Search results for: Electromagnetic signal detection

Authors: P. Selva, B. Lorrain, J. Alexis, A. Seror, A. Longuet, C. Mary, F. Denard

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Over the past four decades, the fatigue behavior of nickel-based alloys has been widely studied. However, in recent years, significant advances in the fabrication process leading to grain size reduction have been made in order to improve fatigue properties of aircraft turbine discs. Indeed, a change in particle size affects the initiation mode of fatigue cracks as well as the fatigue life of the material. The present study aims to investigate the fatigue behavior of a newly developed nickel-based superalloy under biaxial-planar loading. Low Cycle Fatigue (LCF) tests are performed at different stress ratios so as to study the influence of the multiaxial stress state on the fatigue life of the material. Full-field displacement and strain measurements as well as crack initiation detection are obtained using Digital Image Correlation (DIC) techniques. The aim of this presentation is first to provide an in-depth description of both the experimental set-up and protocol: the multiaxial testing machine, the specific design of the cruciform specimen and performances of the DIC code are introduced. Second, results for sixteen specimens related to different load ratios are presented. Crack detection, strain amplitude and number of cycles to crack initiation vs. triaxial stress ratio for each loading case are given. Third, from fractographic investigations by scanning electron microscopy it is found that the mechanism of fatigue crack initiation does not depend on the triaxial stress ratio and that most fatigue cracks initiate from subsurface carbides.

Keywords: Cruciform specimen, multiaxial fatigue, Nickelbased superalloy.

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Authors: M. Magrini, D. Moroni, G. Palazzese, G. Pieri, D. Azzarelli, A. Spada, L. Fanucci, O. Salvetti

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Railway crossings are complex entities whose optimal management cannot be addressed unless with the help of an intelligent transportation system integrating information both on train and vehicular flows. In this paper, we propose an integrated system named SIMPLE (Railway Safety and Infrastructure for Mobility applied at level crossings) that, while providing unparalleled safety in railway level crossings, collects data on rail and road traffic and provides value-added services to citizens and commuters. Such services include for example alerts, via variable message signs to drivers and suggestions for alternative routes, towards a more sustainable, eco-friendly and efficient urban mobility. To achieve these goals, SIMPLE is organized as a System of Systems (SoS), with a modular architecture whose components range from specially-designed radar sensors for obstacle detection to smart ETSI M2M-compliant camera networks for urban traffic monitoring. Computational unit for performing forecast according to adaptive models of train and vehicular traffic are also included. The proposed system has been tested and validated during an extensive trial held in the mid-sized Italian town of Montecatini, a paradigmatic case where the rail network is inextricably linked with the fabric of the city. Results of the tests are reported and discussed.

Keywords: Intelligent Transportation Systems (ITS), railway, railroad crossing, smart camera networks, radar obstacle detection, real-time traffic optimization, IoT, ETSI M2M, transport safety.

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Authors: Patricia B. Cruz, Catrina Jean G. Valenzuela, Analyn N. Yumang

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Nearly a hundred per million of the Filipino population is diagnosed with Chronic Kidney Disease (CKD). The early stage of CKD has no symptoms and can only be discovered once the patient undergoes urinalysis. Over the years, different methods were discovered and used for the quantification of the urinary albumin such as the immunochemical assays where most of these methods require large machinery that has a high cost in maintenance and resources, and a dipstick test which is yet to be proven and is still debated as a reliable method in detecting early stages of microalbuminuria. This research study involves the use of the liquid chromatography concept in microfluidic instruments with biosensor as a means of separation and detection respectively, and linear regression to quantify human urinary albumin. The researchers’ main objective was to create a miniature system that quantifies and detect patients’ urinary albumin while reducing the amount of volume used per five test samples. For this study, 30 urine samples of unknown albumin concentrations were tested using VITROS Analyzer and the microfluidic system for comparison. Based on the data shared by both methods, the actual vs. predicted regression were able to create a positive linear relationship with an R² of 0.9995 and a linear equation of y = 1.09x + 0.07, indicating that the predicted values and actual values are approximately equal. Furthermore, the microfluidic instrument uses 75% less in total volume – sample and reagents combined, compared to the VITROS Analyzer per five test samples.

Keywords: Chronic kidney disease, microfluidics, linear regression, VITROS analyzer, urinary albumin.

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Authors: Tom Dowling, Adam Duffy

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This paper presents an architecture to assist in the development of tools to perform experimental analysis. Existing implementations of tools based on this architecture are also described in this paper. These tools are applied to the real world problem of fault attack emulation and detection in cryptographic algorithms.

Keywords: Software Architectures and Design, Software Componentsand Reuse, Engineering Secure Software.

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Authors: Anatoli Torokhti, Stan Miklavcic

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We study a new technique for optimal data compression subject to conditions of causality and different types of memory. The technique is based on the assumption that some information about compressed data can be obtained from a solution of the associated problem without constraints of causality and memory. This allows us to consider two separate problem related to compression and decompression subject to those constraints. Their solutions are given and the analysis of the associated errors is provided.

Keywords: stochastic signals, optimization problems in signal processing.

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Authors: Nguyen Thu Huong, Nguyen Quang Bau

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The Hall Coefficient (HC) and the Magnetoresistance (MR) have been studied in two-dimensional systems. The HC and the MR in Rectangular Quantum Wire (RQW) subjected to a crossed DC electric field and magnetic field in the presence of a Strong Electromagnetic Wave (EMW) characterized by electric field are studied in this work. Using the quantum kinetic equation for electrons interacting with optical phonons, we obtain the analytic expressions for the HC and the MR with a dependence on magnetic field, EMW frequency, temperatures of systems and the length characteristic parameters of RQW. These expressions are different from those obtained for bulk semiconductors and cylindrical quantum wires. The analytical results are applied to GaAs/GaAs/Al. For this material, MR depends on the ratio of the EMW frequency to the cyclotron frequency. Indeed, MR reaches a minimum at the ratio 5/4, and when this ratio increases, it tends towards a saturation value. The HC can take negative or positive values. Each curve has one maximum and one minimum. When magnetic field increases, the HC is negative, achieves a minimum value and then increases suddenly to a maximum with a positive value. This phenomenon differs from the one observed in cylindrical quantum wire, which does not have maximum and minimum values.

Keywords: Hall coefficient, rectangular quantum wires, electron-optical phonon interaction, quantum kinetic equation.

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Authors: Shrikrishan Yadav, Akhilesh Saini, Krishna Chandra Roy

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The electromagnetic spectrum is a natural resource and hence well-organized usage of the limited natural resources is the necessities for better communication. The present static frequency allocation schemes cannot accommodate demands of the rapidly increasing number of higher data rate services. Therefore, dynamic usage of the spectrum must be distinguished from the static usage to increase the availability of frequency spectrum. Cognitive radio is not a single piece of apparatus but it is a technology that can incorporate components spread across a network. It offers great promise for improving system efficiency, spectrum utilization, more effective applications, reduction in interference and reduced complexity of usage for users. Cognitive radio is aware of its environmental, internal state, and location, and autonomously adjusts its operations to achieve designed objectives. It first senses its spectral environment over a wide frequency band, and then adapts the parameters to maximize spectrum efficiency with high performance. This paper only focuses on the analysis of Bit-Error-Rate in cognitive radio by using Particle Swarm Optimization Algorithm. It is theoretically as well as practically analyzed and interpreted in the sense of advantages and drawbacks and how BER affects the efficiency and performance of the communication system.

Keywords: BER, Cognitive Radio, Environmental Parameters, PSO, Radio spectrum, Transmission Parameters

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Authors: F. Haghjoo, M. Sarlak, S.M. Shahrtash

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In order to perform on-line measuring and detection of PD signals, a total solution composing of an HFCT, A/D converter and a complete software package is proposed. The software package includes compensation of HFCT contribution, filtering and noise reduction using wavelet transform and soft calibration routines. The results have shown good performance and high accuracy.

Keywords: Partial Discharge, Measurement, On-line, HFCT

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Authors: János Levendovszky, András Oláh

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In this paper, novel statistical sampling based equalization techniques and CNN based detection are proposed to increase the spectral efficiency of multiuser communication systems over fading channels. Multiuser communication combined with selective fading can result in interferences which severely deteriorate the quality of service in wireless data transmission (e.g. CDMA in mobile communication). The paper introduces new equalization methods to combat interferences by minimizing the Bit Error Rate (BER) as a function of the equalizer coefficients. This provides higher performance than the traditional Minimum Mean Square Error equalization. Since the calculation of BER as a function of the equalizer coefficients is of exponential complexity, statistical sampling methods are proposed to approximate the gradient which yields fast equalization and superior performance to the traditional algorithms. Efficient estimation of the gradient is achieved by using stratified sampling and the Li-Silvester bounds. A simple mechanism is derived to identify the dominant samples in real-time, for the sake of efficient estimation. The equalizer weights are adapted recursively by minimizing the estimated BER. The near-optimal performance of the new algorithms is also demonstrated by extensive simulations. The paper has also developed a (Cellular Neural Network) CNN based approach to detection. In this case fast quadratic optimization has been carried out by t, whereas the task of equalizer is to ensure the required template structure (sparseness) for the CNN. The performance of the method has also been analyzed by simulations.

Keywords: Cellular Neural Network, channel equalization, communication over fading channels, multiuser communication, spectral efficiency, statistical sampling.

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Authors: H. A. Al-Kahtani, A. A. Abou Arab, M. Asif

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Animal fats (camel, sheep, goat, rabbit and chicken) and vegetable oils (corn, sunflower, palm oil and olive oil) were substituted with different proportions (1, 5, 10 and 20%) of lard. Fatty acid composition in TG and 2-MG were determined using lipase hydrolysis and gas chromatography before and after adulteration. Results indicated that, genuine lard had a high proportion (60.97%) of the total palmitic acid at 2-MG. However, it was 8.70%, 16.40%, 11.38%, 10.57%, 29.97 and 8.97% for camel, beef, sheep, goat, rabbit and chicken, respectively. It could be noticed also the position-2-MG is mostly occupied by unsaturated fatty acids among all tested fats except lard. Vegetable oils (corn, sunflower, palm oil and olive oil) revealed that the levels of palmitic acid esterifies at 2-MG position was 6.84, 1.43, 9.86 and 1.70%, respectively. It could be observed also the studied oils had a higher level of unsaturated fatty acids in the same position, compared with animal fats under investigation. Moreover, palmitic acid esterifies at 2-MG and PAEF increased gradually as the substituted levels increased among all tested fat and oil samples. Statistical analysis showed that the PAEF correlated well with lard level. The detection of lard in some commercial processed foods (5 French fries, 4 Butter fats, 5 processed meat and 6 candy samples) was carried out. Results revealed that 2 samples of French fries and 4 samples of processed meat contained lard due to their higher PAEF, while butter fat and candy were free of lard.

Keywords: Lard, adulteration, PAEF, goat, triglycerides.

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Authors: Jihad S. Daba (Jean-Pierre Dubois), Philip Jreije

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Speckled images arise when coherent microwave, optical, and acoustic imaging techniques are used to image an object, surface or scene. Examples of coherent imaging systems include synthetic aperture radar, laser imaging systems, imaging sonar systems, and medical ultrasound systems. Speckle noise is a form of object or target induced noise that results when the surface of the object is Rayleigh rough compared to the wavelength of the illuminating radiation. Detection and estimation in images corrupted by speckle noise is complicated by the nature of the noise and is not as straightforward as detection and estimation in additive noise. In this work, we derive stochastic models for speckle noise, with an emphasis on speckle as it arises in medical ultrasound images. The motivation for this work is the problem of segmentation and tissue classification using ultrasound imaging. Modeling of speckle in this context involves partially developed speckle model where an underlying Poisson point process modulates a Gram-Charlier series of Laguerre weighted exponential functions, resulting in a doubly stochastic filtered Poisson point process. The statistical distribution of partially developed speckle is derived in a closed canonical form. It is observed that as the mean number of scatterers in a resolution cell is increased, the probability density function approaches an exponential distribution. This is consistent with fully developed speckle noise as demonstrated by the Central Limit theorem.

Keywords: Doubly stochastic filtered process, Poisson point process, segmentation, speckle, ultrasound

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Authors: Charles Chikwendu Okpala, Christopher Chukwutoo Ihueze

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As a technique that reduces variation in a product by lessening the sensitivity of the design to sources of variation, rather than by controlling their sources, Taguchi Robust Design entails the designing of ideal goods, by developing a product that has minimal variance in its characteristics and also meets the desired exact performance. This paper examined the concept of the manufacturing approach and its application to brake pad product of an automotive parts manufacturing company. Although the firm claimed that only defects, excess inventory, and over-production were the few wastes that grossly affect their productivity and profitability, a careful study and analysis of their manufacturing processes with the application of Single Minute Exchange of Dies (SMED) tool showed that the waste of waiting is the fourth waste that bedevils the firm. The selection of the Taguchi L9 orthogonal array which is based on the four parameters and the three levels of variation for each parameter revealed that with a range of 2.17, that waiting is the major waste that the company must reduce in order to continue to be viable. Also, to enhance the company’s throughput and profitability, the wastes of over-production, excess inventory, and defects with ranges of 2.01, 1.46, and 0.82, ranking second, third, and fourth respectively must also be reduced to the barest minimum. After proposing -33.84 as the highest optimum Signal-to-Noise ratio to be maintained for the waste of waiting, the paper advocated for the adoption of all the tools and techniques of Lean Production System (LPS), and Continuous Improvement (CI), and concluded by recommending SMED in order to drastically reduce set up time which leads to unnecessary waiting.

Keywords: Taguchi Robust Design, signal to noise ratio, Single Minute Exchange of Dies, lean production system, waste.

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Authors: Ismail Abubakar, Hamid Mehrabi, Reg Morton

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Currently, extensive signal analysis is performed in order to evaluate structural health of turbomachinery blades. This approach is affected by constraints of time and the availability of qualified personnel. Thus, new approaches to blade dynamics identification that provide faster and more accurate results are sought after. Generally, modal analysis is employed in acquiring dynamic properties of a vibrating turbomachinery blade and is widely adopted in condition monitoring of blades. The analysis provides useful information on the different modes of vibration and natural frequencies by exploring different shapes that can be taken up during vibration since all mode shapes have their corresponding natural frequencies. Experimental modal testing and finite element analysis are the traditional methods used to evaluate mode shapes with limited application to real live scenario to facilitate a robust condition monitoring scheme. For a real time mode shape evaluation, rapid evaluation and low computational cost is required and traditional techniques are unsuitable. In this study, artificial neural network is developed to evaluate the mode shape of a lab scale rotating blade assembly by using result from finite element modal analysis as training data. The network performance evaluation shows that artificial neural network (ANN) is capable of mapping the correlation between natural frequencies and mode shapes. This is achieved without the need of extensive signal analysis. The approach offers advantage from the perspective that the network is able to classify mode shapes and can be employed in real time including simplicity in implementation and accuracy of the prediction. The work paves the way for further development of robust condition monitoring system that incorporates real time mode shape evaluation.

Keywords: Modal analysis, artificial neural network, mode shape, natural frequencies, pattern recognition.

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Authors: Huong M. T. Nguyen, Hoa A. P. Nguyen, Mai P. T. Nguyen, Ngoc D. Ngo, Van T. Ta, Hai T. Le, Chi V. Phan

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Wilson’s disease (WD) is an autosomal recessive disorder of the copper metabolism, which is caused by a mutation in the copper-transporting P-type ATPase (ATP7B). The mechanism of this disease is the failure of hepatic excretion of copper to bile, and leads to copper deposits in the liver and other organs. The ATP7B gene is located on the long arm of chromosome 13 (13q14.3). This study aimed to investigate the gene mutation in the Vietnamese patients with WD, and make a presymptomatic diagnosis for their familial members. Forty-three WD patients and their 65 siblings were identified as having ATP7B gene mutations. Genomic DNA was extracted from peripheral blood samples; 21 exons and exon-intron boundaries of the ATP7B gene were analyzed by direct sequencing. We recognized four mutations ([R723=; H724Tfs*34], V1042Cfs*79, D1027H, and IVS6+3A>G) in the sum of 20 detectable mutations, accounting for 87.2% of the total. Mutation S105* was determined to have a high rate (32.6%) in this study. The hotspot regions of ATP7B were found at exons 2, 16, and 8, and intron 14, in 39.6 %, 11.6 %, 9.3%, and 7 % of patients, respectively. Among nine homozygote/compound heterozygote siblings of the patients with WD, three individuals were determined as asymptomatic by screening mutations of the probands. They would begin treatment after diagnosis. In conclusion, 20 different mutations were detected in 43 WD patients. Of this number, four novel mutations were explored, including [R723=; H724Tfs*34], V1042Cfs*79, D1027H, and IVS6+3A>G. The mutation S105* is the most prevalent and has been considered as a biomarker that can be used in a rapid detection assay for diagnosis of WD patients. Exons 2, 8, and 16, and intron 14 should be screened initially for WD patients in Vietnam. Based on risk profile for WD, genetic testing for presymptomatic patients is also useful in diagnosis and treatment.

Keywords: ATP7B gene, mutation detection, presymptomatic diagnosis, Vietnamese Wilson’s disease.

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Authors: Altab Hossain, Ataur Rahman, A. K. M. Mohiuddin, Yulfian Aminanda

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Fuzzy logic system (FLS) is used in this study to predict the tractive performance in terms of traction force, and motion resistance for an intelligent air cushion track vehicle while it operates in the swamp peat. The system is effective to control the intelligent air –cushion system with measuring the vehicle traction force (TF), motion resistance (MR), cushion clearance height (CH) and cushion pressure (CP). Ultrasonic displacement sensor, pull-in solenoid electromagnetic switch, pressure control sensor, micro controller, and battery pH sensor are incorporated with the Fuzzy logic system to investigate experimentally the TF, MR, CH, and CP. In this study, a comparison for tractive performance of an intelligent air cushion track vehicle has been performed with the results obtained from the predicted values of FLS and experimental actual values. The mean relative error of actual and predicted values from the FLS model on traction force, and total motion resistance are found as 5.58 %, and 6.78 % respectively. For all parameters, the relative error of predicted values are found to be less than the acceptable limits. The goodness of fit of the prediction values from the FLS model on TF, and MR are found as 0.90, and 0.98 respectively.

Keywords: Cushion pressure, Fuzzy logic, Motion resistance, Traction force.

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Authors: Anastasia Rita Widiarti, Phalita Nari Wastu

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Hidden Markov Model (HMM) is a stochastic method which has been used in various signal processing and character recognition. This study proposes to use HMM to recognize Javanese characters from a number of different handwritings, whereby HMM is used to optimize the number of state and feature extraction. An 85.7 % accuracy is obtained as the best result in 16-stated vertical model using pure HMM. This initial result is satisfactory for prompting further research.

Keywords: Character recognition, off-line handwritingrecognition, Hidden Markov Model.

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Authors: Manisha A. Hira, Arup Rakshit

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Textile substrates are endowed with flexibility and ease of making–up, but are non-conductors of electricity. Conductive materials like carbon can be incorporated into textile structures to make flexible conductive materials. Such conductive textiles find applications as electrostatic discharge materials, electromagnetic shielding materials and flexible materials to carry current or signals. This work focuses on use of carbon fiber as conductor of electricity. Carbon fibers in staple or tow form can be incorporated in textile yarn structure to conduct electricity. The paper highlights the process for development of these conductive yarns of polyester/carbon using Friction spinning (DREF) as well as ring spinning. The optimized process parameters for processing hybrid structure of polyester with carbon tow on DREF spinning and polyester with carbon staple fiber using ring spinning have been presented. The studies have been linked to highlight the electrical conductivity of the developed yarns. Further, the developed yarns have been incorporated as weft in fabric and their electrical conductivity has been evaluated. The paper demonstrates the structure and properties of fabrics developed from such polyester/carbon blend yarns and their suitability as electrically dissipative fabrics.

Keywords: Carbon fiber, hybrid yarns, electrostatic dissipative fabrics.

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Authors: Yngvar Berg, Mehdi Azadmehr

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In this paper we present a linear autozeroing ultra lowvoltage amplifier. The autozeroing performed by all ULV circuits is important to reduce the impact of noise and especially avoid power supply noise in mixed signal low-voltage CMOS circuits. The simulated data presented is relevant for a 90nm TSMC CMOS process.

Keywords: Low-voltage, trans conductance amplifier, linearity, floating-gate.

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Authors: F. M. Pisano, M. Ciminello

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Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.

Keywords: Interactive dashboards, optical fibers, structural health monitoring, visual analytics.

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Authors: Samah Jawad Jabari

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Water is the most important and valuable resource not only for human life but also for all living things on the planet. The water supply utilities should fulfill the water requirement quantitatively and qualitatively. Drinking water systems are exposed to both natural (hurricanes and flood) and manmade hazards (risks) that are common in Palestine. Non-Revenue Water (NRW) is a manmade risk which remains a major concern in Palestine, as the NRW levels are estimated to be at a high level. In this research, Hebron city water distribution network was taken as a case study to estimate and audit the NRW levels. The research also investigated the state of the existing water distribution system in the study area by investigating the water losses and obtained more information on NRW prevention and management practices. Data and information have been collected from the Palestinian Water Authority (PWA) and Hebron Municipality (HM) archive. In addition to that, a questionnaire has been designed and administered by the researcher in order to collect the necessary data for water auditing. The questionnaire also assessed the views of stakeholder in PWA and HM (staff) on the current status of the NRW in the Hebron water distribution system. The important result obtained by this research shows that NRW in Hebron city was high and in excess of 30%. The main factors that contribute to NRW were the inaccuracies in billing volumes, unauthorized consumption, and the method of estimating consumptions through faulty meters. Policy for NRW reduction is available in Palestine; however, it is clear that the number of qualified staff available to carry out the activities related to leak detection is low, and that there is a lack of appropriate technologies to reduce water losses and undertake sufficient system maintenance, which needs to be improved to enhance the performance of the network and decrease the level of NRW losses.

Keywords: Non-revenue water, water auditing, leak detection, water meters.

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Authors: P. Chambe, B. Canova, A. Balabanian, M. Pele, N. Coeur

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To avoid battery assisted tags with limited lifetime batteries, it is proposed here to replace them by energy harvesting systems, able to feed from local environment. This would allow total independence to RFID systems, very interesting for applications where tag removal from its location is not possible. Example is here described for luggage safety in airports, and is easily  extendable to similar situation in terms of operation constraints. The idea is to fix RFID tag with energy harvesting system not only to identify luggage but also to supply an embedded microcontroller with a sensor delivering luggage weight making it impossible to add or to remove anything from the luggage during transit phases. The aim is to optimize the harvested energy for such RFID applications, and to study in which limits these applications are theoretically possible. Proposed energy harvester is based on two energy sources: piezoelectricity and electromagnetic waves, so that when the luggage is moving on ground transportation to airline counters, the piezo module supplies the tag and its microcontroller, while the RF module operates during luggage transit thanks to readers located along the way. Tag location on the luggage is analyzed to get best vibrations, as well as harvester better choice for optimizing the energy supply depending on applications and the amount of energy harvested during a period of time. Effects of system parameters (RFID UHF frequencies, limit distance between the tag and the antenna necessary to harvest energy, produced voltage and voltage threshold) are discussed and working conditions for such system are delimited.

Keywords: EM waves, Energy Harvesting, Piezoelectric, RFID Tag.

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Authors: Susannah G. Fleming Lionel Tarassenko

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The photoplethysmogram (PPG) is the pulsatile waveform produced by the pulse oximeter, which is widely used for monitoring arterial oxygen saturation in patients. Various methods for extracting the breathing rate from the PPG waveform have been compared using a consistent data set, and a novel technique using autoregressive modelling is presented. This novel technique is shown to outperform the existing techniques, with a mean error in breathing rate of 0.04 breaths per minute.

Keywords: Autoregressive modelling, breathing rate, photoplethysmogram, pulse oximetry.

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Authors: A. Diet, M. Villegas, G. Baudoin

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This work concerns the measurements of a Bulk Acoustic Waves (BAW) emission filter S parameters and compare with prototypes simulated types. Thanks to HP-ADS, a co-simulation of filters- characteristics in a digital radio-communication chain is performed. Four cases of modulation schemes are studied in order to illustrate the impact of the spectral occupation of the modulated signal. Results of simulations and co-simulation are given in terms of Error Vector Measurements to be useful for a general sensibility analysis of 4th/3rd Generation (G.) emitters (wideband QAM and OFDM signals)

Keywords: RF architectures, BAW filters.

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Authors: Turgay Temel, John Hallam

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An improved processing description to be employed in biosonar signal processing in a cochlea model is proposed and examined. It is compared to conventional models using a modified discrimination analysis and both are tested. Their performances are evaluated with echo data captured from natural targets (trees).Results indicate that the phase characteristics of low-pass filters employed in the echo processing have a significant effect on class separability for this data.

Keywords: Cochlea model, discriminant analysis, neurospikecoding, classification.

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Authors: Shashank Gautam, Pramod Sharma

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In present era, development of digital circuits, signal processors and other integrated circuits, magnitude comparators are challenged by large area and more power consumption. Comparator is most basic circuit that performs comparison. This paper presents a technique to design a two bit comparator which consumes less area and power. DSCH and MICROWIND version 3 are used to design the schematic and design the layout of the schematic, observe the performance parameters at different nanometer technologies respectively.

Keywords: Chip design, consumed power, layout area, two bit comparator.

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Authors: Abeer Aljohani

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The COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred as corona virus which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as Omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. Numerous COVID-19 cases have produced a huge burden on hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease based on the symptoms and medical history of the patient. As machine learning is a widely accepted area and gives promising results for healthcare, this research presents an architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard University of California Irvine (UCI) dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques on the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and Principal Component Analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, Receiver Operating Characteristic (ROC) and Area under Curve (AUC). The results depict that Decision tree, Random Forest and neural networks outperform all other state-of-the-art ML techniques. This result can be used to effectively identify COVID-19 infection cases.

Keywords: Supervised machine learning, COVID-19 prediction, healthcare analytics, Random Forest, Neural Network.

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Authors: Naci Büyükkaracığan

Abstract:

Hydroclimatic observation values ​​are used in the planning of the project of water resources. Climate variables are the first of the values ​​used in planning projects. At the same time, the climate system is a complex and interactive system involving the atmosphere, land surfaces, snow and bubbles, the oceans and other water structures. The amount and distribution of precipitation, which is an important climate parameter, is a limiting environmental factor for dispersed living things. Trend analysis is applied to the detection of the presence of a pattern or trend in the data set. Many trends work in different parts of the world are usually made for the determination of climate change. The detection and attribution of past trends and variability in climatic variables is essential for explaining potential future alteration resulting from anthropogenic activities. Parametric and non-parametric tests are used for determining the trends in climatic variables. In this study, trend tests were applied to annual total precipitation data obtained in period of 1972 and 2012, in the Konya Basin. Non-parametric trend tests, (Sen’s T, Spearman’s Rho, Mann-Kendal, Sen’s T trend, Wald-Wolfowitz) and parametric test (mean square) were applied to annual total precipitations of 15 stations for trend analysis. The linear slopes (change per unit time) of trends are calculated by using a non-parametric estimator developed by Sen. The beginning of trends is determined by using the Mann-Kendall rank correlation test. In addition, homogeneities in precipitation trends are tested by using a method developed by Van Belle and Hughes. As a result of tests, negative linear slopes were found in annual total precipitations in Konya.

Keywords: Trend analysis, precipitation, hydroclimatology, Konya, Turkey.

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Authors: Won-Ho Kim

Abstract:

In this paper, a design of H.263 based wireless video transceiver is presented for wireless camera system. It uses standard WIFI transceiver and the covering area is up to 100m. Furthermore the standard H.263 video encoding technique is used for video compression since wireless video transmitter is unable to transmit high capacity raw data in real time and the implemented system is capable of streaming at speed of less than 1Mbps using NTSC 720x480 video.

Keywords: Digital signal processing, H.263 video encoder, surveillance camera, wireless video transceiver.

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Authors: C. B. Masera, M. Imprialou, L. Budd, C. Morton

Abstract:

Even though signalised intersections are necessary for urban road traffic management, they can act as bottlenecks and disrupt traffic operations. Interrupted traffic flow causes congestion, delays, stop-and-go conditions (i.e. excessive acceleration/deceleration) and longer journey times. Vehicle and infrastructure connectivity offers the potential to provide improved new services with additional functions of assisting drivers. This paper focuses on one of the applications of vehicle-to-infrastructure communication namely Green Light Optimal Speed Advisory (GLOSA). To assess the effectiveness of GLOSA in the urban road network, an integrated microscopic traffic simulation framework is built into VISSIM software. Vehicle movements and vehicle-infrastructure communications are simulated through the interface of External Driver Model. A control algorithm is developed for recommending an optimal speed that is continuously updated in every time step for all vehicles approaching a signal-controlled point. This algorithm allows vehicles to pass a traffic signal without stopping or to minimise stopping times at a red phase. This study is performed with all connected vehicles at 100% penetration rate. Conventional vehicles are also simulated in the same network as a reference. A straight road segment composed of two opposite directions with two traffic lights per lane is studied. The simulation is implemented under 150 vehicles per hour and 200 per hour traffic volume conditions to identify how different traffic densities influence the benefits of GLOSA. The results indicate that traffic flow is improved by the application of GLOSA. According to this study, vehicles passed through the traffic lights more smoothly, and waiting times were reduced by up to 28 seconds. Average delays decreased for the entire network by 86.46% and 83.84% under traffic densities of 150 vehicles per hour per lane and 200 vehicles per hour per lane, respectively.

Keywords: Connected vehicles, GLOSA, intelligent transportation systems, infrastructure-to-vehicle communication.

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Authors: Nadia El Alami El Hassani, Soukaina Motia, Benachir Bouchikhi, Nezha El Bari

Abstract:

Doxycycline (DXy) is a cycline antibiotic, most frequently prescribed to treat bacterial infections in veterinary medicine. However, its broad antimicrobial activity and low cost, lead to an intensive use, which can seriously affect human health. Therefore, its spread in the food products has to be monitored. The scope of this work was to synthetize a sensitive and very selective molecularly imprinted polymer (MIP) for DXy detection in honey samples. Firstly, the synthesis of this biosensor was performed by casting a layer of carboxylate polyvinyl chloride (PVC-COOH) on the working surface of a gold screen-printed electrode (Au-SPE) in order to bind covalently the analyte under mild conditions. Secondly, DXy as a template molecule was bounded to the activated carboxylic groups, and the formation of MIP was performed by a biocompatible polymer by the mean of polyacrylamide matrix. Then, DXy was detected by measurements of differential pulse voltammetry (DPV). A non-imprinted polymer (NIP) prepared in the same conditions and without the use of template molecule was also performed. We have noticed that the elaborated biosensor exhibits a high sensitivity and a linear behavior between the regenerated current and the logarithmic concentrations of DXy from 0.1 pg.mL⁻¹ to 1000 pg.mL⁻¹. This technic was successfully applied to determine DXy residues in honey samples with a limit of detection (LOD) of 0.1 pg.mL⁻¹ and an excellent selectivity when compared to the results of oxytetracycline (OXy) as analogous interfering compound. The proposed method is cheap, sensitive, selective, simple, and is applied successfully to detect DXy in honey with the recoveries of 87% and 95%. Considering these advantages, this system provides a further perspective for food quality control in industrial fields.

Keywords: Electrochemical sensor, molecular imprinted polymer, doxycycline, food control.

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