Search results for: signal detection

Authors: Bhaskar Thakker, Anoop Lal Vyas

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Wrist pulse analysis for identification of health status is found in Ancient Indian as well as Chinese literature. The preprocessing of wrist pulse is necessary to remove outlier pulses and fluctuations prior to the analysis of pulse pressure signal. This paper discusses the identification of irregular pulses present in the pulse series and intricacies associated with the extraction of time domain pulse features. An approach of Dynamic Time Warping (DTW) has been utilized for the identification of outlier pulses in the wrist pulse series. The ambiguity present in the identification of pulse features is resolved with the help of first derivative of Ensemble Average of wrist pulse series. An algorithm for detecting tidal and dicrotic notch in individual wrist pulse segment is proposed.

Keywords: Wrist Pulse Segment, Ensemble Average, Dynamic Time Warping (DTW), Pulse Similarity Vector.

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Authors: Fernando C. Monteiro, Vasco Cadavez

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This paper presents a method for the detection of OD in the retina which takes advantage of the powerful preprocessing techniques such as the contrast enhancement, Gabor wavelet transform for vessel segmentation, mathematical morphology and Earth Mover-s distance (EMD) as the matching process. The OD detection algorithm is based on matching the expected directional pattern of the retinal blood vessels. Vessel segmentation method produces segmentations by classifying each image pixel as vessel or nonvessel, based on the pixel-s feature vector. Feature vectors are composed of the pixel-s intensity and 2D Gabor wavelet transform responses taken at multiple scales. A simple matched filter is proposed to roughly match the direction of the vessels at the OD vicinity using the EMD. The minimum distance provides an estimate of the OD center coordinates. The method-s performance is evaluated on publicly available DRIVE and STARE databases. On the DRIVE database the OD center was detected correctly in all of the 40 images (100%) and on the STARE database the OD was detected correctly in 76 out of the 81 images, even in rather difficult pathological situations.

Keywords: Diabetic retinopathy, Earth Mover's distance, Gabor wavelets, optic disc detection, retinal images

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Authors: Wen W. Zhang, Qian Chen

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Electron multiplying charge coupled devices (EMCCDs) have revolutionized the world of low light imaging by introducing on-chip multiplication gain based on the impact ionization effect in the silicon. They combine the sub-electron readout noise with high frame rates. Signal-to-noise Ratio (SNR) is an important performance parameter for low-light-level imaging systems. This work investigates the SNR performance of an EMCCD operated in Non-inverted Mode (NIMO) and Inverted Mode (IMO). The theory of noise characteristics and operation modes is presented. The results show that the SNR of is determined by dark current and clock induced charge at high gain level. The optimum SNR performance is provided by an EMCCD operated in NIMO in short exposure and strong cooling applications. In contrast, an IMO EMCCD is preferable.

Keywords: electron multiplying charge coupled devices, noise characteristics, operation modes, signal-to-noise ratioperformance

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Authors: Siddhant Rao

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Studies estimate that there will be 266,120 new cases of invasive breast cancer and 40,920 breast cancer induced deaths in the year of 2018 alone. Despite the pervasiveness of this affliction, the current process to obtain an accurate breast cancer prognosis is tedious and time consuming. It usually requires a trained pathologist to manually examine histopathological images and identify the features that characterize various cancer severity levels. We propose MITOS-RCNN: a region based convolutional neural network (RCNN) geared for small object detection to accurately grade one of the three factors that characterize tumor belligerence described by the Nottingham Grading System: mitotic count. Other computational approaches to mitotic figure counting and detection do not demonstrate ample recall or precision to be clinically viable. Our models outperformed all previous participants in the ICPR 2012 challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14 challenge along with recently published works. Our model achieved an F- measure score of 0.955, a 6.11% improvement in accuracy from the most accurate of the previously proposed models.

Keywords: Object detection, histopathology, breast cancer, mitotic count, deep learning, computer vision.

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Authors: H. Mhamdi, N. Hamrouni, A. Temimi, M. Bouhlel

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In this article, we expose our research work in Human-machine Interaction. The research consists in manipulating the workspace by eyes. We present some of our results, in particular the detection of eyes and the mouse actions recognition. Indeed, the handicaped user becomes able to interact with the machine in a more intuitive way in diverse applications and contexts. To test our application we have chooses to work in real time on videos captured by a camera placed in front of the user.

Keywords: Computer vision, Face and Eyes Detection, Mouse pointer recognition.

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Authors: Juan Li, Chunfu Shao, Chunjiao Dong, Dan Zhao, Yinhong Liu

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Mixed-traffic (e.g., pedestrians, bicycles, and vehicles) data at an intersection is one of the essential factors for intersection design and traffic control. However, some data such as pedestrian volume cannot be directly collected by common detectors (e.g. inductive loop, sonar and microwave sensors). In this paper, a video based detection algorithm is proposed for mixed-traffic data collection at intersections using surveillance cameras. The algorithm is derived from Gaussian Mixture Model (GMM), and uses a mergence time adjustment scheme to improve the traditional algorithm. Real-world video data were selected to test the algorithm. The results show that the proposed algorithm has the faster processing speed and more accuracy than the traditional algorithm. This indicates that the improved algorithm can be applied to detect mixed-traffic at signalized intersection, even when conflicts occur.

Keywords: detection, intersection, mixed traffic, moving objects.

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Authors: C. P. Providakis, G. M. Angeli, M. J. Favvata, N. A. Papadopoulos, C. E. Chalioris, C. G. Karayannis

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An effort for the detection of damages in the  reinforcement bars of reinforced concrete members using PZTs is  presented. The damage can be the result of excessive elongation of  the steel bar due to steel yielding or due to local steel corrosion. In  both cases the damage is simulated by considering reduced diameter  of the rebar along the damaged part of its length. An integration  approach based on both electromechanical admittance methodology  and guided wave propagation technique is used to evaluate the  artificial damage on the examined longitudinal steel bar. Two  actuator PZTs and a sensor PZT are considered to be bonded on the  examined steel bar. The admittance of the Sensor PZT is calculated  using COMSOL 3.4a. Fast Furrier Transformation for a better  evaluation of the results is employed. An effort for the quantification  of the damage detection using the root mean square deviation  (RMSD) between the healthy condition and damage state of the  sensor PZT is attempted. The numerical value of the RSMD yields a  level for the difference between the healthy and the damaged  admittance computation indicating this way the presence of damage  in the structure. Experimental measurements are also presented.

 

Keywords: Concrete reinforcement, damage detection, electromechanical admittance, experimental measurements, finite element method, guided waves, PZT.

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Authors: Shaoying Guo, Yanyun Xu, Meng Zhang, Weiqing Huang

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The wireless communication network is developing rapidly, thus the wireless security becomes more and more important. Specific emitter identification (SEI) is an vital part of wireless communication security as a technique to identify the unique transmitters. In this paper, a SEI method based on multiscale dispersion entropy (MDE) and refined composite multiscale dispersion entropy (RCMDE) is proposed. The algorithms of MDE and RCMDE are used to extract features for identification of five wireless devices and cross-validation support vector machine (CV-SVM) is used as the classifier. The experimental results show that the total identification accuracy is 99.3%, even at low signal-to-noise ratio(SNR) of 5dB, which proves that MDE and RCMDE can describe the communication signal series well. In addition, compared with other methods, the proposed method is effective and provides better accuracy and stability for SEI.

Keywords: Cross-validation support vector machine, refined composite multiscale dispersion entropy, specific emitter identification, transient signal, wireless communication device.

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Authors: Jessie Yiying Quah, Vivian Netto, Jack Sheng Kee, Eric Mouchel La Fosse, Mi Kyoung Park

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We present a dextran modified silicon microring resonator sensor for high density antibody immobilization. An array of sensors consisting of three sensor rings and a reference ring was fabricated and its surface sensitivity and the limit of detection were obtained using polyelectrolyte multilayers. The mass sensitivity and the limit of detection of the fabricated sensor ring are 0.35 nm/ng mm-2 and 42.8 pg/mm2 in air, respectively. Dextran modified sensor surface was successfully prepared by covalent grafting of oxidized dextran on 3-aminopropyltriethoxysilane (APTES) modified silicon sensor surface. The antibody immobilization on hydrogel dextran matrix improves 40% compared to traditional antibody immobilization method via APTES and glutaraldehyde linkage.

Keywords: Antibody immobilization, Dextran, Immunosensor, Label-free detection, Silicon micro-ring resonator

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Authors: Neda Navidi, Rene Jr. Landry

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Vehicle tracking and accident recognizing are considered by many industries like insurance and vehicle rental companies. The main goal of this paper is to detect the location of a car accident by combining different methods. The methods, which are considered in this paper, are Global Navigation Satellite Systems/Inertial Measurement Units (GNSS/IMU)-based navigation and vehicle accident detection algorithms. They are expressed by a set of raw measurements, which are obtained from a designed integrator black box using GNSS and inertial sensors. Another concern of this paper is the definition of accident detection algorithm based on its jerk to identify the position of that accident. In fact, the results convinced us that, even in GNSS blockage areas, the position of the accident could be detected by GNSS/INS integration with 50% improvement compared to GNSS stand alone.

Keywords: Driving behavior, integration, IMU, GNSS, monitoring, tracking.

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Authors: S. Korkut, M. S. Kilic, E. Erhan

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In order to detect and quantify the phenolic contents of a wastewater with biosensors, two working electrodes based on modified Poly(Pyrrole) films were fabricated. Enzyme horseradish peroxidase was used as biomolecule of the prepared electrodes. Various phenolics were tested at the biosensor. Phenol detection was realized by electrochemical reduction of quinones produced by enzymatic activity. Analytical parameters were calculated and the results were compared with each other.

Keywords: Carbon nanotube, Phenol biosensor, Polypyrrole, Poly(glutaraldehyde).

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Authors: A. Nachour, L. Ouzizi, Y. Aoura

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Recent developments on multi-agent system have brought a new research field on image processing. Several algorithms are used simultaneously and improved in deferent applications while new methods are investigated. This paper presents a new automatic method for edge detection using several agents and many different actions. The proposed multi-agent system is based on parallel agents that locally perceive their environment, that is to say, pixels and additional environmental information. This environment is built using Vector Field Convolution that attract free agent to the edges. Problems of partial, hidden or edges linking are solved with the cooperation between agents. The presented method was implemented and evaluated using several examples on different synthetic and medical images. The obtained experimental results suggest that this approach confirm the efficiency and accuracy of detected edge.

Keywords: Edge detection, medical MR images, multi-agent systems, vector field convolution.

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Authors: Niloofar Yousefi, Marie Alaghband, Ivan Garibay

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With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Keywords: credit card fraud detection, user authentication, behavioral biometrics, machine learning, literature survey

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Authors: Hamidullah Binol, Abdullah Bal

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Nowadays, food safety is a great public concern; therefore, robust and effective techniques are required for detecting the safety situation of goods. Hyperspectral Imaging (HSI) is an attractive material for researchers to inspect food quality and safety estimation such as meat quality assessment, automated poultry carcass inspection, quality evaluation of fish, bruise detection of apples, quality analysis and grading of citrus fruits, bruise detection of strawberry, visualization of sugar distribution of melons, measuring ripening of tomatoes, defect detection of pickling cucumber, and classification of wheat kernels. HSI can be used to concurrently collect large amounts of spatial and spectral data on the objects being observed. This technique yields with exceptional detection skills, which otherwise cannot be achieved with either imaging or spectroscopy alone. This paper presents a nonlinear technique based on kernel Fukunaga-Koontz transform (KFKT) for detection of fat content in ground meat using HSI. The KFKT which is the nonlinear version of FKT is one of the most effective techniques for solving problems involving two-pattern nature. The conventional FKT method has been improved with kernel machines for increasing the nonlinear discrimination ability and capturing higher order of statistics of data. The proposed approach in this paper aims to segment the fat content of the ground meat by regarding the fat as target class which is tried to be separated from the remaining classes (as clutter). We have applied the KFKT on visible and nearinfrared (VNIR) hyperspectral images of ground meat to determine fat percentage. The experimental studies indicate that the proposed technique produces high detection performance for fat ratio in ground meat.

Keywords: Food (Ground meat) inspection, Fukunaga-Koontz transform, hyperspectral imaging, kernel methods.

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Authors: Priyanka Chaudhary, M. Rizwan

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This paper presents a grid synchronization technique based on adaptive notch filter for SPV (Solar Photovoltaic) system along with MPPT (Maximum Power Point Tracking) techniques. An efficient grid synchronization technique offers proficient detection of various components of grid signal like phase and frequency. It also acts as a barrier for harmonics and other disturbances in grid signal. A reference phase signal synchronized with the grid voltage is provided by the grid synchronization technique to standardize the system with grid codes and power quality standards. Hence, grid synchronization unit plays important role for grid connected SPV systems. As the output of the PV array is fluctuating in nature with the meteorological parameters like irradiance, temperature, wind etc. In order to maintain a constant DC voltage at VSC (Voltage Source Converter) input, MPPT control is required to track the maximum power point from PV array. In this work, a variable step size P & O (Perturb and Observe) MPPT technique with DC/DC boost converter has been used at first stage of the system. This algorithm divides the dPpv/dVpv curve of PV panel into three separate zones i.e. zone 0, zone 1 and zone 2. A fine value of tracking step size is used in zone 0 while zone 1 and zone 2 requires a large value of step size in order to obtain a high tracking speed. Further, adaptive notch filter based control technique is proposed for VSC in PV generation system. Adaptive notch filter (ANF) approach is used to synchronize the interfaced PV system with grid to maintain the amplitude, phase and frequency parameters as well as power quality improvement. This technique offers the compensation of harmonics current and reactive power with both linear and nonlinear loads. To maintain constant DC link voltage a PI controller is also implemented and presented in this paper. The complete system has been designed, developed and simulated using SimPower System and Simulink toolbox of MATLAB. The performance analysis of three phase grid connected solar photovoltaic system has been carried out on the basis of various parameters like PV output power, PV voltage, PV current, DC link voltage, PCC (Point of Common Coupling) voltage, grid voltage, grid current, voltage source converter current, power supplied by the voltage source converter etc. The results obtained from the proposed system are found satisfactory.

Keywords: Solar photovoltaic systems, MPPT, voltage source converter, grid synchronization technique.

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Authors: Vahid Khorramshahi, Alireza Behrad, Neeraj K. Kanhere

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In this paper we present a new method for over-height vehicle detection in low headroom streets and highways using digital video possessing. The accuracy and the lower price comparing to present detectors like laser radars and the capability of providing extra information like speed and height measurement make this method more reliable and efficient. In this algorithm the features are selected and tracked using KLT algorithm. A blob extraction algorithm is also applied using background estimation and subtraction. Then the world coordinates of features that are inside the blobs are estimated using a noble calibration method. As, the heights of the features are calculated, we apply a threshold to select overheight features and eliminate others. The over-height features are segmented using some association criteria and grouped using an undirected graph. Then they are tracked through sequential frames. The obtained groups refer to over-height vehicles in a scene.

Keywords: Feature extraction, over-height vehicle detection, traffic monitoring, vehicle tracking.

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Authors: S. Seyedtabaii, L. Seyedtabaii

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Artifact free photoplethysmographic (PPG) signals are necessary for non-invasive estimation of oxygen saturation (SpO2) in arterial blood. Movement of a patient corrupts the PPGs with motion artifacts, resulting in large errors in the computation of Sp02. This paper presents a study on using Kalman Filter in an innovative way by modeling both the Artillery Blood Pressure (ABP) and the unwanted signal, additive motion artifact, to reduce motion artifacts from corrupted PPG signals. Simulation results show acceptable performance regarding LMS and variable step LMS, thus establishing the efficacy of the proposed method.

Keywords: Kalman filter, Motion artifact, PPG, Photoplethysmography.

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Authors: Khin Thandar Lwin, Than Htike, Zaw Min Naing

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This paper introduces an intelligent system, which can be applied in the monitoring of vehicle speed using a single camera. The ability of motion tracking is extremely useful in many automation problems and the solution to this problem will open up many future applications. One of the most common problems in our daily life is the speed detection of vehicles on a highway. In this paper, a novel technique is developed to track multiple moving objects with their speeds being estimated using a sequence of video frames. Field test has been conducted to capture real-life data and the processed results were presented. Multiple object problems and noisy in data are also considered. Implementing this system in real-time is straightforward. The proposal can accurately evaluate the position and the orientation of moving objects in real-time. The transformations and calibration between the 2D image and the actual road are also considered.

Keywords: Motion Estimation, Image Analyses, Speed Detection

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Authors: Einalou Z., Najafi Z., Maghooli K. Zandi Y, Sheibeigi A

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In this study, an investigation over digestive diseases has been done in which the sound acts as a detector medium. Pursue to the preprocessing the extracted signal in cepstrum domain is registered. After classification of digestive diseases, the system selects random samples based on their features and generates the interest nonstationary, long-term signals via inverse transform in cepstral domain which is presented in digital and sonic form as the output. This structure is updatable or on the other word, by receiving a new signal the corresponding disease classification is updated in the feature domain.

Keywords: Cepstrum, databank, digestive disease, acousticsignal.

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Authors: Salwa Hagag Abdelaziz, Dorria Salem, Hoda Zaki, Suzan Atteya

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Early detection of breast cancer saves many thousands of lives each year via application of mammography and genetic screening and many more lives could be saved if nurses are involved in breast care screening practices. So, the aim of the study was to identify nurse's role in early detection of breast cancer through mammography and genetic screening and its impact on patient's outcome. In order to achieve this aim, 400 women above 40 years, asymptomatic were recruited for mammography and genetic screening. In addition, 50 nurses and 6 technologists were involved in the study. A descriptive analytical design was used. Five tools were utilized: sociodemographic, mammographic examination and risk factors, women's before, during and after mammography, items relaying to technologists, and items related to nurses were also obtained. The study finding revealed that 3% of women detected for malignancy and 7.25% for fibroadenoma. Statistically significant differences were found between mammography results and age, family history, genetic screening, exposure to smoke, and using contraceptive pills. Nurses have insufficient knowledge about screening tests. Based on these findings the present study recommended involvement of nurses in breast care which is very important to in force population about screening practices.

Keywords: Early detection, Genetic Screening, Mammography.

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Authors: S Hariharan, K Chaitanya, P Muthuchidambaranathan

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The IEEE 802.22 working group aims to drive the Digital Video Broadcasting-Terrestrial (DVB-T) bands for data communication to the rural area without interfering the TV broadcast. In this paper, we arrive at a closed-form expression for average detection probability of Fusion center (FC) with multiple antenna over the κ − μ fading channel model. We consider a centralized cooperative multiple antenna network for reporting. The DVB-T samples forwarded by the secondary user (SU) were combined using Maximum ratio combiner at FC, an energy detection is performed to make the decision. The fading effects of the channel degrades the detection probability of the FC, a generalized independent and identically distributed (IID) κ − μ and an additive white Gaussian noise (AWGN) channel is considered for reporting and sensing respectively. The proposed system performance is verified through simulation results.

Keywords: IEEE 802.22, Cooperative spectrum sensing, Multiple antenna, κ − μ .

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Authors: Ahmad Manbohi, Seyyed Hamid Ahmadi

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A low-cost paper-based microfluidic device (PAD) for the multiplex electrochemical determination of glucose, uric acid, and dopamine in biological fluids was developed. Using wax printing, PAD containing a central zone, six channels, and six detection zones was fabricated, and the electrodes were printed on detection zones using pre-made electrodes template. For each analyte, two detection zones were used. The carbon working electrode was coated with chitosan-BSA (and enzymes for glucose and uric acid). To detect glucose and uric acid, enzymatic reactions were employed. These reactions involve enzyme-catalyzed redox reactions of the analytes and produce free electrons for electrochemical measurement. Calibration curves were linear (R^² > 0.980) in the range of 0-80 mM for glucose, 0.09–0.9 mM for dopamine, and 0–50 mM for uric acid, respectively. Blood samples were successfully analyzed by the proposed method.

Keywords: Multiplex, microfluidic paper-based electrochemical biosensors, biomarkers, biological fluids.

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Authors: Ying-Chuan Chen, Shuen-Tai Wang

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Security is an interesting and significance issue for popular virtual platforms, such as virtualization cluster and cloud platforms. Virtualization is the powerful technology for cloud computing services, there are a lot of benefits by using virtual machine tools which be called hypervisors, such as it can quickly deploy all kinds of virtual Operating Systems in single platform, able to control all virtual system resources effectively, cost down for system platform deployment, ability of customization, high elasticity and high reliability. However, some important security problems need to take care and resolved in virtual platforms that include terrible viruses, evil programs, illegal operations and intrusion behavior. In this paper, we present useful Intrusion Detection Mechanism (IDM) software that not only can auto to analyze all system-s operations with the accounting journal database, but also is able to monitor the system-s state for virtual platforms.

Keywords: security, cluster, cloud, virtualization, virtual machine, virus, intrusion detection

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Authors: Benjamin Y. M. Kwan, Hon Keung Kwan

Abstract:

Early detection of lung cancer through chest radiography is a widely used method due to its relatively affordable cost. In this paper, an approach to improve lung nodule visualization on chest radiographs is presented. The approach makes use of linear phase high-frequency emphasis filter for digital filtering and histogram equalization for contrast enhancement to achieve improvements. Results obtained indicate that a filtered image can reveal sharper edges and provide more details. Also, contrast enhancement offers a way to further enhance the global (or local) visualization by equalizing the histogram of the pixel values within the whole image (or a region of interest). The work aims to improve lung nodule visualization of chest radiographs to aid detection of lung cancer which is currently the leading cause of cancer deaths worldwide.

Keywords: Chest radiographs, Contrast enhancement, Digital filtering, Lung nodule detection

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Authors: Priyadarshinee Adhikari, Neeta Gargote, Jyothi Digge, B.G. Hogade

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A number of automated shot-change detection methods for indexing a video sequence to facilitate browsing and retrieval have been proposed in recent years. This paper emphasizes on the simulation of video shot boundary detection using one of the methods of the color histogram wherein scaling of the histogram metrics is an added feature. The difference between the histograms of two consecutive frames is evaluated resulting in the metrics. Further scaling of the metrics is performed to avoid ambiguity and to enable the choice of apt threshold for any type of videos which involves minor error due to flashlight, camera motion, etc. Two sample videos are used here with resolution of 352 X 240 pixels using color histogram approach in the uncompressed media. An attempt is made for the retrieval of color video. The simulation is performed for the abrupt change in video which yields 90% recall and precision value.

Keywords: Abrupt change, color histogram, ground-truthing, precision, recall, scaling, threshold.

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Authors: Oi Mean Foong, Tan Jung Low, Satrio Wibowo

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Hand gesture is one of the typical methods used in sign language for non-verbal communication. It is most commonly used by people who have hearing or speech problems to communicate among themselves or with normal people. Various sign language systems have been developed by manufacturers around the globe but they are neither flexible nor cost-effective for the end users. This paper presents a system prototype that is able to automatically recognize sign language to help normal people to communicate more effectively with the hearing or speech impaired people. The Sign to Voice system prototype, S2V, was developed using Feed Forward Neural Network for two-sequence signs detection. Different sets of universal hand gestures were captured from video camera and utilized to train the neural network for classification purpose. The experimental results have shown that neural network has achieved satisfactory result for sign-to-voice translation.

Keywords: Hand gesture detection, neural network, signlanguage, sequence detection.

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Authors: Junghwan Choi, Seongsoo Lee

Abstract:

Histogram equalization is often used in image enhancement, but it can be also used in auto exposure. However, conventional histogram equalization does not work well when many pixels are concentrated in a narrow luminance range.This paper proposes an auto exposure method based on 2-way histogram equalization. Two cumulative distribution functions are used, where one is from dark to bright and the other is from bright to dark. In this paper, the proposed auto exposure method is also designed and implemented for image signal processors with full-HD images.

Keywords: Histogram equalization, Auto exposure, Image signal processor, Low-cost, Full HD Video.

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Authors: Sangbum Park, Namki Lee, Youngjoon Han, Hernsoo Hahn

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In this paper, we propose the robust water level detection method based on the accumulated histogram under small changed image which is acquired from water level surveillance camera. In general surveillance system, this is detecting and recognizing invasion from searching area which is in big change on the sequential images. However, in case of a water level detection system, these general surveillance techniques are not suitable due to small change on the water surface. Therefore the algorithm introduces the accumulated histogram which is emphasizing change of water surface in sequential images. Accumulated histogram is based on the current image frame. The histogram is cumulating differences between previous images and current image. But, these differences are also appeared in the land region. The band pass filter is able to remove noises in the accumulated histogram Finally, this algorithm clearly separates water and land regions. After these works, the algorithm converts from the water level value on the image space to the real water level on the real space using calibration table. The detected water level is sent to the host computer with current image. To evaluate the proposed algorithm, we use test images from various situations.

Keywords: accumulated histogram, water level detection, band pass filter.

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Authors: Abu Salim Mustafa

Abstract:

Polymerase chain reaction (PCR) assays targeting genomic DNA segments have been established for the detection of Helicobacter pylori in clinical specimens. However, the data on comparative evaluations of various targets in detection of H. pylori are limited. Furthermore, the frequencies of vacA (s1 and s2) and cagA genotypes, which are suggested to be involved in the pathogenesis of H. pylori in other parts of the world, are not well studied in Kuwait. The aim of this study was to evaluate PCR assays for the detection and genotyping of H. pylori by targeting the amplification of DNA targets from four genomic segments. The genomic DNA were isolated from 72 clinical isolates of H. pylori and tested in PCR with four pairs of oligonucleotides primers, i.e. ECH-U/ECH-L, ET-5U/ET-5L, CagAF/CagAR and Vac1F/Vac1XR, which were expected to amplify targets of various sizes (471 bp, 230 bp, 183 bp and 176/203 bp, respectively) from the genomic DNA of H. pylori. The PCR-amplified DNA were analyzed by agarose gel electrophoresis. PCR products of expected size were obtained with all primer pairs by using genomic DNA isolated from H. pylori. DNA dilution experiments showed that the most sensitive PCR target was 471 bp DNA amplified by the primers ECH-U/ECH-L, followed by the targets of Vac1F/Vac1XR (176 bp/203 DNA), CagAF/CagAR (183 bp DNA) and ET-5U/ET-5L (230 bp DNA). However, when tested with undiluted genomic DNA isolated from single colonies of all isolates, the Vac1F/Vac1XR target provided the maximum positive results (71/72 (99% positives)), followed by ECH-U/ECH-L (69/72 (93% positives)), ET-5U/ET-5L (51/72 (71% positives)) and CagAF/CagAR (26/72 (46% positives)). The results of genotyping experiments showed that vacA s1 (46% positive) and vacA s2 (54% positive) genotypes were almost equally associated with VaCA+/CagA- isolates (P > 0.05), but with VacA+/CagA+ isolates, S1 genotype (92% positive) was more frequently detected than S2 genotype (8% positive) (P< 0.0001). In conclusion, among the primer pairs tested, Vac1F/Vac1XR provided the best results for detection of H. pylori. The genotyping experiments showed that vacA s1 and vacA s2 genotypes were almost equally associated with vaCA⁺/cagA^- isolates, but vacA s1 genotype had a significantly increased association with vacA⁺/cagA⁺ isolates.

Keywords: H. pylori, detection, genotyping, Kuwait.

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Authors: Shyama Ranjani Weerakoon

Abstract:

Direct and indirect somatic embryogenesis (SE) from petiole and leaf explants of Scaevola aemula R. Br. cv. 'Purple Fanfare' was achieved. High frequency of somatic embryos was obtained directly from petiole and leaf explants using an inductive plant growth regulator signal thidiazuron (TDZ). Petiole explants were more responsive to SE than leaves. Plants derived from somatic embryos of petiole explants germinated more readily into plants. SE occurred more efficiently in half-strength Murashige and Skoog (MS) medium than in full-strength MS medium. Non-embryogenic callus induced by 2, 4-dichlorophenoxyacetic acid was used to investigate the feasibility of obtaining SE with TDZ as a secondary inductive plant growth regulator (PGR) signal. Non-embryogenic callus of S. aemula was able to convert into an “embryogenic competent mode" with PGR signal. Protocol developed for induction of direct and indirect somatic embryogenesis in S. aemula can improve the large scale propagation system of the plant in future.

Keywords: Petiole and leaf explants, Scaevola aemula, Somaticembryogenesis

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