Search results for: Detect

Authors: Saeid Jalilzadeh, Majid Pakdel

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The customer demand for better power quality and higher reliability has forced the power industry to use distributed generations (DGs) such as wind power and photo voltaic arrays. Islanding is a phenomenon occurs when a power grid becomes electrically isolated from the power system and the distribution system is energized by distributed generators. It is necessary to disconnect all distributed generators immediately after islanding occurrence. Therefore a DG system should have the capability to detect islanding phenomena. In this paper, a novel micro controller based relay for anti-islanding protection of a typical DG system is proposed. The simulation results using Proteus software verify the proper operation and effectiveness of the proposed protective relay.

Keywords: islanding, distributed generation (DG), protective relay, micro controller, proteus software

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Authors: G. Usha, S. Kannimuthu, K. Mahalakshmi

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Mobile Adhoc Network (MANET) is one of the most promising technologies that have applications ranging from various portable devices to military networks. MANET has no fixed infrastructure and the security of such network is a big concern. Therefore, in order to operate MANET’s securely, the misbehavior and intrusions should be detected before the attackers affect the network communication. In this article, we make a comprehensive survey against black hole attack that is a serious threat against MANET that exploits the routing behavior of the MANET. We have given broad survey solutions that detect black hole attacks in MANET. This is achieved by analyzing the techniques involved in detecting the attacks in each scheme. Furthermore, we examine about the challenges to the researchers for constructing an in-depth solution against black hole attack.

Keywords: AODV, cross layer security, mobile Adhoc network (MANET), packet delivery ratio, single layer security

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Authors: Zhongjie Yu, Hancheng Yu

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In this paper, we propose an effective method to detect concentric circles with imperfect edges. First, the gradient of edge pixel is coded and a 2-D lookup table is built to speed up normal generation. Then we take an accumulator to estimate the rough center and collect plausible edges of concentric circles through gradient and distance. Later, we take the contour-based method, which takes the contour and edge intersection, to pre-classify the edges. Finally, we use the extended RANSAC method to find all the candidate circles. The center of concentric circles is determined by the two circles with the highest concentricity. Experimental results demonstrate that the proposed method has both good performance and accuracy for the detection of concentric circles.

Keywords: concentric circle detection, gradient, contour, edge pre-classification, RANSAC

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Authors: F. A. Al-Awadhi, D. Al-Hulail

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In this study, we applied the Bayesian hierarchical model to detect single and multiple change points for daily earthquake body wave magnitude. The change point analysis is used in both backward (off-line) and forward (on-line) statistical research. In this study, it is used with the backward approach. Different types of change parameters are considered (mean, variance or both). The posterior model and the conditional distributions for single and multiple change points are derived and implemented using BUGS software. The model is applicable for any set of data. The sensitivity of the model is tested using different prior and likelihood functions. Using Mb data, we concluded that during January 2002 and December 2003, three changes occurred in the mean magnitude of Mb in Kuwait and its vicinity.

Keywords: multiple change points, Markov Chain Monte Carlo, earthquake magnitude, hierarchical Bayesian mode

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Authors: Hela Ghali, Sihem Ben Fredj, Mohamed Ben Rejeb, Sawssen Layouni, Salwa Khefacha, Lamine Dhidah, Houyem Said Laatiri

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Background: Antimicrobial resistance is a growing threat to public health and motivates to improve prevention and control programs both at international (WHO) and national levels. Despite their low pathogenicity, vancomycin-resistant enterococci (VRE) are common nosocomial pathogens in several countries. The high potential for transmission of VRE between patients and the threat to send its resistance genes to other bacteria such as staphylococcus aureus already resistant to meticilin, justify strict control measures. Indeed, in Europe, the proportion of Enterococcus faecium responsible for invasive infections, varies from 1% to 35% in 2011 and less than 5% were resistant to vancomycin. In addition, it represents the second cause of urinary tract and wound infections and the third cause of nosocomial bacteremia in the United States. The nosocomial outbreaks of VRE have been mainly described in intensive care services, hematology-oncology and haemodialysis. An epidemic of VRE has affected our hospital and the objective of this work is to describe the measures put in place. Materials/Methods: Following the alert given by the service of plastic surgery concerning a patient carrier of VRE, a team of the prevention and healthcare security service (doctor + technician) made an investigation. A review of files was conducted to draw the synoptic table and the table of cases. Results: By contacting the microbiology laboratory, we have identified four other cases of VRE and who were hospitalized in Medical resuscitation department (2 cases, one of them was transferred to the Physical rehabilitation department), and Nephrology department (2 cases). The visit has allowed to detect several malfunctions in professional practice. A crisis cell has allowed to validate, coordinate and implement control measures following the recommendations of the Technical Center of nosocomial infections. In fact, the process was to technically isolate cases in their sector of hospitalization, to restrict the use of antibiotics, to strength measures of basic hygiene, and to make a screening by rectal swab for both cases and contacts (other patients and health staff). These measures have helped to control the situation and no other case has been reported for a month. 2 new cases have been detected in the intensive care unit after a month. However, these are short-term strategies, and other measures in the medium and long term should be taken into account in order to face similar outbreaks. Conclusion: The efforts to control the outbreak were not efficient since 2 new cases have been reported after a month. Therefore, a continuous monitoring in order to detect new cases earlier is crucial to minimize the dissemination of VRE.

Keywords: hospitals, nosocomial infection, outbreak, vancomycin-resistant enterococci

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Authors: Diego Rodrigues, Marcelo Lisboa, Elismar Batista, Marcos Dias

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Based on data on child labor, this work arises questions about how to understand and locate the factors that make up the child labor rates, and which properties are important to analyze these cases. Using data mining techniques to discover valid patterns on Brazilian social databases were evaluated data of child labor in the State of Tocantins (located north of Brazil with a territory of 277000 km2 and comprises 139 counties). This work aims to detect factors that are deterministic for the practice of child labor and their relationships with financial indicators, educational, regional and social, generating information that is not explicit in the government database, thus enabling better monitoring and updating policies for this purpose.

Keywords: social data, government decision making, association of social data, data mining

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Authors: Nour Charara, Hussein Charara, Omar Abou Khaled, Hani Abdallah, Elena Mugellini

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In this paper, we present a human behavior modeling approach in videos scenes. This approach is used to model the normal behaviors in the conference halls. We exploited the Probabilistic Latent Semantic Analysis technique (PLSA), using the 'Bag-of-Terms' paradigm, as a tool for exploring video data to learn the model by grouping similar activities. Our term vocabulary consists of 3D spatio-temporal patch groups assigned by the direction of motion. Our video representation ensures the spatial information, the object trajectory, and the motion. The main importance of this approach is that it can be adapted to detect abnormal behaviors in order to ensure and enhance human security.

Keywords: activity modeling, clustering, PLSA, video representation

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Authors: Anwesha Pathak

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With the increasing number of satellites and space debris, space traffic management (STM) becomes crucial. AI can aid in STM by predicting and preventing potential collisions, optimizing satellite trajectories, and managing orbital slots. Governance frameworks need to address the integration of AI algorithms in STM to ensure safe and sustainable satellite activities. AI and governance play significant roles in the context of satellite activities in space. Artificial intelligence (AI) technologies, such as machine learning and computer vision, can be utilized to process vast amounts of data received from satellites. AI algorithms can analyse satellite imagery, detect patterns, and extract valuable information for applications like weather forecasting, urban planning, agriculture, disaster management, and environmental monitoring. AI can assist in automating and optimizing satellite operations. Autonomous decision-making systems can be developed using AI to handle routine tasks like orbit control, collision avoidance, and antenna pointing. These systems can improve efficiency, reduce human error, and enable real-time responsiveness in satellite operations. AI technologies can be leveraged to enhance the security of satellite systems. AI algorithms can analyze satellite telemetry data to detect anomalies, identify potential cyber threats, and mitigate vulnerabilities. Governance frameworks should encompass regulations and standards for securing satellite systems against cyberattacks and ensuring data privacy. AI can optimize resource allocation and utilization in satellite constellations. By analyzing user demands, traffic patterns, and satellite performance data, AI algorithms can dynamically adjust the deployment and routing of satellites to maximize coverage and minimize latency. Governance frameworks need to address fair and efficient resource allocation among satellite operators to avoid monopolistic practices. Satellite activities involve multiple countries and organizations. Governance frameworks should encourage international cooperation, information sharing, and standardization to address common challenges, ensure interoperability, and prevent conflicts. AI can facilitate cross-border collaborations by providing data analytics and decision support tools for shared satellite missions and data sharing initiatives. AI and governance are critical aspects of satellite activities in space. They enable efficient and secure operations, ensure responsible and ethical use of AI technologies, and promote international cooperation for the benefit of all stakeholders involved in the satellite industry.

Keywords: satellite, space debris, traffic, threats, cyber security.

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Authors: Hossein Javidnia, Salehe Taheri

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The Electrocardiogram (ECG) is the recording of the heart’s electrical potential versus time. ECG signals are often contaminated with noise such as baseline wander and muscle noise. As these signals have been widely used in clinical studies to detect heart diseases, it is essential to filter these noises. In this paper we compare performance of Wiener Filtering and Median Filtering methods to filter Additive White Gaussian (AWG) noise with the determined signal to noise ratio (SNR) ranging from 3 to 5 dB applied to long-term ECG recordings samples. Root mean square error (RMSE) and coefficient of determination (R2) between the filtered ECG and original ECG was used as the filter performance indicator. Experimental results show that Wiener filter has better noise filtering performance than Median filter.

Keywords: ECG noise filtering, Wiener filtering, median filtering, Gaussian noise, filtering performance

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Authors: Chia-Hung Liao, Shih-Chieh Lin

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X-ray computed tomography (CT) technology has been used in the electronics industry as one of the non-destructive inspection tools for years. The key advantage of X-ray computed tomography technology superior to traditional optical inspection is the penetrating characteristics of X-rays can be used to detect defects in the interior of objects. The objective of this study is to find a way to estimate the system geometric deviation of X-ray CT equipment. Projection trajectories of the characteristic points of standard parts were tracked, and ways to calculate the deviation of various geometric parameters of the system will be proposed and evaluated. A simulation study will be conducted to first find out the effects of system geometric deviation on projected trajectories. Then ways to estimate geometric deviation with collected trajectories will be proposed and tested through simulations.

Keywords: geometric calibration, X-ray computed tomography, trajectory tracing, reconstruction optimization

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Authors: Sun-Ki Hong, Ki-Seok Kim, Yong-Ho Jo

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Lots of motors have been being used in industry. Therefore many researchers have studied about the failure diagnosis of motors. In this paper, the effect of measuring environment for diagnosis of gear fault connected to a motor shaft is studied. The fault diagnosis is executed through the comparison of normal gear and abnormal gear. The measured FFT data are compared with the normal data and analyzed for q-axis current, noise and vibration. For bad and good environment, the diagnosis results are compared. From these, it is shown that the bad measuring environment may not be able to detect exactly the motor gear fault. Therefore it is emphasized that the measuring environment should be carefully prepared.

Keywords: motor fault, diagnosis, FFT, vibration, noise, q-axis current, measuring environment

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Authors: Haiyang Su, Kun Qian

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We developed a novel plasmonic matrix assisted laser desorption/ionization mass spectrometry (MALDI MS) approach to detect small nutrients and toxin in complex biological emulsion samples. We used silver nanoshells (SiO₂@Ag) with optimized structures as matrices and achieved direct analysis of ~6 nL of human breast milk without any enrichment or separation. We performed identification and quantitation of small nutrients and toxins with limit-of-detection down to 0.4 pmol (for melamine) and reaction time shortened to minutes, superior to the conventional biochemical methods currently in use. Our approach contributed to the near-future application of MALDI MS in a broad field and personalized design of plasmonic materials for real case bio-analysis.

Keywords: plasmonic materials, laser desorption/ionization, mass spectrometry, small nutrients, toxins

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Authors: Soban Najam, S. M. Jahanzeb, Ahmed Sohail, Faraz Idris Khan

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With the recent increase in reliance on Gas as the primary source of energy across the world, there has been a lot of research conducted on gas distribution networks. As the complexity and size of these networks grow, so does the leakage of gas in the distribution network. One of the most crucial factors in the production and distribution of gas is UFG or Unaccounted for Gas. The presence of UFG signifies that there is a difference between the amount of gas distributed, and the amount of gas billed. Our approach is to use information that we acquire from several specified points in the network. This information will be used to calculate the loss occurring in the network using the developed algorithm. The Algorithm can also identify the leakages at any point of the pipeline so we can easily detect faults and rectify them within minimal time, minimal efforts and minimal resources.

Keywords: FLA, fault location analysis, GDN, gas distribution network, GIS, geographic information system, NMS, network Management system, OMS, outage management system, SSGC, Sui Southern gas company, UFG, unaccounted for gas

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Authors: Nidhal K. Azawi, John M. Gauch

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Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.

Keywords: colonoscopy classification, feature extraction, image alignment, machine learning

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Authors: Gil Soriano, Aubreyrose Casilang

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Soil-transmitted helminth infection remains to be one of the leading public health problem worldwide, which is common in the rural developing regions especially among children. This study aimed to detect the presence of soil transmitted helminths among children and its associated transmission factors. Descriptive cross sectional research was the design used in the study and questionnaires were administered. Stool samples were collected among the samples (n=108) and were analyzed using kato thick method. Results showed that 61 out of 108 respondents are infected by soil transmitted helminth infection with A. lumbricoides the highest, followed by hookworm and T. trichuria. Parent's educational attainment, hand washing practices, and water sources were found to be associated with presence of Soil Transmitted Helminth infection.

Keywords: associated risk factors, barangay, school children, soil transmitted helminth infection

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Authors: Yener Tekeli, Hayri Baba

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The natural active compounds found in medicinal plants are belong to various chemical structures including polyphenolic compounds, flavonoids, essential oils, and vitamins and some of these compounds have anticancer, antioxidant, and antimicrobial activity. However, these compounds have been little known about mechanisms to confer antibacterial drug resistance. In this study; some macrofungi extracts (Pholiota lucifera, Gnaoderma applanatum and Pleurotus ostreatus) were investigated for their abilities to enhance bacterial permeability by flow cytometry. This experiments exhibited enhancement of these extracts to disrupt the cytoplasmic membrane of living bacterial (Listeria innocua and Escherichia coli) cells. These experiments were designed to detect uptake of PI&SYT by enhancing with a ranged concentration of herb extracts.

Keywords: antimicrobial activity, flow cytometry, macrofungi, multidrug resistant

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Authors: Bala Adamu Malami

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The necessity of low-cost electronic vehicle/car security designed in coordination with other security measures is always there in our society to reduce the risk of vehicle intrusion. Keeping this problem in mind, we are designing an automatic GPS system which is technology to build an integrated and fully customized vehicle to detect the movement of the vehicle and also serve as a security system at a reasonable cost. Users can locate the vehicle's position via GPS by using the Google Maps application to show vehicle coordinates on a smartphone. The tracking system uses a Global System for Mobile Communication (GSM) modem for communication between the mobile station and the microcontroller to send and receive commands. Further design can be improved to capture the vehicle movement range and alert the vehicle owner when the vehicle is out of range.

Keywords: electronic, GPS, GSM modem, communication, vehicle

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Authors: S. Bennoud, M. Zergoug

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The numerical simulation of electromagnetic interactions is still a challenging problem, especially in problems that result in fully three dimensional mathematical models. The goal of this work is to use mathematical modeling to characterize the reliability and capacity of eddy current technique to detect and characterize defects embedded in aeronautical in-service pieces. The finite element method is used for describing the eddy current technique in a mathematical model by the prediction of the eddy current interaction with defects. However, this model is an approximation of the full Maxwell equations. In this study, the analysis of the problem is based on a three dimensional finite element model that computes directly the electromagnetic field distortions due to defects.

Keywords: eddy current, finite element method, non destructive testing, numerical simulations

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Authors: Amjad Abdullah, Amjad Yahya, Bushra Aljohani, Amani Alghamdi

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Change point detection is an important part of data analysis. The presence of a change point refers to a significant change in the behavior of a time series. In this article, we examine the detection of multiple change points of parameters of the exponential Lomax distribution, which is broad and flexible compared with other distributions while fitting data. We used the Schwarz information criterion and binary segmentation to detect multiple change points in publicly available data on the average temperature in the ozone layer. The change points were successfully located.

Keywords: binary segmentation, change point, exponentialLomax distribution, information criterion

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Authors: Christa L. Arnold, Margaret C. Stewart

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This research shares the results of an exploratory study examining Statement Analysis (SA) to detect deception in online truthful and untruthful social media posts. Applying a Law Enforcement methodology SA, used in criminal interview statements, this research analyzes what is stated to assist in evaluating written deceptive information. Preliminary findings reveal qualitative and quantitative nuances for SA in online deception detection and uncover insights regarding digital deceptive behavior. Thus far, findings reveal truthful statements tend to differ from untruthful statements in both content and quality.

Keywords: deception detection, online deception, social media content, statement analysis

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Authors: Lana Burmistrova

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Introduction: The influence of visual impairments on several cognitive processes used in the music learning process is an increasingly important area in special education and cognitive musicology. Many children have several visual impairments due to the refractive errors and irreversible inhibitors. However, based on the compensatory neuroplasticity and functional reorganization, congenitally blind (CB) and early blind (EB) individuals use several areas of the occipital lobe to perceive and process auditory and tactile information. CB individuals have greater memory capacity, memory reliability, and less false memory mechanisms are used while executing several tasks, they have better working memory (WM) and short-term memory (STM). Blind individuals use several strategies while executing tactile and working memory n-back tasks: verbalization strategy (mental recall), tactile strategy (tactile recall) and combined strategies. Methods and design: The aim of the pilot study was to substantiate similar tendencies while executing attention, memory and combined auditory tasks in blind and sighted individuals constructed for this study, and to investigate attention, memory and combined mechanisms used in the music learning process. For this study eight (n=8) blind and eight (n=8) sighted individuals aged 13-20 were chosen. All respondents had more than five years music performance and music learning experience. In the attention task, all respondents had to identify pitch changes in tonal and randomized melodic pairs. The memory task was based on the mismatch negativity (MMN) proportion theory: 80 percent standard (not changed) and 20 percent deviant (changed) stimuli (sequences). Every sequence was named (na-na, ra-ra, za-za) and several items (pencil, spoon, tealight) were assigned for each sequence. Respondents had to recall the sequences, to associate them with the item and to detect possible changes. While executing the combined task, all respondents had to focus attention on the pitch changes and had to detect and describe these during the recall. Results and conclusion: The results support specific features in CB and EB, and similarities between late blind (LB) and sighted individuals. While executing attention and memory tasks, it was possible to observe the tendency in CB and EB by using more precise execution tactics and usage of more advanced periodic memory, while focusing on auditory and tactile stimuli. While executing memory and combined tasks, CB and EB individuals used passive working memory to recall standard sequences, active working memory to recall deviant sequences and combined strategies. Based on the observation results, assessment of blind respondents and recording specifics, following attention and memory correlations were identified: reflective attention and STM, reflective attention and periodic memory, auditory attention and WM, tactile attention and WM, auditory tactile attention and STM. The results and the summary of findings highlight the attention and memory features used in the music learning process in the context of blindness, and the tendency of the several attention and memory types correlated based on the task, strategy and individual features.

Keywords: attention, blindness, memory, music learning, strategy

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Authors: N. Das, N. Samanta, L. Pandey, C. Roy Chaudhuri

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Early diagnosis of infection like Hep-B virus in blood is important for low cost medical treatment. For this purpose, it is desirable to develop a point of care device which should be able to detect trace quantities of the target molecule in blood. In this paper, we report a nanoporous silicon oxide sensor which is capable of detecting down to 1fM concentration of Hep-B surface antigen in blood without the requirement of any centrifuge or pre-concentration. This has been made possible by the presence of resonant peak in the sensitivity characteristics. This peak is observed to be dependent only on the concentration of the specific antigen and not on the interfering species in blood serum. The occurrence of opposite impedance change within the pores and at the bottom of the pore is responsible for this effect. An electronic interface has also been designed to provide a display of the virus concentration.

Keywords: impedance spectroscopy, ultrasensitive detection in blood, peak frequency, electronic interface

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Authors: Benazzouz Djamel, Termeche Adel, Touati Youcef, Alem Said, Ouziala Mahdi

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This paper presents an approach which detect and isolate efficiently a fault in a system. This approach avoids false alarms, non-detections and delays in detecting faults. A study case have been proposed to show the importance of taking into consideration the uncertainties in the decision-making procedure and their effect on the degradation diagnostic performance and advantage of using Bond Graph (BG) for such degradation. The use of BG in the Linear Fractional Transformation (LFT) form allows generating robust Analytical Redundancy Relations (ARR’s), where the uncertain part of ARR’s is used to generate the residuals adaptive thresholds. The study case concerns an electromechanical system composed of a motor, a reducer and an external load. The aim of this application is to show the effectiveness of the BG-LFT approach to robust fault detection.

Keywords: bond graph, LFT, uncertainties, detection and faults isolation, ARR

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Authors: Grishma D. Solanki, Karshan Kandoriya

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In modern era of information age, digitalization has revolutionized like never before. Powerful computers, advanced photo editing software packages and high resolution capturing devices have made manipulation of digital images incredibly easy. As per as image forensics concerns, one of the most actively researched area are detection of copy move forgeries. Higher computational complexity is one of the major component of existing techniques to detect such tampering. Moreover, copy move forgery is usually performed in three steps. First, copying of a region in an image then pasting the same one in the same respective image and finally doing some post-processing like rotation, scaling, shift, noise, etc. Consequently, pseudo Zernike moment is used as a features extraction method for matching image blocks and as a primary factor on which performance of detection algorithms depends.

Keywords: copy-move image forgery, digital forensics, image forensics, image forgery

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Authors: Maha Jazouli

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Suicide is one of the most important causes of death in the prison environment, both in Canada and internationally. Rates of attempts of suicide and self-harm have been on the rise in recent years, with hangings being the most frequent method resorted to. The objective of this article is to propose a method to automatically detect in real time suicidal behaviors. We present a gesture recognition system that consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using machine learning algorithms (MLA). Our proposed system gives us satisfactory results. This smart video surveillance system can help assist staff responsible for the safety and health of inmates by alerting them when suicidal behavior is detected, which helps reduce mortality rates and save lives.

Keywords: suicide detection, Kinect azure, RGB-D camera, SVM, machine learning, gesture recognition

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Authors: Bernd Kiefer, Abraham Gebru Tesfay, Dietrich Klakow

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The motivation of our work is to detect different terrain types traversed by a robot based on acoustic data from the robot-terrain interaction. Different acoustic features and classifiers were investigated, such as Mel-frequency cepstral coefficient and Gamma-tone frequency cepstral coefficient for the feature extraction, and Gaussian mixture model and Feed forward neural network for the classification. We analyze the system’s performance by comparing our proposed techniques with some other features surveyed from distinct related works. We achieve precision and recall values between 87% and 100% per class, and an average accuracy at 95.2%. We also study the effect of varying audio chunk size in the application phase of the models and find only a mild impact on performance.

Keywords: acoustic features, autonomous robots, feature extraction, terrain classification

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Authors: O. Hassoon, M. Tarfoui, A. El Malk

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Fiber Bragg optic sensor embedded in composite material to detect and monitor the damage which is occur in composite structure. In this paper we deal with the mode-Ι delamination to determine the resistance of material to crack propagation, and use the coupling mode theory and T-matrix method to simulating the FBGs spectrum for both uniform and non-uniform strain distribution. The double cantilever beam test which is modeling in FEM to determine the Longitudinal strain, there are two models which are used, the first is the global half model, and the second the sub-model to represent the FBGs with refine mesh. This method can simulate the damage in the composite structure and converting the strain to wavelength shifting of the FBG spectrum.

Keywords: fiber bragg grating, delamination detection, DCB, FBG spectrum, structure health monitoring

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Authors: Barbra Bhebhe, Melvyn Quan

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A serological survey was done to detect antibodies against Shuni virus (SHUV) from cattle in Western Kenya. In Kenya the disease status of SHUV in cattle has never been established. It is a zoonotic virus and even though studies have been carried out as early as the 1960s, little research has been published and SHUV is still not a well-recognised Orthobunyavirus. One hundred serum samples were collected from healthy cattle in Kenya and tested for antibodies against SHUV by a serum neutralization assay. All antibody titre values were greater than 1:160, with most of the samples greater than 1:320. Of the samples tested, 87 % had titres greater than 1:320, 12% had a titre of 1:320 and 2% had a titre of 1:160. Samples were classified as positive if the antibody titre was ≥ 1:10 and negative if < 1:10. This study suggests that cattle are exposed commonly to SHUV, which may be endemic in Kenya.

Keywords: Shuni virus, Orthobunyavuruses, serum neutralization test, cell-culture

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Authors: Muneer Abbad

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In search of better, traditional learning universities have expanded their ways to deliver knowledge and integrate cost effective e-learning systems. Universities’ use of information and communication technologies has grown tremendously over the last decade. To ensure efficient use of the e-learning system, this project aimed to evaluate the good and bad practices, detect errors and determine areas for further improvements in usage. This project critically evaluated the students’ perception of the e-learning system and recommended changes to improve students’ e-learning usage, through conducting questionnaire given to the students that have experience with e-learning systems. Results of the study indicated that, in general, students have favourable perceptions toward using the e-learning system. They seemed to value the resources tool and its contribution to building their knowledge more than other e-learning tools. However, they seemed to perceive a limited value from the audio or video podcasts. This study has shown that technology acceptance is the most variable, factor that contributes to students’ perception and satisfaction of the e-learning system.

Keywords: e-learning, perception, Jordan, universities

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Authors: Hyeongju Jeon, Yonghyun Kim, Yongil Kim

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Synthetic Aperture Radar (SAR) is an effective tool for damage assessment induced by disasters due to its all-weather and night/day acquisition capability. In this paper, the 2017 Colombia landslide was observed using full-polarimetric ALOS/PALSAR-2 data. Polarimetric decompositions, including the Freeman-Durden decomposition and the Cloude decomposition, are utilized to analyze the scattering mechanisms changes before and after-landslide. These analyses are used to detect the damaged areas induced by the landslide. Experimental results validate the efficiency of the full polarimetric SAR data since the damaged areas can be well discriminated. Thus, we can conclude the proposed method using full polarimetric data has great potential for damage assessment of landslides.

Keywords: Synthetic Aperture Radar (SAR), polarimetric decomposition, damage assessment, landslide

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