Search results for: detection task

Authors: Majed Omar Al-Dwairi

Abstract:

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: Andrey V. Timofeev, Viktor M. Denisov

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A robust sequential nonparametric method is proposed for adaptation to background noise parameters for real-time. The distribution of background noise was modelled like to Huber contamination mixture. The method is designed to operate as an adaptation-unit, which is included inside a detection subsystem of an integrated multichannel monitoring system. The proposed method guarantees the given size of a nonasymptotic confidence set for noise parameters. Properties of the suggested method are rigorously proved. The proposed algorithm has been successfully tested in real conditions of a functioning C-OTDR monitoring system, which was designed to monitor railways.

Keywords: Guaranteed estimation, multichannel monitoring systems, non-asymptotic confidence set, contamination mixture.

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Authors: Clio G. Vossou, Ioannis N. Koukoulis, Christopher G. Provatidis

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The present work encounters the solution of the defect identification problem with the use of an evolutionary algorithm combined with a simplex method. In more details, a Matlab implementation of Genetic Algorithms is combined with a Simplex method in order to lead to the successful identification of the defect. The influence of the location and the orientation of the depressed ellipsoidal flaw was investigated as well as the use of different amount of static data in the cost function. The results were evaluated according to the ability of the simplex method to locate the global optimum in each test case. In this way, a clear impression regarding the performance of the novel combination of the optimization algorithms, and the influence of the geometrical parameters of the flaw in defect identification problems was obtained.

Keywords: Defect identification, genetic algorithms, optimization.

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Authors: Tsubasa Seto, Kentaro Nagata, Kazushige Magatani

Abstract:

SEMG (Surface Electromyogram) is one of the bio-signals and is generated from the muscle. And there are many research results that use forearm EMG to detect hand motions. In this paper, we will talk about our developed the robot hand system that can control grasping power by SEMG. In our system, we suppose that muscle power is proportional to the amplitude of SEMG. The power is estimated and the grip power of a robot hand is able to be controlled using estimated muscle power in our system. In addition, to perform a more precise control can be considered to build a closed loop feedback system as an object to a subject to pressure from the edge of hand. Our objectives of this study are the development of a method that makes perfect detection of the hand grip force possible using SEMG patterns, and applying this method to the man-machine interface.

Keywords: SEMG, multi electrode, robot hand, power control

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Authors: Muhibul Haque Bhuyan, Sher Shermin Azmiri Khan

Abstract:

At present, it is an imperative and stimulating task to grow the concepts and skills of undergraduate students in any course. Educators must build up students' higher-order complex and critical thinking abilities. But many of them find it difficult to assess and evaluate these abilities of students who undertake their courses during undergraduate studies. In this research work, a simple assessment and evaluation process for the electrical circuit course of the undergraduate Electrical and Electronic Engineering (EEE) program is reported using the Outcome-Based Education (OBE) approach. The methodology of the work, course contents design, course outcomes (COs) preparation and mapping it with program outcomes (POs), question setting following Bloom's taxonomy, assessment strategy of the students, CO and PO evaluation records, statistics, and charts have been reported for a student-cohort of electrical circuit course taken in Spring 2019 Semester at EEE Department of Southeast University (SEU). It is found that the benchmark fixed by the course instructor has been achieved by the students of that course through CO assessment and evaluation. Recommendations of the course teacher for further quality enhancement based on CO achievement are also presented.

Keywords: OBE, COs, POs, assessment and evaluation, electrical circuit course.

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Authors: Sung Wook Yun, Yun Jong Choi, Kyong-min Lee, Poogyeon Park*

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Repetitive systems stand for a kind of systems that perform a simple task on a fixed pattern repetitively, which are widely spread in industrial fields. Hence, many researchers have been interested in those systems, especially in the field of iterative learning control (ILC). In this paper, we propose a finite-horizon tracking control scheme for linear time-varying repetitive systems with uncertain initial conditions. The scheme is derived both analytically and numerically for state-feedback systems and only numerically for output-feedback systems. Then, it is extended to stable systems with input constraints. All numerical schemes are developed in the forms of linear matrix inequalities (LMIs). A distinguished feature of the proposed scheme from the existing iterative learning control is that the scheme guarantees the tracking performance exactly even under uncertain initial conditions. The simulation results demonstrate the good performance of the proposed scheme.

Keywords: Finite time horizon, linear matrix inequality (LMI), repetitive system, uncertain initial condition.

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Authors: T. Bovornvirakit, K. Viravaidya

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Acute kidney injury (AKI) is a new worldwide public health problem. A diagnosis of this disease using creatinine is still a problem in clinical practice. Therefore, a measurement of biomarkers responsible for AKI has received much attention in the past couple years. Cytokine interleukin-18 (IL-18) was reported as one of the early biomarkers for AKI. The most commonly used method to detect this biomarker is an immunoassay. This study used a planar platform to perform an immunoassay using fluorescence for detection. In this study, anti-IL-18 antibody was immobilized onto a microscope slide using a covalent binding method. Make-up samples were diluted at the concentration between 10 to 1000 pg/ml to create a calibration curve. The precision of the system was determined using a coefficient of variability (CV), which was found to be less than 10%. The performance of this immunoassay system was compared with the measurement from ELISA.

Keywords: Acute kidney injury, Acute renal failure, Antibody immobilization, Interleukin-18

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Authors: Youngyoon Lee, Dahae Chong, Myungsoo Lee, Seongho Chae, Seokho Yoon

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This paper proposes two novel schemes for pilot-aided integer frequency offset (IFO) estimation in orthogonal frequency division multiplexing (OFDM)-based digital video broadcastingterrestrial (DVB-T) systems. The conventional scheme proposed for estimating the IFO uses only partial information of combinations that pilots can provide, which stems from a rigorous assumption that the channel responses of pilots used for estimating the IFO change very rapidly. Thus, in this paper, we propose the novel IFO estimation schemes exploiting all information of combinations that pilots can provide to improve the performance of IFO estimation. The simulation results show that the proposed schemes are highly accurate in terms of the IFO detection probability.

Keywords: OFDM, DVB-T, pilot, IFO, estimation

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Authors: Nikhat Nawaz, S. Srinivasulu, P. Kesava Rao

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Feature extraction plays an important role in many remote sensing applications. Automatic extraction of water bodies is of great significance in many remote sensing applications like change detection, image retrieval etc. This paper presents a procedure for automatic extraction of water information from remote sensing images. The algorithm uses the relative location of R color component of the chromaticity diagram. This method is then integrated with the effectiveness of the spatial scale transformation of whole method. The whole method is based on water index fitted from spectral library. Experimental results demonstrate the improved accuracy and effectiveness of the integrated method for automatic extraction of water bodies.

Keywords: Chromaticity, Feature Extraction, Remote Sensing, Spectral library, Water Index.

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Authors: Sang Hoon Lee, Jong Sue Bae, Taewan Kim, Jin Mo Song, Jong Ju Kim

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Image target detection and tracking methods based on target information such as intensity, shape model, histogram and target dynamics have been proven to be robust to target model variations and background clutters as shown by recent researches. However, no definitive answer has been given to occluded target by counter measure or limited field of view(FOV). In this paper, we will present a novel tracking method using filtering and computational geometry. This paper has two central goals: 1) to deal with vulnerable target measurements; and 2) to maintain target tracking out of FOV using non-target-originated information. The experimental results, obtained with airborne images, show a robust tracking ability with respect to the existing approaches. In exploring the questions of target tracking, this paper will be limited to consideration of airborne image.

Keywords: Tracking, Computational geometry, Homography, Filter

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Authors: J. Berčík, A. Mravcová, J. Gálová, K. Neomániová

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In an era when everything is increasingly digital, consumers are always looking for new options in solutions to their everyday needs. In this context, mobile apps are developing at an exponential pace. One of the fastest growing segments of mobile technologies is, obviously, e-commerce. It can be predicted that mobile commerce will record nearly three times the global growth of e-commerce across all platforms, which indicates its importance in the given segment. The current coronavirus pandemic is also changing many of the existing paradigms both socially, economically, and technologically, which has a major impact on changing consumer behavior and the emphasis on simplification and clarity of mobile solutions. This is the area that User Experience (UX) and User Interface (UI) designers deal with. Their task is to design a sufficiently attractive and interesting solution that will be available on all mobile devices and at the same time will be easy enough for the customer/visitor to get to the destination or to get the necessary information in a few clicks. The basis for changes in UX design can now be obtained not only through online analytical tools, but also through neuromarketing, especially in the case of mobile devices. The paper highlights possibilities for testing UX design applications on mobile devices using a special platform that combines a stationary eye camera (eye tracking) and facial analysis (facial coding).

Keywords: Emotions, mobile design, user experience, visual attention.

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Authors: Eckhard M. Ammann

Abstract:

Knowledge development in companies relies on knowledge-intensive business processes, which are characterized by a high complexity in their execution, weak structuring, communication-oriented tasks and high decision autonomy, and often the need for creativity and innovation. A foundation of knowledge development is provided, which is based on a new conception of knowledge and knowledge dynamics. This conception consists of a three-dimensional model of knowledge with types, kinds and qualities. Built on this knowledge conception, knowledge dynamics is modeled with the help of general knowledge conversions between knowledge assets. Here knowledge dynamics is understood to cover all of acquisition, conversion, transfer, development and usage of knowledge. Through this conception we gain a sound basis for knowledge management and development in an enterprise. Especially the type dimension of knowledge, which categorizes it according to its internality and externality with respect to the human being, is crucial for enterprise knowledge management and development, because knowledge should be made available by converting it to more external types. Built on this conception, a modeling approach for knowledgeintensive business processes is introduced, be it human-driven,e-driven or task-driven processes. As an example for this approach, a model of the creative activity for the renewal planning of a product is given.

Keywords: Conception of knowledge, knowledge dynamics, modeling notation, knowledge-intensive business processes.

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Authors: Miloš Šeda

Abstract:

Finding the shortest path between two positions is a fundamental problem in transportation, routing, and communications applications. In robot motion planning, the robot should pass around the obstacles touching none of them, i.e. the goal is to find a collision-free path from a starting to a target position. This task has many specific formulations depending on the shape of obstacles, allowable directions of movements, knowledge of the scene, etc. Research of path planning has yielded many fundamentally different approaches to its solution, mainly based on various decomposition and roadmap methods. In this paper, we show a possible use of visibility graphs in point-to-point motion planning in the Euclidean plane and an alternative approach using Voronoi diagrams that decreases the probability of collisions with obstacles. The second application area, investigated here, is focused on problems of finding minimal networks connecting a set of given points in the plane using either only straight connections between pairs of points (minimum spanning tree) or allowing the addition of auxiliary points to the set to obtain shorter spanning networks (minimum Steiner tree).

Keywords: motion planning, spanning tree, Steiner tree, Delaunay triangulation, Voronoi diagram.

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Authors: Nasir Yusoff, Ahmad Adamu Adamu, Tahamina Begum, Faruque Reza

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The P300 from Event related potential (ERP) explains the psycho-physiological phenomenon in human body. The present study aims to identify the differences of amplitude and latency of P300 component from auditory stimuli, between ambiversion and extraversion types of personality. Ambivert (N=20) and extravert (N=20) undergoing ERP recording at the Hospital Universiti Sains Malaysia (HUSM) laboratory. Electroencephalogram data was recorded with oddball paradigm, counting auditory standard and target tones, from nine electrode sites (Fz, Cz, Pz, T3, T4, T5, T6, P3 and P4) by using the 128 HydroCel Geodesic Sensor Net. The P300 latency of the target tones at all electrodes were insignificant. Similarly, the P300 latency of the standard tones were also insignificant except at Fz and T3 electrode. Likewise, the P300 amplitude of the target and standard tone in all electrode sites were insignificant. Extravert and ambivert indicate similar characteristic in cognition processing from auditory task.

Keywords: Amplitude, Event Related Potential, P300 Component, Latency.

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Authors: Mohammed Qasim, Kyoung-Dae Kim

Abstract:

In this paper, we present the design of the super-ellipsoidal potential function (SEPF), that can be used for autonomous collision avoidance of an unmanned aerial vehicle (UAV) in a 3-dimensional space. In the design of SEPF, we have the full control over the shape and size of the potential function. In particular, we can adjust the length, width, height, and the amount of flattening at the tips of the potential function so that the collision avoidance motion vector generated from the potential function can be adjusted accordingly. Based on the idea of the SEPF, we also propose an approach for the local autonomy of a UAV for its collision avoidance when the UAV is teleoperated by a human operator. In our proposed approach, a teleoperated UAV can not only avoid collision autonomously with other surrounding objects but also track the operator’s control input as closely as possible. As a result, an operator can always be in control of the UAV for his/her high-level guidance and navigation task without worrying too much about the UAVs collision avoidance while it is being teleoperated. The effectiveness of the proposed approach is demonstrated through a human-in-the-loop simulation of quadrotor UAV teleoperation using virtual robot experimentation platform (v-rep) and Matlab programs.

Keywords: Artificial potential function, autonomy, collision avoidance, teleoperation, quadrotor, UAV.

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Authors: A. Belayadi, A. Mougari, L. Ait-Gougam, F. Mekideche-Chafa

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The artificial neural network is one of the interesting techniques that have been advantageously used to deal with modeling problems. In this study, the computing with artificial neural network (CANN) is proposed. The model is applied to modulate the information processing of one-dimensional task. We aim to integrate a new method which is based on a new coding approach of generating the input-output mapping. The latter is based on increasing the neuron unit in the last layer. Accordingly, to show the efficiency of the approach under study, a comparison is made between the proposed method of generating the input-output set and the conventional method. The results illustrated that the increasing of the neuron units, in the last layer, allows to find the optimal network’s parameters that fit with the mapping data. Moreover, it permits to decrease the training time, during the computation process, which avoids the use of computers with high memory usage.

Keywords: Neural network computing, information processing, input-output mapping, training time, computers with high memory.

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Authors: A. Amrani, O. Allali, A. Ben Hamida, F. Defrance, S. Morland, E. Pineau, T. Lacroix

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The energy planning process is a very complex task that involves several stakeholders and requires the consideration of several local and global factors and constraints. In order to optimize and simplify this process, we propose a tool-based iterative approach applied to district heating planning. We build our tool with the collaboration of a French territory using actual district data and implementing the European incentives. We set up an iterative process including data visualization and analysis, identification and extraction of information related to the area concerned by the operation, design of sustainable planning scenarios leveraging local renewable and recoverable energy sources, and finally, the evaluation of scenarios. The last step is performed by a dynamic digital twin replica of the city. Territory’s energy experts confirm that the tool provides them with valuable support towards sustainable energy planning.

Keywords: Climate change, data management, decision support, digital twin, district heating, energy planning, renewables, smart city.

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Authors: Souâd Demigha

Abstract:

Early detection of breast cancer is considered as a major public health issue. Breast cancer screening is not generalized to the entire population due to a lack of resources, staff and appropriate tools. Systematic screening can result in a volume of data which can not be managed by present computer architecture, either in terms of storage capabilities or in terms of exploitation tools. We propose in this paper to design and develop a data warehouse system in radiology-senology (DWRS). The aim of such a system is on one hand, to support this important volume of information providing from multiple sources of data and images and for the other hand, to help assist breast cancer screening in diagnosis, education and research.

Keywords: Breast cancer screening, data warehouse, diagnosis, education, research.

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Authors: V. Geetha, K. S. Aprameya

Abstract:

Early diagnosis of dental caries is essential for maintaining dental health. In this paper, method for diagnosis of dental caries is proposed using Laplacian filter, adaptive thresholding, texture analysis and Support Vector Machine (SVM) classifier. Analysis of the proposed method is compared with Otsu thresholding, watershed segmentation and active contouring method. Adaptive thresholding has comparatively better performance with 96.9% accuracy and 96.1% precision. The results are validated using statistical method, two-way ANOVA, at significant level of 5%, that shows the interaction of proposed method on performance parameter measures are significant. Hence the proposed technique could be used for detection of dental caries in automated computer assisted diagnosis system.

Keywords: Computer assisted diagnosis, dental caries, dental radiography, image segmentation.

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Authors: Seung You Na, Daejung Shin, Jin Young Kim, Seong-Joon Baek, Bae-Ho Lee

Abstract:

Recently there has been a growing interest in the field of bio-mimetic robots that resemble the behaviors of an insect or an aquatic animal, among many others. One of various bio-mimetic robot applications is to explore pipelines, spotting any troubled areas or malfunctions and reporting its data. Moreover, the robot is able to prepare for and react to any abnormal routes in the pipeline. Special types of mobile robots are necessary for the pipeline monitoring tasks. In order to move effectively along a pipeline, the robot-s movement will resemble that of insects or crawling animals. When situated in massive pipelines with complex routes, the robot places fixed sensors in several important spots in order to complete its monitoring. This monitoring task is to prevent a major system failure by preemptively recognizing any minor or partial malfunctions. Areas uncovered by fixed sensors are usually impossible to provide real-time observation and examination, and thus are dependent on periodical offline monitoring. This paper proposes a monitoring system that is able to monitor the entire area of pipelines–with and without fixed sensors–by using the bio-mimetic robot.

Keywords: Bio-mimetic robots, Plant pipes monitoring, Mobile and active monitoring.

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Authors: Gunther Reinhart, Marwan Radi

Abstract:

Since the 1940s, many promising telepresence research results have been obtained. However, telepresence technology still has not reached industrial usage. As human intelligence is necessary for successful execution of most manual assembly tasks, the ability of the human is hindered in some cases, such as the assembly of heavy parts of small/medium lots or prototypes. In such a case of manual assembly, the help of industrial robots is mandatory. The telepresence technology can be considered as a solution for performing assembly tasks, where the human intelligence and haptic sense are needed to identify and minimize the errors during an assembly process and a robot is needed to carry heavy parts. In this paper, preliminary steps to integrate the telepresence technology into industrial robot systems are introduced. The system described here combines both, the human haptic sense and the industrial robot capability to perform a manual assembly task remotely using a force feedback joystick. Mapping between the joystick-s Degrees of Freedom (DOF) and the robot-s ones are introduced. Simulation and experimental results are shown and future work is discussed.

Keywords: Assembly, Force Feedback, Industrial Robot, Teleassembly, Telepresence.

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Authors: Madina Hamiane, May Hashim Ali

Abstract:

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: J. Umamaheswari, G. Radhamani

Abstract:

This paper describes about the process of recognition and classification of brain images such as normal and abnormal based on PSO-SVM. Image Classification is becoming more important for medical diagnosis process. In medical area especially for diagnosis the abnormality of the patient is classified, which plays a great role for the doctors to diagnosis the patient according to the severeness of the diseases. In case of DICOM images it is very tough for optimal recognition and early detection of diseases. Our work focuses on recognition and classification of DICOM image based on collective approach of digital image processing. For optimal recognition and classification Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Support Vector Machine (SVM) are used. The collective approach by using PSO-SVM gives high approximation capability and much faster convergence.

Keywords: Recognition, classification, Relaxed Median Filter, Adaptive thresholding, clustering and Neural Networks

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Authors: Vaibhav Kant Singh, Vijay Shah, Yogendra Kumar Jain, Anupam Shukla, A.S. Thoke, Vinay KumarSingh, Chhaya Dule, Vivek Parganiha

Abstract:

Data mining, which is the exploration of knowledge from the large set of data, generated as a result of the various data processing activities. Frequent Pattern Mining is a very important task in data mining. The previous approaches applied to generate frequent set generally adopt candidate generation and pruning techniques for the satisfaction of the desired objective. This paper shows how the different approaches achieve the objective of frequent mining along with the complexities required to perform the job. This paper will also look for hardware approach of cache coherence to improve efficiency of the above process. The process of data mining is helpful in generation of support systems that can help in Management, Bioinformatics, Biotechnology, Medical Science, Statistics, Mathematics, Banking, Networking and other Computer related applications. This paper proposes the use of both upward and downward closure property for the extraction of frequent item sets which reduces the total number of scans required for the generation of Candidate Sets.

Keywords: Data Mining, Candidate Sets, Frequent Item set, Pruning.

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Authors: J.W. Xiang, M. Liang

Abstract:

This paper presents a method to detect multiple cracks based on frequency information. When a structure is subjected to dynamic or static loads, cracks may develop and the modal frequencies of the cracked structure may change. To detect cracks in a structure, we construct a high precision wavelet finite element (EF) model of a certain structure using the B-spline wavelet on the interval (BSWI). Cracks can be modeled by rotational springs and added to the FE model. The crack detection database will be obtained by solving that model. Then the crack locations and depths can be determined based on the frequency information from the database. The performance of the proposed method has been numerically verified by a rotor example.

Keywords: Rotor, frequency measurement, multiple cracks, wavelet finite element method, identification.

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Authors: A. J. Al-Shareef, E. A. Mohamed, E. Al-Judaibi

Abstract:

Load forecasting has become in recent years one of the major areas of research in electrical engineering. Most traditional forecasting models and artificial intelligence neural network techniques have been tried out in this task. Artificial neural networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This article presents the development of an ANN-based short-term load forecasting model with improved generalization technique for the Regional Power Control Center of Saudi Electricity Company, Western Operation Area (SEC-WOA). The proposed ANN is trained with weather-related data and historical electric load-related data using the data from the calendar years 2001, 2002, 2003, and 2004 for training. The model tested for one week at five different seasons, typically, winter, spring, summer, Ramadan and fall seasons, and the mean absolute average error for one hour-ahead load forecasting found 1.12%.

Keywords: Artificial neural networks, short-term load forecasting, back propagation.

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Authors: Mazliham Mohd Su'ud, Pierre Loonis, Idris Abu Seman

Abstract:

This paper deals with the extraction of information from the experts to automatically identify and recognize Ganoderma infection in oil palm stem using tomography images. Expert-s knowledge are used as rules in a Fuzzy Inference Systems to classify each individual patterns observed in he tomography image. The classification is done by defining membership functions which assigned a set of three possible hypotheses : Ganoderma infection (G), non Ganoderma infection (N) or intact stem tissue (I) to every abnormalities pattern found in the tomography image. A complete comparison between Mamdani and Sugeno style,triangular, trapezoids and mixed triangular-trapezoids membership functions and different methods of aggregation and defuzzification is also presented and analyzed to select suitable Fuzzy Inference System methods to perform the above mentioned task. The results showed that seven out of 30 initial possible combination of available Fuzzy Inference methods in MATLAB Fuzzy Toolbox were observed giving result close to the experts estimation.

Keywords: Fuzzy Inference Systems, Tomography analysis, Modelizationof expert's information, Ganoderma Infection pattern recognition

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Authors: C. I. L. Justino, L. I. B. Silva, K. Duarte, A. C. Freitas, T. A. P. Rocha-Santos, A. C. Duarte

Abstract:

This work proposes an optical fiber system (OF) for sensing various volatile organic compounds (VOCs) in human breath for the diagnosis of some metabolic disorders as a non-invasive methodology. The analyzed VOCs are alkanes (i.e., ethane, pentane, heptane, octane, and decane), and aromatic compounds (i.e., benzene, toluene, and styrene). The OF displays high analytical performance since it provides near real-time responses, rapid analysis, and low instrumentation costs, as well as it exhibits useful linear range and detection limits; the developed OF sensor is also comparable to a reference methodology (gas chromatography-mass spectrometry) for the eight tested VOCs.

Keywords: Breath analysis, gas chromatography-mass spectrometry, optical fiber sensor, volatile organic compounds

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Authors: Cem Karacal, Sohyung Cho, William Yu

Abstract:

In metal cutting industries, mathematical/statistical models are typically used to predict tool replacement time. These off-line methods usually result in less than optimum replacement time thereby either wasting resources or causing quality problems. The few online real-time methods proposed use indirect measurement techniques and are prone to similar errors. Our idea is based on identifying the optimal replacement time using an electronic nose to detect the airborne compounds released when the tool wear reaches to a chemical substrate doped into tool material during the fabrication. The study investigates the feasibility of the idea, possible doping materials and methods along with data stream mining techniques for detection and monitoring different phases of tool wear.

Keywords: Tool condition monitoring, cutting tool replacement, data stream mining, e-Nose.

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Authors: A. Boveiri Monji, H. Yousefnia, S. Zolghadri, B. Salimi

Abstract:

The main goal of this paper was to make use of green reagents as a substitute of perilous synthetic reagents and organic solvents for spectrophotometric determination of hafnium(IV). The extracts taken from six different kinds of tree leaves including Acer negundo, Ficus carica, Cerasus avium, Chimonanthus, Salix babylonica and Pinus brutia, were applied as green reagents for the experiments. In 6-M hydrochloric acid, hafnium reacted with the reagent to form a yellow product and showed maximum absorbance at 421 nm. Among tree leaves, Chimonanthus showed satisfactory results with a molar absorptivity value of 0.61 × 10⁴ l mol^-1 cm^-1 and the method was linear in the 0.3-9 µg mL ^-1 concentration range. The detection limit value was 0.064 µg mL^-1. The proposed method was simple, low cost, clean, and selective.

Keywords: Spectrophotometric determination, tree leaves, synthetic reagents, hafnium.

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