Automatic background updating for video-based vehicle detection

NASA Astrophysics Data System (ADS)

Hu, Chunhai; Li, Dongmei; Liu, Jichuan

2008-03-01

Video-based vehicle detection is one of the most valuable techniques for the Intelligent Transportation System (ITS). The widely used video-based vehicle detection technique is the background subtraction method. The key problem of this method is how to subtract and update the background effectively. In this paper an efficient background updating scheme based on Zone-Distribution for vehicle detection is proposed to resolve the problems caused by sudden camera perturbation, sudden or gradual illumination change and the sleeping person problem. The proposed scheme is robust and fast enough to satisfy the real-time constraints of vehicle detection.

A Protocol Layer Trust-Based Intrusion Detection Scheme for Wireless Sensor Networks

PubMed Central

Wang, Jian; Jiang, Shuai; Fapojuwo, Abraham O.

2017-01-01

This article proposes a protocol layer trust-based intrusion detection scheme for wireless sensor networks. Unlike existing work, the trust value of a sensor node is evaluated according to the deviations of key parameters at each protocol layer considering the attacks initiated at different protocol layers will inevitably have impacts on the parameters of the corresponding protocol layers. For simplicity, the paper mainly considers three aspects of trustworthiness, namely physical layer trust, media access control layer trust and network layer trust. The per-layer trust metrics are then combined to determine the overall trust metric of a sensor node. The performance of the proposed intrusion detection mechanism is then analyzed using the t-distribution to derive analytical results of false positive and false negative probabilities. Numerical analytical results, validated by simulation results, are presented in different attack scenarios. It is shown that the proposed protocol layer trust-based intrusion detection scheme outperforms a state-of-the-art scheme in terms of detection probability and false probability, demonstrating its usefulness for detecting cross-layer attacks. PMID:28555023

A Protocol Layer Trust-Based Intrusion Detection Scheme for Wireless Sensor Networks.

PubMed

Wang, Jian; Jiang, Shuai; Fapojuwo, Abraham O

2017-05-27

This article proposes a protocol layer trust-based intrusion detection scheme for wireless sensor networks. Unlike existing work, the trust value of a sensor node is evaluated according to the deviations of key parameters at each protocol layer considering the attacks initiated at different protocol layers will inevitably have impacts on the parameters of the corresponding protocol layers. For simplicity, the paper mainly considers three aspects of trustworthiness, namely physical layer trust, media access control layer trust and network layer trust. The per-layer trust metrics are then combined to determine the overall trust metric of a sensor node. The performance of the proposed intrusion detection mechanism is then analyzed using the t-distribution to derive analytical results of false positive and false negative probabilities. Numerical analytical results, validated by simulation results, are presented in different attack scenarios. It is shown that the proposed protocol layer trust-based intrusion detection scheme outperforms a state-of-the-art scheme in terms of detection probability and false probability, demonstrating its usefulness for detecting cross-layer attacks.

A DFIG Islanding Detection Scheme Based on Reactive Power Infusion

NASA Astrophysics Data System (ADS)

Wang, M.; Liu, C.; He, G. Q.; Li, G. H.; Feng, K. H.; Sun, W. W.

2017-07-01

A lot of research has been done on photovoltaic (the “PV”) power system islanding detection in recent years. As a comparison, much less attention has been paid to islanding in wind turbines. Meanwhile, wind turbines can work in islanding conditions for quite a long period, which can be harmful to equipments and cause safety hazards. This paper presents and examines a double fed introduction generation (the “DFIG”) islanding detection scheme based on feedback of reactive power and frequency and uses a trigger signal of reactive power infusion which can be obtained by dividing the voltage total harmonic distortion (the "THD") by the voltage THD of last cycle to avoid the deterioration of power quality. This DFIG islanding detection scheme uses feedback of reactive power current loop to amplify the frequency differences in islanding and normal conditions. Simulation results show that the DFIG islanding detection scheme is effective.

Computerized Detection of Lung Nodules by Means of “Virtual Dual-Energy” Radiography

PubMed Central

Chen, Sheng; Suzuki, Kenji

2014-01-01

Major challenges in current computer-aided detection (CADe) schemes for nodule detection in chest radiographs (CXRs) are to detect nodules that overlap with ribs and/or clavicles and to reduce the frequent false positives (FPs) caused by ribs. Detection of such nodules by a CADe scheme is very important, because radiologists are likely to miss such subtle nodules. Our purpose in this study was to develop a CADe scheme with improved sensitivity and specificity by use of “virtual dual-energy” (VDE) CXRs where ribs and clavicles are suppressed with massive-training artificial neural networks (MTANNs). To reduce rib-induced FPs and detect nodules overlapping with ribs, we incorporated the VDE technology in our CADe scheme. The VDE technology suppressed rib and clavicle opacities in CXRs while maintaining soft-tissue opacity by use of the MTANN technique that had been trained with real dual-energy imaging. Our scheme detected nodule candidates on VDE images by use of a morphologic filtering technique. Sixty morphologic and gray-level-based features were extracted from each candidate from both original and VDE CXRs. A nonlinear support vector classifier was employed for classification of the nodule candidates. A publicly available database containing 140 nodules in 140 CXRs and 93 normal CXRs was used for testing our CADe scheme. All nodules were confirmed by computed tomography examinations, and the average size of the nodules was 17.8 mm. Thirty percent (42/140) of the nodules were rated “extremely subtle” or “very subtle” by a radiologist. The original scheme without VDE technology achieved a sensitivity of 78.6% (110/140) with 5 (1165/233) FPs per image. By use of the VDE technology, more nodules overlapping with ribs or clavicles were detected and the sensitivity was improved substantially to 85.0% (119/140) at the same FP rate in a leave-one-out cross-validation test, whereas the FP rate was reduced to 2.5 (583/233) per image at the same sensitivity level as the original CADe scheme obtained (Difference between the specificities of the original and the VDE-based CADe schemes was statistically significant). In particular, the sensitivity of our VDE-based CADe scheme for subtle nodules (66.7% = 28/42) was statistically significantly higher than that of the original CADe scheme (57.1% = 24/42). Therefore, by use of VDE technology, the sensitivity and specificity of our CADe scheme for detection of nodules, especially subtle nodules, in CXRs were improved substantially. PMID:23193306

Computerized detection of lung nodules by means of "virtual dual-energy" radiography.

PubMed

Chen, Sheng; Suzuki, Kenji

2013-02-01

Major challenges in current computer-aided detection (CADe) schemes for nodule detection in chest radiographs (CXRs) are to detect nodules that overlap with ribs and/or clavicles and to reduce the frequent false positives (FPs) caused by ribs. Detection of such nodules by a CADe scheme is very important, because radiologists are likely to miss such subtle nodules. Our purpose in this study was to develop a CADe scheme with improved sensitivity and specificity by use of "virtual dual-energy" (VDE) CXRs where ribs and clavicles are suppressed with massive-training artificial neural networks (MTANNs). To reduce rib-induced FPs and detect nodules overlapping with ribs, we incorporated the VDE technology in our CADe scheme. The VDE technology suppressed rib and clavicle opacities in CXRs while maintaining soft-tissue opacity by use of the MTANN technique that had been trained with real dual-energy imaging. Our scheme detected nodule candidates on VDE images by use of a morphologic filtering technique. Sixty morphologic and gray-level-based features were extracted from each candidate from both original and VDE CXRs. A nonlinear support vector classifier was employed for classification of the nodule candidates. A publicly available database containing 140 nodules in 140 CXRs and 93 normal CXRs was used for testing our CADe scheme. All nodules were confirmed by computed tomography examinations, and the average size of the nodules was 17.8 mm. Thirty percent (42/140) of the nodules were rated "extremely subtle" or "very subtle" by a radiologist. The original scheme without VDE technology achieved a sensitivity of 78.6% (110/140) with 5 (1165/233) FPs per image. By use of the VDE technology, more nodules overlapping with ribs or clavicles were detected and the sensitivity was improved substantially to 85.0% (119/140) at the same FP rate in a leave-one-out cross-validation test, whereas the FP rate was reduced to 2.5 (583/233) per image at the same sensitivity level as the original CADe scheme obtained (Difference between the specificities of the original and the VDE-based CADe schemes was statistically significant). In particular, the sensitivity of our VDE-based CADe scheme for subtle nodules (66.7% = 28/42) was statistically significantly higher than that of the original CADe scheme (57.1% = 24/42). Therefore, by use of VDE technology, the sensitivity and specificity of our CADe scheme for detection of nodules, especially subtle nodules, in CXRs were improved substantially.

Electromechanical Displacement Detection With an On-Chip High Electron Mobility Transistor Amplifier

NASA Astrophysics Data System (ADS)

Oda, Yasuhiko; Onomitsu, Koji; Kometani, Reo; Warisawa, Shin-ichi; Ishihara, Sunao; Yamaguchi, Hiroshi

2011-06-01

We developed a highly sensitive displacement detection scheme for a GaAs-based electromechanical resonator using an integrated high electron mobility transistor (HEMT). Piezoelectric voltage generated by the vibration of the resonator is applied to the gate of the HEMT, resulting in the on-chip amplification of the signal voltage. This detection scheme achieves a displacement sensitivity of ˜9 pm·Hz-1/2, which is one of the highest among on-chip purely electrical displacement detection schemes at room temperature.

High-Performance Sensors Based on Resistance Fluctuations of Single-Layer-Graphene Transistors.

PubMed

Amin, Kazi Rafsanjani; Bid, Aveek

2015-09-09

One of the most interesting predicted applications of graphene-monolayer-based devices is as high-quality sensors. In this article, we show, through systematic experiments, a chemical vapor sensor based on the measurement of low-frequency resistance fluctuations of single-layer-graphene field-effect-transistor devices. The sensor has extremely high sensitivity, very high specificity, high fidelity, and fast response times. The performance of the device using this scheme of measurement (which uses resistance fluctuations as the detection parameter) is more than 2 orders of magnitude better than a detection scheme in which changes in the average value of the resistance is monitored. We propose a number-density-fluctuation-based model to explain the superior characteristics of a noise-measurement-based detection scheme presented in this article.

Compact electrochemical sensor system and method for field testing for metals in saliva or other fluids

DOEpatents

Lin, Yuehe; Bennett, Wendy D.; Timchalk, Charles; Thrall, Karla D.

2004-03-02

Microanalytical systems based on a microfluidics/electrochemical detection scheme are described. Individual modules, such as microfabricated piezoelectrically actuated pumps and a microelectrochemical cell were integrated onto portable platforms. This allowed rapid change-out and repair of individual components by incorporating "plug and play" concepts now standard in PC's. Different integration schemes were used for construction of the microanalytical systems based on microfluidics/electrochemical detection. In one scheme, all individual modules were integrated in the surface of the standard microfluidic platform based on a plug-and-play design. Microelectrochemical flow cell which integrated three electrodes based on a wall-jet design was fabricated on polymer substrate. The microelectrochemical flow cell was then plugged directly into the microfluidic platform. Another integration scheme was based on a multilayer lamination method utilizing stacking modules with different functionality to achieve a compact microanalytical device. Application of the microanalytical system for detection of lead in, for example, river water and saliva samples using stripping voltammetry is described.

Achievable Strength-Based Signal Detection in Quantity-Constrained PAM OOK Concentration-Encoded Molecular Communication.

PubMed

Mahfuz, Mohammad Upal

2016-10-01

In this paper, the expressions of achievable strength-based detection probabilities of concentration-encoded molecular communication (CEMC) system have been derived based on finite pulsewidth (FP) pulse-amplitude modulated (PAM) on-off keying (OOK) modulation scheme and strength threshold. An FP-PAM system is characterized by its duty cycle α that indicates the fraction of the entire symbol duration the transmitter remains on and transmits the signal. Results show that the detection performance of an FP-PAM OOK CEMC system significantly depends on the statistical distribution parameters of diffusion-based propagation noise and intersymbol interference (ISI). Analytical detection performance of an FP-PAM OOK CEMC system under ISI scenario has been explained and compared based on receiver operating characteristics (ROC) for impulse (i.e., spike)-modulated (IM) and FP-PAM CEMC schemes. It is shown that the effects of diffusion noise and ISI on ROC can be explained separately based on their communication range-dependent statistics. With full duty cycle, an FP-PAM scheme provides significantly worse performance than an IM scheme. The paper also analyzes the performance of the system when duty cycle, transmission data rate, and quantity of molecules vary.

An Automatic Detection System of Lung Nodule Based on Multi-Group Patch-Based Deep Learning Network.

PubMed

Jiang, Hongyang; Ma, He; Qian, Wei; Gao, Mengdi; Li, Yan

2017-07-14

High-efficiency lung nodule detection dramatically contributes to the risk assessment of lung cancer. It is a significant and challenging task to quickly locate the exact positions of lung nodules. Extensive work has been done by researchers around this domain for approximately two decades. However, previous computer aided detection (CADe) schemes are mostly intricate and time-consuming since they may require more image processing modules, such as the computed tomography (CT) image transformation, the lung nodule segmentation and the feature extraction, to construct a whole CADe system. It is difficult for those schemes to process and analyze enormous data when the medical images continue to increase. Besides, some state of the art deep learning schemes may be strict in the standard of database. This study proposes an effective lung nodule detection scheme based on multi-group patches cut out from the lung images, which are enhanced by the Frangi filter. Through combining two groups of images, a four-channel convolution neural networks (CNN) model is designed to learn the knowledge of radiologists for detecting nodules of four levels. This CADe scheme can acquire the sensitivity of 80.06% with 4.7 false positives per scan and the sensitivity of 94% with 15.1 false positives per scan. The results demonstrate that the multi-group patch-based learning system is efficient to improve the performance of lung nodule detection and greatly reduce the false positives under a huge amount of image data.

Nuclear Explosion and Infrasound Event Resources of the SMDC Monitoring Research Program

DTIC Science & Technology

2008-09-01

2008 Monitoring Research Review: Ground-Based Nuclear Explosion Monitoring Technologies 928 Figure 7. Dozens of detected infrasound signals from...investigate alternative detection schemes at the two infrasound arrays based on frequency-wavenumber (fk) processing and the F-statistic. The results of... infrasound signal - detection processing schemes. REFERENCES Bahavar, M., B. Barker, J. Bennett, R. Bowman, H. Israelsson, B. Kohl, Y-L. Kung, J. Murphy

A fragile zero watermarking scheme to detect and characterize malicious modifications in database relations.

PubMed

Khan, Aihab; Husain, Syed Afaq

2013-01-01

We put forward a fragile zero watermarking scheme to detect and characterize malicious modifications made to a database relation. Most of the existing watermarking schemes for relational databases introduce intentional errors or permanent distortions as marks into the database original content. These distortions inevitably degrade the data quality and data usability as the integrity of a relational database is violated. Moreover, these fragile schemes can detect malicious data modifications but do not characterize the tempering attack, that is, the nature of tempering. The proposed fragile scheme is based on zero watermarking approach to detect malicious modifications made to a database relation. In zero watermarking, the watermark is generated (constructed) from the contents of the original data rather than introduction of permanent distortions as marks into the data. As a result, the proposed scheme is distortion-free; thus, it also resolves the inherent conflict between security and imperceptibility. The proposed scheme also characterizes the malicious data modifications to quantify the nature of tempering attacks. Experimental results show that even minor malicious modifications made to a database relation can be detected and characterized successfully.

Simplified Interval Observer Scheme: A New Approach for Fault Diagnosis in Instruments

PubMed Central

Martínez-Sibaja, Albino; Astorga-Zaragoza, Carlos M.; Alvarado-Lassman, Alejandro; Posada-Gómez, Rubén; Aguila-Rodríguez, Gerardo; Rodríguez-Jarquin, José P.; Adam-Medina, Manuel

2011-01-01

There are different schemes based on observers to detect and isolate faults in dynamic processes. In the case of fault diagnosis in instruments (FDI) there are different diagnosis schemes based on the number of observers: the Simplified Observer Scheme (SOS) only requires one observer, uses all the inputs and only one output, detecting faults in one detector; the Dedicated Observer Scheme (DOS), which again uses all the inputs and just one output, but this time there is a bank of observers capable of locating multiple faults in sensors, and the Generalized Observer Scheme (GOS) which involves a reduced bank of observers, where each observer uses all the inputs and m-1 outputs, and allows the localization of unique faults. This work proposes a new scheme named Simplified Interval Observer SIOS-FDI, which does not requires the measurement of any input and just with just one output allows the detection of unique faults in sensors and because it does not require any input, it simplifies in an important way the diagnosis of faults in processes in which it is difficult to measure all the inputs, as in the case of biologic reactors. PMID:22346593

Unsupervised iterative detection of land mines in highly cluttered environments.

PubMed

Batman, Sinan; Goutsias, John

2003-01-01

An unsupervised iterative scheme is proposed for land mine detection in heavily cluttered scenes. This scheme is based on iterating hybrid multispectral filters that consist of a decorrelating linear transform coupled with a nonlinear morphological detector. Detections extracted from the first pass are used to improve results in subsequent iterations. The procedure stops after a predetermined number of iterations. The proposed scheme addresses several weaknesses associated with previous adaptations of morphological approaches to land mine detection. Improvement in detection performance, robustness with respect to clutter inhomogeneities, a completely unsupervised operation, and computational efficiency are the main highlights of the method. Experimental results reveal excellent performance.

Improving the performance of lesion-based computer-aided detection schemes of breast masses using a case-based adaptive cueing method

NASA Astrophysics Data System (ADS)

Tan, Maxine; Aghaei, Faranak; Wang, Yunzhi; Qian, Wei; Zheng, Bin

2016-03-01

Current commercialized CAD schemes have high false-positive (FP) detection rates and also have high correlations in positive lesion detection with radiologists. Thus, we recently investigated a new approach to improve the efficacy of applying CAD to assist radiologists in reading and interpreting screening mammograms. Namely, we developed a new global feature based CAD approach/scheme that can cue the warning sign on the cases with high risk of being positive. In this study, we investigate the possibility of fusing global feature or case-based scores with the local or lesion-based CAD scores using an adaptive cueing method. We hypothesize that the information from the global feature extraction (features extracted from the whole breast regions) are different from and can provide supplementary information to the locally-extracted features (computed from the segmented lesion regions only). On a large and diverse full-field digital mammography (FFDM) testing dataset with 785 cases (347 negative and 438 cancer cases with masses only), we ran our lesion-based and case-based CAD schemes "as is" on the whole dataset. To assess the supplementary information provided by the global features, we used an adaptive cueing method to adaptively adjust the original CAD-generated detection scores (Sorg) of a detected suspicious mass region based on the computed case-based score (Scase) of the case associated with this detected region. Using the adaptive cueing method, better sensitivity results were obtained at lower FP rates (<= 1 FP per image). Namely, increases of sensitivities (in the FROC curves) of up to 6.7% and 8.2% were obtained for the ROI and Case-based results, respectively.

Design of fire detection equipment based on ultraviolet detection technology

NASA Astrophysics Data System (ADS)

Liu, Zhenji; Liu, Jin; Chu, Sheng; Ping, Chao; Yuan, Xiaobing

2015-03-01

Utilized the feature of wide bandgap semiconductor of MgZnO, researched and developed a kind of Mid-Ultraviolet-Band(MUV) ultraviolet detector which has passed the simulation experiment in the sun circumstance. Based on the ultraviolet detector, it gives out a design scheme of gun-shot detection device, which is composed of twelve ultraviolet detectors, signal amplifier, processor, annunciator , azimuth indicator and the bracket. Through Analysing the feature of solar blind, ultraviolet responsivity, fire feature of gunshots and detection distance, the feasibility of this design scheme is proved.

Atomic Interferometric Gravitational-Wave Space Observatory (AIGSO)

NASA Astrophysics Data System (ADS)

Gao, Dong-Feng; Wang, Jin; Zhan, Ming-Sheng

2018-01-01

We propose a space-borne gravitational-wave detection scheme, called atom interferometric gravitational-wave space observatory (AIGSO). It is motivated by the progress in the atomic matter-wave interferometry, which solely utilizes the standing light waves to split, deflect and recombine the atomic beam. Our scheme consists of three drag-free satellites orbiting the Earth. The phase shift of AIGSO is dominated by the Sagnac effect of gravitational-waves, which is proportional to the area enclosed by the atom interferometer, the frequency and amplitude of gravitational-waves. The scheme has a strain sensitivity < {10}-20/\\sqrt{{Hz}} in the 100 mHz-10 Hz frequency range, which fills in the detection gap between space-based and ground-based laser interferometric detectors. Thus, our proposed AIGSO can be a good complementary detection scheme to the space-borne laser interferometric schemes, such as LISA. Considering the current status of relevant technology readiness, we expect our AIGSO to be a promising candidate for the future space-based gravitational-wave detection plan. Supported by the National Key Research Program of China under Grant No. 2016YFA0302002, the National Science Foundation of China under Grant Nos. 11227803 and 91536221, and the Strategic Priority Research Program of the Chinese Academy of Sciences under Grant No. XDB21010100

Symbol Synchronization for Diffusion-Based Molecular Communications.

PubMed

Jamali, Vahid; Ahmadzadeh, Arman; Schober, Robert

2017-12-01

Symbol synchronization refers to the estimation of the start of a symbol interval and is needed for reliable detection. In this paper, we develop several symbol synchronization schemes for molecular communication (MC) systems where we consider some practical challenges, which have not been addressed in the literature yet. In particular, we take into account that in MC systems, the transmitter may not be equipped with an internal clock and may not be able to emit molecules with a fixed release frequency. Such restrictions hold for practical nanotransmitters, e.g., modified cells, where the lengths of the symbol intervals may vary due to the inherent randomness in the availability of food and energy for molecule generation, the process for molecule production, and the release process. To address this issue, we develop two synchronization-detection frameworks which both employ two types of molecule. In the first framework, one type of molecule is used for symbol synchronization and the other one is used for data detection, whereas in the second framework, both types of molecule are used for joint symbol synchronization and data detection. For both frameworks, we first derive the optimal maximum likelihood (ML) symbol synchronization schemes as performance upper bounds. Since ML synchronization entails high complexity, for each framework, we also propose three low-complexity suboptimal schemes, namely a linear filter-based scheme, a peak observation-based scheme, and a threshold-trigger scheme, which are suitable for MC systems with limited computational capabilities. Furthermore, we study the relative complexity and the constraints associated with the proposed schemes and the impact of the insertion and deletion errors that arise due to imperfect synchronization. Our simulation results reveal the effectiveness of the proposed synchronization schemes and suggest that the end-to-end performance of MC systems significantly depends on the accuracy of the symbol synchronization.

A two-stage spectrum sensing scheme based on energy detection and a novel multitaper method

NASA Astrophysics Data System (ADS)

Qi, Pei-Han; Li, Zan; Si, Jiang-Bo; Xiong, Tian-Yi

2015-04-01

Wideband spectrum sensing has drawn much attention in recent years since it provides more opportunities to the secondary users. However, wideband spectrum sensing requires a long time and a complex mechanism at the sensing terminal. A two-stage wideband spectrum sensing scheme is considered to proceed spectrum sensing with low time consumption and high performance to tackle this predicament. In this scheme, a novel multitaper spectrum sensing (MSS) method is proposed to mitigate the poor performance of energy detection (ED) in the low signal-to-noise ratio (SNR) region. The closed-form expression of the decision threshold is derived based on the Neyman-Pearson criterion and the probability of detection in the Rayleigh fading channel is analyzed. An optimization problem is formulated to maximize the probability of detection of the proposed two-stage scheme and the average sensing time of the two-stage scheme is analyzed. Numerical results validate the efficiency of MSS and show that the two-stage spectrum sensing scheme enjoys higher performance in the low SNR region and lower time cost in the high SNR region than the single-stage scheme. Project supported by the National Natural Science Foundation of China (Grant No. 61301179), the China Postdoctoral Science Foundation (Grant No. 2014M550479), and the Doctorial Programs Foundation of the Ministry of Education, China (Grant No. 20110203110011).

Protection of Renewable-dominated Microgrids: Challenges and Potential Solutions.

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

Elkhatib, Mohamed; Ellis, Abraham; Milan Biswal

keywords : Microgrid Protection, Impedance Relay, Signal Processing-based Fault Detec- tion, Networked Microgrids, Communication-Assisted Protection In this report we address the challenge of designing efficient protection system for inverter- dominated microgrids. These microgrids are characterised with limited fault current capacity as a result of current-limiting protection functions of inverters. Typically, inverters limit their fault contribution in sub-cycle time frame to as low as 1.1 per unit. As a result, overcurrent protection could fail completely to detect faults in inverter-dominated microgrids. As part of this project a detailed literature survey of existing and proposed microgrid protection schemes were conducted. The surveymore » concluded that there is a gap in the available microgrid protection methods. The only credible protection solution available in literature for low- fault inverter-dominated microgrids is the differential protection scheme which represents a robust transmission-grade protection solution but at a very high cost. Two non-overcurrent protection schemes were investigated as part of this project; impedance-based protection and transient-based protection. Impedance-based protection depends on monitoring impedance trajectories at feeder relays to detect faults. Two communication-based impedance-based protection schemes were developed. the first scheme utilizes directional elements and pilot signals to locate the fault. The second scheme depends on a Central Protection Unit that communicates with all feeder relays to locate the fault based on directional flags received from feeder relays. The later approach could potentially be adapted to protect networked microgrids and dynamic topology microgrids. Transient-based protection relies on analyzing high frequency transients to detect and locate faults. This approach is very promising but its implementation in the filed faces several challenges. For example, high frequency transients due to faults can be confused with transients due to other events such as capacitor switching. Additionally, while detecting faults by analyzing transients could be doable, locating faults based on analyzing transients is still an open question.« less

Antenna Allocation in MIMO Radar with Widely Separated Antennas for Multi-Target Detection

PubMed Central

Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

2014-01-01

In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes. PMID:25350505

Antenna allocation in MIMO radar with widely separated antennas for multi-target detection.

PubMed

Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

2014-10-27

In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes.

Bi-orthogonal Symbol Mapping and Detection in Optical CDMA Communication System

NASA Astrophysics Data System (ADS)

Liu, Maw-Yang

2017-12-01

In this paper, the bi-orthogonal symbol mapping and detection scheme is investigated in time-spreading wavelength-hopping optical CDMA communication system. The carrier-hopping prime code is exploited as signature sequence, whose put-of-phase autocorrelation is zero. Based on the orthogonality of carrier-hopping prime code, the equal weight orthogonal signaling scheme can be constructed, and the proposed scheme using bi-orthogonal symbol mapping and detection can be developed. The transmitted binary data bits are mapped into corresponding bi-orthogonal symbols, where the orthogonal matrix code and its complement are utilized. In the receiver, the received bi-orthogonal data symbol is fed into the maximum likelihood decoder for detection. Under such symbol mapping and detection, the proposed scheme can greatly enlarge the Euclidean distance; hence, the system performance can be drastically improved.

Train axle bearing fault detection using a feature selection scheme based multi-scale morphological filter

NASA Astrophysics Data System (ADS)

Li, Yifan; Liang, Xihui; Lin, Jianhui; Chen, Yuejian; Liu, Jianxin

2018-02-01

This paper presents a novel signal processing scheme, feature selection based multi-scale morphological filter (MMF), for train axle bearing fault detection. In this scheme, more than 30 feature indicators of vibration signals are calculated for axle bearings with different conditions and the features which can reflect fault characteristics more effectively and representatively are selected using the max-relevance and min-redundancy principle. Then, a filtering scale selection approach for MMF based on feature selection and grey relational analysis is proposed. The feature selection based MMF method is tested on diagnosis of artificially created damages of rolling bearings of railway trains. Experimental results show that the proposed method has a superior performance in extracting fault features of defective train axle bearings. In addition, comparisons are performed with the kurtosis criterion based MMF and the spectral kurtosis criterion based MMF. The proposed feature selection based MMF method outperforms these two methods in detection of train axle bearing faults.

An online outlier identification and removal scheme for improving fault detection performance.

PubMed

Ferdowsi, Hasan; Jagannathan, Sarangapani; Zawodniok, Maciej

2014-05-01

Measured data or states for a nonlinear dynamic system is usually contaminated by outliers. Identifying and removing outliers will make the data (or system states) more trustworthy and reliable since outliers in the measured data (or states) can cause missed or false alarms during fault diagnosis. In addition, faults can make the system states nonstationary needing a novel analytical model-based fault detection (FD) framework. In this paper, an online outlier identification and removal (OIR) scheme is proposed for a nonlinear dynamic system. Since the dynamics of the system can experience unknown changes due to faults, traditional observer-based techniques cannot be used to remove the outliers. The OIR scheme uses a neural network (NN) to estimate the actual system states from measured system states involving outliers. With this method, the outlier detection is performed online at each time instant by finding the difference between the estimated and the measured states and comparing its median with its standard deviation over a moving time window. The NN weight update law in OIR is designed such that the detected outliers will have no effect on the state estimation, which is subsequently used for model-based fault diagnosis. In addition, since the OIR estimator cannot distinguish between the faulty or healthy operating conditions, a separate model-based observer is designed for fault diagnosis, which uses the OIR scheme as a preprocessing unit to improve the FD performance. The stability analysis of both OIR and fault diagnosis schemes are introduced. Finally, a three-tank benchmarking system and a simple linear system are used to verify the proposed scheme in simulations, and then the scheme is applied on an axial piston pump testbed. The scheme can be applied to nonlinear systems whose dynamics and underlying distribution of states are subjected to change due to both unknown faults and operating conditions.

Quantum cryptography using single-particle entanglement

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

Lee, Jae-Weon; Lee, Eok Kyun; Chung, Yong Wook

2003-07-01

A quantum cryptography scheme based on entanglement between a single-particle state and a vacuum state is proposed. The scheme utilizes linear optics devices to detect the superposition of the vacuum and single-particle states. Existence of an eavesdropper can be detected by using a variant of Bell's inequality.

Protection of Renewable-dominated Microgrids: Challenges and Potential Solutions

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

Elkhatib, Mohamed; Ellis, Abraham; Biswal, Milan

In this report we address the challenge of designing efficient protection system for inverter- dominated microgrids. These microgrids are characterised with limited fault current capacity as a result of current-limiting protection functions of inverters. Typically, inverters limit their fault contribution in sub-cycle time frame to as low as 1.1 per unit. As a result, overcurrent protection could fail completely to detect faults in inverter-dominated microgrids. As part of this project a detailed literature survey of existing and proposed microgrid protection schemes were conducted. The survey concluded that there is a gap in the available microgrid protection methods. The only crediblemore » protection solution available in literature for low- fault inverter-dominated microgrids is the differential protection scheme which represents a robust transmission-grade protection solution but at a very high cost. Two non-overcurrent protection schemes were investigated as part of this project; impedance-based protection and transient-based protection. Impedance-based protection depends on monitoring impedance trajectories at feeder relays to detect faults. Two communication-based impedance-based protection schemes were developed. the first scheme utilizes directional elements and pilot signals to locate the fault. The second scheme depends on a Central Protection Unit that communicates with all feeder relays to locate the fault based on directional flags received from feeder relays. The later approach could potentially be adapted to protect networked microgrids and dynamic topology microgrids. Transient-based protection relies on analyzing high frequency transients to detect and locate faults. This approach is very promising but its implementation in the filed faces several challenges. For example, high frequency transients due to faults can be confused with transients due to other events such as capacitor switching. Additionally, while detecting faults by analyzing transients could be doable, locating faults based on analyzing transients is still an open question.« less

Detection scheme for a partially occluded pedestrian based on occluded depth in lidar-radar sensor fusion

NASA Astrophysics Data System (ADS)

Kwon, Seong Kyung; Hyun, Eugin; Lee, Jin-Hee; Lee, Jonghun; Son, Sang Hyuk

2017-11-01

Object detections are critical technologies for the safety of pedestrians and drivers in autonomous vehicles. Above all, occluded pedestrian detection is still a challenging topic. We propose a new detection scheme for occluded pedestrian detection by means of lidar-radar sensor fusion. In the proposed method, the lidar and radar regions of interest (RoIs) have been selected based on the respective sensor measurement. Occluded depth is a new means to determine whether an occluded target exists or not. The occluded depth is a region projected out by expanding the longitudinal distance with maintaining the angle formed by the outermost two end points of the lidar RoI. The occlusion RoI is the overlapped region made by superimposing the radar RoI and the occluded depth. The object within the occlusion RoI is detected by the radar measurement information and the occluded object is estimated as a pedestrian based on human Doppler distribution. Additionally, various experiments are performed in detecting a partially occluded pedestrian in outdoor as well as indoor environments. According to experimental results, the proposed sensor fusion scheme has much better detection performance compared to the case without our proposed method.

Privacy-Aware Image Encryption Based on Logistic Map and Data Hiding

NASA Astrophysics Data System (ADS)

Sun, Jianglin; Liao, Xiaofeng; Chen, Xin; Guo, Shangwei

The increasing need for image communication and storage has created a great necessity for securely transforming and storing images over a network. Whereas traditional image encryption algorithms usually consider the security of the whole plain image, region of interest (ROI) encryption schemes, which are of great importance in practical applications, protect the privacy regions of plain images. Existing ROI encryption schemes usually adopt approximate techniques to detect the privacy region and measure the quality of encrypted images; however, their performance is usually inconsistent with a human visual system (HVS) and is sensitive to statistical attacks. In this paper, we propose a novel privacy-aware ROI image encryption (PRIE) scheme based on logistical mapping and data hiding. The proposed scheme utilizes salient object detection to automatically, adaptively and accurately detect the privacy region of a given plain image. After private pixels have been encrypted using chaotic cryptography, the significant bits are embedded into the nonprivacy region of the plain image using data hiding. Extensive experiments are conducted to illustrate the consistency between our automatic ROI detection and HVS. Our experimental results also demonstrate that the proposed scheme exhibits satisfactory security performance.

Adaptive Numerical Dissipative Control in High Order Schemes for Multi-D Non-Ideal MHD

NASA Technical Reports Server (NTRS)

Yee, H. C.; Sjoegreen, B.

2004-01-01

The goal is to extend our adaptive numerical dissipation control in high order filter schemes and our new divergence-free methods for ideal MHD to non-ideal MHD that include viscosity and resistivity. The key idea consists of automatic detection of different flow features as distinct sensors to signal the appropriate type and amount of numerical dissipation/filter where needed and leave the rest of the region free of numerical dissipation contamination. These scheme-independent detectors are capable of distinguishing shocks/shears, flame sheets, turbulent fluctuations and spurious high-frequency oscillations. The detection algorithm is based on an artificial compression method (ACM) (for shocks/shears), and redundant multi-resolution wavelets (WAV) (for the above types of flow feature). These filter approaches also provide a natural and efficient way for the minimization of Div(B) numerical error. The filter scheme consists of spatially sixth order or higher non-dissipative spatial difference operators as the base scheme for the inviscid flux derivatives. If necessary, a small amount of high order linear dissipation is used to remove spurious high frequency oscillations. For example, an eighth-order centered linear dissipation (AD8) might be included in conjunction with a spatially sixth-order base scheme. The inviscid difference operator is applied twice for the viscous flux derivatives. After the completion of a full time step of the base scheme step, the solution is adaptively filtered by the product of a 'flow detector' and the 'nonlinear dissipative portion' of a high-resolution shock-capturing scheme. In addition, the scheme independent wavelet flow detector can be used in conjunction with spatially compact, spectral or spectral element type of base schemes. The ACM and wavelet filter schemes using the dissipative portion of a second-order shock-capturing scheme with sixth-order spatial central base scheme for both the inviscid and viscous MHD flux derivatives and a fourth-order Runge-Kutta method are denoted.

Indoor Trajectory Tracking Scheme Based on Delaunay Triangulation and Heuristic Information in Wireless Sensor Networks.

PubMed

Qin, Junping; Sun, Shiwen; Deng, Qingxu; Liu, Limin; Tian, Yonghong

2017-06-02

Object tracking and detection is one of the most significant research areas for wireless sensor networks. Existing indoor trajectory tracking schemes in wireless sensor networks are based on continuous localization and moving object data mining. Indoor trajectory tracking based on the received signal strength indicator ( RSSI ) has received increased attention because it has low cost and requires no special infrastructure. However, RSSI tracking introduces uncertainty because of the inaccuracies of measurement instruments and the irregularities (unstable, multipath, diffraction) of wireless signal transmissions in indoor environments. Heuristic information includes some key factors for trajectory tracking procedures. This paper proposes a novel trajectory tracking scheme based on Delaunay triangulation and heuristic information (TTDH). In this scheme, the entire field is divided into a series of triangular regions. The common side of adjacent triangular regions is regarded as a regional boundary. Our scheme detects heuristic information related to a moving object's trajectory, including boundaries and triangular regions. Then, the trajectory is formed by means of a dynamic time-warping position-fingerprint-matching algorithm with heuristic information constraints. Field experiments show that the average error distance of our scheme is less than 1.5 m, and that error does not accumulate among the regions.

A study of malware detection on smart mobile devices

NASA Astrophysics Data System (ADS)

Yu, Wei; Zhang, Hanlin; Xu, Guobin

2013-05-01

The growing in use of smart mobile devices for everyday applications has stimulated the spread of mobile malware, especially on popular mobile platforms. As a consequence, malware detection becomes ever more critical in sustaining the mobile market and providing a better user experience. In this paper, we review the existing malware and detection schemes. Using real-world malware samples with known signatures, we evaluate four popular commercial anti-virus tools and our data shows that these tools can achieve high detection accuracy. To deal with the new malware with unknown signatures, we study the anomaly based detection using decision tree algorithm. We evaluate the effectiveness of our detection scheme using malware and legitimate software samples. Our data shows that the detection scheme using decision tree can achieve a detection rate up to 90% and a false positive rate as low as 10%.

A kernel-based novelty detection scheme for the ultra-fast detection of chirp evoked Auditory Brainstem Responses.

PubMed

Corona-Strauss, Farah I; Delb, Wolfgang; Schick, Bernhard; Strauss, Daniel J

2010-01-01

Auditory Brainstem Responses (ABRs) are used as objective method for diagnostics and quantification of hearing loss. Many methods for automatic recognition of ABRs have been developed, but none of them include the individual measurement setup in the analysis. The purpose of this work was to design a fast recognition scheme for chirp-evoked ABRs that is adjusted to the individual measurement condition using spontaneous electroencephalographic activity (SA). For the classification, the kernel-based novelty detection scheme used features based on the inter-sweep instantaneous phase synchronization as well as energy and entropy relations in the time-frequency domain. This method provided SA discrimination from stimulations above the hearing threshold with a minimum number of sweeps, i.e., 200 individual responses. It is concluded that the proposed paradigm, processing procedures and stimulation techniques improve the detection of ABRs in terms of the degree of objectivity, i.e., automation of procedure, and measurement time.

Evaluation of selective control information detection scheme in orthogonal frequency division multiplexing-based radio-over-fiber and visible light communication links

NASA Astrophysics Data System (ADS)

Dalarmelina, Carlos A.; Adegbite, Saheed A.; Pereira, Esequiel da V.; Nunes, Reginaldo B.; Rocha, Helder R. O.; Segatto, Marcelo E. V.; Silva, Jair A. L.

2017-05-01

Block-level detection is required to decode what may be classified as selective control information (SCI) such as control format indicator in 4G-long-term evolution systems. Using optical orthogonal frequency division multiplexing over radio-over-fiber (RoF) links, we report the experimental evaluation of an SCI detection scheme based on a time-domain correlation (TDC) technique in comparison with the conventional maximum likelihood (ML) approach. When compared with the ML method, it is shown that the TDC method improves detection performance over both 20 and 40 km of standard single mode fiber (SSMF) links. We also report a performance analysis of the TDC scheme in noisy visible light communication channel models after propagation through 40 km of SSMF. Experimental and simulation results confirm that the TDC method is attractive for practical orthogonal frequency division multiplexing-based RoF and fiber-wireless systems. Unlike the ML method, another key benefit of the TDC is that it requires no channel estimation.

Wavelet Based Protection Scheme for Multi Terminal Transmission System with PV and Wind Generation

NASA Astrophysics Data System (ADS)

Manju Sree, Y.; Goli, Ravi kumar; Ramaiah, V.

2017-08-01

A hybrid generation is a part of large power system in which number of sources usually attached to a power electronic converter and loads are clustered can operate independent of the main power system. The protection scheme is crucial against faults based on traditional over current protection since there are adequate problems due to fault currents in the mode of operation. This paper adopts a new approach for detection, discrimination of the faults for multi terminal transmission line protection in presence of hybrid generation. Transient current based protection scheme is developed with discrete wavelet transform. Fault indices of all phase currents at all terminals are obtained by analyzing the detail coefficients of current signals using bior 1.5 mother wavelet. This scheme is tested for different types of faults and is found effective for detection and discrimination of fault with various fault inception angle and fault impedance.

Wavelet Representation of the Corneal Pulse for Detecting Ocular Dicrotism

PubMed Central

Melcer, Tomasz; Danielewska, Monika E.; Iskander, D. Robert

2015-01-01

Purpose To develop a reliable and powerful method for detecting the ocular dicrotism from non-invasively acquired signals of corneal pulse without the knowledge of the underlying cardiopulmonary information present in signals of ocular blood pulse and the electrical heart activity. Methods Retrospective data from a study on glaucomatous and age-related changes in corneal pulsation [PLOS ONE 9(7),(2014):e102814] involving 261 subjects was used. Continuous wavelet representation of the signal derivative of the corneal pulse was considered with a complex Gaussian derivative function chosen as mother wavelet. Gray-level Co-occurrence Matrix has been applied to the image (heat-maps) of CWT to yield a set of parameters that can be used to devise the ocular dicrotic pulse detection schemes based on the Conditional Inference Tree and the Random Forest models. The detection scheme was first tested on synthetic signals resembling those of a dicrotic and a non-dicrotic ocular pulse before being used on all 261 real recordings. Results A detection scheme based on a single feature of the Continuous Wavelet Transform of the corneal pulse signal resulted in a low detection rate. Conglomeration of a set of features based on measures of texture (homogeneity, correlation, energy, and contrast) resulted in a high detection rate reaching 93%. Conclusion It is possible to reliably detect a dicrotic ocular pulse from the signals of corneal pulsation without the need of acquiring additional signals related to heart activity, which was the previous state-of-the-art. The proposed scheme can be applied to other non-stationary biomedical signals related to ocular dynamics. PMID:25906236

Fault Analysis and Detection in Microgrids with High PV Penetration

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

El Khatib, Mohamed; Hernandez Alvidrez, Javier; Ellis, Abraham

In this report we focus on analyzing current-controlled PV inverters behaviour under faults in order to develop fault detection schemes for microgrids with high PV penetration. Inverter model suitable for steady state fault studies is presented and the impact of PV inverters on two protection elements is analyzed. The studied protection elements are superimposed quantities based directional element and negative sequence directional element. Additionally, several non-overcurrent fault detection schemes are discussed in this report for microgrids with high PV penetration. A detailed time-domain simulation study is presented to assess the performance of the presented fault detection schemes under different microgridmore » modes of operation.« less

Portable Nanoparticle-Based Sensors for Food Safety Assessment

PubMed Central

Bülbül, Gonca; Hayat, Akhtar; Andreescu, Silvana

2015-01-01

The use of nanotechnology-derived products in the development of sensors and analytical measurement methodologies has increased significantly over the past decade. Nano-based sensing approaches include the use of nanoparticles (NPs) and nanostructures to enhance sensitivity and selectivity, design new detection schemes, improve sample preparation and increase portability. This review summarizes recent advancements in the design and development of NP-based sensors for assessing food safety. The most common types of NPs used to fabricate sensors for detection of food contaminants are discussed. Selected examples of NP-based detection schemes with colorimetric and electrochemical detection are provided with focus on sensors for the detection of chemical and biological contaminants including pesticides, heavy metals, bacterial pathogens and natural toxins. Current trends in the development of low-cost portable NP-based technology for rapid assessment of food safety as well as challenges for practical implementation and future research directions are discussed. PMID:26690169

Applying a 2D based CAD scheme for detecting micro-calcification clusters using digital breast tomosynthesis images: an assessment

NASA Astrophysics Data System (ADS)

Park, Sang Cheol; Zheng, Bin; Wang, Xiao-Hui; Gur, David

2008-03-01

Digital breast tomosynthesis (DBT) has emerged as a promising imaging modality for screening mammography. However, visually detecting micro-calcification clusters depicted on DBT images is a difficult task. Computer-aided detection (CAD) schemes for detecting micro-calcification clusters depicted on mammograms can achieve high performance and the use of CAD results can assist radiologists in detecting subtle micro-calcification clusters. In this study, we compared the performance of an available 2D based CAD scheme with one that includes a new grouping and scoring method when applied to both projection and reconstructed DBT images. We selected a dataset involving 96 DBT examinations acquired on 45 women. Each DBT image set included 11 low dose projection images and a varying number of reconstructed image slices ranging from 18 to 87. In this dataset 20 true-positive micro-calcification clusters were visually detected on the projection images and 40 were visually detected on the reconstructed images, respectively. We first applied the CAD scheme that was previously developed in our laboratory to the DBT dataset. We then tested a new grouping method that defines an independent cluster by grouping the same cluster detected on different projection or reconstructed images. We then compared four scoring methods to assess the CAD performance. The maximum sensitivity level observed for the different grouping and scoring methods were 70% and 88% for the projection and reconstructed images with a maximum false-positive rate of 4.0 and 15.9 per examination, respectively. This preliminary study demonstrates that (1) among the maximum, the minimum or the average CAD generated scores, using the maximum score of the grouped cluster regions achieved the highest performance level, (2) the histogram based scoring method is reasonably effective in reducing false-positive detections on the projection images but the overall CAD sensitivity is lower due to lower signal-to-noise ratio, and (3) CAD achieved higher sensitivity and higher false-positive rate (per examination) on the reconstructed images. We concluded that without changing the detection threshold or performing pre-filtering to possibly increase detection sensitivity, current CAD schemes developed and optimized for 2D mammograms perform relatively poorly and need to be re-optimized using DBT datasets and new grouping and scoring methods need to be incorporated into the schemes if these are to be used on the DBT examinations.

Detection and identification of concealed weapons using matrix pencil

NASA Astrophysics Data System (ADS)

Adve, Raviraj S.; Thayaparan, Thayananthan

2011-06-01

The detection and identification of concealed weapons is an extremely hard problem due to the weak signature of the target buried within the much stronger signal from the human body. This paper furthers the automatic detection and identification of concealed weapons by proposing the use of an effective approach to obtain the resonant frequencies in a measurement. The technique, based on Matrix Pencil, a scheme for model based parameter estimation also provides amplitude information, hence providing a level of confidence in the results. Of specific interest is the fact that Matrix Pencil is based on a singular value decomposition, making the scheme robust against noise.

Computer-Aided Diagnostic (CAD) Scheme by Use of Contralateral Subtraction Technique

NASA Astrophysics Data System (ADS)

Nagashima, Hiroyuki; Harakawa, Tetsumi

We developed a computer-aided diagnostic (CAD) scheme for detection of subtle image findings of acute cerebral infarction in brain computed tomography (CT) by using a contralateral subtraction technique. In our computerized scheme, the lateral inclination of image was first corrected automatically by rotating and shifting. The contralateral subtraction image was then derived by subtraction of reversed image from original image. Initial candidates for acute cerebral infarctions were identified using the multiple-thresholding and image filtering techniques. As the 1st step for removing false positive candidates, fourteen image features were extracted in each of the initial candidates. Halfway candidates were detected by applying the rule-based test with these image features. At the 2nd step, five image features were extracted using the overlapping scale with halfway candidates in interest slice and upper/lower slice image. Finally, acute cerebral infarction candidates were detected by applying the rule-based test with five image features. The sensitivity in the detection for 74 training cases was 97.4% with 3.7 false positives per image. The performance of CAD scheme for 44 testing cases had an approximate result to training cases. Our CAD scheme using the contralateral subtraction technique can reveal suspected image findings of acute cerebral infarctions in CT images.

Detection scheme for acoustic quantum radiation in Bose-Einstein condensates.

PubMed

Schützhold, Ralf

2006-11-10

Based on doubly detuned Raman transitions between (meta)stable atomic or molecular states and recently developed atom counting techniques, a detection scheme for sound waves in dilute Bose-Einstein condensates is proposed whose accuracy might reach down to the level of a few or even single phonons. This scheme could open up a new range of applications including the experimental observation of quantum radiation phenomena such as the Hawking effect in sonic black-hole analogues or the acoustic analogue of cosmological particle creation.

Enhanced DNA Sensing via Catalytic Aggregation of Gold Nanoparticles

PubMed Central

Huttanus, Herbert M.; Graugnard, Elton; Yurke, Bernard; Knowlton, William B.; Kuang, Wan; Hughes, William L.; Lee, Jeunghoon

2014-01-01

A catalytic colorimetric detection scheme that incorporates a DNA-based hybridization chain reaction into gold nanoparticles was designed and tested. While direct aggregation forms an inter-particle linkage from only ones target DNA strand, the catalytic aggregation forms multiple linkages from a single target DNA strand. Gold nanoparticles were functionalized with thiol-modified DNA strands capable of undergoing hybridization chain reactions. The changes in their absorption spectra were measured at different times and target concentrations and compared against direct aggregation. Catalytic aggregation showed a multifold increase in sensitivity at low target concentrations when compared to direct aggregation. Gel electrophoresis was performed to compare DNA hybridization reactions in catalytic and direct aggregation schemes, and the product formation was confirmed in the catalytic aggregation scheme at low levels of target concentrations. The catalytic aggregation scheme also showed high target specificity. This application of a DNA reaction network to gold nanoparticle-based colorimetric detection enables highly-sensitive, field-deployable, colorimetric readout systems capable of detecting a variety of biomolecules. PMID:23891867

Mirror Birefringence in a Fabry-Perot Cavity and the Detection of Vacuum Birefringence in a Magnetic Field

NASA Technical Reports Server (NTRS)

Chui, T. C. P.; Shao, M.; Redding, D.; Gursel, Y.; Boden, A.

1995-01-01

We discuss the effect of mirror birefringence in two optical schemes designed to detect the quantum-electrodynamics (QED) predictions of vacuum birefringence under the influence of a strong magnetic field, B. Both schemes make use of a high finesse Fabry-Perot cavity (F-P) to increase the average path length of the light in the magnetic field. The first scheme, which we called the frequency scheme, is based on measurement of the beat frequency of two orthogonal polarized laser beams in the cavity. We show that mirror birefringence contributes to the detection uncertainties in first order, resulting in a high susceptibility to small thermal disturbances. We estimate that an unreasonably high thermal stability of 10-9 K is required to resolve the effect to 0.1%. In the second scheme, which we called the polarization rotation scheme, laser polarized at 45 relative to the B field is injected into the cavity.

Two-stage Keypoint Detection Scheme for Region Duplication Forgery Detection in Digital Images.

PubMed

Emam, Mahmoud; Han, Qi; Zhang, Hongli

2018-01-01

In digital image forensics, copy-move or region duplication forgery detection became a vital research topic recently. Most of the existing keypoint-based forgery detection methods fail to detect the forgery in the smooth regions, rather than its sensitivity to geometric changes. To solve these problems and detect points which cover all the regions, we proposed two steps for keypoint detection. First, we employed the scale-invariant feature operator to detect the spatially distributed keypoints from the textured regions. Second, the keypoints from the missing regions are detected using Harris corner detector with nonmaximal suppression to evenly distribute the detected keypoints. To improve the matching performance, local feature points are described using Multi-support Region Order-based Gradient Histogram descriptor. Based on precision-recall rates and commonly tested dataset, comprehensive performance evaluation is performed. The results demonstrated that the proposed scheme has better detection and robustness against some geometric transformation attacks compared with state-of-the-art methods. © 2017 American Academy of Forensic Sciences.

Development and evaluation of a computer-aided diagnostic scheme for lung nodule detection in chest radiographs by means of two-stage nodule enhancement with support vector classification

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

Chen Sheng; Suzuki, Kenji; MacMahon, Heber

2011-04-15

Purpose: To develop a computer-aided detection (CADe) scheme for nodules in chest radiographs (CXRs) with a high sensitivity and a low false-positive (FP) rate. Methods: The authors developed a CADe scheme consisting of five major steps, which were developed for improving the overall performance of CADe schemes. First, to segment the lung fields accurately, the authors developed a multisegment active shape model. Then, a two-stage nodule-enhancement technique was developed for improving the conspicuity of nodules. Initial nodule candidates were detected and segmented by using the clustering watershed algorithm. Thirty-one shape-, gray-level-, surface-, and gradient-based features were extracted from each segmentedmore » candidate for determining the feature space, including one of the new features based on the Canny edge detector to eliminate a major FP source caused by rib crossings. Finally, a nonlinear support vector machine (SVM) with a Gaussian kernel was employed for classification of the nodule candidates. Results: To evaluate and compare the scheme to other published CADe schemes, the authors used a publicly available database containing 140 nodules in 140 CXRs and 93 normal CXRs. The CADe scheme based on the SVM classifier achieved sensitivities of 78.6% (110/140) and 71.4% (100/140) with averages of 5.0 (1165/233) FPs/image and 2.0 (466/233) FPs/image, respectively, in a leave-one-out cross-validation test, whereas the CADe scheme based on a linear discriminant analysis classifier had a sensitivity of 60.7% (85/140) at an FP rate of 5.0 FPs/image. For nodules classified as ''very subtle'' and ''extremely subtle,'' a sensitivity of 57.1% (24/42) was achieved at an FP rate of 5.0 FPs/image. When the authors used a database developed at the University of Chicago, the sensitivities was 83.3% (40/48) and 77.1% (37/48) at an FP rate of 5.0 (240/48) FPs/image and 2.0 (96/48) FPs /image, respectively. Conclusions: These results compare favorably to those described for other commercial and noncommercial CADe nodule detection systems.« less

Secure Distributed Detection under Energy Constraint in IoT-Oriented Sensor Networks.

PubMed

Zhang, Guomei; Sun, Hao

2016-12-16

We study the secure distributed detection problems under energy constraint for IoT-oriented sensor networks. The conventional channel-aware encryption (CAE) is an efficient physical-layer secure distributed detection scheme in light of its energy efficiency, good scalability and robustness over diverse eavesdropping scenarios. However, in the CAE scheme, it remains an open problem of how to optimize the key thresholds for the estimated channel gain, which are used to determine the sensor's reporting action. Moreover, the CAE scheme does not jointly consider the accuracy of local detection results in determining whether to stay dormant for a sensor. To solve these problems, we first analyze the error probability and derive the optimal thresholds in the CAE scheme under a specified energy constraint. These results build a convenient mathematic framework for our further innovative design. Under this framework, we propose a hybrid secure distributed detection scheme. Our proposal can satisfy the energy constraint by keeping some sensors inactive according to the local detection confidence level, which is characterized by likelihood ratio. In the meanwhile, the security is guaranteed through randomly flipping the local decisions forwarded to the fusion center based on the channel amplitude. We further optimize the key parameters of our hybrid scheme, including two local decision thresholds and one channel comparison threshold. Performance evaluation results demonstrate that our hybrid scheme outperforms the CAE under stringent energy constraints, especially in the high signal-to-noise ratio scenario, while the security is still assured.

Secure Distributed Detection under Energy Constraint in IoT-Oriented Sensor Networks

PubMed Central

Zhang, Guomei; Sun, Hao

2016-01-01

We study the secure distributed detection problems under energy constraint for IoT-oriented sensor networks. The conventional channel-aware encryption (CAE) is an efficient physical-layer secure distributed detection scheme in light of its energy efficiency, good scalability and robustness over diverse eavesdropping scenarios. However, in the CAE scheme, it remains an open problem of how to optimize the key thresholds for the estimated channel gain, which are used to determine the sensor’s reporting action. Moreover, the CAE scheme does not jointly consider the accuracy of local detection results in determining whether to stay dormant for a sensor. To solve these problems, we first analyze the error probability and derive the optimal thresholds in the CAE scheme under a specified energy constraint. These results build a convenient mathematic framework for our further innovative design. Under this framework, we propose a hybrid secure distributed detection scheme. Our proposal can satisfy the energy constraint by keeping some sensors inactive according to the local detection confidence level, which is characterized by likelihood ratio. In the meanwhile, the security is guaranteed through randomly flipping the local decisions forwarded to the fusion center based on the channel amplitude. We further optimize the key parameters of our hybrid scheme, including two local decision thresholds and one channel comparison threshold. Performance evaluation results demonstrate that our hybrid scheme outperforms the CAE under stringent energy constraints, especially in the high signal-to-noise ratio scenario, while the security is still assured. PMID:27999282

Induction detection of concealed bulk banknotes

NASA Astrophysics Data System (ADS)

Fuller, Christopher; Chen, Antao

2012-06-01

The smuggling of bulk cash across borders is a serious issue that has increased in recent years. In an effort to curb the illegal transport of large numbers of paper bills, a detection scheme has been developed, based on the magnetic characteristics of bank notes. The results show that volumes of paper currency can be detected through common concealing materials such as plastics, cardboard, and fabrics making it a possible potential addition to border security methods. The detection scheme holds the potential of also reducing or eliminating false positives caused by metallic materials found in the vicinity, by observing the stark difference in received signals caused by metal and currency. The detection scheme holds the potential to detect for both the presence and number of concealed bulk notes, while maintaining the ability to reduce false positives caused by metal objects.

Oriented regions grouping based candidate proposal for infrared pedestrian detection

NASA Astrophysics Data System (ADS)

Wang, Jiangtao; Zhang, Jingai; Li, Huaijiang

2018-04-01

Effectively and accurately locating the positions of pedestrian candidates in image is a key task for the infrared pedestrian detection system. In this work, a novel similarity measuring metric is designed. Based on the selective search scheme, the developed similarity measuring metric is utilized to yield the possible locations for pedestrian candidate. Besides this, corresponding diversification strategies are also provided according to the characteristics of the infrared thermal imaging system. Experimental results indicate that the presented scheme can achieve more efficient outputs than the traditional selective search methodology for the infrared pedestrian detection task.

A symmetric metamaterial element-based RF biosensor for rapid and label-free detection

NASA Astrophysics Data System (ADS)

Lee, Hee-Jo; Lee, Jung-Hyun; Jung, Hyo-Il

2011-10-01

A symmetric metamaterial element-based RF biosensing scheme is experimentally demonstrated by detecting biomolecular binding between a prostate-specific antigen (PSA) and its antibody. The metamaterial element in a high-impedance microstrip line shows an intrinsic S21 resonance having a Q-factor of 55. The frequency shift with PSA concentration, i.e., 100 ng/ml, 10 ng/ml, and 1 ng/ml, is observed and the changes are Δf ≈ 20 MHz, 10 MHz, and 5 MHz, respectively. The proposed biosensor offers advantages of label-free detection, a simple and direct scheme, and cost-efficient fabrication.

Experimental quantum-cryptography scheme based on orthogonal states

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

Avella, Alessio; Brida, Giorgio; Degiovanni, Ivo Pietro

2010-12-15

Since, in general, nonorthogonal states cannot be cloned, any eavesdropping attempt in a quantum-communication scheme using nonorthogonal states as carriers of information introduces some errors in the transmission, leading to the possibility of detecting the spy. Usually, orthogonal states are not used in quantum-cryptography schemes since they can be faithfully cloned without altering the transmitted data. Nevertheless, L. Goldberg and L. Vaidman [Phys. Rev. Lett. 75, 1239 (1995)] proposed a protocol in which, even if the data exchange is realized using two orthogonal states, any attempt to eavesdrop is detectable by the legal users. In this scheme the orthogonal statesmore » are superpositions of two localized wave packets traveling along separate channels. Here we present an experiment realizing this scheme.« less

An Adaptive Ship Detection Scheme for Spaceborne SAR Imagery

PubMed Central

Leng, Xiangguang; Ji, Kefeng; Zhou, Shilin; Xing, Xiangwei; Zou, Huanxin

2016-01-01

With the rapid development of spaceborne synthetic aperture radar (SAR) and the increasing need of ship detection, research on adaptive ship detection in spaceborne SAR imagery is of great importance. Focusing on practical problems of ship detection, this paper presents a highly adaptive ship detection scheme for spaceborne SAR imagery. It is able to process a wide range of sensors, imaging modes and resolutions. Two main stages are identified in this paper, namely: ship candidate detection and ship discrimination. Firstly, this paper proposes an adaptive land masking method using ship size and pixel size. Secondly, taking into account the imaging mode, incidence angle, and polarization channel of SAR imagery, it implements adaptive ship candidate detection in spaceborne SAR imagery by applying different strategies to different resolution SAR images. Finally, aiming at different types of typical false alarms, this paper proposes a comprehensive ship discrimination method in spaceborne SAR imagery based on confidence level and complexity analysis. Experimental results based on RADARSAT-1, RADARSAT-2, TerraSAR-X, RS-1, and RS-3 images demonstrate that the adaptive scheme proposed in this paper is able to detect ship targets in a fast, efficient and robust way. PMID:27563902

Immunity-based detection, identification, and evaluation of aircraft sub-system failures

NASA Astrophysics Data System (ADS)

Moncayo, Hever Y.

This thesis describes the design, development, and flight-simulation testing of an integrated Artificial Immune System (AIS) for detection, identification, and evaluation of a wide variety of sensor, actuator, propulsion, and structural failures/damages including the prediction of the achievable states and other limitations on performance and handling qualities. The AIS scheme achieves high detection rate and low number of false alarms for all the failure categories considered. Data collected using a motion-based flight simulator are used to define the self for an extended sub-region of the flight envelope. The NASA IFCS F-15 research aircraft model is used and represents a supersonic fighter which include model following adaptive control laws based on non-linear dynamic inversion and artificial neural network augmentation. The flight simulation tests are designed to analyze and demonstrate the performance of the immunity-based aircraft failure detection, identification and evaluation (FDIE) scheme. A general robustness analysis is also presented by determining the achievable limits for a desired performance in the presence of atmospheric perturbations. For the purpose of this work, the integrated AIS scheme is implemented based on three main components. The first component performs the detection when one of the considered failures is present in the system. The second component consists in the identification of the failure category and the classification according to the failed element. During the third phase a general evaluation of the failure is performed with the estimation of the magnitude/severity of the failure and the prediction of its effect on reducing the flight envelope of the aircraft system. Solutions and alternatives to specific design issues of the AIS scheme, such as data clustering and empty space optimization, data fusion and duplication removal, definition of features, dimensionality reduction, and selection of cluster/detector shape are also analyzed in this thesis. They showed to have an important effect on detection performance and are a critical aspect when designing the configuration of the AIS. The results presented in this thesis show that the AIS paradigm addresses directly the complexity and multi-dimensionality associated with a damaged aircraft dynamic response and provides the tools necessary for a comprehensive/integrated solution to the FDIE problem. Excellent detection, identification, and evaluation performance has been recorded for all types of failures considered. The implementation of the proposed AIS-based scheme can potentially have a significant impact on the safety of aircraft operation. The output information obtained from the scheme will be useful to increase pilot situational awareness and determine automated compensation.

Detection of cat-eye effect echo based on unit APD

NASA Astrophysics Data System (ADS)

Wu, Dong-Sheng; Zhang, Peng; Hu, Wen-Gang; Ying, Jia-Ju; Liu, Jie

2016-10-01

The cat-eye effect echo of optical system can be detected based on CCD, but the detection range is limited within several kilometers. In order to achieve long-range even ultra-long-range detection, it ought to select APD as detector because of the high sensitivity of APD. The detection system of cat-eye effect echo based on unit APD is designed in paper. The implementation scheme and key technology of the detection system is presented. The detection performances of the detection system including detection range, detection probability and false alarm probability are modeled. Based on the model, the performances of the detection system are analyzed using typical parameters. The results of numerical calculation show that the echo signal-to-noise ratio is greater than six, the detection probability is greater than 99.9% and the false alarm probability is less tan 0.1% within 20 km detection range. In order to verify the detection effect, we built the experimental platform of detection system according to the design scheme and carry out the field experiments. The experimental results agree well with the results of numerical calculation, which prove that the detection system based on the unit APD is feasible to realize remote detection for cat-eye effect echo.

A new CAD approach for improving efficacy of cancer screening

NASA Astrophysics Data System (ADS)

Zheng, Bin; Qian, Wei; Li, Lihua; Pu, Jiantao; Kang, Yan; Lure, Fleming; Tan, Maxine; Qiu, Yuchen

2015-03-01

Since performance and clinical utility of current computer-aided detection (CAD) schemes of detecting and classifying soft tissue lesions (e.g., breast masses and lung nodules) is not satisfactory, many researchers in CAD field call for new CAD research ideas and approaches. The purpose of presenting this opinion paper is to share our vision and stimulate more discussions of how to overcome or compensate the limitation of current lesion-detection based CAD schemes in the CAD research community. Since based on our observation that analyzing global image information plays an important role in radiologists' decision making, we hypothesized that using the targeted quantitative image features computed from global images could also provide highly discriminatory power, which are supplementary to the lesion-based information. To test our hypothesis, we recently performed a number of independent studies. Based on our published preliminary study results, we demonstrated that global mammographic image features and background parenchymal enhancement of breast MR images carried useful information to (1) predict near-term breast cancer risk based on negative screening mammograms, (2) distinguish between true- and false-positive recalls in mammography screening examinations, and (3) classify between malignant and benign breast MR examinations. The global case-based CAD scheme only warns a risk level of the cases without cueing a large number of false-positive lesions. It can also be applied to guide lesion-based CAD cueing to reduce false-positives but enhance clinically relevant true-positive cueing. However, before such a new CAD approach is clinically acceptable, more work is needed to optimize not only the scheme performance but also how to integrate with lesion-based CAD schemes in the clinical practice.

A high-resolution and intelligent dead pixel detection scheme for an electrowetting display screen

NASA Astrophysics Data System (ADS)

Luo, ZhiJie; Luo, JianKun; Zhao, WenWen; Cao, Yang; Lin, WeiJie; Zhou, GuoFu

2018-02-01

Electrowetting display technology is realized by tuning the surface energy of a hydrophobic surface by applying a voltage based on electrowetting mechanism. With the rapid development of the electrowetting industry, how to analyze efficiently the quality of an electrowetting display screen has a very important significance. There are two kinds of dead pixels on the electrowetting display screen. One is that the oil of pixel cannot completely cover the display area. The other is that indium tin oxide semiconductor wire connecting pixel and foil was burned. In this paper, we propose a high-resolution and intelligent dead pixel detection scheme for an electrowetting display screen. First, we built an aperture ratio-capacitance model based on the electrical characteristics of electrowetting display. A field-programmable gate array is used as the integrated logic hub of the system for a highly reliable and efficient control of the circuit. Dead pixels can be detected and displayed on a PC-based 2D graphical interface in real time. The proposed dead pixel detection scheme reported in this work has promise in automating electrowetting display experiments.

Probabilistic evaluation of on-line checks in fault-tolerant multiprocessor systems

NASA Technical Reports Server (NTRS)

Nair, V. S. S.; Hoskote, Yatin V.; Abraham, Jacob A.

1992-01-01

The analysis of fault-tolerant multiprocessor systems that use concurrent error detection (CED) schemes is much more difficult than the analysis of conventional fault-tolerant architectures. Various analytical techniques have been proposed to evaluate CED schemes deterministically. However, these approaches are based on worst-case assumptions related to the failure of system components. Often, the evaluation results do not reflect the actual fault tolerance capabilities of the system. A probabilistic approach to evaluate the fault detecting and locating capabilities of on-line checks in a system is developed. The various probabilities associated with the checking schemes are identified and used in the framework of the matrix-based model. Based on these probabilistic matrices, estimates for the fault tolerance capabilities of various systems are derived analytically.

Fault Detection for Automotive Shock Absorber

NASA Astrophysics Data System (ADS)

Hernandez-Alcantara, Diana; Morales-Menendez, Ruben; Amezquita-Brooks, Luis

2015-11-01

Fault detection for automotive semi-active shock absorbers is a challenge due to the non-linear dynamics and the strong influence of the disturbances such as the road profile. First obstacle for this task, is the modeling of the fault, which has been shown to be of multiplicative nature. Many of the most widespread fault detection schemes consider additive faults. Two model-based fault algorithms for semiactive shock absorber are compared: an observer-based approach and a parameter identification approach. The performance of these schemes is validated and compared using a commercial vehicle model that was experimentally validated. Early results shows that a parameter identification approach is more accurate, whereas an observer-based approach is less sensible to parametric uncertainty.

Hierarchical scheme for detecting the rotating MIMO transmission of the in-door RGB-LED visible light wireless communications using mobile-phone camera

NASA Astrophysics Data System (ADS)

Chen, Shih-Hao; Chow, Chi-Wai

2015-01-01

Multiple-input and multiple-output (MIMO) scheme can extend the transmission capacity for the light-emitting-diode (LED) based visible light communication (VLC) systems. The MIMO VLC system that uses the mobile-phone camera as the optical receiver (Rx) to receive MIMO signal from the n×n Red-Green-Blue (RGB) LED array is desirable. The key step of decoding this signal is to detect the signal direction. If the LED transmitter (Tx) is rotated, the Rx may not realize the rotation and transmission error can occur. In this work, we propose and demonstrate a novel hierarchical transmission scheme which can reduce the computation complexity of rotation detection in LED array VLC system. We use the n×n RGB LED array as the MIMO Tx. In our study, a novel two dimensional Hadamard coding scheme is proposed. Using the different LED color layers to indicate the rotation, a low complexity rotation detection method can be used for improving the quality of received signal. The detection correction rate is above 95% in the indoor usage distance. Experimental results confirm the feasibility of the proposed scheme.

A joint asymmetric watermarking and image encryption scheme

NASA Astrophysics Data System (ADS)

Boato, G.; Conotter, V.; De Natale, F. G. B.; Fontanari, C.

2008-02-01

Here we introduce a novel watermarking paradigm designed to be both asymmetric, i.e., involving a private key for embedding and a public key for detection, and commutative with a suitable encryption scheme, allowing both to cipher watermarked data and to mark encrypted data without interphering with the detection process. In order to demonstrate the effectiveness of the above principles, we present an explicit example where the watermarking part, based on elementary linear algebra, and the encryption part, exploiting a secret random permutation, are integrated in a commutative scheme.

Hardware accelerator design for change detection in smart camera

NASA Astrophysics Data System (ADS)

Singh, Sanjay; Dunga, Srinivasa Murali; Saini, Ravi; Mandal, A. S.; Shekhar, Chandra; Chaudhury, Santanu; Vohra, Anil

2011-10-01

Smart Cameras are important components in Human Computer Interaction. In any remote surveillance scenario, smart cameras have to take intelligent decisions to select frames of significant changes to minimize communication and processing overhead. Among many of the algorithms for change detection, one based on clustering based scheme was proposed for smart camera systems. However, such an algorithm could achieve low frame rate far from real-time requirements on a general purpose processors (like PowerPC) available on FPGAs. This paper proposes the hardware accelerator capable of detecting real time changes in a scene, which uses clustering based change detection scheme. The system is designed and simulated using VHDL and implemented on Xilinx XUP Virtex-IIPro FPGA board. Resulted frame rate is 30 frames per second for QVGA resolution in gray scale.

An Enhanced Secure Identity-Based Certificateless Public Key Authentication Scheme for Vehicular Sensor Networks.

PubMed

Li, Congcong; Zhang, Xi; Wang, Haiping; Li, Dongfeng

2018-01-11

Vehicular sensor networks have been widely applied in intelligent traffic systems in recent years. Because of the specificity of vehicular sensor networks, they require an enhanced, secure and efficient authentication scheme. Existing authentication protocols are vulnerable to some problems, such as a high computational overhead with certificate distribution and revocation, strong reliance on tamper-proof devices, limited scalability when building many secure channels, and an inability to detect hardware tampering attacks. In this paper, an improved authentication scheme using certificateless public key cryptography is proposed to address these problems. A security analysis of our scheme shows that our protocol provides an enhanced secure anonymous authentication, which is resilient against major security threats. Furthermore, the proposed scheme reduces the incidence of node compromise and replication attacks. The scheme also provides a malicious-node detection and warning mechanism, which can quickly identify compromised static nodes and immediately alert the administrative department. With performance evaluations, the scheme can obtain better trade-offs between security and efficiency than the well-known available schemes.

A prototype of mammography CADx scheme integrated to imaging quality evaluation techniques

NASA Astrophysics Data System (ADS)

Schiabel, Homero; Matheus, Bruno R. N.; Angelo, Michele F.; Patrocínio, Ana Claudia; Ventura, Liliane

2011-03-01

As all women over the age of 40 are recommended to perform mammographic exams every two years, the demands on radiologists to evaluate mammographic images in short periods of time has increased considerably. As a tool to improve quality and accelerate analysis CADe/Dx (computer-aided detection/diagnosis) schemes have been investigated, but very few complete CADe/Dx schemes have been developed and most are restricted to detection and not diagnosis. The existent ones usually are associated to specific mammographic equipment (usually DR), which makes them very expensive. So this paper describes a prototype of a complete mammography CADx scheme developed by our research group integrated to an imaging quality evaluation process. The basic structure consists of pre-processing modules based on image acquisition and digitization procedures (FFDM, CR or film + scanner), a segmentation tool to detect clustered microcalcifications and suspect masses and a classification scheme, which evaluates as the presence of microcalcifications clusters as well as possible malignant masses based on their contour. The aim is to provide enough information not only on the detected structures but also a pre-report with a BI-RADS classification. At this time the system is still lacking an interface integrating all the modules. Despite this, it is functional as a prototype for clinical practice testing, with results comparable to others reported in literature.

Sensor Fault Detection and Diagnosis Simulation of a Helicopter Engine in an Intelligent Control Framework

NASA Technical Reports Server (NTRS)

Litt, Jonathan; Kurtkaya, Mehmet; Duyar, Ahmet

1994-01-01

This paper presents an application of a fault detection and diagnosis scheme for the sensor faults of a helicopter engine. The scheme utilizes a model-based approach with real time identification and hypothesis testing which can provide early detection, isolation, and diagnosis of failures. It is an integral part of a proposed intelligent control system with health monitoring capabilities. The intelligent control system will allow for accommodation of faults, reduce maintenance cost, and increase system availability. The scheme compares the measured outputs of the engine with the expected outputs of an engine whose sensor suite is functioning normally. If the differences between the real and expected outputs exceed threshold values, a fault is detected. The isolation of sensor failures is accomplished through a fault parameter isolation technique where parameters which model the faulty process are calculated on-line with a real-time multivariable parameter estimation algorithm. The fault parameters and their patterns can then be analyzed for diagnostic and accommodation purposes. The scheme is applied to the detection and diagnosis of sensor faults of a T700 turboshaft engine. Sensor failures are induced in a T700 nonlinear performance simulation and data obtained are used with the scheme to detect, isolate, and estimate the magnitude of the faults.

Intrusion-aware alert validation algorithm for cooperative distributed intrusion detection schemes of wireless sensor networks.

PubMed

Shaikh, Riaz Ahmed; Jameel, Hassan; d'Auriol, Brian J; Lee, Heejo; Lee, Sungyoung; Song, Young-Jae

2009-01-01

Existing anomaly and intrusion detection schemes of wireless sensor networks have mainly focused on the detection of intrusions. Once the intrusion is detected, an alerts or claims will be generated. However, any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in the existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at a modest communication cost. In this paper, we also provide a security resiliency analysis of the proposed intrusion-aware alert validation algorithm.

Intrusion-Aware Alert Validation Algorithm for Cooperative Distributed Intrusion Detection Schemes of Wireless Sensor Networks

PubMed Central

Shaikh, Riaz Ahmed; Jameel, Hassan; d’Auriol, Brian J.; Lee, Heejo; Lee, Sungyoung; Song, Young-Jae

2009-01-01

Existing anomaly and intrusion detection schemes of wireless sensor networks have mainly focused on the detection of intrusions. Once the intrusion is detected, an alerts or claims will be generated. However, any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in the existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at a modest communication cost. In this paper, we also provide a security resiliency analysis of the proposed intrusion-aware alert validation algorithm. PMID:22454568

Detection of Coccolithophore Blooms in Ocean Color Satellite Imagery: a Generalized Approach for Use with Multiple Sensors

NASA Technical Reports Server (NTRS)

Moore, Timothy; Dowell, Mark; Franz, Bryan A.

2012-01-01

A generalized coccolithophore bloom classifier has been developed for use with ocean color imagery. The bloom classifier was developed using extracted satellite reflectance data from SeaWiFS images screened by the default bloom detection mask. In the current application, we extend the optical water type (OWT) classification scheme by adding a new coccolithophore bloom class formed from these extracted reflectances. Based on an in situ coccolithophore data set from the North Atlantic, the detection levels with the new scheme were between 1,500 and 1,800 coccolithophore cellsmL and 43,000 and 78,000 lithsmL. The detected bloom area using the OWT method was an average of 1.75 times greater than the default bloom detector based on a collection of SeaWiFS 1 km imagery. The versatility of the scheme is shown with SeaWiFS, MODIS Aqua, CZCS and MERIS imagery at the 1 km scale. The OWT scheme was applied to the daily global SeaWiFS imagery mission data set (years 19972010). Based on our results, average annual coccolithophore bloom area was more than two times greater in the southern hemisphere compared to the northern hemi- sphere with values of 2.00 106 km2 and 0.75 106 km2, respectively. The new algorithm detects larger bloom areas in the Southern Ocean compared to the default algorithm, and our revised global annual average of 2.75106 km2 is dominated by contributions from the Southern Ocean.

Statistical process control based chart for information systems security

NASA Astrophysics Data System (ADS)

Khan, Mansoor S.; Cui, Lirong

2015-07-01

Intrusion detection systems have a highly significant role in securing computer networks and information systems. To assure the reliability and quality of computer networks and information systems, it is highly desirable to develop techniques that detect intrusions into information systems. We put forward the concept of statistical process control (SPC) in computer networks and information systems intrusions. In this article we propose exponentially weighted moving average (EWMA) type quality monitoring scheme. Our proposed scheme has only one parameter which differentiates it from the past versions. We construct the control limits for the proposed scheme and investigate their effectiveness. We provide an industrial example for the sake of clarity for practitioner. We give comparison of the proposed scheme with EWMA schemes and p chart; finally we provide some recommendations for the future work.

Experimental quantum-cryptography scheme based on orthogonal states

NASA Astrophysics Data System (ADS)

Avella, Alessio; Brida, Giorgio; Degiovanni, Ivo Pietro; Genovese, Marco; Gramegna, Marco; Traina, Paolo

2010-12-01

Since, in general, nonorthogonal states cannot be cloned, any eavesdropping attempt in a quantum-communication scheme using nonorthogonal states as carriers of information introduces some errors in the transmission, leading to the possibility of detecting the spy. Usually, orthogonal states are not used in quantum-cryptography schemes since they can be faithfully cloned without altering the transmitted data. Nevertheless, L. Goldberg and L. Vaidman [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.75.1239 75, 1239 (1995)] proposed a protocol in which, even if the data exchange is realized using two orthogonal states, any attempt to eavesdrop is detectable by the legal users. In this scheme the orthogonal states are superpositions of two localized wave packets traveling along separate channels. Here we present an experiment realizing this scheme.

Notes on two multiparty quantum secret sharing schemes

NASA Astrophysics Data System (ADS)

Gao, Gan

In the paper [H. Abulkasim et al., Int. J. Quantum Inform. 15 (2017) 1750023], Abulkasim et al. proposed a quantum secret sharing scheme based on Bell states. We study the security of the multiparty case in the proposed scheme and detect that it is not secure. In the paper [Y. Du and W. Bao, Opt. Commun. 308 (2013) 159], Du and Bao listed Gao’s scheme and gave a attack strategy on the listed scheme. We point out that their listing scheme is not the genuine Gao’s scheme and their research method is not advisable.

Reset Tree-Based Optical Fault Detection

PubMed Central

Lee, Dong-Geon; Choi, Dooho; Seo, Jungtaek; Kim, Howon

2013-01-01

In this paper, we present a new reset tree-based scheme to protect cryptographic hardware against optical fault injection attacks. As one of the most powerful invasive attacks on cryptographic hardware, optical fault attacks cause semiconductors to misbehave by injecting high-energy light into a decapped integrated circuit. The contaminated result from the affected chip is then used to reveal secret information, such as a key, from the cryptographic hardware. Since the advent of such attacks, various countermeasures have been proposed. Although most of these countermeasures are strong, there is still the possibility of attack. In this paper, we present a novel optical fault detection scheme that utilizes the buffers on a circuit's reset signal tree as a fault detection sensor. To evaluate our proposal, we model radiation-induced currents into circuit components and perform a SPICE simulation. The proposed scheme is expected to be used as a supplemental security tool. PMID:23698267

Implementation of a model based fault detection and diagnosis for actuation faults of the Space Shuttle main engine

NASA Technical Reports Server (NTRS)

Duyar, A.; Guo, T.-H.; Merrill, W.; Musgrave, J.

1992-01-01

In a previous study, Guo, Merrill and Duyar, 1990, reported a conceptual development of a fault detection and diagnosis system for actuation faults of the space shuttle main engine. This study, which is a continuation of the previous work, implements the developed fault detection and diagnosis scheme for the real time actuation fault diagnosis of the space shuttle main engine. The scheme will be used as an integral part of an intelligent control system demonstration experiment at NASA Lewis. The diagnosis system utilizes a model based method with real time identification and hypothesis testing for actuation, sensor, and performance degradation faults.

Correlation-based motion vector processing with adaptive interpolation scheme for motion-compensated frame interpolation.

PubMed

Huang, Ai-Mei; Nguyen, Truong

2009-04-01

In this paper, we address the problems of unreliable motion vectors that cause visual artifacts but cannot be detected by high residual energy or bidirectional prediction difference in motion-compensated frame interpolation. A correlation-based motion vector processing method is proposed to detect and correct those unreliable motion vectors by explicitly considering motion vector correlation in the motion vector reliability classification, motion vector correction, and frame interpolation stages. Since our method gradually corrects unreliable motion vectors based on their reliability, we can effectively discover the areas where no motion is reliable to be used, such as occlusions and deformed structures. We also propose an adaptive frame interpolation scheme for the occlusion areas based on the analysis of their surrounding motion distribution. As a result, the interpolated frames using the proposed scheme have clearer structure edges and ghost artifacts are also greatly reduced. Experimental results show that our interpolated results have better visual quality than other methods. In addition, the proposed scheme is robust even for those video sequences that contain multiple and fast motions.

Comparison of soft-input-soft-output detection methods for dual-polarized quadrature duobinary system

NASA Astrophysics Data System (ADS)

Chang, Chun; Huang, Benxiong; Xu, Zhengguang; Li, Bin; Zhao, Nan

2018-02-01

Three soft-input-soft-output (SISO) detection methods for dual-polarized quadrature duobinary (DP-QDB), including maximum-logarithmic-maximum-a-posteriori-probability-algorithm (Max-log-MAP)-based detection, soft-output-Viterbi-algorithm (SOVA)-based detection, and a proposed SISO detection, which can all be combined with SISO decoding, are presented. The three detection methods are investigated at 128 Gb/s in five-channel wavelength-division-multiplexing uncoded and low-density-parity-check (LDPC) coded DP-QDB systems by simulations. Max-log-MAP-based detection needs the returning-to-initial-states (RTIS) process despite having the best performance. When the LDPC code with a code rate of 0.83 is used, the detecting-and-decoding scheme with the SISO detection does not need RTIS and has better bit error rate (BER) performance than the scheme with SOVA-based detection. The former can reduce the optical signal-to-noise ratio (OSNR) requirement (at BER=10-5) by 2.56 dB relative to the latter. The application of the SISO iterative detection in LDPC-coded DP-QDB systems makes a good trade-off between requirements on transmission efficiency, OSNR requirement, and transmission distance, compared with the other two SISO methods.

Increasing sensitivity of pulse EPR experiments using echo train detection schemes.

PubMed

Mentink-Vigier, F; Collauto, A; Feintuch, A; Kaminker, I; Tarle, V; Goldfarb, D

2013-11-01

Modern pulse EPR experiments are routinely used to study the structural features of paramagnetic centers. They are usually performed at low temperatures, where relaxation times are long and polarization is high, to achieve a sufficient Signal/Noise Ratio (SNR). However, when working with samples whose amount and/or concentration are limited, sensitivity becomes an issue and therefore measurements may require a significant accumulation time, up to 12h or more. As the detection scheme of practically all pulse EPR sequences is based on the integration of a spin echo--either primary, stimulated or refocused--a considerable increase in SNR can be obtained by replacing the single echo detection scheme by a train of echoes. All these echoes, generated by Carr-Purcell type sequences, are integrated and summed together to improve the SNR. This scheme is commonly used in NMR and here we demonstrate its applicability to a number of frequently used pulse EPR experiments: Echo-Detected EPR, Davies and Mims ENDOR (Electron-Nuclear Double Resonance), DEER (Electron-Electron Double Resonance|) and EDNMR (Electron-Electron Double Resonance (ELDOR)-Detected NMR), which were combined with a Carr-Purcell-Meiboom-Gill (CPMG) type detection scheme at W-band. By collecting the transient signal and integrating a number of refocused echoes, this detection scheme yielded a 1.6-5 folds SNR improvement, depending on the paramagnetic center and the pulse sequence applied. This improvement is achieved while keeping the experimental time constant and it does not introduce signal distortion. Copyright © 2013 Elsevier Inc. All rights reserved.

Cryptanalysis of a semi-quantum secret sharing scheme based on Bell states

NASA Astrophysics Data System (ADS)

Gao, Gan; Wang, Yue; Wang, Dong

2018-03-01

In the paper [Mod. Phys. Lett. B 31 (2017) 1750150], Yin et al. proposed a semi-quantum secret sharing scheme by using Bell states. We find that the proposed scheme cannot finish the quantum secret sharing task. In addition, we also find that the proposed scheme has a security loophole, that is, it will not be detected that the dishonest participant, Charlie attacks on the quantum channel.

A computerized scheme for lung nodule detection in multiprojection chest radiography

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

Guo Wei; Li Qiang; Boyce, Sarah J.

2012-04-15

Purpose: Our previous study indicated that multiprojection chest radiography could significantly improve radiologists' performance for lung nodule detection in clinical practice. In this study, the authors further verify that multiprojection chest radiography can greatly improve the performance of a computer-aided diagnostic (CAD) scheme. Methods: Our database consisted of 59 subjects, including 43 subjects with 45 nodules and 16 subjects without nodules. The 45 nodules included 7 real and 38 simulated ones. The authors developed a conventional CAD scheme and a new fusion CAD scheme to detect lung nodules. The conventional CAD scheme consisted of four steps for (1) identification ofmore » initial nodule candidates inside lungs, (2) nodule candidate segmentation based on dynamic programming, (3) extraction of 33 features from nodule candidates, and (4) false positive reduction using a piecewise linear classifier. The conventional CAD scheme processed each of the three projection images of a subject independently and discarded the correlation information between the three images. The fusion CAD scheme included the four steps in the conventional CAD scheme and two additional steps for (5) registration of all candidates in the three images of a subject, and (6) integration of correlation information between the registered candidates in the three images. The integration step retained all candidates detected at least twice in the three images of a subject and removed those detected only once in the three images as false positives. A leave-one-subject-out testing method was used for evaluation of the performance levels of the two CAD schemes. Results: At the sensitivities of 70%, 65%, and 60%, our conventional CAD scheme reported 14.7, 11.3, and 8.6 false positives per image, respectively, whereas our fusion CAD scheme reported 3.9, 1.9, and 1.2 false positives per image, and 5.5, 2.8, and 1.7 false positives per patient, respectively. The low performance of the conventional CAD scheme may be attributed to the high noise level in chest radiography, and the small size and low contrast of most nodules. Conclusions: This study indicated that the fusion of correlation information in multiprojection chest radiography can markedly improve the performance of CAD scheme for lung nodule detection.« less

Trellis-coded CPM for satellite-based mobile communications

NASA Technical Reports Server (NTRS)

Abrishamkar, Farrokh; Biglieri, Ezio

1988-01-01

Digital transmission for satellite-based land mobile communications is discussed. To satisfy the power and bandwidth limitations imposed on such systems, a combination of trellis coding and continuous-phase modulated signals are considered. Some schemes based on this idea are presented, and their performance is analyzed by computer simulation. The results obtained show that a scheme based on directional detection and Viterbi decoding appears promising for practical applications.

Ppb-level mid-infrared ethane detection based on three measurement schemes using a 3.34-μm continuous-wave interband cascade laser

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

Li, Chunguang; Zheng, Chuantao; Dong, Lei

A ppb-level mid-infrared ethane (C 2H 6) sensor was developed using a continuous-wave, thermoelectrically cooled, distributed feedback interband cascade laser emitting at 3.34 μm and a miniature dense patterned multipass gas cell with a 54.6-m optical path length. The performance of the sensor was investigated using two different techniques based on the tunable interband cascade laser: direct absorption spectroscopy (DAS) and second-harmonic wavelength modulation spectroscopy (2f-WMS). Three measurement schemes, DAS, WMS and quasi-simultaneous DAS and WMS, were realized based on the same optical sensor core. A detection limit of ~7.92 ppbv with a precision of ±30 ppbv for the separatemore » DAS scheme with an averaging time of 1 s and a detection limit of ~1.19 ppbv with a precision of about ±4 ppbv for the separate WMS scheme with a 4-s averaging time were achieved. An Allan–Werle variance analysis indicated that the precisions can be further improved to 777 pptv @ 166 s for the separate DAS scheme and 269 pptv @ 108 s for the WMS scheme, respectively. For the quasi-simultaneous DAS and WMS scheme, both the 2f signal and the direct absorption signal were simultaneously extracted using a LabVIEW platform, and four C 2H 6 samples (0, 30, 60 and 90 ppbv with nitrogen as the balance gas) were used as the target gases to assess the sensor performance. A detailed comparison of the three measurement schemes is reported. Here, atmospheric C 2H 6 measurements on the Rice University campus and a field test at a compressed natural gas station in Houston, TX, were conducted to evaluate the performance of the sensor system as a robust and reliable field-deployable sensor system.« less

Ppb-level mid-infrared ethane detection based on three measurement schemes using a 3.34-μm continuous-wave interband cascade laser

DOE PAGES

Li, Chunguang; Zheng, Chuantao; Dong, Lei; ...

2016-06-20

A ppb-level mid-infrared ethane (C 2H 6) sensor was developed using a continuous-wave, thermoelectrically cooled, distributed feedback interband cascade laser emitting at 3.34 μm and a miniature dense patterned multipass gas cell with a 54.6-m optical path length. The performance of the sensor was investigated using two different techniques based on the tunable interband cascade laser: direct absorption spectroscopy (DAS) and second-harmonic wavelength modulation spectroscopy (2f-WMS). Three measurement schemes, DAS, WMS and quasi-simultaneous DAS and WMS, were realized based on the same optical sensor core. A detection limit of ~7.92 ppbv with a precision of ±30 ppbv for the separatemore » DAS scheme with an averaging time of 1 s and a detection limit of ~1.19 ppbv with a precision of about ±4 ppbv for the separate WMS scheme with a 4-s averaging time were achieved. An Allan–Werle variance analysis indicated that the precisions can be further improved to 777 pptv @ 166 s for the separate DAS scheme and 269 pptv @ 108 s for the WMS scheme, respectively. For the quasi-simultaneous DAS and WMS scheme, both the 2f signal and the direct absorption signal were simultaneously extracted using a LabVIEW platform, and four C 2H 6 samples (0, 30, 60 and 90 ppbv with nitrogen as the balance gas) were used as the target gases to assess the sensor performance. A detailed comparison of the three measurement schemes is reported. Here, atmospheric C 2H 6 measurements on the Rice University campus and a field test at a compressed natural gas station in Houston, TX, were conducted to evaluate the performance of the sensor system as a robust and reliable field-deployable sensor system.« less

Studies on Radar Sensor Networks

DTIC Science & Technology

2007-08-08

scheme in which 2-D image was created via adding voltages with the appropriate time offset. Simulation results show that our DCT-based scheme works...using RSNs in terms of the probability of miss detection PMD and the root mean square error (RMSE). Simulation results showed that multi-target detection... Simulation results are presented to evaluate the feasibility and effectiveness of the proposed JMIC algorithm in a query surveillance region. 5 SVD-QR and

A privacy preserving secure and efficient authentication scheme for telecare medical information systems.

PubMed

Mishra, Raghavendra; Barnwal, Amit Kumar

2015-05-01

The Telecare medical information system (TMIS) presents effective healthcare delivery services by employing information and communication technologies. The emerging privacy and security are always a matter of great concern in TMIS. Recently, Chen at al. presented a password based authentication schemes to address the privacy and security. Later on, it is proved insecure against various active and passive attacks. To erase the drawbacks of Chen et al.'s anonymous authentication scheme, several password based authentication schemes have been proposed using public key cryptosystem. However, most of them do not present pre-smart card authentication which leads to inefficient login and password change phases. To present an authentication scheme with pre-smart card authentication, we present an improved anonymous smart card based authentication scheme for TMIS. The proposed scheme protects user anonymity and satisfies all the desirable security attributes. Moreover, the proposed scheme presents efficient login and password change phases where incorrect input can be quickly detected and a user can freely change his password without server assistance. Moreover, we demonstrate the validity of the proposed scheme by utilizing the widely-accepted BAN (Burrows, Abadi, and Needham) logic. The proposed scheme is also comparable in terms of computational overheads with relevant schemes.

Robust Fault Detection and Isolation for Stochastic Systems

NASA Technical Reports Server (NTRS)

George, Jemin; Gregory, Irene M.

2010-01-01

This paper outlines the formulation of a robust fault detection and isolation scheme that can precisely detect and isolate simultaneous actuator and sensor faults for uncertain linear stochastic systems. The given robust fault detection scheme based on the discontinuous robust observer approach would be able to distinguish between model uncertainties and actuator failures and therefore eliminate the problem of false alarms. Since the proposed approach involves precise reconstruction of sensor faults, it can also be used for sensor fault identification and the reconstruction of true outputs from faulty sensor outputs. Simulation results presented here validate the effectiveness of the robust fault detection and isolation system.

Significance of MPEG-7 textural features for improved mass detection in mammography.

PubMed

Eltonsy, Nevine H; Tourassi, Georgia D; Fadeev, Aleksey; Elmaghraby, Adel S

2006-01-01

The purpose of the study is to investigate the significance of MPEG-7 textural features for improving the detection of masses in screening mammograms. The detection scheme was originally based on morphological directional neighborhood features extracted from mammographic regions of interest (ROIs). Receiver Operating Characteristics (ROC) was performed to evaluate the performance of each set of features independently and merged into a back-propagation artificial neural network (BPANN) using the leave-one-out sampling scheme (LOOSS). The study was based on a database of 668 mammographic ROIs (340 depicting cancer regions and 328 depicting normal parenchyma). Overall, the ROC area index of the BPANN using the directional morphological features was Az=0.85+/-0.01. The MPEG-7 edge histogram descriptor-based BPNN showed an ROC area index of Az=0.71+/-0.01 while homogeneous textural descriptors using 30 and 120 channels helped the BPNN achieve similar ROC area indexes of Az=0.882+/-0.02 and Az=0.877+/-0.01 respectively. After merging the MPEG-7 homogeneous textural features with the directional neighborhood features the performance of the BPANN increased providing an ROC area index of Az=0.91+/-0.01. MPEG-7 homogeneous textural descriptor significantly improved the morphology-based detection scheme.

Increasing cancer detection yield of breast MRI using a new CAD scheme of mammograms

NASA Astrophysics Data System (ADS)

Tan, Maxine; Aghaei, Faranak; Hollingsworth, Alan B.; Stough, Rebecca G.; Liu, Hong; Zheng, Bin

2016-03-01

Although breast MRI is the most sensitive imaging modality to detect early breast cancer, its cancer detection yield in breast cancer screening is quite low (< 3 to 4% even for the small group of high-risk women) to date. The purpose of this preliminary study is to test the potential of developing and applying a new computer-aided detection (CAD) scheme of digital mammograms to identify women at high risk of harboring mammography-occult breast cancers, which can be detected by breast MRI. For this purpose, we retrospectively assembled a dataset involving 30 women who had both mammography and breast MRI screening examinations. All mammograms were interpreted as negative, while 5 cancers were detected using breast MRI. We developed a CAD scheme of mammograms, which include a new quantitative mammographic image feature analysis based risk model, to stratify women into two groups with high and low risk of harboring mammography-occult cancer. Among 30 women, 9 were classified into the high risk group by CAD scheme, which included all 5 women who had cancer detected by breast MRI. All 21 low risk women remained negative on the breast MRI examinations. The cancer detection yield of breast MRI applying to this dataset substantially increased from 16.7% (5/30) to 55.6% (5/9), while eliminating 84% (21/25) unnecessary breast MRI screenings. The study demonstrated the potential of applying a new CAD scheme to significantly increase cancer detection yield of breast MRI, while simultaneously reducing the number of negative MRIs in breast cancer screening.

An Enhanced Secure Identity-Based Certificateless Public Key Authentication Scheme for Vehicular Sensor Networks

PubMed Central

Li, Congcong; Zhang, Xi; Wang, Haiping; Li, Dongfeng

2018-01-01

Vehicular sensor networks have been widely applied in intelligent traffic systems in recent years. Because of the specificity of vehicular sensor networks, they require an enhanced, secure and efficient authentication scheme. Existing authentication protocols are vulnerable to some problems, such as a high computational overhead with certificate distribution and revocation, strong reliance on tamper-proof devices, limited scalability when building many secure channels, and an inability to detect hardware tampering attacks. In this paper, an improved authentication scheme using certificateless public key cryptography is proposed to address these problems. A security analysis of our scheme shows that our protocol provides an enhanced secure anonymous authentication, which is resilient against major security threats. Furthermore, the proposed scheme reduces the incidence of node compromise and replication attacks. The scheme also provides a malicious-node detection and warning mechanism, which can quickly identify compromised static nodes and immediately alert the administrative department. With performance evaluations, the scheme can obtain better trade-offs between security and efficiency than the well-known available schemes. PMID:29324719

A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images

PubMed Central

Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

2016-01-01

A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles’ in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians. PMID:27548179

A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images.

PubMed

Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

2016-08-19

A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles' in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians.

Development of a fully automatic scheme for detection of masses in whole breast ultrasound images.

PubMed

Ikedo, Yuji; Fukuoka, Daisuke; Hara, Takeshi; Fujita, Hiroshi; Takada, Etsuo; Endo, Tokiko; Morita, Takako

2007-11-01

Ultrasonography has been used for breast cancer screening in Japan. Screening using a conventional hand-held probe is operator dependent and thus it is possible that some areas of the breast may not be scanned. To overcome such problems, a mechanical whole breast ultrasound (US) scanner has been proposed and developed for screening purposes. However, another issue is that radiologists might tire while interpreting all images in a large-volume screening; this increases the likelihood that masses may remain undetected. Therefore, the aim of this study is to develop a fully automatic scheme for the detection of masses in whole breast US images in order to assist the interpretations of radiologists and potentially improve the screening accuracy. The authors database comprised 109 whole breast US imagoes, which include 36 masses (16 malignant masses, 5 fibroadenomas, and 15 cysts). A whole breast US image with 84 slice images (interval between two slice images: 2 mm) was obtained by the ASU-1004 US scanner (ALOKA Co., Ltd., Japan). The feature based on the edge directions in each slice and a method for subtracting between the slice images were used for the detection of masses in the authors proposed scheme. The Canny edge detector was applied to detect edges in US images; these edges were classified as near-vertical edges or near-horizontal edges using a morphological method. The positions of mass candidates were located using the near-vertical edges as a cue. Then, the located positions were segmented by the watershed algorithm and mass candidate regions were detected using the segmented regions and the low-density regions extracted by the slice subtraction method. For the removal of false positives (FPs), rule-based schemes and a quadratic discriminant analysis were applied for the distribution between masses and FPs. As a result, the sensitivity of the authors scheme for the detection of masses was 80.6% (29/36) with 3.8 FPs per whole breast image. The authors scheme for a computer-aided detection may be useful in improving the screening performance and efficiency.

Expert systems for automated maintenance of a Mars oxygen production system

NASA Technical Reports Server (NTRS)

Ash, Robert L.; Huang, Jen-Kuang; Ho, Ming-Tsang

1989-01-01

A prototype expert system was developed for maintaining autonomous operation of a Mars oxygen production system. Normal operation conditions and failure modes according to certain desired criteria are tested and identified. Several schemes for failure detection and isolation using forward chaining, backward chaining, knowledge-based and rule-based are devised to perform several housekeeping functions. These functions include self-health checkout, an emergency shut down program, fault detection and conventional control activities. An effort was made to derive the dynamic model of the system using Bond-Graph technique in order to develop the model-based failure detection and isolation scheme by estimation method. Finally, computer simulations and experimental results demonstrated the feasibility of the expert system and a preliminary reliability analysis for the oxygen production system is also provided.

Blurry-frame detection and shot segmentation in colonoscopy videos

NASA Astrophysics Data System (ADS)

Oh, JungHwan; Hwang, Sae; Tavanapong, Wallapak; de Groen, Piet C.; Wong, Johnny

2003-12-01

Colonoscopy is an important screening procedure for colorectal cancer. During this procedure, the endoscopist visually inspects the colon. Human inspection, however, is not without error. We hypothesize that colonoscopy videos may contain additional valuable information missed by the endoscopist. Video segmentation is the first necessary step for the content-based video analysis and retrieval to provide efficient access to the important images and video segments from a large colonoscopy video database. Based on the unique characteristics of colonoscopy videos, we introduce a new scheme to detect and remove blurry frames, and segment the videos into shots based on the contents. Our experimental results show that the average precision and recall of the proposed scheme are over 90% for the detection of non-blurry images. The proposed method of blurry frame detection and shot segmentation is extensible to the videos captured from other endoscopic procedures such as upper gastrointestinal endoscopy, enteroscopy, cystoscopy, and laparoscopy.

Communication scheme based on evolutionary spatial 2×2 games

NASA Astrophysics Data System (ADS)

Ziaukas, Pranas; Ragulskis, Tautvydas; Ragulskis, Minvydas

2014-06-01

A visual communication scheme based on evolutionary spatial 2×2 games is proposed in this paper. Self-organizing patterns induced by complex interactions between competing individuals are exploited for hiding and transmitting secret visual information. Properties of the proposed communication scheme are discussed in details. It is shown that the hiding capacity of the system (the minimum size of the detectable primitives and the minimum distance between two primitives) is sufficient for the effective transmission of digital dichotomous images. Also, it is demonstrated that the proposed communication scheme is resilient to time backwards, plain image attacks and is highly sensitive to perturbations of private and public keys. Several computational experiments are used to demonstrate the effectiveness of the proposed communication scheme.

Activity Detection and Retrieval for Image and Video Data with Limited Training

DTIC Science & Technology

2015-06-10

applications. Here we propose two techniques for image segmentation. The first involves an automata based multiple threshold selection scheme, where a... automata . For our second approach to segmentation, we employ a region based segmentation technique that is capable of handling intensity inhomogeneity...techniques for image segmentation. The first involves an automata based multiple threshold selection scheme, where a mixture of Gaussian is fitted to the

Automatic epileptic seizure detection in EEGs using MF-DFA, SVM based on cloud computing.

PubMed

Zhang, Zhongnan; Wen, Tingxi; Huang, Wei; Wang, Meihong; Li, Chunfeng

2017-01-01

Epilepsy is a chronic disease with transient brain dysfunction that results from the sudden abnormal discharge of neurons in the brain. Since electroencephalogram (EEG) is a harmless and noninvasive detection method, it plays an important role in the detection of neurological diseases. However, the process of analyzing EEG to detect neurological diseases is often difficult because the brain electrical signals are random, non-stationary and nonlinear. In order to overcome such difficulty, this study aims to develop a new computer-aided scheme for automatic epileptic seizure detection in EEGs based on multi-fractal detrended fluctuation analysis (MF-DFA) and support vector machine (SVM). New scheme first extracts features from EEG by MF-DFA during the first stage. Then, the scheme applies a genetic algorithm (GA) to calculate parameters used in SVM and classify the training data according to the selected features using SVM. Finally, the trained SVM classifier is exploited to detect neurological diseases. The algorithm utilizes MLlib from library of SPARK and runs on cloud platform. Applying to a public dataset for experiment, the study results show that the new feature extraction method and scheme can detect signals with less features and the accuracy of the classification reached up to 99%. MF-DFA is a promising approach to extract features for analyzing EEG, because of its simple algorithm procedure and less parameters. The features obtained by MF-DFA can represent samples as well as traditional wavelet transform and Lyapunov exponents. GA can always find useful parameters for SVM with enough execution time. The results illustrate that the classification model can achieve comparable accuracy, which means that it is effective in epileptic seizure detection.

Exploring Sampling in the Detection of Multicategory EEG Signals

PubMed Central

Siuly, Siuly; Kabir, Enamul; Wang, Hua; Zhang, Yanchun

2015-01-01

The paper presents a structure based on samplings and machine leaning techniques for the detection of multicategory EEG signals where random sampling (RS) and optimal allocation sampling (OS) are explored. In the proposed framework, before using the RS and OS scheme, the entire EEG signals of each class are partitioned into several groups based on a particular time period. The RS and OS schemes are used in order to have representative observations from each group of each category of EEG data. Then all of the selected samples by the RS from the groups of each category are combined in a one set named RS set. In the similar way, for the OS scheme, an OS set is obtained. Then eleven statistical features are extracted from the RS and OS set, separately. Finally this study employs three well-known classifiers: k-nearest neighbor (k-NN), multinomial logistic regression with a ridge estimator (MLR), and support vector machine (SVM) to evaluate the performance for the RS and OS feature set. The experimental outcomes demonstrate that the RS scheme well represents the EEG signals and the k-NN with the RS is the optimum choice for detection of multicategory EEG signals. PMID:25977705

An improved PCA method with application to boiler leak detection.

PubMed

Sun, Xi; Marquez, Horacio J; Chen, Tongwen; Riaz, Muhammad

2005-07-01

Principal component analysis (PCA) is a popular fault detection technique. It has been widely used in process industries, especially in the chemical industry. In industrial applications, achieving a sensitive system capable of detecting incipient faults, which maintains the false alarm rate to a minimum, is a crucial issue. Although a lot of research has been focused on these issues for PCA-based fault detection and diagnosis methods, sensitivity of the fault detection scheme versus false alarm rate continues to be an important issue. In this paper, an improved PCA method is proposed to address this problem. In this method, a new data preprocessing scheme and a new fault detection scheme designed for Hotelling's T2 as well as the squared prediction error are developed. A dynamic PCA model is also developed for boiler leak detection. This new method is applied to boiler water/steam leak detection with real data from Syncrude Canada's utility plant in Fort McMurray, Canada. Our results demonstrate that the proposed method can effectively reduce false alarm rate, provide effective and correct leak alarms, and give early warning to operators.

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

Li, Wenfang; Du, Jinjin; Wen, Ruijuan

We have investigated the transmission spectra of a Fabry-Perot interferometer (FPI) with squeezed vacuum state injection and non-Gaussian detection, including photon number resolving detection and parity detection. In order to show the suitability of the system, parallel studies were made of the performance of two other light sources: coherent state of light and Fock state of light either with classical mean intensity detection or with non-Gaussian detection. This shows that by using the squeezed vacuum state and non-Gaussian detection simultaneously, the resolution of the FPI can go far beyond the cavity standard bandwidth limit based on the current techniques. Themore » sensitivity of the scheme has also been explored and it shows that the minimum detectable sensitivity is better than that of the other schemes.« less

Sensor data security level estimation scheme for wireless sensor networks.

PubMed

Ramos, Alex; Filho, Raimir Holanda

2015-01-19

Due to their increasing dissemination, wireless sensor networks (WSNs) have become the target of more and more sophisticated attacks, even capable of circumventing both attack detection and prevention mechanisms. This may cause WSN users, who totally trust these security mechanisms, to think that a sensor reading is secure, even when an adversary has corrupted it. For that reason, a scheme capable of estimating the security level (SL) that these mechanisms provide to sensor data is needed, so that users can be aware of the actual security state of this data and can make better decisions on its use. However, existing security estimation schemes proposed for WSNs fully ignore detection mechanisms and analyze solely the security provided by prevention mechanisms. In this context, this work presents the sensor data security estimator (SDSE), a new comprehensive security estimation scheme for WSNs. SDSE is designed for estimating the sensor data security level based on security metrics that analyze both attack prevention and detection mechanisms. In order to validate our proposed scheme, we have carried out extensive simulations that show the high accuracy of SDSE estimates.

Sensor Data Security Level Estimation Scheme for Wireless Sensor Networks

PubMed Central

Ramos, Alex; Filho, Raimir Holanda

2015-01-01

Due to their increasing dissemination, wireless sensor networks (WSNs) have become the target of more and more sophisticated attacks, even capable of circumventing both attack detection and prevention mechanisms. This may cause WSN users, who totally trust these security mechanisms, to think that a sensor reading is secure, even when an adversary has corrupted it. For that reason, a scheme capable of estimating the security level (SL) that these mechanisms provide to sensor data is needed, so that users can be aware of the actual security state of this data and can make better decisions on its use. However, existing security estimation schemes proposed for WSNs fully ignore detection mechanisms and analyze solely the security provided by prevention mechanisms. In this context, this work presents the sensor data security estimator (SDSE), a new comprehensive security estimation scheme for WSNs. SDSE is designed for estimating the sensor data security level based on security metrics that analyze both attack prevention and detection mechanisms. In order to validate our proposed scheme, we have carried out extensive simulations that show the high accuracy of SDSE estimates. PMID:25608215

A Novel DFT-Based DOA Estimation by a Virtual Array Extension Using Simple Multiplications for FMCW Radar

PubMed Central

Kim, Bongseok; Kim, Sangdong; Lee, Jonghun

2018-01-01

We propose a novel discrete Fourier transform (DFT)-based direction of arrival (DOA) estimation by a virtual array extension using simple multiplications for frequency modulated continuous wave (FMCW) radar. DFT-based DOA estimation is usually employed in radar systems because it provides the advantage of low complexity for real-time signal processing. In order to enhance the resolution of DOA estimation or to decrease the missing detection probability, it is essential to have a considerable number of channel signals. However, due to constraints of space and cost, it is not easy to increase the number of channel signals. In order to address this issue, we increase the number of effective channel signals by generating virtual channel signals using simple multiplications of the given channel signals. The increase in channel signals allows the proposed scheme to detect DOA more accurately than the conventional scheme while using the same number of channel signals. Simulation results show that the proposed scheme achieves improved DOA estimation compared to the conventional DFT-based method. Furthermore, the effectiveness of the proposed scheme in a practical environment is verified through the experiment. PMID:29758016

A Blind Reversible Robust Watermarking Scheme for Relational Databases

PubMed Central

Chang, Chin-Chen; Nguyen, Thai-Son; Lin, Chia-Chen

2013-01-01

Protecting the ownership and controlling the copies of digital data have become very important issues in Internet-based applications. Reversible watermark technology allows the distortion-free recovery of relational databases after the embedded watermark data are detected or verified. In this paper, we propose a new, blind, reversible, robust watermarking scheme that can be used to provide proof of ownership for the owner of a relational database. In the proposed scheme, a reversible data-embedding algorithm, which is referred to as “histogram shifting of adjacent pixel difference” (APD), is used to obtain reversibility. The proposed scheme can detect successfully 100% of the embedded watermark data, even if as much as 80% of the watermarked relational database is altered. Our extensive analysis and experimental results show that the proposed scheme is robust against a variety of data attacks, for example, alteration attacks, deletion attacks, mix-match attacks, and sorting attacks. PMID:24223033

A blind reversible robust watermarking scheme for relational databases.

PubMed

Chang, Chin-Chen; Nguyen, Thai-Son; Lin, Chia-Chen

2013-01-01

Protecting the ownership and controlling the copies of digital data have become very important issues in Internet-based applications. Reversible watermark technology allows the distortion-free recovery of relational databases after the embedded watermark data are detected or verified. In this paper, we propose a new, blind, reversible, robust watermarking scheme that can be used to provide proof of ownership for the owner of a relational database. In the proposed scheme, a reversible data-embedding algorithm, which is referred to as "histogram shifting of adjacent pixel difference" (APD), is used to obtain reversibility. The proposed scheme can detect successfully 100% of the embedded watermark data, even if as much as 80% of the watermarked relational database is altered. Our extensive analysis and experimental results show that the proposed scheme is robust against a variety of data attacks, for example, alteration attacks, deletion attacks, mix-match attacks, and sorting attacks.

Fault Diagnosis for Centre Wear Fault of Roll Grinder Based on a Resonance Demodulation Scheme

NASA Astrophysics Data System (ADS)

Wang, Liming; Shao, Yimin; Yin, Lei; Yuan, Yilin; Liu, Jing

2017-05-01

Roll grinder is one of the important parts in the rolling machinery, and the grinding precision of roll surface has direct influence on the surface quality of steel strip. However, during the grinding process, the centre bears the gravity of the roll and alternating stress. Therefore, wear or spalling faults are easily observed on the centre, which will lead to an anomalous vibration of the roll grinder. In this study, a resonance demodulation scheme is proposed to detect the centre wear fault of roll grinder. Firstly, fast kurtogram method is employed to help select the sub-band filter parameters for optimal resonance demodulation. Further, the envelope spectrum are derived based on the filtered signal. Finally, two health indicators are designed to conduct the fault diagnosis for centre wear fault. The proposed scheme is assessed by analysing experimental data from a roll grinder of twenty-high rolling mill. The results show that the proposed scheme can effectively detect the centre wear fault of the roll grinder.

Detection and localization of copy-paste forgeries in digital videos.

PubMed

Singh, Raahat Devender; Aggarwal, Naveen

2017-12-01

Amidst the continual march of technology, we find ourselves relying on digital videos to proffer visual evidence in several highly sensitive areas such as journalism, politics, civil and criminal litigation, and military and intelligence operations. However, despite being an indispensable source of information with high evidentiary value, digital videos are also extremely vulnerable to conscious manipulations. Therefore, in a situation where dependence on video evidence is unavoidable, it becomes crucial to authenticate the contents of this evidence before accepting them as an accurate depiction of reality. Digital videos can suffer from several kinds of manipulations, but perhaps, one of the most consequential forgeries is copy-paste forgery, which involves insertion/removal of objects into/from video frames. Copy-paste forgeries alter the information presented by the video scene, which has a direct effect on our basic understanding of what that scene represents, and so, from a forensic standpoint, the challenge of detecting such forgeries is especially significant. In this paper, we propose a sensor pattern noise based copy-paste detection scheme, which is an improved and forensically stronger version of an existing noise-residue based technique. We also study a demosaicing artifact based image forensic scheme to estimate the extent of its viability in the domain of video forensics. Furthermore, we suggest a simplistic clustering technique for the detection of copy-paste forgeries, and determine if it possess the capabilities desired of a viable and efficacious video forensic scheme. Finally, we validate these schemes on a set of realistically tampered MJPEG, MPEG-2, MPEG-4, and H.264/AVC encoded videos in a diverse experimental set-up by varying the strength of post-production re-compressions and transcodings, bitrates, and sizes of the tampered regions. Such an experimental set-up is representative of a neutral testing platform and simulates a real-world forgery scenario where the forensic investigator has no control over any of the variable parameters of the tampering process. When tested in such an experimental set-up, the four forensic schemes achieved varying levels of detection accuracies and exhibited different scopes of applicabilities. For videos compressed using QFs in the range 70-100, the existing noise residue based technique generated average detection accuracy in the range 64.5%-82.0%, while the proposed sensor pattern noise based scheme generated average accuracy in the range 89.9%-98.7%. For the aforementioned range of QFs, average accuracy rates achieved by the suggested clustering technique and the demosaicing artifact based approach were in the range 79.1%-90.1% and 83.2%-93.3%, respectively. Copyright © 2017 Elsevier B.V. All rights reserved.

A computerized scheme of SARS detection in early stage based on chest image of digital radiograph

NASA Astrophysics Data System (ADS)

Zheng, Zhong; Lan, Rihui; Lv, Guozheng

2004-05-01

A computerized scheme for early severe acute respiratory syndrome(SARS) lesion detection in digital chest radiographs is presented in this paper. The total scheme consists of two main parts: the first part is to determine suspect lesions by the theory of locally orderless images(LOI) and their spatial features; the second part is to select real lesions among these suspect ones by their frequent features. The method we used in the second part is firstly developed by Katsuragawa et al with necessary modification. Preliminary results indicate that these features are good criterions to tell early SARS lesions apart from other normal lung structures.

Subranging scheme for SQUID sensors

NASA Technical Reports Server (NTRS)

Penanen, Konstantin I. (Inventor)

2008-01-01

A readout scheme for measuring the output from a SQUID-based sensor-array using an improved subranging architecture that includes multiple resolution channels (such as a coarse resolution channel and a fine resolution channel). The scheme employs a flux sensing circuit with a sensing coil connected in series to multiple input coils, each input coil being coupled to a corresponding SQUID detection circuit having a high-resolution SQUID device with independent linearizing feedback. A two-resolution configuration (course and fine) is illustrated with a primary SQUID detection circuit for generating a fine readout, and a secondary SQUID detection circuit for generating a course readout, both having feedback current coupled to the respective SQUID devices via feedback/modulation coils. The primary and secondary SQUID detection circuits function and derive independent feedback. Thus, the SQUID devices may be monitored independently of each other (and read simultaneously) to dramatically increase slew rates and dynamic range.

Computerized mass detection in whole breast ultrasound images: reduction of false positives using bilateral subtraction technique

NASA Astrophysics Data System (ADS)

Ikedo, Yuji; Fukuoka, Daisuke; Hara, Takeshi; Fujita, Hiroshi; Takada, Etsuo; Endo, Tokiko; Morita, Takako

2007-03-01

The comparison of left and right mammograms is a common technique used by radiologists for the detection and diagnosis of masses. In mammography, computer-aided detection (CAD) schemes using bilateral subtraction technique have been reported. However, in breast ultrasonography, there are no reports on CAD schemes using comparison of left and right breasts. In this study, we propose a scheme of false positive reduction based on bilateral subtraction technique in whole breast ultrasound images. Mass candidate regions are detected by using the information of edge directions. Bilateral breast images are registered with reference to the nipple positions and skin lines. A false positive region is detected based on a comparison of the average gray values of a mass candidate region and a region with the same position and same size as the candidate region in the contralateral breast. In evaluating the effectiveness of the false positive reduction method, three normal and three abnormal bilateral pairs of whole breast images were employed. These abnormal breasts included six masses larger than 5 mm in diameter. The sensitivity was 83% (5/6) with 13.8 (165/12) false positives per breast before applying the proposed reduction method. By applying the method, false positives were reduced to 4.5 (54/12) per breast without removing a true positive region. This preliminary study indicates that the bilateral subtraction technique is effective for improving the performance of a CAD scheme in whole breast ultrasound images.

Multiple crack detection in 3D using a stable XFEM and global optimization

NASA Astrophysics Data System (ADS)

Agathos, Konstantinos; Chatzi, Eleni; Bordas, Stéphane P. A.

2018-02-01

A numerical scheme is proposed for the detection of multiple cracks in three dimensional (3D) structures. The scheme is based on a variant of the extended finite element method (XFEM) and a hybrid optimizer solution. The proposed XFEM variant is particularly well-suited for the simulation of 3D fracture problems, and as such serves as an efficient solution to the so-called forward problem. A set of heuristic optimization algorithms are recombined into a multiscale optimization scheme. The introduced approach proves effective in tackling the complex inverse problem involved, where identification of multiple flaws is sought on the basis of sparse measurements collected near the structural boundary. The potential of the scheme is demonstrated through a set of numerical case studies of varying complexity.

Innovative hazard detection and avoidance strategy for autonomous safe planetary landing

NASA Astrophysics Data System (ADS)

Jiang, Xiuqiang; Li, Shuang; Tao, Ting

2016-09-01

Autonomous hazard detection and avoidance (AHDA) is one of the key technologies for future safe planetary landing missions. In this paper, we address the latest progress on planetary autonomous hazard detection and avoidance technologies. First, the innovative autonomous relay hazard detection and avoidance strategy adopted in Chang'e-3 lunar soft landing mission and its flight results are reported in detail. Second, two new conceptual candidate schemes of hazard detection and avoidance are presented based on the Chang'e-3 AHDA system and the latest developing technologies for the future planetary missions, and some preliminary testing results are also given. Finally, the related supporting technologies for the two candidate schemes above are analyzed.

Evaluation of hardware costs of implementing PSK signal detection circuit based on "system on chip"

NASA Astrophysics Data System (ADS)

Sokolovskiy, A. V.; Dmitriev, D. D.; Veisov, E. A.; Gladyshev, A. B.

2018-05-01

The article deals with the choice of the architecture of digital signal processing units for implementing the PSK signal detection scheme. As an assessment of the effectiveness of architectures, the required number of shift registers and computational processes are used when implementing the "system on a chip" on the chip. A statistical estimation of the normalized code sequence offset in the signal synchronization scheme for various hardware block architectures is used.

Reliable multicast protocol specifications flow control and NACK policy

NASA Technical Reports Server (NTRS)

Callahan, John R.; Montgomery, Todd L.; Whetten, Brian

1995-01-01

This appendix presents the flow and congestion control schemes recommended for RMP and a NACK policy based on the whiteboard tool. Because RMP uses a primarily NACK based error detection scheme, there is no direct feedback path through which receivers can signal losses through low buffer space or congestion. Reliable multicast protocols also suffer from the fact that throughput for a multicast group must be divided among the members of the group. This division is usually very dynamic in nature and therefore does not lend itself well to a priori determination. These facts have led the flow and congestion control schemes of RMP to be made completely orthogonal to the protocol specification. This allows several differing schemes to be used in different environments to produce the best results. As a default, a modified sliding window scheme based on previous algorithms are suggested and described below.

Automated flaw detection scheme for cast austenitic stainless steel weld specimens using Hilbert-Huang transform of ultrasonic phased array data

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

Khan, Tariq; Majumdar, Shantanu; Udpa, Lalita

2012-05-17

The objective of this work is to develop processing algorithms to detect and localize flaws using ultrasonic phased-array data. Data was collected on cast austenitic stainless stell (CASS) weld specimens onloan from the U.S. nuclear power industry' Pressurized Walter Reactor Owners Group (PWROG) traveling specimen set. Each specimen consists of a centrifugally cast stainless stell (CCSS) pipe section welded to a statically cst(SCSS) or wrought (WRSS) section. The paper presents a novel automated flaw detection and localization scheme using low frequency ultrasonic phased array inspection singals from the weld and heat affected zone of the based materials. The major stepsmore » of the overall scheme are preprocessing and region of interest (ROI) detection followed by the Hilbert-Huang transform (HHT) of A-scans in the detected ROIs. HHT offers time-frequency-energy distribution for each ROI. The Accumulation of energy in a particular frequency band is used as a classification feature for the particular ROI.« less

An adaptive morphological gradient lifting wavelet for detecting bearing defects

NASA Astrophysics Data System (ADS)

Li, Bing; Zhang, Pei-lin; Mi, Shuang-shan; Hu, Ren-xi; Liu, Dong-sheng

2012-05-01

This paper presents a novel wavelet decomposition scheme, named adaptive morphological gradient lifting wavelet (AMGLW), for detecting bearing defects. The adaptability of the AMGLW consists in that the scheme can select between two filters, mean the average filter and morphological gradient filter, to update the approximation signal based on the local gradient of the analyzed signal. Both a simulated signal and vibration signals acquired from bearing are employed to evaluate and compare the proposed AMGLW scheme with the traditional linear wavelet transform (LWT) and another adaptive lifting wavelet (ALW) developed in literature. Experimental results reveal that the AMGLW outperforms the LW and ALW obviously for detecting bearing defects. The impulsive components can be enhanced and the noise can be depressed simultaneously by the presented AMGLW scheme. Thus the fault characteristic frequencies of bearing can be clearly identified. Furthermore, the AMGLW gets an advantage over LW in computation efficiency. It is quite suitable for online condition monitoring of bearings and other rotating machineries.

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

Podoshvedov, S. A., E-mail: podoshvedov@mail.ru

A method to generate Schroedinger cat states in free propagating optical fields based on the use of displaced states (or displacement operators) is developed. Some optical schemes with photon-added coherent states are studied. The schemes are modifications of the general method based on a sequence of displacements and photon additions or subtractions adjusted to generate Schroedinger cat states of a larger size. The effects of detection inefficiency are taken into account.

In-TFT-array-process micro defect inspection using nonlinear principal component analysis.

PubMed

Liu, Yi-Hung; Wang, Chi-Kai; Ting, Yung; Lin, Wei-Zhi; Kang, Zhi-Hao; Chen, Ching-Shun; Hwang, Jih-Shang

2009-11-20

Defect inspection plays a critical role in thin film transistor liquid crystal display (TFT-LCD) manufacture, and has received much attention in the field of automatic optical inspection (AOI). Previously, most focus was put on the problems of macro-scale Mura-defect detection in cell process, but it has recently been found that the defects which substantially influence the yield rate of LCD panels are actually those in the TFT array process, which is the first process in TFT-LCD manufacturing. Defect inspection in TFT array process is therefore considered a difficult task. This paper presents a novel inspection scheme based on kernel principal component analysis (KPCA) algorithm, which is a nonlinear version of the well-known PCA algorithm. The inspection scheme can not only detect the defects from the images captured from the surface of LCD panels, but also recognize the types of the detected defects automatically. Results, based on real images provided by a LCD manufacturer in Taiwan, indicate that the KPCA-based defect inspection scheme is able to achieve a defect detection rate of over 99% and a high defect classification rate of over 96% when the imbalanced support vector machine (ISVM) with 2-norm soft margin is employed as the classifier. More importantly, the inspection time is less than 1 s per input image.

On detection and visualization techniques for cyber security situation awareness

NASA Astrophysics Data System (ADS)

Yu, Wei; Wei, Shixiao; Shen, Dan; Blowers, Misty; Blasch, Erik P.; Pham, Khanh D.; Chen, Genshe; Zhang, Hanlin; Lu, Chao

2013-05-01

Networking technologies are exponentially increasing to meet worldwide communication requirements. The rapid growth of network technologies and perversity of communications pose serious security issues. In this paper, we aim to developing an integrated network defense system with situation awareness capabilities to present the useful information for human analysts. In particular, we implement a prototypical system that includes both the distributed passive and active network sensors and traffic visualization features, such as 1D, 2D and 3D based network traffic displays. To effectively detect attacks, we also implement algorithms to transform real-world data of IP addresses into images and study the pattern of attacks and use both the discrete wavelet transform (DWT) based scheme and the statistical based scheme to detect attacks. Through an extensive simulation study, our data validate the effectiveness of our implemented defense system.

Two-out-of-two color matching based visual cryptography schemes.

PubMed

Machizaud, Jacques; Fournel, Thierry

2012-09-24

Visual cryptography which consists in sharing a secret message between transparencies has been extended to color prints. In this paper, we propose a new visual cryptography scheme based on color matching. The stacked printed media reveal a uniformly colored message decoded by the human visual system. In contrast with the previous color visual cryptography schemes, the proposed one enables to share images without pixel expansion and to detect a forgery as the color of the message is kept secret. In order to correctly print the colors on the media and to increase the security of the scheme, we use spectral models developed for color reproduction describing printed colors from an optical point of view.

A Pedestrian Detection Scheme Using a Coherent Phase Difference Method Based on 2D Range-Doppler FMCW Radar

PubMed Central

Hyun, Eugin; Jin, Young-Seok; Lee, Jong-Hun

2016-01-01

For an automotive pedestrian detection radar system, fast-ramp based 2D range-Doppler Frequency Modulated Continuous Wave (FMCW) radar is effective for distinguishing between moving targets and unwanted clutter. However, when a weak moving target such as a pedestrian exists together with strong clutter, the pedestrian may be masked by the side-lobe of the clutter even though they are notably separated in the Doppler dimension. To prevent this problem, one popular solution is the use of a windowing scheme with a weighting function. However, this method leads to a spread spectrum, so the pedestrian with weak signal power and slow Doppler may also be masked by the main-lobe of clutter. With a fast-ramp based FMCW radar, if the target is moving, the complex spectrum of the range- Fast Fourier Transform (FFT) is changed with a constant phase difference over ramps. In contrast, the clutter exhibits constant phase irrespective of the ramps. Based on this fact, in this paper we propose a pedestrian detection for highly cluttered environments using a coherent phase difference method. By detecting the coherent phase difference from the complex spectrum of the range-FFT, we first extract the range profile of the moving pedestrians. Then, through the Doppler FFT, we obtain the 2D range-Doppler map for only the pedestrian. To test the proposed detection scheme, we have developed a real-time data logging system with a 24 GHz FMCW transceiver. In laboratory tests, we verified that the signal processing results from the proposed method were much better than those expected from the conventional 2D FFT-based detection method. PMID:26805835

A Pedestrian Detection Scheme Using a Coherent Phase Difference Method Based on 2D Range-Doppler FMCW Radar.

PubMed

Hyun, Eugin; Jin, Young-Seok; Lee, Jong-Hun

2016-01-20

For an automotive pedestrian detection radar system, fast-ramp based 2D range-Doppler Frequency Modulated Continuous Wave (FMCW) radar is effective for distinguishing between moving targets and unwanted clutter. However, when a weak moving target such as a pedestrian exists together with strong clutter, the pedestrian may be masked by the side-lobe of the clutter even though they are notably separated in the Doppler dimension. To prevent this problem, one popular solution is the use of a windowing scheme with a weighting function. However, this method leads to a spread spectrum, so the pedestrian with weak signal power and slow Doppler may also be masked by the main-lobe of clutter. With a fast-ramp based FMCW radar, if the target is moving, the complex spectrum of the range- Fast Fourier Transform (FFT) is changed with a constant phase difference over ramps. In contrast, the clutter exhibits constant phase irrespective of the ramps. Based on this fact, in this paper we propose a pedestrian detection for highly cluttered environments using a coherent phase difference method. By detecting the coherent phase difference from the complex spectrum of the range-FFT, we first extract the range profile of the moving pedestrians. Then, through the Doppler FFT, we obtain the 2D range-Doppler map for only the pedestrian. To test the proposed detection scheme, we have developed a real-time data logging system with a 24 GHz FMCW transceiver. In laboratory tests, we verified that the signal processing results from the proposed method were much better than those expected from the conventional 2D FFT-based detection method.

Subdecoherence time generation and detection of orbital entanglement in quantum dots.

PubMed

Brange, F; Malkoc, O; Samuelsson, P

2015-05-01

Recent experiments have demonstrated subdecoherence time control of individual single-electron orbital qubits. Here we propose a quantum-dot-based scheme for generation and detection of pairs of orbitally entangled electrons on a time scale much shorter than the decoherence time. The electrons are entangled, via two-particle interference, and transferred to the detectors during a single cotunneling event, making the scheme insensitive to charge noise. For sufficiently long detector dot lifetimes, cross-correlation detection of the dot charges can be performed with real-time counting techniques, providing for an unambiguous short-time Bell inequality test of orbital entanglement.

Evaluation schemes for video and image anomaly detection algorithms

NASA Astrophysics Data System (ADS)

Parameswaran, Shibin; Harguess, Josh; Barngrover, Christopher; Shafer, Scott; Reese, Michael

2016-05-01

Video anomaly detection is a critical research area in computer vision. It is a natural first step before applying object recognition algorithms. There are many algorithms that detect anomalies (outliers) in videos and images that have been introduced in recent years. However, these algorithms behave and perform differently based on differences in domains and tasks to which they are subjected. In order to better understand the strengths and weaknesses of outlier algorithms and their applicability in a particular domain/task of interest, it is important to measure and quantify their performance using appropriate evaluation metrics. There are many evaluation metrics that have been used in the literature such as precision curves, precision-recall curves, and receiver operating characteristic (ROC) curves. In order to construct these different metrics, it is also important to choose an appropriate evaluation scheme that decides when a proposed detection is considered a true or a false detection. Choosing the right evaluation metric and the right scheme is very critical since the choice can introduce positive or negative bias in the measuring criterion and may favor (or work against) a particular algorithm or task. In this paper, we review evaluation metrics and popular evaluation schemes that are used to measure the performance of anomaly detection algorithms on videos and imagery with one or more anomalies. We analyze the biases introduced by these by measuring the performance of an existing anomaly detection algorithm.

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

NASA Astrophysics Data System (ADS)

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

2010-07-01

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

Interband cascade laser-based ppbv-level mid-infrared methane detection using two digital lock-in amplifier schemes

NASA Astrophysics Data System (ADS)

Song, Fang; Zheng, Chuantao; Yu, Di; Zhou, Yanwen; Yan, Wanhong; Ye, Weilin; Zhang, Yu; Wang, Yiding; Tittel, Frank K.

2018-03-01

A parts-per-billion in volume (ppbv) level mid-infrared methane (CH4) sensor system was demonstrated using second-harmonic wavelength modulation spectroscopy (2 f-WMS). A 3291 nm interband cascade laser (ICL) and a multi-pass gas cell (MPGC) with a 16 m optical path length were adopted in the reported sensor system. Two digital lock-in amplifier (DLIA) schemes, a digital signal processor (DSP)-based DLIA and a LabVIEW-based DLIA, were used for harmonic signal extraction. A limit of detection (LoD) of 13.07 ppbv with an averaging time of 2 s was achieved using the DSP-based DLIA and a LoD of 5.84 ppbv was obtained using the LabVIEW-based DLIA with the same averaging time. A rise time of 0→2 parts-per-million in volume (ppmv) and fall time of 2→0 ppmv were observed. Outdoor atmospheric CH4 concentration measurements were carried out to evaluate the sensor performance using the two DLIA schemes.

Image Motion Detection And Estimation: The Modified Spatio-Temporal Gradient Scheme

NASA Astrophysics Data System (ADS)

Hsin, Cheng-Ho; Inigo, Rafael M.

1990-03-01

The detection and estimation of motion are generally involved in computing a velocity field of time-varying images. A completely new modified spatio-temporal gradient scheme to determine motion is proposed. This is derived by using gradient methods and properties of biological vision. A set of general constraints is proposed to derive motion constraint equations. The constraints are that the second directional derivatives of image intensity at an edge point in the smoothed image will be constant at times t and t+L . This scheme basically has two stages: spatio-temporal filtering, and velocity estimation. Initially, image sequences are processed by a set of oriented spatio-temporal filters which are designed using a Gaussian derivative model. The velocity is then estimated for these filtered image sequences based on the gradient approach. From a computational stand point, this scheme offers at least three advantages over current methods. The greatest advantage of the modified spatio-temporal gradient scheme over the traditional ones is that an infinite number of motion constraint equations are derived instead of only one. Therefore, it solves the aperture problem without requiring any additional assumptions and is simply a local process. The second advantage is that because of the spatio-temporal filtering, the direct computation of image gradients (discrete derivatives) is avoided. Therefore the error in gradients measurement is reduced significantly. The third advantage is that during the processing of motion detection and estimation algorithm, image features (edges) are produced concurrently with motion information. The reliable range of detected velocity is determined by parameters of the oriented spatio-temporal filters. Knowing the velocity sensitivity of a single motion detection channel, a multiple-channel mechanism for estimating image velocity, seldom addressed by other motion schemes in machine vision, can be constructed by appropriately choosing and combining different sets of parameters. By applying this mechanism, a great range of velocity can be detected. The scheme has been tested for both synthetic and real images. The results of simulations are very satisfactory.

Two particle tracking and detection in a single Gaussian beam optical trap.

PubMed

Praveen, P; Yogesha; Iyengar, Shruthi S; Bhattacharya, Sarbari; Ananthamurthy, Sharath

2016-01-20

We have studied in detail the situation wherein two microbeads are trapped axially in a single-beam Gaussian intensity profile optical trap. We find that the corner frequency extracted from a power spectral density analysis of intensity fluctuations recorded on a quadrant photodetector (QPD) is dependent on the detection scheme. Using forward- and backscattering detection schemes with single and two laser wavelengths along with computer simulations, we conclude that fluctuations detected in backscattering bear true position information of the bead encountered first in the beam propagation direction. Forward scattering, on the other hand, carries position information of both beads with substantial contribution from the bead encountered first along the beam propagation direction. Mie scattering analysis further reveals that the interference term from the scattering of the two beads contributes significantly to the signal, precluding the ability to resolve the positions of the individual beads in forward scattering. In QPD-based detection schemes, detection through backscattering, thereby, is imperative to track the true displacements of axially trapped microbeads for possible studies on light-mediated interbead interactions.

Security protection of DICOM medical images using dual-layer reversible watermarking with tamper detection capability.

PubMed

Tan, Chun Kiat; Ng, Jason Changwei; Xu, Xiaotian; Poh, Chueh Loo; Guan, Yong Liang; Sheah, Kenneth

2011-06-01

Teleradiology applications and universal availability of patient records using web-based technology are rapidly gaining importance. Consequently, digital medical image security has become an important issue when images and their pertinent patient information are transmitted across public networks, such as the Internet. Health mandates such as the Health Insurance Portability and Accountability Act require healthcare providers to adhere to security measures in order to protect sensitive patient information. This paper presents a fully reversible, dual-layer watermarking scheme with tamper detection capability for medical images. The scheme utilizes concepts of public-key cryptography and reversible data-hiding technique. The scheme was tested using medical images in DICOM format. The results show that the scheme is able to ensure image authenticity and integrity, and to locate tampered regions in the images.

Securing Collaborative Spectrum Sensing against Untrustworthy Secondary Users in Cognitive Radio Networks

NASA Astrophysics Data System (ADS)

Wang, Wenkai; Li, Husheng; Sun, Yan(Lindsay); Han, Zhu

2009-12-01

Cognitive radio is a revolutionary paradigm to migrate the spectrum scarcity problem in wireless networks. In cognitive radio networks, collaborative spectrum sensing is considered as an effective method to improve the performance of primary user detection. For current collaborative spectrum sensing schemes, secondary users are usually assumed to report their sensing information honestly. However, compromised nodes can send false sensing information to mislead the system. In this paper, we study the detection of untrustworthy secondary users in cognitive radio networks. We first analyze the case when there is only one compromised node in collaborative spectrum sensing schemes. Then we investigate the scenario that there are multiple compromised nodes. Defense schemes are proposed to detect malicious nodes according to their reporting histories. We calculate the suspicious level of all nodes based on their reports. The reports from nodes with high suspicious levels will be excluded in decision-making. Compared with existing defense methods, the proposed scheme can effectively differentiate malicious nodes and honest nodes. As a result, it can significantly improve the performance of collaborative sensing. For example, when there are 10 secondary users, with the primary user detection rate being equal to 0.99, one malicious user can make the false alarm rate [InlineEquation not available: see fulltext.] increase to 72%. The proposed scheme can reduce it to 5%. Two malicious users can make [InlineEquation not available: see fulltext.] increase to 85% and the proposed scheme reduces it to 8%.

Follicle Detection on the USG Images to Support Determination of Polycystic Ovary Syndrome

NASA Astrophysics Data System (ADS)

Adiwijaya; Purnama, B.; Hasyim, A.; Septiani, M. D.; Wisesty, U. N.; Astuti, W.

2015-06-01

Polycystic Ovary Syndrome(PCOS) is the most common endocrine disorders affected to female in their reproductive cycle. This has gained the attention from married couple which affected by infertility. One of the diagnostic criteria considereded by the doctor is analysing manually the ovary USG image to detect the number and size of ovary's follicle. This analysis may affect low varibilites, reproducibility, and efficiency. To overcome this problems. automatic scheme is suggested to detect the follicle on USG image in supporting PCOS diagnosis. The first scheme is determining the initial homogeneous region which will be segmented into real follicle form The next scheme is selecting the appropriate regions to follicle criteria. then measuring the segmented region attribute as the follicle. The measurement remains the number and size that aimed at categorizing the image into the PCOS or non-PCOS. The method used is region growing which includes region-based and seed-based. To measure the follicle diameter. there will be the different method including stereology and euclidean distance. The most optimum system plan to detect PCO is by using region growing and by using euclidean distance on quantification of follicle.

Ship Detection in Gaofen-3 SAR Images Based on Sea Clutter Distribution Analysis and Deep Convolutional Neural Network

PubMed Central

You, Hongjian

2018-01-01

Target detection is one of the important applications in the field of remote sensing. The Gaofen-3 (GF-3) Synthetic Aperture Radar (SAR) satellite launched by China is a powerful tool for maritime monitoring. This work aims at detecting ships in GF-3 SAR images using a new land masking strategy, the appropriate model for sea clutter and a neural network as the discrimination scheme. Firstly, the fully convolutional network (FCN) is applied to separate the sea from the land. Then, by analyzing the sea clutter distribution in GF-3 SAR images, we choose the probability distribution model of Constant False Alarm Rate (CFAR) detector from K-distribution, Gamma distribution and Rayleigh distribution based on a tradeoff between the sea clutter modeling accuracy and the computational complexity. Furthermore, in order to better implement CFAR detection, we also use truncated statistic (TS) as a preprocessing scheme and iterative censoring scheme (ICS) for boosting the performance of detector. Finally, we employ a neural network to re-examine the results as the discrimination stage. Experiment results on three GF-3 SAR images verify the effectiveness and efficiency of this approach. PMID:29364194

Ship Detection in Gaofen-3 SAR Images Based on Sea Clutter Distribution Analysis and Deep Convolutional Neural Network.

PubMed

An, Quanzhi; Pan, Zongxu; You, Hongjian

2018-01-24

Target detection is one of the important applications in the field of remote sensing. The Gaofen-3 (GF-3) Synthetic Aperture Radar (SAR) satellite launched by China is a powerful tool for maritime monitoring. This work aims at detecting ships in GF-3 SAR images using a new land masking strategy, the appropriate model for sea clutter and a neural network as the discrimination scheme. Firstly, the fully convolutional network (FCN) is applied to separate the sea from the land. Then, by analyzing the sea clutter distribution in GF-3 SAR images, we choose the probability distribution model of Constant False Alarm Rate (CFAR) detector from K-distribution, Gamma distribution and Rayleigh distribution based on a tradeoff between the sea clutter modeling accuracy and the computational complexity. Furthermore, in order to better implement CFAR detection, we also use truncated statistic (TS) as a preprocessing scheme and iterative censoring scheme (ICS) for boosting the performance of detector. Finally, we employ a neural network to re-examine the results as the discrimination stage. Experiment results on three GF-3 SAR images verify the effectiveness and efficiency of this approach.

Tiny Grains Give Huge Gains: Nanocrystal–Based Signal Amplification for Biomolecule Detection

PubMed Central

Tong, Sheng; Ren, Binbin; Zheng, Zhilan; Shen, Han; Bao, Gang

2013-01-01

Nanocrystals, despite their tiny sizes, contain thousands to millions of atoms. Here we show that the large number of atoms packed in each metallic nanocrystal can provide a huge gain in signal amplification for biomolecule detection. We have devised a highly sensitive, linear amplification scheme by integrating the dissolution of bound nanocrystals and metal-induced stoichiometric chromogenesis, and demonstrated that signal amplification is fully defined by the size and atom density of nanocrystals, which can be optimized through well-controlled nanocrystal synthesis. Further, the rich library of chromogenic reactions allows implementation of this scheme in various assay formats, as demonstrated by the iron oxide nanoparticle linked immunosorbent assay (ILISA) and blotting assay developed in this study. Our results indicate that, owing to the inherent simplicity, high sensitivity and repeatability, the nanocrystal based amplification scheme can significantly improve biomolecule quantification in both laboratory research and clinical diagnostics. This novel method adds a new dimension to current nanoparticle-based bioassays. PMID:23659350

Localization-Free Detection of Replica Node Attacks in Wireless Sensor Networks Using Similarity Estimation with Group Deployment Knowledge

PubMed Central

Ding, Chao; Yang, Lijun; Wu, Meng

2017-01-01

Due to the unattended nature and poor security guarantee of the wireless sensor networks (WSNs), adversaries can easily make replicas of compromised nodes, and place them throughout the network to launch various types of attacks. Such an attack is dangerous because it enables the adversaries to control large numbers of nodes and extend the damage of attacks to most of the network with quite limited cost. To stop the node replica attack, we propose a location similarity-based detection scheme using deployment knowledge. Compared with prior solutions, our scheme provides extra functionalities that prevent replicas from generating false location claims without deploying resource-consuming localization techniques on the resource-constraint sensor nodes. We evaluate the security performance of our proposal under different attack strategies through heuristic analysis, and show that our scheme achieves secure and robust replica detection by increasing the cost of node replication. Additionally, we evaluate the impact of network environment on the proposed scheme through theoretic analysis and simulation experiments, and indicate that our scheme achieves effectiveness and efficiency with substantially lower communication, computational, and storage overhead than prior works under different situations and attack strategies. PMID:28098846

Localization-Free Detection of Replica Node Attacks in Wireless Sensor Networks Using Similarity Estimation with Group Deployment Knowledge.

PubMed

Ding, Chao; Yang, Lijun; Wu, Meng

2017-01-15

Due to the unattended nature and poor security guarantee of the wireless sensor networks (WSNs), adversaries can easily make replicas of compromised nodes, and place them throughout the network to launch various types of attacks. Such an attack is dangerous because it enables the adversaries to control large numbers of nodes and extend the damage of attacks to most of the network with quite limited cost. To stop the node replica attack, we propose a location similarity-based detection scheme using deployment knowledge. Compared with prior solutions, our scheme provides extra functionalities that prevent replicas from generating false location claims without deploying resource-consuming localization techniques on the resource-constraint sensor nodes. We evaluate the security performance of our proposal under different attack strategies through heuristic analysis, and show that our scheme achieves secure and robust replica detection by increasing the cost of node replication. Additionally, we evaluate the impact of network environment on the proposed scheme through theoretic analysis and simulation experiments, and indicate that our scheme achieves effectiveness and efficiency with substantially lower communication, computational, and storage overhead than prior works under different situations and attack strategies.

Teleportation-based continuous variable quantum cryptography

NASA Astrophysics Data System (ADS)

Luiz, F. S.; Rigolin, Gustavo

2017-03-01

We present a continuous variable (CV) quantum key distribution (QKD) scheme based on the CV quantum teleportation of coherent states that yields a raw secret key made up of discrete variables for both Alice and Bob. This protocol preserves the efficient detection schemes of current CV technology (no single-photon detection techniques) and, at the same time, has efficient error correction and privacy amplification schemes due to the binary modulation of the key. We show that for a certain type of incoherent attack, it is secure for almost any value of the transmittance of the optical line used by Alice to share entangled two-mode squeezed states with Bob (no 3 dB or 50% loss limitation characteristic of beam splitting attacks). The present CVQKD protocol works deterministically (no postselection needed) with efficient direct reconciliation techniques (no reverse reconciliation) in order to generate a secure key and beyond the 50% loss case at the incoherent attack level.

Applying deep learning technology to automatically identify metaphase chromosomes using scanning microscopic images: an initial investigation

NASA Astrophysics Data System (ADS)

Qiu, Yuchen; Lu, Xianglan; Yan, Shiju; Tan, Maxine; Cheng, Samuel; Li, Shibo; Liu, Hong; Zheng, Bin

2016-03-01

Automated high throughput scanning microscopy is a fast developing screening technology used in cytogenetic laboratories for the diagnosis of leukemia or other genetic diseases. However, one of the major challenges of using this new technology is how to efficiently detect the analyzable metaphase chromosomes during the scanning process. The purpose of this investigation is to develop a computer aided detection (CAD) scheme based on deep learning technology, which can identify the metaphase chromosomes with high accuracy. The CAD scheme includes an eight layer neural network. The first six layers compose of an automatic feature extraction module, which has an architecture of three convolution-max-pooling layer pairs. The 1st, 2nd and 3rd pair contains 30, 20, 20 feature maps, respectively. The seventh and eighth layers compose of a multiple layer perception (MLP) based classifier, which is used to identify the analyzable metaphase chromosomes. The performance of new CAD scheme was assessed by receiver operation characteristic (ROC) method. A number of 150 regions of interest (ROIs) were selected to test the performance of our new CAD scheme. Each ROI contains either interphase cell or metaphase chromosomes. The results indicate that new scheme is able to achieve an area under the ROC curve (AUC) of 0.886+/-0.043. This investigation demonstrates that applying a deep learning technique may enable to significantly improve the accuracy of the metaphase chromosome detection using a scanning microscopic imaging technology in the future.

An automated multi-scale network-based scheme for detection and location of seismic sources

NASA Astrophysics Data System (ADS)

Poiata, N.; Aden-Antoniow, F.; Satriano, C.; Bernard, P.; Vilotte, J. P.; Obara, K.

2017-12-01

We present a recently developed method - BackTrackBB (Poiata et al. 2016) - allowing to image energy radiation from different seismic sources (e.g., earthquakes, LFEs, tremors) in different tectonic environments using continuous seismic records. The method exploits multi-scale frequency-selective coherence in the wave field, recorded by regional seismic networks or local arrays. The detection and location scheme is based on space-time reconstruction of the seismic sources through an imaging function built from the sum of station-pair time-delay likelihood functions, projected onto theoretical 3D time-delay grids. This imaging function is interpreted as the location likelihood of the seismic source. A signal pre-processing step constructs a multi-band statistical representation of the non stationary signal, i.e. time series, by means of higher-order statistics or energy envelope characteristic functions. Such signal-processing is designed to detect in time signal transients - of different scales and a priori unknown predominant frequency - potentially associated with a variety of sources (e.g., earthquakes, LFE, tremors), and to improve the performance and the robustness of the detection-and-location location step. The initial detection-location, based on a single phase analysis with the P- or S-phase only, can then be improved recursively in a station selection scheme. This scheme - exploiting the 3-component records - makes use of P- and S-phase characteristic functions, extracted after a polarization analysis of the event waveforms, and combines the single phase imaging functions with the S-P differential imaging functions. The performance of the method is demonstrated here in different tectonic environments: (1) analysis of the one year long precursory phase of 2014 Iquique earthquake in Chile; (2) detection and location of tectonic tremor sources and low-frequency earthquakes during the multiple episodes of tectonic tremor activity in southwestern Japan.

Salmonella enteritidis surveillance by egg immunology: impact of the sampling scheme on the release of contaminated table eggs.

PubMed

Klinkenberg, Don; Thomas, Ekelijn; Artavia, Francisco F Calvo; Bouma, Annemarie

2011-08-01

Design of surveillance programs to detect infections could benefit from more insight into sampling schemes. We address the effect of sampling schemes for Salmonella Enteritidis surveillance in laying hens. Based on experimental estimates for the transmission rate in flocks, and the characteristics of an egg immunological test, we have simulated outbreaks with various sampling schemes, and with the current boot swab program with a 15-week sampling interval. Declaring a flock infected based on a single positive egg was not possible because test specificity was too low. Thus, a threshold number of positive eggs was defined to declare a flock infected, and, for small sample sizes, eggs from previous samplings had to be included in a cumulative sample to guarantee a minimum flock level specificity. Effectiveness of surveillance was measured by the proportion of outbreaks detected, and by the number of contaminated table eggs brought on the market. The boot swab program detected 90% of the outbreaks, with 75% fewer contaminated eggs compared to no surveillance, whereas the baseline egg program (30 eggs each 15 weeks) detected 86%, with 73% fewer contaminated eggs. We conclude that a larger sample size results in more detected outbreaks, whereas a smaller sampling interval decreases the number of contaminated eggs. Decreasing sample size and interval simultaneously reduces the number of contaminated eggs, but not indefinitely: the advantage of more frequent sampling is counterbalanced by the cumulative sample including less recently laid eggs. Apparently, optimizing surveillance has its limits when test specificity is taken into account. © 2011 Society for Risk Analysis.

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

Autonomous Component Health Management with Failed Component Detection, Identification, and Avoidance

NASA Technical Reports Server (NTRS)

Davis, Robert N.; Polites, Michael E.; Trevino, Luis C.

2004-01-01

This paper details a novel scheme for autonomous component health management (ACHM) with failed actuator detection and failed sensor detection, identification, and avoidance. This new scheme has features that far exceed the performance of systems with triple-redundant sensing and voting, yet requires fewer sensors and could be applied to any system with redundant sensing. Relevant background to the ACHM scheme is provided, and the simulation results for the application of that scheme to a single-axis spacecraft attitude control system with a 3rd order plant and dual-redundant measurement of system states are presented. ACHM fulfills key functions needed by an integrated vehicle health monitoring (IVHM) system. It is: autonomous; adaptive; works in realtime; provides optimal state estimation; identifies failed components; avoids failed components; reconfigures for multiple failures; reconfigures for intermittent failures; works for hard-over, soft, and zero-output failures; and works for both open- and closed-loop systems. The ACHM scheme combines a prefilter that generates preliminary state estimates, detects and identifies failed sensors and actuators, and avoids the use of failed sensors in state estimation with a fixed-gain Kalman filter that generates optimal state estimates and provides model-based state estimates that comprise an integral part of the failure detection logic. The results show that ACHM successfully isolates multiple persistent and intermittent hard-over, soft, and zero-output failures. It is now ready to be tested on a computer model of an actual system.

Computer-aided detection and diagnosis of masses and clustered microcalcifications from digital mammograms

NASA Astrophysics Data System (ADS)

Nishikawa, Robert M.; Giger, Maryellen L.; Doi, Kunio; Vyborny, Carl J.; Schmidt, Robert A.; Metz, Charles E.; Wu, Chris Y.; Yin, Fang-Fang; Jiang, Yulei; Huo, Zhimin; Lu, Ping; Zhang, Wei; Ema, Takahiro; Bick, Ulrich; Papaioannou, John; Nagel, Rufus H.

1993-07-01

We are developing an 'intelligent' workstation to assist radiologists in diagnosing breast cancer from mammograms. The hardware for the workstation will consist of a film digitizer, a high speed computer, a large volume storage device, a film printer, and 4 high resolution CRT monitors. The software for the workstation is a comprehensive package of automated detection and classification schemes. Two rule-based detection schemes have been developed, one for breast masses and the other for clustered microcalcifications. The sensitivity of both schemes is 85% with a false-positive rate of approximately 3.0 and 1.5 false detections per image, for the mass and cluster detection schemes, respectively. Computerized classification is performed by an artificial neural network (ANN). The ANN has a sensitivity of 100% with a specificity of 60%. Currently, the ANN, which is a three-layer, feed-forward network, requires as input ratings of 14 different radiographic features of the mammogram that were determined subjectively by a radiologist. We are in the process of developing automated techniques to objectively determine these 14 features. The workstation will be placed in the clinical reading area of the radiology department in the near future, where controlled clinical tests will be performed to measure its efficacy.

The best prostate biopsy scheme is dictated by the gland volume: a monocentric study.

PubMed

Dell'Atti, L

2015-08-01

Accuracy of biopsy scheme depends on different parameters. Prostate-specific antigen (PSA) level and digital rectal examination (DRE) influenced the detection rate and suggested the biopsy scheme to approach each patient. Another parameter is the prostate volume. Sampling accuracy tends to decrease progressively with an increasing prostate volume. We prospectively observed detection cancer rate in suspicious prostate cancer (PCa) and improved by applying a protocol biopsy according to prostate volume (PV). Clinical data and pathological features of these 1356 patients were analysed and included in this study. This protocol is a combined scheme that includes transrectal (TR) 12-core PBx (TR12PBx) for PV ≤ 30 cc, TR 14-core PBx (TR14PBx) for PV > 30 cc but < 60 cc, TR 18-core PBx (TR18PBx) for PV ≥ 60 cc. Out of a total of 1356 patients, in 111 (8.2%) PCa was identified through TR12PBx scheme, in 198 (14.6%) through TR14PBx scheme and in 253 (18.6%) through TR18PBx scheme. The PCa detection rate was increased by 44% by adding two TZ cores (TR14PBx scheme). The TR18PBx scheme increased this rate by 21.7% vs. TR14PBx scheme. The diagnostic yield offered by TR18PBx was statistically significant compared to the detection rate offered by the TR14PBx scheme (p < 0.003). The biopsy Gleason score and the percentage of core involvement were comparable between PCa detected by the TR14PBx scheme diagnostic yield and those detected by the TR18PBx scheme (p = 0.362). The only PV parameter, in our opinion, can be significant in choosing the best biopsy scheme to approach in a first setting of biopsies increasing PCa detection rate.

Sensors with centroid-based common sensing scheme and their multiplexing

NASA Astrophysics Data System (ADS)

Berkcan, Ertugrul; Tiemann, Jerome J.; Brooksby, Glen W.

1993-03-01

The ability to multiplex sensors with different measurands but with a common sensing scheme is of importance in aircraft and aircraft engine applications; this unification of the sensors into a common interface has major implications for weight, cost, and reliability. A new class of sensors based on a common sensing scheme and their E/O Interface has been developed. The approach detects the location of the centroid of a beam of light; the set of fiber optic sensors with this sensing scheme include linear and rotary position, temperature, pressure, as well as duct Mach number. The sensing scheme provides immunity to intensity variations of the source or due to environmental effects on the fiber. A detector spatially multiplexed common electro-optic interface for the sensors has been demonstrated with a position and a temperature sensor.

Computer-aided detection of initial polyp candidates with level set-based adaptive convolution

NASA Astrophysics Data System (ADS)

Zhu, Hongbin; Duan, Chaijie; Liang, Zhengrong

2009-02-01

In order to eliminate or weaken the interference between different topological structures on the colon wall, adaptive and normalized convolution methods were used to compute the first and second order spatial derivatives of computed tomographic colonography images, which is the beginning of various geometric analyses. However, the performance of such methods greatly depends on the single-layer representation of the colon wall, which is called the starting layer (SL) in the following text. In this paper, we introduce a level set-based adaptive convolution (LSAC) method to compute the spatial derivatives, in which the level set method is employed to determine a more reasonable SL. The LSAC was applied to a computer-aided detection (CAD) scheme to detect the initial polyp candidates, and experiments showed that it benefits the CAD scheme in both the detection sensitivity and specificity as compared to our previous work.

MixDroid: A multi-features and multi-classifiers bagging system for Android malware detection

NASA Astrophysics Data System (ADS)

Huang, Weiqing; Hou, Erhang; Zheng, Liang; Feng, Weimiao

2018-05-01

In the past decade, Android platform has rapidly taken over the mobile market for its superior convenience and open source characteristics. However, with the popularity of Android, malwares targeting on Android devices are increasing rapidly, while the conventional rule-based and expert-experienced approaches are no longer able to handle such explosive growth. In this paper, combining with the theory of natural language processing and machine learning, we not only implement the basic feature extraction of permission application features, but also propose two innovative schemes of feature extraction: Dalvik opcode features and malicious code image, and implement an automatic Android malware detection system MixDroid which is based on multi-features and multi-classifiers. According to our experiment results on 20,000 Android applications, detection accuracy of MixDroid is 98.1%, which proves our schemes' effectiveness in Android malware detection.

A multistage approach to improve performance of computer-aided detection of pulmonary embolisms depicted on CT images: preliminary investigation.

PubMed

Park, Sang Cheol; Chapman, Brian E; Zheng, Bin

2011-06-01

This study developed a computer-aided detection (CAD) scheme for pulmonary embolism (PE) detection and investigated several approaches to improve CAD performance. In the study, 20 computed tomography examinations with various lung diseases were selected, which include 44 verified PE lesions. The proposed CAD scheme consists of five basic steps: 1) lung segmentation; 2) PE candidate extraction using an intensity mask and tobogganing region growing; 3) PE candidate feature extraction; 4) false-positive (FP) reduction using an artificial neural network (ANN); and 5) a multifeature-based k-nearest neighbor for positive/negative classification. In this study, we also investigated the following additional methods to improve CAD performance: 1) grouping 2-D detected features into a single 3-D object; 2) selecting features with a genetic algorithm (GA); and 3) limiting the number of allowed suspicious lesions to be cued in one examination. The results showed that 1) CAD scheme using tobogganing, an ANN, and grouping method achieved the maximum detection sensitivity of 79.2%; 2) the maximum scoring method achieved the superior performance over other scoring fusion methods; 3) GA was able to delete "redundant" features and further improve CAD performance; and 4) limiting the maximum number of cued lesions in an examination reduced FP rate by 5.3 times. Combining these approaches, CAD scheme achieved 63.2% detection sensitivity with 18.4 FP lesions per examination. The study suggested that performance of CAD schemes for PE detection depends on many factors that include 1) optimizing the 2-D region grouping and scoring methods; 2) selecting the optimal feature set; and 3) limiting the number of allowed cueing lesions per examination.

A New Optical Scheme for a Polarimetric-Based Glucose Sensor

NASA Technical Reports Server (NTRS)

Ansari, Rafat R.; Boeckle, Stefan; Rovati, Luigi; Salzman, Jack A. (Technical Monitor)

2002-01-01

We describe a new optical scheme to perform polarimetric measurements to detect glucose concentration in the aqueous humor of a model eye. The ultimate aim is to apply this technique in designing a new instrument for measuring glucose levels in diabetic patients routinely, frequently, and non-invasively. The scheme exploits the Brewsterreflection of circularly polarized light off of the lens of the eye. Theoretically, this backreflected linearly polarized light on its way to the detector is expected to rotate its state of polarization due to the presence of glucose molecules in the aqueous humor of patients. An experimental laboratory setup based on this scheme was designed and tested by measuring a range of known concentration of glucose solutions dissolved in water.

Development of online, continuous heavy metals detection and monitoring sensors based on microfluidic plasma reactors

NASA Astrophysics Data System (ADS)

Abdul-Majeed, Wameath Sh

This research is dedicated to develop a fully integrated system for heavy metals determination in water samples based on micro fluidic plasma atomizers. Several configurations of dielectric barrier discharge (DBD) atomizer are designed, fabricated and tested toward this target. Finally, a combination of annular and rectangular DBD atomizers has been utilized to develop a scheme for heavy metals determination. The present thesis has combined both theoretical and experimental investigations to fulfil the requirements. Several mathematical studies are implemented to explore the optimal design parameters for best system performance. On the other hand, expanded experimental explorations are conducted to assess the proposed operational approaches. The experiments were designed according to a central composite rotatable design; hence, an empirical model has been produced for each studied case. Moreover, several statistical approaches are adopted to analyse the system performance and to deduce the optimal operational parameters.. The introduction of the examined analyte to the plasma atomizer has been achieved by applying chemical schemes, where the element in the sample has been derivitized by using different kinds of reducing agents to produce vapour species (e.g. hydrides) for a group of nine elements examined in this research individually and simultaneously. Moreover, other derivatization schemes based on photochemical vapour generation assisted by ultrasound irradiation are also investigated. Generally speaking, the detection limits achieved in this research for the examined set of elements (by applying hydroborate scheme) are found to be acceptable in accordance with the standard limits in drinking water. The results of copper compared with the data from other technologies in the literature, showed a competitive detection limit obtained from applying the developed scheme, with an advantage of conducting simultaneous, fully automated, insitu, online- real time analysis as well as a possibility of connecting the proposed device to control loops..

A novel fully automatic scheme for fiducial marker-based alignment in electron tomography.

PubMed

Han, Renmin; Wang, Liansan; Liu, Zhiyong; Sun, Fei; Zhang, Fa

2015-12-01

Although the topic of fiducial marker-based alignment in electron tomography (ET) has been widely discussed for decades, alignment without human intervention remains a difficult problem. Specifically, the emergence of subtomogram averaging has increased the demand for batch processing during tomographic reconstruction; fully automatic fiducial marker-based alignment is the main technique in this process. However, the lack of an accurate method for detecting and tracking fiducial markers precludes fully automatic alignment. In this paper, we present a novel, fully automatic alignment scheme for ET. Our scheme has two main contributions: First, we present a series of algorithms to ensure a high recognition rate and precise localization during the detection of fiducial markers. Our proposed solution reduces fiducial marker detection to a sampling and classification problem and further introduces an algorithm to solve the parameter dependence of marker diameter and marker number. Second, we propose a novel algorithm to solve the tracking of fiducial markers by reducing the tracking problem to an incomplete point set registration problem. Because a global optimization of a point set registration occurs, the result of our tracking is independent of the initial image position in the tilt series, allowing for the robust tracking of fiducial markers without pre-alignment. The experimental results indicate that our method can achieve an accurate tracking, almost identical to the current best one in IMOD with half automatic scheme. Furthermore, our scheme is fully automatic, depends on fewer parameters (only requires a gross value of the marker diameter) and does not require any manual interaction, providing the possibility of automatic batch processing of electron tomographic reconstruction. Copyright © 2015 Elsevier Inc. All rights reserved.

Computerized scheme for detection of diffuse lung diseases on CR chest images

NASA Astrophysics Data System (ADS)

Pereira, Roberto R., Jr.; Shiraishi, Junji; Li, Feng; Li, Qiang; Doi, Kunio

2008-03-01

We have developed a new computer-aided diagnostic (CAD) scheme for detection of diffuse lung disease in computed radiographic (CR) chest images. One hundred ninety-four chest images (56 normals and 138 abnormals with diffuse lung diseases) were used. The 138 abnormal cases were classified into three levels of severity (34 mild, 60 moderate, and 44 severe) by an experienced chest radiologist with use of five different patterns, i.e., reticular, reticulonodular, nodular, air-space opacity, and emphysema. In our computerized scheme, the first moment of the power spectrum, the root-mean-square variation, and the average pixel value were determined for each region of interest (ROI), which was selected automatically in the lung fields. The average pixel value and its dependence on the location of the ROI were employed for identifying abnormal patterns due to air-space opacity or emphysema. A rule-based method was used for determining three levels of abnormality for each ROI (0: normal, 1: mild, 2: moderate, and 3: severe). The distinction between normal lungs and abnormal lungs with diffuse lung disease was determined based on the fractional number of abnormal ROIs by taking into account the severity of abnormalities. Preliminary results indicated that the area under the ROC curve was 0.889 for the 44 severe cases, 0.825 for the 104 severe and moderate cases, and 0.794 for all cases. We have identified a number of problems and reasons causing false positives on normal cases, and also false negatives on abnormal cases. In addition, we have discussed potential approaches for improvement of our CAD scheme. In conclusion, the CAD scheme for detection of diffuse lung diseases based on texture features extracted from CR chest images has the potential to assist radiologists in their interpretation of diffuse lung diseases.

Modeling and Detection of Ice Particle Accretion in Aircraft Engine Compression Systems

NASA Technical Reports Server (NTRS)

May, Ryan D.; Simon, Donald L.; Guo, Ten-Huei

2012-01-01

The accretion of ice particles in the core of commercial aircraft engines has been an ongoing aviation safety challenge. While no accidents have resulted from this phenomenon to date, numerous engine power loss events ranging from uneventful recoveries to forced landings have been recorded. As a first step to enabling mitigation strategies during ice accretion, a detection scheme must be developed that is capable of being implemented on board modern engines. In this paper, a simple detection scheme is developed and tested using a realistic engine simulation with approximate ice accretion models based on data from a compressor design tool. These accretion models are implemented as modified Low Pressure Compressor maps and have the capability to shift engine performance based on a specified level of ice blockage. Based on results from this model, it is possible to detect the accretion of ice in the engine core by observing shifts in the typical sensed engine outputs. Results are presented in which, for a 0.1 percent false positive rate, a true positive detection rate of 98 percent is achieved.

Novel MDM-PON scheme utilizing self-homodyne detection for high-speed/capacity access networks.

PubMed

Chen, Yuanxiang; Li, Juhao; Zhu, Paikun; Wu, Zhongying; Zhou, Peng; Tian, Yu; Ren, Fang; Yu, Jinyi; Ge, Dawei; Chen, Jingbiao; He, Yongqi; Chen, Zhangyuan

2015-12-14

In this paper, we propose a cost-effective, energy-saving mode-division-multiplexing passive optical network (MDM-PON) scheme utilizing self-homodyne detection for high-speed/capacity access network based on low modal-crosstalk few-mode fiber (FMF) and all-fiber mode multiplexer/demultiplexer (MUX/DEMUX). In the proposed scheme, one of the spatial modes is used to transmit a portion of signal carrier (namely pilot-tone) as the local oscillator (LO), while the others are used for signal-bearing channels. At the receiver, the pilot-tone and the signal can be separated without strong crosstalk and sent to the receiver for coherent detection. The spectral efficiency (SE) is significantly enhanced when multiple spatial channels are used. Meanwhile, the self-homodyne detection scheme can effectively suppress laser phase noise, which relaxes the requirement for the lasers line-width at the optical line terminal or optical network units (OLT/ONUs). The digital signal processing (DSP) at the receiver is also simplified since it removes the need for frequency offset compensation and complex phase correction, which reduces the computational complexity and energy consumption. Polarization division multiplexing (PDM) that offers doubled SE is also supported by the scheme. The proposed scheme is scalable to multi-wavelength application when wavelength MUX/DEMUX is utilized. Utilizing the proposed scheme, we demonstrate a proof of concept 4 × 40-Gb/s orthogonal frequency division multiplexing (OFDM) transmission over 55-km FMF using low modal-crosstalk two-mode FMF and MUX/DEMUX with error free operation. Compared with back to back case, less than 1-dB Q-factor penalty is observed after 55-km FMF of the four channels. Signal power and pilot-tone power are also optimized to achieve the optimal transmission performance.

Gas detection by correlation spectroscopy employing a multimode diode laser.

PubMed

Lou, Xiutao; Somesfalean, Gabriel; Zhang, Zhiguo

2008-05-01

A gas sensor based on the gas-correlation technique has been developed using a multimode diode laser (MDL) in a dual-beam detection scheme. Measurement of CO(2) mixed with CO as an interfering gas is successfully demonstrated using a 1570 nm tunable MDL. Despite overlapping absorption spectra and occasional mode hops, the interfering signals can be effectively excluded by a statistical procedure including correlation analysis and outlier identification. The gas concentration is retrieved from several pair-correlated signals by a linear-regression scheme, yielding a reliable and accurate measurement. This demonstrates the utility of the unsophisticated MDLs as novel light sources for gas detection applications.

In-TFT-Array-Process Micro Defect Inspection Using Nonlinear Principal Component Analysis

PubMed Central

Liu, Yi-Hung; Wang, Chi-Kai; Ting, Yung; Lin, Wei-Zhi; Kang, Zhi-Hao; Chen, Ching-Shun; Hwang, Jih-Shang

2009-01-01

Defect inspection plays a critical role in thin film transistor liquid crystal display (TFT-LCD) manufacture, and has received much attention in the field of automatic optical inspection (AOI). Previously, most focus was put on the problems of macro-scale Mura-defect detection in cell process, but it has recently been found that the defects which substantially influence the yield rate of LCD panels are actually those in the TFT array process, which is the first process in TFT-LCD manufacturing. Defect inspection in TFT array process is therefore considered a difficult task. This paper presents a novel inspection scheme based on kernel principal component analysis (KPCA) algorithm, which is a nonlinear version of the well-known PCA algorithm. The inspection scheme can not only detect the defects from the images captured from the surface of LCD panels, but also recognize the types of the detected defects automatically. Results, based on real images provided by a LCD manufacturer in Taiwan, indicate that the KPCA-based defect inspection scheme is able to achieve a defect detection rate of over 99% and a high defect classification rate of over 96% when the imbalanced support vector machine (ISVM) with 2-norm soft margin is employed as the classifier. More importantly, the inspection time is less than 1 s per input image. PMID:20057957

High-Order Residual-Distribution Schemes for Discontinuous Problems on Irregular Triangular Grids

NASA Technical Reports Server (NTRS)

Mazaheri, Alireza; Nishikawa, Hiroaki

2016-01-01

In this paper, we develop second- and third-order non-oscillatory shock-capturing hyperbolic residual distribution schemes for irregular triangular grids, extending our second- and third-order schemes to discontinuous problems. We present extended first-order N- and Rusanov-scheme formulations for hyperbolic advection-diffusion system, and demonstrate that the hyperbolic diffusion term does not affect the solution of inviscid problems for vanishingly small viscous coefficient. We then propose second- and third-order blended hyperbolic residual-distribution schemes with the extended first-order Rusanov-scheme. We show that these proposed schemes are extremely accurate in predicting non-oscillatory solutions for discontinuous problems. We also propose a characteristics-based nonlinear wave sensor for accurately detecting shocks, compression, and expansion regions. Using this proposed sensor, we demonstrate that the developed hyperbolic blended schemes do not produce entropy-violating solutions (unphysical stocks). We then verify the design order of accuracy of these blended schemes on irregular triangular grids.

Content-based unconstrained color logo and trademark retrieval with color edge gradient co-occurrence histograms

NASA Astrophysics Data System (ADS)

Phan, Raymond; Androutsos, Dimitrios

2008-01-01

In this paper, we present a logo and trademark retrieval system for unconstrained color image databases that extends the Color Edge Co-occurrence Histogram (CECH) object detection scheme. We introduce more accurate information to the CECH, by virtue of incorporating color edge detection using vector order statistics. This produces a more accurate representation of edges in color images, in comparison to the simple color pixel difference classification of edges as seen in the CECH. Our proposed method is thus reliant on edge gradient information, and as such, we call this the Color Edge Gradient Co-occurrence Histogram (CEGCH). We use this as the main mechanism for our unconstrained color logo and trademark retrieval scheme. Results illustrate that the proposed retrieval system retrieves logos and trademarks with good accuracy, and outperforms the CECH object detection scheme with higher precision and recall.

A new approach to develop computer-aided detection schemes of digital mammograms

NASA Astrophysics Data System (ADS)

Tan, Maxine; Qian, Wei; Pu, Jiantao; Liu, Hong; Zheng, Bin

2015-06-01

The purpose of this study is to develop a new global mammographic image feature analysis based computer-aided detection (CAD) scheme and evaluate its performance in detecting positive screening mammography examinations. A dataset that includes images acquired from 1896 full-field digital mammography (FFDM) screening examinations was used in this study. Among them, 812 cases were positive for cancer and 1084 were negative or benign. After segmenting the breast area, a computerized scheme was applied to compute 92 global mammographic tissue density based features on each of four mammograms of the craniocaudal (CC) and mediolateral oblique (MLO) views. After adding three existing popular risk factors (woman’s age, subjectively rated mammographic density, and family breast cancer history) into the initial feature pool, we applied a sequential forward floating selection feature selection algorithm to select relevant features from the bilateral CC and MLO view images separately. The selected CC and MLO view image features were used to train two artificial neural networks (ANNs). The results were then fused by a third ANN to build a two-stage classifier to predict the likelihood of the FFDM screening examination being positive. CAD performance was tested using a ten-fold cross-validation method. The computed area under the receiver operating characteristic curve was AUC = 0.779   ±   0.025 and the odds ratio monotonically increased from 1 to 31.55 as CAD-generated detection scores increased. The study demonstrated that this new global image feature based CAD scheme had a relatively higher discriminatory power to cue the FFDM examinations with high risk of being positive, which may provide a new CAD-cueing method to assist radiologists in reading and interpreting screening mammograms.

A malware detection scheme based on mining format information.

PubMed

Bai, Jinrong; Wang, Junfeng; Zou, Guozhong

2014-01-01

Malware has become one of the most serious threats to computer information system and the current malware detection technology still has very significant limitations. In this paper, we proposed a malware detection approach by mining format information of PE (portable executable) files. Based on in-depth analysis of the static format information of the PE files, we extracted 197 features from format information of PE files and applied feature selection methods to reduce the dimensionality of the features and achieve acceptable high performance. When the selected features were trained using classification algorithms, the results of our experiments indicate that the accuracy of the top classification algorithm is 99.1% and the value of the AUC is 0.998. We designed three experiments to evaluate the performance of our detection scheme and the ability of detecting unknown and new malware. Although the experimental results of identifying new malware are not perfect, our method is still able to identify 97.6% of new malware with 1.3% false positive rates.

A Malware Detection Scheme Based on Mining Format Information

PubMed Central

Bai, Jinrong; Wang, Junfeng; Zou, Guozhong

2014-01-01

Malware has become one of the most serious threats to computer information system and the current malware detection technology still has very significant limitations. In this paper, we proposed a malware detection approach by mining format information of PE (portable executable) files. Based on in-depth analysis of the static format information of the PE files, we extracted 197 features from format information of PE files and applied feature selection methods to reduce the dimensionality of the features and achieve acceptable high performance. When the selected features were trained using classification algorithms, the results of our experiments indicate that the accuracy of the top classification algorithm is 99.1% and the value of the AUC is 0.998. We designed three experiments to evaluate the performance of our detection scheme and the ability of detecting unknown and new malware. Although the experimental results of identifying new malware are not perfect, our method is still able to identify 97.6% of new malware with 1.3% false positive rates. PMID:24991639

FPGA design of correlation-based pattern recognition

NASA Astrophysics Data System (ADS)

Jridi, Maher; Alfalou, Ayman

2017-05-01

Optical/Digital pattern recognition and tracking based on optical/digital correlation are a well-known techniques to detect, identify and localize a target object in a scene. Despite the limited number of treatments required by the correlation scheme, computational time and resources are relatively high. The most computational intensive treatment required by the correlation is the transformation from spatial to spectral domain and then from spectral to spatial domain. Furthermore, these transformations are used on optical/digital encryption schemes like the double random phase encryption (DRPE). In this paper, we present a VLSI architecture for the correlation scheme based on the fast Fourier transform (FFT). One interesting feature of the proposed scheme is its ability to stream image processing in order to perform correlation for video sequences. A trade-off between the hardware consumption and the robustness of the correlation can be made in order to understand the limitations of the correlation implementation in reconfigurable and portable platforms. Experimental results obtained from HDL simulations and FPGA prototype have demonstrated the advantages of the proposed scheme.

A Computational Geometry Approach to Automated Pulmonary Fissure Segmentation in CT Examinations

PubMed Central

Pu, Jiantao; Leader, Joseph K; Zheng, Bin; Knollmann, Friedrich; Fuhrman, Carl; Sciurba, Frank C; Gur, David

2010-01-01

Identification of pulmonary fissures, which form the boundaries between the lobes in the lungs, may be useful during clinical interpretation of CT examinations to assess the early presence and characterization of manifestation of several lung diseases. Motivated by the unique nature of the surface shape of pulmonary fissures in three-dimensional space, we developed a new automated scheme using computational geometry methods to detect and segment fissures depicted on CT images. After a geometric modeling of the lung volume using the Marching Cube Algorithm, Laplacian smoothing is applied iteratively to enhance pulmonary fissures by depressing non-fissure structures while smoothing the surfaces of lung fissures. Next, an Extended Gaussian Image based procedure is used to locate the fissures in a statistical manner that approximates the fissures using a set of plane “patches.” This approach has several advantages such as independence of anatomic knowledge of the lung structure except the surface shape of fissures, limited sensitivity to other lung structures, and ease of implementation. The scheme performance was evaluated by two experienced thoracic radiologists using a set of 100 images (slices) randomly selected from 10 screening CT examinations. In this preliminary evaluation 98.7% and 94.9% of scheme segmented fissure voxels are within 2 mm of the fissures marked independently by two radiologists in the testing image dataset. Using the scheme detected fissures as reference, 89.4% and 90.1% of manually marked fissure points have distance ≤ 2 mm to the reference suggesting a possible under-segmentation of the scheme. The case-based RMS (root-mean-square) distances (“errors”) between our scheme and the radiologist ranged from 1.48±0.92 to 2.04±3.88 mm. The discrepancy of fissure detection results between the automated scheme and either radiologist is smaller in this dataset than the inter-reader variability. PMID:19272987

A Secure Dynamic Identity and Chaotic Maps Based User Authentication and Key Agreement Scheme for e-Healthcare Systems.

PubMed

Li, Chun-Ta; Lee, Cheng-Chi; Weng, Chi-Yao; Chen, Song-Jhih

2016-11-01

Secure user authentication schemes in many e-Healthcare applications try to prevent unauthorized users from intruding the e-Healthcare systems and a remote user and a medical server can establish session keys for securing the subsequent communications. However, many schemes does not mask the users' identity information while constructing a login session between two or more parties, even though personal privacy of users is a significant topic for e-Healthcare systems. In order to preserve personal privacy of users, dynamic identity based authentication schemes are hiding user's real identity during the process of network communications and only the medical server knows login user's identity. In addition, most of the existing dynamic identity based authentication schemes ignore the inputs verification during login condition and this flaw may subject to inefficiency in the case of incorrect inputs in the login phase. Regarding the use of secure authentication mechanisms for e-Healthcare systems, this paper presents a new dynamic identity and chaotic maps based authentication scheme and a secure data protection approach is employed in every session to prevent illegal intrusions. The proposed scheme can not only quickly detect incorrect inputs during the phases of login and password change but also can invalidate the future use of a lost/stolen smart card. Compared the functionality and efficiency with other authentication schemes recently, the proposed scheme satisfies desirable security attributes and maintains acceptable efficiency in terms of the computational overheads for e-Healthcare systems.

Surface Plasmon Enhanced Sensitive Detection for Possible Signature of Majorana Fermions via a Hybrid Semiconductor Quantum Dot-Metal Nanoparticle System

PubMed Central

Chen, Hua-Jun; Zhu, Ka-Di

2015-01-01

In the present work, we theoretically propose an optical scheme to detect the possible signature of Majorana fermions via the optical pump-probe spectroscopy, which is very different from the current tunneling measurement based on electrical methods. The scheme consists of a metal nanoparticle and a semiconductor quantum dot coupled to a hybrid semiconductor/superconductor heterostructures. The results show that the probe absorption spectrum of the quantum dot presents a distinct splitting due to the existence of Majorana fermions. Owing to surface plasmon enhanced effect, this splitting will be more obvious, which makes Majorana fermions more easy to be detectable. The technique proposed here open the door for new applications ranging from robust manipulation of Majorana fermions to quantum information processing based on Majorana fermions. PMID:26310929

Implementation of orthogonal frequency division multiplexing (OFDM) and advanced signal processing for elastic optical networking in accordance with networking and transmission constraints

NASA Astrophysics Data System (ADS)

Johnson, Stanley

An increasing adoption of digital signal processing (DSP) in optical fiber telecommunication has brought to the fore several interesting DSP enabled modulation formats. One such format is orthogonal frequency division multiplexing (OFDM), which has seen great success in wireless and wired RF applications, and is being actively investigated by several research groups for use in optical fiber telecom. In this dissertation, I present three implementations of OFDM for elastic optical networking and distributed network control. The first is a field programmable gate array (FPGA) based real-time implementation of a version of OFDM conventionally known as intensity modulation and direct detection (IMDD) OFDM. I experimentally demonstrate the ability of this transmission system to dynamically adjust bandwidth and modulation format to meet networking constraints in an automated manner. To the best of my knowledge, this is the first real-time software defined networking (SDN) based control of an OFDM system. In the second OFDM implementation, I experimentally demonstrate a novel OFDM transmission scheme that supports both direct detection and coherent detection receivers simultaneously using the same OFDM transmitter. This interchangeable receiver solution enables a trade-off between bit rate and equipment cost in network deployment and upgrades. I show that the proposed transmission scheme can provide a receiver sensitivity improvement of up to 1.73 dB as compared to IMDD OFDM. I also present two novel polarization analyzer based detection schemes, and study their performance using experiment and simulation. In the third implementation, I present an OFDM pilot-tone based scheme for distributed network control. The first instance of an SDN-based OFDM elastic optical network with pilot-tone assisted distributed control is demonstrated. An improvement in spectral efficiency and a fast reconfiguration time of 30 ms have been achieved in this experiment. Finally, I experimentally demonstrate optical re-timing of a 10.7 Gb/s data stream utilizing the property of bound soliton pairs (or "soliton molecules") to relax to an equilibrium temporal separation after propagation through a nonlinear dispersion alternating fiber span. Pulses offset up to 16 ps from bit center are successfully re-timed. The optical re-timing scheme studied here is a good example of signal processing in the optical domain and such a technique can overcome the bandwidth bottleneck present in DSP. An enhanced version of this re-timing scheme is analyzed using numerical simulations.

Automatic Detection of Lung and Liver Lesions in 3-D Positron Emission Tomography Images: A Pilot Study

NASA Astrophysics Data System (ADS)

Lartizien, Carole; Marache-Francisco, Simon; Prost, Rémy

2012-02-01

Positron emission tomography (PET) using fluorine-18 deoxyglucose (18F-FDG) has become an increasingly recommended tool in clinical whole-body oncology imaging for the detection, diagnosis, and follow-up of many cancers. One way to improve the diagnostic utility of PET oncology imaging is to assist physicians facing difficult cases of residual or low-contrast lesions. This study aimed at evaluating different schemes of computer-aided detection (CADe) systems for the guided detection and localization of small and low-contrast lesions in PET. These systems are based on two supervised classifiers, linear discriminant analysis (LDA) and the nonlinear support vector machine (SVM). The image feature sets that serve as input data consisted of the coefficients of an undecimated wavelet transform. An optimization study was conducted to select the best combination of parameters for both the SVM and the LDA. Different false-positive reduction (FPR) methods were evaluated to reduce the number of false-positive detections per image (FPI). This includes the removal of small detected clusters and the combination of the LDA and SVM detection maps. The different CAD schemes were trained and evaluated based on a simulated whole-body PET image database containing 250 abnormal cases with 1230 lesions and 250 normal cases with no lesion. The detection performance was measured on a separate series of 25 testing images with 131 lesions. The combination of the LDA and SVM score maps was shown to produce very encouraging detection performance for both the lung lesions, with 91% sensitivity and 18 FPIs, and the liver lesions, with 94% sensitivity and 10 FPIs. Comparison with human performance indicated that the different CAD schemes significantly outperformed human detection sensitivities, especially regarding the low-contrast lesions.

Coded excitation for infrared non-destructive testing of carbon fiber reinforced plastics.

PubMed

Mulaveesala, Ravibabu; Venkata Ghali, Subbarao

2011-05-01

This paper proposes a Barker coded excitation for defect detection using infrared non-destructive testing. Capability of the proposed excitation scheme is highlighted with recently introduced correlation based post processing approach and compared with the existing phase based analysis by taking the signal to noise ratio into consideration. Applicability of the proposed scheme has been experimentally validated on a carbon fiber reinforced plastic specimen containing flat bottom holes located at different depths.

Fault-tolerant Greenberger-Horne-Zeilinger paradox based on non-Abelian anyons.

PubMed

Deng, Dong-Ling; Wu, Chunfeng; Chen, Jing-Ling; Oh, C H

2010-08-06

We propose a scheme to test the Greenberger-Horne-Zeilinger paradox based on braidings of non-Abelian anyons, which are exotic quasiparticle excitations of topological states of matter. Because topological ordered states are robust against local perturbations, this scheme is in some sense "fault-tolerant" and might close the detection inefficiency loophole problem in previous experimental tests of the Greenberger-Horne-Zeilinger paradox. In turn, the construction of the Greenberger-Horne-Zeilinger paradox reveals the nonlocal property of non-Abelian anyons. Our results indicate that the non-Abelian fractional statistics is a pure quantum effect and cannot be described by local realistic theories. Finally, we present a possible experimental implementation of the scheme based on the anyonic interferometry technologies.

A hybrid deep learning approach to predict malignancy of breast lesions using mammograms

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Heidari, Morteza; Mirniaharikandehei, Seyedehnafiseh; Gong, Jing; Qian, Wei; Qiu, Yuchen; Zheng, Bin

2018-03-01

Applying deep learning technology to medical imaging informatics field has been recently attracting extensive research interest. However, the limited medical image dataset size often reduces performance and robustness of the deep learning based computer-aided detection and/or diagnosis (CAD) schemes. In attempt to address this technical challenge, this study aims to develop and evaluate a new hybrid deep learning based CAD approach to predict likelihood of a breast lesion detected on mammogram being malignant. In this approach, a deep Convolutional Neural Network (CNN) was firstly pre-trained using the ImageNet dataset and serve as a feature extractor. A pseudo-color Region of Interest (ROI) method was used to generate ROIs with RGB channels from the mammographic images as the input to the pre-trained deep network. The transferred CNN features from different layers of the CNN were then obtained and a linear support vector machine (SVM) was trained for the prediction task. By applying to a dataset involving 301 suspicious breast lesions and using a leave-one-case-out validation method, the areas under the ROC curves (AUC) = 0.762 and 0.792 using the traditional CAD scheme and the proposed deep learning based CAD scheme, respectively. An ensemble classifier that combines the classification scores generated by the two schemes yielded an improved AUC value of 0.813. The study results demonstrated feasibility and potentially improved performance of applying a new hybrid deep learning approach to develop CAD scheme using a relatively small dataset of medical images.

Indirect Z-Scheme BiOI/g-C3N4 Photocatalysts with Enhanced Photoreduction CO2 Activity under Visible Light Irradiation.

PubMed

Wang, Ji-Chao; Yao, Hong-Chang; Fan, Ze-Yu; Zhang, Lin; Wang, Jian-She; Zang, Shuang-Quan; Li, Zhong-Jun

2016-02-17

Rational design and construction of Z-scheme photocatalysts has received much attention in the field of CO2 reduction because of its great potential to solve the current energy and environmental crises. In this study, a series of Z-scheme BiOI/g-C3N4 photocatalysts are synthesized and their photocatalytic performance for CO2 reduction to produce CO, H2 and/or CH4 is evaluated under visible light irradiation (λ > 400 nm). The results show that the as-synthesized composites exhibit more highly efficient photocatalytic activity than pure g-C3N4 and BiOI and that the product yields change remarkably depending on the reaction conditions such as irradiation light wavelength. Emphasis is placed on identifying how the charge transfers across the heterojunctions and an indirect Z-scheme charge transfer mechanism is verified by detecting the intermediate I3(-) ions. The reaction mechanism is further proposed based on the detection of the intermediate (•)OH and H2O2. This work may be useful for rationally designing of new types of Z-scheme photocatalyst and provide some illuminating insights into the Z-scheme transfer mechanism.

Optical sensors for application in intelligent food-packaging technology

NASA Astrophysics Data System (ADS)

McEvoy, Aisling K.; Von Bueltzingsloewen, Christoph; McDonagh, Colette M.; MacCraith, Brian D.; Klimant, Ingo; Wolfbeis, Otto S.

2003-03-01

Modified Atmosphere Packaged (MAP) food employs a protective gas mixture, which normally contains selected amounts of carbon dioxide (CO2) and oxygen (O2), in order to extend the shelf life of food. Conventional MAP analysis of package integrity involves destructive sampling of packages followed by carbon dioxide and oxygen detection. For quality control reasons, as well as to enhance food safety, the concept of optical on-pack sensors for monitoring the gas composition of the MAP package at different stages of the distribution process is very attractive. The objective of this work was to develop printable formulations of oxygen and carbon dioxide sensors for use in food packaging. Oxygen sensing is achieved by detecting the degree of quenching of a fluorescent ruthenium complex entrapped in a sol-gel matrix. In particular, a measurement technique based on the quenching of the fluorescence decay time, phase fluorometric detection, is employed. A scheme for detecting CO2 has been developed which is compatible with the oxygen detection scheme. It is fluorescence-based and uses the pH-sensitive 8-hydroxypyrene-1,3,6-trisulfonic acid (HPTS) indicator dye encapsulated in an organically modified silica (ORMOSIL) glass matrix. Dual Luminophore Referencing (DLR) has been employed as an internal referencing scheme, which provides many of the advantages of lifetime-based fluorometric methods. Oxygen cross-sensitivity was minimised by encapsulating the reference luminophore in dense sol-gel microspheres. The sensor performance compared well with standard methods for both oxygen and carbon dioxide detection. The results of preliminary on-pack print trials are presented and a preliminary design of an integrated dual gas optical read-out device is discussed.

Tracking Virus Particles in Fluorescence Microscopy Images Using Multi-Scale Detection and Multi-Frame Association.

PubMed

Jaiswal, Astha; Godinez, William J; Eils, Roland; Lehmann, Maik Jorg; Rohr, Karl

2015-11-01

Automatic fluorescent particle tracking is an essential task to study the dynamics of a large number of biological structures at a sub-cellular level. We have developed a probabilistic particle tracking approach based on multi-scale detection and two-step multi-frame association. The multi-scale detection scheme allows coping with particles in close proximity. For finding associations, we have developed a two-step multi-frame algorithm, which is based on a temporally semiglobal formulation as well as spatially local and global optimization. In the first step, reliable associations are determined for each particle individually in local neighborhoods. In the second step, the global spatial information over multiple frames is exploited jointly to determine optimal associations. The multi-scale detection scheme and the multi-frame association finding algorithm have been combined with a probabilistic tracking approach based on the Kalman filter. We have successfully applied our probabilistic tracking approach to synthetic as well as real microscopy image sequences of virus particles and quantified the performance. We found that the proposed approach outperforms previous approaches.

A Negative Selection Immune System Inspired Methodology for Fault Diagnosis of Wind Turbines.

PubMed

Alizadeh, Esmaeil; Meskin, Nader; Khorasani, Khashayar

2017-11-01

High operational and maintenance costs represent as major economic constraints in the wind turbine (WT) industry. These concerns have made investigation into fault diagnosis of WT systems an extremely important and active area of research. In this paper, an immune system (IS) inspired methodology for performing fault detection and isolation (FDI) of a WT system is proposed and developed. The proposed scheme is based on a self nonself discrimination paradigm of a biological IS. Specifically, the negative selection mechanism [negative selection algorithm (NSA)] of the human body is utilized. In this paper, a hierarchical bank of NSAs are designed to detect and isolate both individual as well as simultaneously occurring faults common to the WTs. A smoothing moving window filter is then utilized to further improve the reliability and performance of the FDI scheme. Moreover, the performance of our proposed scheme is compared with another state-of-the-art data-driven technique, namely the support vector machines (SVMs) to demonstrate and illustrate the superiority and advantages of our proposed NSA-based FDI scheme. Finally, a nonparametric statistical comparison test is implemented to evaluate our proposed methodology with that of the SVM under various fault severities.

A soft computing scheme incorporating ANN and MOV energy in fault detection, classification and distance estimation of EHV transmission line with FSC.

PubMed

Khadke, Piyush; Patne, Nita; Singh, Arvind; Shinde, Gulab

2016-01-01

In this article, a novel and accurate scheme for fault detection, classification and fault distance estimation for a fixed series compensated transmission line is proposed. The proposed scheme is based on artificial neural network (ANN) and metal oxide varistor (MOV) energy, employing Levenberg-Marquardt training algorithm. The novelty of this scheme is the use of MOV energy signals of fixed series capacitors (FSC) as input to train the ANN. Such approach has never been used in any earlier fault analysis algorithms in the last few decades. Proposed scheme uses only single end measurement energy signals of MOV in all the 3 phases over one cycle duration from the occurrence of a fault. Thereafter, these MOV energy signals are fed as input to ANN for fault distance estimation. Feasibility and reliability of the proposed scheme have been evaluated for all ten types of fault in test power system model at different fault inception angles over numerous fault locations. Real transmission system parameters of 3-phase 400 kV Wardha-Aurangabad transmission line (400 km) with 40 % FSC at Power Grid Wardha Substation, India is considered for this research. Extensive simulation experiments show that the proposed scheme provides quite accurate results which demonstrate complete protection scheme with high accuracy, simplicity and robustness.

Data acquisition and path selection decision making for an autonomous roving vehicle. [laser pointing control system for vehicle guidance

NASA Technical Reports Server (NTRS)

Shen, C. N.; YERAZUNIS

1979-01-01

The feasibility of using range/pointing angle data such as might be obtained by a laser rangefinder for the purpose of terrain evaluation in the 10-40 meter range on which to base the guidance of an autonomous rover was investigated. The decision procedure of the rapid estimation scheme for the detection of discrete obstacles has been modified to reinforce the detection ability. With the introduction of the logarithmic scanning scheme and obstacle identification scheme, previously developed algorithms are combined to demonstrate the overall performance of the intergrated route designation system using laser rangefinder. In an attempt to cover a greater range, 30 m to 100 mm, the problem estimating gradients in the presence of positioning angle noise at middle range is investigated.

Sea-Based Infrared Scene Interpretation by Background Type Classification and Coastal Region Detection for Small Target Detection

PubMed Central

Kim, Sungho

2015-01-01

Sea-based infrared search and track (IRST) is important for homeland security by detecting missiles and asymmetric boats. This paper proposes a novel scheme to interpret various infrared scenes by classifying the infrared background types and detecting the coastal regions in omni-directional images. The background type or region-selective small infrared target detector should be deployed to maximize the detection rate and to minimize the number of false alarms. A spatial filter-based small target detector is suitable for identifying stationary incoming targets in remote sea areas with sky only. Many false detections can occur if there is an image sector containing a coastal region, due to ground clutter and the difficulty in finding true targets using the same spatial filter-based detector. A temporal filter-based detector was used to handle these problems. Therefore, the scene type and coastal region information is critical to the success of IRST in real-world applications. In this paper, the infrared scene type was determined using the relationships between the sensor line-of-sight (LOS) and a horizontal line in an image. The proposed coastal region detector can be activated if the background type of the probing sector is determined to be a coastal region. Coastal regions can be detected by fusing the region map and curve map. The experimental results on real infrared images highlight the feasibility of the proposed sea-based scene interpretation. In addition, the effects of the proposed scheme were analyzed further by applying region-adaptive small target detection. PMID:26404308

CAD scheme for detection of hemorrhages and exudates in ocular fundus images

NASA Astrophysics Data System (ADS)

Hatanaka, Yuji; Nakagawa, Toshiaki; Hayashi, Yoshinori; Mizukusa, Yutaka; Fujita, Akihiro; Kakogawa, Masakatsu; Kawase, Kazuhide; Hara, Takeshi; Fujita, Hiroshi

2007-03-01

This paper describes a method for detecting hemorrhages and exudates in ocular fundus images. The detection of hemorrhages and exudates is important in order to diagnose diabetic retinopathy. Diabetic retinopathy is one of the most significant factors contributing to blindness, and early detection and treatment are important. In this study, hemorrhages and exudates were automatically detected in fundus images without using fluorescein angiograms. Subsequently, the blood vessel regions incorrectly detected as hemorrhages were eliminated by first examining the structure of the blood vessels and then evaluating the length-to-width ratio. Finally, the false positives were eliminated by checking the following features extracted from candidate images: the number of pixels, contrast, 13 features calculated from the co-occurrence matrix, two features based on gray-level difference statistics, and two features calculated from the extrema method. The sensitivity of detecting hemorrhages in the fundus images was 85% and that of detecting exudates was 77%. Our fully automated scheme could accurately detect hemorrhages and exudates.

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

Gur, Sourav; Frantziskonis, George N.; Univ. of Arizona, Tucson, AZ

Here, we report results from a numerical study of multi-time-scale bistable dynamics for CO oxidation on a catalytic surface in a flowing, well-mixed gas stream. The problem is posed in terms of surface and gas-phase submodels that dynamically interact in the presence of stochastic perturbations, reflecting the impact of molecular-scale fluctuations on the surface and turbulence in the gas. Wavelet-based methods are used to encode and characterize the temporal dynamics produced by each submodel and detect the onset of sudden state shifts (bifurcations) caused by nonlinear kinetics. When impending state shifts are detected, a more accurate but computationally expensive integrationmore » scheme can be used. This appears to make it possible, at least in some cases, to decrease the net computational burden associated with simulating multi-time-scale, nonlinear reacting systems by limiting the amount of time in which the more expensive integration schemes are required. Critical to achieving this is being able to detect unstable temporal transitions such as the bistable shifts in the example problem considered here. Lastly, our results indicate that a unique wavelet-based algorithm based on the Lipschitz exponent is capable of making such detections, even under noisy conditions, and may find applications in critical transition detection problems beyond catalysis.« less

Application of Wavelet-Based Methods for Accelerating Multi-Time-Scale Simulation of Bistable Heterogeneous Catalysis

DOE PAGES

Gur, Sourav; Frantziskonis, George N.; Univ. of Arizona, Tucson, AZ; ...

2017-02-16

Here, we report results from a numerical study of multi-time-scale bistable dynamics for CO oxidation on a catalytic surface in a flowing, well-mixed gas stream. The problem is posed in terms of surface and gas-phase submodels that dynamically interact in the presence of stochastic perturbations, reflecting the impact of molecular-scale fluctuations on the surface and turbulence in the gas. Wavelet-based methods are used to encode and characterize the temporal dynamics produced by each submodel and detect the onset of sudden state shifts (bifurcations) caused by nonlinear kinetics. When impending state shifts are detected, a more accurate but computationally expensive integrationmore » scheme can be used. This appears to make it possible, at least in some cases, to decrease the net computational burden associated with simulating multi-time-scale, nonlinear reacting systems by limiting the amount of time in which the more expensive integration schemes are required. Critical to achieving this is being able to detect unstable temporal transitions such as the bistable shifts in the example problem considered here. Lastly, our results indicate that a unique wavelet-based algorithm based on the Lipschitz exponent is capable of making such detections, even under noisy conditions, and may find applications in critical transition detection problems beyond catalysis.« less

Coupling photochemical reaction detection based on singlet oxygen sensitization to capillary electrochromatography

PubMed

Dickson; Odom; Ducheneaux; Murray; Milofsky

2000-07-15

Despite the impressive separation efficiency afforded by capillary electrochromatography (CEC), the detection of UV-absorbing compounds following separation in capillary dimensions remains limited by the short path length (5-75 microm) through the column. Moreover, analytes that are poor chromophores present an additional challenge with respect to sensitive detection in CEC. This paper illustrates a new photochemical reaction detection scheme for CEC that takes advantage of the catalytic nature of type II photooxidation reactions. The sensitive detection scheme is selective toward molecules capable of photosensitizing the formation of singlet molecular oxygen (1O2). Following separation by CEC, UV-absorbing analytes promote groundstate 3O2 to an excited state (1O2) which reacts rapidly with tert-butyl-3,4,5-trimethylpyrrolecarboxylate, which is added to the running buffer. Detection is based on the loss of pyrrole. The reaction is catalytic in nature since one analyte molecule may absorb light many times, producing large amounts of 1O2. The detection limit for 9-acetylanthracene, following separation by CEC, is approximately 6 x 10(-9) M (S/N = 3). Optimization of the factors effecting the S/N for four model compounds is discussed.

New optical scheme for a polarimetric-based glucose sensor

NASA Technical Reports Server (NTRS)

Ansari, Rafat R.; Bockle, Stefan; Rovati, Luigi

2004-01-01

A new optical scheme to detect glucose concentration in the aqueous humor of the eye is presented. The ultimate aim is to apply this technique in designing a new instrument for, routinely and frequently, noninvasively monitoring blood glucose levels in diabetic patients without contact (no index matching) between the eye and the instrument. The optical scheme exploits the Brewster reflection of circularly polarized light off of the lens of the eye. Theoretically, this reflected linearly polarized light on its way to the detector is expected to rotate its state of polarization, owing to the presence of glucose molecules in the aqueous humor of a patient's eye. An experimental laboratory setup based on this scheme was designed and tested by measuring a range of known concentrations of glucose solutions dissolved in water. (c) 2004 Society of Photo-Optical Instrumentation Engineers.

Quantum teleportation with atoms trapped in cavities

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

Cho, Jaeyoon; Lee, Hai-Woong

2004-09-01

We propose a scheme to implement the quantum teleportation protocol with single atoms trapped in cavities. The scheme is based on the adiabatic passage and the polarization measurement. We show that it is possible to teleport the internal state of an atom trapped in a cavity to an atom trapped in another cavity with the success probability of 1/2 and the fidelity of 1. The scheme is resistant to a number of considerable imperfections such as the violation of the Lamb-Dicke condition, weak atom-cavity coupling, spontaneous emission, and detection inefficiency.

LSB-Based Steganography Using Reflected Gray Code

NASA Astrophysics Data System (ADS)

Chen, Chang-Chu; Chang, Chin-Chen

Steganography aims to hide secret data into an innocuous cover-medium for transmission and to make the attacker cannot recognize the presence of secret data easily. Even the stego-medium is captured by the eavesdropper, the slight distortion is hard to be detected. The LSB-based data hiding is one of the steganographic methods, used to embed the secret data into the least significant bits of the pixel values in a cover image. In this paper, we propose an LSB-based scheme using reflected-Gray code, which can be applied to determine the embedded bit from secret information. Following the transforming rule, the LSBs of stego-image are not always equal to the secret bits and the experiment shows that the differences are up to almost 50%. According to the mathematical deduction and experimental results, the proposed scheme has the same image quality and payload as the simple LSB substitution scheme. In fact, our proposed data hiding scheme in the case of G1 (one bit Gray code) system is equivalent to the simple LSB substitution scheme.

A fully-automated multiscale kernel graph cuts based particle localization scheme for temporal focusing two-photon microscopy

NASA Astrophysics Data System (ADS)

Huang, Xia; Li, Chunqiang; Xiao, Chuan; Sun, Wenqing; Qian, Wei

2017-03-01

The temporal focusing two-photon microscope (TFM) is developed to perform depth resolved wide field fluorescence imaging by capturing frames sequentially. However, due to strong nonignorable noises and diffraction rings surrounding particles, further researches are extremely formidable without a precise particle localization technique. In this paper, we developed a fully-automated scheme to locate particles positions with high noise tolerance. Our scheme includes the following procedures: noise reduction using a hybrid Kalman filter method, particle segmentation based on a multiscale kernel graph cuts global and local segmentation algorithm, and a kinematic estimation based particle tracking method. Both isolated and partial-overlapped particles can be accurately identified with removal of unrelated pixels. Based on our quantitative analysis, 96.22% isolated particles and 84.19% partial-overlapped particles were successfully detected.

MIMO transmit scheme based on morphological perceptron with competitive learning.

PubMed

Valente, Raul Ambrozio; Abrão, Taufik

2016-08-01

This paper proposes a new multi-input multi-output (MIMO) transmit scheme aided by artificial neural network (ANN). The morphological perceptron with competitive learning (MP/CL) concept is deployed as a decision rule in the MIMO detection stage. The proposed MIMO transmission scheme is able to achieve double spectral efficiency; hence, in each time-slot the receiver decodes two symbols at a time instead one as Alamouti scheme. Other advantage of the proposed transmit scheme with MP/CL-aided detector is its polynomial complexity according to modulation order, while it becomes linear when the data stream length is greater than modulation order. The performance of the proposed scheme is compared to the traditional MIMO schemes, namely Alamouti scheme and maximum-likelihood MIMO (ML-MIMO) detector. Also, the proposed scheme is evaluated in a scenario with variable channel information along the frame. Numerical results have shown that the diversity gain under space-time coding Alamouti scheme is partially lost, which slightly reduces the bit-error rate (BER) performance of the proposed MP/CL-NN MIMO scheme. Copyright © 2016 Elsevier Ltd. All rights reserved.

A hybrid robust fault tolerant control based on adaptive joint unscented Kalman filter.

PubMed

Shabbouei Hagh, Yashar; Mohammadi Asl, Reza; Cocquempot, Vincent

2017-01-01

In this paper, a new hybrid robust fault tolerant control scheme is proposed. A robust H ∞ control law is used in non-faulty situation, while a Non-Singular Terminal Sliding Mode (NTSM) controller is activated as soon as an actuator fault is detected. Since a linear robust controller is designed, the system is first linearized through the feedback linearization method. To switch from one controller to the other, a fuzzy based switching system is used. An Adaptive Joint Unscented Kalman Filter (AJUKF) is used for fault detection and diagnosis. The proposed method is based on the simultaneous estimation of the system states and parameters. In order to show the efficiency of the proposed scheme, a simulated 3-DOF robotic manipulator is used. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Rate adaptive multilevel coded modulation with high coding gain in intensity modulation direct detection optical communication

NASA Astrophysics Data System (ADS)

Xiao, Fei; Liu, Bo; Zhang, Lijia; Xin, Xiangjun; Zhang, Qi; Tian, Qinghua; Tian, Feng; Wang, Yongjun; Rao, Lan; Ullah, Rahat; Zhao, Feng; Li, Deng'ao

2018-02-01

A rate-adaptive multilevel coded modulation (RA-MLC) scheme based on fixed code length and a corresponding decoding scheme is proposed. RA-MLC scheme combines the multilevel coded and modulation technology with the binary linear block code at the transmitter. Bits division, coding, optional interleaving, and modulation are carried out by the preset rule, then transmitted through standard single mode fiber span equal to 100 km. The receiver improves the accuracy of decoding by means of soft information passing through different layers, which enhances the performance. Simulations are carried out in an intensity modulation-direct detection optical communication system using MATLAB®. Results show that the RA-MLC scheme can achieve bit error rate of 1E-5 when optical signal-to-noise ratio is 20.7 dB. It also reduced the number of decoders by 72% and realized 22 rate adaptation without significantly increasing the computing time. The coding gain is increased by 7.3 dB at BER=1E-3.

APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels

NASA Astrophysics Data System (ADS)

Klüser, L.; Killius, N.; Gesell, G.

2015-10-01

The cloud processing scheme APOLLO (AVHRR Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. It builds upon the physical principles that have served well in the original APOLLO scheme. Nevertheless, a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is no longer performed as a binary yes/no decision based on these physical principles. It is rather expressed as cloud probability for each satellite pixel. Consequently, the outcome of the algorithm can be tuned from being sure to reliably identify clear pixels to conditions of reliably identifying definitely cloudy pixels, depending on the purpose. The probabilistic approach allows retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for application to large amounts of historical satellite data. The radiative transfer solution is approximated by the same two-stream approach which also had been used for the original APOLLO. This allows the algorithm to be applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e., within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from NOAA-18 are presented.

Bayesian cloud detection for MERIS, AATSR, and their combination

NASA Astrophysics Data System (ADS)

Hollstein, A.; Fischer, J.; Carbajal Henken, C.; Preusker, R.

2015-04-01

A broad range of different of Bayesian cloud detection schemes is applied to measurements from the Medium Resolution Imaging Spectrometer (MERIS), the Advanced Along-Track Scanning Radiometer (AATSR), and their combination. The cloud detection schemes were designed to be numerically efficient and suited for the processing of large numbers of data. Results from the classical and naive approach to Bayesian cloud masking are discussed for MERIS and AATSR as well as for their combination. A sensitivity study on the resolution of multidimensional histograms, which were post-processed by Gaussian smoothing, shows how theoretically insufficient numbers of truth data can be used to set up accurate classical Bayesian cloud masks. Sets of exploited features from single and derived channels are numerically optimized and results for naive and classical Bayesian cloud masks are presented. The application of the Bayesian approach is discussed in terms of reproducing existing algorithms, enhancing existing algorithms, increasing the robustness of existing algorithms, and on setting up new classification schemes based on manually classified scenes.

Distributed dynamic strain measurement using long-gauge FBG and DTR3 interrogator based on delayed transmission/reflection ratiometric reflectometry

NASA Astrophysics Data System (ADS)

Nishiyama, M.; Igawa, H.; Kasai, T.; Watanabe, N.

2013-09-01

In this paper, we reveal characteristics of static and dynamic distributed strain measurement using a long-gauge fiber Bragg grating (FBG) and a Delayed Transmission/Reflection Ratiometric Reflectometry (DTR3) scheme. The DTR3 scheme has capability of detecting distributed strain using the long-gauge FBG with 50-cm spatial resolution. Additionally, dynamic strain measurement can be achieved using this technique in 100-Hz sampling rate. We evaluated strain sensing characteristics of the long-gauge FBG attached on 2.5-m aluminum bar by a four-point bending equipment. Experimental results showed that the DTR3 using the long-gauge FBG could detect distributed strain in static tests and resonance frequency of structure in free vibration tests. As a result, it is suggested that the DTR3 scheme using the longgauge FBG is attractive to structural health monitoring (SHM) as dynamic deformation detection of a few and tensmeters structure such as the airplane wing and the helicopter blade.

Convective and microphysics parameterization impact on simulating heavy rainfall in Semarang (case study on February 12th, 2015)

NASA Astrophysics Data System (ADS)

Faridatussafura, Nurzaka; Wandala, Agie

2018-05-01

The meteorological model WRF-ARW version 3.8.1 is used for simulating the heavy rainfall in Semarang that occurred on February 12th, 2015. Two different convective schemes and two different microphysics scheme in a nested configuration were chosen. The sensitivity of those schemes in capturing the extreme weather event has been tested. GFS data were used for the initial and boundary condition. Verification on the twenty-four hours accumulated rainfall using GSMaPsatellite data shows that Kain-Fritsch convective scheme and Lin microphysics scheme is the best combination scheme among the others. The combination also gives the highest success ratio value in placing high intensity rainfall area. Based on the ROC diagram, KF-Lin shows the best performance in detecting high intensity rainfall. However, the combination still has high bias value.

High-resolution multi-code implementation of unsteady Navier-Stokes flow solver based on paralleled overset adaptive mesh refinement and high-order low-dissipation hybrid schemes

NASA Astrophysics Data System (ADS)

Li, Gaohua; Fu, Xiang; Wang, Fuxin

2017-10-01

The low-dissipation high-order accurate hybrid up-winding/central scheme based on fifth-order weighted essentially non-oscillatory (WENO) and sixth-order central schemes, along with the Spalart-Allmaras (SA)-based delayed detached eddy simulation (DDES) turbulence model, and the flow feature-based adaptive mesh refinement (AMR), are implemented into a dual-mesh overset grid infrastructure with parallel computing capabilities, for the purpose of simulating vortex-dominated unsteady detached wake flows with high spatial resolutions. The overset grid assembly (OGA) process based on collection detection theory and implicit hole-cutting algorithm achieves an automatic coupling for the near-body and off-body solvers, and the error-and-try method is used for obtaining a globally balanced load distribution among the composed multiple codes. The results of flows over high Reynolds cylinder and two-bladed helicopter rotor show that the combination of high-order hybrid scheme, advanced turbulence model, and overset adaptive mesh refinement can effectively enhance the spatial resolution for the simulation of turbulent wake eddies.

Pseudo-coherent demodulation for mobile satellite systems

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Simon, Marvin K.

1993-01-01

This paper proposes three so-called pseudo-coherent demodulation schemes for use in land mobile satellite channels. The schemes are derived based on maximum likelihood (ML) estimation and detection of an N-symbol observation of the received signal. Simulation results for all three demodulators are presented to allow comparison with the performance of differential PSK (DPSK) and ideal coherent demodulation for various system parameter sets of practical interest.

An Anonymous User Authentication and Key Agreement Scheme Based on a Symmetric Cryptosystem in Wireless Sensor Networks.

PubMed

Jung, Jaewook; Kim, Jiye; Choi, Younsung; Won, Dongho

2016-08-16

In wireless sensor networks (WSNs), a registered user can login to the network and use a user authentication protocol to access data collected from the sensor nodes. Since WSNs are typically deployed in unattended environments and sensor nodes have limited resources, many researchers have made considerable efforts to design a secure and efficient user authentication process. Recently, Chen et al. proposed a secure user authentication scheme using symmetric key techniques for WSNs. They claim that their scheme assures high efficiency and security against different types of attacks. After careful analysis, however, we find that Chen et al.'s scheme is still vulnerable to smart card loss attack and is susceptible to denial of service attack, since it is invalid for verification to simply compare an entered ID and a stored ID in smart card. In addition, we also observe that their scheme cannot preserve user anonymity. Furthermore, their scheme cannot quickly detect an incorrect password during login phase, and this flaw wastes both communication and computational overheads. In this paper, we describe how these attacks work, and propose an enhanced anonymous user authentication and key agreement scheme based on a symmetric cryptosystem in WSNs to address all of the aforementioned vulnerabilities in Chen et al.'s scheme. Our analysis shows that the proposed scheme improves the level of security, and is also more efficient relative to other related schemes.

Statistical-Mechanics-Inspired Optimization of Sensor Field Configuration for Detection of Mobile Targets (PREPRINT)

DTIC Science & Technology

2010-11-01

pected target motion. Along this line, Wettergren [5] analyzed the performance of the track - before - detect schemes for the sensor networks. Furthermore...dressed by Baumgartner and Ferrari [11] for the reorganization of the sensor field to achieve the maximum coverage. The track - before - detect -based optimal...confirming a target. In accordance with the track - before - detect paradigm [4], a moving target is detected if the kd (typically kd = 3 or 4) sensors detect

Design of short-range terahertz wave passive detecting system

NASA Astrophysics Data System (ADS)

Zhang, Chao; Lou, Guowei; Zhu, Li; Qian, Songsong; Li, Ting

2016-09-01

Based on the study of radiation and transmission characteristics on THz waveband, a short-range passive detecting system is designed. The scheme originated from microwave passive detecting system. A prototype was developed following the design of key components including antennas and a harmonic mixer. The system operated at 0.36 THz. A dual-beam Cassegrain antenna was adopted for receiving signals which radiated by object and background. Local oscillator signal was generated by frequency multiplication. Harmonic mixing is adopted for reducing local oscillator signal frequency required by half. Superheterodyne technology is employed for signal acquisition. The system implemented easily. Tests and measurements were taken, which showed that the scheme was feasible and the performance of the prototype system met the design requirements.

Automated detection of retinal nerve fiber layer defects on fundus images: false positive reduction based on vessel likelihood

NASA Astrophysics Data System (ADS)

Muramatsu, Chisako; Ishida, Kyoko; Sawada, Akira; Hatanaka, Yuji; Yamamoto, Tetsuya; Fujita, Hiroshi

2016-03-01

Early detection of glaucoma is important to slow down or cease progression of the disease and for preventing total blindness. We have previously proposed an automated scheme for detection of retinal nerve fiber layer defect (NFLD), which is one of the early signs of glaucoma observed on retinal fundus images. In this study, a new multi-step detection scheme was included to improve detection of subtle and narrow NFLDs. In addition, new features were added to distinguish between NFLDs and blood vessels, which are frequent sites of false positives (FPs). The result was evaluated with a new test dataset consisted of 261 cases, including 130 cases with NFLDs. Using the proposed method, the initial detection rate was improved from 82% to 98%. At the sensitivity of 80%, the number of FPs per image was reduced from 4.25 to 1.36. The result indicates the potential usefulness of the proposed method for early detection of glaucoma.

A reliable transmission protocol for ZigBee-based wireless patient monitoring.

PubMed

Chen, Shyr-Kuen; Kao, Tsair; Chan, Chia-Tai; Huang, Chih-Ning; Chiang, Chih-Yen; Lai, Chin-Yu; Tung, Tse-Hua; Wang, Pi-Chung

2012-01-01

Patient monitoring systems are gaining their importance as the fast-growing global elderly population increases demands for caretaking. These systems use wireless technologies to transmit vital signs for medical evaluation. In a multihop ZigBee network, the existing systems usually use broadcast or multicast schemes to increase the reliability of signals transmission; however, both the schemes lead to significantly higher network traffic and end-to-end transmission delay. In this paper, we present a reliable transmission protocol based on anycast routing for wireless patient monitoring. Our scheme automatically selects the closest data receiver in an anycast group as a destination to reduce the transmission latency as well as the control overhead. The new protocol also shortens the latency of path recovery by initiating route recovery from the intermediate routers of the original path. On the basis of a reliable transmission scheme, we implement a ZigBee device for fall monitoring, which integrates fall detection, indoor positioning, and ECG monitoring. When the triaxial accelerometer of the device detects a fall, the current position of the patient is transmitted to an emergency center through a ZigBee network. In order to clarify the situation of the fallen patient, 4-s ECG signals are also transmitted. Our transmission scheme ensures the successful transmission of these critical messages. The experimental results show that our scheme is fast and reliable. We also demonstrate that our devices can seamlessly integrate with the next generation technology of wireless wide area network, worldwide interoperability for microwave access, to achieve real-time patient monitoring.

Parametric Amplification For Detecting Weak Optical Signals

NASA Technical Reports Server (NTRS)

Hemmati, Hamid; Chen, Chien; Chakravarthi, Prakash

1996-01-01

Optical-communication receivers of proposed type implement high-sensitivity scheme of optical parametric amplification followed by direct detection for reception of extremely weak signals. Incorporates both optical parametric amplification and direct detection into optimized design enhancing effective signal-to-noise ratios during reception in photon-starved (photon-counting) regime. Eliminates need for complexity of heterodyne detection scheme and partly overcomes limitations imposed on older direct-detection schemes by noise generated in receivers and by limits on quantum efficiencies of photodetectors.

Reduction of false-positives in a CAD scheme for automated detection of architectural distortion in digital mammography

NASA Astrophysics Data System (ADS)

de Oliveira, Helder C. R.; Mencattini, Arianna; Casti, Paola; Martinelli, Eugenio; di Natale, Corrado; Catani, Juliana H.; de Barros, Nestor; Melo, Carlos F. E.; Gonzaga, Adilson; Vieira, Marcelo A. C.

2018-02-01

This paper proposes a method to reduce the number of false-positives (FP) in a computer-aided detection (CAD) scheme for automated detection of architectural distortion (AD) in digital mammography. AD is a subtle contraction of breast parenchyma that may represent an early sign of breast cancer. Due to its subtlety and variability, AD is more difficult to detect compared to microcalcifications and masses, and is commonly found in retrospective evaluations of false-negative mammograms. Several computer-based systems have been proposed for automated detection of AD in breast images. The usual approach is automatically detect possible sites of AD in a mammographic image (segmentation step) and then use a classifier to eliminate the false-positives and identify the suspicious regions (classification step). This paper focus on the optimization of the segmentation step to reduce the number of FPs that is used as input to the classifier. The proposal is to use statistical measurements to score the segmented regions and then apply a threshold to select a small quantity of regions that should be submitted to the classification step, improving the detection performance of a CAD scheme. We evaluated 12 image features to score and select suspicious regions of 74 clinical Full-Field Digital Mammography (FFDM). All images in this dataset contained at least one region with AD previously marked by an expert radiologist. The results showed that the proposed method can reduce the false positives of the segmentation step of the CAD scheme from 43.4 false positives (FP) per image to 34.5 FP per image, without increasing the number of false negatives.

A cloud detection scheme for the Chinese Carbon Dioxide Observation Satellite (TANSAT)

NASA Astrophysics Data System (ADS)

Wang, Xi; Guo, Zheng; Huang, Yipeng; Fan, Hongjie; Li, Wanbiao

2017-01-01

Cloud detection is an essential preprocessing step for retrieving carbon dioxide from satellite observations of reflected sunlight. During the pre-launch study of the Chinese Carbon Dioxide Observation Satellite (TANSAT), a cloud-screening scheme was presented for the Cloud and Aerosol Polarization Imager (CAPI), which only performs measurements in five channels located in the visible to near-infrared regions of the spectrum. The scheme for CAPI, based on previous cloudscreening algorithms, defines a method to regroup individual threshold tests for each pixel in a scene according to the derived clear confidence level. This scheme is proven to be more effective for sensors with few channels. The work relies upon the radiance data from the Visible and Infrared Radiometer (VIRR) onboard the Chinese FengYun-3A Polar-orbiting Meteorological Satellite (FY-3A), which uses four wavebands similar to that of CAPI and can serve as a proxy for its measurements. The scheme has been applied to a number of the VIRR scenes over four target areas (desert, snow, ocean, forest) for all seasons. To assess the screening results, comparisons against the cloud-screening product from MODIS are made. The evaluation suggests that the proposed scheme inherits the advantages of schemes described in previous publications and shows improved cloud-screening results. A seasonal analysis reveals that this scheme provides better performance during warmer seasons, except for observations over oceans, where results are much better in colder seasons.

Adaptive skin detection based on online training

NASA Astrophysics Data System (ADS)

Zhang, Ming; Tang, Liang; Zhou, Jie; Rong, Gang

2007-11-01

Skin is a widely used cue for porn image classification. Most conventional methods are off-line training schemes. They usually use a fixed boundary to segment skin regions in the images and are effective only in restricted conditions: e.g. good lightness and unique human race. This paper presents an adaptive online training scheme for skin detection which can handle these tough cases. In our approach, skin detection is considered as a classification problem on Gaussian mixture model. For each image, human face is detected and the face color is used to establish a primary estimation of skin color distribution. Then an adaptive online training algorithm is used to find the real boundary between skin color and background color in current image. Experimental results on 450 images showed that the proposed method is more robust in general situations than the conventional ones.

Quantum Watermarking Scheme Based on INEQR

NASA Astrophysics Data System (ADS)

Zhou, Ri-Gui; Zhou, Yang; Zhu, Changming; Wei, Lai; Zhang, Xiafen; Ian, Hou

2018-04-01

Quantum watermarking technology protects copyright by embedding invisible quantum signal in quantum multimedia data. In this paper, a watermarking scheme based on INEQR was presented. Firstly, the watermark image is extended to achieve the requirement of embedding carrier image. Secondly, the swap and XOR operation is used on the processed pixels. Since there is only one bit per pixel, XOR operation can achieve the effect of simple encryption. Thirdly, both the watermark image extraction and embedding operations are described, where the key image, swap operation and LSB algorithm are used. When the embedding is made, the binary image key is changed. It means that the watermark has been embedded. Of course, if the watermark image is extracted, the key's state need detected. When key's state is |1>, this extraction operation is carried out. Finally, for validation of the proposed scheme, both the Signal-to-noise ratio (PSNR) and the security of the scheme are analyzed.

Surface based detection schemes for molecular interferometry experiments - implications and possible applications

NASA Astrophysics Data System (ADS)

Juffmann, Thomas; Milic, Adriana; Muellneritsch, Michael; Arndt, Markus

2011-03-01

Surface based detection schemes for molecular interferometry experiments might be crucial in the search for the quantum properties of larger and larger objects since they provide single particle sensitivity. Here we report on molecular interferograms of different biomolecules imaged using fluorescence microscopy. Being able to watch the build-up of an interferogram live and in situ reveals the matter-wave behavior of these complex molecules in an unprecedented way. We examine several problems encountered due to van-der-Waals forces between the molecules and the diffraction grating and discuss possible ways to circumvent these. Especially the advent of ultra-thin (1-100 atomic layers) diffraction masks might path the way towards molecular holography. We also discuss other possible applications such as coherent molecular microscopy.

Improving the in-flight security by employing seat occupancy sensors based on Fiber Bragg grating technology

NASA Astrophysics Data System (ADS)

Zhang, Hongtao; Wang, Pengfei

2012-06-01

The current schemes of detecting the status of passengers in airplanes cannot satisfy the more strict regulations recently released by the United States Transportation Security Administration. In basis of investigation on the current seat occupancy sensors for vehicles, in this paper we present a novel scheme of seat occupancy sensors based on Fiber Bragg Grating technology to improve the in-flight security of airplanes. This seat occupancy sensor system can be used to detect the status of passengers and to trigger the airbags to control the inflation of air bags, which have been installed in the airplanes of some major airlines under the new law. This scheme utilizes our previous research results of Weight-In- Motion sensor system based on optical fiber Bragg grating. In contrast to the current seat occupancy sensors for vehicles, this new seat occupancy sensor has so many merits that it is very suitable to be applied in aerospace industry or high speed railway system. Moreover, combined with existing Fiber Bragg Grating strain or temperature sensor systems built in airplanes, this proposed method can construct a complete airline passenger management system.

A complete passive blind image copy-move forensics scheme based on compound statistics features.

PubMed

Peng, Fei; Nie, Yun-ying; Long, Min

2011-10-10

Since most sensor pattern noise based image copy-move forensics methods require a known reference sensor pattern noise, it generally results in non-blinded passive forensics, which significantly confines the application circumstances. In view of this, a novel passive-blind image copy-move forensics scheme is proposed in this paper. Firstly, a color image is transformed into a grayscale one, and wavelet transform based de-noising filter is used to extract the sensor pattern noise, then the variance of the pattern noise, the signal noise ratio between the de-noised image and the pattern noise, the information entropy and the average energy gradient of the original grayscale image are chosen as features, non-overlapping sliding window operations are done to the images to divide them into different sub-blocks. Finally, the tampered areas are detected by analyzing the correlation of the features between the sub-blocks and the whole image. Experimental results and analysis show that the proposed scheme is completely passive-blind, has a good detection rate, and is robust against JPEG compression, noise, rotation, scaling and blurring. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

New-Sum: A Novel Online ABFT Scheme For General Iterative Methods

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

Tao, Dingwen; Song, Shuaiwen; Krishnamoorthy, Sriram

Emerging high-performance computing platforms, with large component counts and lower power margins, are anticipated to be more susceptible to soft errors in both logic circuits and memory subsystems. We present an online algorithm-based fault tolerance (ABFT) approach to efficiently detect and recover soft errors for general iterative methods. We design a novel checksum-based encoding scheme for matrix-vector multiplication that is resilient to both arithmetic and memory errors. Our design decouples the checksum updating process from the actual computation, and allows adaptive checksum overhead control. Building on this new encoding mechanism, we propose two online ABFT designs that can effectively recovermore » from errors when combined with a checkpoint/rollback scheme.« less

Blind ICA detection based on second-order cone programming for MC-CDMA systems

NASA Astrophysics Data System (ADS)

Jen, Chih-Wei; Jou, Shyh-Jye

2014-12-01

The multicarrier code division multiple access (MC-CDMA) technique has received considerable interest for its potential application to future wireless communication systems due to its high data rate. A common problem regarding the blind multiuser detectors used in MC-CDMA systems is that they are extremely sensitive to the complex channel environment. Besides, the perturbation of colored noise may negatively affect the performance of the system. In this paper, a new coherent detection method will be proposed, which utilizes the modified fast independent component analysis (FastICA) algorithm, based on approximate negentropy maximization that is subject to the second-order cone programming (SOCP) constraint. The aim of the proposed coherent detection is to provide robustness against small-to-medium channel estimation mismatch (CEM) that may arise from channel frequency response estimation error in the MC-CDMA system, which is modulated by downlink binary phase-shift keying (BPSK) under colored noise. Noncoherent demodulation schemes are preferable to coherent demodulation schemes, as the latter are difficult to implement over time-varying fading channels. Differential phase-shift keying (DPSK) is therefore the natural choice for an alternative modulation scheme. Furthermore, the new blind differential SOCP-based ICA (SOCP-ICA) detection without channel estimation and compensation will be proposed to combat Doppler spread caused by time-varying fading channels in the DPSK-modulated MC-CDMA system under colored noise. In this paper, numerical simulations are used to illustrate the robustness of the proposed blind coherent SOCP-ICA detector against small-to-medium CEM and to emphasize the advantage of the blind differential SOCP-ICA detector in overcoming Doppler spread.

A recurrent neural-network-based sensor and actuator fault detection and isolation for nonlinear systems with application to the satellite's attitude control subsystem.

PubMed

Talebi, H A; Khorasani, K; Tafazoli, S

2009-01-01

This paper presents a robust fault detection and isolation (FDI) scheme for a general class of nonlinear systems using a neural-network-based observer strategy. Both actuator and sensor faults are considered. The nonlinear system considered is subject to both state and sensor uncertainties and disturbances. Two recurrent neural networks are employed to identify general unknown actuator and sensor faults, respectively. The neural network weights are updated according to a modified backpropagation scheme. Unlike many previous methods developed in the literature, our proposed FDI scheme does not rely on availability of full state measurements. The stability of the overall FDI scheme in presence of unknown sensor and actuator faults as well as plant and sensor noise and uncertainties is shown by using the Lyapunov's direct method. The stability analysis developed requires no restrictive assumptions on the system and/or the FDI algorithm. Magnetorquer-type actuators and magnetometer-type sensors that are commonly employed in the attitude control subsystem (ACS) of low-Earth orbit (LEO) satellites for attitude determination and control are considered in our case studies. The effectiveness and capabilities of our proposed fault diagnosis strategy are demonstrated and validated through extensive simulation studies.

A new cooperative MIMO scheme based on SM for energy-efficiency improvement in wireless sensor network.

PubMed

Peng, Yuyang; Choi, Jaeho

2014-01-01

Improving the energy efficiency in wireless sensor networks (WSN) has attracted considerable attention nowadays. The multiple-input multiple-output (MIMO) technique has been proved as a good candidate for improving the energy efficiency, but it may not be feasible in WSN which is due to the size limitation of the sensor node. As a solution, the cooperative multiple-input multiple-output (CMIMO) technique overcomes this constraint and shows a dramatically good performance. In this paper, a new CMIMO scheme based on the spatial modulation (SM) technique named CMIMO-SM is proposed for energy-efficiency improvement. We first establish the system model of CMIMO-SM. Based on this model, the transmission approach is introduced graphically. In order to evaluate the performance of the proposed scheme, a detailed analysis in terms of energy consumption per bit of the proposed scheme compared with the conventional CMIMO is presented. Later, under the guide of this new scheme we extend our proposed CMIMO-SM to a multihop clustered WSN for further achieving energy efficiency by finding an optimal hop-length. Equidistant hop as the traditional scheme will be compared in this paper. Results from the simulations and numerical experiments indicate that by the use of the proposed scheme, significant savings in terms of total energy consumption can be achieved. Combining the proposed scheme with monitoring sensor node will provide a good performance in arbitrary deployed WSN such as forest fire detection system.

A Novel Technique to Detect Code for SAC-OCDMA System

NASA Astrophysics Data System (ADS)

Bharti, Manisha; Kumar, Manoj; Sharma, Ajay K.

2018-04-01

The main task of optical code division multiple access (OCDMA) system is the detection of code used by a user in presence of multiple access interference (MAI). In this paper, new method of detection known as XOR subtraction detection for spectral amplitude coding OCDMA (SAC-OCDMA) based on double weight codes has been proposed and presented. As MAI is the main source of performance deterioration in OCDMA system, therefore, SAC technique is used in this paper to eliminate the effect of MAI up to a large extent. A comparative analysis is then made between the proposed scheme and other conventional detection schemes used like complimentary subtraction detection, AND subtraction detection and NAND subtraction detection. The system performance is characterized by Q-factor, BER and received optical power (ROP) with respect to input laser power and fiber length. The theoretical and simulation investigations reveal that the proposed detection technique provides better quality factor, security and received power in comparison to other conventional techniques. The wide opening of eye in case of proposed technique also proves its robustness.

Quantum-Enhanced Sensing Based on Time Reversal of Nonlinear Dynamics.

PubMed

Linnemann, D; Strobel, H; Muessel, W; Schulz, J; Lewis-Swan, R J; Kheruntsyan, K V; Oberthaler, M K

2016-07-01

We experimentally demonstrate a nonlinear detection scheme exploiting time-reversal dynamics that disentangles continuous variable entangled states for feasible readout. Spin-exchange dynamics of Bose-Einstein condensates is used as the nonlinear mechanism which not only generates entangled states but can also be time reversed by controlled phase imprinting. For demonstration of a quantum-enhanced measurement we construct an active atom SU(1,1) interferometer, where entangled state preparation and nonlinear readout both consist of parametric amplification. This scheme is capable of exhausting the quantum resource by detecting solely mean atom numbers. Controlled nonlinear transformations widen the spectrum of useful entangled states for applied quantum technologies.

Train integrity detection risk analysis based on PRISM

NASA Astrophysics Data System (ADS)

Wen, Yuan

2018-04-01

GNSS based Train Integrity Monitoring System (TIMS) is an effective and low-cost detection scheme for train integrity detection. However, as an external auxiliary system of CTCS, GNSS may be influenced by external environments, such as uncertainty of wireless communication channels, which may lead to the failure of communication and positioning. In order to guarantee the reliability and safety of train operation, a risk analysis method of train integrity detection based on PRISM is proposed in this article. First, we analyze the risk factors (in GNSS communication process and the on-board communication process) and model them. Then, we evaluate the performance of the model in PRISM based on the field data. Finally, we discuss how these risk factors influence the train integrity detection process.

An efficient fully unsupervised video object segmentation scheme using an adaptive neural-network classifier architecture.

PubMed

Doulamis, A; Doulamis, N; Ntalianis, K; Kollias, S

2003-01-01

In this paper, an unsupervised video object (VO) segmentation and tracking algorithm is proposed based on an adaptable neural-network architecture. The proposed scheme comprises: 1) a VO tracking module and 2) an initial VO estimation module. Object tracking is handled as a classification problem and implemented through an adaptive network classifier, which provides better results compared to conventional motion-based tracking algorithms. Network adaptation is accomplished through an efficient and cost effective weight updating algorithm, providing a minimum degradation of the previous network knowledge and taking into account the current content conditions. A retraining set is constructed and used for this purpose based on initial VO estimation results. Two different scenarios are investigated. The first concerns extraction of human entities in video conferencing applications, while the second exploits depth information to identify generic VOs in stereoscopic video sequences. Human face/ body detection based on Gaussian distributions is accomplished in the first scenario, while segmentation fusion is obtained using color and depth information in the second scenario. A decision mechanism is also incorporated to detect time instances for weight updating. Experimental results and comparisons indicate the good performance of the proposed scheme even in sequences with complicated content (object bending, occlusion).

Post-processing for improving hyperspectral anomaly detection accuracy

NASA Astrophysics Data System (ADS)

Wu, Jee-Cheng; Jiang, Chi-Ming; Huang, Chen-Liang

2015-10-01

Anomaly detection is an important topic in the exploitation of hyperspectral data. Based on the Reed-Xiaoli (RX) detector and a morphology operator, this research proposes a novel technique for improving the accuracy of hyperspectral anomaly detection. Firstly, the RX-based detector is used to process a given input scene. Then, a post-processing scheme using morphology operator is employed to detect those pixels around high-scoring anomaly pixels. Tests were conducted using two real hyperspectral images with ground truth information and the results based on receiver operating characteristic curves, illustrated that the proposed method reduced the false alarm rates of the RXbased detector.

Selective determination of arginine-containing and tyrosine-containing peptides using capillary electrophoresis and laser-induced fluorescence detection.

PubMed

Cobb, K A; Novotny, M V

1992-01-01

The use of two different amino acid-selective fluorogenic reagents for the derivatization of peptides is investigated. One such scheme utilizes a selective reaction of benzoin with the guanidine moiety to derivatize arginine residues occurring in a peptide. The second scheme involves the formylation of tyrosine, followed by reaction with 4-methoxy-1,2-phenylenediamine. The use of capillary electrophoresis and laser-induced fluorescence detection allows enhanced efficiencies and sensitivities to be obtained for the separations of either arginine- or tyrosine-containing peptides. A helium-cadmium laser (325 nm) is ideally suited for the laser-based detection system due to a close match of the excitation maxima of derivatized peptides from both reactions. A detection limit of 270 amol is achieved for model arginine-containing peptides, while the detection limit for model tyrosine-containing peptides is measured at 390 amol. Both derivatization reactions are found to be useful for high-sensitivity peptide mapping applications in which only the peptides containing the derivatized amino acids are detected.

An LMS Programming Scheme and Floating-Gate Technology Enabled Trimmer-Less and Low Voltage Flame Detection Sensor.

PubMed

Iglesias-Rojas, Juan Carlos; Gomez-Castañeda, Felipe; Moreno-Cadenas, Jose Antonio

2017-06-14

In this paper, a Least Mean Square (LMS) programming scheme is used to set the offset voltage of two operational amplifiers that were built using floating-gate transistors, enabling a 0.95 V RMS trimmer-less flame detection sensor. The programming scheme is capable of setting the offset voltage over a wide range of values by means of electron injection. The flame detection sensor consists of two programmable offset operational amplifiers; the first amplifier serves as a 26 μV offset voltage follower, whereas the second amplifier acts as a programmable trimmer-less voltage comparator. Both amplifiers form the proposed sensor, whose principle of functionality is based on the detection of the electrical changes produced by the flame ionization. The experimental results show that it is possible to measure the presence of a flame accurately after programming the amplifiers with a maximum of 35 LMS-algorithm iterations. Current commercial flame detectors are mainly used in absorption refrigerators and large industrial gas heaters, where a high voltage AC source and several mechanical trimmings are used in order to accurately measure the presence of the flame.

An LMS Programming Scheme and Floating-Gate Technology Enabled Trimmer-Less and Low Voltage Flame Detection Sensor

PubMed Central

Iglesias-Rojas, Juan Carlos; Gomez-Castañeda, Felipe; Moreno-Cadenas, Jose Antonio

2017-01-01

In this paper, a Least Mean Square (LMS) programming scheme is used to set the offset voltage of two operational amplifiers that were built using floating-gate transistors, enabling a 0.95 VRMS trimmer-less flame detection sensor. The programming scheme is capable of setting the offset voltage over a wide range of values by means of electron injection. The flame detection sensor consists of two programmable offset operational amplifiers; the first amplifier serves as a 26 μV offset voltage follower, whereas the second amplifier acts as a programmable trimmer-less voltage comparator. Both amplifiers form the proposed sensor, whose principle of functionality is based on the detection of the electrical changes produced by the flame ionization. The experimental results show that it is possible to measure the presence of a flame accurately after programming the amplifiers with a maximum of 35 LMS-algorithm iterations. Current commercial flame detectors are mainly used in absorption refrigerators and large industrial gas heaters, where a high voltage AC source and several mechanical trimmings are used in order to accurately measure the presence of the flame. PMID:28613250

Photooxidation of 3-substituted pyrroles:  a postcolumn reaction detection system for singlet molecular oxygen in HPLC.

PubMed

Denham, K; Milofsky, R E

1998-10-01

A postcolumn photochemical reaction detection scheme, based on the reaction of 3-substituted pyrroles with singlet molecular oxygen ((1)O(2)), has been developed. The method is selective and sensitive for the determination of a class of organic compounds called (1)O(2)-sensitizers and is readily coupled to HPLC. Following separation by HPLC, analytes ((1)O(2)-sensitizers) are excited by a Hg pen-ray lamp. Analytes that are efficient (1)O(2)-sensitizers promote ground-state O(2) ((3)Σ(g)(-)) to an excited state ((1)Σ(g)(+) or (1)Δ(g)), which reacts rapidly with tert-butyl-3,4,5-trimethylpyrrolecarboxylate (BTMPC) or N-benzyl-3-methoxypyrrole-2-tert-carboxylate (BMPC), which is added to the mobile phase. Detection is based on the loss of pyrrole (BTMPC or BMPC). The reaction is catalytic in nature since one analyte molecule may absorb light many times, producing large amounts of (1)O(2). Detection limits for several (1)O(2)-sensitizers were improved by 1-2 orders of magnitude over optimized UV-absorbance detection. This paper discusses the optimization of the reaction conditions for this photochemical reaction detection scheme and its application to the detection of PCBs, nitrogen heterocycles, nitro and chloro aromatics, and other substituted aromatic compounds.

Automated detection of masses on whole breast volume ultrasound scanner: false positive reduction using deep convolutional neural network

NASA Astrophysics Data System (ADS)

Hiramatsu, Yuya; Muramatsu, Chisako; Kobayashi, Hironobu; Hara, Takeshi; Fujita, Hiroshi

2017-03-01

Breast cancer screening with mammography and ultrasonography is expected to improve sensitivity compared with mammography alone, especially for women with dense breast. An automated breast volume scanner (ABVS) provides the operator-independent whole breast data which facilitate double reading and comparison with past exams, contralateral breast, and multimodality images. However, large volumetric data in screening practice increase radiologists' workload. Therefore, our goal is to develop a computer-aided detection scheme of breast masses in ABVS data for assisting radiologists' diagnosis and comparison with mammographic findings. In this study, false positive (FP) reduction scheme using deep convolutional neural network (DCNN) was investigated. For training DCNN, true positive and FP samples were obtained from the result of our initial mass detection scheme using the vector convergence filter. Regions of interest including the detected regions were extracted from the multiplanar reconstraction slices. We investigated methods to select effective FP samples for training the DCNN. Based on the free response receiver operating characteristic analysis, simple random sampling from the entire candidates was most effective in this study. Using DCNN, the number of FPs could be reduced by 60%, while retaining 90% of true masses. The result indicates the potential usefulness of DCNN for FP reduction in automated mass detection on ABVS images.

Performance evaluation of an automatic segmentation method of cerebral arteries in MRA images by use of a large image database

NASA Astrophysics Data System (ADS)

Uchiyama, Yoshikazu; Asano, Tatsunori; Hara, Takeshi; Fujita, Hiroshi; Kinosada, Yasutomi; Asano, Takahiko; Kato, Hiroki; Kanematsu, Masayuki; Hoshi, Hiroaki; Iwama, Toru

2009-02-01

The detection of cerebrovascular diseases such as unruptured aneurysm, stenosis, and occlusion is a major application of magnetic resonance angiography (MRA). However, their accurate detection is often difficult for radiologists. Therefore, several computer-aided diagnosis (CAD) schemes have been developed in order to assist radiologists with image interpretation. The purpose of this study was to develop a computerized method for segmenting cerebral arteries, which is an essential component of CAD schemes. For the segmentation of vessel regions, we first used a gray level transformation to calibrate voxel values. To adjust for variations in the positioning of patients, registration was subsequently employed to maximize the overlapping of the vessel regions in the target image and reference image. The vessel regions were then segmented from the background using gray-level thresholding and region growing techniques. Finally, rule-based schemes with features such as size, shape, and anatomical location were employed to distinguish between vessel regions and false positives. Our method was applied to 854 clinical cases obtained from two different hospitals. The segmentation of cerebral arteries in 97.1%(829/854) of the MRA studies was attained as an acceptable result. Therefore, our computerized method would be useful in CAD schemes for the detection of cerebrovascular diseases in MRA images.

An improved parameter estimation scheme for image modification detection based on DCT coefficient analysis.

PubMed

Yu, Liyang; Han, Qi; Niu, Xiamu; Yiu, S M; Fang, Junbin; Zhang, Ye

2016-02-01

Most of the existing image modification detection methods which are based on DCT coefficient analysis model the distribution of DCT coefficients as a mixture of a modified and an unchanged component. To separate the two components, two parameters, which are the primary quantization step, Q1, and the portion of the modified region, α, have to be estimated, and more accurate estimations of α and Q1 lead to better detection and localization results. Existing methods estimate α and Q1 in a completely blind manner, without considering the characteristics of the mixture model and the constraints to which α should conform. In this paper, we propose a more effective scheme for estimating α and Q1, based on the observations that, the curves on the surface of the likelihood function corresponding to the mixture model is largely smooth, and α can take values only in a discrete set. We conduct extensive experiments to evaluate the proposed method, and the experimental results confirm the efficacy of our method. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Polarization-multiplexed rate-adaptive non-binary-quasi-cyclic-LDPC-coded multilevel modulation with coherent detection for optical transport networks.

PubMed

Arabaci, Murat; Djordjevic, Ivan B; Saunders, Ross; Marcoccia, Roberto M

2010-02-01

In order to achieve high-speed transmission over optical transport networks (OTNs) and maximize its throughput, we propose using a rate-adaptive polarization-multiplexed coded multilevel modulation with coherent detection based on component non-binary quasi-cyclic (QC) LDPC codes. Compared to prior-art bit-interleaved LDPC-coded modulation (BI-LDPC-CM) scheme, the proposed non-binary LDPC-coded modulation (NB-LDPC-CM) scheme not only reduces latency due to symbol- instead of bit-level processing but also provides either impressive reduction in computational complexity or striking improvements in coding gain depending on the constellation size. As the paper presents, compared to its prior-art binary counterpart, the proposed NB-LDPC-CM scheme addresses the needs of future OTNs, which are achieving the target BER performance and providing maximum possible throughput both over the entire lifetime of the OTN, better.

Ultra-high capacity WDM-SDM optical access network with self-homodyne detection downstream and 32QAM-FBMC upstream.

PubMed

Feng, Zhenhua; Xu, Liang; Wu, Qiong; Tang, Ming; Fu, Songnian; Tong, Weijun; Shum, Perry Ping; Liu, Deming

2017-03-20

Towards 100G beyond large-capacity optical access networks, wavelength division multiplexing (WDM) techniques incorporating with space division multiplexing (SDM) and affordable spectrally efficient advanced modulation formats are indispensable. In this paper, we proposed and experimentally demonstrated a cost-efficient multicore fiber (MCF) based hybrid WDM-SDM optical access network with self-homodyne coherent detection (SHCD) based downstream (DS) and direct detection optical filter bank multi carrier (DDO-FBMC) based upstream (US). In the DS experiments, the inner core of the 7-core fiber is used as a dedicated channel to deliver the local oscillator (LO) lights while the other 6 outer cores are used to transmit 4 channels of wavelength multiplexed 200-Gb/s PDM-16QAM-OFDM signals. For US transmission, 4 wavelengths with channel spacing of 100 GHz are intensity modulated with 30 Gb/s 32-QAM-FBMC and directly detected by a ~7 GHz bandwidth receiver after transmission along one of the outer core. The results show that a 4 × 6 × 200-Gb/s DS transmission can be realized over 37 km 7-core fiber without carrier frequency offset (CFO) and phase noise (PN) compensation even using 10 MHz linewidth DFB lasers. The SHCD based on MCF provides a compromise and cost efficient scheme between conventional intradyne coherent detection and intensity modulation and direct detection (IM/DD) schemes. Both US and DS have acceptable BER performance and high spectral efficiency.

BlueDetect: An iBeacon-Enabled Scheme for Accurate and Energy-Efficient Indoor-Outdoor Detection and Seamless Location-Based Service

PubMed Central

Zou, Han; Jiang, Hao; Luo, Yiwen; Zhu, Jianjie; Lu, Xiaoxuan; Xie, Lihua

2016-01-01

The location and contextual status (indoor or outdoor) is fundamental and critical information for upper-layer applications, such as activity recognition and location-based services (LBS) for individuals. In addition, optimizations of building management systems (BMS), such as the pre-cooling or heating process of the air-conditioning system according to the human traffic entering or exiting a building, can utilize the information, as well. The emerging mobile devices, which are equipped with various sensors, become a feasible and flexible platform to perform indoor-outdoor (IO) detection. However, power-hungry sensors, such as GPS and WiFi, should be used with caution due to the constrained battery storage on mobile device. We propose BlueDetect: an accurate, fast response and energy-efficient scheme for IO detection and seamless LBS running on the mobile device based on the emerging low-power iBeacon technology. By leveraging the on-broad Bluetooth module and our proposed algorithms, BlueDetect provides a precise IO detection service that can turn on/off on-board power-hungry sensors smartly and automatically, optimize their performances and reduce the power consumption of mobile devices simultaneously. Moreover, seamless positioning and navigation services can be realized by it, especially in a semi-outdoor environment, which cannot be achieved by GPS or an indoor positioning system (IPS) easily. We prototype BlueDetect on Android mobile devices and evaluate its performance comprehensively. The experimental results have validated the superiority of BlueDetect in terms of IO detection accuracy, localization accuracy and energy consumption. PMID:26907295

An Anonymous User Authentication and Key Agreement Scheme Based on a Symmetric Cryptosystem in Wireless Sensor Networks

PubMed Central

Jung, Jaewook; Kim, Jiye; Choi, Younsung; Won, Dongho

2016-01-01

In wireless sensor networks (WSNs), a registered user can login to the network and use a user authentication protocol to access data collected from the sensor nodes. Since WSNs are typically deployed in unattended environments and sensor nodes have limited resources, many researchers have made considerable efforts to design a secure and efficient user authentication process. Recently, Chen et al. proposed a secure user authentication scheme using symmetric key techniques for WSNs. They claim that their scheme assures high efficiency and security against different types of attacks. After careful analysis, however, we find that Chen et al.’s scheme is still vulnerable to smart card loss attack and is susceptible to denial of service attack, since it is invalid for verification to simply compare an entered ID and a stored ID in smart card. In addition, we also observe that their scheme cannot preserve user anonymity. Furthermore, their scheme cannot quickly detect an incorrect password during login phase, and this flaw wastes both communication and computational overheads. In this paper, we describe how these attacks work, and propose an enhanced anonymous user authentication and key agreement scheme based on a symmetric cryptosystem in WSNs to address all of the aforementioned vulnerabilities in Chen et al.’s scheme. Our analysis shows that the proposed scheme improves the level of security, and is also more efficient relative to other related schemes. PMID:27537890

Detection of concealed cars in complex cargo X-ray imagery using Deep Learning.

PubMed

Jaccard, Nicolas; Rogers, Thomas W; Morton, Edward J; Griffin, Lewis D

2017-01-01

Non-intrusive inspection systems based on X-ray radiography techniques are routinely used at transport hubs to ensure the conformity of cargo content with the supplied shipping manifest. As trade volumes increase and regulations become more stringent, manual inspection by trained operators is less and less viable due to low throughput. Machine vision techniques can assist operators in their task by automating parts of the inspection workflow. Since cars are routinely involved in trafficking, export fraud, and tax evasion schemes, they represent an attractive target for automated detection and flagging for subsequent inspection by operators. Development and evaluation of a novel method for the automated detection of cars in complex X-ray cargo imagery. X-ray cargo images from a stream-of-commerce dataset were classified using a window-based scheme. The limited number of car images was addressed by using an oversampling scheme. Different Convolutional Neural Network (CNN) architectures were compared with well-established bag of words approaches. In addition, robustness to concealment was evaluated by projection of objects into car images. CNN approaches outperformed all other methods evaluated, achieving 100% car image classification rate for a false positive rate of 1-in-454. Cars that were partially or completely obscured by other goods, a modus operandi frequently adopted by criminals, were correctly detected. We believe that this level of performance suggests that the method is suitable for deployment in the field. It is expected that the generic object detection workflow described can be extended to other object classes given the availability of suitable training data.

Energy and Quality Evaluation for Compressive Sensing of Fetal Electrocardiogram Signals

PubMed Central

Da Poian, Giulia; Brandalise, Denis; Bernardini, Riccardo; Rinaldo, Roberto

2016-01-01

This manuscript addresses the problem of non-invasive fetal Electrocardiogram (ECG) signal acquisition with low power/low complexity sensors. A sensor architecture using the Compressive Sensing (CS) paradigm is compared to a standard compression scheme using wavelets in terms of energy consumption vs. reconstruction quality, and, more importantly, vs. performance of fetal heart beat detection in the reconstructed signals. We show in this paper that a CS scheme based on reconstruction with an over-complete dictionary has similar reconstruction quality to one based on wavelet compression. We also consider, as a more important figure of merit, the accuracy of fetal beat detection after reconstruction as a function of the sensor power consumption. Experimental results with an actual implementation in a commercial device show that CS allows significant reduction of energy consumption in the sensor node, and that the detection performance is comparable to that obtained from original signals for compression ratios up to about 75%. PMID:28025510

Receiver bandwidth effects on complex modulation and detection using directly modulated lasers.

PubMed

Yuan, Feng; Che, Di; Shieh, William

2016-05-01

Directly modulated lasers (DMLs) have long been employed for short- and medium-reach optical communications due to their low cost. Recently, a new modulation scheme called complex modulated DMLs has been demonstrated showing a significant optical signal to noise ratio sensitivity enhancement compared with the traditional intensity-only detection scheme. However, chirp-induced optical spectrum broadening is inevitable in complex modulated systems, which may imply a need for high-bandwidth receivers. In this Letter, we study the impact of receiver bandwidth effects on the performance of complex modulation and coherent detection systems based on DMLs. We experimentally demonstrate that such systems exhibit a reasonable tolerance for the reduced receiver bandwidth. For 10 Gbaud 4-level pulse amplitude modulation signals, the required electrical bandwidth is as low as 8.5 and 7.5 GHz for 7% and 20% forward error correction, respectively. Therefore, it is feasible to realize DML-based complex modulated systems using cost-effective receivers with narrow bandwidth.

Generating the Local Oscillator "Locally" in Continuous-Variable Quantum Key Distribution Based on Coherent Detection

NASA Astrophysics Data System (ADS)

Qi, Bing; Lougovski, Pavel; Pooser, Raphael; Grice, Warren; Bobrek, Miljko

2015-10-01

Continuous-variable quantum key distribution (CV-QKD) protocols based on coherent detection have been studied extensively in both theory and experiment. In all the existing implementations of CV-QKD, both the quantum signal and the local oscillator (LO) are generated from the same laser and propagate through the insecure quantum channel. This arrangement may open security loopholes and limit the potential applications of CV-QKD. In this paper, we propose and demonstrate a pilot-aided feedforward data recovery scheme that enables reliable coherent detection using a "locally" generated LO. Using two independent commercial laser sources and a spool of 25-km optical fiber, we construct a coherent communication system. The variance of the phase noise introduced by the proposed scheme is measured to be 0.04 (rad2 ), which is small enough to enable secure key distribution. This technology also opens the door for other quantum communication protocols, such as the recently proposed measurement-device-independent CV-QKD, where independent light sources are employed by different users.

Objective-lens-free Fiber-based Position Detection with Nanometer Resolution in a Fiber Optical Trapping System.

PubMed

Ti, Chaoyang; Ho-Thanh, Minh-Tri; Wen, Qi; Liu, Yuxiang

2017-10-13

Position detection with high accuracy is crucial for force calibration of optical trapping systems. Most existing position detection methods require high-numerical-aperture objective lenses, which are bulky, expensive, and difficult to miniaturize. Here, we report an affordable objective-lens-free, fiber-based position detection scheme with 2 nm spatial resolution and 150 MHz bandwidth. This fiber based detection mechanism enables simultaneous trapping and force measurements in a compact fiber optical tweezers system. In addition, we achieved more reliable signal acquisition with less distortion compared with objective based position detection methods, thanks to the light guiding in optical fibers and small distance between the fiber tips and trapped particle. As a demonstration of the fiber based detection, we used the fiber optical tweezers to apply a force on a cell membrane and simultaneously measure the cellular response.

Improved biliary detection and diagnosis through intelligent machine analysis.

PubMed

Logeswaran, Rajasvaran

2012-09-01

This paper reports on work undertaken to improve automated detection of bile ducts in magnetic resonance cholangiopancreatography (MRCP) images, with the objective of conducting preliminary classification of the images for diagnosis. The proposed I-BDeDIMA (Improved Biliary Detection and Diagnosis through Intelligent Machine Analysis) scheme is a multi-stage framework consisting of successive phases of image normalization, denoising, structure identification, object labeling, feature selection and disease classification. A combination of multiresolution wavelet, dynamic intensity thresholding, segment-based region growing, region elimination, statistical analysis and neural networks, is used in this framework to achieve good structure detection and preliminary diagnosis. Tests conducted on over 200 clinical images with known diagnosis have shown promising results of over 90% accuracy. The scheme outperforms related work in the literature, making it a viable framework for computer-aided diagnosis of biliary diseases. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Vernier-like super resolution with guided correlated photon pairs.

PubMed

Nespoli, Matteo; Goan, Hsi-Sheng; Shih, Min-Hsiung

2016-01-11

We describe a dispersion-enabled, ultra-low power realization of super-resolution in an integrated Mach-Zehnder interferometer. Our scheme is based on a Vernier-like effect in the coincident detection of frequency correlated, non-degenerate photon pairs at the sensor output in the presence of group index dispersion. We design and simulate a realistic integrated refractive index sensor in a silicon nitride on silica platform and characterize its performance in the proposed scheme. We present numerical results showing a sensitivity improvement upward of 40 times over a traditional sensing scheme. The device we design is well within the reach of modern semiconductor fabrication technology. We believe this is the first metrology scheme that uses waveguide group index dispersion as a resource to attain super-resolution.

Computerized scheme for vertebra detection in CT scout image

NASA Astrophysics Data System (ADS)

Guo, Wei; Chen, Qiang; Zhou, Hanxun; Zhang, Guodong; Cong, Lin; Li, Qiang

2016-03-01

Our purposes are to develop a vertebra detection scheme for automated scan planning, which would assist radiological technologists in their routine work for the imaging of vertebrae. Because the orientations of vertebrae were various, and the Haar-like features were only employed to represent the subject on the vertical, horizontal, or diagonal directions, we rotated the CT scout image seven times to make the vertebrae roughly horizontal in least one of the rotated images. Then, we employed Adaboost learning algorithm to construct a strong classifier for the vertebra detection by use of Haar-like features, and combined the detection results with the overlapping region according to the number of times they were detected. Finally, most of the false positives were removed by use of the contextual relationship between them. The detection scheme was evaluated on a database with 76 CT scout image. Our detection scheme reported 1.65 false positives per image at a sensitivity of 94.3% for initial detection of vertebral candidates, and then the performance of detection was improved to 0.95 false positives per image at a sensitivity of 98.6% for the further steps of false positive reduction. The proposed scheme achieved a high performance for the detection of vertebrae with different orientations.

Automatic identification of epileptic seizures from EEG signals using linear programming boosting.

PubMed

Hassan, Ahnaf Rashik; Subasi, Abdulhamit

2016-11-01

Computerized epileptic seizure detection is essential for expediting epilepsy diagnosis and research and for assisting medical professionals. Moreover, the implementation of an epilepsy monitoring device that has low power and is portable requires a reliable and successful seizure detection scheme. In this work, the problem of automated epilepsy seizure detection using singe-channel EEG signals has been addressed. At first, segments of EEG signals are decomposed using a newly proposed signal processing scheme, namely complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Six spectral moments are extracted from the CEEMDAN mode functions and train and test matrices are formed afterward. These matrices are fed into the classifier to identify epileptic seizures from EEG signal segments. In this work, we implement an ensemble learning based machine learning algorithm, namely linear programming boosting (LPBoost) to perform classification. The efficacy of spectral features in the CEEMDAN domain is validated by graphical and statistical analyses. The performance of CEEMDAN is compared to those of its predecessors to further inspect its suitability. The effectiveness and the appropriateness of LPBoost are demonstrated as opposed to the commonly used classification models. Resubstitution and 10 fold cross-validation error analyses confirm the superior algorithm performance of the proposed scheme. The algorithmic performance of our epilepsy seizure identification scheme is also evaluated against state-of-the-art works in the literature. Experimental outcomes manifest that the proposed seizure detection scheme performs better than the existing works in terms of accuracy, sensitivity, specificity, and Cohen's Kappa coefficient. It can be anticipated that owing to its use of only one channel of EEG signal, the proposed method will be suitable for device implementation, eliminate the onus of clinicians for analyzing a large bulk of data manually, and expedite epilepsy diagnosis. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Static magnetic Faraday rotation spectroscopy combined with a differential scheme for OH detection

NASA Astrophysics Data System (ADS)

Zhao, Weixiong; Deng, Lunhua; Qian, Xiaodong; Fang, Bo; Gai, Yanbo; Chen, Weidong; Gao, Xiaoming; Zhang, Weijun

2015-04-01

The hydroxyl (OH) radical plays a critical role in atmospheric chemistry due to its high reactivity with volatile organic compounds (VOCs) and other trace gaseous species. Because of its very short life time and very low concentration in the atmosphere, interference-free high sensitivity in-situ OH monitoring by laser spectroscopy represents a real challenge. Faraday rotation spectroscopy (FRS) relies on the particular magneto-optic effect observed for paramagnetic species, which makes it capable of enhancing the detection sensitivity and mitigation of spectral interferences from diamagnetic species in the atmosphere. When an AC magnetic field is used, the Zeeman splitting of the molecular absorption line (and thus the magnetic circular birefringence) is modulated. This provides an 'internal modulation' of the sample, which permits to suppress the external noise like interference fringes. An alternative FRS detection scheme is to use a static magnetic field (DC-field) associated with laser wavelength modulation to effectively modulate the Zeeman splitting of the absorption lines. In the DC field case, wavelength modulation of the laser frequency can provide excellent performance compared to most of the sensing systems based on direct absorption and wavelength modulation spectroscopy. The dimension of the DC solenoid is not limited by the resonant frequency of the RLC circuit, which makes large dimension solenoid coil achievable and the absorption base length could be further increased. By employing a combination of the environmental photochemical reactor or smog chamber with multipass absorption cell, one can lower the minimum detection limit for high accuracy atmospheric chemistry studies. In this paper, we report on the development of a DC field based FRS in conjunction with a balanced detection scheme for OH radical detection at 2.8 μm and the construction of OH chemistry research platform which combined a large dimension superconducting magnetic coil with the multipass cell and photochemical reactor chamber for real time in-situ measurement of OH radical concentration in the chamber.

An Extension to the Kalman Filter for an Improved Detection of Unknown Behavior

NASA Technical Reports Server (NTRS)

Benazera, Emmanuel; Narasimhan, Sriram

2005-01-01

The use of Kalman filter (KF) interferes with fault detection algorithms based on the residual between estimated and measured variables, since the measured values are used to update the estimates. This feedback results in the estimates being pulled closer to the measured values, influencing the residuals in the process. Here we present a fault detection scheme for systems that are being tracked by a KF. Our approach combines an open-loop prediction over an adaptive window and an information-based measure of the deviation of the Kalman estimate from the prediction to improve fault detection.

Communication channels secured from eavesdropping via transmission of photonic Bell states

NASA Astrophysics Data System (ADS)

Shimizu, Kaoru; Imoto, Nobuyuki

1999-07-01

This paper proposes a quantum communication scheme for sending a definite binary sequence while confirming the security of the transmission. The scheme is very suitable for sending a ciphertext in a secret-key cryptosystem so that we can detect any eavesdropper who attempts to decipher the key. Thus we can continue to use a secret key unless we detect eavesdropping and the security of a key that is used repeatedly can be enhanced to the level of one-time-pad cryptography. In our scheme, a pair of entangled photon twins is employed as a bit carrier which is encoded in a two-term superposition of four Bell states. Different bases are employed for encoding the binary sequence of a ciphertext and a random test bit. The photon twins are measured with a Bell state analyzer and any bit can be decoded from the resultant Bell state when the receiver is later notified of the coding basis through a classical channel. By opening the positions and the values of test bits, ciphertext can be read and eavesdropping is simultaneously detected.

Practical scheme for optimal measurement in quantum interferometric devices

NASA Astrophysics Data System (ADS)

Takeoka, Masahiro; Ban, Masashi; Sasaki, Masahide

2003-06-01

We apply a Kennedy-type detection scheme, which was originally proposed for a binary communications system, to interferometric sensing devices. We show that the minimum detectable perturbation of the proposed system reaches the ultimate precision bound which is predicted by quantum Neyman-Pearson hypothesis testing. To provide concrete examples, we apply our interferometric scheme to phase shift detection by using coherent and squeezed probe fields.

Advanced digital signal processing for short-haul and access network

NASA Astrophysics Data System (ADS)

Zhang, Junwen; Yu, Jianjun; Chi, Nan

2016-02-01

Digital signal processing (DSP) has been proved to be a successful technology recently in high speed and high spectrum-efficiency optical short-haul and access network, which enables high performances based on digital equalizations and compensations. In this paper, we investigate advanced DSP at the transmitter and receiver side for signal pre-equalization and post-equalization in an optical access network. A novel DSP-based digital and optical pre-equalization scheme has been proposed for bandwidth-limited high speed short-distance communication system, which is based on the feedback of receiver-side adaptive equalizers, such as least-mean-squares (LMS) algorithm and constant or multi-modulus algorithms (CMA, MMA). Based on this scheme, we experimentally demonstrate 400GE on a single optical carrier based on the highest ETDM 120-GBaud PDM-PAM-4 signal, using one external modulator and coherent detection. A line rate of 480-Gb/s is achieved, which enables 20% forward-error correction (FEC) overhead to keep the 400-Gb/s net information rate. The performance after fiber transmission shows large margin for both short range and metro/regional networks. We also extend the advanced DSP for short haul optical access networks by using high order QAMs. We propose and demonstrate a high speed multi-band CAP-WDM-PON system on intensity modulation, direct detection and digital equalizations. A hybrid modified cascaded MMA post-equalization schemes are used to equalize the multi-band CAP-mQAM signals. Using this scheme, we successfully demonstrates 550Gb/s high capacity WDMPON system with 11 WDM channels, 55 sub-bands, and 10-Gb/s per user in the downstream over 40-km SMF.

One-laser-based generation/detection of Brillouin dynamic grating and its application to distributed discrimination of strain and temperature.

PubMed

Zou, Weiwen; He, Zuyuan; Hotate, Kazuo

2011-01-31

This paper presents a novel scheme to generate and detect Brillouin dynamic grating in a polarization-maintaining optical fiber based on one laser source. Precise measurement of Brillouin dynamic grating spectrum is achieved benefiting from that the pump, probe and readout waves are coherently originated from the same laser source. Distributed discrimination of strain and temperature is also achieved with high accuracy.

Latest Progress of Fault Detection and Localization in Complex Electrical Engineering

NASA Astrophysics Data System (ADS)

Zhao, Zheng; Wang, Can; Zhang, Yagang; Sun, Yi

2014-01-01

In the researches of complex electrical engineering, efficient fault detection and localization schemes are essential to quickly detect and locate faults so that appropriate and timely corrective mitigating and maintenance actions can be taken. In this paper, under the current measurement precision of PMU, we will put forward a new type of fault detection and localization technology based on fault factor feature extraction. Lots of simulating experiments indicate that, although there are disturbances of white Gaussian stochastic noise, based on fault factor feature extraction principal, the fault detection and localization results are still accurate and reliable, which also identifies that the fault detection and localization technology has strong anti-interference ability and great redundancy.

A novel multi-scale adaptive sampling-based approach for energy saving in leak detection for WSN-based water pipelines

NASA Astrophysics Data System (ADS)

Saqib, Najam us; Faizan Mysorewala, Muhammad; Cheded, Lahouari

2017-12-01

In this paper, we propose a novel monitoring strategy for a wireless sensor networks (WSNs)-based water pipeline network. Our strategy uses a multi-pronged approach to reduce energy consumption based on the use of two types of vibration sensors and pressure sensors, all having different energy levels, and a hierarchical adaptive sampling mechanism to determine the sampling frequency. The sampling rate of the sensors is adjusted according to the bandwidth of the vibration signal being monitored by using a wavelet-based adaptive thresholding scheme that calculates the new sampling frequency for the following cycle. In this multimodal sensing scheme, the duty-cycling approach is used for all sensors to reduce the sampling instances, such that the high-energy, high-precision (HE-HP) vibration sensors have low duty cycles, and the low-energy, low-precision (LE-LP) vibration sensors have high duty cycles. The low duty-cycling (HE-HP) vibration sensor adjusts the sampling frequency of the high duty-cycling (LE-LP) vibration sensor. The simulated test bed considered here consists of a water pipeline network which uses pressure and vibration sensors, with the latter having different energy consumptions and precision levels, at various locations in the network. This is all the more useful for energy conservation for extended monitoring. It is shown that by using the novel features of our proposed scheme, a significant reduction in energy consumption is achieved and the leak is effectively detected by the sensor node that is closest to it. Finally, both the total energy consumed by monitoring as well as the time to detect the leak by a WSN node are computed, and show the superiority of our proposed hierarchical adaptive sampling algorithm over a non-adaptive sampling approach.

A Cross-Layer, Anomaly-Based IDS for WSN and MANET

PubMed Central

Amouri, Amar; Manthena, Raju

2018-01-01

Intrusion detection system (IDS) design for mobile adhoc networks (MANET) is a crucial component for maintaining the integrity of the network. The need for rapid deployment of IDS capability with minimal data availability for training and testing is an important requirement of such systems, especially for MANETs deployed in highly dynamic scenarios, such as battlefields. This work proposes a two-level detection scheme for detecting malicious nodes in MANETs. The first level deploys dedicated sniffers working in promiscuous mode. Each sniffer utilizes a decision-tree-based classifier that generates quantities which we refer to as correctly classified instances (CCIs) every reporting time. In the second level, the CCIs are sent to an algorithmically run supernode that calculates quantities, which we refer to as the accumulated measure of fluctuation (AMoF) of the received CCIs for each node under test (NUT). A key concept that is used in this work is that the variability of the smaller size population which represents the number of malicious nodes in the network is greater than the variance of the larger size population which represents the number of normal nodes in the network. A linear regression process is then performed in parallel with the calculation of the AMoF for fitting purposes and to set a proper threshold based on the slope of the fitted lines. As a result, the malicious nodes are efficiently and effectively separated from the normal nodes. The proposed scheme is tested for various node velocities and power levels and shows promising detection performance even at low-power levels. The results presented also apply to wireless sensor networks (WSN) and represent a novel IDS scheme for such networks. PMID:29470446

A Cross-Layer, Anomaly-Based IDS for WSN and MANET.

PubMed

Amouri, Amar; Morgera, Salvatore D; Bencherif, Mohamed A; Manthena, Raju

2018-02-22

Intrusion detection system (IDS) design for mobile adhoc networks (MANET) is a crucial component for maintaining the integrity of the network. The need for rapid deployment of IDS capability with minimal data availability for training and testing is an important requirement of such systems, especially for MANETs deployed in highly dynamic scenarios, such as battlefields. This work proposes a two-level detection scheme for detecting malicious nodes in MANETs. The first level deploys dedicated sniffers working in promiscuous mode. Each sniffer utilizes a decision-tree-based classifier that generates quantities which we refer to as correctly classified instances (CCIs) every reporting time. In the second level, the CCIs are sent to an algorithmically run supernode that calculates quantities, which we refer to as the accumulated measure of fluctuation (AMoF) of the received CCIs for each node under test (NUT). A key concept that is used in this work is that the variability of the smaller size population which represents the number of malicious nodes in the network is greater than the variance of the larger size population which represents the number of normal nodes in the network. A linear regression process is then performed in parallel with the calculation of the AMoF for fitting purposes and to set a proper threshold based on the slope of the fitted lines. As a result, the malicious nodes are efficiently and effectively separated from the normal nodes. The proposed scheme is tested for various node velocities and power levels and shows promising detection performance even at low-power levels. The results presented also apply to wireless sensor networks (WSN) and represent a novel IDS scheme for such networks.

Point source detection in infrared astronomical surveys

NASA Technical Reports Server (NTRS)

Pelzmann, R. F., Jr.

1977-01-01

Data processing techniques useful for infrared astronomy data analysis systems are reported. This investigation is restricted to consideration of data from space-based telescope systems operating as survey instruments. In this report the theoretical background for specific point-source detection schemes is completed, and the development of specific algorithms and software for the broad range of requirements is begun.

Unobtrusive monitoring of heart rate using a cost-effective speckle-based SI-POF remote sensor

NASA Astrophysics Data System (ADS)

Pinzón, P. J.; Montero, D. S.; Tapetado, A.; Vázquez, C.

2017-03-01

A novel speckle-based sensing technique for cost-effective heart-rate monitoring is demonstrated. This technique detects periodical changes in the spatial distribution of energy on the speckle pattern at the output of a Step-Index Polymer Optical Fiber (SI-POF) lead by using a low-cost webcam. The scheme operates in reflective configuration thus performing a centralized interrogation unit scheme. The prototype has been integrated into a mattress and its functionality has been tested with 5 different patients lying on the mattress in different positions without direct contact with the fiber sensing lead.

Teleportation-based quantum information processing with Majorana zero modes

DOE PAGES

Vijay, Sagar; Fu, Liang

2016-12-29

In this work, we present a measurement-based scheme for performing braiding operations on Majorana zero modes in mesoscopic superconductor islands and for detecting their non-Abelian statistics without moving or hybridizing them. In our scheme for “braiding without braiding”, the topological qubit encoded in any pair of well-separated Majorana zero modes is read out from the transmission phase shift in electron teleportation through the island in the Coulomb-blockade regime. Finally, we propose experimental setups to measure the teleportation phase shift via conductance in an electron interferometer or persistent current in a closed loop.

Teleportation-based quantum information processing with Majorana zero modes

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

Vijay, Sagar; Fu, Liang

In this work, we present a measurement-based scheme for performing braiding operations on Majorana zero modes in mesoscopic superconductor islands and for detecting their non-Abelian statistics without moving or hybridizing them. In our scheme for “braiding without braiding”, the topological qubit encoded in any pair of well-separated Majorana zero modes is read out from the transmission phase shift in electron teleportation through the island in the Coulomb-blockade regime. Finally, we propose experimental setups to measure the teleportation phase shift via conductance in an electron interferometer or persistent current in a closed loop.

Stable radio frequency dissemination by simple hybrid frequency modulation scheme.

PubMed

Yu, Longqiang; Wang, Rong; Lu, Lin; Zhu, Yong; Wu, Chuanxin; Zhang, Baofu; Wang, Peizhang

2014-09-15

In this Letter, we propose a fiber-based stable radio frequency transfer system by a hybrid frequency modulation scheme. Creatively, two radio frequency signals are combined and simultaneously transferred by only one laser diode. One frequency component is used to detect the phase fluctuation, and the other one is the derivative compensated signal providing a stable frequency for the remote end. A proper ratio of the frequencies of the components is well maintained by parameter m to avoid interference between them. Experimentally, a stable 200 MHz signal is transferred over 100 km optical fiber with the help of a 1 GHz detecting signal, and fractional instability of 2×10(-17) at 10(5) s is achieved.

Cardiac induced localised motion of the human torso detected by a long period grating fibre optic sensing scheme

NASA Astrophysics Data System (ADS)

Allsop, T.; Lloyd, G.; Bhamber, R. S.; Hadzievski, L.; Halliday, M.; Webb, D. J.

2014-05-01

Cardiovascular health of the human population is a major concern for medical clinicians, with cardiovascular diseases responsible for 48% of all deaths worldwide, according to the World Health Organisation. Therefore the development of new practicable and economical diagnostic tools to scrutinise the cardiovascular health of humans is a major driver for clinicians. We offer a new technique to obtain seismocardiographic signals covering both ballistocardiography (below 20Hz) and audible heart sounds (20Hz upwards). The detection scheme is based upon an array of curvature/displacement sensors using fibre optic long period gratings interrogated using a variation of the derivative spectroscopy interrogation technique.

Automated detection and quantification of residual brain tumor using an interactive computer-aided detection scheme

NASA Astrophysics Data System (ADS)

Gaffney, Kevin P.; Aghaei, Faranak; Battiste, James; Zheng, Bin

2017-03-01

Detection of residual brain tumor is important to evaluate efficacy of brain cancer surgery, determine optimal strategy of further radiation therapy if needed, and assess ultimate prognosis of the patients. Brain MR is a commonly used imaging modality for this task. In order to distinguish between residual tumor and surgery induced scar tissues, two sets of MRI scans are conducted pre- and post-gadolinium contrast injection. The residual tumors are only enhanced in the post-contrast injection images. However, subjective reading and quantifying this type of brain MR images faces difficulty in detecting real residual tumor regions and measuring total volume of the residual tumor. In order to help solve this clinical difficulty, we developed and tested a new interactive computer-aided detection scheme, which consists of three consecutive image processing steps namely, 1) segmentation of the intracranial region, 2) image registration and subtraction, 3) tumor segmentation and refinement. The scheme also includes a specially designed and implemented graphical user interface (GUI) platform. When using this scheme, two sets of pre- and post-contrast injection images are first automatically processed to detect and quantify residual tumor volume. Then, a user can visually examine segmentation results and conveniently guide the scheme to correct any detection or segmentation errors if needed. The scheme has been repeatedly tested using five cases. Due to the observed high performance and robustness of the testing results, the scheme is currently ready for conducting clinical studies and helping clinicians investigate the association between this quantitative image marker and outcome of patients.

Novel railway-subgrade vibration monitoring technology using phase-sensitive OTDR

NASA Astrophysics Data System (ADS)

Wang, Zhaoyong; Lu, Bin; Zheng, Hanrong; Ye, Qing; Pan, Zhengqing; Cai, Haiwen; Qu, Ronghui; Fang, Zujie; Zhao, Howell

2017-04-01

High-speed railway is being developed rapidly; its safety, including infrastructure and train operation, is vital. This paper presents a railway-subgrade vibration monitoring scheme based on phase-sensitive OTDR for railway safety. The subgrade vibration is detected and rebuilt. Multi-dimension comprehensive analysis (MDCA) is proposed to identify the running train signals and illegal constructions along railway. To our best knowledge, it is the first time that a railway-subgrade vibration monitoring scheme is proposed. This scheme is proved effective by field tests for real-time train tracking and activities monitoring along railway. It provides a new passive distributed way for all-weather railway-subgrade vibration monitoring.

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.

A hybrid CNN feature model for pulmonary nodule malignancy risk differentiation.

PubMed

Wang, Huafeng; Zhao, Tingting; Li, Lihong Connie; Pan, Haixia; Liu, Wanquan; Gao, Haoqi; Han, Fangfang; Wang, Yuehai; Qi, Yifan; Liang, Zhengrong

2018-01-01

The malignancy risk differentiation of pulmonary nodule is one of the most challenge tasks of computer-aided diagnosis (CADx). Most recently reported CADx methods or schemes based on texture and shape estimation have shown relatively satisfactory on differentiating the risk level of malignancy among the nodules detected in lung cancer screening. However, the existing CADx schemes tend to detect and analyze characteristics of pulmonary nodules from a statistical perspective according to local features only. Enlightened by the currently prevailing learning ability of convolutional neural network (CNN), which simulates human neural network for target recognition and our previously research on texture features, we present a hybrid model that takes into consideration of both global and local features for pulmonary nodule differentiation using the largest public database founded by the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI). By comparing three types of CNN models in which two of them were newly proposed by us, we observed that the multi-channel CNN model yielded the best discrimination in capacity of differentiating malignancy risk of the nodules based on the projection of distributions of extracted features. Moreover, CADx scheme using the new multi-channel CNN model outperformed our previously developed CADx scheme using the 3D texture feature analysis method, which increased the computed area under a receiver operating characteristic curve (AUC) from 0.9441 to 0.9702.

Efficient Buffering Scheme in the LMA for Seamless Handover in PMIPv6

NASA Astrophysics Data System (ADS)

Kim, Kwang-Ryoul; Lee, Hyo-Beom; Choi, Hyon-Young; Min, Sung-Gi; Han, Youn-Hee

Proxy Mobile IPv6 (PMIPv6) is proposed as a new network-based local mobility protocol which does not involve the Mobile Node (MN) in mobility management. PMIPv6, which uses link-layer attachment information, reduces the movement detection time and eliminates duplicate address detection procedures in order to provide faster handover than Mobile IPv6 (MIPv6). To eliminate packet loss during the handover period, the Local Mobility Anchor (LMA) buffering scheme is proposed. In this scheme, the LMA buffers lost packets of the Mobile Access Gateway (MAG) and the MN during the handover and recovers them after handover. A new Automatic Repeat reQuest (ARQ) handler is defined which efficiently manages the LMA buffer. The ARQ handler relays ARQ result between the MAG and the MN to the LMA. The LMA removes any buffered packets which have been successfully delivered to the MN. The ARQ handler recovers the packet loss during the handover using buffered packets in the LMA. The ARQ information, between the MAG and LMA, is inserted in the outer header of IP-in-IP encapsulated packets of a standard PMIPv6 tunnel. Since the proposed scheme simply adds information to the standard operation of an IP-in-IP tunnel between the LMA and the MAG, it can be implemented seamlessly without modification to the original PMIPv6 messages and signaling sequence. Unlike other Fast Handovers for Mobile IPv6 (FMIPv6) based enhancement for PMIPv6, the proposed scheme does not require any handover related information before the actual handover.

Countermeasure against blinding attacks on low-noise detectors with a background-noise-cancellation scheme

NASA Astrophysics Data System (ADS)

Lee, Min Soo; Park, Byung Kwon; Woo, Min Ki; Park, Chang Hoon; Kim, Yong-Su; Han, Sang-Wook; Moon, Sung

2016-12-01

We developed a countermeasure against blinding attacks on low-noise detectors with a background-noise-cancellation scheme in quantum key distribution (QKD) systems. Background-noise cancellation includes self-differencing and balanced avalanche photon diode (APD) schemes and is considered a promising solution for low-noise APDs, which are critical components in high-performance QKD systems. However, its vulnerability to blinding attacks has been recently reported. In this work, we propose a countermeasure that prevents this potential security loophole from being used in detector blinding attacks. An experimental QKD setup is implemented and various tests are conducted to verify the feasibility and performance of the proposed method. The obtained measurement results show that the proposed scheme successfully detects occurring blinding-attack-based hacking attempts.

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.

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.

Weak beacon detection for air-to-ground optical wireless link establishment.

PubMed

Han, Yaoqiang; Dang, Anhong; Tang, Junxiong; Guo, Hong

2010-02-01

In an air-to-ground free-space optical communication system, strong background interference seriously affects the beacon detection, which makes it difficult to establish the optical link. In this paper, we propose a correlation beacon detection scheme under strong background interference conditions. As opposed to traditional beacon detection schemes, the beacon is modulated by an m-sequence at the transmitting terminal with a digital differential matched filter (DDMF) array introduced at the receiving end to detect the modulated beacon. This scheme is capable of suppressing both strong interference and noise by correlation reception of the received image sequence. In addition, the DDMF array enables each pixel of the image sensor to have its own DDMF of the same structure to process its received image sequence in parallel, thus it makes fast beacon detection possible. Theoretical analysis and an outdoor experiment have been demonstrated and show that the proposed scheme can realize fast and effective beacon detection under strong background interference conditions. Consequently, the required beacon transmission power can also be reduced dramatically.

Development of Measurement Methods for Detection of Special Nuclear Materials using D-D Pulsed Neutron Source

NASA Astrophysics Data System (ADS)

Misawa, Tsuyoshi; Takahashi, Yoshiyuki; Yagi, Takahiro; Pyeon, Cheol Ho; Kimura, Masaharu; Masuda, Kai; Ohgaki, Hideaki

2015-10-01

For detection of hidden special nuclear materials (SNMs), we have developed an active neutron-based interrogation system combined with a D-D fusion pulsed neutron source and a neutron detection system. In the detection scheme, we have adopted new measurement techniques simultaneously; neutron noise analysis and neutron energy spectrum analysis. The validity of neutron noise analysis method has been experimentally studied in the Kyoto University Critical Assembly (KUCA), and was applied to a cargo container inspection system by simulation.

A novel material detection algorithm based on 2D GMM-based power density function and image detail addition scheme in dual energy X-ray images.

PubMed

Pourghassem, Hossein

2012-01-01

Material detection is a vital need in dual energy X-ray luggage inspection systems at security of airport and strategic places. In this paper, a novel material detection algorithm based on statistical trainable models using 2-Dimensional power density function (PDF) of three material categories in dual energy X-ray images is proposed. In this algorithm, the PDF of each material category as a statistical model is estimated from transmission measurement values of low and high energy X-ray images by Gaussian Mixture Models (GMM). Material label of each pixel of object is determined based on dependency probability of its transmission measurement values in the low and high energy to PDF of three material categories (metallic, organic and mixed materials). The performance of material detection algorithm is improved by a maximum voting scheme in a neighborhood of image as a post-processing stage. Using two background removing and denoising stages, high and low energy X-ray images are enhanced as a pre-processing procedure. For improving the discrimination capability of the proposed material detection algorithm, the details of the low and high energy X-ray images are added to constructed color image which includes three colors (orange, blue and green) for representing the organic, metallic and mixed materials. The proposed algorithm is evaluated on real images that had been captured from a commercial dual energy X-ray luggage inspection system. The obtained results show that the proposed algorithm is effective and operative in detection of the metallic, organic and mixed materials with acceptable accuracy.

Classification of ring artifacts for their effective removal using type adaptive correction schemes.

PubMed

Anas, Emran Mohammad Abu; Lee, Soo Yeol; Hasan, Kamrul

2011-06-01

High resolution tomographic images acquired with a digital X-ray detector are often degraded by the so called ring artifacts. In this paper, a detail analysis including the classification, detection and correction of these ring artifacts is presented. At first, a novel idea for classifying rings into two categories, namely type I and type II rings, is proposed based on their statistical characteristics. The defective detector elements and the dusty scintillator screens result in type I ring and the mis-calibrated detector elements lead to type II ring. Unlike conventional approaches, we emphasize here on the separate detection and correction schemes for each type of rings for their effective removal. For the detection of type I ring, the histogram of the responses of the detector elements is used and a modified fast image inpainting algorithm is adopted to correct the responses of the defective pixels. On the other hand, to detect the type II ring, first a simple filtering scheme is presented based on the fast Fourier transform (FFT) to smooth the sum curve derived form the type I ring corrected projection data. The difference between the sum curve and its smoothed version is then used to detect their positions. Then, to remove the constant bias suffered by the responses of the mis-calibrated detector elements with view angle, an estimated dc shift is subtracted from them. The performance of the proposed algorithm is evaluated using real micro-CT images and is compared with three recently reported algorithms. Simulation results demonstrate superior performance of the proposed technique as compared to the techniques reported in the literature. Copyright © 2011 Elsevier Ltd. All rights reserved.

Detection-enhanced steady state entanglement with ions.

PubMed

Bentley, C D B; Carvalho, A R R; Kielpinski, D; Hope, J J

2014-07-25

Driven dissipative steady state entanglement schemes take advantage of coupling to the environment to robustly prepare highly entangled states. We present a scheme for two trapped ions to generate a maximally entangled steady state with fidelity above 0.99, appropriate for use in quantum protocols. Furthermore, we extend the scheme by introducing detection of our dissipation process, significantly enhancing the fidelity. Our scheme is robust to anomalous heating and requires no sympathetic cooling.

Fault detection and diagnosis in a spacecraft attitude determination system

NASA Astrophysics Data System (ADS)

Pirmoradi, F. N.; Sassani, F.; de Silva, C. W.

2009-09-01

This paper presents a new scheme for fault detection and diagnosis (FDD) in spacecraft attitude determination (AD) sensors. An integrated attitude determination system, which includes measurements of rate and angular position using rate gyros and vector sensors, is developed. Measurement data from all sensors are fused by a linearized Kalman filter, which is designed based on the system kinematics, to provide attitude estimation and the values of the gyro bias. Using this information the erroneous sensor measurements are corrected, and unbounded sensor measurement errors are avoided. The resulting bias-free data are used in the FDD scheme. The FDD algorithm uses model-based state estimation, combining the information from the rotational dynamics and kinematics of a spacecraft with the sensor measurements to predict the future sensor outputs. Fault isolation is performed through extended Kalman filters (EKFs). The innovation sequences of EKFs are monitored by several statistical tests to detect the presence of a failure and to localize the failures in all AD sensors. The isolation procedure is developed in two phases. In the first phase, two EKFs are designed, which use subsets of measurements to provide state estimates and form residuals, which are used to verify the source of the fault. In the second phase of isolation, testing of multiple hypotheses is performed. The generalized likelihood ratio test is utilized to identify the faulty components. In the scheme developed in this paper a relatively small number of hypotheses is used, which results in faster isolation and highly distinguishable fault signatures. An important feature of the developed FDD scheme is that it can provide attitude estimations even if only one type of sensors is functioning properly.

APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels

NASA Astrophysics Data System (ADS)

Klüser, L.; Killius, N.; Gesell, G.

2015-04-01

The cloud processing scheme APOLLO (Avhrr Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. While building upon the physical principles having served well in the original APOLLO a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is not performed as a binary yes/no decision based on these physical principals but is expressed as cloud probability for each satellite pixel. Consequently the outcome of the algorithm can be tuned from clear confident to cloud confident depending on the purpose. The probabilistic approach allows to retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for the application with large amounts of historical satellite data. Thus the radiative transfer solution is approximated by the same two stream approach which also had been used for the original APOLLO. This allows the algorithm to be robust enough for being applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e. within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from on NOAA-18 are presented.

Improving performance of breast cancer risk prediction using a new CAD-based region segmentation scheme

NASA Astrophysics Data System (ADS)

Heidari, Morteza; Zargari Khuzani, Abolfazl; Danala, Gopichandh; Qiu, Yuchen; Zheng, Bin

2018-02-01

Objective of this study is to develop and test a new computer-aided detection (CAD) scheme with improved region of interest (ROI) segmentation combined with an image feature extraction framework to improve performance in predicting short-term breast cancer risk. A dataset involving 570 sets of "prior" negative mammography screening cases was retrospectively assembled. In the next sequential "current" screening, 285 cases were positive and 285 cases remained negative. A CAD scheme was applied to all 570 "prior" negative images to stratify cases into the high and low risk case group of having cancer detected in the "current" screening. First, a new ROI segmentation algorithm was used to automatically remove useless area of mammograms. Second, from the matched bilateral craniocaudal view images, a set of 43 image features related to frequency characteristics of ROIs were initially computed from the discrete cosine transform and spatial domain of the images. Third, a support vector machine model based machine learning classifier was used to optimally classify the selected optimal image features to build a CAD-based risk prediction model. The classifier was trained using a leave-one-case-out based cross-validation method. Applying this improved CAD scheme to the testing dataset, an area under ROC curve, AUC = 0.70+/-0.04, which was significantly higher than using the extracting features directly from the dataset without the improved ROI segmentation step (AUC = 0.63+/-0.04). This study demonstrated that the proposed approach could improve accuracy on predicting short-term breast cancer risk, which may play an important role in helping eventually establish an optimal personalized breast cancer paradigm.

Adaptive-Mesh-Refinement for hyperbolic systems of conservation laws based on a posteriori stabilized high order polynomial reconstructions

NASA Astrophysics Data System (ADS)

Semplice, Matteo; Loubère, Raphaël

2018-02-01

In this paper we propose a third order accurate finite volume scheme based on a posteriori limiting of polynomial reconstructions within an Adaptive-Mesh-Refinement (AMR) simulation code for hydrodynamics equations in 2D. The a posteriori limiting is based on the detection of problematic cells on a so-called candidate solution computed at each stage of a third order Runge-Kutta scheme. Such detection may include different properties, derived from physics, such as positivity, from numerics, such as a non-oscillatory behavior, or from computer requirements such as the absence of NaN's. Troubled cell values are discarded and re-computed starting again from the previous time-step using a more dissipative scheme but only locally, close to these cells. By locally decrementing the degree of the polynomial reconstructions from 2 to 0 we switch from a third-order to a first-order accurate but more stable scheme. The entropy indicator sensor is used to refine/coarsen the mesh. This sensor is also employed in an a posteriori manner because if some refinement is needed at the end of a time step, then the current time-step is recomputed with the refined mesh, but only locally, close to the new cells. We show on a large set of numerical tests that this a posteriori limiting procedure coupled with the entropy-based AMR technology can maintain not only optimal accuracy on smooth flows but also stability on discontinuous profiles such as shock waves, contacts, interfaces, etc. Moreover numerical evidences show that this approach is at least comparable in terms of accuracy and cost to a more classical CWENO approach within the same AMR context.

Computerized detection of unruptured aneurysms in MRA images: reduction of false positives using anatomical location features

NASA Astrophysics Data System (ADS)

Uchiyama, Yoshikazu; Gao, Xin; Hara, Takeshi; Fujita, Hiroshi; Ando, Hiromichi; Yamakawa, Hiroyasu; Asano, Takahiko; Kato, Hiroki; Iwama, Toru; Kanematsu, Masayuki; Hoshi, Hiroaki

2008-03-01

The detection of unruptured aneurysms is a major subject in magnetic resonance angiography (MRA). However, their accurate detection is often difficult because of the overlapping between the aneurysm and the adjacent vessels on maximum intensity projection images. The purpose of this study is to develop a computerized method for the detection of unruptured aneurysms in order to assist radiologists in image interpretation. The vessel regions were first segmented using gray-level thresholding and a region growing technique. The gradient concentration (GC) filter was then employed for the enhancement of the aneurysms. The initial candidates were identified in the GC image using a gray-level threshold. For the elimination of false positives (FPs), we determined shape features and an anatomical location feature. Finally, rule-based schemes and quadratic discriminant analysis were employed along with these features for distinguishing between the aneurysms and the FPs. The sensitivity for the detection of unruptured aneurysms was 90.0% with 1.52 FPs per patient. Our computerized scheme can be useful in assisting the radiologists in the detection of unruptured aneurysms in MRA images.

A multi-view face recognition system based on cascade face detector and improved Dlib

NASA Astrophysics Data System (ADS)

Zhou, Hongjun; Chen, Pei; Shen, Wei

2018-03-01

In this research, we present a framework for multi-view face detect and recognition system based on cascade face detector and improved Dlib. This method is aimed to solve the problems of low efficiency and low accuracy in multi-view face recognition, to build a multi-view face recognition system, and to discover a suitable monitoring scheme. For face detection, the cascade face detector is used to extracted the Haar-like feature from the training samples, and Haar-like feature is used to train a cascade classifier by combining Adaboost algorithm. Next, for face recognition, we proposed an improved distance model based on Dlib to improve the accuracy of multiview face recognition. Furthermore, we applied this proposed method into recognizing face images taken from different viewing directions, including horizontal view, overlooks view, and looking-up view, and researched a suitable monitoring scheme. This method works well for multi-view face recognition, and it is also simulated and tested, showing satisfactory experimental results.

Fuzzy Inference System Approach for Locating Series, Shunt, and Simultaneous Series-Shunt Faults in Double Circuit Transmission Lines

PubMed Central

Swetapadma, Aleena; Yadav, Anamika

2015-01-01

Many schemes are reported for shunt fault location estimation, but fault location estimation of series or open conductor faults has not been dealt with so far. The existing numerical relays only detect the open conductor (series) fault and give the indication of the faulty phase(s), but they are unable to locate the series fault. The repair crew needs to patrol the complete line to find the location of series fault. In this paper fuzzy based fault detection/classification and location schemes in time domain are proposed for both series faults, shunt faults, and simultaneous series and shunt faults. The fault simulation studies and fault location algorithm have been developed using Matlab/Simulink. Synchronized phasors of voltage and current signals of both the ends of the line have been used as input to the proposed fuzzy based fault location scheme. Percentage of error in location of series fault is within 1% and shunt fault is 5% for all the tested fault cases. Validation of percentage of error in location estimation is done using Chi square test with both 1% and 5% level of significance. PMID:26413088

An authenticated image encryption scheme based on chaotic maps and memory cellular automata

NASA Astrophysics Data System (ADS)

Bakhshandeh, Atieh; Eslami, Ziba

2013-06-01

This paper introduces a new image encryption scheme based on chaotic maps, cellular automata and permutation-diffusion architecture. In the permutation phase, a piecewise linear chaotic map is utilized to confuse the plain-image and in the diffusion phase, we employ the Logistic map as well as a reversible memory cellular automata to obtain an efficient and secure cryptosystem. The proposed method admits advantages such as highly secure diffusion mechanism, computational efficiency and ease of implementation. A novel property of the proposed scheme is its authentication ability which can detect whether the image is tampered during the transmission or not. This is particularly important in applications where image data or part of it contains highly sensitive information. Results of various analyses manifest high security of this new method and its capability for practical image encryption.

Improved Readout Scheme for SQUID-Based Thermometry

NASA Technical Reports Server (NTRS)

Penanen, Konstantin

2007-01-01

An improved readout scheme has been proposed for high-resolution thermometers, (HRTs) based on the use of superconducting quantum interference devices (SQUIDs) to measure temperature- dependent magnetic susceptibilities. The proposed scheme would eliminate counting ambiguities that arise in the conventional scheme, while maintaining the superior magnetic-flux sensitivity of the conventional scheme. The proposed scheme is expected to be especially beneficial for HRT-based temperature control of multiplexed SQUIDbased bolometer sensor arrays. SQUID-based HRTs have become standard for measuring and controlling temperatures in the sub-nano-Kelvin temperature range in a broad range of low-temperature scientific and engineering applications. A typical SQUIDbased HRT that utilizes the conventional scheme includes a coil wound on a core made of a material that has temperature- dependent magnetic susceptibility in the temperature range of interest. The core and the coil are placed in a DC magnetic field provided either by a permanent magnet or as magnetic flux inside a superconducting outer wall. The aforementioned coil is connected to an input coil of a SQUID. Changes in temperature lead to changes in the susceptibility of the core and to changes in the magnetic flux detected by the SQUID. The SQUID readout instrumentation is capable of measuring magnetic-flux changes that correspond to temperature changes down to a noise limit .0.1 nK/Hz1/2. When the flux exceeds a few fundamental flux units, which typically corresponds to a temperature of .100 nK, the SQUID is reset. The temperature range can be greatly expanded if the reset events are carefully tracked and counted, either by a computer running appropriate software or by a dedicated piece of hardware.

Flexible Ag-C60 nano-biosensors based on surface plasmon coupled emission for clinical and forensic applications.

PubMed

Mulpur, Pradyumna; Yadavilli, Sairam; Mulpur, Praharsha; Kondiparthi, Neeharika; Sengupta, Bishwambhar; Rao, Apparao M; Podila, Ramakrishna; Kamisetti, Venkataramaniah

2015-10-14

The relatively low sensitivity of fluorescence detection schemes, which are mainly limited by the isotropic nature of fluorophore emission, can be overcome by utilizing surface plasmon coupled emission (SPCE). In this study, we demonstrate directional emission from fluorophores on flexible Ag-C60 SPCE sensor platforms for point-of-care sensing, in healthcare and forensic sensing scenarios, with at least 10 times higher sensitivity than traditional fluorescence sensing schemes. Adopting the highly sensitive Ag-C60 SPCE platform based on glass and novel low-cost flexible substrates, we report the unambiguous detection of acid-fast Mycobacterium tuberculosis (Mtb) bacteria at densities as low as 20 Mtb mm(-2); from non-acid-fast bacteria (e.g., E. coli and S. aureus), and the specific on-site detection of acid-fast sperm cells in human semen samples. In combination with the directional emission and high-sensitivity of SPCE platforms, we also demonstrate the utility of smartphones that can replace expensive and cumbersome detectors to enable rapid hand-held detection of analytes in resource-limited settings; a much needed critical advance to biosensors, for developing countries.

Ice detection and classification on an aircraft wing with ultrasonic shear horizontal guided waves.

PubMed

Gao, Huidong; Rose, Joseph L

2009-02-01

Ice accumulation on airfoils has been identified as a primary cause of many accidents in commercial and military aircraft. To improve aviation safety as well as reduce cost and environmental threats related to aircraft icing, sensitive, reliable, and aerodynamically compatible ice detection techniques are in great demand. Ultrasonic guided-wave-based techniques have been proved reliable for "go" and "no go" types of ice detection in some systems including the HALO system, in which the second author of this paper is a primary contributor. In this paper, we propose a new model that takes the ice layer into guided-wave modeling. Using this model, the thickness and type of ice formation can be determined from guided-wave signals. Five experimental schemes are also proposed in this paper based on some unique features identified from the guided- wave dispersion curves. A sample experiment is also presented in this paper, where a 1 mm thick glaze ice on a 2 mm aluminum plate is clearly detected. Quantitative match of the experiment data to theoretical prediction serves as a strong support for future implementation of other testing schemes proposed in this paper.

Hybrid detection of lung nodules on CT scan images

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

Lu, Lin; Tan, Yongqiang; Schwartz, Lawrence H.

Purpose: The diversity of lung nodules poses difficulty for the current computer-aided diagnostic (CAD) schemes for lung nodule detection on computed tomography (CT) scan images, especially in large-scale CT screening studies. We proposed a novel CAD scheme based on a hybrid method to address the challenges of detection in diverse lung nodules. Methods: The hybrid method proposed in this paper integrates several existing and widely used algorithms in the field of nodule detection, including morphological operation, dot-enhancement based on Hessian matrix, fuzzy connectedness segmentation, local density maximum algorithm, geodesic distance map, and regression tree classification. All of the adopted algorithmsmore » were organized into tree structures with multi-nodes. Each node in the tree structure aimed to deal with one type of lung nodule. Results: The method has been evaluated on 294 CT scans from the Lung Image Database Consortium (LIDC) dataset. The CT scans were randomly divided into two independent subsets: a training set (196 scans) and a test set (98 scans). In total, the 294 CT scans contained 631 lung nodules, which were annotated by at least two radiologists participating in the LIDC project. The sensitivity and false positive per scan for the training set were 87% and 2.61%. The sensitivity and false positive per scan for the testing set were 85.2% and 3.13%. Conclusions: The proposed hybrid method yielded high performance on the evaluation dataset and exhibits advantages over existing CAD schemes. We believe that the present method would be useful for a wide variety of CT imaging protocols used in both routine diagnosis and screening studies.« less

Integration of Model-Based Estimation Theory With an Adaptive Finite Volume Method for the Detection of a Moving Gaseous Source via a Mobile Sensor

DTIC Science & Technology

2012-02-29

couples the estimation scheme with the computational scheme, using one to enhance the other. Numerically, this switching changes several of the matrices...2011. 11. M.A. Demetriou, Enforcing and enhancing consensus of spatially distributed filters utilizing mobile sensor networks, Proceedings of the 49th...expected May, 2012. References [1] J. H. Seinfeld and S. N. Pandis, Atmospheric Chemistry and Physics: From Air Pollution to Climate Change. New York

Quantum key distribution with passive decoy state selection

NASA Astrophysics Data System (ADS)

Mauerer, Wolfgang; Silberhorn, Christine

2007-05-01

We propose a quantum key distribution scheme which closely matches the performance of a perfect single photon source. It nearly attains the physical upper bound in terms of key generation rate and maximally achievable distance. Our scheme relies on a practical setup based on a parametric downconversion source and present day, nonideal photon-number detection. Arbitrary experimental imperfections which lead to bit errors are included. We select decoy states by classical postprocessing. This allows one to improve the effective signal statistics and achievable distance.

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.

Compact, cost-effective and field-portable microscope prototype based on MISHELF microscopy

NASA Astrophysics Data System (ADS)

Sanz, Martín; Picazo-Bueno, José Ángel; Granero, Luis; García, Javier; Micó, Vicente

2017-02-01

We report on a reduced cost, portable and compact prototype design of lensless holographic microscope with an illumination/detection scheme based on wavelength multiplexing, working with single hologram acquisition and using a fast convergence algorithm for image processing. All together, MISHELF (initials coming from Multi-Illumination Single-Holographic-Exposure Lensless Fresnel) microscopy allows the recording of three Fresnel domain diffraction patterns in a single camera snap-shot incoming from illuminating the sample with three coherent lights at once. Previous implementations have proposed an illumination/detection procedure based on a tuned (illumination wavelengths centered at the maximum sensitivity of the camera detection channels) configuration but here we report on a detuned (non-centered ones) scheme resulting in prototype miniaturization and cost reduction. Thus, MISHELF microscopy in combination with a novel and fast iterative algorithm allows high-resolution (μm range) phase-retrieved (twin image elimination) quantitative phase imaging of dynamic events (video rate recording speed). The performance of this microscope prototype is validated through experiments using both amplitude (USAF resolution test) and complex (live swine sperm cells and flowing microbeads) samples. The proposed method becomes in an alternative instrument improving some capabilities of existing lensless microscopes.

Compact, cost-effective and field-portable microscope prototype based on MISHELF microscopy

PubMed Central

Sanz, Martín; Picazo-Bueno, José Ángel; Granero, Luis; García, Javier; Micó, Vicente

2017-01-01

We report on a reduced cost, portable and compact prototype design of lensless holographic microscope with an illumination/detection scheme based on wavelength multiplexing, working with single hologram acquisition and using a fast convergence algorithm for image processing. All together, MISHELF (initials coming from Multi-Illumination Single-Holographic-Exposure Lensless Fresnel) microscopy allows the recording of three Fresnel domain diffraction patterns in a single camera snap-shot incoming from illuminating the sample with three coherent lights at once. Previous implementations have proposed an illumination/detection procedure based on a tuned (illumination wavelengths centered at the maximum sensitivity of the camera detection channels) configuration but here we report on a detuned (non-centered ones) scheme resulting in prototype miniaturization and cost reduction. Thus, MISHELF microscopy in combination with a novel and fast iterative algorithm allows high-resolution (μm range) phase-retrieved (twin image elimination) quantitative phase imaging of dynamic events (video rate recording speed). The performance of this microscope prototype is validated through experiments using both amplitude (USAF resolution test) and complex (live swine sperm cells and flowing microbeads) samples. The proposed method becomes in an alternative instrument improving some capabilities of existing lensless microscopes. PMID:28233829

Distributed Denial of Service Attack Source Detection Using Efficient Traceback Technique (ETT) in Cloud-Assisted Healthcare Environment.

PubMed

Latif, Rabia; Abbas, Haider; Latif, Seemab; Masood, Ashraf

2016-07-01

Security and privacy are the first and foremost concerns that should be given special attention when dealing with Wireless Body Area Networks (WBANs). As WBAN sensors operate in an unattended environment and carry critical patient health information, Distributed Denial of Service (DDoS) attack is one of the major attacks in WBAN environment that not only exhausts the available resources but also influence the reliability of information being transmitted. This research work is an extension of our previous work in which a machine learning based attack detection algorithm is proposed to detect DDoS attack in WBAN environment. However, in order to avoid complexity, no consideration was given to the traceback mechanism. During traceback, the challenge lies in reconstructing the attack path leading to identify the attack source. Among existing traceback techniques, Probabilistic Packet Marking (PPM) approach is the most commonly used technique in conventional IP- based networks. However, since marking probability assignment has significant effect on both the convergence time and performance of a scheme, it is not directly applicable in WBAN environment due to high convergence time and overhead on intermediate nodes. Therefore, in this paper we have proposed a new scheme called Efficient Traceback Technique (ETT) based on Dynamic Probability Packet Marking (DPPM) approach and uses MAC header in place of IP header. Instead of using fixed marking probability, the proposed scheme uses variable marking probability based on the number of hops travelled by a packet to reach the target node. Finally, path reconstruction algorithms are proposed to traceback an attacker. Evaluation and simulation results indicate that the proposed solution outperforms fixed PPM in terms of convergence time and computational overhead on nodes.

Turbulence mitigation scheme based on multiple-user detection in an orbital-angular-momentum multiplexed system

NASA Astrophysics Data System (ADS)

Zou, Li; Wang, Le; Zhao, Sheng-Mei; Chen, Han-Wu

2016-11-01

Atmospheric turbulence (AT) induced crosstalk can significantly impair the performance of a free-space optical (FSO) communication link using orbital angular momentum (OAM) multiplexing. In this paper, we propose a multiple-user detection (MUD) turbulence mitigation scheme in an OAM-multiplexed FSO communication link. First, we present a MUD equivalent communication model for an OAM-multiplexed FSO communication link under AT. In the equivalent model, each input bit stream represents one user’s information. The deformed OAM spatial modes caused by AT, instead of the pure OAM spatial modes, are used as information carriers, and the overlapping between the deformed OAM spatial modes are computed as the correlation coefficients between the users. Then, we present a turbulence mitigation scheme based on MUD idea to enhance AT tolerance of the OAM-multiplexed FSO communication link. In the proposed scheme, the crosstalk caused by AT is used as a useful component to deduce users’ information. The numerical results show that the performance of the OAM-multiplexed communication link has greatly improved by the proposed scheme. When the turbulence strength is 1 × 10-15 m-2/3, the transmission distance is 1000 m and the channel signal-to-noise ratio (SNR) is 26 dB, the bit-error-rate (BER) performance of four spatial multiplexed OAM modes lm = +1,+2,+3,+4 are all close to 10-5, and there is a 2-3 fold increase in the BER performance in comparison with those results without the proposed scheme. In addition, the proposed scheme is more effective for an OAM-multiplexed FSO communication link with a larger OAM mode topological charge interval. The proposed scheme is a promising direction for compensating the interference caused by AT in the OAM-multiplexed FSO communication link. Project supported by the National Natural Science Foundation of China (Grant Nos. 61271238 and 61475075), the Open Research Fund of Key Lab of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education, China (Grant No. NYKL2015011), the Postgraduate Innovation Research Plan of Jiangsu Province, China (Grant No. CXZZ13_0489), and the University Natural Science Foundation of Jiangsu Province, China (Grant No. 16KJB510037).

An improved anonymous authentication scheme for roaming in ubiquitous networks.

PubMed

Lee, Hakjun; Lee, Donghoon; Moon, Jongho; Jung, Jaewook; Kang, Dongwoo; Kim, Hyoungshick; Won, Dongho

2018-01-01

With the evolution of communication technology and the exponential increase of mobile devices, the ubiquitous networking allows people to use our data and computing resources anytime and everywhere. However, numerous security concerns and complicated requirements arise as these ubiquitous networks are deployed throughout people's lives. To meet the challenge, the user authentication schemes in ubiquitous networks should ensure the essential security properties for the preservation of the privacy with low computational cost. In 2017, Chaudhry et al. proposed a password-based authentication scheme for the roaming in ubiquitous networks to enhance the security. Unfortunately, we found that their scheme remains insecure in its protection of the user privacy. In this paper, we prove that Chaudhry et al.'s scheme is vulnerable to the stolen-mobile device and user impersonation attacks, and its drawbacks comprise the absence of the incorrect login-input detection, the incorrectness of the password change phase, and the absence of the revocation provision. Moreover, we suggest a possible way to fix the security flaw in Chaudhry et al's scheme by using the biometric-based authentication for which the bio-hash is applied in the implementation of a three-factor authentication. We prove the security of the proposed scheme with the random oracle model and formally verify its security properties using a tool named ProVerif, and analyze it in terms of the computational and communication cost. The analysis result shows that the proposed scheme is suitable for resource-constrained ubiquitous environments.

An improved anonymous authentication scheme for roaming in ubiquitous networks

PubMed Central

Lee, Hakjun; Lee, Donghoon; Moon, Jongho; Jung, Jaewook; Kang, Dongwoo; Kim, Hyoungshick

2018-01-01

With the evolution of communication technology and the exponential increase of mobile devices, the ubiquitous networking allows people to use our data and computing resources anytime and everywhere. However, numerous security concerns and complicated requirements arise as these ubiquitous networks are deployed throughout people’s lives. To meet the challenge, the user authentication schemes in ubiquitous networks should ensure the essential security properties for the preservation of the privacy with low computational cost. In 2017, Chaudhry et al. proposed a password-based authentication scheme for the roaming in ubiquitous networks to enhance the security. Unfortunately, we found that their scheme remains insecure in its protection of the user privacy. In this paper, we prove that Chaudhry et al.’s scheme is vulnerable to the stolen-mobile device and user impersonation attacks, and its drawbacks comprise the absence of the incorrect login-input detection, the incorrectness of the password change phase, and the absence of the revocation provision. Moreover, we suggest a possible way to fix the security flaw in Chaudhry et al’s scheme by using the biometric-based authentication for which the bio-hash is applied in the implementation of a three-factor authentication. We prove the security of the proposed scheme with the random oracle model and formally verify its security properties using a tool named ProVerif, and analyze it in terms of the computational and communication cost. The analysis result shows that the proposed scheme is suitable for resource-constrained ubiquitous environments. PMID:29505575

Optical measurement of sound using time-varying laser speckle patterns

NASA Astrophysics Data System (ADS)

Leung, Terence S.; Jiang, Shihong; Hebden, Jeremy

2011-02-01

In this work, we introduce an optical technique to measure sound. The technique involves pointing a coherent pulsed laser beam on the surface of the measurement site and capturing the time-varying speckle patterns using a CCD camera. Sound manifests itself as vibrations on the surface which induce a periodic translation of the speckle pattern over time. Using a parallel speckle detection scheme, the dynamics of the time-varying speckle patterns can be captured and processed to produce spectral information of the sound. One potential clinical application is to measure pathological sounds from the brain as a screening test. We performed experiments to demonstrate the principle of the detection scheme using head phantoms. The results show that the detection scheme can measure the spectra of single frequency sounds between 100 and 2000 Hz. The detection scheme worked equally well in both a flat geometry and an anatomical head geometry. However, the current detection scheme is too slow for use in living biological tissues which has a decorrelation time of a few milliseconds. Further improvements have been suggested.

Amplified detection of cocaine based on strand-displacement polymerization and fluorescence resonance energy transfer.

PubMed

Huang, Jin; Chen, Yan; Yang, Liu; Zhu, Zhi; Zhu, Guizhi; Yang, Xiaohai; Wang, Kemin; Tan, Weihong

2011-10-15

Cocaine is one of the most abused drugs in the United States and is potentially dangerous when consumed in excess. Its detection is thus important in many areas in the fight against drug trafficking. We have developed an amplified detection method for cocaine based on a strand-displacement polymerization reaction using aptamer recognition. The system mainly consists of a hairpin probe with Cy5 labeled on its 3' end, a primer with FAM labeled on its 5' end, and polymerase. The aptamer sequence is integrated into the 5'-section of the hairpin probe. The primer is designed complementary to the 3' end of the hairpin probe, which is also part of the hairpin stem region. The cocaine induced reaction cycle generates product for detection and thus for signal amplification. The detection limit of this method is 200 nM in about 16 min and the specificity of this approach is excellent. We believe that this strategy will be useful for the development of analytical schemes for a variety of aptamers for small molecules, metal ions, and proteins. This simple scheme employing the strand-displacement polymerization reaction may find wide application in forensic analysis, environmental monitoring, and clinical diagnostics. Copyright © 2011 Elsevier B.V. All rights reserved.

Vision communications based on LED array and imaging sensor

NASA Astrophysics Data System (ADS)

Yoo, Jong-Ho; Jung, Sung-Yoon

2012-11-01

In this paper, we propose a brand new communication concept, called as "vision communication" based on LED array and image sensor. This system consists of LED array as a transmitter and digital device which include image sensor such as CCD and CMOS as receiver. In order to transmit data, the proposed communication scheme simultaneously uses the digital image processing and optical wireless communication scheme. Therefore, the cognitive communication scheme is possible with the help of recognition techniques used in vision system. By increasing data rate, our scheme can use LED array consisting of several multi-spectral LEDs. Because arranged each LED can emit multi-spectral optical signal such as visible, infrared and ultraviolet light, the increase of data rate is possible similar to WDM and MIMO skills used in traditional optical and wireless communications. In addition, this multi-spectral capability also makes it possible to avoid the optical noises in communication environment. In our vision communication scheme, the data packet is composed of Sync. data and information data. Sync. data is used to detect the transmitter area and calibrate the distorted image snapshots obtained by image sensor. By making the optical rate of LED array be same with the frame rate (frames per second) of image sensor, we can decode the information data included in each image snapshot based on image processing and optical wireless communication techniques. Through experiment based on practical test bed system, we confirm the feasibility of the proposed vision communications based on LED array and image sensor.

A paralleled readout system for an electrical DNA-hybridization assay based on a microstructured electrode array

NASA Astrophysics Data System (ADS)

Urban, Matthias; Möller, Robert; Fritzsche, Wolfgang

2003-02-01

DNA analytics is a growing field based on the increasing knowledge about the genome with special implications for the understanding of molecular bases for diseases. Driven by the need for cost-effective and high-throughput methods for molecular detection, DNA chips are an interesting alternative to more traditional analytical methods in this field. The standard readout principle for DNA chips is fluorescence based. Fluorescence is highly sensitive and broadly established, but shows limitations regarding quantification (due to signal and/or dye instability) and the need for sophisticated (and therefore high-cost) equipment. This article introduces a readout system for an alternative detection scheme based on electrical detection of nanoparticle-labeled DNA. If labeled DNA is present in the analyte solution, it will bind on complementary capture DNA immobilized in a microelectrode gap. A subsequent metal enhancement step leads to a deposition of conductive material on the nanoparticles, and finally an electrical contact between the electrodes. This detection scheme offers the potential for a simple (low-cost as well as robust) and highly miniaturizable method, which could be well-suited for point-of-care applications in the context of lab-on-a-chip technologies. The demonstrated apparatus allows a parallel readout of an entire array of microstructured measurement sites. The readout is combined with data-processing by an embedded personal computer, resulting in an autonomous instrument that measures and presents the results. The design and realization of such a system is described, and first measurements are presented.

An Improved Pathological Brain Detection System Based on Two-Dimensional PCA and Evolutionary Extreme Learning Machine.

PubMed

Nayak, Deepak Ranjan; Dash, Ratnakar; Majhi, Banshidhar

2017-12-07

Pathological brain detection has made notable stride in the past years, as a consequence many pathological brain detection systems (PBDSs) have been proposed. But, the accuracy of these systems still needs significant improvement in order to meet the necessity of real world diagnostic situations. In this paper, an efficient PBDS based on MR images is proposed that markedly improves the recent results. The proposed system makes use of contrast limited adaptive histogram equalization (CLAHE) to enhance the quality of the input MR images. Thereafter, two-dimensional PCA (2DPCA) strategy is employed to extract the features and subsequently, a PCA+LDA approach is used to generate a compact and discriminative feature set. Finally, a new learning algorithm called MDE-ELM is suggested that combines modified differential evolution (MDE) and extreme learning machine (ELM) for segregation of MR images as pathological or healthy. The MDE is utilized to optimize the input weights and hidden biases of single-hidden-layer feed-forward neural networks (SLFN), whereas an analytical method is used for determining the output weights. The proposed algorithm performs optimization based on both the root mean squared error (RMSE) and norm of the output weights of SLFNs. The suggested scheme is benchmarked on three standard datasets and the results are compared against other competent schemes. The experimental outcomes show that the proposed scheme offers superior results compared to its counterparts. Further, it has been noticed that the proposed MDE-ELM classifier obtains better accuracy with compact network architecture than conventional algorithms.

Enhanced photoelectric detection of NV magnetic resonances in diamond under dual-beam excitation

NASA Astrophysics Data System (ADS)

Bourgeois, E.; Londero, E.; Buczak, K.; Hruby, J.; Gulka, M.; Balasubramaniam, Y.; Wachter, G.; Stursa, J.; Dobes, K.; Aumayr, F.; Trupke, M.; Gali, A.; Nesladek, M.

2017-01-01

The core issue for the implementation of NV center qubit technology is a sensitive readout of the NV spin state. We present here a detailed theoretical and experimental study of NV center photoionization processes, used as a basis for the design of a dual-beam photoelectric method for the detection of NV magnetic resonances (PDMR). This scheme, based on NV one-photon ionization, is significantly more efficient than the previously reported single-beam excitation scheme. We demonstrate this technique on small ensembles of ˜10 shallow NVs implanted in electronic grade diamond (a relevant material for quantum technology), on which we achieve a cw magnetic resonance contrast of 9%—three times enhanced compared to previous work. The dual-beam PDMR scheme allows independent control of the photoionization rate and spin magnetic resonance contrast. Under a similar excitation, we obtain a significantly higher photocurrent, and thus an improved signal-to-noise ratio, compared to single-beam PDMR. Finally, this scheme is predicted to enhance magnetic resonance contrast in the case of samples with a high proportion of substitutional nitrogen defects, and could therefore enable the photoelectric readout of single NV spins.

DS-ARP: a new detection scheme for ARP spoofing attacks based on routing trace for ubiquitous environments.

PubMed

Song, Min Su; Lee, Jae Dong; Jeong, Young-Sik; Jeong, Hwa-Young; Park, Jong Hyuk

2014-01-01

Despite the convenience, ubiquitous computing suffers from many threats and security risks. Security considerations in the ubiquitous network are required to create enriched and more secure ubiquitous environments. The address resolution protocol (ARP) is a protocol used to identify the IP address and the physical address of the associated network card. ARP is designed to work without problems in general environments. However, since it does not include security measures against malicious attacks, in its design, an attacker can impersonate another host using ARP spoofing or access important information. In this paper, we propose a new detection scheme for ARP spoofing attacks using a routing trace, which can be used to protect the internal network. Tracing routing can find the change of network movement path. The proposed scheme provides high constancy and compatibility because it does not alter the ARP protocol. In addition, it is simple and stable, as it does not use a complex algorithm or impose extra load on the computer system.

DS-ARP: A New Detection Scheme for ARP Spoofing Attacks Based on Routing Trace for Ubiquitous Environments

PubMed Central

Song, Min Su; Lee, Jae Dong; Jeong, Hwa-Young; Park, Jong Hyuk

2014-01-01

Despite the convenience, ubiquitous computing suffers from many threats and security risks. Security considerations in the ubiquitous network are required to create enriched and more secure ubiquitous environments. The address resolution protocol (ARP) is a protocol used to identify the IP address and the physical address of the associated network card. ARP is designed to work without problems in general environments. However, since it does not include security measures against malicious attacks, in its design, an attacker can impersonate another host using ARP spoofing or access important information. In this paper, we propose a new detection scheme for ARP spoofing attacks using a routing trace, which can be used to protect the internal network. Tracing routing can find the change of network movement path. The proposed scheme provides high constancy and compatibility because it does not alter the ARP protocol. In addition, it is simple and stable, as it does not use a complex algorithm or impose extra load on the computer system. PMID:25243205

A novel track-before-detect algorithm based on optimal nonlinear filtering for detecting and tracking infrared dim target

NASA Astrophysics Data System (ADS)

Tian, Yuexin; Gao, Kun; Liu, Ying; Han, Lu

2015-08-01

Aiming at the nonlinear and non-Gaussian features of the real infrared scenes, an optimal nonlinear filtering based algorithm for the infrared dim target tracking-before-detecting application is proposed. It uses the nonlinear theory to construct the state and observation models and uses the spectral separation scheme based Wiener chaos expansion method to resolve the stochastic differential equation of the constructed models. In order to improve computation efficiency, the most time-consuming operations independent of observation data are processed on the fore observation stage. The other observation data related rapid computations are implemented subsequently. Simulation results show that the algorithm possesses excellent detection performance and is more suitable for real-time processing.

Automobile inspection system based on wireless communication

NASA Astrophysics Data System (ADS)

Miao, Changyun; Ye, Chunqing

2010-07-01

This paper aims to research the Automobile Inspection System based on Wireless Communication, and suggests an overall design scheme which uses GPS for speed detection and Bluetooth and GPRS for communication. The communication between PDA and PC was realized by means of GPRS and TCP/IP; and the hardware circuit and software for detection terminal were devised by means of JINOU-3264 Bluetooth Module after analyzing the Bluetooth and its communication protocol. According to the results of debugging test, this system accomplished GPRS based data communication and management as well as the real-time detection on auto safety performance parameters in crash test via PC, whereby the need for mobility and reliability was met and the efficiency and level of detection was improved.

Watermarking of ultrasound medical images in teleradiology using compressed watermark

PubMed Central

Badshah, Gran; Liew, Siau-Chuin; Zain, Jasni Mohamad; Ali, Mushtaq

2016-01-01

Abstract. The open accessibility of Internet-based medical images in teleradialogy face security threats due to the nonsecured communication media. This paper discusses the spatial domain watermarking of ultrasound medical images for content authentication, tamper detection, and lossless recovery. For this purpose, the image is divided into two main parts, the region of interest (ROI) and region of noninterest (RONI). The defined ROI and its hash value are combined as watermark, lossless compressed, and embedded into the RONI part of images at pixel’s least significant bits (LSBs). The watermark lossless compression and embedding at pixel’s LSBs preserve image diagnostic and perceptual qualities. Different lossless compression techniques including Lempel-Ziv-Welch (LZW) were tested for watermark compression. The performances of these techniques were compared based on more bit reduction and compression ratio. LZW was found better than others and used in tamper detection and recovery watermarking of medical images (TDARWMI) scheme development to be used for ROI authentication, tamper detection, localization, and lossless recovery. TDARWMI performance was compared and found to be better than other watermarking schemes. PMID:26839914

Generating the local oscillator "locally" in continuous-variable quantum key distribution based on coherent detection

DOE PAGES

Qi, Bing; Lougovski, Pavel; Pooser, Raphael C.; ...

2015-10-21

Continuous-variable quantum key distribution (CV-QKD) protocols based on coherent detection have been studied extensively in both theory and experiment. In all the existing implementations of CV-QKD, both the quantum signal and the local oscillator (LO) are generated from the same laser and propagate through the insecure quantum channel. This arrangement may open security loopholes and limit the potential applications of CV-QKD. In our paper, we propose and demonstrate a pilot-aided feedforward data recovery scheme that enables reliable coherent detection using a “locally” generated LO. Using two independent commercial laser sources and a spool of 25-km optical fiber, we construct amore » coherent communication system. The variance of the phase noise introduced by the proposed scheme is measured to be 0.04 (rad 2), which is small enough to enable secure key distribution. This technology opens the door for other quantum communication protocols, such as the recently proposed measurement-device-independent CV-QKD, where independent light sources are employed by different users.« less

NMRPipe: a multidimensional spectral processing system based on UNIX pipes.

PubMed

Delaglio, F; Grzesiek, S; Vuister, G W; Zhu, G; Pfeifer, J; Bax, A

1995-11-01

The NMRPipe system is a UNIX software environment of processing, graphics, and analysis tools designed to meet current routine and research-oriented multidimensional processing requirements, and to anticipate and accommodate future demands and developments. The system is based on UNIX pipes, which allow programs running simultaneously to exchange streams of data under user control. In an NMRPipe processing scheme, a stream of spectral data flows through a pipeline of processing programs, each of which performs one component of the overall scheme, such as Fourier transformation or linear prediction. Complete multidimensional processing schemes are constructed as simple UNIX shell scripts. The processing modules themselves maintain and exploit accurate records of data sizes, detection modes, and calibration information in all dimensions, so that schemes can be constructed without the need to explicitly define or anticipate data sizes or storage details of real and imaginary channels during processing. The asynchronous pipeline scheme provides other substantial advantages, including high flexibility, favorable processing speeds, choice of both all-in-memory and disk-bound processing, easy adaptation to different data formats, simpler software development and maintenance, and the ability to distribute processing tasks on multi-CPU computers and computer networks.

Direct trust-based security scheme for RREQ flooding attack in mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Kumar, Sunil; Dutta, Kamlesh

2017-06-01

The routing algorithms in MANETs exhibit distributed and cooperative behaviour which makes them easy target for denial of service (DoS) attacks. RREQ flooding attack is a flooding-type DoS attack in context to Ad hoc On Demand Distance Vector (AODV) routing protocol, where the attacker broadcasts massive amount of bogus Route Request (RREQ) packets to set up the route with the non-existent or existent destination in the network. This paper presents direct trust-based security scheme to detect and mitigate the impact of RREQ flooding attack on the network, in which, every node evaluates the trust degree value of its neighbours through analysing the frequency of RREQ packets originated by them over a short period of time. Taking the node's trust degree value as the input, the proposed scheme is smoothly extended for suppressing the surplus RREQ and bogus RREQ flooding packets at one-hop neighbours during the route discovery process. This scheme distinguishes itself from existing techniques by not directly blocking the service of a normal node due to increased amount of RREQ packets in some unusual conditions. The results obtained throughout the simulation experiments clearly show the feasibility and effectiveness of the proposed defensive scheme.

Distributed measurement of polarization mode coupling in fiber ring based on P-OTDR complete polarization state detection.

PubMed

Huang, Zejia; Wu, Chongqing; Wang, Zhi; Wang, Jian; Liu, Lanlan

2018-02-19

Using a quaternion method, the polarization mode-coupling coefficient can be derived from three components of the Stokes vectors at three adjacent points along a fiber. A complete polarization optical time-domain reflectometry scheme for polarization mode coupling distributed measurement in polarization-maintaining fiber ring is proposed based on the above theoretical derivations. By comparing the measurement results of two opposite incident directions and two orthogonal polarization axes of polarization-maintaining fiber rings with different lengths, the feasibility and repeatability of the measurement scheme are verified experimentally with a positioning spatial resolution of 1 meter.

Assistive obstacle detection and navigation devices for vision-impaired users.

PubMed

Ong, S K; Zhang, J; Nee, A Y C

2013-09-01

Quality of life for the visually impaired is an urgent worldwide issue that needs to be addressed. Obstacle detection is one of the most important navigation tasks for the visually impaired. In this research, a novel range sensor placement scheme is proposed in this paper for the development of obstacle detection devices. Based on this scheme, two prototypes have been developed targeting at different user groups. This paper discusses the design issues, functional modules and the evaluation tests carried out for both prototypes. Implications for Rehabilitation Visual impairment problem is becoming more severe due to the worldwide ageing population. Individuals with visual impairment require assistance from assistive devices in daily navigation tasks. Traditional assistive devices that assist navigation may have certain drawbacks, such as the limited sensing range of a white cane. Obstacle detection devices applying the range sensor technology can identify road conditions with a higher sensing range to notify the users of potential dangers in advance.

Detection of pseudosinusoidal epileptic seizure segments in the neonatal EEG by cascading a rule-based algorithm with a neural network.

PubMed

Karayiannis, Nicolaos B; Mukherjee, Amit; Glover, John R; Ktonas, Periklis Y; Frost, James D; Hrachovy, Richard A; Mizrahi, Eli M

2006-04-01

This paper presents an approach to detect epileptic seizure segments in the neonatal electroencephalogram (EEG) by characterizing the spectral features of the EEG waveform using a rule-based algorithm cascaded with a neural network. A rule-based algorithm screens out short segments of pseudosinusoidal EEG patterns as epileptic based on features in the power spectrum. The output of the rule-based algorithm is used to train and compare the performance of conventional feedforward neural networks and quantum neural networks. The results indicate that the trained neural networks, cascaded with the rule-based algorithm, improved the performance of the rule-based algorithm acting by itself. The evaluation of the proposed cascaded scheme for the detection of pseudosinusoidal seizure segments reveals its potential as a building block of the automated seizure detection system under development.

Locally adaptive decision in detection of clustered microcalcifications in mammograms.

PubMed

Sainz de Cea, María V; Nishikawa, Robert M; Yang, Yongyi

2018-02-15

In computer-aided detection or diagnosis of clustered microcalcifications (MCs) in mammograms, the performance often suffers from not only the presence of false positives (FPs) among the detected individual MCs but also large variability in detection accuracy among different cases. To address this issue, we investigate a locally adaptive decision scheme in MC detection by exploiting the noise characteristics in a lesion area. Instead of developing a new MC detector, we propose a decision scheme on how to best decide whether a detected object is an MC or not in the detector output. We formulate the individual MCs as statistical outliers compared to the many noisy detections in a lesion area so as to account for the local image characteristics. To identify the MCs, we first consider a parametric method for outlier detection, the Mahalanobis distance detector, which is based on a multi-dimensional Gaussian distribution on the noisy detections. We also consider a non-parametric method which is based on a stochastic neighbor graph model of the detected objects. We demonstrated the proposed decision approach with two existing MC detectors on a set of 188 full-field digital mammograms (95 cases). The results, evaluated using free response operating characteristic (FROC) analysis, showed a significant improvement in detection accuracy by the proposed outlier decision approach over traditional thresholding (the partial area under the FROC curve increased from 3.95 to 4.25, p-value  <10 -4 ). There was also a reduction in case-to-case variability in detected FPs at a given sensitivity level. The proposed adaptive decision approach could not only reduce the number of FPs in detected MCs but also improve case-to-case consistency in detection.

Locally adaptive decision in detection of clustered microcalcifications in mammograms

NASA Astrophysics Data System (ADS)

Sainz de Cea, María V.; Nishikawa, Robert M.; Yang, Yongyi

2018-02-01

In computer-aided detection or diagnosis of clustered microcalcifications (MCs) in mammograms, the performance often suffers from not only the presence of false positives (FPs) among the detected individual MCs but also large variability in detection accuracy among different cases. To address this issue, we investigate a locally adaptive decision scheme in MC detection by exploiting the noise characteristics in a lesion area. Instead of developing a new MC detector, we propose a decision scheme on how to best decide whether a detected object is an MC or not in the detector output. We formulate the individual MCs as statistical outliers compared to the many noisy detections in a lesion area so as to account for the local image characteristics. To identify the MCs, we first consider a parametric method for outlier detection, the Mahalanobis distance detector, which is based on a multi-dimensional Gaussian distribution on the noisy detections. We also consider a non-parametric method which is based on a stochastic neighbor graph model of the detected objects. We demonstrated the proposed decision approach with two existing MC detectors on a set of 188 full-field digital mammograms (95 cases). The results, evaluated using free response operating characteristic (FROC) analysis, showed a significant improvement in detection accuracy by the proposed outlier decision approach over traditional thresholding (the partial area under the FROC curve increased from 3.95 to 4.25, p-value  <10-4). There was also a reduction in case-to-case variability in detected FPs at a given sensitivity level. The proposed adaptive decision approach could not only reduce the number of FPs in detected MCs but also improve case-to-case consistency in detection.

A Resonant Synchronous Vibration Based Approach for Rotor Imbalance Detection

NASA Technical Reports Server (NTRS)

Luo, Huangeng; Rodriquez, Hector; Hallman, Darren; Lewicki, David G.

2006-01-01

This paper presents a methodology of detecting rotor imbalances, such as mass imbalance and crack-induced imbalance, using shaft synchronous vibrations. An iterative scheme is developed to identify parameters from measured synchronous vibration data. A detection system is integrated by using state-of-the-art commercial analysis equipment. A laboratory rotor test rig is used to verify the system integration and algorithm validation. A real engine test has been carried out and the results are reported.

Computer-Aided Diagnosis in Medical Imaging: Historical Review, Current Status and Future Potential

PubMed Central

Doi, Kunio

2007-01-01

Computer-aided diagnosis (CAD) has become one of the major research subjects in medical imaging and diagnostic radiology. In this article, the motivation and philosophy for early development of CAD schemes are presented together with the current status and future potential of CAD in a PACS environment. With CAD, radiologists use the computer output as a “second opinion” and make the final decisions. CAD is a concept established by taking into account equally the roles of physicians and computers, whereas automated computer diagnosis is a concept based on computer algorithms only. With CAD, the performance by computers does not have to be comparable to or better than that by physicians, but needs to be complementary to that by physicians. In fact, a large number of CAD systems have been employed for assisting physicians in the early detection of breast cancers on mammograms. A CAD scheme that makes use of lateral chest images has the potential to improve the overall performance in the detection of lung nodules when combined with another CAD scheme for PA chest images. Because vertebral fractures can be detected reliably by computer on lateral chest radiographs, radiologists’ accuracy in the detection of vertebral fractures would be improved by the use of CAD, and thus early diagnosis of osteoporosis would become possible. In MRA, a CAD system has been developed for assisting radiologists in the detection of intracranial aneurysms. On successive bone scan images, a CAD scheme for detection of interval changes has been developed by use of temporal subtraction images. In the future, many CAD schemes could be assembled as packages and implemented as a part of PACS. For example, the package for chest CAD may include the computerized detection of lung nodules, interstitial opacities, cardiomegaly, vertebral fractures, and interval changes in chest radiographs as well as the computerized classification of benign and malignant nodules and the differential diagnosis of interstitial lung diseases. In order to assist in the differential diagnosis, it would be possible to search for and retrieve images (or lesions) with known pathology, which would be very similar to a new unknown case, from PACS when a reliable and useful method has been developed for quantifying the similarity of a pair of images for visual comparison by radiologists. PMID:17349778

Wavelet subspace decomposition of thermal infrared images for defect detection in artworks

NASA Astrophysics Data System (ADS)

Ahmad, M. Z.; Khan, A. A.; Mezghani, S.; Perrin, E.; Mouhoubi, K.; Bodnar, J. L.; Vrabie, V.

2016-07-01

Health of ancient artworks must be routinely monitored for their adequate preservation. Faults in these artworks may develop over time and must be identified as precisely as possible. The classical acoustic testing techniques, being invasive, risk causing permanent damage during periodic inspections. Infrared thermometry offers a promising solution to map faults in artworks. It involves heating the artwork and recording its thermal response using infrared camera. A novel strategy based on pseudo-random binary excitation principle is used in this work to suppress the risks associated with prolonged heating. The objective of this work is to develop an automatic scheme for detecting faults in the captured images. An efficient scheme based on wavelet based subspace decomposition is developed which favors identification of, the otherwise invisible, weaker faults. Two major problems addressed in this work are the selection of the optimal wavelet basis and the subspace level selection. A novel criterion based on regional mutual information is proposed for the latter. The approach is successfully tested on a laboratory based sample as well as real artworks. A new contrast enhancement metric is developed to demonstrate the quantitative efficiency of the algorithm. The algorithm is successfully deployed for both laboratory based and real artworks.

An Effective and Robust Decentralized Target Tracking Scheme in Wireless Camera Sensor Networks.

PubMed

Fu, Pengcheng; Cheng, Yongbo; Tang, Hongying; Li, Baoqing; Pei, Jun; Yuan, Xiaobing

2017-03-20

In this paper, we propose an effective and robust decentralized tracking scheme based on the square root cubature information filter (SRCIF) to balance the energy consumption and tracking accuracy in wireless camera sensor networks (WCNs). More specifically, regarding the characteristics and constraints of camera nodes in WCNs, some special mechanisms are put forward and integrated in this tracking scheme. First, a decentralized tracking approach is adopted so that the tracking can be implemented energy-efficiently and steadily. Subsequently, task cluster nodes are dynamically selected by adopting a greedy on-line decision approach based on the defined contribution decision (CD) considering the limited energy of camera nodes. Additionally, we design an efficient cluster head (CH) selection mechanism that casts such selection problem as an optimization problem based on the remaining energy and distance-to-target. Finally, we also perform analysis on the target detection probability when selecting the task cluster nodes and their CH, owing to the directional sensing and observation limitations in field of view (FOV) of camera nodes in WCNs. From simulation results, the proposed tracking scheme shows an obvious improvement in balancing the energy consumption and tracking accuracy over the existing methods.

An Effective and Robust Decentralized Target Tracking Scheme in Wireless Camera Sensor Networks

PubMed Central

Fu, Pengcheng; Cheng, Yongbo; Tang, Hongying; Li, Baoqing; Pei, Jun; Yuan, Xiaobing

2017-01-01

In this paper, we propose an effective and robust decentralized tracking scheme based on the square root cubature information filter (SRCIF) to balance the energy consumption and tracking accuracy in wireless camera sensor networks (WCNs). More specifically, regarding the characteristics and constraints of camera nodes in WCNs, some special mechanisms are put forward and integrated in this tracking scheme. First, a decentralized tracking approach is adopted so that the tracking can be implemented energy-efficiently and steadily. Subsequently, task cluster nodes are dynamically selected by adopting a greedy on-line decision approach based on the defined contribution decision (CD) considering the limited energy of camera nodes. Additionally, we design an efficient cluster head (CH) selection mechanism that casts such selection problem as an optimization problem based on the remaining energy and distance-to-target. Finally, we also perform analysis on the target detection probability when selecting the task cluster nodes and their CH, owing to the directional sensing and observation limitations in field of view (FOV) of camera nodes in WCNs. From simulation results, the proposed tracking scheme shows an obvious improvement in balancing the energy consumption and tracking accuracy over the existing methods. PMID:28335537

Clustering-based energy-saving algorithm in ultra-dense network

NASA Astrophysics Data System (ADS)

Huang, Junwei; Zhou, Pengguang; Teng, Deyang; Zhang, Renchi; Xu, Hao

2017-06-01

In Ultra-dense Networks (UDN), dense deployment of low power small base stations will cause serious small cells interference and a large amount of energy consumption. The purpose of this paper is to explore the method of reducing small cells interference and energy saving system in UDN, and we innovatively propose a sleep-waking-active (SWA) scheme. The scheme decreases the user outage causing by failure to detect users’ service requests, shortens the opening time of active base stations directly switching to sleep mode; we further proposes a Vertex Surrounding Clustering(VSC) algorithm, which first colours the small cells with the most strongest interference and next extends to the adjacent small cells. VSC algorithm can use the least colour to stain the small cell, reduce the number of iterations and promote the efficiency of colouring. The simulation results show that SWA scheme can effectively improve the system Energy Efficiency (EE), the VSC algorithm can reduce the small cells interference and optimize the users’ Spectrum Efficiency (SE) and throughput.

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

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

Consensus-Based Cooperative Spectrum Sensing with Improved Robustness Against SSDF Attacks

NASA Astrophysics Data System (ADS)

Liu, Quan; Gao, Jun; Guo, Yunwei; Liu, Siyang

2011-05-01

Based on the consensus algorithm, an attack-proof cooperative spectrum sensing (CSS) scheme is presented for decentralized cognitive radio networks (CRNs), where a common fusion center is not available and some malicious users may launch attacks with spectrum sensing data falsification (SSDF). Local energy detection is firstly performed by each secondary user (SU), and then, utilizing the consensus notions, each SU can make its own decision individually only by local information exchange with its neighbors rather than any centralized fusion used in most existing schemes. With the help of some anti-attack tricks, each authentic SU can generally identify and exclude those malicious reports during the interactions within the neighborhood. Compared with the existing solutions, the proposed scheme is proved to have much better robustness against three categories of SSDF attack, without requiring any a priori knowledge of the whole network.

Experimental research of UWB over fiber system employing 128-QAM and ISFA-optimized scheme

NASA Astrophysics Data System (ADS)

He, Jing; Xiang, Changqing; Long, Fengting; Chen, Zuo

2018-05-01

In this paper, an optimized intra-symbol frequency-domain averaging (ISFA) scheme is proposed and experimentally demonstrated in intensity-modulation and direct-detection (IMDD) multiband orthogonal frequency division multiplexing (MB-OFDM) ultra-wideband over fiber (UWBoF) system. According to the channel responses of three MB-OFDM UWB sub-bands, the optimal ISFA window size for each sub-band is investigated. After 60-km standard single mode fiber (SSMF) transmission, the experimental results show that, at the bit error rate (BER) of 3.8 × 10-3, the receiver sensitivity of 128-quadrature amplitude modulation (QAM) can be improved by 1.9 dB using the proposed enhanced ISFA combined with training sequence (TS)-based channel estimation scheme, compared with the conventional TS-based channel estimation. Moreover, the spectral efficiency (SE) is up to 5.39 bit/s/Hz.

Utilization and costs of glucose lowering therapies following health technology assessment for the new reimbursement scheme in Sweden.

PubMed

Pettersson, Billie; Hoffmann, Mikael; Andersson, David; Wändell, Per; Levin, Lars-Åke

2012-12-01

A new reimbursement scheme (RS) for glucose lowering therapies (GLT) was implemented in Sweden on March 1, 2010. Products on the market were retained, restricted, excluded or excluded for new courses in the new RS. The aim of this study was to compare utilization and costs of GLT for type 2 diabetes Mellitus (T2DM) before and after the implementation of the changed RS. This was a quasi-experimental study using data on dispensed GLT and costs from a database on dispensed individual based prescriptions in Sweden. Segmented regression analyses were used to assess utilization and costs. Following the changed reimbursement status, there was an accelerated increasing trend in number of patients treated with restricted (P=0.0007) or retained (P=0.0021) insulins, as well as in costs for insulin based GLT (P=0.0014). No impact was detected in the total number of patients treated with oral GLT, but a slightly negative trend in total costs for oral GLT was detected following the intervention (P=0.0177). The new reimbursement scheme had a minor impact on utilization and costs of oral GLT. Despite restricted reimbursement for patients with T2DM, the utilization of insulin based GLT and related costs increased faster following the intervention. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Linear segmentation algorithm for detecting layer boundary with lidar.

PubMed

Mao, Feiyue; Gong, Wei; Logan, Timothy

2013-11-04

The automatic detection of aerosol- and cloud-layer boundary (base and top) is important in atmospheric lidar data processing, because the boundary information is not only useful for environment and climate studies, but can also be used as input for further data processing. Previous methods have demonstrated limitations in defining the base and top, window-size setting, and have neglected the in-layer attenuation. To overcome these limitations, we present a new layer detection scheme for up-looking lidars based on linear segmentation with a reasonable threshold setting, boundary selecting, and false positive removing strategies. Preliminary results from both real and simulated data show that this algorithm cannot only detect the layer-base as accurate as the simple multi-scale method, but can also detect the layer-top more accurately than that of the simple multi-scale method. Our algorithm can be directly applied to uncalibrated data without requiring any additional measurements or window size selections.

Improving efficacy of metastatic tumor segmentation to facilitate early prediction of ovarian cancer patients' response to chemotherapy

NASA Astrophysics Data System (ADS)

Danala, Gopichandh; Wang, Yunzhi; Thai, Theresa; Gunderson, Camille C.; Moxley, Katherine M.; Moore, Kathleen; Mannel, Robert S.; Cheng, Samuel; Liu, Hong; Zheng, Bin; Qiu, Yuchen

2017-02-01

Accurate tumor segmentation is a critical step in the development of the computer-aided detection (CAD) based quantitative image analysis scheme for early stage prognostic evaluation of ovarian cancer patients. The purpose of this investigation is to assess the efficacy of several different methods to segment the metastatic tumors occurred in different organs of ovarian cancer patients. In this study, we developed a segmentation scheme consisting of eight different algorithms, which can be divided into three groups: 1) Region growth based methods; 2) Canny operator based methods; and 3) Partial differential equation (PDE) based methods. A number of 138 tumors acquired from 30 ovarian cancer patients were used to test the performance of these eight segmentation algorithms. The results demonstrate each of the tested tumors can be successfully segmented by at least one of the eight algorithms without the manual boundary correction. Furthermore, modified region growth, classical Canny detector, and fast marching, and threshold level set algorithms are suggested in the future development of the ovarian cancer related CAD schemes. This study may provide meaningful reference for developing novel quantitative image feature analysis scheme to more accurately predict the response of ovarian cancer patients to the chemotherapy at early stage.

Space-based detection of space debris by photometric and polarimetric characteristics

NASA Astrophysics Data System (ADS)

Pang, Shuxia; Wang, Hu; Lu, Xiaoyun; Shen, Yang; Pan, Yue

2017-10-01

The number of space debris has been increasing dramatically in the last few years, and is expected to increase as much in the future. As the orbital debris population grows, the risk of collision between debris and other orbital objects also grows. Therefore, space debris detection is a particularly important task for space environment security, and then supports for space debris modeling, protection and mitigation. This paper aims to review space debris detection systematically and completely. Firstly, the research status of space debris detection at home and abroad is presented. Then, three kinds of optical observation methods of space debris are summarized. Finally, we propose a space-based detection scheme for space debris by photometric and polarimetric characteristics.

Robotic Attention Processing And Its Application To Visual Guidance

NASA Astrophysics Data System (ADS)

Barth, Matthew; Inoue, Hirochika

1988-03-01

This paper describes a method of real-time visual attention processing for robots performing visual guidance. This robot attention processing is based on a novel vision processor, the multi-window vision system that was developed at the University of Tokyo. The multi-window vision system is unique in that it only processes visual information inside local area windows. These local area windows are quite flexible in their ability to move anywhere on the visual screen, change their size and shape, and alter their pixel sampling rate. By using these windows for specific attention tasks, it is possible to perform high speed attention processing. The primary attention skills of detecting motion, tracking an object, and interpreting an image are all performed at high speed on the multi-window vision system. A basic robotic attention scheme using the attention skills was developed. The attention skills involved detection and tracking of salient visual features. The tracking and motion information thus obtained was utilized in producing the response to the visual stimulus. The response of the attention scheme was quick enough to be applicable to the real-time vision processing tasks of playing a video 'pong' game, and later using an automobile driving simulator. By detecting the motion of a 'ball' on a video screen and then tracking the movement, the attention scheme was able to control a 'paddle' in order to keep the ball in play. The response was faster than that of a human's, allowing the attention scheme to play the video game at higher speeds. Further, in the application to the driving simulator, the attention scheme was able to control both direction and velocity of a simulated vehicle following a lead car. These two applications show the potential of local visual processing in its use for robotic attention processing.

A parameterized logarithmic image processing method with Laplacian of Gaussian filtering for lung nodule enhancement in chest radiographs.

PubMed

Chen, Sheng; Yao, Liping; Chen, Bao

2016-11-01

The enhancement of lung nodules in chest radiographs (CXRs) plays an important role in the manual as well as computer-aided detection (CADe) lung cancer. In this paper, we proposed a parameterized logarithmic image processing (PLIP) method combined with the Laplacian of a Gaussian (LoG) filter to enhance lung nodules in CXRs. We first applied several LoG filters with varying parameters to an original CXR to enhance the nodule-like structures as well as the edges in the image. We then applied the PLIP model, which can enhance lung nodule images with high contrast and was beneficial in extracting effective features for nodule detection in the CADe scheme. Our method combined the advantages of both the PLIP algorithm and the LoG algorithm, which can enhance lung nodules in chest radiographs with high contrast. To test our nodule enhancement method, we tested a CADe scheme, with a relatively high performance in nodule detection, using a publically available database containing 140 nodules in 140 CXRs enhanced through our nodule enhancement method. The CADe scheme attained a sensitivity of 81 and 70 % with an average of 5.0 frame rate (FP) and 2.0 FP, respectively, in a leave-one-out cross-validation test. By contrast, the CADe scheme based on the original image recorded a sensitivity of 77 and 63 % at 5.0 FP and 2.0 FP, respectively. We introduced the measurement of enhancement by entropy evaluation to objectively assess our method. Experimental results show that the proposed method obtains an effective enhancement of lung nodules in CXRs for both radiologists and CADe schemes.

An inter-lighting interference cancellation scheme for MISO-VLC systems

NASA Astrophysics Data System (ADS)

Kim, Kyuntak; Lee, Kyujin; Lee, Kyesan

2017-08-01

In this paper, we propose an inter-lighting interference cancellation (ILIC) scheme to reduce the interference between adjacent light-emitting diodes (LEDs) and enhance the transmission capacity of multiple-input-single-output (MISO)-visible light communication (VLC) systems. In indoor environments, multiple LEDs have normally been used as lighting sources, allowing the design of MISO-VLC systems. To enhance the transmission capacity, different data should be simultaneously transmitted from each LED; however, that can lead to interference between adjacent LEDs. In that case, relatively low-received power signals are subjected to large interference because wireless optical systems generally use intensity modulation and direct detection. Thus, only the signal with the highest received power can be detected, while the other received signals cannot be detected. To solve this problem, we propose the ILIC scheme for MISO-VLC systems. The proposed scheme preferentially detects the highest received power signal, and this signal is referred as interference signal by an interference component generator. Then, relatively low-received power signal can be detected by cancelling the interference signal from the total received signals. Therefore, the performance of the proposed scheme can improve the total average bit error rate and throughput of a MISO-VLC system.

Towards a Low-Cost Remote Memory Attestation for the Smart Grid

PubMed Central

Yang, Xinyu; He, Xiaofei; Yu, Wei; Lin, Jie; Li, Rui; Yang, Qingyu; Song, Houbing

2015-01-01

In the smart grid, measurement devices may be compromised by adversaries, and their operations could be disrupted by attacks. A number of schemes to efficiently and accurately detect these compromised devices remotely have been proposed. Nonetheless, most of the existing schemes detecting compromised devices depend on the incremental response time in the attestation process, which are sensitive to data transmission delay and lead to high computation and network overhead. To address the issue, in this paper, we propose a low-cost remote memory attestation scheme (LRMA), which can efficiently and accurately detect compromised smart meters considering real-time network delay and achieve low computation and network overhead. In LRMA, the impact of real-time network delay on detecting compromised nodes can be eliminated via investigating the time differences reported from relay nodes. Furthermore, the attestation frequency in LRMA is dynamically adjusted with the compromised probability of each node, and then, the total number of attestations could be reduced while low computation and network overhead can be achieved. Through a combination of extensive theoretical analysis and evaluations, our data demonstrate that our proposed scheme can achieve better detection capacity and lower computation and network overhead in comparison to existing schemes. PMID:26307998

Towards a Low-Cost Remote Memory Attestation for the Smart Grid.

PubMed

Yang, Xinyu; He, Xiaofei; Yu, Wei; Lin, Jie; Li, Rui; Yang, Qingyu; Song, Houbing

2015-08-21

In the smart grid, measurement devices may be compromised by adversaries, and their operations could be disrupted by attacks. A number of schemes to efficiently and accurately detect these compromised devices remotely have been proposed. Nonetheless, most of the existing schemes detecting compromised devices depend on the incremental response time in the attestation process, which are sensitive to data transmission delay and lead to high computation and network overhead. To address the issue, in this paper, we propose a low-cost remote memory attestation scheme (LRMA), which can efficiently and accurately detect compromised smart meters considering real-time network delay and achieve low computation and network overhead. In LRMA, the impact of real-time network delay on detecting compromised nodes can be eliminated via investigating the time differences reported from relay nodes. Furthermore, the attestation frequency in LRMA is dynamically adjusted with the compromised probability of each node, and then, the total number of attestations could be reduced while low computation and network overhead can be achieved. Through a combination of extensive theoretical analysis and evaluations, our data demonstrate that our proposed scheme can achieve better detection capacity and lower computation and network overhead in comparison to existing schemes.

Mammogram classification scheme using 2D-discrete wavelet and local binary pattern for detection of breast cancer

NASA Astrophysics Data System (ADS)

Adi Putra, Januar

2018-04-01

In this paper, we propose a new mammogram classification scheme to classify the breast tissues as normal or abnormal. Feature matrix is generated using Local Binary Pattern to all the detailed coefficients from 2D-DWT of the region of interest (ROI) of a mammogram. Feature selection is done by selecting the relevant features that affect the classification. Feature selection is used to reduce the dimensionality of data and features that are not relevant, in this paper the F-test and Ttest will be performed to the results of the feature extraction dataset to reduce and select the relevant feature. The best features are used in a Neural Network classifier for classification. In this research we use MIAS and DDSM database. In addition to the suggested scheme, the competent schemes are also simulated for comparative analysis. It is observed that the proposed scheme has a better say with respect to accuracy, specificity and sensitivity. Based on experiments, the performance of the proposed scheme can produce high accuracy that is 92.71%, while the lowest accuracy obtained is 77.08%.

Pilot-multiplexed continuous-variable quantum key distribution with a real local oscillator

NASA Astrophysics Data System (ADS)

Wang, Tao; Huang, Peng; Zhou, Yingming; Liu, Weiqi; Zeng, Guihua

2018-01-01

We propose a pilot-multiplexed continuous-variable quantum key distribution (CVQKD) scheme based on a local local oscillator (LLO). Our scheme utilizes time-multiplexing and polarization-multiplexing techniques to dramatically isolate the quantum signal from the pilot, employs two heterodyne detectors to separately detect the signal and the pilot, and adopts a phase compensation method to almost eliminate the multifrequency phase jitter. In order to analyze the performance of our scheme, a general LLO noise model is constructed. Besides the phase noise and the modulation noise, the photon-leakage noise from the reference path and the quantization noise due to the analog-to-digital converter (ADC) are also considered, which are first analyzed in the LLO regime. Under such general noise model, our scheme has a higher key rate and longer secure distance compared with the preexisting LLO schemes. Moreover, we also conduct an experiment to verify our pilot-multiplexed scheme. Results show that it maintains a low level of the phase noise and is expected to obtain a 554-Kbps secure key rate within a 15-km distance under the finite-size effect.

Detection of proteins and bacteria using an array of feedback capacitance sensors.

PubMed

Mehta, Manav; Hanumanthaiah, Chandra Sekar; Betala, Pravin Ajitkumar; Zhang, Hong; Roh, SaeWeon; Buttner, William; Penrose, William R; Stetter, Joseph R; Pérez-Luna, Victor H

2007-12-15

An integrated array of micron-dimension capacitors, originally developed for biometric applications (fingerprint identification), was engineered for detection of biological agents such as proteins and bacteria. This device consists of an array of 93,184 (256 x 364) individual capacitor-based sensing elements located underneath a thin (0.8 microm) layer of glass. This glass layer can be functionalized with organosilane-based monolayers to provide groups amenable for the immobilization of bioreceptors such as antibodies, enzymes, peptides, aptamers, and nucleotides. Upon functionalization with antibodies and in conjunction with signal amplification schemes that result in perturbation of the dielectric constant around the captured antigens, this system can be used as a detector of biological agents. Two signal amplification schemes were tested in this work: one consisted of 4 microm diameter latex immunobeads and a second one was based on colloidal gold catalyzed reduction of silver. These signal amplification approaches were demonstrated and show that this system is capable of specific detection of bacteria (Escherichia coli) and proteins (ovalbumin). The present work shows proof-of-principle demonstration that a simple fingerprint detector based on feedback capacitance measurements can be implemented as a biosensor. The approach presented could be easily expanded to simultaneously test for a large number of analytes and multiple samples given that this device has a large number of detectors. The device and required instrumentation is highly portable and does not require expensive and bulky instrumentation because it relies purely on electronic detection.

The role of muscle synergies in myoelectric control: trends and challenges for simultaneous multifunction control

NASA Astrophysics Data System (ADS)

Ison, Mark; Artemiadis, Panagiotis

2014-10-01

Myoelectric control is filled with potential to significantly change human-robot interaction due to the ability to non-invasively measure human motion intent. However, current control schemes have struggled to achieve the robust performance that is necessary for use in commercial applications. As demands in myoelectric control trend toward simultaneous multifunctional control, multi-muscle coordinations, or synergies, play larger roles in the success of the control scheme. Detecting and refining patterns in muscle activations robust to the high variance and transient changes associated with surface electromyography is essential for efficient, user-friendly control. This article reviews the role of muscle synergies in myoelectric control schemes by dissecting each component of the scheme with respect to associated challenges for achieving robust simultaneous control of myoelectric interfaces. Electromyography recording details, signal feature extraction, pattern recognition and motor learning based control schemes are considered, and future directions are proposed as steps toward fulfilling the potential of myoelectric control in clinically and commercially viable applications.

A novel 'Gold on Gold' biosensing scheme for an on-fiber immunoassay

NASA Astrophysics Data System (ADS)

Punjabi, N.; Satija, J.; Mukherji, S.

2015-05-01

In this paper, we propose a novel „gold on gold‟ biosensing scheme for absorbance based fiber-optic biosensor. First, a self-assembled monolayer of gold nanoparticles is formed at the sensing region of the fiber-optic probe by incubating an amino-silanized probe in a colloidal gold solution. Thereafter, the receptor moieties, i.e. Human immunoglobulin G (HIgG) were immobilized by using standard alkanethiol and classic carbodiimide coupling chemistry. Finally, biosensing experiments were performed with different concentrations of gold nanoparticle-tagged analyte, i.e. Goat anti- Human immunoglobulin G (Nanogold-GaHIgG). The sensor response was observed to be more than five-fold compared to the control bioassay, in which the sensor matrix was devoid of gold nanoparticle film. Also, the response was found to be ~10 times higher compared to the FITC-tagged scheme and ~14.5 times better compared to untagged scheme. This novel scheme also demonstrated the potential in improving the limit of detection for the fiber-optic biosensors.

Secure Data Aggregation in Wireless Sensor Network-Fujisaki Okamoto(FO) Authentication Scheme against Sybil Attack.

PubMed

Nirmal Raja, K; Maraline Beno, M

2017-07-01

In the wireless sensor network(WSN) security is a major issue. There are several network security schemes proposed in research. In the network, malicious nodes obstruct the performance of the network. The network can be vulnerable by Sybil attack. When a node illicitly assertions multiple identities or claims fake IDs, the WSN grieves from an attack named Sybil attack. This attack threatens wireless sensor network in data aggregation, synchronizing system, routing, fair resource allocation and misbehavior detection. Henceforth, the research is carried out to prevent the Sybil attack and increase the performance of the network. This paper presents the novel security mechanism and Fujisaki Okamoto algorithm and also application of the work. The Fujisaki-Okamoto (FO) algorithm is ID based cryptographic scheme and gives strong authentication against Sybil attack. By using Network simulator2 (NS2) the scheme is simulated. In this proposed scheme broadcasting key, time taken for different key sizes, energy consumption, Packet delivery ratio, Throughput were analyzed.

Implications of non-sustainable agricultural water policies for the water-food nexus in large-scale irrigation systems: A remote sensing approach

NASA Astrophysics Data System (ADS)

Al Zayed, Islam Sabry; Elagib, Nadir Ahmed

2017-12-01

This study proposes a novel monitoring tool based on Satellite Remote Sensing (SRS) data to examine the status of water distribution and Water Use Efficiency (WUE) under changing water policies in large-scale and complex irrigation schemes. The aim is to improve our understanding of the water-food nexus in such schemes. With a special reference to the Gezira Irrigation Scheme (GeIS) in Sudan during the period 2000-2014, the tool devised herein is well suited for cases where validation data are absent. First, it introduces an index, referred to as the Crop Water Consumption Index (CWCI), to assess the efficiency of water policies. The index is defined as the ratio of actual evapotranspiration (ETa) over agricultural areas to total ETa for the whole scheme where ETa is estimated using the Simplified Surface Energy Balance model (SSEB). Second, the tool uses integrated Normalized Difference Vegetation Index (iNDVI), as a proxy for crop productivity, and ETa to assess the WUE. Third, the tool uses SSEB ETa and NDVI in an attempt to detect wastage of water. Four key results emerged from this research as follows: 1) the WUE has not improved despite the changing agricultural and water policies, 2) the seasonal ETa can be used to detect the drier areas of GeIS, i.e. areas with poor irrigation water supply, 3) the decreasing trends of CWCI, slope of iNDVI-ETa linear regression and iNDVI are indicative of inefficient utilization of irrigation water in the scheme, and 4) it is possible to use SSEB ETa and NDVI to identify channels with spillover problems and detect wastage of rainwater that is not used as a source for irrigation. In conclusion, the innovative tool developed herein has provided important information on the efficiency of a large-scale irrigation scheme to help rationalize laborious water management processes and increase productivity.

Entanglement of remote material qubits through nonexciting interaction with single photons

NASA Astrophysics Data System (ADS)

Li, Gang; Zhang, Pengfei; Zhang, Tiancai

2018-05-01

We propose a scheme to entangle multiple material qubits through interaction with single photons via nonexciting processes associated with strongly coupling systems. The basic idea is based on the material state dependent reflection and transmission for the input photons. Thus, the material qubits in several systems can be entangled when one photon interacts with each system in cascade and the photon paths are mixed by the photon detection. The character of nonexciting of material qubits does not change the state of the material qubit and thus ensures the possibility of purifying entangled states by using more photons under realistic imperfect parameters. It also guarantees directly scaling up the scheme to entangle more qubits. Detailed analysis of fidelity and success probability of the scheme in the frame of an optical Fabry-Pérot cavity based strongly coupling system is presented. It is shown that a two-qubit entangled state with fidelity above 0.99 is promised with only two photons by using currently feasible experimental parameters. Our scheme can also be directly implemented on other strongly coupled system.

Improved detection and false alarm rejection using FLGPR and color imagery in a forward-looking system

NASA Astrophysics Data System (ADS)

Havens, Timothy C.; Spain, Christopher J.; Ho, K. C.; Keller, James M.; Ton, Tuan T.; Wong, David C.; Soumekh, Mehrdad

2010-04-01

Forward-looking ground-penetrating radar (FLGPR) has received a significant amount of attention for use in explosivehazards detection. A drawback to FLGPR is that it results in an excessive number of false detections. This paper presents our analysis of the explosive-hazards detection system tested by the U.S. Army Night Vision and Electronic Sensors Directorate (NVESD). The NVESD system combines an FLGPR with a visible-spectrum color camera. We present a target detection algorithm that uses a locally-adaptive detection scheme with spectrum-based features. The remaining FLGPR detections are then projected into the camera imagery and image-based features are collected. A one-class classifier is then used to reduce the number of false detections. We show that our proposed FLGPR target detection algorithm, coupled with our camera-based false alarm (FA) reduction method, is effective at reducing the number of FAs in test data collected at a US Army test facility.

Development of smart piezoelectric transducer self-sensing, self-diagnosis and tuning schemes for structural health monitoring applications

NASA Astrophysics Data System (ADS)

Lee, Sang Jun

Autonomous structural health monitoring (SHM) systems using active sensing devices have been studied extensively to diagnose the current state of aerospace, civil infrastructure and mechanical systems in near real-time and aims to eventually reduce life-cycle costs by replacing current schedule-based maintenance with condition-based maintenance. This research develops four schemes for SHM applications: (1) a simple and reliable PZT transducer self-sensing scheme; (2) a smart PZT self-diagnosis scheme; (3) an instantaneous reciprocity-based PZT diagnosis scheme; and (4) an effective PZT transducer tuning scheme. First, this research develops a PZT transducer self-sensing scheme, which is a necessary condition to accomplish a PZT transducer self-diagnosis. Main advantages of the proposed self-sensing approach are its simplicity and adaptability. The necessary hardware is only an additional self-sensing circuit which includes a minimum of electric components. With this circuit, the self-sensing parameters can be calibrated instantaneously in the presence of changing operational and environmental conditions of the system. In particular, this self-sensing scheme focuses on estimating the mechanical response in the time domain for the subsequent applications of the PZT transducer self-diagnosis and tuning with guided wave propagation. The most significant challenge of this self-sensing comes from the fact that the magnitude of the mechanical response is generally several orders of magnitude smaller than that of the input signal. The proposed self-sensing scheme fully takes advantage of the fact that any user-defined input signals can be applied to a host structure and the input waveform is known. The performance of the proposed self-sensing scheme is demonstrated by theoretical analysis, numerical simulations and various experiments. Second, this research proposes a smart PZT transducer self-diagnosis scheme based on the developed self-sensing scheme. Conventionally, the capacitance change of the PZT wafer is monitored to identify the abnormal PZT condition because the capacitance of the PZT wafer is linearly proportional to its size and also related to the bonding condition. However, temperature variation is another primary factor that affects the PZT capacitance. To ensure the reliable transducer self-diagnosis, two different self-diagnosis features are proposed to differentiate two main PZT wafer defects, i.e., PZT debonding and PZT cracking, from temperature variations and structural damages. The PZT debonding is identified using two indices based on time reversal process (TRP) without any baseline data. Also, the PZT cracking is identified by monitoring the change of the generated Lamb wave power ratio index with respect to the driving frequency. The uniqueness of this self-diagnosis scheme is that the self-diagnosis features can differentiate the PZT defects from environmental variations and structural damages. Therefore, it is expected to minimize false-alarms which are induced by operational or environmental variations as well as structural damages. The applicability of the proposed self-diagnosis scheme is verified by theoretical analysis, numerical simulations, and experimental tests. Third, a new methodology of guided wave-based PZT transducer diagnosis is developed to identify PZT transducer defects without using prior baseline data. This methodology can be applied when a number of same-size PZT transducers are attached to a target structure to form a sensor network. The advantage of the proposed technique is that abnormal PZT transducers among intact PZT transducers can be detected even when the system being monitored is subjected to varying operational and environmental conditions or changing structural conditions. To achieve this goal, the proposed diagnosis technique utilizes the linear reciprocity of guided wave propagation between a pair of surface-bonded PZT transducers. Finally, a PZT transducer tuning scheme is being developed for selective Lamb wave excitation and sensing. This is useful for structural damage detection based on Lamb wave propagation because the proper transducer size and the corresponding input frequency can be is crucial for selective Lamb wave excitation and sensing. The circular PZT response model is derived, and the energy balance is included for a better prediction of the PZT responses because the existing PZT response models do not consider any energy balance between Lamb wave modes. In addition, two calibration methods are also suggested in order to model the PZT responses more accurately by considering a bonding layer effect. (Abstract shortened by UMI.)

Generation and coherent detection of QPSK signal using a novel method of digital signal processing

NASA Astrophysics Data System (ADS)

Zhao, Yuan; Hu, Bingliang; He, Zhen-An; Xie, Wenjia; Gao, Xiaohui

2018-02-01

We demonstrate an optical quadrature phase-shift keying (QPSK) signal transmitter and an optical receiver for demodulating optical QPSK signal with homodyne detection and digital signal processing (DSP). DSP on the homodyne detection scheme is employed without locking the phase of the local oscillator (LO). In this paper, we present an extracting one-dimensional array of down-sampling method for reducing unwanted samples of constellation diagram measurement. Such a novel scheme embodies the following major advantages over the other conventional optical QPSK signal detection methods. First, this homodyne detection scheme does not need strict requirement on LO in comparison with linear optical sampling, such as having a flat spectral density and phase over the spectral support of the source under test. Second, the LabVIEW software is directly used for recovering the QPSK signal constellation without employing complex DSP circuit. Third, this scheme is applicable to multilevel modulation formats such as M-ary PSK and quadrature amplitude modulation (QAM) or higher speed signals by making minor changes.

Detection of Listeria monocytogenes from selective enrichment broth using MALDI-TOF Mass Spectrometry.

PubMed

Jadhav, Snehal; Sevior, Danielle; Bhave, Mrinal; Palombo, Enzo A

2014-01-31

Conventional methods used for primary detection of Listeria monocytogenes from foods and subsequent confirmation of presumptive positive samples involve prolonged incubation and biochemical testing which generally require four to five days to obtain a result. In the current study, a simple and rapid proteomics-based MALDI-TOF MS approach was developed to detect L. monocytogenes directly from selective enrichment broths. Milk samples spiked with single species and multiple species cultures were incubated in a selective enrichment broth for 24h, followed by an additional 6h secondary enrichment. As few as 1 colony-forming unit (cfu) of L. monocytogenes per mL of initial selective broth culture could be detected within 30h. On applying the same approach to solid foods previously implicated in listeriosis, namely chicken pâté, cantaloupe and Camembert cheese, detection was achieved within the same time interval at inoculation levels of 10cfu/mL. Unlike the routine application of MALDI-TOF MS for identification of bacteria from solid media, this study proposes a cost-effective and time-saving detection scheme for direct identification of L. monocytogenes from broth cultures.This article is part of a Special Issue entitled: Trends in Microbial Proteomics. Globally, foodborne diseases are major causes of illness and fatalities in humans. Hence, there is a continual need for reliable and rapid means for pathogen detection from food samples. Recent applications of MALDI-TOF MS for diagnostic microbiology focused on detection of microbes from clinical specimens. However, the current study has emphasized its use as a tool for detecting the major foodborne pathogen, Listeria monocytogenes, directly from selective enrichment broths. This proof-of-concept study proposes a detection scheme that is more rapid and simple compared to conventional methods of Listeria detection. Very low levels of the pathogen could be identified from different food samples post-enrichment in selective enrichment broths. Use of this scheme will facilitate rapid and cost-effective testing for this important foodborne pathogen. © 2013.

Characterization of malaria infected blood cells by scanning confocal laser and acoustic vector contrast microscopy

NASA Astrophysics Data System (ADS)

Ahmed Mohamed, E. T.; Schubert, S.; Gilberger, T. W.; Kamanyi, A., Jr.; Wannemacher, R.; Grill, W.

2006-03-01

Acoustic and optical multiple contrast microscopy has been employed in order to explore characterizable parameters of red blood cells, including cells infected by the parasite Plasmodium falciparum, in order to investigate cellular modifications caused by the infection and to identify possible detection schemes for disease monitoring. Imaging schemes were based on fluorescence, optical transmission, optical reflection, and amplitude and phase of ultrasound reflected from the cells. Contrast variations observed in acoustic microscopy, but not in optical microscopy, were tentatively ascribed to changes caused by the infection.

Initial study of Schroedinger eigenmaps for spectral target detection

NASA Astrophysics Data System (ADS)

Dorado-Munoz, Leidy P.; Messinger, David W.

2016-08-01

Spectral target detection refers to the process of searching for a specific material with a known spectrum over a large area containing materials with different spectral signatures. Traditional target detection methods in hyperspectral imagery (HSI) require assuming the data fit some statistical or geometric models and based on the model, to estimate parameters for defining a hypothesis test, where one class (i.e., target class) is chosen over the other classes (i.e., background class). Nonlinear manifold learning methods such as Laplacian eigenmaps (LE) have extensively shown their potential use in HSI processing, specifically in classification or segmentation. Recently, Schroedinger eigenmaps (SE), which is built upon LE, has been introduced as a semisupervised classification method. In SE, the former Laplacian operator is replaced by the Schroedinger operator. The Schroedinger operator includes by definition, a potential term V that steers the transformation in certain directions improving the separability between classes. In this regard, we propose a methodology for target detection that is not based on the traditional schemes and that does not need the estimation of statistical or geometric parameters. This method is based on SE, where the potential term V is taken into consideration to include the prior knowledge about the target class and use it to steer the transformation in directions where the target location in the new space is known and the separability between target and background is augmented. An initial study of how SE can be used in a target detection scheme for HSI is shown here. In-scene pixel and spectral signature detection approaches are presented. The HSI data used comprise various target panels for testing simultaneous detection of multiple objects with different complexities.

Population genomics of C. melanopterus using target gene capture data: demographic inferences and conservation perspectives

PubMed Central

Maisano Delser, Pierpaolo; Corrigan, Shannon; Hale, Matthew; Li, Chenhong; Veuille, Michel; Planes, Serge; Naylor, Gavin; Mona, Stefano

2016-01-01

Population genetics studies on non-model organisms typically involve sampling few markers from multiple individuals. Next-generation sequencing approaches open up the possibility of sampling many more markers from fewer individuals to address the same questions. Here, we applied a target gene capture method to deep sequence ~1000 independent autosomal regions of a non-model organism, the blacktip reef shark (Carcharhinus melanopterus). We devised a sampling scheme based on the predictions of theoretical studies of metapopulations to show that sampling few individuals, but many loci, can be extremely informative to reconstruct the evolutionary history of species. We collected data from a single deme (SID) from Northern Australia and from a scattered sampling representing various locations throughout the Indian Ocean (SCD). We explored the genealogical signature of population dynamics detected from both sampling schemes using an ABC algorithm. We then contrasted these results with those obtained by fitting the data to a non-equilibrium finite island model. Both approaches supported an Nm value ~40, consistent with philopatry in this species. Finally, we demonstrate through simulation that metapopulations exhibit greater resilience to recent changes in effective size compared to unstructured populations. We propose an empirical approach to detect recent bottlenecks based on our sampling scheme. PMID:27651217

Population genomics of C. melanopterus using target gene capture data: demographic inferences and conservation perspectives.

PubMed

Maisano Delser, Pierpaolo; Corrigan, Shannon; Hale, Matthew; Li, Chenhong; Veuille, Michel; Planes, Serge; Naylor, Gavin; Mona, Stefano

2016-09-21

Population genetics studies on non-model organisms typically involve sampling few markers from multiple individuals. Next-generation sequencing approaches open up the possibility of sampling many more markers from fewer individuals to address the same questions. Here, we applied a target gene capture method to deep sequence ~1000 independent autosomal regions of a non-model organism, the blacktip reef shark (Carcharhinus melanopterus). We devised a sampling scheme based on the predictions of theoretical studies of metapopulations to show that sampling few individuals, but many loci, can be extremely informative to reconstruct the evolutionary history of species. We collected data from a single deme (SID) from Northern Australia and from a scattered sampling representing various locations throughout the Indian Ocean (SCD). We explored the genealogical signature of population dynamics detected from both sampling schemes using an ABC algorithm. We then contrasted these results with those obtained by fitting the data to a non-equilibrium finite island model. Both approaches supported an Nm value ~40, consistent with philopatry in this species. Finally, we demonstrate through simulation that metapopulations exhibit greater resilience to recent changes in effective size compared to unstructured populations. We propose an empirical approach to detect recent bottlenecks based on our sampling scheme.

Sensing cocaine in saliva with infrared laser spectroscopy

NASA Astrophysics Data System (ADS)

Hans, Kerstin M.-C.; Müller, Matthias; Gianella, Michele; Wägli, Ph.; Sigrist, Markus W.

2013-02-01

Increasing numbers of accidents caused by drivers under the influence of drugs, raise drug tests to worldwide interest. We developed a one-step extraction technique for cocaine in saliva and analyzed reference samples with laser spectroscopy employing two different schemes. The first is based on attenuated total reflection (ATR), which is applied to dried samples. The second scheme uses transmission measurements for the analysis of liquid samples. ATR spectroscopy achieved a limit of detection (LOD) of 3μg/ml. The LOD for the transmission approach in liquid samples is < 10 μg/ml. These LODs are realistic as such concentration ranges are encountered in the saliva of drug users after the administration of a single dose of cocaine. An improved stabilization of the set-up should lower the limit of detection significantly.

Can a totally different approach to soft tissue computer aided detection (CADe) result in affecting radiologists' decisions?

NASA Astrophysics Data System (ADS)

Gur, David

2018-03-01

We tested whether a case based CADe scheme, developed only on negatively interpreted screening mammograms, has predictive value for cancer detection during subsequent screening and how this approach may affect radiologists' performances when alerting them to a small subset ( 15%) of exams on which radiologists tend to miss cancers. A series of six parameters case based CADe schemes, using 200 negative mammograms (800 images 100 women with breast cancer at subsequent screening and 100 women who remained negative), carefully matched by age and breast density, were optimized. CADe alone schemes performed at AUC=0.68 (+/- 0.01). Five radiologists and 4 residents interpreted the same cases and performed at AUC =0.71 (experienced radiologists) and AUC= 0.61 (residents). With the "CADe warnings" shown to the interpreters only if they did not recall one of 24 highest CADe scoring cases, assisted performance of radiologists and residents respectively, were 0.71 and 0.63 (p>0.05). However, when the CADe alone performance was raised to an AUC=0.78, by artificially increasing the number of possible warnings from 16 to 24, radiologists' performances significantly improved from an AUC of 0.68 to 0.72 (p<0.05). In conclusion, the use case based information other than breast density could highlight a small fraction of women whose cancers are more likely to be missed by radiologists and later detected during subsequent mammograms, thereby, leading to an assisted approach that improves radiologists' performances. However, to be effective, the performance of the CADe alone should be substantially higher (e.g. ΔAUC >=0.07) than that of the un-assisted radiologist.

Optical sectioning in induced coherence tomography with frequency-entangled photons

NASA Astrophysics Data System (ADS)

Vallés, Adam; Jiménez, Gerard; Salazar-Serrano, Luis José; Torres, Juan P.

2018-02-01

We demonstrate a different scheme to perform optical sectioning of a sample based on the concept of induced coherence [Zou et al., Phys. Rev. Lett. 67, 318 (1991), 10.1103/PhysRevLett.67.318]. This can be viewed as a different type of optical coherence tomography scheme where the varying reflectivity of the sample along the direction of propagation of an optical beam translates into changes of the degree of first-order coherence between two beams. As a practical advantage the scheme allows probing the sample with one wavelength and measuring photons with another wavelength. In a bio-imaging scenario, this would result in a deeper penetration into the sample because of probing with longer wavelengths, while still using the optimum wavelength for detection. The scheme proposed here could achieve submicron axial resolution by making use of nonlinear parametric sources with broad spectral bandwidth emission.

Geographic Wormhole Detection in Wireless Sensor Networks

PubMed Central

Sookhak, Mehdi; Akhundzada, Adnan; Sookhak, Alireza; Eslaminejad, Mohammadreza; Gani, Abdullah; Khurram Khan, Muhammad; Li, Xiong; Wang, Xiaomin

2015-01-01

Wireless sensor networks (WSNs) are ubiquitous and pervasive, and therefore; highly susceptible to a number of security attacks. Denial of Service (DoS) attack is considered the most dominant and a major threat to WSNs. Moreover, the wormhole attack represents one of the potential forms of the Denial of Service (DoS) attack. Besides, crafting the wormhole attack is comparatively simple; though, its detection is nontrivial. On the contrary, the extant wormhole defense methods need both specialized hardware and strong assumptions to defend against static and dynamic wormhole attack. The ensuing paper introduces a novel scheme to detect wormhole attacks in a geographic routing protocol (DWGRP). The main contribution of this paper is to detect malicious nodes and select the best and the most reliable neighbors based on pairwise key pre-distribution technique and the beacon packet. Moreover, this novel technique is not subject to any specific assumption, requirement, or specialized hardware, such as a precise synchronized clock. The proposed detection method is validated by comparisons with several related techniques in the literature, such as Received Signal Strength (RSS), Authentication of Nodes Scheme (ANS), Wormhole Detection uses Hound Packet (WHOP), and Wormhole Detection with Neighborhood Information (WDI) using the NS-2 simulator. The analysis of the simulations shows promising results with low False Detection Rate (FDR) in the geographic routing protocols. PMID:25602616

Two-photon Shack-Hartmann wavefront sensor.

PubMed

Xia, Fei; Sinefeld, David; Li, Bo; Xu, Chris

2017-03-15

We introduce a simple wavefront sensing scheme for aberration measurement of pulsed laser beams in near-infrared wavelengths (<2200  nm), where detectors are not always available or are very expensive. The method is based on two-photon absorption in a silicon detector array for longer wavelengths detection. We demonstrate the simplicity of such implementations with a commercially available Shack-Hartmann wavefront sensor and discuss the detection sensitivity of this method.

Spectroscopic techniques to study the immune response in human saliva

NASA Astrophysics Data System (ADS)

Nepomnyashchaya, E.; Savchenko, E.; Velichko, E.; Bogomaz, T.; Aksenov, E.

2018-01-01

Studies of the immune response dynamics by means of spectroscopic techniques, i.e., laser correlation spectroscopy and fluorescence spectroscopy, are described. The laser correlation spectroscopy is aimed at measuring sizes of particles in biological fluids. The fluorescence spectroscopy allows studying of the conformational and other structural changings in immune complex. We have developed a new scheme of a laser correlation spectrometer and an original signal processing algorithm. We have suggested a new fluorescence detection scheme based on a prism and an integrating pin diode. The developed system based on the spectroscopic techniques allows studies of complex process in human saliva and opens some prospects for an individual treatment of immune diseases.

Quantum random number generator based on quantum nature of vacuum fluctuations

NASA Astrophysics Data System (ADS)

Ivanova, A. E.; Chivilikhin, S. A.; Gleim, A. V.

2017-11-01

Quantum random number generator (QRNG) allows obtaining true random bit sequences. In QRNG based on quantum nature of vacuum, optical beam splitter with two inputs and two outputs is normally used. We compare mathematical descriptions of spatial beam splitter and fiber Y-splitter in the quantum model for QRNG, based on homodyne detection. These descriptions were identical, that allows to use fiber Y-splitters in practical QRNG schemes, simplifying the setup. Also we receive relations between the input radiation and the resulting differential current in homodyne detector. We experimentally demonstrate possibility of true random bits generation by using QRNG based on homodyne detection with Y-splitter.

Robust obstacle detection for unmanned surface vehicles

NASA Astrophysics Data System (ADS)

Qin, Yueming; Zhang, Xiuzhi

2018-03-01

Obstacle detection is of essential importance for Unmanned Surface Vehicles (USV). Although some obstacles (e.g., ships, islands) can be detected by Radar, there are many other obstacles (e.g., floating pieces of woods, swimmers) which are difficult to be detected via Radar because these obstacles have low radar cross section. Therefore, detecting obstacle from images taken onboard is an effective supplement. In this paper, a robust vision-based obstacle detection method for USVs is developed. The proposed method employs the monocular image sequence captured by the camera on the USVs and detects obstacles on the sea surface from the image sequence. The experiment results show that the proposed scheme is efficient to fulfill the obstacle detection task.

Detecting Pulsing Denial-of-Service Attacks with Nondeterministic Attack Intervals

NASA Astrophysics Data System (ADS)

Luo, Xiapu; Chan, Edmond W. W.; Chang, Rocky K. C.

2009-12-01

This paper addresses the important problem of detecting pulsing denial of service (PDoS) attacks which send a sequence of attack pulses to reduce TCP throughput. Unlike previous works which focused on a restricted form of attacks, we consider a very broad class of attacks. In particular, our attack model admits any attack interval between two adjacent pulses, whether deterministic or not. It also includes the traditional flooding-based attacks as a limiting case (i.e., zero attack interval). Our main contribution is Vanguard, a new anomaly-based detection scheme for this class of PDoS attacks. The Vanguard detection is based on three traffic anomalies induced by the attacks, and it detects them using a CUSUM algorithm. We have prototyped Vanguard and evaluated it on a testbed. The experiment results show that Vanguard is more effective than the previous methods that are based on other traffic anomalies (after a transformation using wavelet transform, Fourier transform, and autocorrelation) and detection algorithms (e.g., dynamic time warping).

Long period gratings in multimode optical fibers: application in chemical sensing

NASA Astrophysics Data System (ADS)

Thomas Lee, S.; Dinesh Kumar, R.; Suresh Kumar, P.; Radhakrishnan, P.; Vallabhan, C. P. G.; Nampoori, V. P. N.

2003-09-01

We propose and demonstrate a new technique for evanescent wave chemical sensing by writing long period gratings in a bare multimode plastic clad silica fiber. The sensing length of the present sensor is only 10 mm, but is as sensitive as a conventional unclad evanescent wave sensor having about 100 mm sensing length. The minimum measurable concentration of the sensor reported here is 10 nmol/l and the operating range is more than 4 orders of magnitude. Moreover, the detection is carried out in two independent detection configurations viz., bright field detection scheme that detects the core-mode power and dark field detection scheme that detects the cladding mode power. The use of such a double detection scheme definitely enhances the reliability and accuracy of the results. Furthermore, the cladding of the present fiber need not be removed as done in conventional evanescent wave fiber sensors.

Hazard-Ranking of Agricultural Pesticides for Chronic Health Effects in Yuma County, Arizona

PubMed Central

Sugeng, Anastasia J.; Beamer, Paloma I.; Lutz, Eric A.; Rosales, Cecilia B.

2013-01-01

With thousands of pesticides registered by the United States Environmental Protection Agency, it not feasible to sample for all pesticides applied in agricultural communities. Hazard-ranking pesticides based on use, toxicity, and exposure potential can help prioritize community-specific pesticide hazards. This study applied hazard-ranking schemes for cancer, endocrine disruption, and reproductive/developmental toxicity in Yuma County, Arizona. An existing cancer hazard-ranking scheme was modified, and novel schemes for endocrine disruption and reproductive/developmental toxicity were developed to rank pesticide hazards. The hazard-ranking schemes accounted for pesticide use, toxicity, and exposure potential based on chemical properties of each pesticide. Pesticides were ranked as hazards with respect to each health effect, as well as overall chronic health effects. The highest hazard-ranked pesticides for overall chronic health effects were maneb, metam sodium, trifluralin, pronamide, and bifenthrin. The relative pesticide rankings were unique for each health effect. The highest hazard-ranked pesticides differed from those most heavily applied, as well as from those previously detected in Yuma homes over a decade ago. The most hazardous pesticides for cancer in Yuma County, Arizona were also different from a previous hazard-ranking applied in California. Hazard-ranking schemes that take into account pesticide use, toxicity, and exposure potential can help prioritize pesticides of greatest health risk in agricultural communities. This study is the first to provide pesticide hazard-rankings for endocrine disruption and reproductive/developmental toxicity based on use, toxicity, and exposure potential. These hazard-ranking schemes can be applied to other agricultural communities for prioritizing community-specific pesticide hazards to target decreasing health risk. PMID:23783270

Magnetic wire trap arrays for biomarker-based molecular detection

NASA Astrophysics Data System (ADS)

Vieira, Gregory; Mahajan, Kalpesh; Ruan, Gang; Winter, Jessica; Sooryakumar, R.

2012-02-01

Submicrometer-scale magnetic devices built on chip-based platforms have recently been shown to present opportunities for new particle trapping and manipulation technologies. Meanwhile, advances in nanoparticle fabrication allow for the building of custom-made particles with precise control of their size, composition, and other properties such as magnetism, fluorescence, and surface biomarker characteristics. In particular, carefully tailored surface biomarkers facilitate precise binding to targeted molecules, self-actuated construction of hybrid structures, and fluorescence-based detection schemes. Based on these progresses, we present an on-chip detection mechanism for molecules with known surface markers. Hybrid nanostructures consisting of micelle nanoparticles, fluorescent quantum dots, and superparamagnetic iron oxide nanoparticles are used to detect proteins or DNA molecules. The target is detected by the magnetic and fluorescent functionalities of the composite nanostructure, whereas in the absence of the target these signals are not present. Underlying this approach is the simultaneous manipulation via ferromagnetic zigzag nanowire arrays and imaging via quantum dot excitation. This chip-based detection technique could provide a powerful, low cost tool for ultrasensitive molecule detection with ramifications in healthcare diagnostics and small-scale chemical synthesis.

A High Order Finite Difference Scheme with Sharp Shock Resolution for the Euler Equations

NASA Technical Reports Server (NTRS)

Gerritsen, Margot; Olsson, Pelle

1996-01-01

We derive a high-order finite difference scheme for the Euler equations that satisfies a semi-discrete energy estimate, and present an efficient strategy for the treatment of discontinuities that leads to sharp shock resolution. The formulation of the semi-discrete energy estimate is based on a symmetrization of the Euler equations that preserves the homogeneity of the flux vector, a canonical splitting of the flux derivative vector, and the use of difference operators that satisfy a discrete analogue to the integration by parts procedure used in the continuous energy estimate. Around discontinuities or sharp gradients, refined grids are created on which the discrete equations are solved after adding a newly constructed artificial viscosity. The positioning of the sub-grids and computation of the viscosity are aided by a detection algorithm which is based on a multi-scale wavelet analysis of the pressure grid function. The wavelet theory provides easy to implement mathematical criteria to detect discontinuities, sharp gradients and spurious oscillations quickly and efficiently.

[GENOTYPING OF THE BURKHOLDERIA MALLEI STRAINS BASED ON DIFFERENT REGION ANALYSIS].

PubMed

Bondareva, O S; Savchenko, S S; Tkachenko, G A; Ledeneva, M L; Lemasova, L V; Antonov, V A

2016-01-01

Development of the genotyping methods of glanders agent is urgent due to its high pathogenicity, lack of effective preventive measures and threat of the use of Burkholderia mallei as a biological weapon. In this work we proposed a scheme for the typing of the B. mallei strains based on different region analysis (DFR). The choice of variable loci differentially presented in various strains of glanders agents was performed by analyzing annotated whole-genome sequences of the B. mallei strains. Primers and fluorescence probes were designed for 9 selected loci. The amplification conditions for different regions were optimized in two variants: with electrophoretic detection and hybridization-fluorescence detection in the strip format. The possibility of applying the DFR analysis to genetic characterization of strains was assessed in 14 B. mallei strains. The genetic profiles of the studied B. mallei strains revealed that the developed DFR-typing scheme was characterized by high discrimination power (Hunter-Gaston index value was 0.92), reproducibility, rapidity, easy interpretation, and applicability for epidemiological surveillance of glanders.

A new detection scheme for ultrafast 2D J-resolved spectroscopy

NASA Astrophysics Data System (ADS)

Giraudeau, Patrick; Akoka, Serge

2007-06-01

Recent ultrafast techniques enable 2D NMR spectra to be obtained in a single scan. A modification of the detection scheme involved in this technique is proposed, permitting the achievement of 2D 1H J-resolved spectra in 500 ms. The detection gradient echoes are substituted by spin echoes to obtain spectra where the coupling constants are encoded along the direct ν2 domain. The use of this new J-resolved detection block after continuous phase-encoding excitation schemes is discussed in terms of resolution and sensitivity. J-resolved spectra obtained on cinnamic acid and 3-ethyl bromopropionate are presented, revealing the expected 2D J-patterns with coupling constants as small as 2 Hz.

Pseudorange Measurement Method Based on AIS Signals.

PubMed

Zhang, Jingbo; Zhang, Shufang; Wang, Jinpeng

2017-05-22

In order to use the existing automatic identification system (AIS) to provide additional navigation and positioning services, a complete pseudorange measurements solution is presented in this paper. Through the mathematical analysis of the AIS signal, the bit-0-phases in the digital sequences were determined as the timestamps. Monte Carlo simulation was carried out to compare the accuracy of the zero-crossing and differential peak, which are two timestamp detection methods in the additive white Gaussian noise (AWGN) channel. Considering the low-speed and low-dynamic motion characteristics of ships, an optimal estimation method based on the minimum mean square error is proposed to improve detection accuracy. Furthermore, the α difference filter algorithm was used to achieve the fusion of the optimal estimation results of the two detection methods. The results show that the algorithm can greatly improve the accuracy of pseudorange estimation under low signal-to-noise ratio (SNR) conditions. In order to verify the effectiveness of the scheme, prototypes containing the measurement scheme were developed and field tests in Xinghai Bay of Dalian (China) were performed. The test results show that the pseudorange measurement accuracy was better than 28 m (σ) without any modification of the existing AIS system.

Pseudorange Measurement Method Based on AIS Signals

PubMed Central

Zhang, Jingbo; Zhang, Shufang; Wang, Jinpeng

2017-01-01

In order to use the existing automatic identification system (AIS) to provide additional navigation and positioning services, a complete pseudorange measurements solution is presented in this paper. Through the mathematical analysis of the AIS signal, the bit-0-phases in the digital sequences were determined as the timestamps. Monte Carlo simulation was carried out to compare the accuracy of the zero-crossing and differential peak, which are two timestamp detection methods in the additive white Gaussian noise (AWGN) channel. Considering the low-speed and low-dynamic motion characteristics of ships, an optimal estimation method based on the minimum mean square error is proposed to improve detection accuracy. Furthermore, the α difference filter algorithm was used to achieve the fusion of the optimal estimation results of the two detection methods. The results show that the algorithm can greatly improve the accuracy of pseudorange estimation under low signal-to-noise ratio (SNR) conditions. In order to verify the effectiveness of the scheme, prototypes containing the measurement scheme were developed and field tests in Xinghai Bay of Dalian (China) were performed. The test results show that the pseudorange measurement accuracy was better than 28 m (σ) without any modification of the existing AIS system. PMID:28531153

Wideband optical sensing using pulse interferometry.

PubMed

Rosenthal, Amir; Razansky, Daniel; Ntziachristos, Vasilis

2012-08-13

Advances in fabrication of high-finesse optical resonators hold promise for the development of miniaturized, ultra-sensitive, wide-band optical sensors, based on resonance-shift detection. Many potential applications are foreseen for such sensors, among them highly sensitive detection in ultrasound and optoacoustic imaging. Traditionally, sensor interrogation is performed by tuning a narrow linewidth laser to the resonance wavelength. Despite the ubiquity of this method, its use has been mostly limited to lab conditions due to its vulnerability to environmental factors and the difficulty of multiplexing - a key factor in imaging applications. In this paper, we develop a new optical-resonator interrogation scheme based on wideband pulse interferometry, potentially capable of achieving high stability against environmental conditions without compromising sensitivity. Additionally, the method can enable multiplexing several sensors. The unique properties of the pulse-interferometry interrogation approach are studied theoretically and experimentally. Methods for noise reduction in the proposed scheme are presented and experimentally demonstrated, while the overall performance is validated for broadband optical detection of ultrasonic fields. The achieved sensitivity is equivalent to the theoretical limit of a 6 MHz narrow-line width laser, which is 40 times higher than what can be usually achieved by incoherent interferometry for the same optical resonator.

Study on nondestructive detection system based on x-ray for wire ropes conveyer belt

NASA Astrophysics Data System (ADS)

Miao, Changyun; Shi, Boya; Wan, Peng; Li, Jie

2008-03-01

A nondestructive detection system based on X-ray for wire ropes conveyer belt is designed by X-ray detection technology. In this paper X-ray detection principle is analyzed, a design scheme of the system is presented; image processing of conveyer belt is researched and image processing algorithms are given; X-ray acquisition receiving board is designed with the use of FPGA and DSP; the software of the system is programmed by C#.NET on WINXP/WIN2000 platform. The experiment indicates the system can implement remote real-time detection of wire ropes conveyer belt images, find faults and give an alarm in time. The system is direct perceived, strong real-time and high accurate. It can be used for fault detection of wire ropes conveyer belts in mines, ports, terminals and other fields.

Implementation of a custom time-domain firmware trigger for RADAR-based cosmic ray detection

NASA Astrophysics Data System (ADS)

Prohira, S.; Besson, D.; Kunwar, S.; Ratzlaff, K.; Young, R.

2018-05-01

Interest in Radio-based detection schemes for ultra-high energy cosmic rays (UHECR) has surged in recent years, owing to the potentially very low cost/detection ratio. The method of radio-frequency (RF) scatter has been proposed as potentially the most economical detection technology. Though the first dedicated experiment to employ this method, the Telescope Array RADAR experiment (TARA) reported no signal, efforts to develop more robust and sensitive trigger techniques continue. This paper details the development of a time-domain firmware trigger that exploits characteristics of the expected scattered signal from an UHECR extensive-air shower (EAS). The improved sensitivity of this trigger is discussed, as well as implementation in two separate field deployments from 2016 to 2017.

ROS-based ground stereo vision detection: implementation and experiments.

PubMed

Hu, Tianjiang; Zhao, Boxin; Tang, Dengqing; Zhang, Daibing; Kong, Weiwei; Shen, Lincheng

This article concentrates on open-source implementation on flying object detection in cluttered scenes. It is of significance for ground stereo-aided autonomous landing of unmanned aerial vehicles. The ground stereo vision guidance system is presented with details on system architecture and workflow. The Chan-Vese detection algorithm is further considered and implemented in the robot operating systems (ROS) environment. A data-driven interactive scheme is developed to collect datasets for parameter tuning and performance evaluating. The flying vehicle outdoor experiments capture the stereo sequential images dataset and record the simultaneous data from pan-and-tilt unit, onboard sensors and differential GPS. Experimental results by using the collected dataset validate the effectiveness of the published ROS-based detection algorithm.

Combining image-processing and image compression schemes

NASA Technical Reports Server (NTRS)

Greenspan, H.; Lee, M.-C.

1995-01-01

An investigation into the combining of image-processing schemes, specifically an image enhancement scheme, with existing compression schemes is discussed. Results are presented on the pyramid coding scheme, the subband coding scheme, and progressive transmission. Encouraging results are demonstrated for the combination of image enhancement and pyramid image coding schemes, especially at low bit rates. Adding the enhancement scheme to progressive image transmission allows enhanced visual perception at low resolutions. In addition, further progressing of the transmitted images, such as edge detection schemes, can gain from the added image resolution via the enhancement.

Electric machine differential for vehicle traction control and stability control

NASA Astrophysics Data System (ADS)

Kuruppu, Sandun Shivantha

Evolving requirements in energy efficiency and tightening regulations for reliable electric drivetrains drive the advancement of the hybrid electric (HEV) and full electric vehicle (EV) technology. Different configurations of EV and HEV architectures are evaluated for their performance. The future technology is trending towards utilizing distinctive properties in electric machines to not only to improve efficiency but also to realize advanced road adhesion controls and vehicle stability controls. Electric machine differential (EMD) is such a concept under current investigation for applications in the near future. Reliability of a power train is critical. Therefore, sophisticated fault detection schemes are essential in guaranteeing reliable operation of a complex system such as an EMD. The research presented here emphasize on implementation of a 4kW electric machine differential, a novel single open phase fault diagnostic scheme, an implementation of a real time slip optimization algorithm and an electric machine differential based yaw stability improvement study. The proposed d-q current signature based SPO fault diagnostic algorithm detects the fault within one electrical cycle. The EMD based extremum seeking slip optimization algorithm reduces stopping distance by 30% compared to hydraulic braking based ABS.

Novel Helmholtz-based photoacoustic sensor for trace gas detection at ppm level using GaInAsSb/GaAlAsSb DFB lasers.

PubMed

Mattiello, Mario; Niklès, Marc; Schilt, Stéphane; Thévenaz, Luc; Salhi, Abdelmajid; Barat, David; Vicet, Aurore; Rouillard, Yves; Werner, Ralph; Koeth, Johannes

2006-04-01

A new and compact photoacoustic sensor for trace gas detection in the 2-2.5 microm atmospheric window is reported. Both the development of antimonide-based DFB lasers with singlemode emission in this spectral range and a novel design of photoacoustic cell adapted to the characteristics of these lasers are discussed. The laser fabrication was made in two steps. The structure was firstly grown by molecular beam epitaxy then a metallic DFB grating was processed. The photoacoustic cell is based on a Helmholtz resonator that was designed in order to fully benefit from the highly divergent emission of the antimonide laser. An optimized modulation scheme based on wavelength modulation of the laser source combined with second harmonic detection has been implemented for efficient suppression of wall noise. Using a 2211 nm laser, sub-ppm detection limit has been demonstrated for ammonia.

Selective coupling of individual electron and nuclear spins with integrated all-spin coherence protection

NASA Astrophysics Data System (ADS)

Terletska, Hanna; Dobrovitski, Viatcheslav

2015-03-01

The electron spin of the NV center in diamond is a promising platform for spin sensing. Applying the dynamical decoupling, the NV electron spin can be used to detect the individual weakly coupled carbon-13 nuclear spins in diamond and employ them for small-scale quantum information processing. However, the nuclear spins within this approach remain unprotected from decoherence, which ultimately limits the detection and restricts the fidelity of the quantum operation. Here we investigate possible schemes for combining the resonant decoupling on the NV spin with the decoherence protection of the nuclear spins. Considering several schemes based on pulse and continuous-wave decoupling, we study how the joint electron-nuclear spin dynamics is affected. We identify regimes where the all-spin coherence protection improves the detection and manipulation. We also discuss potential applications of the all-spin decoupling for detecting spins outside diamond, with the purpose of implementing the nanoscale NMR. This work was supported by the US Department of Energy Basic Energy Sciences (Contract No. DE-AC02-07CH11358).

A supervised 'lesion-enhancement' filter by use of a massive-training artificial neural network (MTANN) in computer-aided diagnosis (CAD).

PubMed

Suzuki, Kenji

2009-09-21

Computer-aided diagnosis (CAD) has been an active area of study in medical image analysis. A filter for the enhancement of lesions plays an important role for improving the sensitivity and specificity in CAD schemes. The filter enhances objects similar to a model employed in the filter; e.g. a blob-enhancement filter based on the Hessian matrix enhances sphere-like objects. Actual lesions, however, often differ from a simple model; e.g. a lung nodule is generally modeled as a solid sphere, but there are nodules of various shapes and with internal inhomogeneities such as a nodule with spiculations and ground-glass opacity. Thus, conventional filters often fail to enhance actual lesions. Our purpose in this study was to develop a supervised filter for the enhancement of actual lesions (as opposed to a lesion model) by use of a massive-training artificial neural network (MTANN) in a CAD scheme for detection of lung nodules in CT. The MTANN filter was trained with actual nodules in CT images to enhance actual patterns of nodules. By use of the MTANN filter, the sensitivity and specificity of our CAD scheme were improved substantially. With a database of 69 lung cancers, nodule candidate detection by the MTANN filter achieved a 97% sensitivity with 6.7 false positives (FPs) per section, whereas nodule candidate detection by a difference-image technique achieved a 96% sensitivity with 19.3 FPs per section. Classification-MTANNs were applied for further reduction of the FPs. The classification-MTANNs removed 60% of the FPs with a loss of one true positive; thus, it achieved a 96% sensitivity with 2.7 FPs per section. Overall, with our CAD scheme based on the MTANN filter and classification-MTANNs, an 84% sensitivity with 0.5 FPs per section was achieved.

B-Spline Filtering for Automatic Detection of Calcification Lesions in Mammograms

NASA Astrophysics Data System (ADS)

Bueno, G.; Sánchez, S.; Ruiz, M.

2006-10-01

Breast cancer continues to be an important health problem between women population. Early detection is the only way to improve breast cancer prognosis and significantly reduce women mortality. It is by using CAD systems that radiologist can improve their ability to detect, and classify lesions in mammograms. In this study the usefulness of using B-spline based on a gradient scheme and compared to wavelet and adaptative filtering has been investigated for calcification lesion detection and as part of CAD systems. The technique has been applied to different density tissues. A qualitative validation shows the success of the method.

Visual privacy by context: proposal and evaluation of a level-based visualisation scheme.

PubMed

Padilla-López, José Ramón; Chaaraoui, Alexandros Andre; Gu, Feng; Flórez-Revuelta, Francisco

2015-06-04

Privacy in image and video data has become an important subject since cameras are being installed in an increasing number of public and private spaces. Specifically, in assisted living, intelligent monitoring based on computer vision can allow one to provide risk detection and support services that increase people's autonomy at home. In the present work, a level-based visualisation scheme is proposed to provide visual privacy when human intervention is necessary, such as at telerehabilitation and safety assessment applications. Visualisation levels are dynamically selected based on the previously modelled context. In this way, different levels of protection can be provided, maintaining the necessary intelligibility required for the applications. Furthermore, a case study of a living room, where a top-view camera is installed, is presented. Finally, the performed survey-based evaluation indicates the degree of protection provided by the different visualisation models, as well as the personal privacy preferences and valuations of the users.

Sensitivity and Specificity of the World Health Organization Dengue Classification Schemes for Severe Dengue Assessment in Children in Rio de Janeiro

PubMed Central

Macedo, Gleicy A.; Gonin, Michelle Luiza C.; Pone, Sheila M.; Cruz, Oswaldo G.; Nobre, Flávio F.; Brasil, Patrícia

2014-01-01

Background The clinical definition of severe dengue fever remains a challenge for researchers in hyperendemic areas like Brazil. The ability of the traditional (1997) as well as the revised (2009) World Health Organization (WHO) dengue case classification schemes to detect severe dengue cases was evaluated in 267 children admitted to hospital with laboratory-confirmed dengue. Principal Findings Using the traditional scheme, 28.5% of patients could not be assigned to any category, while the revised scheme categorized all patients. Intensive therapeutic interventions were used as the reference standard to evaluate the ability of both the traditional and revised schemes to detect severe dengue cases. Analyses of the classified cases (n = 183) demonstrated that the revised scheme had better sensitivity (86.8%, P<0.001), while the traditional scheme had better specificity (93.4%, P<0.001) for the detection of severe forms of dengue. Conclusions/Significance This improved sensitivity of the revised scheme allows for better case capture and increased ICU admission, which may aid pediatricians in avoiding deaths due to severe dengue among children, but, in turn, it may also result in the misclassification of the patients' condition as severe, reflected in the observed lower positive predictive value (61.6%, P<0.001) when compared with the traditional scheme (82.6%, P<0.001). The inclusion of unusual dengue manifestations in the revised scheme has not shifted the emphasis from the most important aspects of dengue disease and the major factors contributing to fatality in this study: shock with consequent organ dysfunction. PMID:24777054

Sensitivity and specificity of the World Health Organization dengue classification schemes for severe dengue assessment in children in Rio de Janeiro.

PubMed

Macedo, Gleicy A; Gonin, Michelle Luiza C; Pone, Sheila M; Cruz, Oswaldo G; Nobre, Flávio F; Brasil, Patrícia

2014-01-01

The clinical definition of severe dengue fever remains a challenge for researchers in hyperendemic areas like Brazil. The ability of the traditional (1997) as well as the revised (2009) World Health Organization (WHO) dengue case classification schemes to detect severe dengue cases was evaluated in 267 children admitted to hospital with laboratory-confirmed dengue. Using the traditional scheme, 28.5% of patients could not be assigned to any category, while the revised scheme categorized all patients. Intensive therapeutic interventions were used as the reference standard to evaluate the ability of both the traditional and revised schemes to detect severe dengue cases. Analyses of the classified cases (n = 183) demonstrated that the revised scheme had better sensitivity (86.8%, P<0.001), while the traditional scheme had better specificity (93.4%, P<0.001) for the detection of severe forms of dengue. This improved sensitivity of the revised scheme allows for better case capture and increased ICU admission, which may aid pediatricians in avoiding deaths due to severe dengue among children, but, in turn, it may also result in the misclassification of the patients' condition as severe, reflected in the observed lower positive predictive value (61.6%, P<0.001) when compared with the traditional scheme (82.6%, P<0.001). The inclusion of unusual dengue manifestations in the revised scheme has not shifted the emphasis from the most important aspects of dengue disease and the major factors contributing to fatality in this study: shock with consequent organ dysfunction.

Earthquake Fingerprints: Representing Earthquake Waveforms for Similarity-Based Detection

NASA Astrophysics Data System (ADS)

Bergen, K.; Beroza, G. C.

2016-12-01

New earthquake detection methods, such as Fingerprint and Similarity Thresholding (FAST), use fast approximate similarity search to identify similar waveforms in long-duration data without templates (Yoon et al. 2015). These methods have two key components: fingerprint extraction and an efficient search algorithm. Fingerprint extraction converts waveforms into fingerprints, compact signatures that represent short-duration waveforms for identification and search. Earthquakes are detected using an efficient indexing and search scheme, such as locality-sensitive hashing, that identifies similar waveforms in a fingerprint database. The quality of the search results, and thus the earthquake detection results, is strongly dependent on the fingerprinting scheme. Fingerprint extraction should map similar earthquake waveforms to similar waveform fingerprints to ensure a high detection rate, even under additive noise and small distortions. Additionally, fingerprints corresponding to noise intervals should have mutually dissimilar fingerprints to minimize false detections. In this work, we compare the performance of multiple fingerprint extraction approaches for the earthquake waveform similarity search problem. We apply existing audio fingerprinting (used in content-based audio identification systems) and time series indexing techniques and present modified versions that are specifically adapted for seismic data. We also explore data-driven fingerprinting approaches that can take advantage of labeled or unlabeled waveform data. For each fingerprinting approach we measure its ability to identify similar waveforms in a low signal-to-noise setting, and quantify the trade-off between true and false detection rates in the presence of persistent noise sources. We compare the performance using known event waveforms from eight independent stations in the Northern California Seismic Network.

Digital electronic engine control fault detection and accommodation flight evaluation

NASA Technical Reports Server (NTRS)

Baer-Ruedhart, J. L.

1984-01-01

The capabilities and performance of various fault detection and accommodation (FDA) schemes in existing and projected engine control systems were investigated. Flight tests of the digital electronic engine control (DEEC) in an F-15 aircraft show discrepancies between flight results and predictions based on simulation and altitude testing. The FDA methodology and logic in the DEEC system, and the results of the flight failures which occurred to date are described.

Applying a new computer-aided detection scheme generated imaging marker to predict short-term breast cancer risk

NASA Astrophysics Data System (ADS)

Mirniaharikandehei, Seyedehnafiseh; Hollingsworth, Alan B.; Patel, Bhavika; Heidari, Morteza; Liu, Hong; Zheng, Bin

2018-05-01

This study aims to investigate the feasibility of identifying a new quantitative imaging marker based on false-positives generated by a computer-aided detection (CAD) scheme to help predict short-term breast cancer risk. An image dataset including four view mammograms acquired from 1044 women was retrospectively assembled. All mammograms were originally interpreted as negative by radiologists. In the next subsequent mammography screening, 402 women were diagnosed with breast cancer and 642 remained negative. An existing CAD scheme was applied ‘as is’ to process each image. From CAD-generated results, four detection features including the total number of (1) initial detection seeds and (2) the final detected false-positive regions, (3) average and (4) sum of detection scores, were computed from each image. Then, by combining the features computed from two bilateral images of left and right breasts from either craniocaudal or mediolateral oblique view, two logistic regression models were trained and tested using a leave-one-case-out cross-validation method to predict the likelihood of each testing case being positive in the next subsequent screening. The new prediction model yielded the maximum prediction accuracy with an area under a ROC curve of AUC  =  0.65  ±  0.017 and the maximum adjusted odds ratio of 4.49 with a 95% confidence interval of (2.95, 6.83). The results also showed an increasing trend in the adjusted odds ratio and risk prediction scores (p  <  0.01). Thus, this study demonstrated that CAD-generated false-positives might include valuable information, which needs to be further explored for identifying and/or developing more effective imaging markers for predicting short-term breast cancer risk.

Detection of convective initiation using Meteosat SEVIRI: implementation in and verification with the tracking and nowcasting algorithm Cb-TRAM

NASA Astrophysics Data System (ADS)

Merk, D.; Zinner, T.

2013-02-01

In this paper a new detection scheme for Convective Initation (CI) under day and night conditions is presented. The new algorithm combines the strengths of two existing methods for detecting Convective Initation with geostationary satellite data and uses the channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG). For the new algorithm five infrared criteria from the Satellite Convection Analysis and Tracking algorithm (SATCAST) and one High Resolution Visible channel (HRV) criteria from Cb-TRAM were adapted. This set of criteria aims for identifying the typical development of quickly developing convective cells in an early stage. The different criteria include timetrends of the 10.8 IR channel and IR channel differences as well as their timetrends. To provide the trend fields an optical flow based method is used, the Pyramidal Matching algorithm which is part of Cb-TRAM. The new detection scheme is implemented in Cb-TRAM and is verified for seven days which comprise different weather situations in Central Europe. Contrasted with the original early stage detection scheme of Cb-TRAM skill scores are provided. From the comparison against detections of later thunderstorm stages, which are also provided by Cb-TRAM, a decrease in false prior warnings (false alarm ratio) from 91 to 81% is presented, an increase of the critical success index from 7.4 to 12.7%, and a decrease of the BIAS from 320 to 146% for normal scan mode. Similar trends are found for rapid scan mode. Most obvious is the decline of false alarms found for synoptic conditions with upper cold air masses triggering convection.

Detection of convective initiation using Meteosat SEVIRI: implementation in and verification with the tracking and nowcasting algorithm Cb-TRAM

NASA Astrophysics Data System (ADS)

Merk, D.; Zinner, T.

2013-08-01

In this paper a new detection scheme for convective initiation (CI) under day and night conditions is presented. The new algorithm combines the strengths of two existing methods for detecting CI with geostationary satellite data. It uses the channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG). For the new algorithm five infrared (IR) criteria from the Satellite Convection Analysis and Tracking algorithm (SATCAST) and one high-resolution visible channel (HRV) criteria from Cb-TRAM were adapted. This set of criteria aims to identify the typical development of quickly developing convective cells in an early stage. The different criteria include time trends of the 10.8 IR channel, and IR channel differences, as well as their time trends. To provide the trend fields an optical-flow-based method is used: the pyramidal matching algorithm, which is part of Cb-TRAM. The new detection scheme is implemented in Cb-TRAM, and is verified for seven days which comprise different weather situations in central Europe. Contrasted with the original early-stage detection scheme of Cb-TRAM, skill scores are provided. From the comparison against detections of later thunderstorm stages, which are also provided by Cb-TRAM, a decrease in false prior warnings (false alarm ratio) from 91 to 81% is presented, an increase of the critical success index from 7.4 to 12.7%, and a decrease of the BIAS from 320 to 146% for normal scan mode. Similar trends are found for rapid scan mode. Most obvious is the decline of false alarms found for the synoptic class "cold air" masses.

Robust Fault Detection for Switched Fuzzy Systems With Unknown Input.

PubMed

Han, Jian; Zhang, Huaguang; Wang, Yingchun; Sun, Xun

2017-10-03

This paper investigates the fault detection problem for a class of switched nonlinear systems in the T-S fuzzy framework. The unknown input is considered in the systems. A novel fault detection unknown input observer design method is proposed. Based on the proposed observer, the unknown input can be removed from the fault detection residual. The weighted H∞ performance level is considered to ensure the robustness. In addition, the weighted H₋ performance level is introduced, which can increase the sensibility of the proposed detection method. To verify the proposed scheme, a numerical simulation example and an electromechanical system simulation example are provided at the end of this paper.

Combining Particle Filters and Consistency-Based Approaches for Monitoring and Diagnosis of Stochastic Hybrid Systems

NASA Technical Reports Server (NTRS)

Narasimhan, Sriram; Dearden, Richard; Benazera, Emmanuel

2004-01-01

Fault detection and isolation are critical tasks to ensure correct operation of systems. When we consider stochastic hybrid systems, diagnosis algorithms need to track both the discrete mode and the continuous state of the system in the presence of noise. Deterministic techniques like Livingstone cannot deal with the stochasticity in the system and models. Conversely Bayesian belief update techniques such as particle filters may require many computational resources to get a good approximation of the true belief state. In this paper we propose a fault detection and isolation architecture for stochastic hybrid systems that combines look-ahead Rao-Blackwellized Particle Filters (RBPF) with the Livingstone 3 (L3) diagnosis engine. In this approach RBPF is used to track the nominal behavior, a novel n-step prediction scheme is used for fault detection and L3 is used to generate a set of candidates that are consistent with the discrepant observations which then continue to be tracked by the RBPF scheme.

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.

Applying a deep learning based CAD scheme to segment and quantify visceral and subcutaneous fat areas from CT images

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; Moore, Kathleen; Liu, Hong; Zheng, Bin

2017-03-01

Abdominal obesity is strongly associated with a number of diseases and accurately assessment of subtypes of adipose tissue volume plays a significant role in predicting disease risk, diagnosis and prognosis. The objective of this study is to develop and evaluate a new computer-aided detection (CAD) scheme based on deep learning models to automatically segment subcutaneous fat areas (SFA) and visceral (VFA) fat areas depicting on CT images. A dataset involving CT images from 40 patients were retrospectively collected and equally divided into two independent groups (i.e. training and testing group). The new CAD scheme consisted of two sequential convolutional neural networks (CNNs) namely, Selection-CNN and Segmentation-CNN. Selection-CNN was trained using 2,240 CT slices to automatically select CT slices belonging to abdomen areas and SegmentationCNN was trained using 84,000 fat-pixel patches to classify fat-pixels as belonging to SFA or VFA. Then, data from the testing group was used to evaluate the performance of the optimized CAD scheme. Comparing to manually labelled results, the classification accuracy of CT slices selection generated by Selection-CNN yielded 95.8%, while the accuracy of fat pixel segmentation using Segmentation-CNN yielded 96.8%. Therefore, this study demonstrated the feasibility of using deep learning based CAD scheme to recognize human abdominal section from CT scans and segment SFA and VFA from CT slices with high agreement compared with subjective segmentation results.

Road sign recognition with fuzzy adaptive pre-processing models.

PubMed

Lin, Chien-Chuan; Wang, Ming-Shi

2012-01-01

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance.

Proteins detection by polymer optical fibers sensitised with overlayers of block and random copolymers

NASA Astrophysics Data System (ADS)

El Sachat, Alexandros; Meristoudi, Anastasia; Markos, Christos; Pispas, Stergios; Riziotis, Christos

2014-03-01

A low cost and low complexity optical detection method of proteins is presented by employing a detection scheme based on electrostatic interactions, and implemented by sensitization of a polymer optical fibers' (POF) surface by thin overlayers of properly designed sensitive copolymer materials with predesigned charges. This method enables the fast detection of proteins having opposite charge to the overlayer, and also the effective discrimination of differently charged proteins like lysozyme (LYS) and bovine serum albumin (BSA). As sensitive materials the block and the random copolymers of the same monomers were employed, namely the block copolymer poly(styrene-b-2vinylpyridine) (PS-b- P2VP) and the corresponding random copolymer poly(styrene-r-2vinylpyridine) (PS-r-P2VP), of similar composition and molecular weights. Results show systematically different response between the block and the random copolymers, although of the same order of magnitude, drawing thus important conclusions on their applications' techno-economic aspects given that they have significantly different associated manufacturing method and costs. The use of the POF platform, in combination with those adaptable copolymer sensing materials could lead to efficient low cost bio-detection schemes.

Road Sign Recognition with Fuzzy Adaptive Pre-Processing Models

PubMed Central

Lin, Chien-Chuan; Wang, Ming-Shi

2012-01-01

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance. PMID:22778650

Application of stochastic discrete event system framework for detection of induced low rate TCP attack.

PubMed

Barbhuiya, F A; Agarwal, Mayank; Purwar, Sanketh; Biswas, Santosh; Nandi, Sukumar

2015-09-01

TCP is the most widely accepted transport layer protocol. The major emphasis during the development of TCP was its functionality and efficiency. However, not much consideration was given on studying the possibility of attackers exploiting the protocol, which has lead to several attacks on TCP. This paper deals with the induced low rate TCP attack. Since the attack is relatively new, only a few schemes have been proposed to mitigate it. However, the main issues with these schemes are scalability, change in TCP header, lack of formal frameworks, etc. In this paper, we have adapted the stochastic DES framework for detecting the attack, which addresses most of these issues. We have successfully deployed and tested the proposed DES based IDS on a test bed. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

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

Kang, Moses; Kim, Keonhui; Muljadi, Eduard

This paper proposes a torque limit-based inertial control scheme of a doubly-fed induction generator (DFIG) that supports the frequency control of a power system. If a frequency deviation occurs, the proposed scheme aims to release a large amount of kinetic energy (KE) stored in the rotating masses of a DFIG to raise the frequency nadir (FN). Upon detecting the event, the scheme instantly increases its output to the torque limit and then reduces the output with the rotor speed so that it converges to the stable operating range. To restore the rotor speed while causing a small second frequency dipmore » (SFD), after the rotor speed converges the power reference is reduced by a small amount and maintained until it meets the reference for maximum power point tracking control. The test results demonstrate that the scheme can improve the FN and maximum rate of change of frequency while causing a small SFD in any wind conditions and in a power system that has a high penetration of wind power, and thus the scheme helps maintain the required level of system reliability. The scheme releases the KE from 2.9 times to 3.7 times the Hydro-Quebec requirement depending on the power reference.« less

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

Bueno, G.; Ruiz, M.; Sanchez, S

Breast cancer continues to be an important health problem between women population. Early detection is the only way to improve breast cancer prognosis and significantly reduce women mortality. It is by using CAD systems that radiologist can improve their ability to detect, and classify lesions in mammograms. In this study the usefulness of using B-spline based on a gradient scheme and compared to wavelet and adaptative filtering has been investigated for calcification lesion detection and as part of CAD systems. The technique has been applied to different density tissues. A qualitative validation shows the success of the method.

Experimental demonstration of the transmission performance for LDPC-coded multiband OFDM ultra-wideband over fiber system

NASA Astrophysics Data System (ADS)

He, Jing; Wen, Xuejie; Chen, Ming; Chen, Lin; Su, Jinshu

2015-01-01

To improve the transmission performance of multiband orthogonal frequency division multiplexing (MB-OFDM) ultra-wideband (UWB) over optical fiber, a pre-coding scheme based on low-density parity-check (LDPC) is adopted and experimentally demonstrated in the intensity-modulation and direct-detection MB-OFDM UWB over fiber system. Meanwhile, a symbol synchronization and pilot-aided channel estimation scheme is implemented on the receiver of the MB-OFDM UWB over fiber system. The experimental results show that the LDPC pre-coding scheme can work effectively in the MB-OFDM UWB over fiber system. After 70 km standard single-mode fiber (SSMF) transmission, at the bit error rate of 1 × 10-3, the receiver sensitivities are improved about 4 dB when the LDPC code rate is 75%.

Qubit-loss-free fusion of atomic W states via photonic detection

NASA Astrophysics Data System (ADS)

Ding, Cheng-Yun; Kong, Fan-Zhen; Yang, Qing; Yang, Ming; Cao, Zhuo-Liang

2018-06-01

In this paper, we propose two new qubit-loss-free (QLF) fusion schemes for W states in cavity QED system. Resonant interactions between atoms and single cavity mode constitute the main fusion mechanism, with which atomic |W_{n+m}> and |W_{n+m+q}> states can be generated, respectively, from a |Wn> and a |Wm>; and from a |Wn>, a |Wm> and a |Wq>, by detecting the cavity mode. The QLF property of the schemes makes them more efficient and simpler than the currently existing ones, and fewer intermediate steps and memory resources are required for generating a target large-scale W state. Furthermore, the fusion of atomic states can be realized via the detection on cavity mode rather than the much complicated atomic detection, which makes our schemes feasible. In addition, the analyses of the optimal resource cost and the experimental feasibility indicate that the present schemes are simple and efficient, and maybe implementable within the current experimental techniques.

Sparse Representations-Based Super-Resolution of Key-Frames Extracted from Frames-Sequences Generated by a Visual Sensor Network

PubMed Central

Sajjad, Muhammad; Mehmood, Irfan; Baik, Sung Wook

2014-01-01

Visual sensor networks (VSNs) usually generate a low-resolution (LR) frame-sequence due to energy and processing constraints. These LR-frames are not very appropriate for use in certain surveillance applications. It is very important to enhance the resolution of the captured LR-frames using resolution enhancement schemes. In this paper, an effective framework for a super-resolution (SR) scheme is proposed that enhances the resolution of LR key-frames extracted from frame-sequences captured by visual-sensors. In a VSN, a visual processing hub (VPH) collects a huge amount of visual data from camera sensors. In the proposed framework, at the VPH, key-frames are extracted using our recent key-frame extraction technique and are streamed to the base station (BS) after compression. A novel effective SR scheme is applied at BS to produce a high-resolution (HR) output from the received key-frames. The proposed SR scheme uses optimized orthogonal matching pursuit (OOMP) for sparse-representation recovery in SR. OOMP does better in terms of detecting true sparsity than orthogonal matching pursuit (OMP). This property of the OOMP helps produce a HR image which is closer to the original image. The K-SVD dictionary learning procedure is incorporated for dictionary learning. Batch-OMP improves the dictionary learning process by removing the limitation in handling a large set of observed signals. Experimental results validate the effectiveness of the proposed scheme and show its superiority over other state-of-the-art schemes. PMID:24566632

Sparse representations-based super-resolution of key-frames extracted from frames-sequences generated by a visual sensor network.

PubMed

Sajjad, Muhammad; Mehmood, Irfan; Baik, Sung Wook

2014-02-21

Visual sensor networks (VSNs) usually generate a low-resolution (LR) frame-sequence due to energy and processing constraints. These LR-frames are not very appropriate for use in certain surveillance applications. It is very important to enhance the resolution of the captured LR-frames using resolution enhancement schemes. In this paper, an effective framework for a super-resolution (SR) scheme is proposed that enhances the resolution of LR key-frames extracted from frame-sequences captured by visual-sensors. In a VSN, a visual processing hub (VPH) collects a huge amount of visual data from camera sensors. In the proposed framework, at the VPH, key-frames are extracted using our recent key-frame extraction technique and are streamed to the base station (BS) after compression. A novel effective SR scheme is applied at BS to produce a high-resolution (HR) output from the received key-frames. The proposed SR scheme uses optimized orthogonal matching pursuit (OOMP) for sparse-representation recovery in SR. OOMP does better in terms of detecting true sparsity than orthogonal matching pursuit (OMP). This property of the OOMP helps produce a HR image which is closer to the original image. The K-SVD dictionary learning procedure is incorporated for dictionary learning. Batch-OMP improves the dictionary learning process by removing the limitation in handling a large set of observed signals. Experimental results validate the effectiveness of the proposed scheme and show its superiority over other state-of-the-art schemes.

10-Gbps optical duobinary signal generated by bandwidth-limited reflective semiconductor optical amplifier in colorless optical network units and compensated by fiber Bragg grating-based equalizer in optical line terminal

NASA Astrophysics Data System (ADS)

Fu, Meixia; Zhang, Min; Wang, Danshi; Cui, Yue; Han, Huanhuan

2016-10-01

We propose a scheme of optical duobinary-modulated upstream transmission system for reflective semiconductor optical amplifier-based colorless optical network units in 10-Gbps wavelength-division multiplexed passive optical network (WDM-PON), where a fiber Bragg grating (FBG) is adopted as an optical equalizer for better performance. The demodulation module is extremely simple, only needing a binary intensity modulation direct detection receiver. A better received sensitivity of -16.98 dBm at bit rate error (BER)=1.0×10-4 can be achieved at 120 km without FBG, and the BER at the sensitivity of -18.49 dBm can be up to 2.1×10-5 at the transmission distance of 160 km with FBG, which demonstrates the feasibility of our proposed scheme. Moreover, it could be a high cost-effectiveness scheme for WDM-PON in the future.

High speed, high performance, portable, dual-channel, optical fiber Bragg grating (FBG) demodulator

NASA Astrophysics Data System (ADS)

Zhang, Hongtao; Wei, Zhanxiong; Fan, Lingling; Wang, Pengfei; Zhao, Xilin; Wang, Zhenhua; Yang, Shangming; Cui, Hong-Liang

2009-10-01

A high speed, high performance, portable, dual-channel, optical Fiber Bragg Grating demodulator based on fiber Fabry- Pérot tunable filter (FFP-FT) is reported in this paper. The high speed demodulation can be achieved to detect the dynamical loads of vehicles with speed of 15 mph. However, the drifts of piezoelectric transducer (PZT) in the cavity of FFP-FT dramatically degrade the stability of system. Two schemes are implemented to improve the stability of system. Firstly, a temperature control system is installed to effectively remove the thermal drifts of PZT. Secondly, a scheme of changing the bias voltage of FFP-FT to restrain non-thermal drifts has been realized at lab and will be further developed to an automatic control system based on microcontroller. Although this demodulator is originally used in Weight-In- Motion (WIM) sensing system, it can be extended into other aspects and the schemes presented in this paper will be useful in many applications.

Adaptively loaded SP-offset-QAM OFDM for IM/DD communication systems.

PubMed

Zhao, Jian; Chan, Chun-Kit

2017-09-04

In this paper, we propose adaptively loaded set-partitioned offset quadrature amplitude modulation (SP-offset-QAM) orthogonal frequency division multiplexing (OFDM) for low-cost intensity-modulation direct-detection (IM/DD) communication systems. We compare this scheme with multi-band carrier-less amplitude phase modulation (CAP) and conventional OFDM, and demonstrate >40 Gbit/s transmission over 50-km single-mode fiber. It is shown that the use of SP-QAM formats, together with the adaptive loading algorithm specifically designed to this group of formats, results in significant performance improvement for all these three schemes. SP-offset-QAM OFDM exhibits greatly reduced complexity compared to SP-QAM based multi-band CAP, via parallelized implementation and minimized memory length for spectral shaping. On the other hand, this scheme shows better performance than SP-QAM based conventional OFDM at both back-to-back and after transmission. We also characterize the proposed scheme in terms of enhanced tolerance to fiber intra-channel nonlinearity and the potential to increase the communication security. The studies show that adaptive SP-offset-QAM OFDM is a promising IM/DD solution for medium- and long-reach optical access networks and data center connections.

Deep ensemble learning of virtual endoluminal views for polyp detection in CT colonography

NASA Astrophysics Data System (ADS)

Umehara, Kensuke; Näppi, Janne J.; Hironaka, Toru; Regge, Daniele; Ishida, Takayuki; Yoshida, Hiroyuki

2017-03-01

Robust training of a deep convolutional neural network (DCNN) requires a very large number of annotated datasets that are currently not available in CT colonography (CTC). We previously demonstrated that deep transfer learning provides an effective approach for robust application of a DCNN in CTC. However, at high detection accuracy, the differentiation of small polyps from non-polyps was still challenging. In this study, we developed and evaluated a deep ensemble learning (DEL) scheme for reviewing of virtual endoluminal images to improve the performance of computer-aided detection (CADe) of polyps in CTC. Nine different types of image renderings were generated from virtual endoluminal images of polyp candidates detected by a conventional CADe system. Eleven DCNNs that represented three types of publically available pre-trained DCNN models were re-trained by transfer learning to identify polyps from the virtual endoluminal images. A DEL scheme that determines the final detected polyps by a review of the nine types of VE images was developed by combining the DCNNs using a random forest classifier as a meta-classifier. For evaluation, we sampled 154 CTC cases from a large CTC screening trial and divided the cases randomly into a training dataset and a test dataset. At 3.9 falsepositive (FP) detections per patient on average, the detection sensitivities of the conventional CADe system, the highestperforming single DCNN, and the DEL scheme were 81.3%, 90.7%, and 93.5%, respectively, for polyps ≥6 mm in size. For small polyps, the DEL scheme reduced the number of false positives by up to 83% over that of using a single DCNN alone. These preliminary results indicate that the DEL scheme provides an effective approach for improving the polyp detection performance of CADe in CTC, especially for small polyps.

A Low-Cost Tracking System for Running Race Applications Based on Bluetooth Low Energy Technology.

PubMed

Perez-Diaz-de-Cerio, David; Hernández-Solana, Ángela; Valdovinos, Antonio; Valenzuela, Jose Luis

2018-03-20

Timing points used in running races and other competition events are generally based on radio-frequency identification (RFID) technology. Athletes' times are calculated via passive RFID tags and reader kits. Specifically, the reader infrastructure needed is complex and requires the deployment of a mat or ramps which hide the receiver antennae under them. Moreover, with the employed tags, it is not possible to transmit additional and dynamic information such as pulse or oximetry monitoring, alarms, etc. In this paper we present a system based on two low complex schemes allowed in Bluetooth Low Energy (BLE): the non-connectable undirected advertisement process and a modified version of scannable undirected advertisement process using the new capabilities present in Bluetooth 5. After fully describing the system architecture, which allows full real-time position monitoring of the runners using mobile phones on the organizer side and BLE sensors on the participants' side, we derive the mobility patterns of runners and capacity requirements, which are determinant for evaluating the performance of the proposed system. They have been obtained from the analysis of the real data measured in the last Barcelona Marathon. By means of simulations, we demonstrate that, even under disadvantageous conditions (50% error ratio), both schemes perform reliably and are able to detect the 100% of the participants in all the cases. The cell coverage of the system needs to be adjusted when non-connectable process is considered. Nevertheless, through simulation and experimental, we show that the proposed scheme based on the new events available in Bluetooth 5 is clearly the best implementation alternative for all the cases, no matter the coverage area and the runner speed. The proposal widely exceeds the detection requirements of the real scenario, surpassing the measured peaks of 20 sensors per second incoming in the coverage area, moving at speeds that range from 1.5 m/s to 6.25 m/s. The designed real test-bed shows that the scheme is able to detect 72 sensors below 600 ms, fulfilling comfortably the requirements determined for the intended application. The main disadvantage of this system would be that the sensors are active, but we have proved that its consumption can be so low (9.5 µA) that, with a typical button cell, the sensor battery life would be over 10,000 h of use.

A Low-Cost Tracking System for Running Race Applications Based on Bluetooth Low Energy Technology

PubMed Central

2018-01-01

Timing points used in running races and other competition events are generally based on radio-frequency identification (RFID) technology. Athletes’ times are calculated via passive RFID tags and reader kits. Specifically, the reader infrastructure needed is complex and requires the deployment of a mat or ramps which hide the receiver antennae under them. Moreover, with the employed tags, it is not possible to transmit additional and dynamic information such as pulse or oximetry monitoring, alarms, etc. In this paper we present a system based on two low complex schemes allowed in Bluetooth Low Energy (BLE): the non-connectable undirected advertisement process and a modified version of scannable undirected advertisement process using the new capabilities present in Bluetooth 5. After fully describing the system architecture, which allows full real-time position monitoring of the runners using mobile phones on the organizer side and BLE sensors on the participants’ side, we derive the mobility patterns of runners and capacity requirements, which are determinant for evaluating the performance of the proposed system. They have been obtained from the analysis of the real data measured in the last Barcelona Marathon. By means of simulations, we demonstrate that, even under disadvantageous conditions (50% error ratio), both schemes perform reliably and are able to detect the 100% of the participants in all the cases. The cell coverage of the system needs to be adjusted when non-connectable process is considered. Nevertheless, through simulation and experimental, we show that the proposed scheme based on the new events available in Bluetooth 5 is clearly the best implementation alternative for all the cases, no matter the coverage area and the runner speed. The proposal widely exceeds the detection requirements of the real scenario, surpassing the measured peaks of 20 sensors per second incoming in the coverage area, moving at speeds that range from 1.5 m/s to 6.25 m/s. The designed real test-bed shows that the scheme is able to detect 72 sensors below 600 ms, fulfilling comfortably the requirements determined for the intended application. The main disadvantage of this system would be that the sensors are active, but we have proved that its consumption can be so low (9.5 µA) that, with a typical button cell, the sensor battery life would be over 10,000 h of use. PMID:29558432

A robust trust establishment scheme for wireless sensor networks.

PubMed

Ishmanov, Farruh; Kim, Sung Won; Nam, Seung Yeob

2015-03-23

Security techniques like cryptography and authentication can fail to protect a network once a node is compromised. Hence, trust establishment continuously monitors and evaluates node behavior to detect malicious and compromised nodes. However, just like other security schemes, trust establishment is also vulnerable to attack. Moreover, malicious nodes might misbehave intelligently to trick trust establishment schemes. Unfortunately, attack-resistance and robustness issues with trust establishment schemes have not received much attention from the research community. Considering the vulnerability of trust establishment to different attacks and the unique features of sensor nodes in wireless sensor networks, we propose a lightweight and robust trust establishment scheme. The proposed trust scheme is lightweight thanks to a simple trust estimation method. The comprehensiveness and flexibility of the proposed trust estimation scheme make it robust against different types of attack and misbehavior. Performance evaluation under different types of misbehavior and on-off attacks shows that the detection rate of the proposed trust mechanism is higher and more stable compared to other trust mechanisms.

Detection, isolation and diagnosability analysis of intermittent faults in stochastic systems

NASA Astrophysics Data System (ADS)

Yan, Rongyi; He, Xiao; Wang, Zidong; Zhou, D. H.

2018-02-01

Intermittent faults (IFs) have the properties of unpredictability, non-determinacy, inconsistency and repeatability, switching systems between faulty and healthy status. In this paper, the fault detection and isolation (FDI) problem of IFs in a class of linear stochastic systems is investigated. For the detection and isolation of IFs, it includes: (1) to detect all the appearing time and the disappearing time of an IF; (2) to detect each appearing (disappearing) time of the IF before the subsequent disappearing (appearing) time; (3) to determine where the IFs happen. Based on the outputs of the observers we designed, a novel set of residuals is constructed by using the sliding-time window technique, and two hypothesis tests are proposed to detect all the appearing time and disappearing time of IFs. The isolation problem of IFs is also considered. Furthermore, within a statistical framework, the definition of the diagnosability of IFs is proposed, and a sufficient condition is brought forward for the diagnosability of IFs. Quantitative performance analysis results for the false alarm rate and missing detection rate are discussed, and the influences of some key parameters of the proposed scheme on performance indices such as the false alarm rate and missing detection rate are analysed rigorously. The effectiveness of the proposed scheme is illustrated via a simulation example of an unmanned helicopter longitudinal control system.

Phage-protease-peptide: a novel trifecta enabling multiplex detection of viable bacterial pathogens.

PubMed

Alcaine, S D; Tilton, L; Serrano, M A C; Wang, M; Vachet, R W; Nugen, S R

2015-10-01

Bacteriophages represent rapid, readily targeted, and easily produced molecular probes for the detection of bacterial pathogens. Molecular biology techniques have allowed researchers to make significant advances in the bioengineering of bacteriophage to further improve speed and sensitivity of detection. Despite their host specificity, bacteriophages have not been meaningfully leveraged in multiplex detection of bacterial pathogens. We propose a proof-of-principal phage-based scheme to enable multiplex detection. Our scheme involves bioengineering bacteriophage to carry a gene for a specific protease, which is expressed during infection of the target cell. Upon lysis, the protease is released to cleave a reporter peptide, and the signal detected. Here we demonstrate the successful (i) modification of T7 bacteriophage to carry tobacco etch virus (TEV) protease; (ii) expression of TEV protease by Escherichia coli following infection by our modified T7, an average of 2000 units of protease per phage are produced during infection; and (iii) proof-of-principle detection of E. coli in 3 h after a primary enrichment via TEV protease activity using a fluorescent peptide and using a designed target peptide for matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis (MALDI-TOF MS) analysis. This proof-of-principle can be translated to other phage-protease-peptide combinations to enable multiplex bacterial detection and readily adopted on multiple platforms, like MALDI-TOF MS or fluorescent readers, commonly found in labs.

Hazard-ranking of agricultural pesticides for chronic health effects in Yuma County, Arizona.

PubMed

Sugeng, Anastasia J; Beamer, Paloma I; Lutz, Eric A; Rosales, Cecilia B

2013-10-01

With thousands of pesticides registered by the United States Environmental Protection Agency, it not feasible to sample for all pesticides applied in agricultural communities. Hazard-ranking pesticides based on use, toxicity, and exposure potential can help prioritize community-specific pesticide hazards. This study applied hazard-ranking schemes for cancer, endocrine disruption, and reproductive/developmental toxicity in Yuma County, Arizona. An existing cancer hazard-ranking scheme was modified, and novel schemes for endocrine disruption and reproductive/developmental toxicity were developed to rank pesticide hazards. The hazard-ranking schemes accounted for pesticide use, toxicity, and exposure potential based on chemical properties of each pesticide. Pesticides were ranked as hazards with respect to each health effect, as well as overall chronic health effects. The highest hazard-ranked pesticides for overall chronic health effects were maneb, metam-sodium, trifluralin, pronamide, and bifenthrin. The relative pesticide rankings were unique for each health effect. The highest hazard-ranked pesticides differed from those most heavily applied, as well as from those previously detected in Yuma homes over a decade ago. The most hazardous pesticides for cancer in Yuma County, Arizona were also different from a previous hazard-ranking applied in California. Hazard-ranking schemes that take into account pesticide use, toxicity, and exposure potential can help prioritize pesticides of greatest health risk in agricultural communities. This study is the first to provide pesticide hazard-rankings for endocrine disruption and reproductive/developmental toxicity based on use, toxicity, and exposure potential. These hazard-ranking schemes can be applied to other agricultural communities for prioritizing community-specific pesticide hazards to target decreasing health risk. Copyright © 2013 Elsevier B.V. All rights reserved.

Neural Networks and other Techniques for Fault Identification and Isolation of Aircraft Systems

NASA Technical Reports Server (NTRS)

Innocenti, M.; Napolitano, M.

2003-01-01

Fault identification, isolation, and accomodation have become critical issues in the overall performance of advanced aircraft systems. Neural Networks have shown to be a very attractive alternative to classic adaptation methods for identification and control of non-linear dynamic systems. The purpose of this paper is to show the improvements in neural network applications achievable through the use of learning algorithms more efficient than the classic Back-Propagation, and through the implementation of the neural schemes in parallel hardware. The results of the analysis of a scheme for Sensor Failure, Detection, Identification and Accommodation (SFDIA) using experimental flight data of a research aircraft model are presented. Conventional approaches to the problem are based on observers and Kalman Filters while more recent methods are based on neural approximators. The work described in this paper is based on the use of neural networks (NNs) as on-line learning non-linear approximators. The performances of two different neural architectures were compared. The first architecture is based on a Multi Layer Perceptron (MLP) NN trained with the Extended Back Propagation algorithm (EBPA). The second architecture is based on a Radial Basis Function (RBF) NN trained with the Extended-MRAN (EMRAN) algorithms. In addition, alternative methods for communications links fault detection and accomodation are presented, relative to multiple unmanned aircraft applications.

Saliency detection using mutual consistency-guided spatial cues combination

NASA Astrophysics Data System (ADS)

Wang, Xin; Ning, Chen; Xu, Lizhong

2015-09-01

Saliency detection has received extensive interests due to its remarkable contribution to wide computer vision and pattern recognition applications. However, most existing computational models are designed for detecting saliency in visible images or videos. When applied to infrared images, they may suffer from limitations in saliency detection accuracy and robustness. In this paper, we propose a novel algorithm to detect visual saliency in infrared images by mutual consistency-guided spatial cues combination. First, based on the luminance contrast and contour characteristics of infrared images, two effective saliency maps, i.e., the luminance contrast saliency map and contour saliency map are constructed, respectively. Afterwards, an adaptive combination scheme guided by mutual consistency is exploited to integrate these two maps to generate the spatial saliency map. This idea is motivated by the observation that different maps are actually related to each other and the fusion scheme should present a logically consistent view of these maps. Finally, an enhancement technique is adopted to incorporate spatial saliency maps at various scales into a unified multi-scale framework to improve the reliability of the final saliency map. Comprehensive evaluations on real-life infrared images and comparisons with many state-of-the-art saliency models demonstrate the effectiveness and superiority of the proposed method for saliency detection in infrared images.

Automatic Approach for Lung Segmentation with Juxta-Pleural Nodules from Thoracic CT Based on Contour Tracing and Correction.

PubMed

Wang, Jinke; Guo, Haoyan

2016-01-01

This paper presents a fully automatic framework for lung segmentation, in which juxta-pleural nodule problem is brought into strong focus. The proposed scheme consists of three phases: skin boundary detection, rough segmentation of lung contour, and pulmonary parenchyma refinement. Firstly, chest skin boundary is extracted through image aligning, morphology operation, and connective region analysis. Secondly, diagonal-based border tracing is implemented for lung contour segmentation, with maximum cost path algorithm used for separating the left and right lungs. Finally, by arc-based border smoothing and concave-based border correction, the refined pulmonary parenchyma is obtained. The proposed scheme is evaluated on 45 volumes of chest scans, with volume difference (VD) 11.15 ± 69.63 cm 3 , volume overlap error (VOE) 3.5057 ± 1.3719%, average surface distance (ASD) 0.7917 ± 0.2741 mm, root mean square distance (RMSD) 1.6957 ± 0.6568 mm, maximum symmetric absolute surface distance (MSD) 21.3430 ± 8.1743 mm, and average time-cost 2 seconds per image. The preliminary results on accuracy and complexity prove that our scheme is a promising tool for lung segmentation with juxta-pleural nodules.

Experimental Assessment and Enhancement of Planar Laser-Induced Fluorescence Measurements of Nitric Oxide in an Inverse Diffusion Flame

NASA Technical Reports Server (NTRS)

Partridge, William P.; Laurendeau, Normand M.

1997-01-01

We have experimentally assessed the quantitative nature of planar laser-induced fluorescence (PLIF) measurements of NO concentration in a unique atmospheric pressure, laminar, axial inverse diffusion flame (IDF). The PLIF measurements were assessed relative to a two-dimensional array of separate laser saturated fluorescence (LSF) measurements. We demonstrated and evaluated several experimentally-based procedures for enhancing the quantitative nature of PLIF concentration images. Because these experimentally-based PLIF correction schemes require only the ability to make PLIF and LSF measurements, they produce a more broadly applicable PLIF diagnostic compared to numerically-based correction schemes. We experimentally assessed the influence of interferences on both narrow-band and broad-band fluorescence measurements at atmospheric and high pressures. Optimum excitation and detection schemes were determined for the LSF and PLIF measurements. Single-input and multiple-input, experimentally-based PLIF enhancement procedures were developed for application in test environments with both negligible and significant quench-dependent error gradients. Each experimentally-based procedure provides an enhancement of approximately 50% in the quantitative nature of the PLIF measurements, and results in concentration images nominally as quantitative as LSF point measurements. These correction procedures can be applied to other species, including radicals, for which no experimental data are available from which to implement numerically-based PLIF enhancement procedures.

Nonlinear detection of secondary isotopic chemical shifts in NMR through spin noise

PubMed Central

Pöschko, Maria Theresia; Rodin, Victor V.; Schlagnitweit, Judith; Müller, Norbert; Desvaux, Hervé

2017-01-01

The detection of minor species in the presence of large amounts of similar main components remains a key challenge in analytical chemistry, for instance, to obtain isotopic fingerprints. As an alternative to the classical NMR scheme based on coherent excitation and detection, here we introduce an approach based on spin-noise detection. Chemical shifts and transverse relaxation rates are determined using only the detection circuit. Thanks to a nonlinear effect in mixtures with small chemical shift dispersion, small signals on top of a larger one can be observed with increased sensitivity as bumps on a dip; the latter being the signature of the main magnetization. Experimental observations are underpinned by an analytical theory: the coupling between the magnetization and the coil provides an amplified detection capability of both small static magnetic field inhomogeneities and small NMR signals. This is illustrated by two-bond 12C/13C isotopic measurements. PMID:28067218

RF Tomography for Tunnel Detection: Principles and Inversion Schemes

NASA Astrophysics Data System (ADS)

Lo Monte, L.; Erricolo, D.; Inan, U. S.; Wicks, M. C.

2008-12-01

We propose a novel way to detect underground tunnels based on classical seismic tomography, Ground Penetrating Radar (GPR), inverse scattering principles, and the deployment of distributed sensors, which we call "Distributed RF Tomography". Tunnel detection has been a critical problem that cannot be considered fully solved. Presently, tunnel detection is performed by methods that include seismic sensors, electrical impedance, microgravity, boreholes, and GPR. All of these methods have drawbacks that make them not applicable for use in unfriendly environments, such as battlefields. Specifically, they do not cover wide surface areas, they are generally shallow, they are limited to vertical prospecting, and require the user to be in situ, which may jeopardize one's safety. Additional application of the proposed distributed RF tomography include monitoring sensitive areas, (e.g. banks, power plants, military bases, prisons, national borders) and civil applications (e.g. environmental engineering, mine safety, search and rescue, speleology, archaeology and geophysics). The novelty of a Distributed RF tomography system consists of the following. 1) Sensors are scattered randomly above the ground, thus saving time and money compared to the use of boreholes. 2) The use of lower operating frequency (around HF), which allows for deeper penetration. 3) The use of CW diffraction tomography, which increases the resolution to sub-wavelength values, independently from the sensor displacement, and increases the SNR. 4) Use of linear inversion schemes that are suited for tunnel detection. 5) The use of modulation schemes and signal processing algorithms to mitigate interferences and noise. This presentation will cover: 1. Current physical limits of existing techniques for tunnel detection. 2. Concept of Distributed RF Tomography. 3. Inversion theories and strategies a. Proper forward model for voids buried into an homogeneous medium b. Extended matched filtering inversion c. Near field formulation : Dyadic representation d. Fourier approach: principles and techniques aimed at improving the reconstructed image. e. Theoretical Limits f. Super-Resolution : Singular Values Decomposition and MUSIC 4. Propagation Model and theoretical limitations. 5. Transmitting and Receiving design, with signal processing and modulation. 6. Numerical Simulations using FDTD tools.

High Sensitivity Optomechanical Reference Accelerometer over 10 kHz

DTIC Science & Technology

2014-06-05

bandwidth of 10 kHz and is traceable. We have incorporated a Fabry-P erot fiber-optic micro-cavity that is currently capable of measuring the test-mass...10 kHz- bandwidth requires displacement detection sensitivities at levels of 10 16 m= Hz p . Optical detection schemes, such as Fabry-P erot ...based micro- mirror Fabry-P erot cavity19,20 was built to operate in reflec- tion as the optical sensor. The mechanical oscillator ground platform and

Active identification and control of aerodynamic instabilities in axial and centrifugal compressors

NASA Astrophysics Data System (ADS)

Krichene, Assad

In this thesis, it is experimentally shown that dynamic cursors to stall and surge exist in both axial and centrifugal compressors using the experimental axial and centrifugal compressor rigs located in the School of Aerospace Engineering at the Georgia Institute of Technology. Further, it is shown that the dynamic cursors to stall and surge can be identified in real-time and they can be used in a simple control scheme to avoid the occurrence of stall and surge instabilities altogether. For the centrifugal compressor, a previously developed real-time observer is used in order to detect dynamic cursors to surge in real-time. An off-line analysis using the Fast Fourier Transform (FFT) of the open loop experimental data from the centrifugal compressor rig is carried out to establish the influence of compressor speed on the dynamic cursor frequency. The variation of the amplitude of dynamic cursors with compressor operating condition from experimental data is qualitatively compared with simulation results obtained using a generic compression system model subjected to white noise excitation. Using off-line analysis results, a simple control scheme based on fuzzy logic is synthesized for surge avoidance and recovery. The control scheme is implemented in the centrifugal compressor rig using compressor bleed as well as fuel flow to the combustor. Closed loop experimental results are obtained to demonstrate the effectiveness of the controller for both surge avoidance and surge recovery. The existence of stall cursors in an axial compression system is established using the observer scheme from off-line analysis of an existing database of a commercial gas turbine engine. However, the observer scheme is found to be ineffective in detecting stall cursors in the experimental axial compressor rig in the School of Aerospace Engineering at the Georgia Institute of Technology. An alternate scheme based on the amplitude of pressure data content at the blade passage frequency obtained using a pressure sensor located (in the casing) over the blade row is developed and used in the axial compressor rig for stall and surge avoidance and recovery. (Abstract shortened by UMI.)

Detection of Rooftop Cooling Unit Faults Based on Electrical Measurements

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

Armstrong, Peter R.; Laughman, C R.; Leeb, S B.

Non-intrusive load monitoring (NILM) is accomplished by sampling voltage and current at high rates and reducing the resulting start transients or harmonic contents to concise ''signatures''. Changes in these signatures can be used to detect, and in many cases directly diagnose, equipment and component faults associated with roof-top cooling units. Use of the NILM for fault detection and diagnosis (FDD) is important because (1) it complements other FDD schemes that are based on thermo-fluid sensors and analyses and (2) it is minimally intrusive (one measuring point in the relatively protected confines of the control panel) and therefore inherently reliable. Thismore » paper describes changes in the power signatures of fans and compressors that were found, experimentally and theoretically, to be useful for fault detection.« less

Climate Change Effects on Stream and River Biological Indicators: A Preliminary Analysis (External Review Draft)

EPA Science Inventory

This draft report is a preliminary assessment that describes how biological indicators are likely to respond to climate change, how well current sampling schemes may detect climate-driven changes, and how likely it is that these sampling schemes will continue to detect impairment...

Wavelength-Scanning SPR Imaging Sensors Based on an Acousto-Optic Tunable Filter and a White Light Laser

PubMed Central

Zeng, Youjun; Wang, Lei; Wu, Shu-Yuen; He, Jianan; Qu, Junle; Li, Xuejin; Ho, Ho-Pui; Gu, Dayong; Gao, Bruce Zhi; Shao, Yonghong

2017-01-01

A fast surface plasmon resonance (SPR) imaging biosensor system based on wavelength interrogation using an acousto-optic tunable filter (AOTF) and a white light laser is presented. The system combines the merits of a wide-dynamic detection range and high sensitivity offered by the spectral approach with multiplexed high-throughput data collection and a two-dimensional (2D) biosensor array. The key feature is the use of AOTF to realize wavelength scan from a white laser source and thus to achieve fast tracking of the SPR dip movement caused by target molecules binding to the sensor surface. Experimental results show that the system is capable of completing a SPR dip measurement within 0.35 s. To the best of our knowledge, this is the fastest time ever reported in the literature for imaging spectral interrogation. Based on a spectral window with a width of approximately 100 nm, a dynamic detection range and resolution of 4.63 × 10−2 refractive index unit (RIU) and 1.27 × 10−6 RIU achieved in a 2D-array sensor is reported here. The spectral SPR imaging sensor scheme has the capability of performing fast high-throughput detection of biomolecular interactions from 2D sensor arrays. The design has no mechanical moving parts, thus making the scheme completely solid-state. PMID:28067766

Establishment of a Molecular Serotyping Scheme and a Multiplexed Luminex-Based Array for Enterobacter aerogenes

PubMed Central

Guo, Xi; Wang, Min; Wang, Lu; Wang, Yao; Chen, Tingting; Wu, Pan; Chen, Min; Liu, Bin; Feng, Lu

2018-01-01

Serotyping based on surface polysaccharide antigens is important for the clinical detection and epidemiological surveillance of pathogens. Polysaccharide gene clusters (PSgcs) are typically responsible for the diversity of bacterial surface polysaccharides. Through whole-genome sequencing and analysis, eight putative PSgc types were identified in 23 Enterobacter aerogenes strains from several geographic areas, allowing us to present the first molecular serotyping system for E. aerogenes. A conventional antigenic scheme was also established and correlated well with the molecular serotyping system that was based on PSgc genetic variation, indicating that PSgc-based molecular typing and immunological serology provide equally valid results. Further, a multiplex Luminex-based array was developed, and a double-blind test was conducted with 97 clinical specimens from Shanghai, China, to validate our array. The results of these analyses indicated that strains containing PSgc4 and PSgc7 comprised the predominant groups. We then examined 86 publicly available E. aerogenes strain genomes and identified an additional seven novel PSgc types, with PSgc10 being the most abundant type. In total, our study identified 15 PSgc types in E. aerogenes, providing the basis for a molecular serotyping scheme. From these results, differing epidemic patterns were identified between strains that were predominant in different regions. Our study highlights the feasibility and reliability of a serotyping system based on PSgc diversity, and for the first time, presents a molecular serotyping system, as well as an antigenic scheme for E. aerogenes, providing the basis for molecular diagnostics and epidemiological surveillance of this important emerging pathogen. PMID:29616012

Establishment of a Molecular Serotyping Scheme and a Multiplexed Luminex-Based Array for Enterobacter aerogenes.

PubMed

Guo, Xi; Wang, Min; Wang, Lu; Wang, Yao; Chen, Tingting; Wu, Pan; Chen, Min; Liu, Bin; Feng, Lu

2018-01-01

Serotyping based on surface polysaccharide antigens is important for the clinical detection and epidemiological surveillance of pathogens. Polysaccharide gene clusters (PSgcs) are typically responsible for the diversity of bacterial surface polysaccharides. Through whole-genome sequencing and analysis, eight putative PSgc types were identified in 23 Enterobacter aerogenes strains from several geographic areas, allowing us to present the first molecular serotyping system for E. aerogenes . A conventional antigenic scheme was also established and correlated well with the molecular serotyping system that was based on PSgc genetic variation, indicating that PSgc-based molecular typing and immunological serology provide equally valid results. Further, a multiplex Luminex-based array was developed, and a double-blind test was conducted with 97 clinical specimens from Shanghai, China, to validate our array. The results of these analyses indicated that strains containing PSgc4 and PSgc7 comprised the predominant groups. We then examined 86 publicly available E. aerogenes strain genomes and identified an additional seven novel PSgc types, with PSgc10 being the most abundant type. In total, our study identified 15 PSgc types in E. aerogenes , providing the basis for a molecular serotyping scheme. From these results, differing epidemic patterns were identified between strains that were predominant in different regions. Our study highlights the feasibility and reliability of a serotyping system based on PSgc diversity, and for the first time, presents a molecular serotyping system, as well as an antigenic scheme for E. aerogenes , providing the basis for molecular diagnostics and epidemiological surveillance of this important emerging pathogen.

Simplified demultiplexing scheme for two PDM-IM/DD systems utilizing a single Stokes analyzer over 25-km SMF.

PubMed

Pan, Yan; Yan, Lianshan; Yi, Anlin; Jiang, Lin; Pan, Wei; Luo, Bin; Zou, Xihua

2017-10-15

We propose a four-linear state of polarization multiplexed intensity modulation and direct detection (IM/DD) scheme based on two orthogonal polarization division multiplexing (PDM) on-off keying systems. We also experimentally demonstrate a simple demultiplexing algorithm for this scheme by utilizing only a single Stokes analyzer. At the rate of 4×10  Gbit/s, the experimental results show that the power penalty of the proposed scheme is about 1.5 dB, compared to the single PDM-IM/DD for back-to-back (B2B) transmission. Compared to B2B, just about 1.7 dB power penalty is required after 25 km Corning LEAF optical fiber transmission. Meanwhile, the performance of the polarization tracking is evaluated, and the results show that the BER fluctuation is less than 0.5 dB with a polarization scrambling rate up to 708.75 deg/s.

Best Hiding Capacity Scheme for Variable Length Messages Using Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Bajaj, Ruchika; Bedi, Punam; Pal, S. K.

Steganography is an art of hiding information in such a way that prevents the detection of hidden messages. Besides security of data, the quantity of data that can be hidden in a single cover medium, is also very important. We present a secure data hiding scheme with high embedding capacity for messages of variable length based on Particle Swarm Optimization. This technique gives the best pixel positions in the cover image, which can be used to hide the secret data. In the proposed scheme, k bits of the secret message are substituted into k least significant bits of the image pixel, where k varies from 1 to 4 depending on the message length. The proposed scheme is tested and results compared with simple LSB substitution, uniform 4-bit LSB hiding (with PSO) for the test images Nature, Baboon, Lena and Kitty. The experimental study confirms that the proposed method achieves high data hiding capacity and maintains imperceptibility and minimizes the distortion between the cover image and the obtained stego image.

Interference Information Based Power Control for Cognitive Radio with Multi-Hop Cooperative Sensing

NASA Astrophysics Data System (ADS)

Yu, Youngjin; Murata, Hidekazu; Yamamoto, Koji; Yoshida, Susumu

Reliable detection of other radio systems is crucial for systems that share the same frequency band. In wireless communication channels, there is uncertainty in the received signal level due to multipath fading and shadowing. Cooperative sensing techniques in which radio stations share their sensing information can improve the detection probability of other systems. In this paper, a new cooperative sensing scheme that reduces the false detection probability while maintaining the outage probability of other systems is investigated. In the proposed system, sensing information is collected using multi-hop transmission from all sensing stations that detect other systems, and transmission decisions are based on the received sensing information. The proposed system also controls the transmit power based on the received CINRs from the sensing stations. Simulation results reveal that the proposed system can reduce the outage probability of other systems, or improve its link success probability.

Phase magnification by two-axis countertwisting for detection-noise robust interferometry

NASA Astrophysics Data System (ADS)

Anders, Fabian; Pezzè, Luca; Smerzi, Augusto; Klempt, Carsten

2018-04-01

Entanglement-enhanced atom interferometry has the potential of surpassing the standard quantum limit and eventually reaching the ultimate Heisenberg bound. The experimental progress is, however, hindered by various technical noise sources, including the noise in the detection of the output quantum state. The influence of detection noise can be largely overcome by exploiting echo schemes, where the entanglement-generating interaction is repeated after the interferometer sequence. Here, we propose an echo protocol that uses two-axis countertwisting as the main nonlinear interaction. We demonstrate that the scheme is robust to detection noise and its performance is superior compared to the already demonstrated one-axis twisting echo scheme. In particular, the sensitivity maintains the Heisenberg scaling in the limit of a large particle number. Finally, we show that the protocol can be implemented with spinor Bose-Einstein condensates. Our results thus outline a realistic approach to mitigate the detection noise in quantum-enhanced interferometry.

Optimizing the loss of one-dimensional photonic crystal towards high-sensitivity Bloch-surface-wave sensors under intensity interrogation scheme

NASA Astrophysics Data System (ADS)

Kong, Weijing; Wan, Yuhang; Du, Kun; Zhao, Wenhui; Wang, Shuang; Zheng, Zheng

2016-11-01

The reflected intensity change of the Bloch-surface-wave (BSW) resonance influenced by the loss of a truncated onedimensional photonic crystal structure is numerically analyzed and studied in order to enhance the sensitivity of the Bloch-surface-wave-based sensors. The finite truncated one-dimensional photonic crystal structure is designed to be able to excite BSW mode for water (n=1.33) as the external medium and for p-polarized plane wave incident light. The intensity interrogation scheme which can be operated on a typical Kretschmann prism-coupling configuration by measuring the reflected intensity change of the resonance dip is investigated to optimize the sensitivity. A figure of merit (FOM) is introduced to measure the performance of the one-dimensional photonic crystal multilayer structure under the scheme. The detection sensitivities are calculated under different device parameters with a refractive index change corresponding to different solutions of glycerol in de-ionized (DI)-water. The results show that the intensity sensitivity curve varies similarly with the FOM curve and the sensitivity of the Bloch-surface-wave sensor is greatly affected by the device loss, where an optimized loss value can be got. For the low-loss BSW devices, the intensity interrogation sensing sensitivity may drop sharply from the optimal value. On the other hand, the performance of the detection scheme is less affected by the higher device loss. This observation is in accordance with BSW experimental sensing demonstrations as well. The results obtained could be useful for improving the performance of the Bloch-surface-wave sensors for the investigated sensing scheme.

Development of an improved CAD scheme for automated detection of lung nodules in digital chest images.

PubMed

Xu, X W; Doi, K; Kobayashi, T; MacMahon, H; Giger, M L

1997-09-01

Lung cancer is the leading cause of cancer deaths in men and women in the United States, with a 5-year survival rate of only about 13%. However, this survival rate can be improved to 47% if the disease is diagnosed and treated at an early stage. In this study, we developed an improved computer-aided diagnosis (CAD) scheme for the automated detection of lung nodules in digital chest images to assist radiologists, who could miss up to 30% of the actually positive cases in their daily practice. Two hundred PA chest radiographs, 100 normals and 100 abnormals, were used as the database for our study. The presence of nodules in the 100 abnormal cases was confirmed by two experienced radiologists on the basis of CT scans or radiographic follow-up. In our CAD scheme, nodule candidates were selected initially by multiple gray-level thresholding of the difference image (which corresponds to the subtraction of a signal-enhanced image and a signal-suppressed image) and then classified into six groups. A large number of false positives were eliminated by adaptive rule-based tests and an artificial neural network (ANN). The CAD scheme achieved, on average, a sensitivity of 70% with 1.7 false positives per chest image, a performance which was substantially better as compared with other studies. The CPU time for the processing of one chest image was about 20 seconds on an IBM RISC/6000 Powerstation 590. We believe that the CAD scheme with the current performance is ready for initial clinical evaluation.

Optimal rotated staggered-grid finite-difference schemes for elastic wave modeling in TTI media

NASA Astrophysics Data System (ADS)

Yang, Lei; Yan, Hongyong; Liu, Hong

2015-11-01

The rotated staggered-grid finite-difference (RSFD) is an effective approach for numerical modeling to study the wavefield characteristics in tilted transversely isotropic (TTI) media. But it surfaces from serious numerical dispersion, which directly affects the modeling accuracy. In this paper, we propose two different optimal RSFD schemes based on the sampling approximation (SA) method and the least-squares (LS) method respectively to overcome this problem. We first briefly introduce the RSFD theory, based on which we respectively derive the SA-based RSFD scheme and the LS-based RSFD scheme. Then different forms of analysis are used to compare the SA-based RSFD scheme and the LS-based RSFD scheme with the conventional RSFD scheme, which is based on the Taylor-series expansion (TE) method. The contrast in numerical accuracy analysis verifies the greater accuracy of the two proposed optimal schemes, and indicates that these schemes can effectively widen the wavenumber range with great accuracy compared with the TE-based RSFD scheme. Further comparisons between these two optimal schemes show that at small wavenumbers, the SA-based RSFD scheme performs better, while at large wavenumbers, the LS-based RSFD scheme leads to a smaller error. Finally, the modeling results demonstrate that for the same operator length, the SA-based RSFD scheme and the LS-based RSFD scheme can achieve greater accuracy than the TE-based RSFD scheme, while for the same accuracy, the optimal schemes can adopt shorter difference operators to save computing time.

A summary of image segmentation techniques

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly

1993-01-01

Machine vision systems are often considered to be composed of two subsystems: low-level vision and high-level vision. Low level vision consists primarily of image processing operations performed on the input image to produce another image with more favorable characteristics. These operations may yield images with reduced noise or cause certain features of the image to be emphasized (such as edges). High-level vision includes object recognition and, at the highest level, scene interpretation. The bridge between these two subsystems is the segmentation system. Through segmentation, the enhanced input image is mapped into a description involving regions with common features which can be used by the higher level vision tasks. There is no theory on image segmentation. Instead, image segmentation techniques are basically ad hoc and differ mostly in the way they emphasize one or more of the desired properties of an ideal segmenter and in the way they balance and compromise one desired property against another. These techniques can be categorized in a number of different groups including local vs. global, parallel vs. sequential, contextual vs. noncontextual, interactive vs. automatic. In this paper, we categorize the schemes into three main groups: pixel-based, edge-based, and region-based. Pixel-based segmentation schemes classify pixels based solely on their gray levels. Edge-based schemes first detect local discontinuities (edges) and then use that information to separate the image into regions. Finally, region-based schemes start with a seed pixel (or group of pixels) and then grow or split the seed until the original image is composed of only homogeneous regions. Because there are a number of survey papers available, we will not discuss all segmentation schemes. Rather than a survey, we take the approach of a detailed overview. We focus only on the more common approaches in order to give the reader a flavor for the variety of techniques available yet present enough details to facilitate implementation and experimentation.

Does typing of Chlamydia trachomatis using housekeeping multilocus sequence typing reveal different sexual networks among heterosexuals and men who have sex with men?

PubMed

Versteeg, Bart; Bruisten, Sylvia M; van der Ende, Arie; Pannekoek, Yvonne

2016-04-18

Chlamydia trachomatis infections remain the most common bacterial sexually transmitted infection worldwide. To gain more insight into the epidemiology and transmission of C. trachomatis, several schemes of multilocus sequence typing (MLST) have been developed. We investigated the clustering of C. trachomatis strains derived from men who have sex with men (MSM) and heterosexuals using the MLST scheme based on 7 housekeeping genes (MLST-7) adapted for clinical specimens and a high-resolution MLST scheme based on 6 polymorphic genes, including ompA (hr-MLST-6). Specimens from 100 C. trachomatis infected men who have sex with men (MSM) and 100 heterosexual women were randomly selected from previous studies and sequenced. We adapted the MLST-7 scheme to a nested assay to be suitable for direct typing of clinical specimens. All selected specimens were typed using both the adapted MLST-7 scheme and the hr-MLST-6 scheme. Clustering of C. trachomatis strains derived from MSM and heterosexuals was assessed using minimum spanning tree analysis. Sufficient chlamydial DNA was present in 188 of the 200 (94 %) selected samples. Using the adapted MLST-7 scheme, full MLST profiles were obtained for 187 of 188 tested specimens resulting in a high success rate of 99.5 %. Of these 187 specimens, 91 (48.7 %) were from MSM and 96 (51.3 %) from heterosexuals. We detected 21 sequence types (STs) using the adapted MLST-7 and 79 STs using the hr-MLST-6 scheme. Minimum spanning tree analyses was used to examine the clustering of MLST-7 data, which showed no reflection of separate transmission in MSM and heterosexual hosts. Moreover, typing using the hr-MLST-6 scheme identified genetically related clusters within each of clusters that were identified by using the MLST-7 scheme. No distinct transmission of C. trachomatis could be observed in MSM and heterosexuals using the adapted MLST-7 scheme in contrast to using the hr-MLST-6. In addition, we compared clustering of both MLST schemes and demonstrated that typing using the hr-MLST-6 scheme is able to identify genetically related clusters of C. trachomatis strains within each of the clusters that were identified by using the MLST-7 scheme.

Angle and Context Free Grammar Based Precarious Node Detection and Secure Data Transmission in MANETs.

PubMed

Veerasamy, Anitha; Madane, Srinivasa Rao; Sivakumar, K; Sivaraman, Audithan

2016-01-01

Growing attractiveness of Mobile Ad Hoc Networks (MANETs), its features, and usage has led to the launching of threats and attacks to bring negative consequences in the society. The typical features of MANETs, especially with dynamic topology and open wireless medium, may leave MANETs vulnerable. Trust management using uncertain reasoning scheme has previously attempted to solve this problem. However, it produces additional overhead while securing the network. Hence, a Location and Trust-based secure communication scheme (L&TS) is proposed to overcome this limitation. Since the design securing requires more than two data algorithms, the cost of the system goes up. Another mechanism proposed in this paper, Angle and Context Free Grammar (ACFG) based precarious node elimination and secure communication in MANETs, intends to secure data transmission and detect precarious nodes in a MANET at a comparatively lower cost. The Elliptic Curve function is used to isolate a malicious node, thereby incorporating secure data transfer. Simulation results show that the dynamic estimation of the metrics improves throughput by 26% in L&TS when compared to the TMUR. ACFG achieves 33% and 51% throughput increase when compared to L&TS and TMUR mechanisms, respectively.

Balanced detection for self-mixing interferometry.

PubMed

Li, Kun; Cavedo, Federico; Pesatori, Alessandro; Zhao, Changming; Norgia, Michele

2017-01-15

We propose a new detection scheme for self-mixing interferometry using two photodiodes for implementing a differential acquisition. The method is based on the phase opposition of the self-mixing signal measured between the two laser diode facet outputs. The subtraction of the two outputs implements a sort of balanced detection that improves the signal quality, and allows canceling of unwanted signals due to laser modulation and disturbances on laser supply and transimpedance amplifier. Experimental results demonstrate the benefits of differential acquisition in a system for both absolute distance and displacement-vibration measurement. This Letter provides guidance for the design of self-mixing interferometers using balanced detection.

A Wrf-Chem Flash Rate Parameterization Scheme and LNO(x) Analysis of the 29-30 May 2012 Convective Event in Oklahoma During DC3

NASA Technical Reports Server (NTRS)

Cummings, Kristin A.; Pickering, Kenneth E.; Barth, M.; Weinheimer, A.; Bela, M.; Li, Y.; Allen, D.; Bruning, E.; MacGorman, D.; Rutledge, S.;

A WRF-Chem Flash Rate Parameterization Scheme and LNOx Analysis of the 29-30 May 2012 Convective Event in Oklahoma During DC3

NASA Technical Reports Server (NTRS)

Cummings, Kristin A.; Pickering, Kenneth E.; Barth, M.; Weinheimer, A.; Bela, M.; Li, Y.; Allen, D.; Bruning, E.; MacGorman, D.; Rutledge, S.;

Glucose-oxidase label-based redox cycling for an incubation period-free electrochemical immunosensor.

PubMed

Singh, Amardeep; Park, Seonhwa; Yang, Haesik

2013-05-21

Catalytic reactions of enzyme labels in enzyme-linked immunosorbent assays require a long incubation period to obtain high signal amplification. We present herein a simple immunosensing scheme in which the incubation period is minimized without a large increase in the detection limit. This scheme is based on electrochemical-enzymatic (EN) redox cycling using glucose oxidase (GOx) as an enzyme label, Ru(NH3)6(3+) as a redox mediator, and glucose as an enzyme substrate. Fast electron mediation of Ru(NH3)6(3+) between the electrode and the GOx label attached to the electrode allows high signal amplification. The acquisition of chronocoulometric charges at a potential in the mass transfer-controlled region excludes the influence of the kinetics of Ru(NH3)6(2+) electrooxidation and also facilitates high signal-to-background ratios. The reaction between reduced GOx and Ru(NH3)6(3+) is rapid even in air-saturated Tris buffer, where the faster competitive reaction between reduced GOx and dissolved oxygen also occurs. The direct electrooxidation of glucose at the electrode and the direct electron transfer between glucose and Ru(NH3)6(3+) that undesirably increase background levels occur relatively slowly. The detection limit for the EN redox cycling-based detection of cancer antigen 125 (CA-125) in human serum is slightly higher than 0.1 U/mL for the incubation period of 0 min, and the detection limits for the incubation periods of 5 and 10 min are slightly lower than 0.1 U/mL, indicating that the detection limits are almost similar irrespective of the incubation period and that the immunosensor is highly sensitive.

Enhancing a Simple MODIS Cloud Mask Algorithm for the Landsat Data Continuity Mission

NASA Technical Reports Server (NTRS)

Wilson, Michael J.; Oreopoulos, Lazarous

2011-01-01

The presence of clouds in images acquired by the Landsat series of satellites is usually an undesirable, but generally unavoidable fact. With the emphasis of the program being on land imaging, the suspended liquid/ice particles of which clouds are made of fully or partially obscure the desired observational target. Knowing the amount and location of clouds in a Landsat scene is therefore valuable information for scene selection, for making clear-sky composites from multiple scenes, and for scheduling future acquisitions. The two instruments in the upcoming Landsat Data Continuity Mission (LDCM) will include new channels that will enhance our ability to detect high clouds which are often also thin in the sense that a large fraction of solar radiation can pass through them. This work studies the potential impact of these new channels on enhancing LDCM's cloud detection capabilities compared to previous Landsat missions. We revisit a previously published scheme for cloud detection and add new tests to capture more of the thin clouds that are harder to detect with the more limited arsenal channels. Since there are no Landsat data yet that include the new LDCM channels, we resort to data from another instrument, MODIS, which has these bands, as well as the other bands of LDCM, to test the capabilities of our new algorithm. By comparing our revised scheme's performance against the performance of the official MODIS cloud detection scheme, we conclude that the new scheme performs better than the earlier scheme which was not very good at thin cloud detection.

Suppression of laser phase noise in direct-detection optical OFDM transmission using phase-conjugated pilots

NASA Astrophysics Data System (ADS)

Zhang, Lu; Ming, Yi; Li, Jin

2017-11-01

Due to the unique phase noise (PN) characteristics in direct-detection optical OFDM (DDO-OFDM) systems, the design of PN compensator is considered as a difficult task. In this paper, a laser PN suppression scheme with low complexity for DDO-OFDM based on coherent superposition of data carrying subcarriers and their phase conjugates is proposed. Through theoretical derivation, the obvious PN suppression is observed. The effectiveness of this technique is demonstrated by simulation of a 4-QAM DDO-OFDM system over 1000 km transmission length at different laser line-width and subcarrier frequency spacing. The results show that the proposed scheme can significantly suppress both varied phase rotation term (PTR) and inter-carrier interference (ICI), and the laser line-width can be relaxed with up to 9 dB OSNR saving or even breakthrough of performance floor.

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

Stobinska, M.; Institute for Theoretical Physics II, Erlangen-Nuernberg University, Erlangen; Sekatski, P.

Quantum correlations may violate the Bell inequalities. Most experimental schemes confirming this prediction have been realized in all-optical Bell tests suffering from the detection loophole. Experiments which simultaneously close this loophole and the locality loophole are highly desirable and remain challenging. An approach to loophole-free Bell tests is based on amplification of the entangled photons (i.e., on macroscopic entanglement), for which an optical signal should be easy to detect. However, the macroscopic states are partially indistinguishable by classical detectors. An interesting idea to overcome these limitations is to replace the postselection by an appropriate preselection immediately after the amplification. Thismore » is in the spirit of state preprocessing revealing hidden nonlocality. Here, we examine one of the possible preselections, but the presented tools can be used for analysis of other schemes. Filtering methods making the macroscopic entanglement useful for Bell tests and quantum protocols are the subject of an intensive study in the field nowadays.« less

A novel dynamical community detection algorithm based on weighting scheme

NASA Astrophysics Data System (ADS)

Li, Ju; Yu, Kai; Hu, Ke

2015-12-01

Network dynamics plays an important role in analyzing the correlation between the function properties and the topological structure. In this paper, we propose a novel dynamical iteration (DI) algorithm, which incorporates the iterative process of membership vector with weighting scheme, i.e. weighting W and tightness T. These new elements can be used to adjust the link strength and the node compactness for improving the speed and accuracy of community structure detection. To estimate the optimal stop time of iteration, we utilize a new stability measure which is defined as the Markov random walk auto-covariance. We do not need to specify the number of communities in advance. It naturally supports the overlapping communities by associating each node with a membership vector describing the node's involvement in each community. Theoretical analysis and experiments show that the algorithm can uncover communities effectively and efficiently.

A phase angle based diagnostic scheme to planetary gear faults diagnostics under non-stationary operational conditions

NASA Astrophysics Data System (ADS)

Feng, Ke; Wang, Kesheng; Ni, Qing; Zuo, Ming J.; Wei, Dongdong

2017-11-01

Planetary gearbox is a critical component for rotating machinery. It is widely used in wind turbines, aerospace and transmission systems in heavy industry. Thus, it is important to monitor planetary gearboxes, especially for fault diagnostics, during its operational conditions. However, in practice, operational conditions of planetary gearbox are often characterized by variations of rotational speeds and loads, which may bring difficulties for fault diagnosis through the measured vibrations. In this paper, phase angle data extracted from measured planetary gearbox vibrations is used for fault detection under non-stationary operational conditions. Together with sample entropy, fault diagnosis on planetary gearbox is implemented. The proposed scheme is explained and demonstrated in both simulation and experimental studies. The scheme proves to be effective and features advantages on fault diagnosis of planetary gearboxes under non-stationary operational conditions.

Experimentally feasible security check for n-qubit quantum secret sharing

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

Schauer, Stefan; Huber, Marcus; Hiesmayr, Beatrix C.

In this article we present a general security strategy for quantum secret sharing (QSS) protocols based on the scheme presented by Hillery, Buzek, and Berthiaume (HBB) [Phys. Rev. A 59, 1829 (1999)]. We focus on a generalization of the HBB protocol to n communication parties thus including n-partite Greenberger-Horne-Zeilinger states. We show that the multipartite version of the HBB scheme is insecure in certain settings and impractical when going to large n. To provide security for such QSS schemes in general we use the framework presented by some of the authors [M. Huber, F. Mintert, A. Gabriel, B. C. Hiesmayr,more » Phys. Rev. Lett. 104, 210501 (2010)] to detect certain genuine n-partite entanglement between the communication parties. In particular, we present a simple inequality which tests the security.« less

A comparison of frame synchronization methods. [Deep Space Network

NASA Technical Reports Server (NTRS)

Swanson, L.

1982-01-01

Different methods are considered for frame synchronization of a concatenated block code/Viterbi link. Synchronization after Viterbi decoding, synchronization before Viterbi decoding based on hard-quantized channel symbols are all compared. For each scheme, the probability under certain conditions of true detection of sync within four 10,000 bit frames is tabulated.

Near-infrared surface-enhanced-Raman-scattering (SERS) mediated identification of single optically trapped, bacterial spores

NASA Astrophysics Data System (ADS)

Alexander, Troy A.; Gillespie, James B.; Pellegrino, Paul M.; Fell, Nicholas F., Jr.; Wood, Gary L.; Salamo, Gregory J.

2003-03-01

A novel methodology has been developed for the investigation of bacterial spores. Specifically, this method has been used to probe the spore coat composition of several Bacillus species. This technique may be useful in many applications; most notably, development of novel detection schemes toward potentially harmful biological agents. This method would also be useful as an ancillary environmental monitoring system where sterility is of importance (i.e., food preparation areas as well as invasive and minimally invasive medical applications). This unique detection scheme is based on the near-infrared (NIR) Surface-Enhanced-Raman-Scattering (SERS) from single, optically trapped, bacterial spores. The SERS spectra of several bacterial spores in aqueous media have been measured using SERS substrates based on 60-nm diameter gold colloids bound to 3-Aminopropyltriethoxysilane derivatized glass. The light from a 785-nm laser diode was used to capture/manipulate as well as simultaneously excite the SERS of an individual bacterial spore. The collected SERS spectra were examined for uniqueness and the applicability of this technique for the species identification of bacterial spores.

Sensitivity Limits of Rydberg Atom-Based Radio Frequency Electric Field Sensing

NASA Astrophysics Data System (ADS)

Jahangiri, Akbar J.; Kumar, Santosh; Kuebler, Harald; Fan, Haoquan; Shaffer, James P.

2017-04-01

We present progress on Rydberg atom-based RF electric field sensing using Rydberg state electromagnetically induced transparency (EIT) in room temperature atomic vapor cells. In recent experiments on homodyne detection with a Mach-Zehnder interferometer and frequency modulation spectroscopy with active control of residual amplitude modulation we determined that photon shot noise on the probe laser detector limits the sensitivity. Another factor that limits the accuracy is residual Doppler broadening due to the wave-vector mismatch between the coupling and the probe lasers. The sensor as limited by project noise can be orders of magnitude better. A multi-photon scheme is presented that can eliminate the residual Doppler effect by matching the wave-vectors of three lasers and reduce the photon shot noise limit by correctly choosing the Rabi frequencies of the first two steps of the EIT scheme. Using density matrix calculations, we predict that the three-photon approach can improve the detection sensitivity to below 200 nV cm-1 Hz- 1 / 2 and expand the Autler-Townes regime which improves the accuracy. This work is supported by DARPA and the NRO.

Broadband Mid-Infrared Stand-Off Reflection-Absorption Spectroscopy Using a Pulsed External Cavity Quantum Cascade Laser.

PubMed

Liu, Xunchen; Chae, Inseok; Miriyala, Naresh; Lee, Dongkyu; Thundat, Thomas; Kim, Seonghwan

2017-07-01

Broadband mid-infrared molecular spectroscopy is essential for detection and identification of many chemicals and materials. In this report, we present stand-off mid-infrared spectra of 1,3,5-trinitro-1,3,5-triazine or cyclotrimethylene trinitramine (RDX) residues on a stainless-steel surface measured by a broadband external cavity quantum cascade laser (QCL) system. The pulsed QCL is continuously scanned over 800 cm -1 in the molecular fingerprint region and the amplitude of the reflection signal is measured by either a boxcar-averager-based scheme or a lock-in-amplifier-based scheme with 1 MHz and 100 kHz quartz crystal oscillators. The main background noise is due to the laser source instability and is around 0.1% of normalized intensity. The direct absorption spectra have linewidth resolution around 0.1 cm -1 and peak height sensitivity around 10 -2 due to baseline interference fringes. Stand-off detection of 5-50 µg/cm 2 of RDX trace adsorbed on a stainless steel surface at the distance of 5 m is presented.

Robust sensor fault detection and isolation of gas turbine engines subjected to time-varying parameter uncertainties

NASA Astrophysics Data System (ADS)

Pourbabaee, Bahareh; Meskin, Nader; Khorasani, Khashayar

2016-08-01

In this paper, a novel robust sensor fault detection and isolation (FDI) strategy using the multiple model-based (MM) approach is proposed that remains robust with respect to both time-varying parameter uncertainties and process and measurement noise in all the channels. The scheme is composed of robust Kalman filters (RKF) that are constructed for multiple piecewise linear (PWL) models that are constructed at various operating points of an uncertain nonlinear system. The parameter uncertainty is modeled by using a time-varying norm bounded admissible structure that affects all the PWL state space matrices. The robust Kalman filter gain matrices are designed by solving two algebraic Riccati equations (AREs) that are expressed as two linear matrix inequality (LMI) feasibility conditions. The proposed multiple RKF-based FDI scheme is simulated for a single spool gas turbine engine to diagnose various sensor faults despite the presence of parameter uncertainties, process and measurement noise. Our comparative studies confirm the superiority of our proposed FDI method when compared to the methods that are available in the literature.

Watermarked cardiac CT image segmentation using deformable models and the Hermite transform

NASA Astrophysics Data System (ADS)

Gomez-Coronel, Sandra L.; Moya-Albor, Ernesto; Escalante-Ramírez, Boris; Brieva, Jorge

2015-01-01

Medical image watermarking is an open area for research and is a solution for the protection of copyright and intellectual property. One of the main challenges of this problem is that the marked images should not differ perceptually from the original images allowing a correct diagnosis and authentication. Furthermore, we also aim at obtaining watermarked images with very little numerical distortion so that computer vision tasks such as segmentation of important anatomical structures do not be impaired or affected. We propose a preliminary watermarking application in cardiac CT images based on a perceptive approach that includes a brightness model to generate a perceptive mask and identify the image regions where the watermark detection becomes a difficult task for the human eye. We propose a normalization scheme of the image in order to improve robustness against geometric attacks. We follow a spread spectrum technique to insert an alphanumeric code, such as patient's information, within the watermark. The watermark scheme is based on the Hermite transform as a bio-inspired image representation model. In order to evaluate the numerical integrity of the image data after watermarking, we perform a segmentation task based on deformable models. The segmentation technique is based on a vector-value level sets method such that, given a curve in a specific image, and subject to some constraints, the curve can evolve in order to detect objects. In order to stimulate the curve evolution we introduce simultaneously some image features like the gray level and the steered Hermite coefficients as texture descriptors. Segmentation performance was assessed by means of the Dice index and the Hausdorff distance. We tested different mark sizes and different insertion schemes on images that were later segmented either automatic or manual by physicians.

Development of optical micro resonance based sensor for detection and identification of microparticles and biological agents

NASA Astrophysics Data System (ADS)

Saetchnikov, Vladimir A.; Tcherniavskaia, Elina A.; Schweiger, Gustav

2009-05-01

A novel emerging technique for the label-free analysis of nanoparticles including biomolecules using optical micro cavity resonance of whispering-gallery-type modes is being developed. Schemes of such a method based on microsphere melted by laser on the tip of a standard single mode fiber optical cable with a laser and free microsphere matrix have been developed. Using a calibration principal of ultra high resolution spectroscopy based on such a scheme the method is being transformed to make further development for microbial application. The sensitivity of developed schemes has been tested to refractive index changes by monitoring the magnitude of the whispering gallery modes spectral shift. Water solutions of ethanol, glucose, vitamin C and biotin have been used. Some other schemes using similar principals: stand-alone, array and matrix microsphere resonators, liquid core optical ring resonators are also being under development. The influences of the gap in whispering-gallery modes on energy coupling, resonance quality and frequency have been investigated. An optimum gap for sensing applications has been defined at the half maximum energy coupling where both the Q factor and coupling efficiency are high and the resonance frequency is little affected by the gap variation. Developed schemes have been demonstrated to be a promising technology platform for sensitive, lab-on-chip type sensor which can be used for development of diagnostic tools for different biological molecules, e.g. proteins, oligonucleotides, oligosaccharides, lipids, small molecules, viral particles, cells as well as in different experimental contexts e.g. proteomics, genomics, drug discovery, and membrane studies.

Photon Shot Noise Limited Radio Frequency Electric Field Sensing Using Rydberg Atoms in Vapor Cells

NASA Astrophysics Data System (ADS)

Kumar, Santosh; Jahangiri, Akbar J.; Fan, Haoquan; Kuebler, Harald; Shaffer, James P.

2017-04-01

We report Rydberg atom-based radio frequency (RF) electrometry measurements at a sensitivity limited by probe laser photon shot noise. By utilizing the phenomena of electromagnetically induced transparency (EIT) in room temperature atomic vapor cells, Rydberg atoms can be used for absolute electric field measurements that significantly surpass conventional methods in utility, sensitivity and accuracy. We show that by using a Mach-Zehnder interferometer with homodyne detection or using frequency modulation spectroscopy with active control of residual amplitude modulation we can achieve a RF electric field detection sensitivity of 3 μVcm-1Hz/2. The sensitivity is limited by photon shot noise on the detector used to readout the probe laser of the EIT scheme. We suggest a new multi-photon scheme that can mitigate the effect of photon shot noise. The multi-photon approach allows an increase in probe laser power without decreasing atomic coherence times that result from collisions caused by an increase in Rydberg atom excitation. The multi-photon scheme also reduces Residual Doppler broadening enabling more accurate measurements to be carried out. This work is supported by DARPA, and NRO.

Hiding Electronic Patient Record (EPR) in medical images: A high capacity and computationally efficient technique for e-healthcare applications.

PubMed

Loan, Nazir A; Parah, Shabir A; Sheikh, Javaid A; Akhoon, Jahangir A; Bhat, Ghulam M

2017-09-01

A high capacity and semi-reversible data hiding scheme based on Pixel Repetition Method (PRM) and hybrid edge detection for scalable medical images has been proposed in this paper. PRM has been used to scale up the small sized image (seed image) and hybrid edge detection ensures that no important edge information is missed. The scaled up version of seed image has been divided into 2×2 non overlapping blocks. In each block there is one seed pixel whose status decides the number of bits to be embedded in the remaining three pixels of that block. The Electronic Patient Record (EPR)/data have been embedded by using Least Significant and Intermediate Significant Bit Substitution (ISBS). The RC4 encryption has been used to add an additional security layer for embedded EPR/data. The proposed scheme has been tested for various medical and general images and compared with some state of art techniques in the field. The experimental results reveal that the proposed scheme besides being semi-reversible and computationally efficient is capable of handling high payload and as such can be used effectively for electronic healthcare applications. Copyright © 2017. Published by Elsevier Inc.

Cardiac-induced localized thoracic motion detected by a fiber optic sensing scheme

NASA Astrophysics Data System (ADS)

Allsop, Thomas; Lloyd, Glynn; Bhamber, Ranjeet S.; Hadzievski, Ljupco; Halliday, Michael; Webb, David J.; Bennion, Ian

2014-11-01

The cardiovascular health of the human population is a major concern for medical clinicians, with cardiovascular diseases responsible for 48% of all deaths worldwide, according to the World Health Organization. The development of new diagnostic tools that are practicable and economical to scrutinize the cardiovascular health of humans is a major driver for clinicians. We offer a new technique to obtain seismocardiographic signals up to 54 Hz covering both ballistocardiography (below 20 Hz) and audible heart sounds (20 Hz upward), using a system based on curvature sensors formed from fiber optic long period gratings. This system can visualize the real-time three-dimensional (3-D) mechanical motion of the heart by using the data from the sensing array in conjunction with a bespoke 3-D shape reconstruction algorithm. Visualization is demonstrated by adhering three to four sensors on the outside of the thorax and in close proximity to the apex of the heart; the sensing scheme revealed a complex motion of the heart wall next to the apex region of the heart. The detection scheme is low-cost, portable, easily operated and has the potential for ambulatory applications.

Design of Provider-Provisioned Website Protection Scheme against Malware Distribution

NASA Astrophysics Data System (ADS)

Yagi, Takeshi; Tanimoto, Naoto; Hariu, Takeo; Itoh, Mitsutaka

Vulnerabilities in web applications expose computer networks to security threats, and many websites are used by attackers as hopping sites to attack other websites and user terminals. These incidents prevent service providers from constructing secure networking environments. To protect websites from attacks exploiting vulnerabilities in web applications, service providers use web application firewalls (WAFs). WAFs filter accesses from attackers by using signatures, which are generated based on the exploit codes of previous attacks. However, WAFs cannot filter unknown attacks because the signatures cannot reflect new types of attacks. In service provider environments, the number of exploit codes has recently increased rapidly because of the spread of vulnerable web applications that have been developed through cloud computing. Thus, generating signatures for all exploit codes is difficult. To solve these problems, our proposed scheme detects and filters malware downloads that are sent from websites which have already received exploit codes. In addition, to collect information for detecting malware downloads, web honeypots, which automatically extract the communication records of exploit codes, are used. According to the results of experiments using a prototype, our scheme can filter attacks automatically so that service providers can provide secure and cost-effective network environments.

Near-infrared surface-enhanced-Raman-scattering (SERS) mediated detection of single optically trapped bacterial spores

NASA Astrophysics Data System (ADS)

Alexander, Troy A.; Pellegrino, Paul M.; Gillespie, James B.

2003-08-01

A novel methodology has been developed for the investigation of bacterial spores. Specifically, this method has been used to probe the spore coat composition of two different Bacillus stearothermophilus variants. This technique may be useful in many applications; most notably, development of novel detection schemes toward potentially harmful bacteria. This method would also be useful as an ancillary environmental monitoring system where sterility is of importance (i.e., food preparation areas as well as invasive and minimally invasive medical applications). This unique detection scheme is based on the near-infrared (NIR) Surface-Enhanced-Raman-Scattering (SERS) from single, optically trapped, bacterial spores. The SERS spectra of bacterial spores in aqueous media have been measured using SERS substrates based on ~60-nm diameter gold colloids bound to 3-Aminopropyltriethoxysilane derivatized glass. The light from a 787-nm laser diode was used to trap/manipulate as well as simultaneously excite the SERS of an individual bacterial spore. The collected SERS spectra were examined for uniqueness and the applicability of this technique for the strain discrimination of Bacillus stearothermophilus spores. Comparison of normal Raman and SERS spectra reveal not only an enhancement of the normal Raman spectral features but also the appearance of spectral features absent in the normal Raman spectrum.

Near-IR photon number resolving detector design

NASA Astrophysics Data System (ADS)

Bogdanski, Jan; Huntington, Elanor H.

2013-05-01

Photon-Number-Resolving-Detection (PNRD) capability is crucial for many Quantum-Information (QI) applications, e.g. for Coherent-State-Quantum-Computing, Linear-Optics-Quantum-Computing. In Quantum-Key-Distribution and Quantum-Secret-Sharing over 1310/1550 nm fiber, two other important, defense and information security related, QI applications, it's crucial for the information transmission security to guarantee that the information carriers (photons) are single. Thus a PNRD can provide an additional security level against eavesdropping. Currently, there are at least a couple of promising PNRD technologies in the Near-Infrared, but all of them require cryogenic cooling. Thus a compact, portable PNRD, based on commercial Avalanche-Photo-Diodes (APDs), could be a very useful instrument for many QI experiments. For an APD-based PNRD, it is crucial to measure the APD-current in the beginning of the avalanche. Thus an efficient cancellation of the APD capacitive spikes is a necessary condition for the very weak APD current measurement. The detector's principle is based on two commercial, pair-matched InGaAs/InP APDs, connected in series. It leads to a great cancelation of the capacitive spikes caused by the narrow (300 ps), differential gate-pulses of maximum 4V amplitude assuming that both pulses are perfectly matched in regards to their phases, amplitudes, and shapes. The cancellation scheme could be used for other APD-technologies, e.g. Silicon, extending the detection spectrum from visible to NIR. The design distinguishes itself from other, APD-based, schemes by its scalability feature and its computer controlled cancellation of the capacitive spikes. Furthermore, both APDs could be equally used for the detection purpose, which opens a possibility for the odd-even photon number parity detection.

Dark Matter Detection Using Helium Evaporation and Field Ionization

NASA Astrophysics Data System (ADS)

Maris, Humphrey J.; Seidel, George M.; Stein, Derek

2017-11-01

We describe a method for dark matter detection based on the evaporation of helium atoms from a cold surface and their subsequent detection using field ionization. When a dark matter particle scatters off a nucleus of the target material, elementary excitations (phonons or rotons) are produced. Excitations which have an energy greater than the binding energy of helium to the surface can result in the evaporation of helium atoms. We propose to detect these atoms by ionizing them in a strong electric field. Because the binding energy of helium to surfaces can be below 1 meV, this detection scheme opens up new possibilities for the detection of dark matter particles in a mass range down to 1 MeV /c2 .

Rapid detection of Escherichia coli O157:H7 using tunneling magnetoresistance biosensor

NASA Astrophysics Data System (ADS)

Wu, Yuanzhao; Liu, Yiwei; Zhan, Qingfeng; Liu, J. Ping; Li, Run-Wei

2017-05-01

A rapid method for the sensitive detection of bacteria using magnetic immunoassay, which are measured with a tunneling magnetoresistance (TMR) sensor, is described. For the measurement of Escherichia coli O157:H7 (E. coli O157:H7) bacteria, the target was labeled by magnetic beads through magnetic immunoassay. The magnetic beads produce a weak magnetic fringe field when external field is applied, thus induce the magnetoresistance change of TMR sensor. A detection limit of 100 CFU/mL E. coli O157:H7 bacteria in 5 hours was obtained. With its high sensitive and rapid detection scheme based on the TMR biosensor, the detection system is an excellent candidate suitable and promising for food safety and biomedical detection.

Dark Matter Detection Using Helium Evaporation and Field Ionization.

PubMed

Maris, Humphrey J; Seidel, George M; Stein, Derek

2017-11-03

We describe a method for dark matter detection based on the evaporation of helium atoms from a cold surface and their subsequent detection using field ionization. When a dark matter particle scatters off a nucleus of the target material, elementary excitations (phonons or rotons) are produced. Excitations which have an energy greater than the binding energy of helium to the surface can result in the evaporation of helium atoms. We propose to detect these atoms by ionizing them in a strong electric field. Because the binding energy of helium to surfaces can be below 1 meV, this detection scheme opens up new possibilities for the detection of dark matter particles in a mass range down to 1  MeV/c^{2}.

Comb-referenced ultra-high sensitivity spectroscopic molecular detection by compact non-linear sources

NASA Astrophysics Data System (ADS)

Cancio, P.; Gagliardi, G.; Galli, I.; Giusfredi, G.; Maddaloni, P.; Malara, P.; Mazzotti, D.; De Natale, P.

2017-11-01

We present a new generation of compact and rugged mid-infrared (MIR) difference-frequency coherent radiation sources referenced to fiber-based optical frequency comb synthesizers (OFCSs). By coupling the MIR radiation to high-finesse optical cavities, high-resolution and high-sensitivity spectroscopy is demonstrated for CH4 and CO2 around 3.3 and 4.5 μm respectively. Finally, the most effective detection schemes for space-craft trace-gas monitoring applications are singled out.

Femtogram-scale photothermal spectroscopy of explosive molecules on nanostrings.

PubMed

Biswas, T S; Miriyala, N; Doolin, C; Liu, X; Thundat, T; Davis, J P

2014-11-18

We demonstrate detection of femtogram-scale quantities of the explosive molecule 1,3,5-trinitroperhydro-1,3,5-triazine (RDX) via combined nanomechanical photothermal spectroscopy and mass desorption. Photothermal spectroscopy provides a spectroscopic fingerprint of the molecule, which is unavailable using mass adsorption/desorption alone. Our measurement, based on thermomechanical measurement of silicon nitride nanostrings, represents the highest mass resolution ever demonstrated via nanomechanical photothermal spectroscopy. This detection scheme is quick, label-free, and is compatible with parallelized molecular analysis of multicomponent targets.

Luminescent nanodiamonds for biomedical applications.

PubMed

Say, Jana M; van Vreden, Caryn; Reilly, David J; Brown, Louise J; Rabeau, James R; King, Nicholas J C

2011-12-01

In recent years, nanodiamonds have emerged from primarily an industrial and mechanical applications base, to potentially underpinning sophisticated new technologies in biomedical and quantum science. Nanodiamonds are relatively inexpensive, biocompatible, easy to surface functionalise and optically stable. This combination of physical properties are ideally suited to biological applications, including intracellular labelling and tracking, extracellular drug delivery and adsorptive detection of bioactive molecules. Here we describe some of the methods and challenges for processing nanodiamond materials, detection schemes and some of the leading applications currently under investigation.

Smaller to larger biomolecule detection using a lab-built surface plasmon resonance based instrument

NASA Astrophysics Data System (ADS)

Lukose, J.; Kulal, V.; Chidangil, S.; Sinha, R. K.

2016-10-01

We have developed a low-cost surface plasmon resonance (SPR) instrument based on the Kretschmann configuration for biosensing applications. The fabricated instrument is capable of operating in both angular and intensity interrogation schemes. The proposed sensor has proved enormously versatile by detecting a range of analytes with low to high molecular weights. The refractive index based sensor has been used for detecting the variation in the concentration of the aqueous solution of glucose and glycerine. Real time immobilization of protein molecules, bovine serum albumin on a gold (Au) film surface, has also been detected using the SPR imaging technique. Alkanethiol functionalization of the Au surface was performed, and bovine serum albumin was immobilized onto the carboxyl functionalized surface using amine reactive cross linker chemistry. In future, the present approach can also be utilized for the selective detection of a wide range of target biomolecules with the help of specific capture probes, as well as for monitoring protein-drug interactions.

Isotope-selective sensor for medical diagnostics based on PAS

NASA Astrophysics Data System (ADS)

Wolff, M.; Groninga, H. G.; Harde, H.

2005-06-01

Development of new optical sensor technologies has a major impact on the progression of diagnostic methods. Of the permanently increasing number of non-invasive 13C-breath tests, the Urea Breath Test for detection of Helicobacter pylori is the most prominent. However, many recent developments go beyond gastroenterological applications. We present a new detection scheme for breath analysis that employs an especially compact and simple set-up based on Photoacoustic Spectroscopy. Using a wavelength-modulated DFB-diode laser and taking advantage of acoustical resonances of the sample cell, we performed very sensitive isotope-selective measurements on CO2. Detection limits for 13CO2 of a few ppm and for the variation of the 13CO2 concentration of approximately 1% were achieved.

Detection of Single Molecules Illuminated by a Light-Emitting Diode

PubMed Central

Gerhardt, Ilja; Mai, Lijian; Lamas-Linares, Antía; Kurtsiefer, Christian

2011-01-01

Optical detection and spectroscopy of single molecules has become an indispensable tool in biological imaging and sensing. Its success is based on fluorescence of organic dye molecules under carefully engineered laser illumination. In this paper we demonstrate optical detection of single molecules on a wide-field microscope with an illumination based on a commercially available, green light-emitting diode. The results are directly compared with laser illumination in the same experimental configuration. The setup and the limiting factors, such as light transfer to the sample, spectral filtering and the resulting signal-to-noise ratio are discussed. A theoretical and an experimental approach to estimate these parameters are presented. The results can be adapted to other single emitter and illumination schemes. PMID:22346610

Flexible-rate optical packet generation/detection and label swapping for optical label switching networks

NASA Astrophysics Data System (ADS)

Wu, Zhongying; Li, Juhao; Tian, Yu; Ge, Dawei; Zhu, Paikun; Chen, Yuanxiang; Chen, Zhangyuan; He, Yongqi

2017-03-01

In recent years, optical label switching (OLS) gains lots of attentions due to its intrinsic advantages to implement protocol, bit-rate, granularity and data format transparency packet switching. In this paper, we propose a novel scheme to realize flexible-rate optical packet switching for OLS networks. At the transmitter node, flexible-rate packet is generated by parallel modulating different combinations of optical carriers generated from the optical multi-carrier generator (OMCG), among which the low-speed optical label occupies one carrier. At the switching node, label is extracted and re-generated in label processing unit (LPU). The payloads are switched based on routing information and new label is added after switching. At the receiver node, another OMCG serves as local oscillators (LOs) for optical payloads coherent detection. The proposed scheme offers good flexibility for dynamic optical packet switching by adjusting the payload bandwidth and could also effectively reduce the number of lasers, modulators and receivers for packet generation/detection. We present proof-of-concept demonstrations of flexible-rate packet generation/detection and label swapping in 12.5 GHz grid. The influence of crosstalk for cascaded label swapping is also investigated.

Evidence for wave resonance as a key mechanism for generating high-amplitude quasi-stationary waves in boreal summer

NASA Astrophysics Data System (ADS)

Kornhuber, K.; Petoukhov, V.; Petri, S.; Rahmstorf, S.; Coumou, D.

2017-09-01

Several recent northern hemisphere summer extremes have been linked to persistent high-amplitude wave patterns (e.g. heat waves in Europe 2003, Russia 2010 and in the US 2011, Floods in Pakistan 2010 and Europe 2013). Recently quasi-resonant amplification (QRA) was proposed as a mechanism that, when certain dynamical conditions are fulfilled, can lead to such high-amplitude wave events. Based on these resonance conditions a detection scheme to scan reanalysis data for QRA events in boreal summer months was implemented. With this objective detection scheme we analyzed the occurrence and duration of QRA events and the associated atmospheric flow patterns in 1979-2015 reanalysis data. We detect a total number of 178 events for wave 6, 7 and 8 and find that during roughly one-third of all high amplitude events QRA conditions were met for respective waves. Our analysis reveals a significant shift for quasi-stationary waves 6 and 7 towards high amplitudes during QRA events, lagging first QRA-detection by typically one week. The results provide further evidence for the validity of the QRA hypothesis and its important role in generating high amplitude waves in boreal summer.

Atom-atom entanglement by single-photon detection.

PubMed

Slodička, L; Hétet, G; Röck, N; Schindler, P; Hennrich, M; Blatt, R

2013-02-22

A scheme for entangling distant atoms is realized, as proposed in the seminal paper by [C. Cabrillo et al., Phys. Rev. A 59, 1025 (1999)]. The protocol is based on quantum interference and detection of a single photon scattered from two effectively one meter distant laser cooled and trapped atomic ions. The detection of a single photon heralds entanglement of two internal states of the trapped ions with high rate and with a fidelity limited mostly by atomic motion. Control of the entangled state phase is demonstrated by changing the path length of the single-photon interferometer.

Multiple-image encryption via lifting wavelet transform and XOR operation based on compressive ghost imaging scheme

NASA Astrophysics Data System (ADS)

Li, Xianye; Meng, Xiangfeng; Yang, Xiulun; Wang, Yurong; Yin, Yongkai; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

2018-03-01

A multiple-image encryption method via lifting wavelet transform (LWT) and XOR operation is proposed, which is based on a row scanning compressive ghost imaging scheme. In the encryption process, the scrambling operation is implemented for the sparse images transformed by LWT, then the XOR operation is performed on the scrambled images, and the resulting XOR images are compressed in the row scanning compressive ghost imaging, through which the ciphertext images can be detected by bucket detector arrays. During decryption, the participant who possesses his/her correct key-group, can successfully reconstruct the corresponding plaintext image by measurement key regeneration, compression algorithm reconstruction, XOR operation, sparse images recovery, and inverse LWT (iLWT). Theoretical analysis and numerical simulations validate the feasibility of the proposed method.

A Novel Physical Layer Assisted Authentication Scheme for Mobile Wireless Sensor Networks

PubMed Central

Wang, Qiuhua

2017-01-01

Physical-layer authentication can address physical layer vulnerabilities and security threats in wireless sensor networks, and has been considered as an effective complementary enhancement to existing upper-layer authentication mechanisms. In this paper, to advance the existing research and improve the authentication performance, we propose a novel physical layer assisted authentication scheme for mobile wireless sensor networks. In our proposed scheme, we explore the reciprocity and spatial uncorrelation of the wireless channel to verify the identities of involved transmitting users and decide whether all data frames are from the same sender. In our proposed scheme, a new method is developed for the legitimate users to compare their received signal strength (RSS) records, which avoids the information from being disclosed to the adversary. Our proposed scheme can detect the spoofing attack even in a high dynamic environment. We evaluate our scheme through experiments under indoor and outdoor environments. Experiment results show that our proposed scheme is more efficient and achieves a higher detection rate as well as keeping a lower false alarm rate. PMID:28165423

A Novel Physical Layer Assisted Authentication Scheme for Mobile Wireless Sensor Networks.

PubMed

Wang, Qiuhua

2017-02-04

Physical-layer authentication can address physical layer vulnerabilities and security threats in wireless sensor networks, and has been considered as an effective complementary enhancement to existing upper-layer authentication mechanisms. In this paper, to advance the existing research and improve the authentication performance, we propose a novel physical layer assisted authentication scheme for mobile wireless sensor networks. In our proposed scheme, we explore the reciprocity and spatial uncorrelation of the wireless channel to verify the identities of involved transmitting users and decide whether all data frames are from the same sender. In our proposed scheme, a new method is developed for the legitimate users to compare their received signal strength (RSS) records, which avoids the information from being disclosed to the adversary. Our proposed scheme can detect the spoofing attack even in a high dynamic environment. We evaluate our scheme through experiments under indoor and outdoor environments. Experiment results show that our proposed scheme is more efficient and achieves a higher detection rate as well as keeping a lower false alarm rate.

Accelerometer and Camera-Based Strategy for Improved Human Fall Detection.

PubMed

Zerrouki, Nabil; Harrou, Fouzi; Sun, Ying; Houacine, Amrane

2016-12-01

In this paper, we address the problem of detecting human falls using anomaly detection. Detection and classification of falls are based on accelerometric data and variations in human silhouette shape. First, we use the exponentially weighted moving average (EWMA) monitoring scheme to detect a potential fall in the accelerometric data. We used an EWMA to identify features that correspond with a particular type of fall allowing us to classify falls. Only features corresponding with detected falls were used in the classification phase. A benefit of using a subset of the original data to design classification models minimizes training time and simplifies models. Based on features corresponding to detected falls, we used the support vector machine (SVM) algorithm to distinguish between true falls and fall-like events. We apply this strategy to the publicly available fall detection databases from the university of Rzeszow's. Results indicated that our strategy accurately detected and classified fall events, suggesting its potential application to early alert mechanisms in the event of fall situations and its capability for classification of detected falls. Comparison of the classification results using the EWMA-based SVM classifier method with those achieved using three commonly used machine learning classifiers, neural network, K-nearest neighbor and naïve Bayes, proved our model superior.

Fault Detection for Nonlinear Process With Deterministic Disturbances: A Just-In-Time Learning Based Data Driven Method.

PubMed

Yin, Shen; Gao, Huijun; Qiu, Jianbin; Kaynak, Okyay

2017-11-01

Data-driven fault detection plays an important role in industrial systems due to its applicability in case of unknown physical models. In fault detection, disturbances must be taken into account as an inherent characteristic of processes. Nevertheless, fault detection for nonlinear processes with deterministic disturbances still receive little attention, especially in data-driven field. To solve this problem, a just-in-time learning-based data-driven (JITL-DD) fault detection method for nonlinear processes with deterministic disturbances is proposed in this paper. JITL-DD employs JITL scheme for process description with local model structures to cope with processes dynamics and nonlinearity. The proposed method provides a data-driven fault detection solution for nonlinear processes with deterministic disturbances, and owns inherent online adaptation and high accuracy of fault detection. Two nonlinear systems, i.e., a numerical example and a sewage treatment process benchmark, are employed to show the effectiveness of the proposed method.

Spin-torque resonant expulsion of the vortex core for an efficient radiofrequency detection scheme.

PubMed

Jenkins, A S; Lebrun, R; Grimaldi, E; Tsunegi, S; Bortolotti, P; Kubota, H; Yakushiji, K; Fukushima, A; de Loubens, G; Klein, O; Yuasa, S; Cros, V

2016-04-01

It has been proposed that high-frequency detectors based on the so-called spin-torque diode effect in spin transfer oscillators could eventually replace conventional Schottky diodes due to their nanoscale size, frequency tunability and large output sensitivity. Although a promising candidate for information and communications technology applications, the output voltage generated from this effect has still to be improved and, more pertinently, reduces drastically with decreasing radiofrequency (RF) current. Here we present a scheme for a new type of spintronics-based high-frequency detector based on the expulsion of the vortex core in a magnetic tunnel junction (MTJ). The resonant expulsion of the core leads to a large and sharp change in resistance associated with the difference in magnetoresistance between the vortex ground state and the final C-state configuration. Interestingly, this reversible effect is independent of the incoming RF current amplitude, offering a fast real-time RF threshold detector.

Photonic generation of phase-stable and wideband chirped microwave signals based on phase-locked dual optical frequency combs.

PubMed

Tong, Yitian; Zhou, Qian; Han, Daming; Li, Baiyu; Xie, Weilin; Liu, Zhangweiyi; Qin, Jie; Wang, Xiaocheng; Dong, Yi; Hu, Weisheng

2016-08-15

A photonics-based scheme is presented for generating wideband and phase-stable chirped microwave signals based on two phase-locked combs with fixed and agile repetition rates. By tuning the difference of the two combs' repetition rates and extracting different order comb tones, a wideband linearly frequency-chirped microwave signal with flexible carrier frequency and chirped range is obtained. Owing to the scheme of dual-heterodyne phase transfer and phase-locked loop, extrinsic phase drift and noise induced by the separated optical paths is detected and suppressed efficiently. Linearly frequency-chirped microwave signals from 5 to 15 GHz and 237 to 247 GHz with 30 ms duration are achieved, respectively, contributing to the time-bandwidth product of 3×10⁸. And less than 1.3×10^-5 linearity errors (RMS) are also obtained.

Visual Privacy by Context: Proposal and Evaluation of a Level-Based Visualisation Scheme

PubMed Central

Padilla-López, José Ramón; Chaaraoui, Alexandros Andre; Gu, Feng; Flórez-Revuelta, Francisco

2015-01-01

Privacy in image and video data has become an important subject since cameras are being installed in an increasing number of public and private spaces. Specifically, in assisted living, intelligent monitoring based on computer vision can allow one to provide risk detection and support services that increase people's autonomy at home. In the present work, a level-based visualisation scheme is proposed to provide visual privacy when human intervention is necessary, such as at telerehabilitation and safety assessment applications. Visualisation levels are dynamically selected based on the previously modelled context. In this way, different levels of protection can be provided, maintaining the necessary intelligibility required for the applications. Furthermore, a case study of a living room, where a top-view camera is installed, is presented. Finally, the performed survey-based evaluation indicates the degree of protection provided by the different visualisation models, as well as the personal privacy preferences and valuations of the users. PMID:26053746

Palladium-based Mass-Tag Cell Barcoding with a Doublet-Filtering Scheme and Single Cell Deconvolution Algorithm

PubMed Central

Zunder, Eli R.; Finck, Rachel; Behbehani, Gregory K.; Amir, El-ad D.; Krishnaswamy, Smita; Gonzalez, Veronica D.; Lorang, Cynthia G.; Bjornson, Zach; Spitzer, Matthew H.; Bodenmiller, Bernd; Fantl, Wendy J.; Pe’er, Dana; Nolan, Garry P.

2015-01-01

SUMMARY Mass-tag cell barcoding (MCB) labels individual cell samples with unique combinatorial barcodes, after which they are pooled for processing and measurement as a single multiplexed sample. The MCB method eliminates variability between samples in antibody staining and instrument sensitivity, reduces antibody consumption, and shortens instrument measurement time. Here, we present an optimized MCB protocol with several improvements over previously described methods. The use of palladium-based labeling reagents expands the number of measurement channels available for mass cytometry and reduces interference with lanthanide-based antibody measurement. An error-detecting combinatorial barcoding scheme allows cell doublets to be identified and removed from the analysis. A debarcoding algorithm that is single cell-based rather than population-based improves the accuracy and efficiency of sample deconvolution. This debarcoding algorithm has been packaged into software that allows rapid and unbiased sample deconvolution. The MCB procedure takes 3–4 h, not including sample acquisition time of ~1 h per million cells. PMID:25612231

UWB pulse detection and TOA estimation using GLRT

NASA Astrophysics Data System (ADS)

Xie, Yan; Janssen, Gerard J. M.; Shakeri, Siavash; Tiberius, Christiaan C. J. M.

2017-12-01

In this paper, a novel statistical approach is presented for time-of-arrival (TOA) estimation based on first path (FP) pulse detection using a sub-Nyquist sampling ultra-wide band (UWB) receiver. The TOA measurement accuracy, which cannot be improved by averaging of the received signal, can be enhanced by the statistical processing of a number of TOA measurements. The TOA statistics are modeled and analyzed for a UWB receiver using threshold crossing detection of a pulse signal with noise. The detection and estimation scheme based on the Generalized Likelihood Ratio Test (GLRT) detector, which captures the full statistical information of the measurement data, is shown to achieve accurate TOA estimation and allows for a trade-off between the threshold level, the noise level, the amplitude and the arrival time of the first path pulse, and the accuracy of the obtained final TOA.

An iterative learning strategy for the auto-tuning of the feedforward and feedback controller in type-1 diabetes.

PubMed

Fravolini, M L; Fabietti, P G

2014-01-01

This paper proposes a scheme for the control of the blood glucose in subjects with type-1 diabetes mellitus based on the subcutaneous (s.c.) glucose measurement and s.c. insulin administration. The tuning of the controller is based on an iterative learning strategy that exploits the repetitiveness of the daily feeding habit of a patient. The control consists of a mixed feedback and feedforward contribution whose parameters are tuned through an iterative learning process that is based on the day-by-day automated analysis of the glucose response to the infusion of exogenous insulin. The scheme does not require any a priori information on the patient insulin/glucose response, on the meal times and on the amount of ingested carbohydrates (CHOs). Thanks to the learning mechanism the scheme is able to improve its performance over time. A specific logic is also introduced for the detection and prevention of possible hypoglycaemia events. The effectiveness of the methodology has been validated using long-term simulation studies applied to a set of nine in silico patients considering realistic uncertainties on the meal times and on the quantities of ingested CHOs.

Onboard Nonlinear Engine Sensor and Component Fault Diagnosis and Isolation Scheme

NASA Technical Reports Server (NTRS)

Tang, Liang; DeCastro, Jonathan A.; Zhang, Xiaodong

2011-01-01

A method detects and isolates in-flight sensor, actuator, and component faults for advanced propulsion systems. In sharp contrast to many conventional methods, which deal with either sensor fault or component fault, but not both, this method considers sensor fault, actuator fault, and component fault under one systemic and unified framework. The proposed solution consists of two main components: a bank of real-time, nonlinear adaptive fault diagnostic estimators for residual generation, and a residual evaluation module that includes adaptive thresholds and a Transferable Belief Model (TBM)-based residual evaluation scheme. By employing a nonlinear adaptive learning architecture, the developed approach is capable of directly dealing with nonlinear engine models and nonlinear faults without the need of linearization. Software modules have been developed and evaluated with the NASA C-MAPSS engine model. Several typical engine-fault modes, including a subset of sensor/actuator/components faults, were tested with a mild transient operation scenario. The simulation results demonstrated that the algorithm was able to successfully detect and isolate all simulated faults as long as the fault magnitudes were larger than the minimum detectable/isolable sizes, and no misdiagnosis occurred

Sliding mode based fault detection, reconstruction and fault tolerant control scheme for motor systems.

PubMed

Mekki, Hemza; Benzineb, Omar; Boukhetala, Djamel; Tadjine, Mohamed; Benbouzid, Mohamed

2015-07-01

The fault-tolerant control problem belongs to the domain of complex control systems in which inter-control-disciplinary information and expertise are required. This paper proposes an improved faults detection, reconstruction and fault-tolerant control (FTC) scheme for motor systems (MS) with typical faults. For this purpose, a sliding mode controller (SMC) with an integral sliding surface is adopted. This controller can make the output of system to track the desired position reference signal in finite-time and obtain a better dynamic response and anti-disturbance performance. But this controller cannot deal directly with total system failures. However an appropriate combination of the adopted SMC and sliding mode observer (SMO), later it is designed to on-line detect and reconstruct the faults and also to give a sensorless control strategy which can achieve tolerance to a wide class of total additive failures. The closed-loop stability is proved, using the Lyapunov stability theory. Simulation results in healthy and faulty conditions confirm the reliability of the suggested framework. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Sensor-less pseudo-sinusoidal drive for a permanent-magnet brushless ac motor

NASA Astrophysics Data System (ADS)

Liu, Li-Hsiang; Chern, Tzuen-Lih; Pan, Ping-Lung; Huang, Tsung-Mou; Tsay, Der-Min; Kuang, Jao-Hwa

2012-04-01

The precise rotor-position information is required for a permanent-magnet brushless ac motor (BLACM) drive. In the conventional sinusoidal drive method, either an encoder or a resolver is usually employed. For position sensor-less vector control schemes, the rotor flux estimation and torque components are obtained by complicated coordinate transformations. These computational intensive methods are susceptible to current distortions and parameter variations. To simplify the method complexity, this work presents a sensor-less pseudo-sinusoidal drive scheme with speed control for a three-phase BLACM. Based on the sinusoidal drive scheme, a floating period of each phase current is inserted for back electromotive force detection. The zero-crossing point is determined directly by the proposed scheme, and the rotor magnetic position and rotor speed can be estimated simultaneously. Several experiments for various active angle periods are undertaken. Furthermore, a current feedback control is included to minimize and compensate the torque fluctuation. The experimental results show that the proposed method has a competitive performance compared with the conventional drive manners for BLACM. The proposed scheme is straightforward, bringing the benefits of sensor-less drive and negating the need for coordinate transformations in the operating process.

Fingerprint multicast in secure video streaming.

PubMed

Zhao, H Vicky; Liu, K J Ray

2006-01-01

Digital fingerprinting is an emerging technology to protect multimedia content from illegal redistribution, where each distributed copy is labeled with unique identification information. In video streaming, huge amount of data have to be transmitted to a large number of users under stringent latency constraints, so the bandwidth-efficient distribution of uniquely fingerprinted copies is crucial. This paper investigates the secure multicast of anticollusion fingerprinted video in streaming applications and analyzes their performance. We first propose a general fingerprint multicast scheme that can be used with most spread spectrum embedding-based multimedia fingerprinting systems. To further improve the bandwidth efficiency, we explore the special structure of the fingerprint design and propose a joint fingerprint design and distribution scheme. From our simulations, the two proposed schemes can reduce the bandwidth requirement by 48% to 87%, depending on the number of users, the characteristics of video sequences, and the network and computation constraints. We also show that under the constraint that all colluders have the same probability of detection, the embedded fingerprints in the two schemes have approximately the same collusion resistance. Finally, we propose a fingerprint drift compensation scheme to improve the quality of the reconstructed sequences at the decoder's side without introducing extra communication overhead.

Stable Short-Term Frequency Support Using Adaptive Gains for a DFIG-Based Wind Power Plant

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

Lee, Jinsik; Jang, Gilsoo; Muljadi, Eduard

For the fixed-gain inertial control of wind power plants (WPPs), a large gain setting provides a large contribution to supporting system frequency control, but it may cause over-deceleration for a wind turbine generator that has a small amount of kinetic energy (KE). Further, if the wind speed decreases during inertial control, even a small gain may cause over-deceleration. This paper proposes a stable inertial control scheme using adaptive gains for a doubly fed induction generator (DFIG)-based WPP. The scheme aims to improve the frequency nadir (FN) while ensuring stable operation of all DFIGs, particularly when the wind speed decreases duringmore » inertial control. In this scheme, adaptive gains are set to be proportional to the KE stored in DFIGs, which is spatially and temporally dependent. To improve the FN, upon detecting an event, large gains are set to be proportional to the KE of DFIGs; to ensure stable operation, the gains decrease with the declining KE. The simulation results demonstrate that the scheme improves the FN while ensuring stable operation of all DFIGs in various wind and system conditions. Further, it prevents over-deceleration even when the wind speed decreases during inertial control.« less

An improved fault detection classification and location scheme based on wavelet transform and artificial neural network for six phase transmission line using single end data only.

PubMed

Koley, Ebha; Verma, Khushaboo; Ghosh, Subhojit

2015-01-01

Restrictions on right of way and increasing power demand has boosted development of six phase transmission. It offers a viable alternative for transmitting more power, without major modification in existing structure of three phase double circuit transmission system. Inspite of the advantages, low acceptance of six phase system is attributed to the unavailability of a proper protection scheme. The complexity arising from large number of possible faults in six phase lines makes the protection quite challenging. The proposed work presents a hybrid wavelet transform and modular artificial neural network based fault detector, classifier and locator for six phase lines using single end data only. The standard deviation of the approximate coefficients of voltage and current signals obtained using discrete wavelet transform are applied as input to the modular artificial neural network for fault classification and location. The proposed scheme has been tested for all 120 types of shunt faults with variation in location, fault resistance, fault inception angles. The variation in power system parameters viz. short circuit capacity of the source and its X/R ratio, voltage, frequency and CT saturation has also been investigated. The result confirms the effectiveness and reliability of the proposed protection scheme which makes it ideal for real time implementation.

Recognition of three dimensional obstacles by an edge detection scheme. [for Mars roving vehicle using laser range finder

NASA Technical Reports Server (NTRS)

Reed, M. A.

1974-01-01

The need for an obstacle detection system on the Mars roving vehicle was assumed, and a practical scheme was investigated and simulated. The principal sensing device on this vehicle was taken to be a laser range finder. Both existing and original algorithms, ending with thresholding operations, were used to obtain the outlines of obstacles from the raw data of this laser scan. A theoretical analysis was carried out to show how proper value of threshold may be chosen. Computer simulations considered various mid-range boulders, for which the scheme was quite successful. The extension to other types of obstacles, such as craters, was considered. The special problems of bottom edge detection and scanning procedure are discussed.

Moving object detection using dynamic motion modelling from UAV aerial images.

PubMed

Saif, A F M Saifuddin; Prabuwono, Anton Satria; Mahayuddin, Zainal Rasyid

2014-01-01

Motion analysis based moving object detection from UAV aerial image is still an unsolved issue due to inconsideration of proper motion estimation. Existing moving object detection approaches from UAV aerial images did not deal with motion based pixel intensity measurement to detect moving object robustly. Besides current research on moving object detection from UAV aerial images mostly depends on either frame difference or segmentation approach separately. There are two main purposes for this research: firstly to develop a new motion model called DMM (dynamic motion model) and secondly to apply the proposed segmentation approach SUED (segmentation using edge based dilation) using frame difference embedded together with DMM model. The proposed DMM model provides effective search windows based on the highest pixel intensity to segment only specific area for moving object rather than searching the whole area of the frame using SUED. At each stage of the proposed scheme, experimental fusion of the DMM and SUED produces extracted moving objects faithfully. Experimental result reveals that the proposed DMM and SUED have successfully demonstrated the validity of the proposed methodology.

Performance analysis of EM-based blind detection for ON-OFF keying modulation over atmospheric optical channels

NASA Astrophysics Data System (ADS)

Dabiri, Mohammad Taghi; Sadough, Seyed Mohammad Sajad

2018-04-01

In the free-space optical (FSO) links, atmospheric turbulence lead to scintillation in the received signal. Due to its ease of implementation, intensity modulation with direct detection (IM/DD) based on ON-OFF keying (OOK) is a popular signaling scheme in these systems. Over turbulence channel, to detect OOK symbols in a blind way, i.e., without sending pilot symbols, an expectation-maximization (EM)-based detection method was recently proposed in the literature related to free-space optical (FSO) communication. However, the performance of EM-based detection methods severely depends on the length of the observation interval (Ls). To choose the optimum values of Ls at target bit error rates (BER)s of FSO communications which are commonly lower than 10-9, Monte-Carlo simulations would be very cumbersome and require a very long processing time. To facilitate performance evaluation, in this letter we derive the analytic expressions for BER and outage probability. Numerical results validate the accuracy of our derived analytic expressions. Our results may serve to evaluate the optimum value for Ls without resorting to time-consuming Monte-Carlo simulations.

High-speed detection of DNA translocation in nanopipettes.

PubMed

Fraccari, Raquel L; Ciccarella, Pietro; Bahrami, Azadeh; Carminati, Marco; Ferrari, Giorgio; Albrecht, Tim

2016-04-14

We present a high-speed electrical detection scheme based on a custom-designed CMOS amplifier which allows the analysis of DNA translocation in glass nanopipettes on a microsecond timescale. Translocation of different DNA lengths in KCl electrolyte provides a scaling factor of the DNA translocation time equal to p = 1.22, which is different from values observed previously with nanopipettes in LiCl electrolyte or with nanopores. Based on a theoretical model involving electrophoresis, hydrodynamics and surface friction, we show that the experimentally observed range of p-values may be the result of, or at least be affected by DNA adsorption and friction between the DNA and the substrate surface.

Analog nonlinear MIMO receiver for optical mode division multiplexing transmission.

PubMed

Spalvieri, Arnaldo; Boffi, Pierpaolo; Pecorino, Simone; Barletta, Luca; Magarini, Maurizio; Gatto, Alberto; Martelli, Paolo; Martinelli, Mario

2013-10-21

The complexity and the power consumption of digital signal processing are crucial issues in optical transmission systems based on mode division multiplexing and coherent multiple-input multiple-output (MIMO) processing at the receiver. In this paper the inherent characteristic of spatial separation between fiber modes is exploited, getting a MIMO system where joint demultiplexing and detection is based on spatially separated photodetectors. After photodetection, one has a MIMO system with nonlinear crosstalk between modes. The paper shows that the nonlinear crosstalk can be dealt with by a low-complexity and non-adaptive detection scheme, at least in the cases presented in the paper.

Efficient entanglement distribution over 200 kilometers.

PubMed

Dynes, J F; Takesue, H; Yuan, Z L; Sharpe, A W; Harada, K; Honjo, T; Kamada, H; Tadanaga, O; Nishida, Y; Asobe, M; Shields, A J

2009-07-06

Here we report the first demonstration of entanglement distribution over a record distance of 200 km which is of sufficient fidelity to realize secure communication. In contrast to previous entanglement distribution schemes, we use detection elements based on practical avalanche photodiodes (APDs) operating in a self-differencing mode. These APDs are low-cost, compact and easy to operate requiring only electrical cooling to achieve high single photon detection efficiency. The self-differencing APDs in combination with a reliable parametric down-conversion source demonstrate that entanglement distribution over ultra-long distances has become both possible and practical. Consequently the outlook is extremely promising for real world entanglement-based communication between distantly separated parties.

Comparison of Respiratory Disease Prevalence among Voluntary Monitoring Systems for Pig Health and Welfare in the UK.

PubMed

Eze, J I; Correia-Gomes, C; Borobia-Belsué, J; Tucker, A W; Sparrow, D; Strachan, D W; Gunn, G J

2015-01-01

Surveillance of animal diseases provides information essential for the protection of animal health and ultimately public health. The voluntary pig health schemes, implemented in the United Kingdom, are integrated systems which capture information on different macroscopic disease conditions detected in slaughtered pigs. Many of these conditions have been associated with a reduction in performance traits and consequent increases in production costs. The schemes are the Wholesome Pigs Scotland in Scotland, the BPEX Pig Health Scheme in England and Wales and the Pig Regen Ltd. health and welfare checks done in Northern Ireland. This report set out to compare the prevalence of four respiratory conditions (enzootic pneumonia-like lesions, pleurisy, pleuropneumonia lesions and abscesses in the lung) assessed by these three Pig Health Schemes. The seasonal variations and year trends associated with the conditions in each scheme are presented. The paper also highlights the differences in prevalence for each condition across these schemes and areas where further research is needed. A general increase in the prevalence of enzootic pneumonia like lesions was observed in Scotland, England and Wales since 2009, while a general decrease was observed in Northern Ireland over the years of the scheme. Pleurisy prevalence has increased since 2010 in all three schemes, whilst pleuropneumonia has been decreasing. Prevalence of abscesses in the lung has decreased in England, Wales and Northern Ireland but has increased in Scotland. This analysis highlights the value of surveillance schemes based on abattoir pathology monitoring of four respiratory lesions. The outputs at scheme level have significant value as indicators of endemic and emerging disease, and for producers and herd veterinarians in planning and evaluating herd health control programs when comparing individual farm results with national averages.