Search results for: Photon Detection Efficiency

Authors: Fattah Alizadeh, Saeed Nalousi, Chiman Savari

Abstract:

Because of increasing demands for security in today-s society and also due to paying much more attention to machine vision, biometric researches, pattern recognition and data retrieval in color images, face detection has got more application. In this article we present a scientific approach for modeling human skin color, and also offer an algorithm that tries to detect faces within color images by combination of skin features and determined threshold in the model. Proposed model is based on statistical data in different color spaces. Offered algorithm, using some specified color threshold, first, divides image pixels into two groups: skin pixel group and non-skin pixel group and then based on some geometric features of face decides which area belongs to face. Two main results that we received from this research are as follow: first, proposed model can be applied easily on different databases and color spaces to establish proper threshold. Second, our algorithm can adapt itself with runtime condition and its results demonstrate desirable progress in comparison with similar cases.

Keywords: face detection, skin color modeling, color, colorfulimages, face recognition.

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Authors: Petar Halachev

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Forecasting the values of the indicators, which characterize the effectiveness of performance of organizations is of great importance for their successful development. Such forecasting is necessary in order to assess the current state and to foresee future developments, so that measures to improve the organization-s activity could be undertaken in time. The article presents an overview of the applied mathematical and statistical methods for developing forecasts. Special attention is paid to artificial neural networks as a forecasting tool. Their strengths and weaknesses are analyzed and a synopsis is made of the application of artificial neural networks in the field of forecasting of the values of different education efficiency indicators. A method of evaluation of the activity of universities using the Balanced Scorecard is proposed and Key Performance Indicators for assessment of e-learning are selected. Resulting indicators for the evaluation of efficiency of the activity are proposed. An artificial neural network is constructed and applied in the forecasting of the values of indicators for e-learning efficiency on the basis of the KPI values.

Keywords: artificial neural network, balanced scorecard, e-learning

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Authors: Y. Duvarci, A. K. Kutluca

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Design and land use are closely linked to the energy efficiency levels for an urban area. The current city planning practice does not involve an effective land useenergy evaluation in its 'blueprint' urban plans. The study proposed an appraisal method that can be embedded in GIS programs using five planning criteria as how far a planner can give away from the planning principles (criteria) for the most energy output s/he can obtain. The case of Balcova, a district in the Izmir Metropolitan area, is used conformingly for evaluating the proposed master plan and the geothermal energy (heating only) use for the concern district. If the land use design were proposed accordingly at-most energy efficiency (a 30% obtained), mainly increasing the density around the geothermal wells and also proposing more mixed use zones, we could have 17% distortion (infidelity to the main planning principles) from the original plan. The proposed method can be an effective tool for planners as simulation media, of which calculations can be made by GIS ready tools, to evaluate efficiency levels for different plan proposals, letting to know how much energy saving causes how much deviation from the other planning ideals. Lower energy uses can be possible for different land use proposals for various policy trials.

Keywords: Sustainable Urban Planning, Energy Efficiency, Geothermal Energy, District Heating Systems (DHS), EnergyPlanning

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Authors: Eric Filiol

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This paper presents a formalisation of the different existing code mutation techniques (polymorphism and metamorphism) by means of formal grammars. While very few theoretical results are known about the detection complexity of viral mutation techniques, we exhaustively address this critical issue by considering the Chomsky classification of formal grammars. This enables us to determine which family of code mutation techniques are likely to be detected or on the contrary are bound to remain undetected. As an illustration we then present, on a formal basis, a proof-of-concept metamorphic mutation engine denoted PB MOT, whose detection has been proven to be undecidable.

Keywords: Polymorphism, Metamorphism, Formal Grammars, Formal Languages, Language Decision, Code Mutation, Word Problem

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Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

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Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: Fake news detection, types of fake news, machine learning, natural language processing, classification techniques.

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Authors: Mohamed Fathy Heweage, Xiao Wen, Ayman Mokhtar, Ahmed Eldamarawy

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In this paper, we are interested in modeling, simulation, and measurement of the laser spot position with a quadrant detector. We enhance detection and tracking of semi-laser weapon decoding system based on microcontroller. The system receives the reflected pulse through quadrant detector and processes the laser pulses through a processing circuit, a microcontroller decoding laser pulse reflected by the target. The seeker accuracy will be enhanced by the decoding system, the laser detection time based on the receiving pulses number is reduced, a gate is used to limit the laser pulse width. The model is implemented based on Pulse Repetition Frequency (PRF) technique with two microcontroller units (MCU). MCU1 generates laser pulses with different codes. MCU2 decodes the laser code and locks the system at the specific code. The codes EW selected based on the two selector switches. The system is implemented and tested in Proteus ISIS software. The implementation of the full position determination circuit with the detector is produced. General system for the spot position determination was performed with the laser PRF for incident radiation and the mechanical system for adjusting system at different angles. The system test results show that the system can detect the laser code with only three received pulses based on the narrow gate signal, and good agreement between simulation and measured system performance is obtained.

Keywords: 4-quadrant detector, pulse code detection, laser guided weapons, pulse repetition frequency, ATmega 32 microcontrollers.

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Authors: Majed Omar Al-Dwairi

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This paper evaluate the multilevel modulation for different techniques such as amplitude shift keying (M-ASK), MASK, differential phase shift keying (M-ASK-Bipolar), Quaternary Amplitude Shift Keying (QASK) and Quaternary Polarization-ASK (QPol-ASK) at a total bit rate of 107 Gbps. The aim is to find a costeffective very high speed transport solution. Numerical investigation was performed using Monte Carlo simulations. The obtained results indicate that some modulation formats can be operated at 100Gbps in optical communication systems with low implementation effort and high spectral efficiency.

Keywords: Optical communication, multilevel amplitude shift keying (M-ASK), Differential phase shift keying (DPSK), Quaternary Amplitude Shift Keying (QASK), Quaternary Polarization-ASK (QPol-ASK).

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Authors: Prakash K. Aithal, U. Dinesh Acharya, Rajesh Gopakumar

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Edge is variation of brightness in an image. Edge detection is useful in many application areas such as finding forests, rivers from a satellite image, detecting broken bone in a medical image etc. The paper discusses about finding edge of multiple aerial images in parallel. The proposed work tested on 38 images 37 colored and one monochrome image. The time taken to process N images in parallel is equivalent to time taken to process 1 image in sequential. Message Passing Interface (MPI) and Open Computing Language (OpenCL) is used to achieve task and pixel level parallelism respectively.

Keywords: Edge detection, multicore, GPU, openCL, MPI.

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Authors: N. Chaitawittanun, M. Munlin

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Due to rapid advancement of powerful image processing software, digital images are easy to manipulate and modify by ordinary people. Lots of digital images are edited for a specific purpose and more difficult to distinguish form their original ones. We propose a clustering method to detect a copy-move image forgery of JPEG, BMP, TIFF, and PNG. The process starts with reducing the color of the photos. Then, we use the clustering technique to divide information of measuring data by Hausdorff Distance. The result shows that the purposed methods is capable of inspecting the image file and correctly identify the forgery.

Keywords: Image detection, forgery image, copy-paste.

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Authors: Koushlendra Kumar Singh, Manish Kumar Bajpai, Rajesh K. Pandey

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The edges of low contrast images are not clearly distinguishable to human eye. It is difficult to find the edges and boundaries in it. The present work encompasses a new approach for low contrast images. The Chebyshev polynomial based fractional order filter has been used for filtering operation on an image. The preprocessing has been performed by this filter on the input image. Laplacian of Gaussian method has been applied on preprocessed image for edge detection. The algorithm has been tested on two test images.

Keywords: Chebyshev polynomials, Fractional order differentiator, Laplacian of Gaussian (LoG) method, Low contrast image.

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Authors: Hsiao-Wei Wang, Jung-Tang Huang, Chun-Chiang Lin

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Aptamers are useful tools in microorganism researches, diagnoses, and treatment. Aptamers are specific target molecules formed by oligonucleic acid molecules, and are not decomposed by alcohol. Aptamers used to detect Mycobacterium tuberculosis (MTB) have been proved to have specific affinity to the outer membrane proteins of MTB. This article presents a biosensor chip set with aptamers for early detection of MTB with high specificity and sensitivity, even in very low concentration. Meanwhile, we have already made a modified hydrophobic facial mask module with internal rendering hydrophobic for effectively collecting M. tuberculosis.

Keywords: Aptamers, CNTFET, Mycobacterium tuberculosis, early detection.

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Authors: Yanshuang Zhang, Byungho Jeong

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Data Envelopment Analysis (DEA) is a methodology that computes efficiency values for decision making units (DMU) in a given period by comparing the outputs with the inputs. In many cases, there are some time lag between the consumption of inputs and the production of outputs. For a long-term research project, it is hard to avoid the production lead time phenomenon. This time lag effect should be considered in evaluating the performance of organizations. This paper suggests a model to calculate efficiency values for the performance evaluation problem with time lag. In the experimental part, the proposed methods are compared with the CCR and an existing time lag model using the data set of the 21st century frontier R&D program which is a long-term national R&D program of Korea.

Keywords: DEA, Efficiency, Time Lag

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Authors: Javier Romera, Alberto Justo, Ignacio Fidalgo, Javier Araluce, Joshué Pérez

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Nowadays, individuals with mobility needs face a significant challenge when docking vehicles. In many cases, after parking, they encounter insufficient space to exit, leading to two undesired outcomes: either avoiding parking in that spot or settling for improperly placed vehicles. To address this issue, this paper presents a parking control system employing gestural teleoperation. The system comprises three main phases: capturing body markers, interpreting gestures, and transmitting orders to the vehicle. The initial phase is centered around the MediaPipe framework, a versatile tool optimized for real-time gesture recognition. MediaPipe excels at detecting and tracing body markers, with a special emphasis on hand gestures. Hands detection is done by generating 21 reference points for each hand. Subsequently, after data capture, the project employs the MultiPerceptron Layer (MPL) for in-depth gesture classification. This tandem of MediaPipe’s extraction prowess and MPL’s analytical capability ensures that human gestures are translated into actionable commands with high precision. Furthermore, the system has been trained and validated within a built-in dataset. To prove the domain adaptation, a framework based on the Robot Operating System 2 (ROS2), as a communication backbone, alongside CARLA Simulator, is used. Following successful simulations, the system is transitioned to a real-world platform, marking a significant milestone in the project. This real-vehicle implementation verifies the practicality and efficiency of the system beyond theoretical constructs.

Keywords: Gesture detection, MediaPipe, MultiLayer Perceptron Layer, Robot Operating System.

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Authors: Yi-Feng Su, Chia-Tseng Chen, Hsueh-Lung Liao

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The objective of this research is to develop an advanced driver assistance system characterized with the functions of lane departure warning (LDW), forward collision warning (FCW) and adaptive front-lighting system (AFS). The system is mainly configured a CCD/CMOS camera to acquire the images of roadway ahead in association with the analysis made by an image-processing unit concerning the lane ahead and the preceding vehicles. The input image captured by a camera is used to recognize the lane and the preceding vehicle positions by image detection and DROI (Dynamic Range of Interesting) algorithms. Therefore, the system is able to issue real-time auditory and visual outputs of warning when a driver is departing the lane or driving too close to approach the preceding vehicle unwittingly so that the danger could be prevented from occurring. During the nighttime, in addition to the foregoing warning functions, the system is able to control the bending light of headlamp to provide an immediate light illumination when making a turn at a curved lane and adjust the level automatically to reduce the lighting interference against the oncoming vehicles driving in the opposite direction by the curvature of lane and the vanishing point estimations. The experimental results show that the integrated vehicle image system is robust to most environments such as the lane detection and preceding vehicle detection average accuracy performances are both above 90 %.

Keywords: Lane mark detection, lane departure warning (LDW), dynamic range of interesting (DROI), forward collision warning (FCW), adaptive front-lighting system (AFS).

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Authors: P. Siriarchawatana, K. Leungchavaphongse, N. Covavisaruch, K. Rojananuangnit, P. Boondaeng, N. Panyayingyong

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Glaucoma is a disease that causes visual loss in adults. Glaucoma causes damage to the optic nerve and its overall pathophysiology is still not fully understood. Vasculopathy may be one of the possible causes of nerve damage. Photographic imaging of retinal vessels by fundus camera during eye examination may complement clinical management. This paper presents an innovation for measuring central light reflex width-to-retinal vessel diameter ratio (CRR) from digital retinal photographs. Using our edge detection technique, CRRs from glaucoma and normal eyes were compared to examine differences and associations. CRRs were evaluated on fundus photographs of participants from Mettapracharak (Wat Raikhing) Hospital in Nakhon Pathom, Thailand. Fifty-five photographs from normal eyes and twenty-one photographs from glaucoma eyes were included. Participants with hypertension were excluded. In each photograph, CRRs from four retinal vessels, including arteries and veins in the inferotemporal and superotemporal regions, were quantified using edge detection technique. From our finding, mean CRRs of all four retinal arteries and veins were significantly higher in persons with glaucoma than in those without glaucoma (0.34 vs. 0.32, p < 0.05 for inferotemporal vein, 0.33 vs. 0.30, p < 0.01 for inferotemporal artery, 0.34 vs. 0.31, p < 0.01 for superotemporal vein, and 0.33 vs. 0.30, p < 0.05 for superotemporal artery). From these results, an increase in CRRs of retinal vessels, as quantitatively measured from fundus photographs, could be associated with glaucoma.

Keywords: Glaucoma, retinal vessel, central light reflex, image processing, fundus photograph, edge detection.

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Authors: Florin Gorunescu

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Diagnosis can be achieved by building a model of a certain organ under surveillance and comparing it with the real time physiological measurements taken from the patient. This paper deals with the presentation of the benefits of using Data Mining techniques in the computer-aided diagnosis (CAD), focusing on the cancer detection, in order to help doctors to make optimal decisions quickly and accurately. In the field of the noninvasive diagnosis techniques, the endoscopic ultrasound elastography (EUSE) is a recent elasticity imaging technique, allowing characterizing the difference between malignant and benign tumors. Digitalizing and summarizing the main EUSE sample movies features in a vector form concern with the use of the exploratory data analysis (EDA). Neural networks are then trained on the corresponding EUSE sample movies vector input in such a way that these intelligent systems are able to offer a very precise and objective diagnosis, discriminating between benign and malignant tumors. A concrete application of these Data Mining techniques illustrates the suitability and the reliability of this methodology in CAD.

Keywords: Endoscopic ultrasound elastography, exploratorydata analysis, neural networks, non-invasive cancer detection.

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Authors: J. E. Ortiz, P. Plaza, J. Herrero, I. Cabria, J. L. Blanco, J. Gavilanes, J. I. Escavy, I. López-Cilla, V. Yagüe, C. Pérez, S. Rodríguez, J. Rico, C. Serrano, J. Bernat

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The development of Artificial Intelligence services in mining processes, specifically in aggregate quarries, is facilitating automation and improving numerous aspects of operations. Ultimately, AI is transforming the mining industry by improving efficiency, safety and sustainability. With the ability to analyze large amounts of data and make autonomous decisions, AI offers great opportunities to optimize mining operations and maximize the economic and social benefits of this vital industry. Within the framework of the European DIGIECOQUARRY project, various services were developed for the identification of material quality, production estimation, detection of anomalies and prediction of consumption and production automatically with good results.

Keywords: Aggregates, artificial intelligence, automatization, mining operations.

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Authors: Aziza Benaboud, Alfred Rufer

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In this paper the authors propose a flexible electronic solution, to improve the energetic efficiency of a thermo plant. This is achieved by replacing the mechanical gear box, placed traditionally between a gas turbine and a synchronous generator; by a power electronic converter. After reminding problematic of gear boxes and interest of a proposed electronic solution in high power plants, the authors describe a new control strategy for an indirect frequency converter, which is characterized by its high efficiency due to the use of SWM: Square Wave Modulation. The main advantage of this mode is the quasi absence of switching losses. A control method is also proposed to resolve some problems incurred by using square wave modulation, in particular to reduce the harmonics distortion of the output inverter voltage and current. Simulation examples as well as experimental results are included.

Keywords: Angle shift, high efficiency, indirect converter, gas turbine, NPC three level converter, square wave modulation SWM, switching angle.

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Authors: Sheetal Chavan, P. J. Kulkarni, Vivek Shanbhag

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Although achieving zero-defect software release is practically impossible, software industries should take maximum care to detect defects/bugs well ahead in time allowing only bare minimums to creep into released version. This is a clear indicator of time playing an important role in the bug detection. In addition to this, software quality is the major factor in software engineering process. Moreover, early detection can be achieved only through static code analysis as opposed to conventional testing. BugCatcher.Net is a static analysis tool, which detects bugs in .NET® languages through MSIL (Microsoft Intermediate Language) inspection. The tool utilizes a Parser based on Finite State Automata to carry out bug detection. After being detected, bugs need to be corrected immediately. BugCatcher.Net facilitates correction, by proposing a corrective solution for reported warnings/bugs to end users with minimum side effects. Moreover, the tool is also capable of analyzing the bug trend of a program under inspection.

Keywords: Dependence, Early solution, Finite State Automata, Grammar, Late solution, Parser State Transition Diagram, StaticProgram Analysis.

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Authors: Madina Hamiane, May Hashim Ali

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This paper presents the processing and analysis of ECG signals. The study is based on wavelet transform and uses exclusively the MATLAB environment. This study includes removing Baseline wander and further de-noising through wavelet transform and metrics such as signal-to noise ratio (SNR), Peak signal-to-noise ratio (PSNR) and the mean squared error (MSE) are used to assess the efficiency of the de-noising techniques. Feature extraction is subsequently performed whereby signal features such as heart rate, rise and fall levels are extracted and the QRS complex was detected which helped in classifying the ECG signal. The classification is the last step in the analysis of the ECG signals and it is shown that these are successfully classified as Normal rhythm or Abnormal rhythm.  The final result proved the adequacy of using wavelet transform for the analysis of ECG signals.

Keywords: ECG Signal, QRS detection, thresholding, wavelet decomposition, feature extraction.

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Authors: H. Kaatuzian, M. Sedghi, S. Khatami

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In this paper, by exploiting a single semiconductor optical amplifier-Mach Zehnder Interferometer (SOA-MZI), an integratable all-optical flip-flop (AOFF) is proposed. It is composed of a SOA-MZI with a bidirectional coupler at the output. Output signals of both bar and crossbar of the SOA-MZI is fed back to SOAs located in the arms of the Mach-Zehnder Interferometer (MZI). The injected photon-rates to the SOAs are modulated by feedback signals in order to form optical flip-flop. According to numerical analysis, Gaussian optical pulses with the energy of 15.2 fJ and 20 ps duration with the full width at half-maximum criterion, can switch the states of the SR-AOFF. Also simulation results show that the SR-AOFF has the contrast ratio of 8.5 dB between two states with the transition time of nearly 20 ps.

Keywords: All Optical, Flip-Flop, Mach-Zehnder Interferometer (MZI), Semiconductor Optical Amplifier (SOA).

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Authors: Hayder Natiq Jasem, Zuriati Ahmad Zukarnain, Mohamed Othman, Shamala Subramaniam

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Congestion control is one of the fundamental issues in computer networks. Without proper congestion control mechanisms there is the possibility of inefficient utilization of resources, ultimately leading to network collapse. Hence congestion control is an effort to adapt the performance of a network to changes in the traffic load without adversely affecting users perceived utilities. AIMD (Additive Increase Multiplicative Decrease) is the best algorithm among the set of liner algorithms because it reflects good efficiency as well as good fairness. Our control model is based on the assumption of the original AIMD algorithm; we show that both efficiency and fairness of AIMD can be improved. We call our approach is New AIMD. We present experimental results with TCP that match the expectation of our theoretical analysis.

Keywords: Congestion control, Efficiency, Fairness, TCP, AIMD.

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Authors: Mahanijah Md Kamal., Dingli Yu

Abstract:

This paper presents a new method of fault detection and isolation (FDI) for polymer electrolyte membrane (PEM) fuel cell (FC) dynamic systems under an open-loop scheme. This method uses a radial basis function (RBF) neural network to perform fault identification, classification and isolation. The novelty is that the RBF model of independent mode is used to predict the future outputs of the FC stack. One actuator fault, one component fault and three sensor faults have been introduced to the PEMFC systems experience faults between -7% to +10% of fault size in real-time operation. To validate the results, a benchmark model developed by Michigan University is used in the simulation to investigate the effect of these five faults. The developed independent RBF model is tested on MATLAB R2009a/Simulink environment. The simulation results confirm the effectiveness of the proposed method for FDI under an open-loop condition. By using this method, the RBF networks able to detect and isolate all five faults accordingly and accurately.

Keywords: Polymer electrolyte membrane fuel cell, radial basis function neural networks, fault detection, fault isolation.

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Authors: Farhat Hajer, Khir Tahar, Cherni Rafik, Dakhli Radhouen, Ammar Ben Brahim

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This paper presents the energy and exergy optimization of a real gas turbine power plant performance of 100 MW of power, installed in the South East of Tunisia. A simulation code is established using the EES (Engineering Equation Solver) software. The parameters considered are those of the actual operating conditions of the gas turbine thermal power station under study. The results show that thermal and exergetic efficiency decreases with the increase of the ambient temperature. Air excess has an important effect on the thermal efficiency. The emission of NOx rises in the summer and decreases in the winter. The obtained rates of NOx are compared with measurements results.

Keywords: Efficiency, exergy, gas turbine, temperature.

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Authors: Petra Balla, Gabor Manhertz, Akos Antal

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Nowadays spinal deformities are very frequent problems among teenagers. Scheuermann disease is a one dimensional deformity of the spine, but it has prevalence over 11% of the children. A traditional technology, the moiré method was used by us for screening and diagnosing this type of spinal deformity. A LabVIEW program has been developed to evaluate the moiré pictures of patients with Scheuermann disease. Two different solutions were tested in this computer program, the extreme and the inflexion point calculation methods. Effects using these methods were compared and according to the results both solutions seemed to be appropriate. Statistical results showed better efficiency in case of the extreme search method where the average difference was only 6,09⁰.

Keywords: Spinal deformity, picture evaluation, moiré method, Scheuermann disease, curve detection, moiré topography.

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Authors: Yong Ho Shim, Ki Youn Kim, Ji Yeon Cho, Jin Kyung Park, Bong Gyou Lee

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This study considers priorities of primary goals to increase policy efficiency of Green ICT. Recently several studies have been published that address how IT is linked to climate change. However, most of the previous studies are limited to Green ICT industrial statute and policy directions. This paper present Green ICT policy making processes systematically. As a result of the analysis of Korean Green ICT policy, the following emerged as important to accomplish for Green ICT policy: eco-friendliness, technology evolution, economic efficiency, energy efficiency, and stable supply of energy. This is an initial study analyzing Green ICT policy, which provides an academic framework that can be used a guideline to establish Green ICT policy.

Keywords: AHP(Analytic Hierarchy Process), Case Study, Green ICT, Policy Priority

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Authors: Kavita Khairnar, Shikha Nema

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DS-CDMA system is well known wireless technology. This system suffers from MAI (Multiple Access Interference) caused by Direct Sequence users. Multi-User Detection schemes were introduced to detect the users- data in presence of MAI. This paper focuses on linear multi-user detection schemes used for data demodulation. Simulation results depict the performance of three detectors viz-conventional detector, Decorrelating detector and Subspace MMSE (Minimum Mean Square Error) detector. It is seen that the performance of these detectors depends on the number of paths and the length of Gold code used.

Keywords: Cross Correlation Matrix, MAI, Multi-UserDetection, Multipath Effect.

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Authors: M. Baryshev, D.Vainauska, S. Kozireva, A.Karpovs

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Liposomal magnetofection is the most powerful nonviral method for the nucleic acid delivery into the cultured cancer cells and widely used for in vitro applications. Use of the static magnetic field condition may result in non-uniform distribution of aggregate complexes on the surface of cultured cells. To prevent this, we developed the new device which allows to concentrate aggregate complexes under dynamic magnetic field, assisting more contact of these complexes with cellular membrane and, possibly, stimulating endocytosis. Newly developed device for magnetofection under dynamic gradient magnetic field, “DynaFECTOR", was used to compare transfection efficiency of human liver hepatocellular carcinoma cell line HepG2 with that obtained by lipofection and magnetofection. The effect of two parameters on transfection efficiency, incubation time under dynamic magnetic field and rotation frequency of magnet, was estimated. Liposomal magnetofection under dynamic gradient magnetic field showed the highest transfection efficiency for HepG2 cells.

Keywords: Dynamic magnetic field, Lipofection, Magnetofection

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Authors: Arvind Srivastav, Tarun Kanti Bhattacharyya

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The north-eastern, Himalayan, and Eastern Ghats Belt of India comprise of earthquake-prone, remote, and hilly terrains. Earthquakes have caused enormous damages in these regions in the past. A wireless sensor network based earthquake early warning system (EEWS) is being developed to mitigate the damages caused by earthquakes. It consists of sensor nodes, distributed over the region, that perform majority voting of the output of the seismic sensors in the vicinity, and relay a message to a base station to alert the residents when an earthquake is detected. At the heart of the EEWS is a low-power two-stage seismic sensor that continuously tracks seismic events from incoming three-axis accelerometer signal at the first-stage, and, in the presence of a seismic event, triggers the second-stage P-wave detector that detects the onset of P-wave in an earthquake event. The parameters of the P-wave detector have been optimized for minimizing detection time and maximizing the accuracy of detection.Working of the sensor scheme has been verified with seven earthquakes data retrieved from IRIS. In all test cases, the scheme detected the onset of P-wave accurately. Also, it has been established that the P-wave onset detection time reduces linearly with the sampling rate. It has been verified with test data; the detection time for data sampled at 10Hz was around 2 seconds which reduced to 0.3 second for the data sampled at 100Hz.

Keywords: Earthquake early warning system, EEWS, STA/LTA, polarization, wavelet, event detector, P-wave detector.

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Authors: R. F. Ajayi, U. Sidwaba, U. Feleni, S. F. Douman, E. Nxusani, L. Wilson, C. Rassie, O. Tovide, P. G. L. Baker, S. L. Vilakazi, R. Tshikhudo, E. I. Iwuoha

Abstract:

Pyrazinamide (PZA) is among the first-line pro-drugs  in the tuberculosis (TB) combination chemotherapy used to treat  Mycobacterium tuberculosis. Numerous reports have suggested that  hepatotoxicity due to pyrazinamide in patients is due to inappropriate  dosing. It is, therefore necessary to develop sensitive and reliable  techniques for determining the PZA metabolic profile of diagnosed  patients promptly and at point-of-care. This study reports the  determination of PZA based on nanobiosensor systems developed  from disuccinimidyl octanedioate modified Cytochrome P450-2E1  (CYP2E1) electrodeposited on gold substrates derivatised with  (poly(8-anilino-1-napthalene sulphonic acid) PANSA/PVP-AgNPs  nanocomposites. The rapid and sensitive amperometric PZA  detection gave a dynamic linear range of 2µM to 16µM revealing a  limit of detection of 0.044µM and a sensitivity of 1.38µA/µM. The  Michaelis-Menten parameters; KM, KM app and IMAX were calculated to  be 6.0µM, 1.41µM and 1.51x10-6 A, respectively, indicating a  nanobiosensor suitable for use in serum.

Keywords: Cytochrome P450-2E1, Disuccinimidyl octanedioate, Pyrazinamide, Tuberculosis.

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