the wave made by a particle strike. To cope with DUE (detected unrecoverable errors) caused by the sensing latency of error detection, Clover leverages a novel selective instruction duplication technique called tail-DMR (dual modular redundancy). Once a soft error is detected by either themore » sensor or the tail-DMR, Clover takes care of the error as in the case of exception handling. To recover from the error, Clover simply redirects program control to the beginning of the code region where the error is detected. Lastly, the experiment results demonstrate that the average runtime overhead is only 26%, which is a 75% reduction compared to that of the state-of-the-art soft error resilience technique.« less

Detecting ‘Wrong Blood in Tube’ Errors: Evaluation of a Bayesian Network Approach

PubMed Central

Doctor, Jason N.; Strylewicz, Greg

2010-01-01

Objective In an effort to address the problem of laboratory errors, we develop and evaluate a method to detect mismatched specimens from nationally collected blood laboratory data in two experiments. Methods In Experiment 1 and 2 using blood labs from National Health and Nutrition Examination Survey (NHANES) and values derived from the Diabetes Prevention Program (DPP) respectively, a proportion of glucose and HbA1c specimens were randomly mismatched. A Bayesian network that encoded probabilistic relationships among analytes was used to predict mismatches. In Experiment 1 the performance of the network was compared against existing error detection software. In Experiment 2 the network was compared against 11 human experts recruited from the American Academy of Clinical Chemists. Results were compared via area under the receiver-operating characteristics curves (AUCs) and with agreement statistics. Results In Experiment 1 the network was most predictive of mismatches that produced clinically significant discrepancies between true and mismatched scores ((AUC of 0.87 (±0.04) for HbA1c and 0.83 (±0.02) for glucose), performed well in identifying errors among those self-reporting diabetes (N = 329) (AUC = 0.79 (± 0.02)) and performed significantly better than the established approach it was tested against (in all cases p < .0.05). In Experiment 2 it performed better (and in no case worse) than 7 of the 11 human experts. Average percent agreement was 0.79. and Kappa (κ) was 0.59, between experts and the Bayesian network. Conclusions Bayesian network can accurately identify mismatched specimens. The algorithm is best at identifying mismatches that result in a clinically significant magnitude of error. PMID:20566275

Detection of material property errors in handbooks and databases using artificial neural networks with hidden correlations

NASA Astrophysics Data System (ADS)

Zhang, Y. M.; Evans, J. R. G.; Yang, S. F.

2010-11-01

The authors have discovered a systematic, intelligent and potentially automatic method to detect errors in handbooks and stop their transmission using unrecognised relationships between materials properties. The scientific community relies on the veracity of scientific data in handbooks and databases, some of which have a long pedigree covering several decades. Although various outlier-detection procedures are employed to detect and, where appropriate, remove contaminated data, errors, which had not been discovered by established methods, were easily detected by our artificial neural network in tables of properties of the elements. We started using neural networks to discover unrecognised relationships between materials properties and quickly found that they were very good at finding inconsistencies in groups of data. They reveal variations from 10 to 900% in tables of property data for the elements and point out those that are most probably correct. Compared with the statistical method adopted by Ashby and co-workers [Proc. R. Soc. Lond. Ser. A 454 (1998) p. 1301, 1323], this method locates more inconsistencies and could be embedded in database software for automatic self-checking. We anticipate that our suggestion will be a starting point to deal with this basic problem that affects researchers in every field. The authors believe it may eventually moderate the current expectation that data field error rates will persist at between 1 and 5%.

A New Approach to Detection of Systematic Errors in Secondary Substation Monitoring Equipment Based on Short Term Load Forecasting

PubMed Central

Moriano, Javier; Rodríguez, Francisco Javier; Martín, Pedro; Jiménez, Jose Antonio; Vuksanovic, Branislav

2016-01-01

In recent years, Secondary Substations (SSs) are being provided with equipment that allows their full management. This is particularly useful not only for monitoring and planning purposes but also for detecting erroneous measurements, which could negatively affect the performance of the SS. On the other hand, load forecasting is extremely important since they help electricity companies to make crucial decisions regarding purchasing and generating electric power, load switching, and infrastructure development. In this regard, Short Term Load Forecasting (STLF) allows the electric power load to be predicted over an interval ranging from one hour to one week. However, important issues concerning error detection by employing STLF has not been specifically addressed until now. This paper proposes a novel STLF-based approach to the detection of gain and offset errors introduced by the measurement equipment. The implemented system has been tested against real power load data provided by electricity suppliers. Different gain and offset error levels are successfully detected. PMID:26771613

The effectiveness of pretreatment physics plan review for detecting errors in radiation therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gopan, Olga; Zeng, Jing; Novak, Avrey

Purpose: The pretreatment physics plan review is a standard tool for ensuring treatment quality. Studies have shown that the majority of errors in radiation oncology originate in treatment planning, which underscores the importance of the pretreatment physics plan review. This quality assurance measure is fundamentally important and central to the safety of patients and the quality of care that they receive. However, little is known about its effectiveness. The purpose of this study was to analyze reported incidents to quantify the effectiveness of the pretreatment physics plan review with the goal of improving it. Methods: This study analyzed 522 potentiallymore » severe or critical near-miss events within an institutional incident learning system collected over a three-year period. Of these 522 events, 356 originated at a workflow point that was prior to the pretreatment physics plan review. The remaining 166 events originated after the pretreatment physics plan review and were not considered in the study. The applicable 356 events were classified into one of the three categories: (1) events detected by the pretreatment physics plan review, (2) events not detected but “potentially detectable” by the physics review, and (3) events “not detectable” by the physics review. Potentially detectable events were further classified by which specific checks performed during the pretreatment physics plan review detected or could have detected the event. For these events, the associated specific check was also evaluated as to the possibility of automating that check given current data structures. For comparison, a similar analysis was carried out on 81 events from the international SAFRON radiation oncology incident learning system. Results: Of the 356 applicable events from the institutional database, 180/356 (51%) were detected or could have been detected by the pretreatment physics plan review. Of these events, 125 actually passed through the physics review

Using virtual reality to assess theory of mind subprocesses and error types in early and chronic schizophrenia.

PubMed

Canty, Allana L; Neumann, David L; Shum, David H K

2017-12-01

Individuals with schizophrenia often demonstrate theory of mind (ToM) impairment relative to healthy adults. However, the exact nature of this impairment (first- vs. second-order ToM and cognitive vs. affective ToM) and the extent to which ToM abilities deteriorate with illness chronicity is unclear. Furthermore, little is known about the relationships between clinical symptoms and ToM error types (overmentalising, reduced mentalising and no ToM) in early and chronic schizophrenia. This study examined the nature and types of ToM impairment in individuals with early ( n  = 26) and chronic schizophrenia ( n  = 32) using a novel virtual reality task. Clinical participants and demographically-matched controls were administered the Virtual Assessment of Mentalising Ability, which provides indices of first- and second-order cognitive and affective ToM, and quantifies three different types of mentalising errors (viz., overmentalising, reduced mentalising, and no ToM). Individuals with early schizophrenia performed significantly poorer than healthy controls on first-order affective and second-order cognitive and affective ToM, but significantly higher than individuals with chronic schizophrenia on all ToM subscales. Whereas a lack of mental state concept was associated with negative symptoms, overmentalising was associated with positive symptoms. These findings suggest that ToM abilities selectively deteriorate with illness chronicity and error types are related to these individuals' presenting symptomology. An implication of the findings is that social-cognitive interventions for schizophrenia need to consider the nature, time course and symptomatology of the presenting patient.

SU-E-J-81: Beveled Needle Tip Detection Error in Ultrasound-Guided Prostate Brachytherapy.

PubMed

Leu, S; Ruiz, B; Podder, T

2012-06-01

To quantify the needle tip detection errors in ultrasound images due to bevel-tip orientation in relation to the location on template grid. Transrectal ultrasound (TRUS) system (BK Medical) with physical template grid and 18-gauge bevel-tip (20-deg beveled angle) brachytherapy needle (Bard Medical, Covington, GA) were used. The TRUS was set at 6.5MHz in water phantom at 40°C and measurements were taken with 50% and 100% TRUS gains. Needles were oriented with bevel-tip facing up (0-degree) and inserted through template grid-holes. Reference needle depths were measured when needle tip image intensity was bright enough for potentially consistent readings. High-resolution digital vernier caliper was used to measure needle depth. Needle bevel-tip orientation was then changed to bevel down (by rotating 180-degree) and needle depth was adjusted by retracting so that the needle-tip image intensity appeared similar to when the needle bevel-tip was at 0-degree orientation. Clinically relevant locations were considered for needle placement on the template grids (1st row to 9th row, and 'a-f' columns). For 50% TRUS gain, bevel tip detection errors/differences were 0.69±0.30mm (1st row) to 3.23±0.22mm (9th row) and 0.78±0.71mm (1st row) to 4.14±0.56mm (9th row) in columns 'a' and 'D', respectively. The corresponding errors for 100% TRUS gain were 0.57±0.25mm to 5.24±0.36mm and 0.84±0.30mm to 4.2±0.20mm in columns 'a' and 'D', respectively. These errors/differences varied linearly for grid-hole locations on the rows and columns in between, smaller to large depending on distance from the TRUS probe. Observed no effect of gains (50% vs. 100%) along 'D' column, which was directly above the TRUS probe. Experiment results revealed that the beveled needle tip orientation could significantly impact the detection accuracy of the needle tips, based on which the seeds might be delivered. These errors may lead to considerable dosimetric deviations in prostate brachytherapy seed

Impact of Measurement Error on Synchrophasor Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yilu; Gracia, Jose R.; Ewing, Paul D.

2015-07-01

Phasor measurement units (PMUs), a type of synchrophasor, are powerful diagnostic tools that can help avert catastrophic failures in the power grid. Because of this, PMU measurement errors are particularly worrisome. This report examines the internal and external factors contributing to PMU phase angle and frequency measurement errors and gives a reasonable explanation for them. It also analyzes the impact of those measurement errors on several synchrophasor applications: event location detection, oscillation detection, islanding detection, and dynamic line rating. The primary finding is that dynamic line rating is more likely to be influenced by measurement error. Other findings include themore » possibility of reporting nonoscillatory activity as an oscillation as the result of error, failing to detect oscillations submerged by error, and the unlikely impact of error on event location and islanding detection.« less

Comparison between refractometer and retinoscopy in determining refractive errors in children--false doubt.

PubMed

Pokupec, Rajko; Mrazovac, Danijela; Popović-Suić, Smiljka; Mrazovac, Visnja; Kordić, Rajko; Petricek, Igor

2013-04-01

Early detection of a refractive error and its correction are extremely important for the prevention of amblyopia (poor vision). The golden standard in the detection of refractive errors is retinoscopy--a method where the pupils are dilated in order to exclude accomodation. This results in a more accurate measurement of a refractive error. Automatic computer refractometer is also in use. The study included 30 patients, 15 boys, 15 girls aged 4-16. The first examination was conducted with refractometer on narrow pupils. Retinoscopy, followed by another examination with refractometer was performed on pupils dilated with mydriatic drops administered 3 times. The results obtained with three methods were compared. They indicate that in narrow pupils the autorefractometer revealed an increased diopter value in nearsightedness (myopia), the minus overcorrection, whereas findings obtained with retinoscopy and autorefractometer in mydriasis cycloplegia, were much more accurate. The results were statistically processed, which confirmed the differences between obtained measurements. These findings are consistent with the results of studies conducted by other authors. Automatic refractometry on narrow pupils has proven to be a method for detection of refractive errors in children. However, the exact value of the refractive error is obtained only in mydriasis--with retinoscopy or an automatic refractometer on dilated pupils.

Recovery of chemical Estimates by Field Inhomogeneity Neighborhood Error Detection (REFINED): Fat/Water Separation at 7T

PubMed Central

Narayan, Sreenath; Kalhan, Satish C.; Wilson, David L.

2012-01-01

I.Abstract Purpose To reduce swaps in fat-water separation methods, a particular issue on 7T small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map. Materials and Methods Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction. Results Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic. Conclusion Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically. PMID:23023815

Recovery of chemical estimates by field inhomogeneity neighborhood error detection (REFINED): fat/water separation at 7 tesla.

PubMed

Narayan, Sreenath; Kalhan, Satish C; Wilson, David L

2013-05-01

To reduce swaps in fat-water separation methods, a particular issue on 7 Tesla (T) small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map. Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction. Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic. Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically. Copyright © 2012 Wiley Periodicals, Inc.

Early Detection and Intervention of ASD: A European Overview

PubMed Central

Narzisi, Antonio; García-Primo, Patricia; Kawa, Rafal

2017-01-01

Over the last several years there has been an increasing focus on early detection of Autism Spectrum Disorder (ASD), not only from the scientific field but also from professional associations and public health systems all across Europe. Not surprisingly, in order to offer better services and quality of life for both children with ASD and their families, different screening procedures and tools have been developed for early assessment and intervention. However, current evidence is needed for healthcare providers and policy makers to be able to implement specific measures and increase autism awareness in European communities. The general aim of this review is to address the latest and most relevant issues related to early detection and treatments. The specific objectives are (1) analyse the impact, describing advantages and drawbacks, of screening procedures based on standardized tests, surveillance programmes, or other observational measures; and (2) provide a European framework of early intervention programmes and practices and what has been learnt from implementing them in public or private settings. This analysis is then discussed and best practices are suggested to help professionals, health systems and policy makers to improve their local procedures or to develop new proposals for early detection and intervention programmes. PMID:29194420

Early detection of invasive plants: principles and practices

USGS Publications Warehouse

Welch, Bradley A.; Geissler, Paul H.; Latham, Penelope

2014-01-01

Invasive plants infest an estimated 2.6 million acres of the 83 million acres managed by the National Park Service (NPS) in the United States. The consequences of these invasions present a significant challenge for the NPS to manage the agency’s natural resources “unimpaired for the enjoyment of future generations.” More NPS lands are infested daily despite diligent efforts to curtail the problem. Impacts from invasive species have been realized in most parks, resulting in an expressed need to control existing infestations and restore affected ecosystems. There is a growing urgency in the NPS and other resource management organizations to be proactive. The NPS I&M Program, in collaboration with the U.S. Geological Survey (USGS) Status and Trends Program, compiled this document to provide guidance and insight to parks and other natural areas engaged in developing early-detection monitoring protocols for invasive plants. While several rapid response frameworks exist, there is no consistent or comprehensive guidance informing the active detection of nonnative plants early in the invasion process. Early-detection was selected as a primary focus for invasive-species monitoring because, along with rapid response, it is a key strategy for successful management of invasive species. Eradication efforts are most successful on small infestations (that is less than 1 hectare) and become less successful as infestation size increases, to the point that eradication is unlikely for large (that is greater than 1,000 hectares) populations of invasive plants. This document provides guidance for natural resource managers wishing to detect invasive plants early through an active, directed monitoring program. It has a Quick-Start Guide to direct readers to specific chapters and text relevant to their needs. Decision trees and flow charts assist the reader in deciding what methods to choose and when to use them. This document is written in a modular format to accommodate use of

[Research on early fire detection with CO-CO2 FTIR-spectroscopy].

PubMed

Du, Jian-hua; Zhang, Ren-cheng; Huang, Xiang-ying; Gong, Xue; Zhang, Xiao-hua

2007-05-01

A new fire detection method is put forward based on the theory of FTIR spectroscopy through analyzing all kinds of detection methods, in which CO and CO2 are chosen as early fire detection objects, and an early fire experiment system has been set up. The concentration characters of CO and CO2 were obtained through early fire experiments including real alarm sources and nuisance alarm sources. In real alarm sources there are abundant CO and CO2 which change regularly. In nuisance alarm sources there is almost no CO. So it's feasible to reduce the false alarms and increase the sensitivity of early fire detectors through analyzing the concentration characters of CO and CO2.

A concept for early cancer detection and therapy

NASA Astrophysics Data System (ADS)

Waynant, Ronald W.; Ilev, Ilko K.; Mitra, Kunal

2003-06-01

Early detection and treatment of breast cancer is least costly in terms of dollars, morbidity and mortality. With new early detection x-ray technology, tumors can be found, diagnosed and treated at a much smaller size than is currently possible. This paper proposes the development of a high resolution, high quality imaging system. It is a laser-driven x-ray system with time-gated detection that removes scattering noise in the image and produces resolution on the order of 10 μm. This higher resolution and higher image quality will enable the detection of one or two millimeter tumors hopefully detecting them before metastasis. We also propose that tumor detection should be followed by an immediate needle-directed, optical fiber biopsy to instantly determine if cancer is present and, if present, the tumor should immediately be given a lethal treatment of laser or x-radiation through the same needle using fiber optics or hollow waveguides. This technology will help prevent multiple interventions resulting in both the lowest overall cost and a more efficacious therapy. The approach can be stopped at the first negative (benign) indication and will help forestall repeated examination as well as reduce patient anxiety.

Early Detection of Lung Cancer Using Nano-Nose - A Review

PubMed Central

Fernandes, M. P.; Venkatesh, S; Sudarshan, B. G

2015-01-01

Lung cancer is one of the malignancies causing deaths worldwide. The yet to be developed non-invasive diagnostic techniques, are a challenge for early detection of cancer before it progresses to its later stages. The currently available diagnostic methods are expensive or invasive, and are not fit for general screening purposes. Early identification not only helps in detecting primary cancer, but also in treating its secondaries; which creates a need for easily applicable tests to screen individuals at risk. A detailed review of the various screening methods, including the latest trend of breath analysis using gold nanoparticles, to identify cancer at its early stage, are studied here. The VOC based breath biomarkers are used to analyze the exhaled breath of the patients. These biomarkers are utilized by Chemiresistors coated with gold nanoparticles, which are found to be the most suited technique for early detection of lung cancer. This technique is highly accurate and is relatively easy to operate and was tested on smokers and non-smokers. This review also gives as an outline of the fabrication and working of the device Na-Nose. The Chemiresistors coated with Gold nanoparticles, show a great potential in being an non-invasive and cost-effective diagnostic technique for early detection of lung cancer. PMID:26628933

Early Detection of Lung Cancer Using Nano-Nose - A Review.

PubMed

Fernandes, M P; Venkatesh, S; Sudarshan, B G

2015-01-01

Lung cancer is one of the malignancies causing deaths worldwide. The yet to be developed non-invasive diagnostic techniques, are a challenge for early detection of cancer before it progresses to its later stages. The currently available diagnostic methods are expensive or invasive, and are not fit for general screening purposes. Early identification not only helps in detecting primary cancer, but also in treating its secondaries; which creates a need for easily applicable tests to screen individuals at risk. A detailed review of the various screening methods, including the latest trend of breath analysis using gold nanoparticles, to identify cancer at its early stage, are studied here. The VOC based breath biomarkers are used to analyze the exhaled breath of the patients. These biomarkers are utilized by Chemiresistors coated with gold nanoparticles, which are found to be the most suited technique for early detection of lung cancer. This technique is highly accurate and is relatively easy to operate and was tested on smokers and non-smokers. This review also gives as an outline of the fabrication and working of the device Na-Nose. The Chemiresistors coated with Gold nanoparticles, show a great potential in being an non-invasive and cost-effective diagnostic technique for early detection of lung cancer.

Error-Related Psychophysiology and Negative Affect

ERIC Educational Resources Information Center

Hajcak, G.; McDonald, N.; Simons, R.F.

2004-01-01

The error-related negativity (ERN/Ne) and error positivity (Pe) have been associated with error detection and response monitoring. More recently, heart rate (HR) and skin conductance (SC) have also been shown to be sensitive to the internal detection of errors. An enhanced ERN has consistently been observed in anxious subjects and there is some…

Neurometaplasticity: Glucoallostasis control of plasticity of the neural networks of error commission, detection, and correction modulates neuroplasticity to influence task precision

NASA Astrophysics Data System (ADS)

Welcome, Menizibeya O.; Dane, Şenol; Mastorakis, Nikos E.; Pereverzev, Vladimir A.

2017-12-01

The term "metaplasticity" is a recent one, which means plasticity of synaptic plasticity. Correspondingly, neurometaplasticity simply means plasticity of neuroplasticity, indicating that a previous plastic event determines the current plasticity of neurons. Emerging studies suggest that neurometaplasticity underlie many neural activities and neurobehavioral disorders. In our previous work, we indicated that glucoallostasis is essential for the control of plasticity of the neural network that control error commission, detection and correction. Here we review recent works, which suggest that task precision depends on the modulatory effects of neuroplasticity on the neural networks of error commission, detection, and correction. Furthermore, we discuss neurometaplasticity and its role in error commission, detection, and correction.

A Cell-Based Approach to Early Pancreatic Cancer Detection

DTIC Science & Technology

2016-10-01

Award Number: W81XWH-15-1-0457 TITLE: A Cell -Based Approach to Early Pancreatic Cancer Detection PRINCIPAL INVESTIGATOR: Dr. Ben Stanger...SUBTITLE 5a. CONTRACT NUMBER A Cell -Based Approach to Early Pancreatic Cancer Detection 5b. GRANT NUMBER W81XWH-15-1-0457 5c. PROGRAM ELEMENT NUMBER 6...tumor cells from mouse blood by depleting the sample of white blood cells (WBCs). Furthermore, the RNA profile of these cells can be assessed by

Measurement Error and Equating Error in Power Analysis

ERIC Educational Resources Information Center

Phillips, Gary W.; Jiang, Tao

2016-01-01

Power analysis is a fundamental prerequisite for conducting scientific research. Without power analysis the researcher has no way of knowing whether the sample size is large enough to detect the effect he or she is looking for. This paper demonstrates how psychometric factors such as measurement error and equating error affect the power of…

Validation, Edits, and Application Processing Phase II and Error-Prone Model Report.

ERIC Educational Resources Information Center

Gray, Susan; And Others

The impact of quality assurance procedures on the correct award of Basic Educational Opportunity Grants (BEOGs) for 1979-1980 was assessed, and a model for detecting error-prone applications early in processing was developed. The Bureau of Student Financial Aid introduced new comments into the edit system in 1979 and expanded the pre-established…

Dual-mode microwave system to enhance early detection of cancer

NASA Technical Reports Server (NTRS)

Carr, K. L.; El-Mahdi, A. M.; Shaeffer, J.

1981-01-01

A dual-mode microwave system has been developed that will permit early detection of cancer. The system combines the use of the passive microwave radiometer with an active transmitter. The active transmitter will provide localized heating to enhance early detection by taking advantage of the differential heating (i.e., tumor temperature with respect to surrounding tissue) associated with the thermal characteristics of tumors.

Error Analysis in a Stereo Vision-Based Pedestrian Detection Sensor for Collision Avoidance Applications

PubMed Central

Llorca, David F.; Sotelo, Miguel A.; Parra, Ignacio; Ocaña, Manuel; Bergasa, Luis M.

2010-01-01

This paper presents an analytical study of the depth estimation error of a stereo vision-based pedestrian detection sensor for automotive applications such as pedestrian collision avoidance and/or mitigation. The sensor comprises two synchronized and calibrated low-cost cameras. Pedestrians are detected by combining a 3D clustering method with Support Vector Machine-based (SVM) classification. The influence of the sensor parameters in the stereo quantization errors is analyzed in detail providing a point of reference for choosing the sensor setup according to the application requirements. The sensor is then validated in real experiments. Collision avoidance maneuvers by steering are carried out by manual driving. A real time kinematic differential global positioning system (RTK-DGPS) is used to provide ground truth data corresponding to both the pedestrian and the host vehicle locations. The performed field test provided encouraging results and proved the validity of the proposed sensor for being used in the automotive sector towards applications such as autonomous pedestrian collision avoidance. PMID:22319323

Error analysis in a stereo vision-based pedestrian detection sensor for collision avoidance applications.

PubMed

Llorca, David F; Sotelo, Miguel A; Parra, Ignacio; Ocaña, Manuel; Bergasa, Luis M

2010-01-01

This paper presents an analytical study of the depth estimation error of a stereo vision-based pedestrian detection sensor for automotive applications such as pedestrian collision avoidance and/or mitigation. The sensor comprises two synchronized and calibrated low-cost cameras. Pedestrians are detected by combining a 3D clustering method with Support Vector Machine-based (SVM) classification. The influence of the sensor parameters in the stereo quantization errors is analyzed in detail providing a point of reference for choosing the sensor setup according to the application requirements. The sensor is then validated in real experiments. Collision avoidance maneuvers by steering are carried out by manual driving. A real time kinematic differential global positioning system (RTK-DGPS) is used to provide ground truth data corresponding to both the pedestrian and the host vehicle locations. The performed field test provided encouraging results and proved the validity of the proposed sensor for being used in the automotive sector towards applications such as autonomous pedestrian collision avoidance.

The good, the bad and the outliers: automated detection of errors and outliers from groundwater hydrographs

NASA Astrophysics Data System (ADS)

Peterson, Tim J.; Western, Andrew W.; Cheng, Xiang

2018-03-01

Suspicious groundwater-level observations are common and can arise for many reasons ranging from an unforeseen biophysical process to bore failure and data management errors. Unforeseen observations may provide valuable insights that challenge existing expectations and can be deemed outliers, while monitoring and data handling failures can be deemed errors, and, if ignored, may compromise trend analysis and groundwater model calibration. Ideally, outliers and errors should be identified but to date this has been a subjective process that is not reproducible and is inefficient. This paper presents an approach to objectively and efficiently identify multiple types of errors and outliers. The approach requires only the observed groundwater hydrograph, requires no particular consideration of the hydrogeology, the drivers (e.g. pumping) or the monitoring frequency, and is freely available in the HydroSight toolbox. Herein, the algorithms and time-series model are detailed and applied to four observation bores with varying dynamics. The detection of outliers was most reliable when the observation data were acquired quarterly or more frequently. Outlier detection where the groundwater-level variance is nonstationary or the absolute trend increases rapidly was more challenging, with the former likely to result in an under-estimation of the number of outliers and the latter an overestimation in the number of outliers.

The detection error of thermal test low-frequency cable based on M sequence correlation algorithm

NASA Astrophysics Data System (ADS)

Wu, Dongliang; Ge, Zheyang; Tong, Xin; Du, Chunlin

2018-04-01

The problem of low accuracy and low efficiency of off-line detecting on thermal test low-frequency cable faults could be solved by designing a cable fault detection system, based on FPGA export M sequence code(Linear feedback shift register sequence) as pulse signal source. The design principle of SSTDR (Spread spectrum time-domain reflectometry) reflection method and hardware on-line monitoring setup figure is discussed in this paper. Testing data show that, this detection error increases with fault location of thermal test low-frequency cable.

Study on the special vision sensor for detecting position error in robot precise TIG welding of some key part of rocket engine

NASA Astrophysics Data System (ADS)

Zhang, Wenzeng; Chen, Nian; Wang, Bin; Cao, Yipeng

2005-01-01

Rocket engine is a hard-core part of aerospace transportation and thrusting system, whose research and development is very important in national defense, aviation and aerospace. A novel vision sensor is developed, which can be used for error detecting in arc length control and seam tracking in precise pulse TIG welding of the extending part of the rocket engine jet tube. The vision sensor has many advantages, such as imaging with high quality, compactness and multiple functions. The optics design, mechanism design and circuit design of the vision sensor have been described in detail. Utilizing the mirror imaging of Tungsten electrode in the weld pool, a novel method is proposed to detect the arc length and seam tracking error of Tungsten electrode to the center line of joint seam from a single weld image. A calculating model of the method is proposed according to the relation of the Tungsten electrode, weld pool, the mirror of Tungsten electrode in weld pool and joint seam. The new methodologies are given to detect the arc length and seam tracking error. Through analyzing the results of the experiments, a system error modifying method based on a linear function is developed to improve the detecting precise of arc length and seam tracking error. Experimental results show that the final precision of the system reaches 0.1 mm in detecting the arc length and the seam tracking error of Tungsten electrode to the center line of joint seam.

A concatenated coding scheme for error control

NASA Technical Reports Server (NTRS)

Lin, S.

1985-01-01

A concatenated coding scheme for error contol in data communications was analyzed. The inner code is used for both error correction and detection, however the outer code is used only for error detection. A retransmission is requested if either the inner code decoder fails to make a successful decoding or the outer code decoder detects the presence of errors after the inner code decoding. Probability of undetected error of the proposed scheme is derived. An efficient method for computing this probability is presented. Throughout efficiency of the proposed error control scheme incorporated with a selective repeat ARQ retransmission strategy is analyzed.

The Neural Basis of Error Detection: Conflict Monitoring and the Error-Related Negativity

ERIC Educational Resources Information Center

Yeung, Nick; Botvinick, Matthew M.; Cohen, Jonathan D.

2004-01-01

According to a recent theory, anterior cingulate cortex is sensitive to response conflict, the coactivation of mutually incompatible responses. The present research develops this theory to provide a new account of the error-related negativity (ERN), a scalp potential observed following errors. Connectionist simulations of response conflict in an…

Colorectal Cancer: The Importance of Early Detection

MedlinePlus

... of this page please turn JavaScript on. Feature: Colorectal Cancer The Importance of Early Detection Past Issues / Summer ... Cancer of the colon or rectum is called colorectal cancer. The colon and the rectum are part of ...

Automated detection of dark and bright lesions in retinal images for early detection of diabetic retinopathy.

PubMed

Akram, Usman M; Khan, Shoab A

2012-10-01

There is an ever-increasing interest in the development of automatic medical diagnosis systems due to the advancement in computing technology and also to improve the service by medical community. The knowledge about health and disease is required for reliable and accurate medical diagnosis. Diabetic Retinopathy (DR) is one of the most common causes of blindness and it can be prevented if detected and treated early. DR has different signs and the most distinctive are microaneurysm and haemorrhage which are dark lesions and hard exudates and cotton wool spots which are bright lesions. Location and structure of blood vessels and optic disk play important role in accurate detection and classification of dark and bright lesions for early detection of DR. In this article, we propose a computer aided system for the early detection of DR. The article presents algorithms for retinal image preprocessing, blood vessel enhancement and segmentation and optic disk localization and detection which eventually lead to detection of different DR lesions using proposed hybrid fuzzy classifier. The developed methods are tested on four different publicly available databases. The presented methods are compared with recently published methods and the results show that presented methods outperform all others.

Detecting Careless Responses to Self-Reported Questionnaires

ERIC Educational Resources Information Center

Kountur, Ronny

2016-01-01

Problem Statement: The use of self-report questionnaires may lead to biases such as careless responses that distort the research outcomes. Early detection of careless responses in self-report questionnaires may reduce error, but little guidance exists in the literature regarding techniques for detecting such careless or random responses in…

Malignant external otitis: early scintigraphic detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Strashun, A.M.; Nejatheim, M.; Goldsmith, S.J.

1984-02-01

Pseudomonas otitis externa in elderly diabetics may extend aggressively to adjacent bone, cranial nerves, meninges, and vessels, leading to a clinical diagnosis of ''malignant'' external otitis. Early diagnosis is necessary for successful treatment. This study compares the findings of initial radiographs, thin-section tomography of temporal bone, CT scans of head and neck, technetium-99m methylene diphosphonate (MDP) and gallium-67 citrate scintigraphy, and single-photon emission computed tomography (SPECT) for detection of temporal bone osteomylitis in ten patients fulfilling the clinical diagnostic criteria of malignant external otitis. Skull radiographs were negative in all of the eight patients studied. Thin-section tomography was positive inmore » one of the seven patients studied using this modality. CT scanning suggested osteomyelitis in three of nine patients. Both Tc-99m and Ga-67 citrate scintigraphy were positive in 10 of 10 patients. These results suggest that technetium and gallium scintigraphy are more sensitive than radiographs and CT scans for early detection of malignant external otitis.« less

Annotation of Korean Learner Corpora for Particle Error Detection

ERIC Educational Resources Information Center

Lee, Sun-Hee; Jang, Seok Bae; Seo, Sang-Kyu

2009-01-01

In this study, we focus on particle errors and discuss an annotation scheme for Korean learner corpora that can be used to extract heuristic patterns of particle errors efficiently. We investigate different properties of particle errors so that they can be later used to identify learner errors automatically, and we provide resourceful annotation…

Predicting the geographic distribution of a species from presence-only data subject to detection errors

USGS Publications Warehouse

Dorazio, Robert M.

2012-01-01

Several models have been developed to predict the geographic distribution of a species by combining measurements of covariates of occurrence at locations where the species is known to be present with measurements of the same covariates at other locations where species occurrence status (presence or absence) is unknown. In the absence of species detection errors, spatial point-process models and binary-regression models for case-augmented surveys provide consistent estimators of a species’ geographic distribution without prior knowledge of species prevalence. In addition, these regression models can be modified to produce estimators of species abundance that are asymptotically equivalent to those of the spatial point-process models. However, if species presence locations are subject to detection errors, neither class of models provides a consistent estimator of covariate effects unless the covariates of species abundance are distinct and independently distributed from the covariates of species detection probability. These analytical results are illustrated using simulation studies of data sets that contain a wide range of presence-only sample sizes. Analyses of presence-only data of three avian species observed in a survey of landbirds in western Montana and northern Idaho are compared with site-occupancy analyses of detections and nondetections of these species.

A concatenated coding scheme for error control

NASA Technical Reports Server (NTRS)

Kasami, T.; Fujiwara, T.; Lin, S.

1986-01-01

In this paper, a concatenated coding scheme for error control in data communications is presented and analyzed. In this scheme, the inner code is used for both error correction and detection; however, the outer code is used only for error detection. A retransmission is requested if either the inner code decoder fails to make a successful decoding or the outer code decoder detects the presence of errors after the inner code decoding. Probability of undetected error (or decoding error) of the proposed scheme is derived. An efficient method for computing this probability is presented. Throughput efficiency of the proposed error control scheme incorporated with a selective-repeat ARQ retransmission strategy is also analyzed. Three specific examples are presented. One of the examples is proposed for error control in the NASA Telecommand System.

Using Renyi entropy to detect early cardiac autonomic neuropathy.

PubMed

Cornforth, David J; Tarvainen, Mika P; Jelinek, Herbert F

2013-01-01

Cardiac Autonomic Neuropathy (CAN) is a disease that involves nerve damage leading to abnormal control of heart rate. CAN affects the correct operation of the heart and in turn leads to associated arrhythmias and heart attack. An open question is to what extent this condition is detectable by the measurement of Heart Rate Variability (HRV). An even more desirable option is to detect CAN in its early, preclinical stage, to improve treatment and outcomes. In previous work we have shown a difference in the Renyi spectrum between participants identified with well-defined CAN and controls. In this work we applied the multi-scale Renyi entropy for identification of early CAN in diabetes patients. Results suggest that Renyi entropy derived from a 20 minute, Lead-II ECG recording, forms a useful contribution to the detection of CAN even in the early stages of the disease. The positive α parameters (1 ≤ α ≤ 5) associated with the Renyi distribution indicated a significant difference (p < 0.00004) between controls and early CAN as well as definite CAN. This is a significant achievement given the simple nature of the information collected, and raises prospects of a simple screening test and improved outcomes of patients.

Residual Error Based Anomaly Detection Using Auto-Encoder in SMD Machine Sound.

PubMed

Oh, Dong Yul; Yun, Il Dong

2018-04-24

Detecting an anomaly or an abnormal situation from given noise is highly useful in an environment where constantly verifying and monitoring a machine is required. As deep learning algorithms are further developed, current studies have focused on this problem. However, there are too many variables to define anomalies, and the human annotation for a large collection of abnormal data labeled at the class-level is very labor-intensive. In this paper, we propose to detect abnormal operation sounds or outliers in a very complex machine along with reducing the data-driven annotation cost. The architecture of the proposed model is based on an auto-encoder, and it uses the residual error, which stands for its reconstruction quality, to identify the anomaly. We assess our model using Surface-Mounted Device (SMD) machine sound, which is very complex, as experimental data, and state-of-the-art performance is successfully achieved for anomaly detection.

Detection of early seizures by diffuse optical tomography

NASA Astrophysics Data System (ADS)

Zhang, Tao; Hajihashemi, M. Reza; Zhou, Junli; Carney, Paul R.; Jiang, Huabei

2015-03-01

In epilepsy it has been challenging to detect early changes in brain activity that occurs prior to seizure onset and to map their origin and evolution for possible intervention. Besides, preclinical seizure experiments need to be conducted in awake animals with images reconstructed and displayed in real-time. We demonstrate using a rat model of generalized epilepsy that diffuse optical tomography (DOT) provides a unique functional neuroimaging modality for noninvasively and continuously tracking brain activities with high spatiotemporal resolution. We developed methods to conduct seizure experiments in fully awake rats using a subject-specific helmet and a restraining mechanism. For the first time, we detected early hemodynamic responses with heterogeneous patterns several minutes preceding the electroencephalographic seizure onset, supporting the presence of a "pre-seizure" state both in anesthetized and awake rats. Using a novel time-series analysis of scattering images, we show that the analysis of scattered diffuse light is a sensitive and reliable modality for detecting changes in neural activity associated with generalized seizure. We found widespread hemodynamic changes evolving from local regions of the bilateral cortex and thalamus to the entire brain, indicating that the onset of generalized seizures may originate locally rather than diffusely. Together, these findings suggest DOT represents a powerful tool for mapping early seizure onset and propagation pathways.

Integrated digital error suppression for improved detection of circulating tumor DNA

PubMed Central

Kurtz, David M.; Chabon, Jacob J.; Scherer, Florian; Stehr, Henning; Liu, Chih Long; Bratman, Scott V.; Say, Carmen; Zhou, Li; Carter, Justin N.; West, Robert B.; Sledge, George W.; Shrager, Joseph B.; Loo, Billy W.; Neal, Joel W.; Wakelee, Heather A.; Diehn, Maximilian; Alizadeh, Ash A.

2016-01-01

High-throughput sequencing of circulating tumor DNA (ctDNA) promises to facilitate personalized cancer therapy. However, low quantities of cell-free DNA (cfDNA) in the blood and sequencing artifacts currently limit analytical sensitivity. To overcome these limitations, we introduce an approach for integrated digital error suppression (iDES). Our method combines in silico elimination of highly stereotypical background artifacts with a molecular barcoding strategy for the efficient recovery of cfDNA molecules. Individually, these two methods each improve the sensitivity of cancer personalized profiling by deep sequencing (CAPP-Seq) by ~3 fold, and synergize when combined to yield ~15-fold improvements. As a result, iDES-enhanced CAPP-Seq facilitates noninvasive variant detection across hundreds of kilobases. Applied to clinical non-small cell lung cancer (NSCLC) samples, our method enabled biopsy-free profiling of EGFR kinase domain mutations with 92% sensitivity and 96% specificity and detection of ctDNA down to 4 in 105 cfDNA molecules. We anticipate that iDES will aid the noninvasive genotyping and detection of ctDNA in research and clinical settings. PMID:27018799

Early detection of pancreatic cancer

PubMed Central

Ahuja, Nita

2015-01-01

Pancreatic adenocarcinoma is a low-incident but highly mortal disease. It accounts for only 3% of estimated new cancer cases each year but is currently the fourth common cause of cancer mortality. By 2030, it is expected to be the 2nd leading cause of cancer death. There is a clear need to diagnose and classify pancreatic cancer at earlier stages in order to give patients the best chance at a definitive cure through surgery. Three precursor lesions that distinctly lead to pancreatic adenocarcinoma have been identified, and we have increasing understanding the non-genetic and genetic risk factors for the disease. With increased understanding about the risk factors, the familial patters, and associated accumulation of genetic mutations involved in pancreatic cancer, we know that there are mutations that occur early in the development of pancreatic cancer and that improved genetic risk-based strategies in screening for pancreatic cancer may be possible and successful at saving or prolonging lives. The remaining challenge is that current standards for diagnosing pancreatic cancer remain too invasive and too costly for widespread screening for pancreatic cancer. Furthermore, the promises of noninvasive methods of detection such as blood, saliva, and stool remain underdeveloped or lack robust testing. However, significant progress has been made, and we are drawing closer to a strategy for the screening and early detection of pancreatic cancer. PMID:26361402

Nanotechnology-Based Detection of Novel microRNAs for Early Diagnosis of Prostate Cancer

DTIC Science & Technology

2017-08-01

AWARD NUMBER: W81XWH-15-1-0157 TITLE: Nanotechnology -Based Detection of Novel microRNAs for Early Diagnosis of Prostate Cancer PRINCIPAL...TITLE AND SUBTITLE Nanotechnology -Based Detection of Novel microRNAs for Early Diagnosis of Prostate Cancer 5a. CONTRACT NUMBER 5b. GRANT NUMBER...identify novel differentially expressed miRNAs in the body fluids (blood, urine, etc.) for an early detection of PCa. Advances in nanotechnology and

Early Detection of Diabetic Retinopathy.

PubMed

Safi, Hamid; Safi, Sare; Hafezi-Moghadam, Ali; Ahmadieh, Hamid

2018-04-18

Diabetic retinopathy (DR) is a primary cause of visual impairment worldwide. Diabetes mellitus may be associated with ophthalmoscopically nonvisible neurovascular damage that progresses before the first clinical signs of DR appear. Reduction of the inner neuroretinal layer thickness on macular optical coherence tomography (OCT), reduced contrast sensitivity primarily at low spatial frequencies, abnormal results in color vision and microperimetry tests, and a prolonged implicit time recorded by multifocal electroretinography have been proposed for detection of early functional and nonvisible structural neuroretinal changes. Vascular abnormalities such as changes in the retinal vessels caliber, architectural indices, and blood flow have been investigated to evaluate the early stages of DR. The results of OCT angiography, retinal vessel oxygen saturation patterns, and elevated levels of circulating blood markers and cytokines have been suggested as early signs of DR. Light-based molecular imaging in rodents has been developed to demonstrate changes in protein expressions in the retinal microvessels as diagnostic biomarkers. Future clinical studies will examine the safety and efficacy of this approach in humans. We summarize all studies related to subclinical DR biomarkers. Copyright © 2018 Elsevier Inc. All rights reserved.

Kick Detection at the Bit: Early Detection via Low Cost Monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tost, Brian; Rose, Kelly; Aminzadeh, Fred

2016-06-07

Formation fluid influxes (i.e. kicks) pose persistent challenges and operational costs during drilling operations. Implications of kicks range in scale but cumulatively result in substantial costs that affect drilling safety, environment, schedule, and infrastructure. Early kick detection presents a low-cost, easily adopted solution for avoiding well control challenges associated with kicks near the bit. Borehole geophysical tools used during the drilling process as part of the logging-while-drilling (LWD) and measurement-while-drilling (MWD) provide the advantage of offering real-time downhole data. LWD/MWD collect data on both the annulus and borehole wall. The annular data are normally treated as background, and are filteredmore » out to isolate the formation measurements. Because kicks will change the local physical properties of annular fluids, bottom-hole measurements are among the first indicators that a formation fluid has invaded the wellbore. This report describes and validates a technique for using the annular portion of LWD/MWD data to facilitate early kick detection using first order principles. The detection technique leverages data from standard and cost-effective technologies that are typically implemented during well drilling, such as MWD/LWD data in combination with mud-pulse telemetry for data transmission.« less

Prescribing Errors Involving Medication Dosage Forms

PubMed Central

Lesar, Timothy S

2002-01-01

CONTEXT Prescribing errors involving medication dose formulations have been reported to occur frequently in hospitals. No systematic evaluations of the characteristics of errors related to medication dosage formulation have been performed. OBJECTIVE To quantify the characteristics, frequency, and potential adverse patient effects of prescribing errors involving medication dosage forms . DESIGN Evaluation of all detected medication prescribing errors involving or related to medication dosage forms in a 631-bed tertiary care teaching hospital. MAIN OUTCOME MEASURES Type, frequency, and potential for adverse effects of prescribing errors involving or related to medication dosage forms. RESULTS A total of 1,115 clinically significant prescribing errors involving medication dosage forms were detected during the 60-month study period. The annual number of detected errors increased throughout the study period. Detailed analysis of the 402 errors detected during the last 16 months of the study demonstrated the most common errors to be: failure to specify controlled release formulation (total of 280 cases; 69.7%) both when prescribing using the brand name (148 cases; 36.8%) and when prescribing using the generic name (132 cases; 32.8%); and prescribing controlled delivery formulations to be administered per tube (48 cases; 11.9%). The potential for adverse patient outcome was rated as potentially “fatal or severe” in 3 cases (0.7%), and “serious” in 49 cases (12.2%). Errors most commonly involved cardiovascular agents (208 cases; 51.7%). CONCLUSIONS Hospitalized patients are at risk for adverse outcomes due to prescribing errors related to inappropriate use of medication dosage forms. This information should be considered in the development of strategies to prevent adverse patient outcomes resulting from such errors. PMID:12213138

Life Detection on the Early Earth

NASA Technical Reports Server (NTRS)

Runnegar, B.

2004-01-01

Finding evidence for first the existence, and then the nature of life on the early Earth or early Mars requires both the recognition of subtle biosignatures and the elimination of false positives. The history of the search for fossils in increasingly older Precambrian strata illustrates these difficulties very clearly, and new observational and theoretical approaches are both needed and being developed. At the microscopic level of investigation, three-dimensional morphological characterization coupled with in situ chemical (isotopic, elemental, structural) analysis is the desirable first step. Geological context is paramount, as has been demonstrated by the controversies over AH84001, the Greenland graphites, and the Apex chert microfossils . At larger scales, the nature of sedimentary bedforms and the structures they display becomes crucial, and here the methods of condensed matter physics prove most useful in discriminating between biological and non-biological constructions. Ultimately, a combination of geochemical, morphological, and contextural evidence may be required for certain life detection on the early Earth or elsewhere.

Detection of early caries by laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Sasazawa, Shuhei; Kakino, Satoko; Matsuura, Yuji

2015-07-01

To improve sensitivity of dental caries detection by laser-induced breakdown spectroscopy (LIBS) analysis, it is proposed to utilize emission peaks in the ultraviolet. We newly focused on zinc whose emission peaks exist in ultraviolet because zinc exists at high concentration in the outer layer of enamel. It was shown that by using ratios between heights of an emission peak of Zn and that of Ca, the detection sensitivity and stability are largely improved. It was also shown that early caries are differentiated from healthy part by properly setting a threshold in the detected ratios. The proposed caries detection system can be applied to dental laser systems such as ones based on Er:YAG-lasers. When ablating early caries part by laser light, the system notices the dentist that the ablation of caries part is finished. We also show the intensity of emission peaks of zinc decreased with ablation with Er:YAG laser light.

Progress towards an AIS early detection monitoring network for the Great Lakes

EPA Science Inventory

As an invasion prone location, the lower St. Louis River system (SLR) has been a case study for ongoing research to develop the framework for a practical Great Lakes monitoring network for early detection of aquatic invasive species (AIS). Early detection, however, necessitates f...

Prevention and Early Detection of Prostate Cancer

PubMed Central

Cuzick, Jack; Thorat, Mangesh A.; Andriole, Gerald; Brawley, Otis W.; Brown, Powel H.; Culig, Zoran; Eeles, Rosalind A.; Ford, Leslie G.; Hamdy, Freddie C.; Holmberg, Lars; Ilic, Dragan; Key, Timothy J.; La Vecchia, Carlo; Lilja, Hans; Marberger, Michael; Meyskens, Frank L.; Minasian, Lori M.; Parker, Chris; Parnes, Howard L.; Perner, Sven; Rittenhouse, Harry; Schalken, Jack; Schmid, Hans-Peter; Schmitz-Dräger, Bernd J.; Schröder, Fritz H.; Stenzl, Arnulf; Tombal, Bertrand; Wilt, Timothy J.; Wolk, Alicja

2014-01-01

Prostate cancer is one of the most common cancers in men and the global burden of this disease is rising. Lifestyle modifications like smoking cessation, exercise and weight control offer opportunities to decrease the risk of developing prostate cancer. Early detection of prostate cancer by PSA screening remains controversial; yet, changes in PSA threshold, frequency of screening, and addition of other biomarkers have potential to minimise overdiagnosis associated with PSA screening. Several new biomarkers appear promising in individuals with elevated PSA levels or those diagnosed with prostate cancer, these are likely to guide in separating individuals who can be spared of aggressive treatment from those who need it. Several pharmacological agents like 5α-reductase inhibitors, aspirin etc. have a potential to prevent development of prostate cancer. In this review, we discuss the current evidence and research questions regarding prevention, early detection of prostate cancer and management of men either at high risk of prostate cancer or diagnosed with low-grade prostate cancer. PMID:25281467

An analysis of four error detection and correction schemes for the proposed Federal standard 1024 (land mobile radio)

NASA Astrophysics Data System (ADS)

Lohrmann, Carol A.

1990-03-01

Interoperability of commercial Land Mobile Radios (LMR) and the military's tactical LMR is highly desirable if the U.S. government is to respond effectively in a national emergency or in a joint military operation. This ability to talk securely and immediately across agency and military service boundaries is often overlooked. One way to ensure interoperability is to develop and promote Federal communication standards (FS). This thesis surveys one area of the proposed FS 1024 for LMRs; namely, the error detection and correction (EDAC) of the message indicator (MI) bits used for cryptographic synchronization. Several EDAC codes are examined (Hamming, Quadratic Residue, hard decision Golay and soft decision Golay), tested on three FORTRAN programmed channel simulations (INMARSAT, Gaussian and constant burst width), compared and analyzed (based on bit error rates and percent of error-free super-frame runs) so that a best code can be recommended. Out of the four codes under study, the soft decision Golay code (24,12) is evaluated to be the best. This finding is based on the code's ability to detect and correct errors as well as the relative ease of implementation of the algorithm.

EEG error potentials detection and classification using time-frequency features for robot reinforcement learning.

PubMed

Boubchir, Larbi; Touati, Youcef; Daachi, Boubaker; Chérif, Arab Ali

2015-08-01

In thought-based steering of robots, error potentials (ErrP) can appear when the action resulting from the brain-machine interface (BMI) classifier/controller does not correspond to the user's thought. Using the Steady State Visual Evoked Potentials (SSVEP) techniques, ErrP, which appear when a classification error occurs, are not easily recognizable by only examining the temporal or frequency characteristics of EEG signals. A supplementary classification process is therefore needed to identify them in order to stop the course of the action and back up to a recovery state. This paper presents a set of time-frequency (t-f) features for the detection and classification of EEG ErrP in extra-brain activities due to misclassification observed by a user exploiting non-invasive BMI and robot control in the task space. The proposed features are able to characterize and detect ErrP activities in the t-f domain. These features are derived from the information embedded in the t-f representation of EEG signals, and include the Instantaneous Frequency (IF), t-f information complexity, SVD information, energy concentration and sub-bands' energies. The experiment results on real EEG data show that the use of the proposed t-f features for detecting and classifying EEG ErrP achieved an overall classification accuracy up to 97% for 50 EEG segments using 2-class SVM classifier.

Mortality in children with early detected congenital central hypothyroidism.

PubMed

Zwaveling-Soonawala, Nitash; Naafs, Jolanda C; Verkerk, Paul H; van Trotsenburg, A S Paul

2018-06-07

Approximately 60-80% of patients with congenital central hypothyroidism (CH-C) have multiple pituitary hormone deficiencies (MPHD), making CH-C a potentially life-threatening disease. Data on mortality in CH-C patients, however, are lacking. To study mortality rate in early detected and treated pediatric CH-C patients in the Netherlands and to investigate whether causes of death were related to pituitary hormone deficiencies. Overall mortality rate, infant mortality rate and under-5 mortality rate were calculated in all children with CH-C detected by neonatal screening between 1-1-1995 and 1-1-2013. Medical charts were reviewed to establish causes of death. 139 children with CH-C were identified, of which 138 could be traced (82 MPHD/56 isolated CHC). Total observation time was 1414 years with a median follow up duration of 10.2 years. The overall mortality rate was 10.9% (15/138). Infant mortality rate (IMR) and under-5 mortality rate were 65.2/1000 (9/138) and 101.4/1000 (14/138), respectively, compared to an IMR of 4.7/1000 and under-5 mortality of 5.4/1000 live born children in the Netherlands during the same time period (p<0.0001). Main causes of death were severe congenital malformations in six patients, asphyxia in two patients, and congenital or early neonatal infection in two patients. Pituitary hormone deficiency was noted as cause of death in only one infant. We report an increased mortality rate in early detected CH-C patients which does not seem to be related to endocrine disease. This suggests that mortality due to pituitary insufficiency is low in an early detected and treated CH-C population.

Radar detection with the Neyman-Pearson criterion using supervised-learning-machines trained with the cross-entropy error

NASA Astrophysics Data System (ADS)

Jarabo-Amores, María-Pilar; la Mata-Moya, David de; Gil-Pita, Roberto; Rosa-Zurera, Manuel

2013-12-01

The application of supervised learning machines trained to minimize the Cross-Entropy error to radar detection is explored in this article. The detector is implemented with a learning machine that implements a discriminant function, which output is compared to a threshold selected to fix a desired probability of false alarm. The study is based on the calculation of the function the learning machine approximates to during training, and the application of a sufficient condition for a discriminant function to be used to approximate the optimum Neyman-Pearson (NP) detector. In this article, the function a supervised learning machine approximates to after being trained to minimize the Cross-Entropy error is obtained. This discriminant function can be used to implement the NP detector, which maximizes the probability of detection, maintaining the probability of false alarm below or equal to a predefined value. Some experiments about signal detection using neural networks are also presented to test the validity of the study.

Does raising type 1 error rate improve power to detect interactions in linear regression models? A simulation study.

PubMed

Durand, Casey P

2013-01-01

Statistical interactions are a common component of data analysis across a broad range of scientific disciplines. However, the statistical power to detect interactions is often undesirably low. One solution is to elevate the Type 1 error rate so that important interactions are not missed in a low power situation. To date, no study has quantified the effects of this practice on power in a linear regression model. A Monte Carlo simulation study was performed. A continuous dependent variable was specified, along with three types of interactions: continuous variable by continuous variable; continuous by dichotomous; and dichotomous by dichotomous. For each of the three scenarios, the interaction effect sizes, sample sizes, and Type 1 error rate were varied, resulting in a total of 240 unique simulations. In general, power to detect the interaction effect was either so low or so high at α = 0.05 that raising the Type 1 error rate only served to increase the probability of including a spurious interaction in the model. A small number of scenarios were identified in which an elevated Type 1 error rate may be justified. Routinely elevating Type 1 error rate when testing interaction effects is not an advisable practice. Researchers are best served by positing interaction effects a priori and accounting for them when conducting sample size calculations.

All-optical photoacoustic imaging and detection of early-stage dental caries

NASA Astrophysics Data System (ADS)

Sampathkumar, Ashwin; Hughes, David A.; Longbottom, Chris; Kirk, Katherine J.

2015-02-01

Dental caries remain one of the most common oral diseases in the world. Current detection methods, such as dental explorer and X-ray radiography, suffer from poor sensitivity and specificity at the earliest (and reversible) stages of the disease because of the small size (< 100 microns) of early-stage lesions. We have developed a fine-resolution (480 nm), ultra-broadband (1 GHz), all-optical photoacoustic imaging (AOPAI) system to image and detect early stages of tooth decay. This AOPAI system provides a non-contact, non-invasive and non-ionizing means of detecting early-stage dental caries. Ex-vivo teeth exhibiting early-stage, white-spot lesions were imaged using AOPAI. Experimental scans targeted each early-stage lesion and a reference healthy enamel region. Photoacoustic (PA) signals were generated in the tooth using a 532-nm pulsed laser and the light-induced broadband ultrasound signal was detected at the surface of the tooth with an optical path-stabilized Michelson interferometer operating at 532 nm. The measured time-domain signal was spatially resolved and back-projected to form 2D and 3D maps of the lesion using k-wave reconstruction methods. Experimental data collected from areas of healthy and diseased enamel indicate that the lesion generated a larger PA response compared to healthy enamel. The PA-signal amplitude alone was able to detect a lesion on the surface of the tooth. However, time- reversal reconstructions of the PA scans also quantitatively depicted the depth of the lesion. 3D PA reconstruction of the diseased tooth indicated a sub-surface lesion at a depth of 0.6 mm, in addition to the surface lesion. These results suggest that our AOPAI system is well suited for rapid clinical assessment of early-stage dental caries. An overview of the AOPAI system, fine-resolution PA and histology results of diseased and healthy teeth will be presented.

A multiobserver study of the effects of including point-of-care patient photographs with portable radiography: a means to detect wrong-patient errors.

PubMed

Tridandapani, Srini; Ramamurthy, Senthil; Provenzale, James; Obuchowski, Nancy A; Evanoff, Michael G; Bhatti, Pamela

2014-08-01

To evaluate whether the presence of facial photographs obtained at the point-of-care of portable radiography leads to increased detection of wrong-patient errors. In this institutional review board-approved study, 166 radiograph-photograph combinations were obtained from 30 patients. Consecutive radiographs from the same patients resulted in 83 unique pairs (ie, a new radiograph and prior, comparison radiograph) for interpretation. To simulate wrong-patient errors, mismatched pairs were generated by pairing radiographs from different patients chosen randomly from the sample. Ninety radiologists each interpreted a unique randomly chosen set of 10 radiographic pairs, containing up to 10% mismatches (ie, error pairs). Radiologists were randomly assigned to interpret radiographs with or without photographs. The number of mismatches was identified, and interpretation times were recorded. Ninety radiologists with 21 ± 10 (mean ± standard deviation) years of experience were recruited to participate in this observer study. With the introduction of photographs, the proportion of errors detected increased from 31% (9 of 29) to 77% (23 of 30; P = .006). The odds ratio for detection of error with photographs to detection without photographs was 7.3 (95% confidence interval: 2.29-23.18). Observer qualifications, training, or practice in cardiothoracic radiology did not influence sensitivity for error detection. There is no significant difference in interpretation time for studies without photographs and those with photographs (60 ± 22 vs. 61 ± 25 seconds; P = .77). In this observer study, facial photographs obtained simultaneously with portable chest radiographs increased the identification of any wrong-patient errors, without substantial increase in interpretation time. This technique offers a potential means to increase patient safety through correct patient identification. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Potential Landslide Early Detection Near Wenchuan by a Qualitatively Multi-Baseline Dinsar Method

NASA Astrophysics Data System (ADS)

Dai, K.; Chen, G.; Xu, Q.; Li, Z.; Qu, T.; Hu, L.; Lu, H.

2018-04-01

Early detection of landslides is important for disaster prevention, which was still very hard work with traditional surveying methods. Interferometric Synthetic Aperture Radar (InSAR) technology provided us the ability to monitor displacements along the slope with wide coverage and high accuracy. In this paper, we proposed a qualitatively multi-baseline DInSAR method to early detect and map the potential landslides. Two sections of China National Highway 317 and 213 were selected as study area. With this method 10 potential landslide areas were early detected and mapped in a quick and effective way. One of them (i.e. Shidaguan landslide) collapsed on August 2017, which was coincident with our results, suggesting that this method could become an effective way to acquire the landslide early detection map to assist the future disaster prevention work.

A patient with an inborn error of vitamin B12 metabolism (cblF) detected by newborn screening.

PubMed

Armour, Christine M; Brebner, Alison; Watkins, David; Geraghty, Michael T; Chan, Alicia; Rosenblatt, David S

2013-07-01

A neonate, who was found to have an elevated C3/C2 ratio and minimally elevated propionylcarnitine on newborn screening, was subsequently identified as having the rare cblF inborn error of vitamin B12 (cobalamin) metabolism. This disorder is characterized by the retention of unmetabolized cobalamin in lysosomes such that it is not readily available for cellular metabolism. Although cultured fibroblasts from the patient did not show the expected functional abnormalities of the cobalamin-dependent enzymes, methylmalonyl-CoA mutase and methionine synthase, they did show reduced synthesis of the active cobalamin cofactors adenosylcobalamin and methylcobalamin. Mutation analysis of LMBRD1 established that the patient had the cblF disorder. Treatment was initiated promptly, and the patient showed a robust response to regular injections of cyanocobalamin, and she was later switched to hydroxocobalamin. Currently, at 3 years of age, the child is clinically well, with appropriate development. Adjusted newborn screening cutoffs in Ontario allowed detection of a deficiency that might not have otherwise been identified, allowing early treatment and perhaps preventing the adverse sequelae seen in some untreated patients.

PRESAGE: Protecting Structured Address Generation against Soft Errors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharma, Vishal C.; Gopalakrishnan, Ganesh; Krishnamoorthy, Sriram

Modern computer scaling trends in pursuit of larger component counts and power efficiency have, unfortunately, lead to less reliable hardware and consequently soft errors escaping into application data ("silent data corruptions"). Techniques to enhance system resilience hinge on the availability of efficient error detectors that have high detection rates, low false positive rates, and lower computational overhead. Unfortunately, efficient detectors to detect faults during address generation (to index large arrays) have not been widely researched. We present a novel lightweight compiler-driven technique called PRESAGE for detecting bit-flips affecting structured address computations. A key insight underlying PRESAGE is that any addressmore » computation scheme that flows an already incurred error is better than a scheme that corrupts one particular array access but otherwise (falsely) appears to compute perfectly. Enabling the flow of errors allows one to situate detectors at loop exit points, and helps turn silent corruptions into easily detectable error situations. Our experiments using PolyBench benchmark suite indicate that PRESAGE-based error detectors have a high error-detection rate while incurring low overheads.« less

Early Detection of Child Abuse

PubMed Central

Shearman, J.K.

1987-01-01

Child abuse, neglect and deprivation are more common than was previously thought. Family physicians are in a unique position to help abusers and abused because of their knowledge of patients from the cradle to the grave. They should use this knowledge to observe clues about parenting potential and should make a thorough family history a routine part of history taking in potential parents. They should also observe patients carefully during pregnancy and early childhood to detect parenting problems and to try to prevent all types of abuse, physical, mental and sexual. PMID:21267341

Time-resolved in vivo luminescence dosimetry for online error detection in pulsed dose-rate brachytherapy.

PubMed

Andersen, Claus E; Nielsen, Søren Kynde; Lindegaard, Jacob Christian; Tanderup, Kari

2009-11-01

The purpose of this study is to present and evaluate a dose-verification protocol for pulsed dose-rate (PDR) brachytherapy based on in vivo time-resolved (1 s time resolution) fiber-coupled luminescence dosimetry. Five cervix cancer patients undergoing PDR brachytherapy (Varian GammaMed Plus with 192Ir) were monitored. The treatments comprised from 10 to 50 pulses (1 pulse/h) delivered by intracavitary/interstitial applicators (tandem-ring systems and/or needles). For each patient, one or two dosimetry probes were placed directly in or close to the tumor region using stainless steel or titanium needles. Each dosimeter probe consisted of a small aluminum oxide crystal attached to an optical fiber cable (1 mm outer diameter) that could guide radioluminescence (RL) and optically stimulated luminescence (OSL) from the crystal to special readout instrumentation. Positioning uncertainty and hypothetical dose-delivery errors (interchanged guide tubes or applicator movements from +/-5 to +/-15 mm) were simulated in software in order to assess the ability of the system to detect errors. For three of the patients, the authors found no significant differences (P>0.01) for comparisons between in vivo measurements and calculated reference values at the level of dose per dwell position, dose per applicator, or total dose per pulse. The standard deviations of the dose per pulse were less than 3%, indicating a stable dose delivery and a highly stable geometry of applicators and dosimeter probes during the treatments. For the two other patients, the authors noted significant deviations for three individual pulses and for one dosimeter probe. These deviations could have been due to applicator movement during the treatment and one incorrectly positioned dosimeter probe, respectively. Computer simulations showed that the likelihood of detecting a pair of interchanged guide tubes increased by a factor of 10 or more for the considered patients when going from integrating to time

Early detection monitoring of Phytophthora ramorum in high-risk forests of California

Treesearch

Ross Meentemeyer; Elizabeth Lotz; David M. Rizzo; Kelly Buja; Walter Mark

2006-01-01

Early detection monitoring is essential for successful control of invasive organisms. Detection of invasions at an early stage of establishment when a population is small and isolated makes eradication more feasible and less costly. Sudden oak death, caused by the recently described pathogen Phytophthora ramorum, is an emerging forest disease that...

Early Detection of Human Focal Seizures Based on Cortical Multiunit Activity

PubMed Central

Park, Yun S.; Hochberg, Leigh R.; Eskandar, Emad N.; Cash, Sydney S.; Truccolo, Wilson

2014-01-01

Approximately 50 million people in the world suffer from epileptic seizures. Reliable early seizure detection could bring significantly beneficial therapeutic alternatives. In recent decades, most approaches have relied on scalp EEG and intracranial EEG signals, but practical early detection for closed-loop seizure control remains challenging. In this study, we present preliminary analyses of an early detection approach based on intracortical neuronal multiunit activity (MUA) recorded from a 96-microelectrode array (MEA). The approach consists of (1) MUA detection from broadband field potentials recorded at 30 kHz by the MEA; (2) MUA feature extraction; (3) cost-sensitive support vector machine classification of ictal and interictal samples; and (4) Kalman-filtering postprocessing. MUA was here defined as the number of threshold crossing (spike counts) applied to the 300 Hz – 6 kHz bandpass filtered local field potentials in 0.1 sec time windows. MUA features explored in this study included the mean, variance, and Fano-factor, computed across the MEA channels. In addition, we used the leading eigenvalues of MUA spatial and temporal correlation matrices computed in 1-sec moving time windows. We assessed the seizure detection approach on out-of-sample data from one-participant recordings with six seizure events and 4.73-hour interictal data. The proposed MUA-based detection approach yielded a 100% sensitivity (6/6) and no false positives, and a latency of 4.17 ± 2.27 sec (mean ± SD) with respect to ECoG-identified seizure onsets. These preliminary results indicate intracortical MUA may be a useful signal for early detection of human epileptic seizures. PMID:25571313

TU-C-BRE-05: Clinical Implications of AAA Commissioning Errors and Ability of Common Commissioning ' Credentialing Procedures to Detect Them

DOE Office of Scientific and Technical Information (OSTI.GOV)

McVicker, A; Oldham, M; Yin, F

2014-06-15

Purpose: To test the ability of the TG-119 commissioning process and RPC credentialing to detect errors in the commissioning process for a commercial Treatment Planning System (TPS). Methods: We introduced commissioning errors into the commissioning process for the Anisotropic Analytical Algorithm (AAA) within the Eclipse TPS. We included errors in Dosimetric Leaf Gap (DLG), electron contamination, flattening filter material, and beam profile measurement with an inappropriately large farmer chamber (simulated using sliding window smoothing of profiles). We then evaluated the clinical impact of these errors on clinical intensity modulated radiation therapy (IMRT) plans (head and neck, low and intermediate riskmore » prostate, mesothelioma, and scalp) by looking at PTV D99, and mean and max OAR dose. Finally, for errors with substantial clinical impact we determined sensitivity of the RPC IMRT film analysis at the midpoint between PTV and OAR using a 4mm distance to agreement metric, and of a 7% TLD dose comparison. We also determined sensitivity of the 3 dose planes of the TG-119 C-shape IMRT phantom using gamma criteria of 3% 3mm. Results: The largest clinical impact came from large changes in the DLG with a change of 1mm resulting in up to a 5% change in the primary PTV D99. This resulted in a discrepancy in the RPC TLDs in the PTVs and OARs of 7.1% and 13.6% respectively, which would have resulted in detection. While use of incorrect flattening filter caused only subtle errors (<1%) in clinical plans, the effect was most pronounced for the RPC TLDs in the OARs (>6%). Conclusion: The AAA commissioning process within the Eclipse TPS is surprisingly robust to user error. When errors do occur, the RPC and TG-119 commissioning credentialing criteria are effective at detecting them; however OAR TLDs are the most sensitive despite the RPC currently excluding them from analysis.« less

Early detection and rapid response

USGS Publications Warehouse

Westbrooks, Randy G.; Eplee, Robert E.; Simberloff, Daniel; Rejmánek, Marcel

2011-01-01

Prevention is the first line of defense against introduced invasive species - it is always preferable to prevent the introduction of new invaders into a region or country. However, it is not always possible to detect all alien hitchhikers imported in cargo, or to predict with any degree of certainty which introduced species will become invasive over time. Fortunately, the majority of introduced plants and animals don't become invasive. But, according to scientists at Cornell University, costs and losses due to species that do become invasive are now estimated to be over $137 billion/year in the United States. Early detection and rapid response (EDRR) is the second line of defense against introduced invasive species - EDRR is the preferred management strategy for preventing the establishment and spread of invasive species. Over the past 50 years, there has been a gradual shift away from large and medium scale federal/state single-agency-led weed eradication programs in the United States, to smaller interagency-led projects involving impacted and potential stakeholders. The importance of volunteer weed spotters in detecting and reporting suspected new invasive species has also been recognized in recent years.

Form Overrides Meaning When Bilinguals Monitor for Errors

PubMed Central

Ivanova, Iva; Ferreira, Victor S.; Gollan, Tamar H.

2016-01-01

Bilinguals rarely produce unintended language switches, which may in part be because switches are detected and corrected by an internal monitor. But are language switches easier or harder to detect than within-language semantic errors? To approximate internal monitoring, bilinguals listened (Experiment 1) or read aloud (Experiment 2) stories, and detected language switches (translation equivalents or semantically unrelated to expected words) and within-language errors (semantically related or unrelated to expected words). Bilinguals detected semantically related within-language errors most slowly and least accurately, language switches more quickly and accurately than within-language errors, and (in Experiment 2), translation equivalents as quickly and accurately as unrelated language switches. These results suggest that internal monitoring of form (which can detect mismatches in language membership) completes earlier than, and is independent of, monitoring of meaning. However, analysis of reading times prior to error detection revealed meaning violations to be more disruptive for processing than language violations. PMID:28649169

Health responsibility and workplace health promotion among women: early detection of cancer.

PubMed

Kushnir, T; Rabinowitz, S; Melamed, S; Weisberg, E; Ribak, J

1995-01-01

The importance of health responsibility as one aspect of a health-promoting lifestyle has been emphasized repeatedly. Yet there are only a few empirical studies of its role in preventive behavior. We examined the relationship between health responsibility and early-detection practices for breast and cervical cancer. A group of 253 women employees of a large industrial company participated in a cancer screening program subsidized by the employer. They completed questionnaires assessing health responsibility and reported early-detection practices: frequency of breast self-examination and physician breast examinations, frequency of Pap tests, and time lapsed since last Pap test and breast examinations. Health responsibility was a significant independent predictor of breast examination indicators but not of Pap tests. Education level was an important predictor for Pap tests, and age predicted most early-detection practices. The findings lend some support to the role of health responsibility in initiating breast examinations. Better prediction of early-detection practices could be achieved by adding cognitive and emotional components to the existing responsibility scale and by distinguishing between retrospective and prospective responsibility.

Mathematical models for the early detection and treatment of colorectal cancer.

PubMed

Harper, P R; Jones, S K

2005-05-01

Colorectal cancer is a major cause of death for men and women in the Western world. When the cancer is detected through an awareness of the symptoms by a patient, typically it is at an advanced stage. It is possible to detect cancer at an early stage through screening and the marked differences in survival for early and late stages provide the incentive for the primary prevention or early detection of colorectal cancer. This paper considers mathematical models for colorectal cancer screening together with models for the treatment of patients. Illustrative results demonstrate that detailed attention to the processes involved in diseases, interventions and treatment enable us to combine data and expert knowledge from various sources. Thus a detailed operational model is a very useful tool in helping to make decisions about screening at national and local levels.

Innovative design for early detection of invasive species

EPA Science Inventory

Non-native aquatic species impose significant ecological impacts and rising financial costs in marine and freshwater ecosystems worldwide. Early detection of invasive species, as they enter a vulnerable ecosystem, is critical to successful containment and eradication. ORD, at t...

Early esophageal cancer detection using RF classifiers

NASA Astrophysics Data System (ADS)

Janse, Markus H. A.; van der Sommen, Fons; Zinger, Svitlana; Schoon, Erik J.; de With, Peter H. N.

2016-03-01

Esophageal cancer is one of the fastest rising forms of cancer in the Western world. Using High-Definition (HD) endoscopy, gastroenterology experts can identify esophageal cancer at an early stage. Recent research shows that early cancer can be found using a state-of-the-art computer-aided detection (CADe) system based on analyzing static HD endoscopic images. Our research aims at extending this system by applying Random Forest (RF) classification, which introduces a confidence measure for detected cancer regions. To visualize this data, we propose a novel automated annotation system, employing the unique characteristics of the previous confidence measure. This approach allows reliable modeling of multi-expert knowledge and provides essential data for real-time video processing, to enable future use of the system in a clinical setting. The performance of the CADe system is evaluated on a 39-patient dataset, containing 100 images annotated by 5 expert gastroenterologists. The proposed system reaches a precision of 75% and recall of 90%, thereby improving the state-of-the-art results by 11 and 6 percentage points, respectively.

PRESAGE: Protecting Structured Address Generation against Soft Errors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharma, Vishal C.; Gopalakrishnan, Ganesh; Krishnamoorthy, Sriram

Modern computer scaling trends in pursuit of larger component counts and power efficiency have, unfortunately, lead to less reliable hardware and consequently soft errors escaping into application data ("silent data corruptions"). Techniques to enhance system resilience hinge on the availability of efficient error detectors that have high detection rates, low false positive rates, and lower computational overhead. Unfortunately, efficient detectors to detect faults during address generation have not been widely researched (especially in the context of indexing large arrays). We present a novel lightweight compiler-driven technique called PRESAGE for detecting bit-flips affecting structured address computations. A key insight underlying PRESAGEmore » is that any address computation scheme that propagates an already incurred error is better than a scheme that corrupts one particular array access but otherwise (falsely) appears to compute perfectly. Ensuring the propagation of errors allows one to place detectors at loop exit points and helps turn silent corruptions into easily detectable error situations. Our experiments using the PolyBench benchmark suite indicate that PRESAGE-based error detectors have a high error-detection rate while incurring low overheads.« less

Working memory load impairs the evaluation of behavioral errors in the medial frontal cortex.

PubMed

Maier, Martin E; Steinhauser, Marco

2017-10-01

Early error monitoring in the medial frontal cortex enables error detection and the evaluation of error significance, which helps prioritize adaptive control. This ability has been assumed to be independent from central capacity, a limited pool of resources assumed to be involved in cognitive control. The present study investigated whether error evaluation depends on central capacity by measuring the error-related negativity (Ne/ERN) in a flanker paradigm while working memory load was varied on two levels. We used a four-choice flanker paradigm in which participants had to classify targets while ignoring flankers. Errors could be due to responding either to the flankers (flanker errors) or to none of the stimulus elements (nonflanker errors). With low load, the Ne/ERN was larger for flanker errors than for nonflanker errors-an effect that has previously been interpreted as reflecting differential significance of these error types. With high load, no such effect of error type on the Ne/ERN was observable. Our findings suggest that working memory load does not impair the generation of an Ne/ERN per se but rather impairs the evaluation of error significance. They demonstrate that error monitoring is composed of capacity-dependent and capacity-independent mechanisms. © 2017 Society for Psychophysiological Research.

FMEA: a model for reducing medical errors.

PubMed

Chiozza, Maria Laura; Ponzetti, Clemente

2009-06-01

Patient safety is a management issue, in view of the fact that clinical risk management has become an important part of hospital management. Failure Mode and Effect Analysis (FMEA) is a proactive technique for error detection and reduction, firstly introduced within the aerospace industry in the 1960s. Early applications in the health care industry dating back to the 1990s included critical systems in the development and manufacture of drugs and in the prevention of medication errors in hospitals. In 2008, the Technical Committee of the International Organization for Standardization (ISO), licensed a technical specification for medical laboratories suggesting FMEA as a method for prospective risk analysis of high-risk processes. Here we describe the main steps of the FMEA process and review data available on the application of this technique to laboratory medicine. A significant reduction of the risk priority number (RPN) was obtained when applying FMEA to blood cross-matching, to clinical chemistry analytes, as well as to point-of-care testing (POCT).

Early optical detection of cerebral edema in vivo.

PubMed

Gill, Amandip S; Rajneesh, Kiran F; Owen, Christopher M; Yeh, James; Hsu, Mike; Binder, Devin K

2011-02-01

Cerebral edema is a significant cause of morbidity and mortality in diverse disease states. Currently, the means to detect progressive cerebral edema in vivo includes the use of intracranial pressure (ICP) monitors and/or serial radiological studies. However, ICP measurements exhibit a high degree of variability, and ICP monitors detect edema only after it becomes sufficient to significantly raise ICP. The authors report the development of 2 distinct minimally invasive fiberoptic near-infrared (NIR) techniques able to directly detect early cerebral edema. Cytotoxic brain edema was induced in adult CD1 mice via water intoxication by intraperitoneal water administration (30% body weight intraperitoneally). An implantable dual-fiberoptic probe was stereotactically placed into the cerebral cortex and connected to optical source and detector hardware. Optical sources consisted of either broadband halogen illumination or a single-wavelength NIR laser diode, and the detector was a sensitive NIR spectrometer or optical power meter. In one subset of animals, a left-sided craniectomy was performed to obtain cortical biopsies for water-content determination to verify cerebral edema. In another subset of animals, an ICP transducer was placed on the contralateral cortex, which was synchronized to a computer and time stamped. Using either broadband illumination with NIR spectroscopy or single-wavelength laser diode illumination with optical power meter detection, the authors detected a reduction in NIR optical reflectance during early cerebral edema. The time intervals between water injection (Time Point 0), optical trigger (defined as a 2-SD change in optical reflectance from baseline), and defined threshold ICP values of 10, 15 and 20 mm Hg were calculated. Reduction in NIR reflectance occurred significantly earlier than any of the ICP thresholds (p < 0.001). Saline-injected control mice exhibited a steady baseline optical signal. There was a significant correlation between

[Autism, neurodevelopment and early detection].

PubMed

Martos-Pérez, J

2006-02-13

Autistic disorder is briefly explained and defined in the light of recent research. From the perspective offered by ontogenesis and the acquisitions that take place during normal development, we present an updated vision of the genesis of autistic disorder and also review the most significant data provided by the different studies that have been conducted on the subject. Detection of the disorder is clearly a difficult task before the age of one year and, in any case, the earliest symptoms are clearly linked to the social and communicative interaction that characteristically takes place at the end of the infant's first year of life. Early detection of the disorder is made possible precisely because of alterations in social and communicative development and, in general, the appearance of psychological functions that play a significant role in the process of humanisation. The article concludes by pointing out the need for further studies that focus on the possible alteration of earlier socio-emotional and affective manifestations.

Early Career Teachers' Ability to Focus on Typical Students Errors in Relation to the Complexity of a Mathematical Topic

ERIC Educational Resources Information Center

Pankow, Lena; Kaiser, Gabriele; Busse, Andreas; König, Johannes; Blömeke, Sigrid; Hoth, Jessica; Döhrmann, Martina

2016-01-01

The paper presents results from a computer-based assessment in which 171 early career mathematics teachers from Germany were asked to anticipate typical student errors on a given mathematical topic and identify them under time constraints. Fast and accurate perception and knowledge-based judgments are widely accepted characteristics of teacher…

What are incident reports telling us? A comparative study at two Australian hospitals of medication errors identified at audit, detected by staff and reported to an incident system

PubMed Central

Westbrook, Johanna I.; Li, Ling; Lehnbom, Elin C.; Baysari, Melissa T.; Braithwaite, Jeffrey; Burke, Rosemary; Conn, Chris; Day, Richard O.

2015-01-01

Objectives To (i) compare medication errors identified at audit and observation with medication incident reports; (ii) identify differences between two hospitals in incident report frequency and medication error rates; (iii) identify prescribing error detection rates by staff. Design Audit of 3291patient records at two hospitals to identify prescribing errors and evidence of their detection by staff. Medication administration errors were identified from a direct observational study of 180 nurses administering 7451 medications. Severity of errors was classified. Those likely to lead to patient harm were categorized as ‘clinically important’. Setting Two major academic teaching hospitals in Sydney, Australia. Main Outcome Measures Rates of medication errors identified from audit and from direct observation were compared with reported medication incident reports. Results A total of 12 567 prescribing errors were identified at audit. Of these 1.2/1000 errors (95% CI: 0.6–1.8) had incident reports. Clinically important prescribing errors (n = 539) were detected by staff at a rate of 218.9/1000 (95% CI: 184.0–253.8), but only 13.0/1000 (95% CI: 3.4–22.5) were reported. 78.1% (n = 421) of clinically important prescribing errors were not detected. A total of 2043 drug administrations (27.4%; 95% CI: 26.4–28.4%) contained ≥1 errors; none had an incident report. Hospital A had a higher frequency of incident reports than Hospital B, but a lower rate of errors at audit. Conclusions Prescribing errors with the potential to cause harm frequently go undetected. Reported incidents do not reflect the profile of medication errors which occur in hospitals or the underlying rates. This demonstrates the inaccuracy of using incident frequency to compare patient risk or quality performance within or across hospitals. New approaches including data mining of electronic clinical information systems are required to support more effective medication error detection and

What are incident reports telling us? A comparative study at two Australian hospitals of medication errors identified at audit, detected by staff and reported to an incident system.

PubMed

Westbrook, Johanna I; Li, Ling; Lehnbom, Elin C; Baysari, Melissa T; Braithwaite, Jeffrey; Burke, Rosemary; Conn, Chris; Day, Richard O

2015-02-01

To (i) compare medication errors identified at audit and observation with medication incident reports; (ii) identify differences between two hospitals in incident report frequency and medication error rates; (iii) identify prescribing error detection rates by staff. Audit of 3291 patient records at two hospitals to identify prescribing errors and evidence of their detection by staff. Medication administration errors were identified from a direct observational study of 180 nurses administering 7451 medications. Severity of errors was classified. Those likely to lead to patient harm were categorized as 'clinically important'. Two major academic teaching hospitals in Sydney, Australia. Rates of medication errors identified from audit and from direct observation were compared with reported medication incident reports. A total of 12 567 prescribing errors were identified at audit. Of these 1.2/1000 errors (95% CI: 0.6-1.8) had incident reports. Clinically important prescribing errors (n = 539) were detected by staff at a rate of 218.9/1000 (95% CI: 184.0-253.8), but only 13.0/1000 (95% CI: 3.4-22.5) were reported. 78.1% (n = 421) of clinically important prescribing errors were not detected. A total of 2043 drug administrations (27.4%; 95% CI: 26.4-28.4%) contained ≥ 1 errors; none had an incident report. Hospital A had a higher frequency of incident reports than Hospital B, but a lower rate of errors at audit. Prescribing errors with the potential to cause harm frequently go undetected. Reported incidents do not reflect the profile of medication errors which occur in hospitals or the underlying rates. This demonstrates the inaccuracy of using incident frequency to compare patient risk or quality performance within or across hospitals. New approaches including data mining of electronic clinical information systems are required to support more effective medication error detection and mitigation. © The Author 2015. Published by Oxford University Press in association

Factors Influencing Early Detection of Oral Cancer by Primary Health-Care Professionals.

PubMed

Hassona, Y; Scully, C; Shahin, A; Maayta, W; Sawair, F

2016-06-01

The purposes of this study are to determine early detection practices performed by primary healthcare professionals, to compare medical and dental sub-groups, and to identify factors that influence the ability of medical and dental practitioners to recognize precancerous changes and clinical signs of oral cancer. A 28-item survey instrument was used to interview a total of 330 Jordanian primary health-care professionals (165 dental and 165 medical). An oral cancer knowledge scale (0 to 31) was generated from correct responses on oral cancer general knowledge. An early detection practice scale (0 to 24) was generated from the reported usage and frequency of procedures in oral cancer examination. Also, a diagnostic ability scale (0 to 100) was generated from correct selections of suspicious oral lesions. Only 17.8 % of the participants reported that they routinely performed oral cancer screening in practices. Their oral cancer knowledge scores ranged from 3 to 31 with a mean of 15.6. The early detection practice scores ranged from 2 to 21 with a mean of 11.6. A significant positive correlation was found between knowledge scores and early detection practice scores (r = 0.22; p < 0.001). The diagnostic ability scores ranged from 11.5 to 96 with a mean of 43.6. The diagnostic ability score was significantly correlated with knowledge scores (r = 0.39; p < 0.001), but not with early detection practice scores (r = 0.01; p = 0.92). Few significant differences were found between medical and dental primary care professionals. Continuous education courses on early diagnosis of oral cancer and oral mucosal lesions are needed for primary health-care professionals.

Detecting Signatures of GRACE Sensor Errors in Range-Rate Residuals

NASA Astrophysics Data System (ADS)

Goswami, S.; Flury, J.

2016-12-01

In order to reach the accuracy of the GRACE baseline, predicted earlier from the design simulations, efforts are ongoing since a decade. GRACE error budget is highly dominated by noise from sensors, dealiasing models and modeling errors. GRACE range-rate residuals contain these errors. Thus, their analysis provides an insight to understand the individual contribution to the error budget. Hence, we analyze the range-rate residuals with focus on contribution of sensor errors due to mis-pointing and bad ranging performance in GRACE solutions. For the analysis of pointing errors, we consider two different reprocessed attitude datasets with differences in pointing performance. Then range-rate residuals are computed from these two datasetsrespectively and analysed. We further compare the system noise of four K-and Ka- band frequencies of the two spacecrafts, with range-rate residuals. Strong signatures of mis-pointing errors can be seen in the range-rate residuals. Also, correlation between range frequency noise and range-rate residuals are seen.

Early detection of sporadic pancreatic cancer: strategic map for innovation--a white paper.

PubMed

Kenner, Barbara J; Chari, Suresh T; Cleeter, Deborah F; Go, Vay Liang W

2015-07-01

Innovation leading to significant advances in research and subsequent translation to clinical practice is urgently necessary in early detection of sporadic pancreatic cancer. Addressing this need, the Early Detection of Sporadic Pancreatic Cancer Summit Conference was conducted by Kenner Family Research Fund in conjunction with the 2014 American Pancreatic Association and Japan Pancreas Society Meeting. International interdisciplinary scientific representatives engaged in strategic facilitated conversations based on distinct areas of inquiry: Case for Early Detection: Definitions, Detection, Survival, and Challenges; Biomarkers for Early Detection; Imaging; and Collaborative Studies. Ideas generated from the summit have led to the development of a Strategic Map for Innovation built upon 3 components: formation of an international collaborative effort, design of an actionable strategic plan, and implementation of operational standards, research priorities, and first-phase initiatives. Through invested and committed efforts of leading researchers and institutions, philanthropic partners, government agencies, and supportive business entities, this endeavor will change the future of the field and consequently the survival rate of those diagnosed with pancreatic cancer.

Error coding simulations

NASA Technical Reports Server (NTRS)

Noble, Viveca K.

1993-01-01

There are various elements such as radio frequency interference (RFI) which may induce errors in data being transmitted via a satellite communication link. When a transmission is affected by interference or other error-causing elements, the transmitted data becomes indecipherable. It becomes necessary to implement techniques to recover from these disturbances. The objective of this research is to develop software which simulates error control circuits and evaluate the performance of these modules in various bit error rate environments. The results of the evaluation provide the engineer with information which helps determine the optimal error control scheme. The Consultative Committee for Space Data Systems (CCSDS) recommends the use of Reed-Solomon (RS) and convolutional encoders and Viterbi and RS decoders for error correction. The use of forward error correction techniques greatly reduces the received signal to noise needed for a certain desired bit error rate. The use of concatenated coding, e.g. inner convolutional code and outer RS code, provides even greater coding gain. The 16-bit cyclic redundancy check (CRC) code is recommended by CCSDS for error detection.

A combination of circulating miRNAs for the early detection of ovarian cancer

PubMed Central

Yokoi, Akira; Yoshioka, Yusuke; Hirakawa, Akihiro; Yamamoto, Yusuke; Ishikawa, Mitsuya; Ikeda, Shun-ichi; Kato, Tomoyasu; Niimi, Kaoru; Kajiyama, Hiroaki; Kikkawa, Fumitaka; Ochiya, Takahiro

2017-01-01

Ovarian cancer is the leading cause of gynecologic cancer mortality, due to the difficulty of early detection. Current screening methods lack sufficient accuracy, and it is still challenging to propose a new early detection method that improves patient outcomes with less-invasiveness. Although many studies have suggested the utility of circulating microRNAs in cancer detection, their potential for early detection remains elusive. Here, we develop novel predictive models using a combination of 8 circulating serum miRNAs. This method was able to successfully distinguish ovarian cancer patients from healthy controls (area under the curve, 0.97; sensitivity, 0.92; and specificity, 0.91) and early-stage ovarian cancer from patients with benign tumors (0.91, 0.86 and 0.83, respectively). This method also enables subtype classification in 4 types of epithelial ovarian cancer. Furthermore, it is found that most of the 8 miRNAs were packaged in extracellular vesicles, including exosomes, derived from ovarian cancer cells, and they were circulating in murine blood stream. The circulating miRNAs described in this study may serve as biomarkers for ovarian cancer patients. Early detection and subtype determination prior to surgery are crucial for clinicians to design an effective treatment strategy for each patient, as is the goal of precision medicine. PMID:29163790

[CODEPEH 2014 recommendations for the early detection of delayed hearing loss].

PubMed

Núñez-Batalla, Faustino; Jáudenes-Casaubón, Carmen; Sequí-Canet, José Miguel; Vivanco-Allende, Ana; Zubicaray-Ugarteche, José

2016-10-01

The latest scientific literature considers early diagnosis of deafness as key element to define the educational prognosis and inclusion of the deaf child, as advantage can be taken in the critical period of development (0-4 years). Highly significant differences exist between those deaf persons who have been stimulated early and those who have received late or inappropriate intervention. Early identification of late-onset disorders requires special attention and knowledge of all childcare professionals. Programs and additional actions beyond neonatal screening should be designed and planned in order to ensure that every child with a significant hearing loss is detected early. For this purpose, the Committee for the Early Detection of Deafness (CODEPEH) would like to highlight the need for continuous monitoring on the hearing health of children. And, for this reason, CODEPEH drafts the recommendations included in the present document. Copyright © 2015 Asociación Española de Pediatría. Publicado por Elsevier España, S.L.U. All rights reserved.

Early hearing detection and intervention: 2010 CODEPEH recommendation.

PubMed

Trinidad-Ramos, Germán; de Aguilar, Valentín Alzina; Jaudenes-Casaubón, Carmen; Núñez-Batalla, Faustino; Sequí-Canet, José Miguel

2010-01-01

Newborn hearing screening is currently performed routinely in many regional health-care systems in Spain. Despite the remarkable expansion in newborn hearing screening since 2000, its feasibility and the benefits of early identification and intervention, many major challenges still remain. In this article, the Committee for the Early Detection of Hearing Loss (Comisión para la Detección Precoz de la Hipoacusia, CODEPEH) updates the recommendations that are considered important for the future development of early hearing detection and intervention (EDHI) systems in the following points: 1. Screening protocols: Separate protocols are recommended for NICU (Neonatal Intensive Care Units) and well-infant nurseries. 2. Diagnostic audiology evaluation. Professionals with skills and expertise in evaluating newborn and young infants should provide diagnosis, selection and fitting of amplification devices. 3. Medical evaluation. Risk factors for congenital and acquired hearing loss have been combined in a single list rather than grouped by time of onset. A stepwise diagnostic paradigm is diagnostically more efficient and cost-effective than a simultaneous testing approach. 4. Early intervention and surveillance. All individuals providing services to infants with hearing loss should have specialized training and expertise in the development of audition, speech and language. Regular surveillance should be performed on developmental milestones, auditory skills, parental concerns, and middle ear status. 5. Quality control. Data management as part of an integrated system is important to monitor and improve the quality of EDHI services. 2009 Elsevier España, S.L. All rights reserved.

Early detection of fungi damage in citrus using NIR spectroscopy

NASA Astrophysics Data System (ADS)

Blasco, Jose; Ortiz, Coral; Sabater, Maria D.; Molto, Enrique

2000-12-01

Early detection of defects and diseases in fruit helps to correctly classify them and make more adequate decisions about the destination of the product: internal market, export or industry. An early fungi infection detection is especially important because a few infected fruits can disseminate the infection to a whole batch, causing great economic losses and affecting to further exports. Ensure products with excellent quality and absolute absence of fungi infections is particularly important in those batches for long conservation or to be exported. The main objective of this work is to detect the fungi infections before they can be visible. Near Infrared spectroscopy has been employed in this work, because it is a non-destructive technique and can be easily implemented on line due to the high speed and simplicity of the process.

Detection of pointing errors with CMOS-based camera in intersatellite optical communications

NASA Astrophysics Data System (ADS)

Yu, Si-yuan; Ma, Jing; Tan, Li-ying

2005-01-01

For very high data rates, intersatellite optical communications hold a potential performance edge over microwave communications. Acquisition and Tracking problem is critical because of the narrow transmit beam. A single array detector in some systems performs both spatial acquisition and tracking functions to detect pointing errors, so both wide field of view and high update rate is required. The past systems tend to employ CCD-based camera with complex readout arrangements, but the additional complexity reduces the applicability of the array based tracking concept. With the development of CMOS array, CMOS-based cameras can employ the single array detector concept. The area of interest feature of the CMOS-based camera allows a PAT system to specify portion of the array. The maximum allowed frame rate increases as the size of the area of interest decreases under certain conditions. A commercially available CMOS camera with 105 fps @ 640×480 is employed in our PAT simulation system, in which only part pixels are used in fact. Beams angle varying in the field of view can be detected after getting across a Cassegrain telescope and an optical focus system. Spot pixel values (8 bits per pixel) reading out from CMOS are transmitted to a DSP subsystem via IEEE 1394 bus, and pointing errors can be computed by the centroid equation. It was shown in test that: (1) 500 fps @ 100×100 is available in acquisition when the field of view is 1mrad; (2)3k fps @ 10×10 is available in tracking when the field of view is 0.1mrad.

A Virtual Bioinformatics Knowledge Environment for Early Cancer Detection

NASA Technical Reports Server (NTRS)

Crichton, Daniel; Srivastava, Sudhir; Johnsey, Donald

2003-01-01

Discovery of disease biomarkers for cancer is a leading focus of early detection. The National Cancer Institute created a network of collaborating institutions focused on the discovery and validation of cancer biomarkers called the Early Detection Research Network (EDRN). Informatics plays a key role in enabling a virtual knowledge environment that provides scientists real time access to distributed data sets located at research institutions across the nation. The distributed and heterogeneous nature of the collaboration makes data sharing across institutions very difficult. EDRN has developed a comprehensive informatics effort focused on developing a national infrastructure enabling seamless access, sharing and discovery of science data resources across all EDRN sites. This paper will discuss the EDRN knowledge system architecture, its objectives and its accomplishments.

Virtual multiple errands test (VMET): a virtual reality-based tool to detect early executive functions deficit in Parkinson's disease.

PubMed

Cipresso, Pietro; Albani, Giovanni; Serino, Silvia; Pedroli, Elisa; Pallavicini, Federica; Mauro, Alessandro; Riva, Giuseppe

2014-01-01

Several recent studies have pointed out that early impairment of executive functions (EFs) in Parkinson's Disease (PD) may be a crucial marker to detect patients at risk for developing dementia. The main objective of this study was to compare the performances of PD patients with mild cognitive impairment (PD-MCI) with PD patients with normal cognition (PD-NC) and a control group (CG) using a traditional assessment of EFs and the Virtual Multiple Errands Test (VMET), a virtual reality (VR)-based tool. In order to understand which subcomponents of EFs are early impaired, this experimental study aimed to investigate specifically which instrument best discriminates among these three groups. The study included three groups of 15 individuals each (for a total of 45 participants): 15 PD-NC; 15 PD-MCI, and 15 cognitively healthy individuals (CG). To assess the global neuropsychological functioning and the EFs, several tests (including the Mini Mental State Examination (MMSE), Clock Drawing Test, and Tower of London test) were administered to the participants. The VMET was used for a more ecologically valid neuropsychological evaluation of EFs. Findings revealed significant differences in the VMET scores between the PD-NC patients vs. the controls. In particular, patients made more errors in the tasks of the VMET, and showed a poorer ability to use effective strategies to complete the tasks. This VMET result seems to be more sensitive in the early detection of executive deficits because these two groups did not differ in the traditional assessment of EFs (neuropsychological battery). This study offers initial evidence that a more ecologically valid evaluation of EFs is more likely to lead to detection of subtle executive deficits.

Early indices of deviance detection in humans and animal models.

PubMed

Grimm, Sabine; Escera, Carles; Nelken, Israel

2016-04-01

Detecting unexpected stimuli in the environment is a critical function of the auditory system. Responses to unexpected "deviant" sounds are enhanced compared to responses to expected stimuli. At the human scalp, deviance detection is reflected in the mismatch negativity (MMN) and in an enhancement of the middle-latency response (MLR). Single neurons often respond more strongly to a stimulus when rare than when common, a phenomenon termed stimulus-specific adaptation (SSA). Here we compare stimulus-specific adaptation with scalp-recorded deviance-related responses. We conclude that early markers of deviance detection in the time range of the MLR could be a direct correlate of cortical SSA. Both occur at an early level of cortical activation, both are robust findings with low-probability stimuli, and both show properties of genuine deviance detection. Their causal relation with the later scalp-recorded MMN is a key question in this field. Copyright © 2015 Elsevier B.V. All rights reserved.

[Early detection of autism in children. Review of literature].

PubMed

Pisula, E

1997-01-01

The difficulties with early detection of autistic disorder in children are discussed. DSM-IV diagnostic criteria are presented. Usefulness of clinical interview and clinical experiment in diagnosing autistic disorder are analyzed.

A decade of aquatic invasive species (AIS) early detection ...

EPA Pesticide Factsheets

As an invasion prone location, the St. Louis River Estuary (SLRE) has been a case study for ongoing research to develop the framework for a practical Great Lakes monitoring network for early detection of aquatic invasive species (AIS). Early detection, however, necessitates finding new invaders before they are common. Here we outline our research (2005 present) approach and findings, including strategies to increase detection efficiency by optimizing specimen collection and identification methods. Initial surveys were designed to over-sample to amass data as the basis for numerical experiments to investigate to the effort required for a given detection probability. Later surveys tested the outcome of implementing these strategies, examined the potential benefits of sampling larval fish instead of adults and explored the prospect of using advanced DNA based methods as an alternative to traditional taxonomy. To date we have identified several previously undetected invertebrate invaders, developed survey design and gear recommendations and have refined the search strategy for systems beyond the SLRE. In addition, because we’ve accumulated such a large body of data we now have the basis to show spatial-temporal trends for native and non-native species in the SLRE. not applicable

Error-Analysis for Correctness, Effectiveness, and Composing Procedure.

ERIC Educational Resources Information Center

Ewald, Helen Rothschild

The assumptions underpinning grammatical mistakes can often be detected by looking for patterns of errors in a student's work. Assumptions that negatively influence rhetorical effectiveness can similarly be detected through error analysis. On a smaller scale, error analysis can also reveal assumptions affecting rhetorical choice. Snags in the…

TU-G-BRD-01: Quantifying the Effectiveness of the Physics Pre-Treatment Plan Review for Detecting Errors in Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gopan, O; Novak, A; Zeng, J

Purpose: Physics pre-treatment plan review is crucial to safe radiation oncology treatments. Studies show that most errors originate in treatment planning, which underscores the importance of physics plan review. As a QA measure the physics review is of fundamental importance and is central to the profession of medical physics. However, little is known about its effectiveness. More hard data are needed. The purpose of this study was to quantify the effectiveness of physics review with the goal of improving it. Methods: This study analyzed 315 “potentially serious” near-miss incidents within an institutional incident learning system collected over a two-year period.more » 139 of these originated prior to physics review and were found at the review or after. Incidents were classified as events that: 1)were detected by physics review, 2)could have been detected (but were not), and 3)could not have been detected. Category 1 and 2 events were classified by which specific check (within physics review) detected or could have detected the event. Results: Of the 139 analyzed events, 73/139 (53%) were detected or could have been detected by the physics review; although, 42/73 (58%) were not actually detected. 45/73 (62%) errors originated in treatment planning, making physics review the first step in the workflow that could detect the error. Two specific physics checks were particularly effective (combined effectiveness of >20%): verifying DRRs (8/73) and verifying isocenter (7/73). Software-based plan checking systems were evaluated and found to have potential effectiveness of 40%. Given current data structures, software implementations of some tests such as isocenter verification check would be challenging. Conclusion: Physics plan review is a key safety measure and can detect majority of reported events. However, a majority of events that potentially could have been detected were NOT detected in this study, indicating the need to improve the performance of physics

Permanence analysis of a concatenated coding scheme for error control

NASA Technical Reports Server (NTRS)

Costello, D. J., Jr.; Lin, S.; Kasami, T.

1983-01-01

A concatenated coding scheme for error control in data communications is analyzed. In this scheme, the inner code is used for both error correction and detection, however, the outer code is used only for error detection. A retransmission is requested if the outer code detects the presence of errors after the inner code decoding. Probability of undetected error is derived and bounded. A particular example, proposed for the planetary program, is analyzed.

An Investigation into Soft Error Detection Efficiency at Operating System Level

PubMed Central

Taheri, Hassan

2014-01-01

Electronic equipment operating in harsh environments such as space is subjected to a range of threats. The most important of these is radiation that gives rise to permanent and transient errors on microelectronic components. The occurrence rate of transient errors is significantly more than permanent errors. The transient errors, or soft errors, emerge in two formats: control flow errors (CFEs) and data errors. Valuable research results have already appeared in literature at hardware and software levels for their alleviation. However, there is the basic assumption behind these works that the operating system is reliable and the focus is on other system levels. In this paper, we investigate the effects of soft errors on the operating system components and compare their vulnerability with that of application level components. Results show that soft errors in operating system components affect both operating system and application level components. Therefore, by providing endurance to operating system level components against soft errors, both operating system and application level components gain tolerance. PMID:24574894

An investigation into soft error detection efficiency at operating system level.

PubMed

Asghari, Seyyed Amir; Kaynak, Okyay; Taheri, Hassan

2014-01-01

Electronic equipment operating in harsh environments such as space is subjected to a range of threats. The most important of these is radiation that gives rise to permanent and transient errors on microelectronic components. The occurrence rate of transient errors is significantly more than permanent errors. The transient errors, or soft errors, emerge in two formats: control flow errors (CFEs) and data errors. Valuable research results have already appeared in literature at hardware and software levels for their alleviation. However, there is the basic assumption behind these works that the operating system is reliable and the focus is on other system levels. In this paper, we investigate the effects of soft errors on the operating system components and compare their vulnerability with that of application level components. Results show that soft errors in operating system components affect both operating system and application level components. Therefore, by providing endurance to operating system level components against soft errors, both operating system and application level components gain tolerance.

Office-based spirometry for early detection of obstructive lung disease.

PubMed

Wallace, Laura D; Troy, Kenneth E

2006-09-01

To review the research-based evidence supporting smoking cessation as the only proven method to reduce chronic obstructive pulmonary disease (COPD) progression and to show that early detection of disease with office-based spirometry can lead to therapeutic intervention before physiologic symptoms arise. Extensive review of national and international scientific literature supplemented with drawings and algorithms. Early detection of COPD with spirometry, along with smoking cessation, and aggressive intervention can alter the insidious course of this highly preventable disease. It is imperative that nurse practitioners utilize this simple and inexpensive procedure to identify COPD in its earliest stages, so treatment can reduce individual and community disease burden, reduce morbidity and mortality, and help reduce healthcare costs. Determination of early airflow obstruction supports smoking cessation education, provides objective data for patient motivation, thereby doubling patient compliance and reducing further disease burden.

SU-D-BRD-07: Evaluation of the Effectiveness of Statistical Process Control Methods to Detect Systematic Errors For Routine Electron Energy Verification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parker, S

2015-06-15

Purpose: To evaluate the ability of statistical process control methods to detect systematic errors when using a two dimensional (2D) detector array for routine electron beam energy verification. Methods: Electron beam energy constancy was measured using an aluminum wedge and a 2D diode array on four linear accelerators. Process control limits were established. Measurements were recorded in control charts and compared with both calculated process control limits and TG-142 recommended specification limits. The data was tested for normality, process capability and process acceptability. Additional measurements were recorded while systematic errors were intentionally introduced. Systematic errors included shifts in the alignmentmore » of the wedge, incorrect orientation of the wedge, and incorrect array calibration. Results: Control limits calculated for each beam were smaller than the recommended specification limits. Process capability and process acceptability ratios were greater than one in all cases. All data was normally distributed. Shifts in the alignment of the wedge were most apparent for low energies. The smallest shift (0.5 mm) was detectable using process control limits in some cases, while the largest shift (2 mm) was detectable using specification limits in only one case. The wedge orientation tested did not affect the measurements as this did not affect the thickness of aluminum over the detectors of interest. Array calibration dependence varied with energy and selected array calibration. 6 MeV was the least sensitive to array calibration selection while 16 MeV was the most sensitive. Conclusion: Statistical process control methods demonstrated that the data distribution was normally distributed, the process was capable of meeting specifications, and that the process was centered within the specification limits. Though not all systematic errors were distinguishable from random errors, process control limits increased the ability to detect systematic

Heuristic errors in clinical reasoning.

PubMed

Rylander, Melanie; Guerrasio, Jeannette

2016-08-01

Errors in clinical reasoning contribute to patient morbidity and mortality. The purpose of this study was to determine the types of heuristic errors made by third-year medical students and first-year residents. This study surveyed approximately 150 clinical educators inquiring about the types of heuristic errors they observed in third-year medical students and first-year residents. Anchoring and premature closure were the two most common errors observed amongst third-year medical students and first-year residents. There was no difference in the types of errors observed in the two groups. Errors in clinical reasoning contribute to patient morbidity and mortality Clinical educators perceived that both third-year medical students and first-year residents committed similar heuristic errors, implying that additional medical knowledge and clinical experience do not affect the types of heuristic errors made. Further work is needed to help identify methods that can be used to reduce heuristic errors early in a clinician's education. © 2015 John Wiley & Sons Ltd.

Investigations of remote sensing techniques for early detection of Dutch elm disease

NASA Technical Reports Server (NTRS)

Hammerschlag, R. S.; Sopstyle, W. J.

1975-01-01

Several forms of aerial photography were pursued in quest of a technique which could provide early detection of Dutch elm disease. The two most promising techniques tested were multispectral photography with object enhancement and biband ratioing coupled with scanning microdensitometry. For practical purposes the multispectral system has the advantage of providing a readily interpretable image in a relatively short time. Laboratory studies indicated that less emphasis should be placed on the use of a red filter or the near infrared beyond 750 mm for early detection of stress within a single plant species. Color infrared film would be optimal when used for a long term detection of loss of plant vigor which results in a physical change in a plant canopy, but should find minimal practicality for early detection of specific sources of plant stress such as Dutch elm disease. Considerable discretion should be used when interpreting imagery on copy film because of loss of resolution and color definition.

SU-G-BRB-11: On the Sensitivity of An EPID-Based 3D Dose Verification System to Detect Delivery Errors in VMAT Treatments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gonzalez, P; Olaciregui-Ruiz, I; Mijnheer, B

2016-06-15

Purpose: To investigate the sensitivity of an EPID-based 3D dose verification system to detect delivery errors in VMAT treatments. Methods: For this study 41 EPID-reconstructed 3D in vivo dose distributions of 15 different VMAT plans (H&N, lung, prostate and rectum) were selected. To simulate the effect of delivery errors, their TPS plans were modified by: 1) scaling of the monitor units by ±3% and ±6% and 2) systematic shifting of leaf bank positions by ±1mm, ±2mm and ±5mm. The 3D in vivo dose distributions where then compared to the unmodified and modified treatment plans. To determine the detectability of themore » various delivery errors, we made use of a receiver operator characteristic (ROC) methodology. True positive and false positive rates were calculated as a function of the γ-parameters γmean, γ1% (near-maximum γ) and the PTV dose parameter ΔD{sub 50} (i.e. D{sub 50}(EPID)-D{sub 50}(TPS)). The ROC curve is constructed by plotting the true positive rate vs. the false positive rate. The area under the ROC curve (AUC) then serves as a measure of the performance of the EPID dosimetry system in detecting a particular error; an ideal system has AUC=1. Results: The AUC ranges for the machine output errors and systematic leaf position errors were [0.64 – 0.93] and [0.48 – 0.92] respectively using γmean, [0.57 – 0.79] and [0.46 – 0.85] using γ1% and [0.61 – 0.77] and [ 0.48 – 0.62] using ΔD{sub 50}. Conclusion: For the verification of VMAT deliveries, the parameter γmean is the best discriminator for the detection of systematic leaf position errors and monitor unit scaling errors. Compared to γmean and γ1%, the parameter ΔD{sub 50} performs worse as a discriminator in all cases.« less

Error Detection in Mechanized Classification Systems

ERIC Educational Resources Information Center

Hoyle, W. G.

1976-01-01

When documentary material is indexed by a mechanized classification system, and the results judged by trained professionals, the number of documents in disagreement, after suitable adjustment, defines the error rate of the system. In a test case disagreement was 22 percent and, of this 22 percent, the computer correctly identified two-thirds of…

Error image aware content restoration

NASA Astrophysics Data System (ADS)

Choi, Sungwoo; Lee, Moonsik; Jung, Byunghee

2015-12-01

As the resolution of TV significantly increased, content consumers have become increasingly sensitive to the subtlest defect in TV contents. This rising standard in quality demanded by consumers has posed a new challenge in today's context where the tape-based process has transitioned to the file-based process: the transition necessitated digitalizing old archives, a process which inevitably produces errors such as disordered pixel blocks, scattered white noise, or totally missing pixels. Unsurprisingly, detecting and fixing such errors require a substantial amount of time and human labor to meet the standard demanded by today's consumers. In this paper, we introduce a novel, automated error restoration algorithm which can be applied to different types of classic errors by utilizing adjacent images while preserving the undamaged parts of an error image as much as possible. We tested our method to error images detected from our quality check system in KBS(Korean Broadcasting System) video archive. We are also implementing the algorithm as a plugin of well-known NLE(Non-linear editing system), which is a familiar tool for quality control agent.

New technology for early detection of health threats

NASA Astrophysics Data System (ADS)

Southern, Šárka O.; Lilienthal, Gerald W.

2008-04-01

Governmental agencies charged with protecting the health of the population and agriculture have several main strategic objectives including the detection of harmful agents, the identification of vulnerable biological targets, the prediction of health outcomes and the development of countermeasures. New technologies are urgently needed in several critical areas of bio-chemical defense: economical and minimally invasive biosensors for field use in humans and other species important for agriculture and infrastructure, universal analytical platforms for broad-based, early warnings of threats and technologies guiding the development of countermeasures. A new technology called Stress Response Profiling (SRP) was recently developed by the Gaia Medical Institute. SRP provides a universal analytical platform for monitoring health status based on measurements of physiological stress. The platform is implemented through handheld devices that can be used for noninvasive detection of early-stage health problems. This paper summarizes SRP features, advantages and potential benefits for critical areas of homeland defense.

Point/Counterpoint: early detection of prostate cancer: do the benefits outweigh the consequences?

PubMed

Carroll, Peter R; Vickers, Andrew J

2014-05-01

Few clinical issues have polarized the oncology community as much as screening for prostate cancer, with advocates of prostate-specific antigen (PSA) testing vocal on one side and skeptics just as vocal on the other. At the NCCN 19th Annual Conference, Dr. Peter R. Carroll and Dr. Andrew J. Vickers tackled the controversy surrounding early detection of prostate cancer, focusing attention on the randomized trial results at the heart of the matter; over-detection (the Achilles' heel of screening); and the rationale behind the new, streamlined 2014 NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Prostate Cancer Early Detection, which emphasize selective early detection and treatment and are tightly aligned with the NCCN Guidelines for Prostate Cancer. Copyright © 2014 by the National Comprehensive Cancer Network.

Biomarkers for early detection of Alzheimer disease.

PubMed

Barber, Robert C

2010-09-01

The existence of an effective biomarker for early detection of Alzheimer disease would facilitate improved diagnosis and stimulate therapeutic trials. Multidisciplinary clinical diagnosis of Alzheimer disease is time consuming and expensive and relies on experts who are rarely available outside of specialty clinics. Thus, many patients do not receive proper diagnosis until the disease has progressed beyond stages in which treatments are maximally effective. In the clinical trial setting, rapid, cost-effective screening of patients for Alzheimer disease is of paramount importance for the development of new treatments. Neuroimaging of cortical amyloid burden and volumetric changes in the brain and assessment of protein concentrations (eg, β-amyloid 1-42, total tau, phosphorylated tau) in cerebrospinal fluid are diagnostic tools that are not widely available. Known genetic markers do not provide sufficient discriminatory power between different forms of dementia to be useful in isolation. Recent studies using panels of biomarkers for diagnosis of Alzheimer disease or mild cognitive impairment have been promising, though no such studies have been cross-validated in independent samples of subjects. The ideal biomarker enabling early detection of Alzheimer disease has not yet been identified.

Diagnostic Error in Stroke-Reasons and Proposed Solutions.

PubMed

Bakradze, Ekaterina; Liberman, Ava L

2018-02-13

We discuss the frequency of stroke misdiagnosis and identify subgroups of stroke at high risk for specific diagnostic errors. In addition, we review common reasons for misdiagnosis and propose solutions to decrease error. According to a recent report by the National Academy of Medicine, most people in the USA are likely to experience a diagnostic error during their lifetimes. Nearly half of such errors result in serious disability and death. Stroke misdiagnosis is a major health care concern, with initial misdiagnosis estimated to occur in 9% of all stroke patients in the emergency setting. Under- or missed diagnosis (false negative) of stroke can result in adverse patient outcomes due to the preclusion of acute treatments and failure to initiate secondary prevention strategies. On the other hand, the overdiagnosis of stroke can result in inappropriate treatment, delayed identification of actual underlying disease, and increased health care costs. Young patients, women, minorities, and patients presenting with non-specific, transient, or posterior circulation stroke symptoms are at increased risk of misdiagnosis. Strategies to decrease diagnostic error in stroke have largely focused on early stroke detection via bedside examination strategies and a clinical decision rules. Targeted interventions to improve the diagnostic accuracy of stroke diagnosis among high-risk groups as well as symptom-specific clinical decision supports are needed. There are a number of open questions in the study of stroke misdiagnosis. To improve patient outcomes, existing strategies to improve stroke diagnostic accuracy should be more broadly adopted and novel interventions devised and tested to reduce diagnostic errors.

Sentinel lymph node detection in patients with early cervical cancer.

PubMed

Acharya, B C; Jihong, L

2009-01-01

Lymph node status is the most important independent prognostic factor in early stage cervical cancer. Intraoperative lymphatic mapping and sentinel lymph node detection have been increasingly evaluated in the treatment of a variety of solid tumors, particularly breast cancer and cutaneous melanoma. This study evaluated the feasibility of these procedures in patients undergoing radical hysterectomy with pelvic lymphadenectomy for early cervical cancer. A total of 30 patients with histologically diagnosed FIGO stage IA to IIA cervical cancer were enrolled to this study. They were scheduled to undergo radical abdominal hysterectomy and pelvic lymphadenectomy after injecting patent blue dye in cervix. A total of 60 SLNs (mean 2.5) were detected in 24 patients with detection rate of 80%. Bilateral SLNs were detected in 70.1% of cases. SLNs were identified in obturator and external iliac areas in 50% and 31.7%, respectively; no SLNs were discovered in the common iliac region. Seven patients (23.3%) had lymph node metastases; one of these had false negative SLN.The false negative rate and negative predictive value were 14.3% and 94.4%, respectively. SLN detection procedure with blue dye technique is a feasible procedure in cervical cancer. Patent blue dye is cheap, safe and effective tracer to detect sentinel node in carcinoma of cervix.

Phenotyping for patient safety: algorithm development for electronic health record based automated adverse event and medical error detection in neonatal intensive care.

PubMed

Li, Qi; Melton, Kristin; Lingren, Todd; Kirkendall, Eric S; Hall, Eric; Zhai, Haijun; Ni, Yizhao; Kaiser, Megan; Stoutenborough, Laura; Solti, Imre

2014-01-01

Although electronic health records (EHRs) have the potential to provide a foundation for quality and safety algorithms, few studies have measured their impact on automated adverse event (AE) and medical error (ME) detection within the neonatal intensive care unit (NICU) environment. This paper presents two phenotyping AE and ME detection algorithms (ie, IV infiltrations, narcotic medication oversedation and dosing errors) and describes manual annotation of airway management and medication/fluid AEs from NICU EHRs. From 753 NICU patient EHRs from 2011, we developed two automatic AE/ME detection algorithms, and manually annotated 11 classes of AEs in 3263 clinical notes. Performance of the automatic AE/ME detection algorithms was compared to trigger tool and voluntary incident reporting results. AEs in clinical notes were double annotated and consensus achieved under neonatologist supervision. Sensitivity, positive predictive value (PPV), and specificity are reported. Twelve severe IV infiltrates were detected. The algorithm identified one more infiltrate than the trigger tool and eight more than incident reporting. One narcotic oversedation was detected demonstrating 100% agreement with the trigger tool. Additionally, 17 narcotic medication MEs were detected, an increase of 16 cases over voluntary incident reporting. Automated AE/ME detection algorithms provide higher sensitivity and PPV than currently used trigger tools or voluntary incident-reporting systems, including identification of potential dosing and frequency errors that current methods are unequipped to detect. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Adaptive algorithm of selecting optimal variant of errors detection system for digital means of automation facility of oil and gas complex

NASA Astrophysics Data System (ADS)

Poluyan, A. Y.; Fugarov, D. D.; Purchina, O. A.; Nesterchuk, V. V.; Smirnova, O. V.; Petrenkova, S. B.

2018-05-01

To date, the problems associated with the detection of errors in digital equipment (DE) systems for the automation of explosive objects of the oil and gas complex are extremely actual. Especially this problem is actual for facilities where a violation of the accuracy of the DE will inevitably lead to man-made disasters and essential material damage, at such facilities, the diagnostics of the accuracy of the DE operation is one of the main elements of the industrial safety management system. In the work, the solution of the problem of selecting the optimal variant of the errors detection system of errors detection by a validation criterion. Known methods for solving these problems have an exponential valuation of labor intensity. Thus, with a view to reduce time for solving the problem, a validation criterion is compiled as an adaptive bionic algorithm. Bionic algorithms (BA) have proven effective in solving optimization problems. The advantages of bionic search include adaptability, learning ability, parallelism, the ability to build hybrid systems based on combining. [1].

Potential utility of environmental DNA for early detection of Eurasian watermilfoil (Myriophyllum spicatum)

USGS Publications Warehouse

Newton, Jeremy; Sepulveda, Adam; Sylvester, K; Thum, Ryan

2016-01-01

Considering the harmful and irreversible consequences of many biological invasions, early detection of an invasive species is an important step toward protecting ecosystems (Sepulveda et al. 2012). Early detection increases the probability that suppression or eradication efforts will be successful because invasive populations are small and localized (Vander Zanden et al. 2010). However, most invasive species are not detected early because current tools have low detection probabilities when target species are rare and the sampling effort required to achieve acceptable detection capabilities with current tools is seldom tractable (Jerde et al. 2011). As a result, many invasive species go undetected until they are abundant and suppression efforts become costly. Novel DNA-based surveillance tools have recently revolutionized early detection abilities using environmental DNA (eDNA) present in the water (Darling and Mahon 2011, Bohmann et al. 2014). In brief, eDNA monitoring enables the identification of organisms from DNA present and collected in water samples. Aquatic and semiaquatic organisms release DNA contained in sloughed, damaged, or partially decomposed tissue and waste products into the water and molecular techniques allow this eDNA in the water column to be identified from simple and easy-tocollect water samples (Darling and Mahon 2011). Despite limited understanding of the production, persistence, and spread of DNA in water (Barnes et al. 2014), eDNA monitoring has been applied not only to invasive species (Jerde et al. 2011), but also to species that are rare, endangered, or highly elusive (Spear et al. 2014). However, most eDNA research and monitoring has focused on detection of invertebrates and vertebrates and less attentionhas been given to developing eDNA techniques for detecting aquatic invasive plants. Eurasian watermilfoil (EWM; Myriophyllum spicatum L.) is an invasive species for which improved early detection would be particularly helpful. Advanced

Early detection of health and welfare compromises through automated detection of behavioural changes in pigs.

PubMed

Matthews, Stephen G; Miller, Amy L; Clapp, James; Plötz, Thomas; Kyriazakis, Ilias

2016-11-01

Early detection of health and welfare compromises in commercial piggeries is essential for timely intervention to enhance treatment success, reduce impact on welfare, and promote sustainable pig production. Behavioural changes that precede or accompany subclinical and clinical signs may have diagnostic value. Often referred to as sickness behaviour, this encompasses changes in feeding, drinking, and elimination behaviours, social behaviours, and locomotion and posture. Such subtle changes in behaviour are not easy to quantify and require lengthy observation input by staff, which is impractical on a commercial scale. Automated early-warning systems may provide an alternative by objectively measuring behaviour with sensors to automatically monitor and detect behavioural changes. This paper aims to: (1) review the quantifiable changes in behaviours with potential diagnostic value; (2) subsequently identify available sensors for measuring behaviours; and (3) describe the progress towards automating monitoring and detection, which may allow such behavioural changes to be captured, measured, and interpreted and thus lead to automation in commercial, housed piggeries. Multiple sensor modalities are available for automatic measurement and monitoring of behaviour, which require humans to actively identify behavioural changes. This has been demonstrated for the detection of small deviations in diurnal drinking, deviations in feeding behaviour, monitoring coughs and vocalisation, and monitoring thermal comfort, but not social behaviour. However, current progress is in the early stages of developing fully automated detection systems that do not require humans to identify behavioural changes; e.g., through automated alerts sent to mobile phones. Challenges for achieving automation are multifaceted and trade-offs are considered between health, welfare, and costs, between analysis of individuals and groups, and between generic and compromise-specific behaviours. Copyright © 2016

The Effect of Piano Playing on Preservice Teachers' Ability to Detect Errors in a Choral Score

ERIC Educational Resources Information Center

Napoles, Jessica; Babb, Sandra L.; Bowers, Judy; Hankle, Steven; Zrust, Adam

2017-01-01

The purpose of this study was to examine and empirically test the pedagogical claim that playing the piano while listening to choral singers impedes error detection ability. In a within-subjects design, participants (N = 55 preservice teachers) either listened to four excerpts of choral hymns or played a single part (soprano/bass) on the piano…

Updating of Aversive Memories after Temporal Error Detection Is Differentially Modulated by mTOR across Development

ERIC Educational Resources Information Center

Tallot, Lucille; Diaz-Mataix, Lorenzo; Perry, Rosemarie E.; Wood, Kira; LeDoux, Joseph E.; Mouly, Anne-Marie; Sullivan, Regina M.; Doyère, Valérie

2017-01-01

The updating of a memory is triggered whenever it is reactivated and a mismatch from what is expected (i.e., prediction error) is detected, a process that can be unraveled through the memory's sensitivity to protein synthesis inhibitors (i.e., reconsolidation). As noted in previous studies, in Pavlovian threat/aversive conditioning in adult rats,…

How can clinicians detect and treat autism early? Methodological trends of technology use in research

PubMed Central

Bölte, S; Bartl-Pokorny, KD; Jonsson, U; Berggren, S; Zhang, D; Kostrzewa, E; Falck-Ytter, T; Einspieler, C; Pokorny, FB; Jones, EJH; Roeyers, H; Charman, T; Marschik, PB

2018-01-01

We reviewed original research papers that used quantifiable technology to detect early autism spectrum disorder (ASD) and identified 376 studies from 34 countries from 1965-2013. Publications have increased significantly since 2000, with most coming from the USA. Electroencephalogram, magnetic resonance imaging and eye-tracking were the most frequently used technologies. Conclusion The use of quantifiable technology to detect early ASD has increased in recent decades, but has had limited impact on early detection and treatment. Further scientific developments are anticipated and we hope that they will increasingly be used in clinical practice for early ASD screening, diagnosis and intervention. PMID:26479859

Early Detection of Progressive Adolescent Idiopathic Scoliosis: A Severity Index.

PubMed

Skalli, Wafa; Vergari, Claudio; Ebermeyer, Eric; Courtois, Isabelle; Drevelle, Xavier; Kohler, Remi; Abelin-Genevois, Kariman; Dubousset, Jean

2017-06-01

Early detection of progressive adolescent idiopathic scoliosis (AIS) was assessed based on 3D quantification of the deformity. Based on 3D quantitative description of scoliosis curves, the aim is to assess a specific phenotype that could be an early detectable severity index for progressive AIS. Early detection of progressive scoliosis is important for adapted treatment to limit progression. However, progression risk assessment is mainly based on the follow up, waiting for signs of rapid progression that generally occur during the growth peak. Sixty-five mild scoliosis (16 boys, 49 girls, Cobb Angle between 10 and 20°) with a Risser between 0 and 2 were followed from their first examination until a decision was made by the clinician, either considering the spine as stable at the end of growth (26 patients) or planning to brace because of progression (39 patients). Calibrated biplanar x-rays were performed and 3D reconstructions of the spine allowed calculating six local parameters related to main curve deformity. For progressive curve 3D phenotype assessment, data were compared with those previously assessed for 30 severe scoliosis (Cobb Angle > 35°), 17 scoliosis before brace (Cobb Angle > 29°) and 53 spines of nonscoliosis subjects. A predictive discriminant analysis was performed to assess similarity of mild scoliosis curves either to those of scoliosis or nonscoliosis spines, yielding a severity index (S-index). S-index value at first examination was compared with clinical outcome. At the first exam, 53 out of 65 predictions (82%) were in agreement with actual clinical outcome. Approximately, 89% of the curves that were predicted as progressive proved accurate. Although still requiring large scale validation, results are promising for early detection of progressive curves. 2.

Error Estimation of Pathfinder Version 5.3 SST Level 3C Using Three-way Error Analysis

NASA Astrophysics Data System (ADS)

Saha, K.; Dash, P.; Zhao, X.; Zhang, H. M.

2017-12-01

One of the essential climate variables for monitoring as well as detecting and attributing climate change, is Sea Surface Temperature (SST). A long-term record of global SSTs are available with observations obtained from ships in the early days to the more modern observation based on in-situ as well as space-based sensors (satellite/aircraft). There are inaccuracies associated with satellite derived SSTs which can be attributed to the errors associated with spacecraft navigation, sensor calibrations, sensor noise, retrieval algorithms, and leakages due to residual clouds. Thus it is important to estimate accurate errors in satellite derived SST products to have desired results in its applications.Generally for validation purposes satellite derived SST products are compared against the in-situ SSTs which have inaccuracies due to spatio/temporal inhomogeneity between in-situ and satellite measurements. A standard deviation in their difference fields usually have contributions from both satellite as well as the in-situ measurements. A real validation of any geophysical variable must require the knowledge of the "true" value of the said variable. Therefore a one-to-one comparison of satellite based SST with in-situ data does not truly provide us the real error in the satellite SST and there will be ambiguity due to errors in the in-situ measurements and their collocation differences. A Triple collocation (TC) or three-way error analysis using 3 mutually independent error-prone measurements, can be used to estimate root-mean square error (RMSE) associated with each of the measurements with high level of accuracy without treating any one system a perfectly-observed "truth". In this study we are estimating the absolute random errors associated with Pathfinder Version 5.3 Level-3C SST product Climate Data record. Along with the in-situ SST data, the third source of dataset used for this analysis is the AATSR reprocessing of climate (ARC) dataset for the corresponding

Recursive SVM biomarker selection for early detection of breast cancer in peripheral blood.

PubMed

Zhang, Fan; Kaufman, Howard L; Deng, Youping; Drabier, Renee

2013-01-01

Breast cancer is worldwide the second most common type of cancer after lung cancer. Traditional mammography and Tissue Microarray has been studied for early cancer detection and cancer prediction. However, there is a need for more reliable diagnostic tools for early detection of breast cancer. This can be a challenge due to a number of factors and logistics. First, obtaining tissue biopsies can be difficult. Second, mammography may not detect small tumors, and is often unsatisfactory for younger women who typically have dense breast tissue. Lastly, breast cancer is not a single homogeneous disease but consists of multiple disease states, each arising from a distinct molecular mechanism and having a distinct clinical progression path which makes the disease difficult to detect and predict in early stages. In the paper, we present a Support Vector Machine based on Recursive Feature Elimination and Cross Validation (SVM-RFE-CV) algorithm for early detection of breast cancer in peripheral blood and show how to use SVM-RFE-CV to model the classification and prediction problem of early detection of breast cancer in peripheral blood.The training set which consists of 32 health and 33 cancer samples and the testing set consisting of 31 health and 34 cancer samples were randomly separated from a dataset of peripheral blood of breast cancer that is downloaded from Gene Express Omnibus. First, we identified the 42 differentially expressed biomarkers between "normal" and "cancer". Then, with the SVM-RFE-CV we extracted 15 biomarkers that yield zero cross validation score. Lastly, we compared the classification and prediction performance of SVM-RFE-CV with that of SVM and SVM Recursive Feature Elimination (SVM-RFE). We found that 1) the SVM-RFE-CV is suitable for analyzing noisy high-throughput microarray data, 2) it outperforms SVM-RFE in the robustness to noise and in the ability to recover informative features, and 3) it can improve the prediction performance (Area Under

Infrared light sensor applied to early detection of tooth decay

NASA Astrophysics Data System (ADS)

Benjumea, Eberto; Espitia, José; Díaz, Leonardo; Torres, Cesar

2017-08-01

The approach dentistry to dental care is gradually shifting to a model focused on early detection and oral-disease prevention; one of the most important methods of prevention of tooth decay is opportune diagnosis of decay and reconstruction. The present study aimed to introduce a procedure for early diagnosis of tooth decay and to compare result of experiment of this method with other common treatments. In this setup, a laser emitting infrared light is injected in core of one bifurcated fiber-optic and conduced to tooth surface and with the same bifurcated fiber the radiation reflected for the same tooth is collected and them conduced to surface of sensor that measures thermal and light frequencies to detect early signs of decay below a tooth surface, where demineralization is difficult to spot with x-ray technology. This device will can be used to diagnose tooth decay without any chemicals and rays such as high power lasers or X-rays.

Does Assessing Eye Alignment along with Refractive Error or Visual Acuity Increase Sensitivity for Detection of Strabismus in Preschool Vision Screening?

PubMed Central

2007-01-01

Purpose Preschool vision screenings often include refractive error or visual acuity (VA) testing to detect amblyopia, as well as alignment testing to detect strabismus. The purpose of this study was to determine the effect of combining screening for eye alignment with screening for refractive error or reduced VA on sensitivity for detection of strabismus, with specificity set at 90% and 94%. Methods Over 3 years, 4040 preschool children were screened in the Vision in Preschoolers (VIP) Study, with different screening tests administered each year. Examinations were performed to identify children with strabismus. The best screening tests for detecting children with any targeted condition were noncycloplegic retinoscopy (NCR), Retinomax autorefractor (Right Manufacturing, Virginia Beach, VA), SureSight Vision Screener (Welch-Allyn, Inc., Skaneateles, NY), and Lea Symbols (Precision Vision, LaSalle, IL and Good-Lite Co., Elgin, IL) and HOTV optotypes VA tests. Analyses were conducted with these tests of refractive error or VA paired with the best tests for detecting strabismus (unilateral cover testing, Random Dot “E” [RDE] and Stereo Smile Test II [Stereo Optical, Inc., Chicago, IL]; and MTI PhotoScreener [PhotoScreener, Inc., Palm Beach, FL]). The change in sensitivity that resulted from combining a test of eye alignment with a test of refractive error or VA was determined with specificity set at 90% and 94%. Results Among the 4040 children, 157 were identified as having strabismus. For screening tests conducted by eye care professionals, the addition of a unilateral cover test to a test of refraction generally resulted in a statistically significant increase (range, 15%–25%) in detection of strabismus. For screening tests administered by trained lay screeners, the addition of Stereo Smile II to SureSight resulted in a statistically significant increase (21%) in sensitivity for detection of strabismus. Conclusions The most efficient and low-cost ways to achieve

UWB based low-cost and non-invasive practical breast cancer early detection

NASA Astrophysics Data System (ADS)

Vijayasarveswari, V.; Khatun, S.; Fakir, M. M.; Jusoh, M.; Ali, S.

2017-03-01

Breast cancer is one of the main causes of women death worldwide. Breast tumor is an early stage of cancer that locates in cells of a human breast. As there is no remedy, early detection is crucial. Towards this, Ultra-Wideband (UWB) is a prominent candidate. It is a wireless communication technology which can achieve high bandwidth with low power utilization. UWB is suitable to be used for short range communication systems including breast cancer detection since it is secure, non-invasive and human health friendly. This paper presents the low-cost and non-invasive early breast cancer detection strategy using UWB sensor (or antenna). Emphasis is given here to detect breast tumor in 2D and 3D environments. The developed system consisted of hardware and software. Hardware included UWB transceiver and a pair of home-made directional sensor/antenna. The software included feed-forward back propagation Neural Network (NN) module to detect the tumor existence, size and location along with soft interface between software and hardware. Forward scattering technique was used by placing two sensors diagonally opposite sides of a breast phantom. UWB pulses were transmitted from one side of phantom and received from other side, controlled by the software interface in PC environment. Collected received signals were then fed into the NN module for training, testing and validation. The system exhibited detection efficiency on tumor existence, location (x, y, z), and size were approximately 100%, (78.17%, 70.66%, 92.46%), 85.86% respectively. The proposed UWB based early breast cancer detection system could be more practical with low-cost, user friendly and non-harmful features. This project may help users to monitor their breast health regularly at their home.

[Diagnostic performance of surface electrocardiogram in early detection of chagasic cardiomyopathy].

PubMed

Bochard-Villanueva, Bruno; Estornell-Erill, Jordi; Fabregat-Andrés, Óscar; García-González, Pilar; Morell-Cabedo, Salvador; Ridocci-Soriano, Francisco

2015-03-15

Contrast-enhanced cardiac magnetic resonance imaging (CMR) allows early detection of myocardial involvement by Trypanosoma cruzi infection. The aim of our study was to assess the diagnostic performance of the surface electrocardiogram (ECG) in the early detection of Chagas' cardiomyopathy (CCM) compared with CMR. We included 43 asymptomatic patients (30 women, 42 ± 9.8 years), diagnosed of Chagas disease. The sample was divided into 2 groups according to the presence (n=17) or absence (n=26) of electrocardiographic abnormalities. All patients underwent CMR and late gadolinium enhancement (LGE) was used as a marker of early myocardial involvement. Six (14%) patients had a LGE significantly higher in the group who had electrocardiographic abnormalities (29 vs. 4%, P<.05). With CMR as the method of reference, the ECG had a sensitivity of 83% and a negative predictive value of 96% to detect CCM. ECG is a useful, inexpensive and globally available tool for the screening of CCM in asymptomatic patients but with proven myocardial involvement in CMR. Copyright © 2013 Elsevier España, S.L.U. All rights reserved.

Probability of undetected error after decoding for a concatenated coding scheme

NASA Technical Reports Server (NTRS)

Costello, D. J., Jr.; Lin, S.

1984-01-01

A concatenated coding scheme for error control in data communications is analyzed. In this scheme, the inner code is used for both error correction and detection, however the outer code is used only for error detection. A retransmission is requested if the outer code detects the presence of errors after the inner code decoding. Probability of undetected error is derived and bounded. A particular example, proposed for NASA telecommand system is analyzed.

Error Budgeting and Tolerancing of Starshades for Exoplanet Detection

NASA Technical Reports Server (NTRS)

Shaklan, Stuart B.; Noecker, M. Charley; Glassman, Tiffany; Lo, Amy S.; Dumont, Philip J.; Kasdin, N. Jeremy; Cady, Eric J.; Vanderbei, Robert; Lawson, Peter R.

2010-01-01

A flower-like starshade positioned between a star and a space telescope is an attractive option for blocking the starlight to reveal the faint reflected light of an orbiting Earth-like planet. Planet light passes around the petals and directly enters the telescope where it is seen along with a background of scattered light due to starshade imperfections. We list the major perturbations that are expected to impact the performance of a starshade system and show that independent models at NGAS and JPL yield nearly identical optical sensitivities. We give the major sensitivities in the image plane for a design consisting of a 34-m diameter starshade, and a 2-m diameter telescope separated by 39,000 km, operating between 0.25 and 0.55 um. These sensitivities include individual petal and global shape terms evaluated at the inner working angle. Following a discussion of the combination of individual perturbation terms, we then present an error budget that is consistent with detection of an Earth-like planet 26 magnitudes fainter than its host star.

Passive quantum error correction of linear optics networks through error averaging

NASA Astrophysics Data System (ADS)

Marshman, Ryan J.; Lund, Austin P.; Rohde, Peter P.; Ralph, Timothy C.

2018-02-01

We propose and investigate a method of error detection and noise correction for bosonic linear networks using a method of unitary averaging. The proposed error averaging does not rely on ancillary photons or control and feedforward correction circuits, remaining entirely passive in its operation. We construct a general mathematical framework for this technique and then give a series of proof of principle examples including numerical analysis. Two methods for the construction of averaging are then compared to determine the most effective manner of implementation and probe the related error thresholds. Finally we discuss some of the potential uses of this scheme.

New double-byte error-correcting codes for memory systems

NASA Technical Reports Server (NTRS)

Feng, Gui-Liang; Wu, Xinen; Rao, T. R. N.

1996-01-01

Error-correcting or error-detecting codes have been used in the computer industry to increase reliability, reduce service costs, and maintain data integrity. The single-byte error-correcting and double-byte error-detecting (SbEC-DbED) codes have been successfully used in computer memory subsystems. There are many methods to construct double-byte error-correcting (DBEC) codes. In the present paper we construct a class of double-byte error-correcting codes, which are more efficient than those known to be optimum, and a decoding procedure for our codes is also considered.

Error detection capability of a novel transmission detector: a validation study for online VMAT monitoring.

PubMed

Pasler, Marlies; Michel, Kilian; Marrazzo, Livia; Obenland, Michael; Pallotta, Stefania; Björnsgard, Mari; Lutterbach, Johannes

2017-09-01

The purpose of this study was to characterize a new single large-area ionization chamber, the integral quality monitor system (iRT, Germany), for online and real-time beam monitoring. Signal stability, monitor unit (MU) linearity and dose rate dependence were investigated for static and arc deliveries and compared to independent ionization chamber measurements. The dose verification capability of the transmission detector system was evaluated by comparing calculated and measured detector signals for 15 volumetric modulated arc therapy plans. The error detection sensitivity was tested by introducing MLC position and linac output errors. Deviations in dose distributions between the original and error-induced plans were compared in terms of detector signal deviation, dose-volume histogram (DVH) metrics and 2D γ-evaluation (2%/2 mm and 3%/3 mm). The detector signal is linearly dependent on linac output and shows negligible (<0.4%) dose rate dependence up to 460 MU min -1 . Signal stability is within 1% for cumulative detector output; substantial variations were observed for the segment-by-segment signal. Calculated versus measured cumulative signal deviations ranged from  -0.16%-2.25%. DVH, mean 2D γ-value and detector signal evaluations showed increasing deviations with regard to the respective reference with growing MLC and dose output errors; good correlation between DVH metrics and detector signal deviation was found (e.g. PTV D mean : R 2   =  0.97). Positional MLC errors of 1 mm and errors in linac output of 2% were identified with the transmission detector system. The extensive tests performed in this investigation show that the new transmission detector provides a stable and sensitive cumulative signal output and is suitable for beam monitoring during patient treatment.

Error detection capability of a novel transmission detector: a validation study for online VMAT monitoring

NASA Astrophysics Data System (ADS)

Pasler, Marlies; Michel, Kilian; Marrazzo, Livia; Obenland, Michael; Pallotta, Stefania; Björnsgard, Mari; Lutterbach, Johannes

2017-09-01

The purpose of this study was to characterize a new single large-area ionization chamber, the integral quality monitor system (iRT, Germany), for online and real-time beam monitoring. Signal stability, monitor unit (MU) linearity and dose rate dependence were investigated for static and arc deliveries and compared to independent ionization chamber measurements. The dose verification capability of the transmission detector system was evaluated by comparing calculated and measured detector signals for 15 volumetric modulated arc therapy plans. The error detection sensitivity was tested by introducing MLC position and linac output errors. Deviations in dose distributions between the original and error-induced plans were compared in terms of detector signal deviation, dose-volume histogram (DVH) metrics and 2D γ-evaluation (2%/2 mm and 3%/3 mm). The detector signal is linearly dependent on linac output and shows negligible (<0.4%) dose rate dependence up to 460 MU min-1. Signal stability is within 1% for cumulative detector output; substantial variations were observed for the segment-by-segment signal. Calculated versus measured cumulative signal deviations ranged from  -0.16%-2.25%. DVH, mean 2D γ-value and detector signal evaluations showed increasing deviations with regard to the respective reference with growing MLC and dose output errors; good correlation between DVH metrics and detector signal deviation was found (e.g. PTV D mean: R 2  =  0.97). Positional MLC errors of 1 mm and errors in linac output of 2% were identified with the transmission detector system. The extensive tests performed in this investigation show that the new transmission detector provides a stable and sensitive cumulative signal output and is suitable for beam monitoring during patient treatment.

Designing and evaluating an automated system for real-time medication administration error detection in a neonatal intensive care unit.

PubMed

Ni, Yizhao; Lingren, Todd; Hall, Eric S; Leonard, Matthew; Melton, Kristin; Kirkendall, Eric S

2018-05-01

Timely identification of medication administration errors (MAEs) promises great benefits for mitigating medication errors and associated harm. Despite previous efforts utilizing computerized methods to monitor medication errors, sustaining effective and accurate detection of MAEs remains challenging. In this study, we developed a real-time MAE detection system and evaluated its performance prior to system integration into institutional workflows. Our prospective observational study included automated MAE detection of 10 high-risk medications and fluids for patients admitted to the neonatal intensive care unit at Cincinnati Children's Hospital Medical Center during a 4-month period. The automated system extracted real-time medication use information from the institutional electronic health records and identified MAEs using logic-based rules and natural language processing techniques. The MAE summary was delivered via a real-time messaging platform to promote reduction of patient exposure to potential harm. System performance was validated using a physician-generated gold standard of MAE events, and results were compared with those of current practice (incident reporting and trigger tools). Physicians identified 116 MAEs from 10 104 medication administrations during the study period. Compared to current practice, the sensitivity with automated MAE detection was improved significantly from 4.3% to 85.3% (P = .009), with a positive predictive value of 78.0%. Furthermore, the system showed potential to reduce patient exposure to harm, from 256 min to 35 min (P < .001). The automated system demonstrated improved capacity for identifying MAEs while guarding against alert fatigue. It also showed promise for reducing patient exposure to potential harm following MAE events.

[Early detection of breast and cervical cancer among indigenous communities in Morelos, Mexico].

PubMed

Campero, Lourdes; Atienzo, Erika E; Marín, Eréndira; de la Vara-Salazar, Elvia; Pelcastre-Villafuerte, Blanca; González, Guillermo

2014-01-01

To analyze the perception in relation to when and how to perform actions for the early detection of breast and cervical cancer among women and health care providers in communities with a high percentage of indigenous population in Morelos, Mexico. Ten health providers and 58 women users of health services were interviewed which have a first level of attention in five communities. The analysis was developed under the approach of the Grounded Theory. Providers are poorly informed about current regulations and specific clinical indications for the detection of cervical and breast cancer. Few practice health literacy under intercultural sensitization. The users have imprecise or wrong notions of the early detection. The need for training in adherence to norms is evident. It is urgent to assume a culturally relevant approach to enable efficient communication and promote health literacy for early detection of these two cancers.

Repeat-aware modeling and correction of short read errors.

PubMed

Yang, Xiao; Aluru, Srinivas; Dorman, Karin S

2011-02-15

High-throughput short read sequencing is revolutionizing genomics and systems biology research by enabling cost-effective deep coverage sequencing of genomes and transcriptomes. Error detection and correction are crucial to many short read sequencing applications including de novo genome sequencing, genome resequencing, and digital gene expression analysis. Short read error detection is typically carried out by counting the observed frequencies of kmers in reads and validating those with frequencies exceeding a threshold. In case of genomes with high repeat content, an erroneous kmer may be frequently observed if it has few nucleotide differences with valid kmers with multiple occurrences in the genome. Error detection and correction were mostly applied to genomes with low repeat content and this remains a challenging problem for genomes with high repeat content. We develop a statistical model and a computational method for error detection and correction in the presence of genomic repeats. We propose a method to infer genomic frequencies of kmers from their observed frequencies by analyzing the misread relationships among observed kmers. We also propose a method to estimate the threshold useful for validating kmers whose estimated genomic frequency exceeds the threshold. We demonstrate that superior error detection is achieved using these methods. Furthermore, we break away from the common assumption of uniformly distributed errors within a read, and provide a framework to model position-dependent error occurrence frequencies common to many short read platforms. Lastly, we achieve better error correction in genomes with high repeat content. The software is implemented in C++ and is freely available under GNU GPL3 license and Boost Software V1.0 license at "http://aluru-sun.ece.iastate.edu/doku.php?id = redeem". We introduce a statistical framework to model sequencing errors in next-generation reads, which led to promising results in detecting and correcting errors

Early detection monitoring for larval dreissenid mussels: How much plankton sampling is enough?

USGS Publications Warehouse

Counihan, Timothy D.; Bollens, Stephen M.

2017-01-01

The development of quagga and zebra mussel (dreissenids) monitoring programs in the Pacific Northwest provides a unique opportunity to evaluate a regional invasive species detection effort early in its development. Recent studies suggest that the ecological and economic costs of a dreissenid infestation in the Pacific Northwest of the USA would be significant. Consequently, efforts are underway to monitor for the presence of dreissenids. However, assessments of whether these efforts provide for early detection are lacking. We use information collected from 2012 to 2014 to characterize the development of larval dreissenid monitoring programs in the states of Idaho, Montana, Oregon, and Washington in the context of introduction and establishment risk. We also estimate the effort needed for high-probability detection of rare planktonic taxa in four Columbia and Snake River reservoirs and assess whether the current level of effort provides for early detection. We found that the effort expended to monitor for dreissenid mussels increased substantially from 2012 to 2014, that efforts were distributed across risk categories ranging from high to very low, and that substantial gaps in our knowledge of both introduction and establishment risk exist. The estimated volume of filtered water required to fully census planktonic taxa or to provide high-probability detection of rare taxa was high for the four reservoirs examined. We conclude that the current level of effort expended does not provide for high-probability detection of larval dreissenids or other planktonic taxa when they are rare in these reservoirs. We discuss options to improve early detection capabilities.

Experimental investigation of observation error in anuran call surveys

USGS Publications Warehouse

McClintock, B.T.; Bailey, L.L.; Pollock, K.H.; Simons, T.R.

2010-01-01

Occupancy models that account for imperfect detection are often used to monitor anuran and songbird species occurrence. However, presenceabsence data arising from auditory detections may be more prone to observation error (e.g., false-positive detections) than are sampling approaches utilizing physical captures or sightings of individuals. We conducted realistic, replicated field experiments using a remote broadcasting system to simulate simple anuran call surveys and to investigate potential factors affecting observation error in these studies. Distance, time, ambient noise, and observer abilities were the most important factors explaining false-negative detections. Distance and observer ability were the best overall predictors of false-positive errors, but ambient noise and competing species also affected error rates for some species. False-positive errors made up 5 of all positive detections, with individual observers exhibiting false-positive rates between 0.5 and 14. Previous research suggests false-positive errors of these magnitudes would induce substantial positive biases in standard estimators of species occurrence, and we recommend practices to mitigate for false positives when developing occupancy monitoring protocols that rely on auditory detections. These recommendations include additional observer training, limiting the number of target species, and establishing distance and ambient noise thresholds during surveys. ?? 2010 The Wildlife Society.

Hypoglycemia Early Alarm Systems Based on Recursive Autoregressive Partial Least Squares Models

PubMed Central

Bayrak, Elif Seyma; Turksoy, Kamuran; Cinar, Ali; Quinn, Lauretta; Littlejohn, Elizabeth; Rollins, Derrick

2013-01-01

Background Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas systems. Many of the proposed alarm systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early alarm systems of potential hypoglycemia. Methods A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia alarm systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia alarm algorithm using these models is proposed and evaluated. Results Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early alarm systems based on RARPLS shows good performance. A sensitivity of 86% and a false alarm rate of 0.42 false positive/day are obtained for the early alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. Conclusions The RARPLS models developed provide satisfactory glucose prediction with relatively smaller error than other proposed algorithms and are good candidates to forecast and warn about potential hypoglycemia unless preventive action is taken far in advance. PMID:23439179

Hypoglycemia early alarm systems based on recursive autoregressive partial least squares models.

PubMed

Bayrak, Elif Seyma; Turksoy, Kamuran; Cinar, Ali; Quinn, Lauretta; Littlejohn, Elizabeth; Rollins, Derrick

2013-01-01

Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas systems. Many of the proposed alarm systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early alarm systems of potential hypoglycemia. A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia alarm systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia alarm algorithm using these models is proposed and evaluated. Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early alarm systems based on RARPLS shows good performance. A sensitivity of 86% and a false alarm rate of 0.42 false positive/day are obtained for the early alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. The RARPLS models developed provide satisfactory glucose prediction with relatively smaller error than other proposed algorithms and are good candidates to forecast and warn about potential hypoglycemia unless preventive action is taken far in advance. © 2012 Diabetes Technology Society.

A concatenated coding scheme for error control

NASA Technical Reports Server (NTRS)

Lin, S.

1985-01-01

A concatenated coding scheme for error control in data communications is analyzed. The inner code is used for both error correction and detection, however the outer code is used only for error detection. A retransmission is requested if the outer code detects the presence of errors after the inner code decoding. The probability of undetected error of the above error control scheme is derived and upper bounded. Two specific exmaples are analyzed. In the first example, the inner code is a distance-4 shortened Hamming code with generator polynomial (X+1)(X(6)+X+1) = X(7)+X(6)+X(2)+1 and the outer code is a distance-4 shortened Hamming code with generator polynomial (X+1)X(15+X(14)+X(13)+X(12)+X(4)+X(3)+X(2)+X+1) = X(16)+X(12)+X(5)+1 which is the X.25 standard for packet-switched data network. This example is proposed for error control on NASA telecommand links. In the second example, the inner code is the same as that in the first example but the outer code is a shortened Reed-Solomon code with symbols from GF(2(8)) and generator polynomial (X+1)(X+alpha) where alpha is a primitive element in GF(z(8)).

A Context-Aware EEG Headset System for Early Detection of Driver Drowsiness.

PubMed

Li, Gang; Chung, Wan-Young

2015-08-21

Driver drowsiness is a major cause of mortality in traffic accidents worldwide. Electroencephalographic (EEG) signal, which reflects the brain activities, is more directly related to drowsiness. Thus, many Brain-Machine-Interface (BMI) systems have been proposed to detect driver drowsiness. However, detecting driver drowsiness at its early stage poses a major practical hurdle when using existing BMI systems. This study proposes a context-aware BMI system aimed to detect driver drowsiness at its early stage by enriching the EEG data with the intensity of head-movements. The proposed system is carefully designed for low-power consumption with on-chip feature extraction and low energy Bluetooth connection. Also, the proposed system is implemented using JAVA programming language as a mobile application for on-line analysis. In total, 266 datasets obtained from six subjects who participated in a one-hour monotonous driving simulation experiment were used to evaluate this system. According to a video-based reference, the proposed system obtained an overall detection accuracy of 82.71% for classifying alert and slightly drowsy events by using EEG data alone and 96.24% by using the hybrid data of head-movement and EEG. These results indicate that the combination of EEG data and head-movement contextual information constitutes a robust solution for the early detection of driver drowsiness.

Early Detection of Amyloid Plaque in Alzheimer’s Disease via X-ray Phase CT

DTIC Science & Technology

2016-08-01

AWARD NUMBER: W81XWH-12-1-0138 TITLE: Early Detection of Amyloid Plaque in Alzheimer’s Disease via X-ray Phase CT PRINCIPAL INVESTIGATOR...NUMBER W81XWH-12-1-0138 Early Detection of Amyloid Plaque in Alzheimer’s Disease via X-ray Phase CT 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...method for early detection of amyloid plaque in Alzheimer’s disease , with three Specific Aims: #1 Develop and optimize an x-ray PCCT to explore the

Model Development and Trial of Early Detection Manual for the Special Needs Children at Early Age Education Level

ERIC Educational Resources Information Center

Anwar, Zainul; Ingarianti, Tri Muji; Suryaningrum, Cahyaning

2016-01-01

This research was aimed to produce the manual for early detection for ABK at the level of early age education (PAUD = "Pendidikan Anak Usia Dini"). Research was "action research" with stages as proposed by Buunk and Van Vugt. Metodology of research these stages were called as PATH ("Problem-Analysis-Test…

Early detection of materials degradation

NASA Astrophysics Data System (ADS)

Meyendorf, Norbert

2017-02-01

Lightweight components for transportation and aerospace applications are designed for an estimated lifecycle, taking expected mechanical and environmental loads into account. The main reason for catastrophic failure of components within the expected lifecycle are material inhomogeneities, like pores and inclusions as origin for fatigue cracks, that have not been detected by NDE. However, material degradation by designed or unexpected loading conditions or environmental impacts can accelerate the crack initiation or growth. Conventional NDE methods are usually able to detect cracks that are formed at the end of the degradation process, but methods for early detection of fatigue, creep, and corrosion are still a matter of research. For conventional materials ultrasonic, electromagnetic, or thermographic methods have been demonstrated as promising. Other approaches are focused to surface damage by using optical methods or characterization of the residual surface stresses that can significantly affect the creation of fatigue cracks. For conventional metallic materials, material models for nucleation and propagation of damage have been successfully applied for several years. Material microstructure/property relations are well established and the effect of loading conditions on the component life can be simulated. For advanced materials, for example carbon matrix composites or ceramic matrix composites, the processes of nucleation and propagation of damage is still not fully understood. For these materials NDE methods can not only be used for the periodic inspections, but can significantly contribute to the material scientific knowledge to understand and model the behavior of composite materials.

Development of an assisting detection system for early infarct diagnosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sim, K. S.; Nia, M. E.; Ee, C. S.

2015-04-24

In this paper, a detection assisting system for early infarct detection is developed. This new developed method is used to assist the medical practitioners to diagnose infarct from computed tomography images of brain. Using this assisting system, the infarct could be diagnosed at earlier stages. The non-contrast computed tomography (NCCT) brain images are the data set used for this system. Detection module extracts the pixel data from NCCT brain images, and produces the colourized version of images. The proposed method showed great potential in detecting infarct, and helps medical practitioners to make earlier and better diagnoses.

Error Detection-Based Model to Assess Educational Outcomes in Crisis Resource Management Training: A Pilot Study.

PubMed

Bouhabel, Sarah; Kay-Rivest, Emily; Nhan, Carol; Bank, Ilana; Nugus, Peter; Fisher, Rachel; Nguyen, Lily Hp

2017-06-01

Otolaryngology-head and neck surgery (OTL-HNS) residents face a variety of difficult, high-stress situations, which may occur early in their training. Since these events occur infrequently, simulation-based learning has become an important part of residents' training and is already well established in fields such as anesthesia and emergency medicine. In the domain of OTL-HNS, it is gradually gaining in popularity. Crisis Resource Management (CRM), a program adapted from the aviation industry, aims to improve outcomes of crisis situations by attempting to mitigate human errors. Some examples of CRM principles include cultivating situational awareness; promoting proper use of available resources; and improving rapid decision making, particularly in high-acuity, low-frequency clinical situations. Our pilot project sought to integrate CRM principles into an airway simulation course for OTL-HNS residents, but most important, it evaluated whether learning objectives were met, through use of a novel error identification model.

Multi-disciplinary team for early gastric cancer diagnosis improves the detection rate of early gastric cancer.

PubMed

Di, Lianjun; Wu, Huichao; Zhu, Rong; Li, Youfeng; Wu, Xinglong; Xie, Rui; Li, Hongping; Wang, Haibo; Zhang, Hua; Xiao, Hong; Chen, Hui; Zhen, Hong; Zhao, Kui; Yang, Xuefeng; Xie, Ming; Tuo, Bigung

2017-12-06

Gastric cancer is a frequent malignant tumor worldwide and its early detection is crucial for curing the disease and enhancing patients' survival rate. This study aimed to assess whether the multi-disciplinary team (MDT) can improve the detection rate of early gastric cancer (EGC). The detection rate of EGC at the Digestive Endoscopy Center, Affiliated Hospital, Zunyi Medical College, China between September 2013 and September 2015 was analyzed. MDT for the diagnosis of EGC in the hospital was established in September 2014. The study was divided into 2 time periods: September 1, 2013 to August 31, 2014 (period 1) and September 1, 2014 to September 1, 2015 (period 2). A total of 60,800 patients' gastroscopies were performed during the two years. 61 of these patients (0.1%) were diagnosed as EGC, accounting for 16.44% (61/371) of total patients with gastric cancer. The EGC detection rate before MDT (period 1) was 0.05% (16/29403), accounting for 9.09% (16/176) of total patients with gastric cancer during this period. In comparison, the EGC detection rate during MDT (period 2) was 0.15% (45/31397), accounting for 23% (45/195) of total patients with gastric cancer during this period (P < 0.05). Univariate and multivariate logistic analyses showed that intensive gastroscopy for high risk patients of gastric cancer enhanced the detection rate of EGC in cooperation with Department of Pathology (OR = 10.1, 95% CI 2.39-43.3, P < 0.05). MDT could improve the endoscopic detection rate of EGC.

Nanostructured materials with plasmonic nanobiosensors for early cancer detection: A past and future prospect.

PubMed

Sugumaran, Sathish; Jamlos, Mohd Faizal; Ahmad, Mohd Noor; Bellan, Chandar Shekar; Schreurs, Dominique

2018-02-15

Early cancer detection and treatment is an emerging and fascinating field of plasmonic nanobiosensor research. It paves to enrich a life without affecting living cells leading to a possible survival of the patient. This review describes a past and future prospect of an integrated research field on nanostructured metamaterials, microwave transmission, surface plasmonic resonance, nanoantennas, and their manifested versatile properties with nano-biosensors towards early cancer detection to preserve human health. Interestingly, (i) microwave transmission shows more advantages than other electromagnetic radiation in reacting with biological tissues, (ii) nanostructured metamaterial (Au) with special properties like size and shape can stimulate plasmonic effects, (iii) plasmonic based nanobiosensors are to explore the efficacy for early cancer tumour detection or single molecular detection and (iv) nanoantenna wireless communication by using microwave inverse scattering nanomesh (MISN) technique instead of conventional techniques can be adopted to characterize the microwave scattered signals from the biomarkers. It reveals that the nanostructured material with plasmonic nanobiosensor paves a fascinating platform towards early detection of cancer tumour and is anticipated to be exploited as a magnificent field in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

Early Detection of Pancreatic Cancer: The Role of Industry in the Development of Biomarkers.

PubMed

Kenner, Barbara J; Go, Vay Liang W; Chari, Suresh T; Goldberg, Ann E; Rothschild, Laura J

A diagnosis of pancreatic cancer is devastating owing to its poor prognosis, with a 5-year survival rate of only 9%. Currently, most individuals are diagnosed at a late stage when treatment options are limited. Early detection of pancreatic cancer provides the greatest hope for making substantial improvements in survival. The Kenner Family Research Fund in partnership with the American Pancreatic Association has sponsored a series of fora to stimulate discussion and collaboration on early detection of pancreatic cancer. At the first forum in 2014, "Early Detection of Sporadic Pancreatic Cancer Summit Conference," a strategic plan was set forth by an international group of interdisciplinary scientific representatives and subsequently The Strategic Map for Innovation was generated. The current conference report is the third forum in the series, "Early Detection of Pancreatic Cancer: The Role of Industry in the Development of Biomarkers," which was held in Boston, Massachusetts, on October 27, 2016. This report provides an overview of examples of innovative initiatives by industry and confirms the critical need for collaboration among industry, government, research institutions, and advocacy groups in order to make pancreatic cancer more easily detectable in its earlier stages, when it is more treatable.

Detection and Proportion of Very Early Dental Caries in Independent Living Older Adults

PubMed Central

Holtzman, Jennifer S.; Kohanchi, Daniel; Biren-Fetz, John; Fontana, Margherita; Ramchandani, Manisha; Osann, Kathryn; Hallajian, Lucy; Mansour, Stephanie; Nabelsi, Tasneem; Chung, Na Eun; Wilder-Smith, Petra

2015-01-01

Background and Objectives Dental caries is an important healthcare challenge in adults over 65 years of age. Integration of oral health screening into non-dental primary care practice may improve access to preventive dental care for vulnerable populations such as the elderly. Such integration would require easy, fast, and accurate early caries detection tools. Primary goal of this study was to evaluate the diagnostic performance of optical coherence tomography (OCT) imaging for detecting very early caries in the elderly living in community-based settings. The International Caries Detection and Assessment System (ICDAS) served as gold standard. Secondary goal of this study was to provide baseline prevalence data of very early caries lesions in independent living adults aged 65+ years. Materials and Methods Seventy-two subjects were recruited from three sites in Southern California: a retirement community, a senior health fair, and a convalescent hospital. Clinical examination was performed using the ICDAS visual criteria and this was followed by OCT imaging. The two-dimensional OCT images (B-scan) were analyzed with simple software. Locations with a log of back-scattered light intensity (BSLI) below 2.9 were scored as sound, and areas equaling or exceeding 2.9 BSLI were considered carious. Diagnostic performance of OCT imaging was compared with ICDAS score. Results OCT-based diagnosis demonstrated very good sensitivity (95.1%) and good specificity (85.8%). 54.7% of dentate subjects had at least one tooth with very early coronal caries. Conclusions Early coronal decay is prevalent in the unrestored pits and fissures of coronal surfaces of teeth in independent living adults aged 65+ years. Though OCT imaging coupled with a simple diagnostic algorithm can accurately detect areas of very early caries in community-based settings, existing devices are expensive and not well-suited for use by non-dental health care providers. Simple, inexpensive, fast, and accurate tools

Automatic detection of patient identification and positioning errors in radiation therapy treatment using 3-dimensional setup images.

PubMed

Jani, Shyam S; Low, Daniel A; Lamb, James M

2015-01-01

To develop an automated system that detects patient identification and positioning errors between 3-dimensional computed tomography (CT) and kilovoltage CT planning images. Planning kilovoltage CT images were collected for head and neck (H&N), pelvis, and spine treatments with corresponding 3-dimensional cone beam CT and megavoltage CT setup images from TrueBeam and TomoTherapy units, respectively. Patient identification errors were simulated by registering setup and planning images from different patients. For positioning errors, setup and planning images were misaligned by 1 to 5 cm in the 6 anatomical directions for H&N and pelvis patients. Spinal misalignments were simulated by misaligning to adjacent vertebral bodies. Image pairs were assessed using commonly used image similarity metrics as well as custom-designed metrics. Linear discriminant analysis classification models were trained and tested on the imaging datasets, and misclassification error (MCE), sensitivity, and specificity parameters were estimated using 10-fold cross-validation. For patient identification, our workflow produced MCE estimates of 0.66%, 1.67%, and 0% for H&N, pelvis, and spine TomoTherapy images, respectively. Sensitivity and specificity ranged from 97.5% to 100%. MCEs of 3.5%, 2.3%, and 2.1% were obtained for TrueBeam images of the above sites, respectively, with sensitivity and specificity estimates between 95.4% and 97.7%. MCEs for 1-cm H&N/pelvis misalignments were 1.3%/5.1% and 9.1%/8.6% for TomoTherapy and TrueBeam images, respectively. Two-centimeter MCE estimates were 0.4%/1.6% and 3.1/3.2%, respectively. MCEs for vertebral body misalignments were 4.8% and 3.6% for TomoTherapy and TrueBeam images, respectively. Patient identification and gross misalignment errors can be robustly and automatically detected using 3-dimensional setup images of different energies across 3 commonly treated anatomical sites. Copyright © 2015 American Society for Radiation Oncology. Published by

Error Detection and Self-Assessment as Mechanisms to Promote Self-Regulation of Learning among Secondary Education Students

ERIC Educational Resources Information Center

Zamora, Ángela; Suárez, José Manuel; Ardura, Diego

2018-01-01

The authors' objective was to study the role of error detection and retroactive self-regulation as determinants of performance in secondary education students. A total of 198 students participated in the quasiexperimental study, which involved a control group and two experimental groups. This enabled the authors to analyze the effects of both…

Errors Detection by 5- to 8-Year-Olds Listening to a Wrong French Sequence of Number Words: Music before Lyrics?

ERIC Educational Resources Information Center

Gauderat-Bagault, Laurence; Lehalle, Henri

Children, ages 5 to 8 years (n=71), were required to listen and detect errors out of a partly wrong sequence of tape-recorded French number words from 1 to 100. Children (from several schools near Montpellier, France) were from preschool, grade 1, and grade 2. Results show that wrong syntactic rules were better detected than omissions, whereas…

Evidence for aversive withdrawal response to own errors.

PubMed

Hochman, Eldad Yitzhak; Milman, Valery; Tal, Liron

2017-10-01

Recent model suggests that error detection gives rise to defensive motivation prompting protective behavior. Models of active avoidance behavior predict it should grow larger with threat imminence and avoidance. We hypothesized that in a task requiring left or right key strikes, error detection would drive an avoidance reflex manifested by rapid withdrawal of an erring finger growing larger with threat imminence and avoidance. In experiment 1, three groups differing by error-related threat imminence and avoidance performed a flanker task requiring left or right force sensitive-key strikes. As predicted, errors were followed by rapid force release growing faster with threat imminence and opportunity to evade threat. In experiment 2, we established a link between error key release time (KRT) and the subjective sense of inner-threat. In a simultaneous, multiple regression analysis of three error-related compensatory mechanisms (error KRT, flanker effect, error correction RT), only error KRT was significantly associated with increased compulsive checking tendencies. We propose that error response withdrawal reflects an error-withdrawal reflex. Copyright © 2017 Elsevier B.V. All rights reserved.

Mapping DNA polymerase errors by single-molecule sequencing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, David F.; Lu, Jenny; Chang, Seungwoo

Genomic integrity is compromised by DNA polymerase replication errors, which occur in a sequence-dependent manner across the genome. Accurate and complete quantification of a DNA polymerase's error spectrum is challenging because errors are rare and difficult to detect. We report a high-throughput sequencing assay to map in vitro DNA replication errors at the single-molecule level. Unlike previous methods, our assay is able to rapidly detect a large number of polymerase errors at base resolution over any template substrate without quantification bias. To overcome the high error rate of high-throughput sequencing, our assay uses a barcoding strategy in which each replicationmore » product is tagged with a unique nucleotide sequence before amplification. Here, this allows multiple sequencing reads of the same product to be compared so that sequencing errors can be found and removed. We demonstrate the ability of our assay to characterize the average error rate, error hotspots and lesion bypass fidelity of several DNA polymerases.« less

Mapping DNA polymerase errors by single-molecule sequencing

DOE PAGES

Lee, David F.; Lu, Jenny; Chang, Seungwoo; ...

2016-05-16

Genomic integrity is compromised by DNA polymerase replication errors, which occur in a sequence-dependent manner across the genome. Accurate and complete quantification of a DNA polymerase's error spectrum is challenging because errors are rare and difficult to detect. We report a high-throughput sequencing assay to map in vitro DNA replication errors at the single-molecule level. Unlike previous methods, our assay is able to rapidly detect a large number of polymerase errors at base resolution over any template substrate without quantification bias. To overcome the high error rate of high-throughput sequencing, our assay uses a barcoding strategy in which each replicationmore » product is tagged with a unique nucleotide sequence before amplification. Here, this allows multiple sequencing reads of the same product to be compared so that sequencing errors can be found and removed. We demonstrate the ability of our assay to characterize the average error rate, error hotspots and lesion bypass fidelity of several DNA polymerases.« less

The effect of monetary punishment on error evaluation in a Go/No-go task.

PubMed

Maruo, Yuya; Sommer, Werner; Masaki, Hiroaki

2017-10-01

Little is known about the effects of the motivational significance of errors in Go/No-go tasks. We investigated the impact of monetary punishment on the error-related negativity (ERN) and error positivity (Pe) for both overt errors and partial errors, that is, no-go trials without overt responses but with covert muscle activities. We compared high and low punishment conditions where errors were penalized with 50 or 5 yen, respectively, and a control condition without monetary consequences for errors. Because we hypothesized that the partial-error ERN might overlap with the no-go N2, we compared ERPs between correct rejections (i.e., successful no-go trials) and partial errors in no-go trials. We also expected that Pe amplitudes should increase with the severity of the penalty for errors. Mean error rates were significantly lower in the high punishment than in the control condition. Monetary punishment did not influence the overt-error ERN and partial-error ERN in no-go trials. The ERN in no-go trials did not differ between partial errors and overt errors; in addition, ERPs for correct rejections in no-go trials without partial errors were of the same size as in go-trial. Therefore the overt-error ERN and the partial-error ERN may share similar error monitoring processes. Monetary punishment increased Pe amplitudes for overt errors, suggesting enhanced error evaluation processes. For partial errors an early Pe was observed, presumably representing inhibition processes. Interestingly, even partial errors elicited the Pe, suggesting that covert erroneous activities could be detected in Go/No-go tasks. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Genetics and Early Detection in Idiopathic Pulmonary Fibrosis

PubMed Central

Putman, Rachel K.; Rosas, Ivan O.

2014-01-01

Genetic studies hold promise in helping to identify patients with early idiopathic pulmonary fibrosis (IPF). Recent studies using chest computed tomograms (CTs) in smokers and in the general population have demonstrated that imaging abnormalities suggestive of an early stage of pulmonary fibrosis are not uncommon and are associated with respiratory symptoms, physical examination abnormalities, and physiologic decrements expected, but less severe than those noted in patients with IPF. Similarly, recent genetic studies have demonstrated strong and replicable associations between a common promoter polymorphism in the mucin 5B gene (MUC5B) and both IPF and the presence of abnormal imaging findings in the general population. Despite these findings, it is important to note that the definition of early-stage IPF remains unclear, limited data exist to definitively connect abnormal imaging findings to IPF, and genetic studies assessing early-stage pulmonary fibrosis remain in their infancy. In this perspective we provide updated information on interstitial lung abnormalities and their connection to IPF. We summarize information on the genetics of pulmonary fibrosis by focusing on the recent genetic findings of MUC5B. Finally, we discuss the implications of these findings and suggest a roadmap for the use of genetics in the detection of early IPF. PMID:24547893

A clinic-based study of refractive errors, strabismus, and amblyopia in pediatric age-group.

PubMed

Al-Tamimi, Elham R; Shakeel, Ayisha; Yassin, Sanaa A; Ali, Syed I; Khan, Umar A

2015-01-01

The purpose of this cross-sectional observational study was to determine the distribution and patterns of refractive errors, strabismus, and amblyopia in children seen at a pediatric eye care. The study was conducted in a Private Hospital in Dammam, Kingdom of Saudi Arabia, from March to July 2013. During this period, a total of 1350 children, aged 1-15 years were seen at this Center's Pediatric Ophthalmology Unit. All the children underwent complete ophthalmic examination with cycloplegic refraction. Refractive errors accounted for 44.4% of the cases, the predominant refractive error being hypermetropia which represented 83%. Strabismus and amblyopia were present in 38% and 9.1% of children, respectively. In this clinic-based study, the focus was on the frequency of refractive errors, strabismus, and amblyopia which were considerably high. Hypermetropia was the predominant refractive error in contrast to other studies in which myopia was more common. This could be attributed to the criteria for sample selection since it was clinic-based rather than a population-based study. However, it is important to promote public education on the significance of early detection of refractive errors, and have periodic screening in schools.

Virtual multiple errands test (VMET): a virtual reality-based tool to detect early executive functions deficit in Parkinson’s disease

PubMed Central

Cipresso, Pietro; Albani, Giovanni; Serino, Silvia; Pedroli, Elisa; Pallavicini, Federica; Mauro, Alessandro; Riva, Giuseppe

2014-01-01

Introduction: Several recent studies have pointed out that early impairment of executive functions (EFs) in Parkinson’s Disease (PD) may be a crucial marker to detect patients at risk for developing dementia. The main objective of this study was to compare the performances of PD patients with mild cognitive impairment (PD-MCI) with PD patients with normal cognition (PD-NC) and a control group (CG) using a traditional assessment of EFs and the Virtual Multiple Errands Test (VMET), a virtual reality (VR)-based tool. In order to understand which subcomponents of EFs are early impaired, this experimental study aimed to investigate specifically which instrument best discriminates among these three groups. Materials and methods: The study included three groups of 15 individuals each (for a total of 45 participants): 15 PD-NC; 15 PD-MCI, and 15 cognitively healthy individuals (CG). To assess the global neuropsychological functioning and the EFs, several tests (including the Mini Mental State Examination (MMSE), Clock Drawing Test, and Tower of London test) were administered to the participants. The VMET was used for a more ecologically valid neuropsychological evaluation of EFs. Results: Findings revealed significant differences in the VMET scores between the PD-NC patients vs. the controls. In particular, patients made more errors in the tasks of the VMET, and showed a poorer ability to use effective strategies to complete the tasks. This VMET result seems to be more sensitive in the early detection of executive deficits because these two groups did not differ in the traditional assessment of EFs (neuropsychological battery). Conclusion: This study offers initial evidence that a more ecologically valid evaluation of EFs is more likely to lead to detection of subtle executive deficits. PMID:25538578

A Novel Arc Fault Detector for Early Detection of Electrical Fires

PubMed Central

Yang, Kai; Zhang, Rencheng; Yang, Jianhong; Liu, Canhua; Chen, Shouhong; Zhang, Fujiang

2016-01-01

Arc faults can produce very high temperatures and can easily ignite combustible materials; thus, they represent one of the most important causes of electrical fires. The application of arc fault detection, as an emerging early fire detection technology, is required by the National Electrical Code to reduce the occurrence of electrical fires. However, the concealment, randomness and diversity of arc faults make them difficult to detect. To improve the accuracy of arc fault detection, a novel arc fault detector (AFD) is developed in this study. First, an experimental arc fault platform is built to study electrical fires. A high-frequency transducer and a current transducer are used to measure typical load signals of arc faults and normal states. After the common features of these signals are studied, high-frequency energy and current variations are extracted as an input eigenvector for use by an arc fault detection algorithm. Then, the detection algorithm based on a weighted least squares support vector machine is designed and successfully applied in a microprocessor. Finally, an AFD is developed. The test results show that the AFD can detect arc faults in a timely manner and interrupt the circuit power supply before electrical fires can occur. The AFD is not influenced by cross talk or transient processes, and the detection accuracy is very high. Hence, the AFD can be installed in low-voltage circuits to monitor circuit states in real-time to facilitate the early detection of electrical fires. PMID:27070618

Improving early detection initiatives: a qualitative study exploring perspectives of older people and professionals.

PubMed

Lette, Manon; Stoop, Annerieke; Lemmens, Lidwien C; Buist, Yvette; Baan, Caroline A; de Bruin, Simone R

2017-06-23

A wide range of initiatives on early detection and intervention have been developed to proactively identify problems related to health and wellbeing in (frail) older people, with the aim of supporting them to live independently for as long as possible. Nevertheless, it remains unclear what the best way is to design such initiatives and how older people's needs and preferences can be best addressed. This study aimed to address this gap in the literature by exploring: 1) older people's perspectives on health and living environment in relation to living independently at home; 2) older people's needs and preferences in relation to initiating and receiving care and support; and 3) professionals' views on what would be necessary to enable the alignment of early detection initiatives with older people's own needs and preferences. In this qualitative study, we conducted semi-structured interviews with 36 older people and 19 professionals in proactive elderly care. Data were analysed using the framework analysis method. From the interviews with older people important themes in relation to health and living environment emerged, such as maintaining independence, appropriate housing, social relationships, a supporting network and a sense of purpose and autonomy. Older people preferred to remain self-sufficient, and they would rather not ask for help for psychological or social problems. However, the interviews also highlighted that they were not always able or willing to anticipate future needs, which can hinder early detection or early intervention. At the same time, professionals indicated that older people tend to over-estimate their self-reliance and therefore advocated for early detection and intervention, including social and psychological issues. Older people have a broad range of needs in different domains of life. Discrepancies exist between older people and professionals with regard to their views on timing and scope of early detection initiatives. This study aimed

Catalyzing Novel Approaches to Rapid, Accurate, and Affordable Early Cancer Detection.

PubMed

Dhar, Asif; Meagher, Beth; Ryscavage, Andrew

Inspired by the Cancer Moonshot, a dedicated team of professionals worked with leaders across the cancer ecosystem to look for an opportunity to radically reduce cancer mortality globally by focusing on early cancer detection. After an initial survey of cancer innovation, progress, and pitfalls, the team believed that if new rapid, affordable, and accurate early detection solutions were appropriately brought to market, it would be possible to intervene earlier when cancer is most treatable.An extensive process began, informed by dozens of experts in the cancer ecosystem. The Cancer XPRIZE team designed a prize competition where "the winning team will develop a means to rapidly, accurately, and affordably screen for early cancers where intervention can reduce human suffering."The following outlines the Cancer XPRIZE's experience using a powerful approach-the radical prize design-to catch more cancers in time to make a difference saving lives, dollars, and suffering.

A Context-Aware EEG Headset System for Early Detection of Driver Drowsiness

PubMed Central

Li, Gang; Chung, Wan-Young

2015-01-01

Driver drowsiness is a major cause of mortality in traffic accidents worldwide. Electroencephalographic (EEG) signal, which reflects the brain activities, is more directly related to drowsiness. Thus, many Brain-Machine-Interface (BMI) systems have been proposed to detect driver drowsiness. However, detecting driver drowsiness at its early stage poses a major practical hurdle when using existing BMI systems. This study proposes a context-aware BMI system aimed to detect driver drowsiness at its early stage by enriching the EEG data with the intensity of head-movements. The proposed system is carefully designed for low-power consumption with on-chip feature extraction and low energy Bluetooth connection. Also, the proposed system is implemented using JAVA programming language as a mobile application for on-line analysis. In total, 266 datasets obtained from six subjects who participated in a one-hour monotonous driving simulation experiment were used to evaluate this system. According to a video-based reference, the proposed system obtained an overall detection accuracy of 82.71% for classifying alert and slightly drowsy events by using EEG data alone and 96.24% by using the hybrid data of head-movement and EEG. These results indicate that the combination of EEG data and head-movement contextual information constitutes a robust solution for the early detection of driver drowsiness. PMID:26308002

The Early Detection of Pancreatic Cancer: What Will it Take to Diagnose and Treat Curable Pancreatic Neoplasia?

PubMed Central

Lennon, Anne Marie; Wolfgang, Christopher L.; Canto, Marcia Irene; Klein, Alison P.; Herman, Joseph M.; Goggins, Michael; Fishman, Elliot K.; Kamel, Ihab; Weiss, Matthew J.; Diaz, Luis A.; Papadopoulos, Nickolas; Kinzler, Kenneth W.; Vogelstein, Bert; Hruban, Ralph H.

2014-01-01

Pancreatic cancer is the deadliest of all solid malignancies. Early detection offers the best hope for a cure, but characteristics of this disease such as the lack of early clinical symptoms, make the early detection difficult. Recent genetic mapping of the molecular evolution of pancreatic cancer suggests that a large window of opportunity exists for the early detection of pancreatic neoplasia, and developments in cancer genetics offer new, potentially highly specific, approaches for screening for curable pancreatic neoplasia. We review the challenges of screening for early pancreatic neoplasia, as well as opportunities presented by incorporating molecular genetics into these efforts. PMID:24924775

Software error data collection and categorization

NASA Technical Reports Server (NTRS)

Ostrand, T. J.; Weyuker, E. J.

1982-01-01

Software errors detected during development of an interactive special purpose editor system were studied. This product was followed during nine months of coding, unit testing, function testing, and system testing. A new error categorization scheme was developed.

Early detection of ecosystem regime shifts: a multiple method evaluation for management application.

PubMed

Lindegren, Martin; Dakos, Vasilis; Gröger, Joachim P; Gårdmark, Anna; Kornilovs, Georgs; Otto, Saskia A; Möllmann, Christian

2012-01-01

Critical transitions between alternative stable states have been shown to occur across an array of complex systems. While our ability to identify abrupt regime shifts in natural ecosystems has improved, detection of potential early-warning signals previous to such shifts is still very limited. Using real monitoring data of a key ecosystem component, we here apply multiple early-warning indicators in order to assess their ability to forewarn a major ecosystem regime shift in the Central Baltic Sea. We show that some indicators and methods can result in clear early-warning signals, while other methods may have limited utility in ecosystem-based management as they show no or weak potential for early-warning. We therefore propose a multiple method approach for early detection of ecosystem regime shifts in monitoring data that may be useful in informing timely management actions in the face of ecosystem change.

Early Detection of Ecosystem Regime Shifts: A Multiple Method Evaluation for Management Application

PubMed Central

Lindegren, Martin; Dakos, Vasilis; Gröger, Joachim P.; Gårdmark, Anna; Kornilovs, Georgs; Otto, Saskia A.; Möllmann, Christian

2012-01-01

Critical transitions between alternative stable states have been shown to occur across an array of complex systems. While our ability to identify abrupt regime shifts in natural ecosystems has improved, detection of potential early-warning signals previous to such shifts is still very limited. Using real monitoring data of a key ecosystem component, we here apply multiple early-warning indicators in order to assess their ability to forewarn a major ecosystem regime shift in the Central Baltic Sea. We show that some indicators and methods can result in clear early-warning signals, while other methods may have limited utility in ecosystem-based management as they show no or weak potential for early-warning. We therefore propose a multiple method approach for early detection of ecosystem regime shifts in monitoring data that may be useful in informing timely management actions in the face of ecosystem change. PMID:22808007

Nanotechnology-Based Detection of Novel microRNAs for Early Diagnosis of Prostate Cancer

DTIC Science & Technology

2016-08-01

1 AD _________________ AWARD NUMBER: W81XWH-15-1-0157 TITLE: Nanotechnology -Based Detection of Novel microRNAs for Early Diagnosis of Prostate...DATES COVERED 15 Jul 2015 - 14 Jul 2016 4. TITLE AND SUBTITLE Nanotechnology -Based Detection of Novel microRNAs for Early Diagnosis of Prostate Cancer...the expression level of deregulated miRNAs in mouse and human PCa tissues as well as serum samples using an advanced nanotechnology -based sensing

Is there any electrophysiological evidence for subliminal error processing?

PubMed

Shalgi, Shani; Deouell, Leon Y

2013-08-29

The role of error awareness in executive control and modification of behavior is not fully understood. In line with many recent studies showing that conscious awareness is unnecessary for numerous high-level processes such as strategic adjustments and decision making, it was suggested that error detection can also take place unconsciously. The Error Negativity (Ne) component, long established as a robust error-related component that differentiates between correct responses and errors, was a fine candidate to test this notion: if an Ne is elicited also by errors which are not consciously detected, it would imply a subliminal process involved in error monitoring that does not necessarily lead to conscious awareness of the error. Indeed, for the past decade, the repeated finding of a similar Ne for errors which became aware and errors that did not achieve awareness, compared to the smaller negativity elicited by correct responses (Correct Response Negativity; CRN), has lent the Ne the prestigious status of an index of subliminal error processing. However, there were several notable exceptions to these findings. The study in the focus of this review (Shalgi and Deouell, 2012) sheds new light on both types of previous results. We found that error detection as reflected by the Ne is correlated with subjective awareness: when awareness (or more importantly lack thereof) is more strictly determined using the wagering paradigm, no Ne is elicited without awareness. This result effectively resolves the issue of why there are many conflicting findings regarding the Ne and error awareness. The average Ne amplitude appears to be influenced by individual criteria for error reporting and therefore, studies containing different mixtures of participants who are more confident of their own performance or less confident, or paradigms that either encourage or don't encourage reporting low confidence errors will show different results. Based on this evidence, it is no longer possible to

Is there any electrophysiological evidence for subliminal error processing?

PubMed Central

Shalgi, Shani; Deouell, Leon Y.

2013-01-01

The role of error awareness in executive control and modification of behavior is not fully understood. In line with many recent studies showing that conscious awareness is unnecessary for numerous high-level processes such as strategic adjustments and decision making, it was suggested that error detection can also take place unconsciously. The Error Negativity (Ne) component, long established as a robust error-related component that differentiates between correct responses and errors, was a fine candidate to test this notion: if an Ne is elicited also by errors which are not consciously detected, it would imply a subliminal process involved in error monitoring that does not necessarily lead to conscious awareness of the error. Indeed, for the past decade, the repeated finding of a similar Ne for errors which became aware and errors that did not achieve awareness, compared to the smaller negativity elicited by correct responses (Correct Response Negativity; CRN), has lent the Ne the prestigious status of an index of subliminal error processing. However, there were several notable exceptions to these findings. The study in the focus of this review (Shalgi and Deouell, 2012) sheds new light on both types of previous results. We found that error detection as reflected by the Ne is correlated with subjective awareness: when awareness (or more importantly lack thereof) is more strictly determined using the wagering paradigm, no Ne is elicited without awareness. This result effectively resolves the issue of why there are many conflicting findings regarding the Ne and error awareness. The average Ne amplitude appears to be influenced by individual criteria for error reporting and therefore, studies containing different mixtures of participants who are more confident of their own performance or less confident, or paradigms that either encourage or don't encourage reporting low confidence errors will show different results. Based on this evidence, it is no longer possible to

Video comparator system for early detection of cutaneous malignant melanoma

NASA Astrophysics Data System (ADS)

Craine, Eric R.; Craine, Brian L.

1992-05-01

The recognized incidence of cutaneous malignant melanoma in the United States is now rising faster than any other cancer, increasing by 83% from 1980 to 1987. Recent revelations that depletion of the earth's ozone layer is accelerating at a more rapid rate than previously believed can only exacerbate current projections for the increased incidence of this deadly disease. Because there is no good treatment for metastatic melanoma even small cancers often prove fatal if not detected early. Melanoma allowed to invade the subcutaneous tissue is associated with a five-year survival rate of only 44%. Ironically, few cancers provide a greater opportunity for early discovery and cure. Cutaneous melanoma is not only located where it is readily observed, but typically undergoes a `radial growth' phase prior to metastasis. During this phase the net growth is superficial and circumferential, gradually increasing the area of the lesion and changing its coloration. Screening measures for the early detection of melanoma must concentrate on two primary tasks: (1) detection of lesion changes indicative of the radial growth stage of malignancy and (2) alerting the patient and physician to the existence of a new or changed lesion on the skin. To accomplish these goals we have experimented with the applicability of a microcomputer based video imaging system which stores an image archive of historical reference images for each patient. With the acquisition of new images of the patient, easily registered with the archival images through a technique we have developed we are able to perform a blink comparison of the image pairs. This technique appears to be far more effective than currently used techniques for detecting changed lesions on a comprehensive basis.

A Technique for Real-Time Ionospheric Ranging Error Correction Based On Radar Dual-Frequency Detection

NASA Astrophysics Data System (ADS)

Lyu, Jiang-Tao; Zhou, Chen

2017-12-01

Ionospheric refraction is one of the principal error sources for limiting the accuracy of radar systems for space target detection. High-accuracy measurement of the ionospheric electron density along the propagation path of radar wave is the most important procedure for the ionospheric refraction correction. Traditionally, the ionospheric model and the ionospheric detection instruments, like ionosonde or GPS receivers, are employed for obtaining the electron density. However, both methods are not capable of satisfying the requirements of correction accuracy for the advanced space target radar system. In this study, we propose a novel technique for ionospheric refraction correction based on radar dual-frequency detection. Radar target range measurements at two adjacent frequencies are utilized for calculating the electron density integral exactly along the propagation path of the radar wave, which can generate accurate ionospheric range correction. The implementation of radar dual-frequency detection is validated by a P band radar located in midlatitude China. The experimental results present that the accuracy of this novel technique is more accurate than the traditional ionospheric model correction. The technique proposed in this study is very promising for the high-accuracy radar detection and tracking of objects in geospace.

Role of EEG as Biomarker in the Early Detection and Classification of Dementia

PubMed Central

Al-Qazzaz, Noor Kamal; Ali, Sawal Hamid Bin MD.; Ahmad, Siti Anom; Chellappan, Kalaivani; Islam, Md. Shabiul; Escudero, Javier

2014-01-01

The early detection and classification of dementia are important clinical support tasks for medical practitioners in customizing patient treatment programs to better manage the development and progression of these diseases. Efforts are being made to diagnose these neurodegenerative disorders in the early stages. Indeed, early diagnosis helps patients to obtain the maximum treatment benefit before significant mental decline occurs. The use of electroencephalogram as a tool for the detection of changes in brain activities and clinical diagnosis is becoming increasingly popular for its capabilities in quantifying changes in brain degeneration in dementia. This paper reviews the role of electroencephalogram as a biomarker based on signal processing to detect dementia in early stages and classify its severity. The review starts with a discussion of dementia types and cognitive spectrum followed by the presentation of the effective preprocessing denoising to eliminate possible artifacts. It continues with a description of feature extraction by using linear and nonlinear techniques, and it ends with a brief explanation of vast variety of separation techniques to classify EEG signals. This paper also provides an idea from the most popular studies that may help in diagnosing dementia in early stages and classifying through electroencephalogram signal processing and analysis. PMID:25093211

Role of EEG as biomarker in the early detection and classification of dementia.

PubMed

Al-Qazzaz, Noor Kamal; Ali, Sawal Hamid Bin Md; Ahmad, Siti Anom; Chellappan, Kalaivani; Islam, Md Shabiul; Escudero, Javier

2014-01-01

The early detection and classification of dementia are important clinical support tasks for medical practitioners in customizing patient treatment programs to better manage the development and progression of these diseases. Efforts are being made to diagnose these neurodegenerative disorders in the early stages. Indeed, early diagnosis helps patients to obtain the maximum treatment benefit before significant mental decline occurs. The use of electroencephalogram as a tool for the detection of changes in brain activities and clinical diagnosis is becoming increasingly popular for its capabilities in quantifying changes in brain degeneration in dementia. This paper reviews the role of electroencephalogram as a biomarker based on signal processing to detect dementia in early stages and classify its severity. The review starts with a discussion of dementia types and cognitive spectrum followed by the presentation of the effective preprocessing denoising to eliminate possible artifacts. It continues with a description of feature extraction by using linear and nonlinear techniques, and it ends with a brief explanation of vast variety of separation techniques to classify EEG signals. This paper also provides an idea from the most popular studies that may help in diagnosing dementia in early stages and classifying through electroencephalogram signal processing and analysis.

FluBreaks: early epidemic detection from Google flu trends.

PubMed

Pervaiz, Fahad; Pervaiz, Mansoor; Abdur Rehman, Nabeel; Saif, Umar

2012-10-04

The Google Flu Trends service was launched in 2008 to track changes in the volume of online search queries related to flu-like symptoms. Over the last few years, the trend data produced by this service has shown a consistent relationship with the actual number of flu reports collected by the US Centers for Disease Control and Prevention (CDC), often identifying increases in flu cases weeks in advance of CDC records. However, contrary to popular belief, Google Flu Trends is not an early epidemic detection system. Instead, it is designed as a baseline indicator of the trend, or changes, in the number of disease cases. To evaluate whether these trends can be used as a basis for an early warning system for epidemics. We present the first detailed algorithmic analysis of how Google Flu Trends can be used as a basis for building a fully automated system for early warning of epidemics in advance of methods used by the CDC. Based on our work, we present a novel early epidemic detection system, called FluBreaks (dritte.org/flubreaks), based on Google Flu Trends data. We compared the accuracy and practicality of three types of algorithms: normal distribution algorithms, Poisson distribution algorithms, and negative binomial distribution algorithms. We explored the relative merits of these methods, and related our findings to changes in Internet penetration and population size for the regions in Google Flu Trends providing data. Across our performance metrics of percentage true-positives (RTP), percentage false-positives (RFP), percentage overlap (OT), and percentage early alarms (EA), Poisson- and negative binomial-based algorithms performed better in all except RFP. Poisson-based algorithms had average values of 99%, 28%, 71%, and 76% for RTP, RFP, OT, and EA, respectively, whereas negative binomial-based algorithms had average values of 97.8%, 17.8%, 60%, and 55% for RTP, RFP, OT, and EA, respectively. Moreover, the EA was also affected by the region's population size

Sampling design for aquatic invasive species early detection in Great Lakes ports

EPA Science Inventory

From 2006-2012, we evaluated a pilot aquatic invasive species (AIS) early detection monitoring program in Lake Superior that was designed to detect newly introduced fishes. We established survey protocols for three major ports (Duluth-Superior, Sault Ste. Marie, Thunder Bay) and ...

[Early detection of cervical cancer in Chile: time for change].

PubMed

Léniz Martelli, Javiera; Van De Wyngard, Vanessa; Lagos, Marcela; Barriga, María Isabel; Puschel Illanes, Klaus; Ferreccio Readi, Catterina

2014-08-01

Mortality rates for cervical cancer (CC) in Chile are higher than those of developed countries and it has an unequal socioeconomic distribution. The recognition of human papilloma virus (HPV) as the causal agent of cervical cancer in the early 80's changed the prevention paradigms. Current goals are to prevent HPV infection by vaccination before the onset of sexual activity and to detect HPV infection in women older than 30 years. This article reviews CC prevention and early detection methods, discusses relevant evidence to support a change in Chile and presents an innovation proposal. A strategy of primary screening based on HPV detection followed by triage of HPV-positive women by colposcopy in primary care or by cytological or molecular reflex testing is proposed. Due to the existence in Chile of a well-organized nationwide CC prevention program, the replacement of a low-sensitivity screening test such as the Papanicolau test with a highly sensitive one such as HPV detection, could quickly improve the effectiveness of the program. The program also has a network of personnel qualified to conduct naked-eye inspections of the cervix, who could easily be trained to perform triage colposcopy. The incorporation of new prevention strategies could reduce the deaths of Chilean women and correct inequities.

Early Oscillation Detection Technique for Hybrid DC/DC Converters

NASA Technical Reports Server (NTRS)

Wang, Bright L.

2011-01-01

Oscillation or instability is a situation that must be avoided for reliable hybrid DC/DC converters. A real-time electronics measurement technique was developed to detect catastrophic oscillations at early stages for hybrid DC/DC converters. It is capable of identifying low-level oscillation and determining the degree of the oscillation at a unique frequency for every individual model of the converters without disturbing their normal operations. This technique is specially developed for space-used hybrid DC/DC converters, but it is also suitable for most of commercial and military switching-mode power supplies. This is a weak-electronic-signal detection technique to detect hybrid DC/DC converter oscillation presented as a specific noise signal at power input pins. It is based on principles of feedback control loop oscillation and RF signal modulations, and is realized by using signal power spectral analysis. On the power spectrum, a channel power amplitude at characteristic frequency (CPcf) and a channel power amplitude at switching frequency (CPsw) are chosen as oscillation level indicators. If the converter is stable, the CPcf is a very small pulse and the CPsw is a larger, clear, single pulse. At early stage of oscillation, the CPcf increases to a certain level and the CPsw shows a small pair of sideband pulses around it. If the converter oscillates, the CPcf reaches to a higher level and the CPsw shows more high-level sideband pulses. A comprehensive stability index (CSI) is adopted as a quantitative measure to accurately assign a degree of stability to a specific DC/DC converter. The CSI is a ratio of normal and abnormal power spectral density, and can be calculated using specified and measured CPcf and CPsw data. The novel and unique feature of this technique is the use of power channel amplitudes at characteristic frequency and switching frequency to evaluate stability and identify oscillations at an early stage without interfering with a DC/DC converter s

Stochastic output error vibration-based damage detection and assessment in structures under earthquake excitation

NASA Astrophysics Data System (ADS)

Sakellariou, J. S.; Fassois, S. D.

2006-11-01

A stochastic output error (OE) vibration-based methodology for damage detection and assessment (localization and quantification) in structures under earthquake excitation is introduced. The methodology is intended for assessing the state of a structure following potential damage occurrence by exploiting vibration signal measurements produced by low-level earthquake excitations. It is based upon (a) stochastic OE model identification, (b) statistical hypothesis testing procedures for damage detection, and (c) a geometric method (GM) for damage assessment. The methodology's advantages include the effective use of the non-stationary and limited duration earthquake excitation, the handling of stochastic uncertainties, the tackling of the damage localization and quantification subproblems, the use of "small" size, simple and partial (in both the spatial and frequency bandwidth senses) identified OE-type models, and the use of a minimal number of measured vibration signals. Its feasibility and effectiveness are assessed via Monte Carlo experiments employing a simple simulation model of a 6 storey building. It is demonstrated that damage levels of 5% and 20% reduction in a storey's stiffness characteristics may be properly detected and assessed using noise-corrupted vibration signals.

How do Community Pharmacies Recover from E-prescription Errors?

PubMed Central

Odukoya, Olufunmilola K.; Stone, Jamie A.; Chui, Michelle A.

2014-01-01

Background The use of e-prescribing is increasing annually, with over 788 million e-prescriptions received in US pharmacies in 2012. Approximately 9% of e-prescriptions have medication errors. Objective To describe the process used by community pharmacy staff to detect, explain, and correct e-prescription errors. Methods The error recovery conceptual framework was employed for data collection and analysis. 13 pharmacists and 14 technicians from five community pharmacies in Wisconsin participated in the study. A combination of data collection methods were utilized, including direct observations, interviews, and focus groups. The transcription and content analysis of recordings were guided by the three-step error recovery model. Results Most of the e-prescription errors were detected during the entering of information into the pharmacy system. These errors were detected by both pharmacists and technicians using a variety of strategies which included: (1) performing double checks of e-prescription information; (2) printing the e-prescription to paper and confirming the information on the computer screen with information from the paper printout; and (3) using colored pens to highlight important information. Strategies used for explaining errors included: (1) careful review of patient’ medication history; (2) pharmacist consultation with patients; (3) consultation with another pharmacy team member; and (4) use of online resources. In order to correct e-prescription errors, participants made educated guesses of the prescriber’s intent or contacted the prescriber via telephone or fax. When e-prescription errors were encountered in the community pharmacies, the primary goal of participants was to get the order right for patients by verifying the prescriber’s intent. Conclusion Pharmacists and technicians play an important role in preventing e-prescription errors through the detection of errors and the verification of prescribers’ intent. Future studies are needed

Early Hearing Detection and Intervention in Developing Countries: Current Status and Prospects

ERIC Educational Resources Information Center

Olusanya, Bolajoko O.

2006-01-01

Infant hearing screening is emerging rapidly as a silent global revolution for the early detection of children with congenital or early onset hearing loss to ensure timely enrollment in family-oriented intervention programs for the development of spoken language. This article examines the overriding and interrelated scientific, ethical and…

Early detection of tooth wear by en-face optical coherence tomography

NASA Astrophysics Data System (ADS)

Mărcăuteanu, Corina; Negrutiu, Meda; Sinescu, Cosmin; Demjan, Eniko; Hughes, Mike; Bradu, Adrian; Dobre, George; Podoleanu, Adrian G.

2009-02-01

Excessive dental wear (pathological attrition and/or abfractions) is a frequent complication in bruxing patients. The parafunction causes heavy occlusal loads. The aim of this study is the early detection and monitoring of occlusal overload in bruxing patients. En-face optical coherence tomography was used for investigating and imaging of several extracted tooth, with a normal morphology, derived from patients with active bruxism and from subjects without parafunction. We found a characteristic pattern of enamel cracks in patients with first degree bruxism and with a normal tooth morphology. We conclude that the en-face optical coherence tomography is a promising non-invasive alternative technique for the early detection of occlusal overload, before it becomes clinically evident as tooth wear.

Oral cancer. Practical prevention and early detection for the dental team.

PubMed

Kerr, A Ross; Cruz, Gustavo D

2002-01-01

Approximately 2,000 patients a year are diagnosed with oral cancer in New York State. In an effort to control this deadly disease, Governor George Pataki has taken a leadership role in the United States by mandating and funding training for dentists in the prevention and early detection of oral cancer. The purpose of this article is to highlight the epidemiology of oral cancer, to show how the dental profession can contribute to the health of the citizens of New York State, and to provide practical guidelines for both tobacco cessation intervention and utilization of existing technology for the early detection of oral cancer and precancerous conditions in the general dental practice setting.

Structural MRI-based detection of Alzheimer's disease using feature ranking and classification error.

PubMed

Beheshti, Iman; Demirel, Hasan; Farokhian, Farnaz; Yang, Chunlan; Matsuda, Hiroshi

2016-12-01

This paper presents an automatic computer-aided diagnosis (CAD) system based on feature ranking for detection of Alzheimer's disease (AD) using structural magnetic resonance imaging (sMRI) data. The proposed CAD system is composed of four systematic stages. First, global and local differences in the gray matter (GM) of AD patients compared to the GM of healthy controls (HCs) are analyzed using a voxel-based morphometry technique. The aim is to identify significant local differences in the volume of GM as volumes of interests (VOIs). Second, the voxel intensity values of the VOIs are extracted as raw features. Third, the raw features are ranked using a seven-feature ranking method, namely, statistical dependency (SD), mutual information (MI), information gain (IG), Pearson's correlation coefficient (PCC), t-test score (TS), Fisher's criterion (FC), and the Gini index (GI). The features with higher scores are more discriminative. To determine the number of top features, the estimated classification error based on training set made up of the AD and HC groups is calculated, with the vector size that minimized this error selected as the top discriminative feature. Fourth, the classification is performed using a support vector machine (SVM). In addition, a data fusion approach among feature ranking methods is introduced to improve the classification performance. The proposed method is evaluated using a data-set from ADNI (130 AD and 130 HC) with 10-fold cross-validation. The classification accuracy of the proposed automatic system for the diagnosis of AD is up to 92.48% using the sMRI data. An automatic CAD system for the classification of AD based on feature-ranking method and classification errors is proposed. In this regard, seven-feature ranking methods (i.e., SD, MI, IG, PCC, TS, FC, and GI) are evaluated. The optimal size of top discriminative features is determined by the classification error estimation in the training phase. The experimental results indicate that

A Simple System for the Early Detection of Breast Cancer

DTIC Science & Technology

2016-07-01

AWARD NUMBER: W81XWH-14-1-0231 TITLE: A Simple System for Early Detection of Breast Cancer PRINCIPAL INVESTIGATOR: Stephen Johnston CONTRACTING...ADDRESS. 1. REPORT DATE July 2016 2. REPORT TYPE Annual 3. DATES COVERED 1Jul2015 - 30Jun2016 4. TITLE AND SUBTITLE A Simple System for the Early...Form 298 (Rev. 8-98) Prescribed by ANSI Std. Z39.18 W81XWH-14-1-0231 Abstract: We invented the immunosignature technology (IMS) as a simple , universal

Early Detection Research Network (EDRN) | Division of Cancer Prevention

Cancer.gov

http://edrn.nci.nih.gov/EDRN is a collaborative network that maintains comprehensive infrastructure and resources critical to the discovery, development and validation of biomarkers for cancer risk and early detection. The program comprises a public/private sector consortium to accelerate the development of biomarkers that will change medical practice, ensure data

EARLY DETECTION MONITORING OF INVASIVE SPECIES IN GREAT LAKES HARBORS

EPA Science Inventory

The Great Ships Initiative (GSI) has asked for a presentation on designing harbor monitoring. Our research/development project on early detection provides some examples and lessons for GSI to consider in evaluating effectiveness of ballast water treatments; the presentation allo...

Results of an early hearing detection program.

PubMed

Borkoski Barreiro, Silvia A; Falcón González, Juan C; Bueno Yanes, Jorge; Pérez Bermúdez, José L; López Cano, Zoraida; Ramos Macías, Ángel

2013-01-01

Neonatal hearing loss is a public health problem that meets the requirements for submission to universal screening. Our objective was to analyse the results of the early hearing detection and intervention program implemented at our centre between January 2007 and December 2010. We studied 26,717 newborns during the period mentioned, using transient otoacoustic emissions (TOAEs) for the screening. The diagnostic phase was carried out at the hearing loss department. In our area, there were 27,935 births between January 2007 and December 2010. The screening was performed on 26,717 children. Of these, 24,173 had positive TOAEs, 1,040 had no TOAEs and 1,504 presented TOAEs in 1 ear with absence of TOAEs in the contralateral ear. Risk factors associated with hearing loss were found in 4,674 infants. In a second phase of the program, TOAEs were given to 5,156 children, of whom 4,626 had positive otoacoustic emissions in both ears, 323 had no TOAEs in 1 ear and 207 failed this second phase. Of all children studied, 3.8% were referred to auditory brainstem response (ABR) testing and 26 children entered the cochlear implant program. The program reached coverage of 95.64%. The early hearing detection and intervention program at our hospital is suitable for our environment, reaching 95.64% of coverage. We consider the relationship between effectiveness and efficiency to be positive. Copyright © 2012 Elsevier España, S.L. All rights reserved.

Acoustic Evidence for Phonologically Mismatched Speech Errors

ERIC Educational Resources Information Center

Gormley, Andrea

2015-01-01

Speech errors are generally said to accommodate to their new phonological context. This accommodation has been validated by several transcription studies. The transcription methodology is not the best choice for detecting errors at this level, however, as this type of error can be difficult to perceive. This paper presents an acoustic analysis of…

Errors in Bibliographic Citations: A Continuing Problem.

ERIC Educational Resources Information Center

Sweetland, James H.

1989-01-01

Summarizes studies examining citation errors and illustrates errors resulting from a lack of standardization, misunderstanding of foreign languages, failure to examine the document cited, and general lack of training in citation norms. It is argued that the failure to detect and correct citation errors is due to diffusion of responsibility in the…

Early Detection of Infection in Pigs through an Online Monitoring System.

PubMed

Martínez-Avilés, M; Fernández-Carrión, E; López García-Baones, J M; Sánchez-Vizcaíno, J M

2017-04-01

Late detection of emergency diseases causes significant economic losses for pig producers and governments. As the first signs of animal infection are usually fever and reduced motion that lead to reduced consumption of water and feed, we developed a novel smart system to monitor body temperature and motion in real time, facilitating the early detection of infectious diseases. In this study, carried out within the framework of the European Union research project Rapidia Field, we tested the smart system on 10 pigs experimentally infected with two doses of an attenuated strain of African swine fever. Biosensors and an accelerometer embedded in an eartag captured data before and after infection, and video cameras were used to monitor the animals 24 h per day. The results showed that in 8 of 9 cases, the monitoring system detected infection onset as an increase in body temperature and decrease in movement before or simultaneously with fever detection based on rectal temperature measurement, observation of clinical signs, the decrease in water consumption or positive qPCR detection of virus. In addition, this decrease in movement was reliably detected using automatic analysis of video images therefore providing an inexpensive alternative to direct motion measurement. The system can be set up to alert staff when high fever, reduced motion or both are detected in one or more animals. This system may be useful for monitoring sentinel herds in real time, considerably reducing the financial and logistical costs of periodic sampling and increasing the chances of early detection of infection. © 2015 Blackwell Verlag GmbH.

Method for early detection of infectious mononucleosis

DOEpatents

Willard, K.E.

1982-08-10

Early detection of infectious mononucleosis is carried out using a sample of human blood by isolating and identifying the presence of Inmono proteins in the sample from a two-dimensional protein map with the proteins being characterized by having isoelectric banding as measured in urea of about -16 to -17 with respect to certain isoelectric point standards and molecular mass of about 70 to 75 K daltons as measured in the presence of sodium dodecylsulfate containing polyacrylamide gels, the presence of the Inmono proteins being correlated with the existence of infectious mononucleosis.

Strategies for Early Outbreak Detection of Malaria in the Amhara Region of Ethiopia

NASA Astrophysics Data System (ADS)

Nekorchuk, D.; Gebrehiwot, T.; Mihretie, A.; Awoke, W.; Wimberly, M. C.

2017-12-01

Traditional epidemiological approaches to early detection of disease outbreaks are based on relatively straightforward thresholds (e.g. 75th percentile, standard deviations) estimated from historical case data. For diseases with strong seasonality, these can be modified to create separate thresholds for each seasonal time step. However, for disease processes that are non-stationary, more sophisticated techniques are needed to more accurately estimate outbreak threshold values. Early detection for geohealth-related diseases that also have environmental drivers, such as vector-borne diseases, may also benefit from the integration of time-lagged environmental data and disease ecology models into the threshold calculations. The Epidemic Prognosis Incorporating Disease and Environmental Monitoring for Integrated Assessment (EPIDEMIA) project has been integrating malaria case surveillance with remotely-sensed environmental data for early detection, warning, and forecasting of malaria epidemics in the Amhara region of Ethiopia, and has five years of weekly time series data from 47 woredas (districts). Efforts to reduce the burden of malaria in Ethiopia has been met with some notable success in the past two decades with major reduction in cases and deaths. However, malaria remains a significant public health threat as 60% of the population live in malarious areas, and due to the seasonal and unstable transmission patterns with cyclic outbreaks, protective immunity is generally low which could cause high morbidity and mortality during the epidemics. This study compared several approaches for defining outbreak thresholds and for identifying a potential outbreak based on deviations from these thresholds. We found that model-based approaches that accounted for climate-driven seasonality in malaria transmission were most effective, and that incorporating a trend component improved outbreak detection in areas with active malaria elimination efforts. An advantage of these early

First step toward translation of thermophotonic lock-in imaging to dentistry as an early caries detection technology

NASA Astrophysics Data System (ADS)

Ojaghi, Ashkan; Parkhimchyk, Artur; Tabatabaei, Nima

2016-09-01

Early detection of the most prevalent oral disease worldwide, i.e., dental caries, still remains as one of the major challenges in dentistry. The current dental standard of care relies on caries detection methods, such as visual inspection and x-ray radiography, which lack the sufficient specificity and sensitivity to detect caries at early stages of formation when they can be healed. We report on the feasibility of early caries detection in a clinically and commercially viable thermophotonic imaging system. The system incorporates intensity-modulated laser light along with a low-cost long-wavelength infrared (LWIR; 8 to 14 μm) camera, providing diagnostic contrast based on the enhanced light absorption of early caries. The LWIR camera is highly suitable for integration into clinical platforms because of its low weight and cost. In addition, through theoretical modeling, we show that LWIR detection enhances the diagnostic contrast due to the minimal LWIR transmittance of enamel and suppression of the masking effect of the direct thermal Planck emission. Diagnostic performance of the system and its detection threshold are experimentally evaluated by monitoring the inception and progression of artificially induced occlusal and smooth surface caries. The results are suggestive of the suitability of the developed LWIR system for detecting early dental caries.

Recent advances in targeted endoscopic imaging: Early detection of gastrointestinal neoplasms

PubMed Central

Kwon, Yong-Soo; Cho, Young-Seok; Yoon, Tae-Jong; Kim, Ho-Shik; Choi, Myung-Gyu

2012-01-01

Molecular imaging has emerged as a new discipline in gastrointestinal endoscopy. This technology encompasses modalities that can visualize disease-specific morphological or functional tissue changes based on the molecular signature of individual cells. Molecular imaging has several advantages including minimal damage to tissues, repetitive visualization, and utility for conducting quantitative analyses. Advancements in basic science coupled with endoscopy have made early detection of gastrointestinal cancer possible. Molecular imaging during gastrointestinal endoscopy requires the development of safe biomarkers and exogenous probes to detect molecular changes in cells with high specificity anda high signal-to-background ratio. Additionally, a high-resolution endoscope with an accurate wide-field viewing capability must be developed. Targeted endoscopic imaging is expected to improve early diagnosis and individual therapy of gastrointestinal cancer. PMID:22442742

Early Breast Cancer Detection by Ultrawide Band Imaging with Dispersion Consideration

NASA Astrophysics Data System (ADS)

Xiao, Xia; Kikkawa, Takamaro

2008-04-01

Ultrawide band (UWB) microwave imaging is a promising method for early-stage breast cancer detection based on the large contrast of electric parameters between the tumor and the normal breast tissue. The tumor can be detected by analyzing the reflection and scattering behavior of the UWB microwave propagating in the breast. In this study, the tumor location is determined by comparing the waveforms resulted from the tumor-containing and tumor-free breasts. The frequency dispersive characteristics of the fatty breast tissue, skin and tumor are considered in the study to approach the actual electrical properties of the breast. The correct location and size are visualized for an early-stage tumor embedded in the breast using the principle of a confocal microwave imaging technique.

Advancing Early Detection of Autism Spectrum Disorder by Applying an Integrated Two-Stage Screening Approach

ERIC Educational Resources Information Center

Oosterling, Iris J.; Wensing, Michel; Swinkels, Sophie H.; van der Gaag, Rutger Jan; Visser, Janne C.; Woudenberg, Tim; Minderaa, Ruud; Steenhuis, Mark-Peter; Buitelaar, Jan K.

2010-01-01

Background: Few field trials exist on the impact of implementing guidelines for the early detection of autism spectrum disorders (ASD). The aims of the present study were to develop and evaluate a clinically relevant integrated early detection programme based on the two-stage screening approach of Filipek et al. (1999), and to expand the evidence…

The Early Detection of the Emerald Ash Borer (EAB) Using Advanced Geospacial Technologies

NASA Astrophysics Data System (ADS)

Hu, B.; Li, J.; Wang, J.; Hall, B.

2014-11-01

The objectives of this study were to exploit Light Detection And Ranging (LiDAR) and very high spatial resolution (VHR) data and their synergy with hyperspectral imagery in the early detection of the EAB presence in trees within urban areas and to develop a framework to combine information extracted from multiple data sources. To achieve these, an object-oriented framework was developed to combine information derived from available data sets to characterize ash trees. Within this framework, individual trees were first extracted and then classified into different species based on their spectral information derived from hyperspectral imagery, spatial information from VHR imagery, and for each ash tree its health state and EAB infestation stage were determined based on hyperspectral imagery. The developed framework and methods were demonstrated to be effective according to the results obtained on two study sites in the city of Toronto, Ontario Canada. The individual tree delineation method provided satisfactory results with an overall accuracy of 78 % and 19 % commission and 23 % omission errors when used on the combined very high-spatial resolution imagery and LiDAR data. In terms of the identification of ash trees, given sufficient representative training data, our classification model was able to predict tree species with above 75 % overall accuracy, and mis-classification occurred mainly between ash and maple trees. The hypothesis that a strong correlation exists between general tree stress and EAB infestation was confirmed. Vegetation indices sensitive to leaf chlorophyll content derived from hyperspectral imagery can be used to predict the EAB infestation levels for each ash tree.

Detecting COPD exacerbations early using daily telemonitoring of symptoms and k-means clustering: a pilot study.

PubMed

Sanchez-Morillo, Daniel; Fernandez-Granero, Miguel Angel; Jiménez, Antonio León

2015-05-01

COPD places an enormous burden on the healthcare systems and causes diminished health-related quality of life. The highest proportion of human and economic cost is associated with admissions for acute exacerbation of respiratory symptoms (AECOPD). Since prompt detection and treatment of exacerbations may improve outcomes, early detection of AECOPD is a critical issue. This pilot study was aimed to determine whether a mobile health system could enable early detection of AECOPD on a day-to-day basis. A novel electronic questionnaire for the early detection of COPD exacerbations was evaluated during a 6-months field trial in a group of 16 patients. Pattern recognition techniques were applied. A k-means clustering algorithm was trained and validated, and its accuracy in detecting AECOPD was assessed. Sensitivity and specificity were 74.6 and 89.7 %, respectively, and area under the receiver operating characteristic curve was 0.84. 31 out of 33 AECOPD were early identified with an average of 4.5 ± 2.1 days prior to the onset of the exacerbation that was considered the day of medical attendance. Based on the findings of this preliminary pilot study, the proposed electronic questionnaire and the applied methodology could help to early detect COPD exacerbations on a day-to-day basis and therefore could provide support to patients and physicians.