Search results for: Design Algorithm

Authors: M.K. Bhuyan, Aragala Jagan.

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Current image-based individual human recognition methods, such as fingerprints, face, or iris biometric modalities generally require a cooperative subject, views from certain aspects, and physical contact or close proximity. These methods cannot reliably recognize non-cooperating individuals at a distance in the real world under changing environmental conditions. Gait, which concerns recognizing individuals by the way they walk, is a relatively new biometric without these disadvantages. The inherent gait characteristic of an individual makes it irreplaceable and useful in visual surveillance. In this paper, an efficient gait recognition system for human identification by extracting two features namely width vector of the binary silhouette and the MPEG-7-based region-based shape descriptors is proposed. In the proposed method, foreground objects i.e., human and other moving objects are extracted by estimating background information by a Gaussian Mixture Model (GMM) and subsequently, median filtering operation is performed for removing noises in the background subtracted image. A moving target classification algorithm is used to separate human being (i.e., pedestrian) from other foreground objects (viz., vehicles). Shape and boundary information is used in the moving target classification algorithm. Subsequently, width vector of the outer contour of binary silhouette and the MPEG-7 Angular Radial Transform coefficients are taken as the feature vector. Next, the Principal Component Analysis (PCA) is applied to the selected feature vector to reduce its dimensionality. These extracted feature vectors are used to train an Hidden Markov Model (HMM) for identification of some individuals. The proposed system is evaluated using some gait sequences and the experimental results show the efficacy of the proposed algorithm.

Keywords: Gait Recognition, Gaussian Mixture Model, PrincipalComponent Analysis, MPEG-7 Angular Radial Transform.

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Authors: Anchana Khemphila, Veera Boonjing

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In this study, the Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm are used to classify to effective diagnosis Parkinsons disease(PD).It-s a challenging problem for medical community.Typically characterized by tremor, PD occurs due to the loss of dopamine in the brains thalamic region that results in involuntary or oscillatory movement in the body. A feature selection algorithm along with biomedical test values to diagnose Parkinson disease.Clinical diagnosis is done mostly by doctor-s expertise and experience.But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests for diagnosis.In many cases,not all the tests contribute towards effective diagnosis of a disease.Our work is to classify the presence of Parkinson disease with reduced number of attributes.Original,22 attributes are involved in classify.We use Information Gain to determine the attributes which reduced the number of attributes which is need to be taken from patients.The Artificial neural networks is used to classify the diagnosis of patients.Twenty-Two attributes are reduced to sixteen attributes.The accuracy is in training data set is 82.051% and in the validation data set is 83.333%.

Keywords: Data mining, classification, Parkinson disease, artificial neural networks, feature selection, information gain.

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Authors: Wernhuar Tarng, Wen-Shin Tsai, Yu-Si Lin, Chen-Kai Shiu

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Ecological ponds can be a good teaching tool for science teachers, but they must be built and maintained properly to provide students with a safe and suitable learning environment. Hence, many schools do not have the ability to build an ecological pond. This study used virtual reality technology to develop a webbased virtual ecological pond. Supported by situated learning theory and the instructional design of “Aquatic Life" learning unit, elementary school students can actively explore in the virtual ecological pond to observe aquatic animals and plants and learn about the concept of ecological conservation. A teaching experiment was conducted to investigate the learning effectiveness and practicability of this instructional design, and the results showed that students improved a great deal in learning about aquatic life. They found the virtual ecological pond interesting, easy to operate and helpful to understanding the aquatic ecological system. Therefore, it is useful in elementary science education.

Keywords: Virtual reality, virtual ecological ponds, situated learning, instructional design, science education.

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Authors: Noura Boudiaf, Allaoua Chaoui

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To analyze the behavior of Petri nets, the accessibility graph and Model Checking are widely used. However, if the analyzed Petri net is unbounded then the accessibility graph becomes infinite and Model Checking can not be used even for small Petri nets. ECATNets [2] are a category of algebraic Petri nets. The main feature of ECATNets is their sound and complete semantics based on rewriting logic [8] and its language Maude [9]. ECATNets analysis may be done by using techniques of accessibility analysis and Model Checking defined in Maude. But, these two techniques supported by Maude do not work also with infinite-states systems. As a category of Petri nets, ECATNets can be unbounded and so infinite systems. In order to know if we can apply accessibility analysis and Model Checking of Maude to an ECATNet, we propose in this paper an algorithm allowing the detection if the ECATNet is bounded or not. Moreover, we propose a rewriting logic based tool implementing this algorithm. We show that the development of this tool using the Maude system is facilitated thanks to the reflectivity of the rewriting logic. Indeed, the self-interpretation of this logic allows us both the modelling of an ECATNet and acting on it.

Keywords: ECATNets, Rewriting Logic, Maude, Finite-stateSystems, Infinite-state Systems, Boundness Property Checking.

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Authors: Melvin A. Ballera

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Prior literature in the field of adaptive and personalized learning sequence in e-learning have proposed and implemented various mechanisms to improve the learning process such as individualization and personalization, but complex to implement due to expensive algorithmic programming and need of extensive and prior data. The main objective of personalizing learning sequence is to maximize learning by dynamically selecting the closest teaching operation in order to achieve the learning competency of learner. In this paper, a revolutionary technique has been proposed and tested to perform individualization and personalization using modified reversed roulette wheel selection algorithm that runs at O(n). The technique is simpler to implement and is algorithmically less expensive compared to other revolutionary algorithms since it collects the dynamic real time performance matrix such as examinations, reviews, and study to form the RWSA single numerical fitness value. Results show that the implemented system is capable of recommending new learning sequences that lessens time of study based on student's prior knowledge and real performance matrix.

Keywords: E-learning, fitness value, personalized learning sequence, reversed roulette wheel selection algorithms.

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Authors: Chiung-Hui Chen

Abstract:

Traditional service channel is losing its edge due to emerging service technology. To establish interaction with the clients, the service industry is using effective mechanism to give clients direct access to services with emerging technologies. Thus, as service science receives attention, special and unique consumption pattern evolves; henceforth, leading to new market mechanism and influencing attitudes toward life and consumption patterns. The market demand for customized services is thus valued due to the emphasis of personal value, and is gradually changing the demand and supply relationship in the traditional industry. In respect of interior design service, in the process of traditional interior design, a designer converts to a concrete form the concept generated from the ideas and needs dictated by a user (client), by using his/her professional knowledge and drawing tool. The final product is generated through iterations of communication and modification, which is a very time-consuming process. Although this process has been accelerated with the help of computer graphics software today, repeated discussions and confirmations with users are still required to complete the task. In consideration of what is addressed above a space user’s life model is analyzed with visualization technique to create an interaction system modeled after interior design knowledge. The space user document intuitively personal life experience in a model requirement chart, allowing a researcher to analyze interrelation between analysis documents, identify the logic and the substance of data conversion. The repeated data which is documented are then transformed into design information for reuse and sharing. A professional interior designer may sort out the correlation among user’s preference, life pattern and design specification, thus deciding the critical design elements in the process of service design.

Keywords: Information Design, Life Model-Based, Aesthetic Computing, Communication.

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Authors: Vishal Awasthi, Krishna Raj

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Any digital processing performed on a signal with larger nyquist interval requires more computation than signal processing performed on smaller nyquist interval. The sampling rate alteration generates the unwanted effects in the system such as spectral aliasing and spectral imaging during signal processing. Multirate-multistage implementation of digital filter can result a significant computational saving than single rate filter designed for sample rate conversion. In this paper, we presented an efficient cascaded integrator comb (CIC) decimation filter that perform fast down sampling using signed digit adder algorithm with compensated frequency droop that arises due to aliasing effect during the decimation process. This proposed compensated CIC decimation filter structure with a hybrid signed digit (HSD) fast adder provide an improved performance in terms of down sampling speed by 65.15% than ripple carry adder (RCA) and reduced area and power by 57.5% and 0.01 % than signed digit (SD) adder algorithms respectively.

Keywords: Sampling rate conversion, Multirate Filtering, Compensation Theory, Decimation filter, CIC filter, Redundant signed digit arithmetic, Fast adders.

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Authors: Kuryati Kipli, Kasumawati Lias, Dayang Azra Awang Mat, Al-Khalid Othman, Ade Syaheda Wani Marzuki, Nurdiani Zamhari

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Visual attention allows user to select the most relevant information to ongoing behaviour. This paper presents a study on; i) the performance of people measurements, ii) accurateness of people measurement of the peaks that correspond to chemical quantities from the Magnetic Resonance Spectroscopy (MRS) graphs and iii) affects of people measurements to the algorithm-based diagnosis. Participant-s eye-movement was recorded using eye-tracker tool (Eyelink II). This experiment involves three participants for examining 20 MRS graphs to estimate the peaks of chemical quantities which indicate the abnormalities associated with Cerebellar Tumours (CT). The status of each MRS is verified by using decision algorithm. Analysis involves determination of humans-s eye movement pattern in measuring the peak of spectrograms, scan path and determining the relationship of distributions of fixation durations with the accuracy of measurement. In particular, the eye-tracking data revealed which aspects of the spectrogram received more visual attention and in what order they were viewed. This preliminary investigation provides a proof of concept for use of the eye tracking technology as the basis for expanded CT diagnosis.

Keywords: eye tracking, fixation durations, pattern, scan paths, spectrograms, visual.

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Authors: A. G. Pradeep, Gorantla Giridhar Kumar, Vijay Turaga, Vinod Srinivasa

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The major problem in the flow control valve is of lower Flow Capacity (Cv) which will reduce overall efficiency of flow circuit. Designers are continuously working to improve the Cv of the valve, but they need to validate the design ideas they have regarding the improvement of Cv. Traditional method of prototype and testing take a lot of time, that is where CFD comes into picture with very quick and accurate validation along with the visualization which is not possible with traditional testing method. We have developed a method to predict Cv value using CFD analysis by iterating on various Boundary conditions, solver settings and by carrying out grid convergence studies to establish correlation between the CFD model and Test data. The present study investigates 3 different ideas put forward by the designers for improving the flow capacity of the valves like reducing the cage thickness, changing the port position, and using the parabolic plug to guide the flow. Using CFD, we analyzed all design changes using the established methodology that we developed. We were able to evaluate the effect of these design changes on the Valve Cv. We optimized the wetted surface of the valve further by suggesting the design modification to the lower part of the valve to make the flow more streamlined. We could find that changing cage thickness and port position has little impact on the valve Cv. Combination of optimized wetted surface and introduction of parabolic plug improved the Cv of the valve significantly.

Keywords: Flow control valves, flow capacity, CFD simulations, design validation.

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Authors: Neethu S., Shinoy K.S., A.S. Shajilal

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This paper presents the optimal design and development of an axial flux motor for blood pump application. With the design objective of maximizing the motor efficiency and torque, different topologies of AFPM machine has been examined. Selection of optimal magnet fraction, Halbach arrangement of rotor magnets and the use of Soft Magnetic Composite (SMC) material for the stator core results in a novel motor with improved efficiency and torque profile. The results of the 3D Finite element analysis for the novel motor have been shown.

Keywords: Axial flux motor, Finite Element Methods, Halbach array, Left Ventricular Assist Device, Soft magnetic composite.

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Authors: Satean Tunyasrirut, Tianchai Suksri, Arjin Numsomran, Supan Gulpanich, Kitti Tirasesth

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This paper presents the approach to design the Auto- Tuning PID controller for interactive Water Level Process using integral step response. The Integral Step Response (ISR) is the method to model a dynamic process which can be done easily, conveniently and very efficiently. Therefore this method is advantage for design the auto tune PID controller. Our scheme uses the root locus technique to design PID controller. In this paper MATLAB is used for modeling and testing of the control system. The experimental results of the interacting water level process can be satisfyingly illustrated the transient response and the steady state response.

Keywords: Coupled-Tank, Interacting water level process, PIDController, Auto-tuning.

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Authors: Mohammed Niyasdeen Nejaamtheen

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The accelerated growth in aircraft industries desire effectual schemes, programs, innovative designs of advanced systems and facilities to accomplish the augmenting need for home-free air transportation. In this paper, a contemporary conceptual design of a cambered airfoil has been proposed in order to providing augmented effective lift force relative to the airplane, and to eliminating drawbacks and limitations of an airfoil in a commercial airplane by using a kind of smart materials. This invention of an unsymmetrical airfoil structure utilizes the amplified air momentum around the airfoil and increased camber length to providing improved aircraft performance and assist to enhancing the reliability of the aircraft components. Moreover, this conjectured design helps to reducing airplane weight and total drag.

Keywords: Collector electrode, corona electrode, Temperatureresponsive polymer and ultra-faims microchip.

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Authors: S. Di Benedetto, M. P. Di Donato, A. Rispoli, S. Cardone, J. Riehmer, J. Steelant, L. Vecchione

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Thanks to a coordinated funding by the European Space Agency (ESA) and the European Commission (EC) within the 7th framework program, the High-Speed Experimental Fly Vehicles – International (HEXAFLY-INT) project is aimed at the flight validation of hypersonics technologies enabling future trans-atmospheric flights. The project, which is currently involving partners from Europe, Russian Federation and Australia operating under ESA/ESTEC coordination, will achieve the goal of designing, manufacturing, assembling and flight testing an unpowered high speed vehicle in a glider configuration by 2018. The main technical challenges of the project are specifically related to the design of the vehicle gliding configuration and to the complexity of integrating breakthrough technologies with standard aeronautical technologies, e.g. high temperature protection system and airframe cold structures. Also, the sonic boom impact, which is one of the environmental challenges of the high speed flight, will be assessed. This paper provides a comprehensive and detailed update on all the current projects activities carried out to date on both the vehicle and mission design.

Keywords: Design, flight testing, hypersonics, integration.

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Authors: Justin D. Olmanson, Katrina S. Kennett, Bill Cope

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In educational technology, the idea of innovation is usually tethered to contemporary technological inventions and emerging technologies. Yet, using long-known technologies in ways that are pedagogically or experimentially new can reposition them as emerging educational technologies. In this study we explore how a subtle pivot in pedagogical thinking led to an innovative education technology. We describe the design and implementation of an online writing tool that scaffolds students in the evaluation of their own informational texts. We think about how pathways to innovation can emerge from pivots, namely a leveraging of longstanding practices in novel ways has the potential to cultivate new opportunities for learning. We first unpack Infowriter in terms of its design, then we describe some results of a study in which we implemented an intervention which included our designed application.

Keywords: Design, innovation, learning, technology, writing.

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Authors: Masoud Sadeghian, Alireza Fatehi

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One of the most important parts of a cement factory is the cement rotary kiln which plays a key role in quality and quantity of produced cement. In this part, the physical exertion and bilateral movement of air and materials, together with chemical reactions take place. Thus, this system has immensely complex and nonlinear dynamic equations. These equations have not worked out yet. Only in exceptional case; however, a large number of the involved parameter were crossed out and an approximation model was presented instead. This issue caused many problems for designing a cement rotary kiln controller. In this paper, we presented nonlinear predictor and simulator models for a real cement rotary kiln by using nonlinear identification technique on the Locally Linear Neuro- Fuzzy (LLNF) model. For the first time, a simulator model as well as a predictor one with a precise fifteen minute prediction horizon for a cement rotary kiln is presented. These models are trained by LOLIMOT algorithm which is an incremental tree-structure algorithm. At the end, the characteristics of these models are expressed. Furthermore, we presented the pros and cons of these models. The data collected from White Saveh Cement Company is used for modeling.

Keywords: Cement rotary kiln, nonlinear identification, Locally Linear Neuro-Fuzzy model.

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Authors: Kwangjin Hong, Chulhan Lee, Keechul Jung, Kyoungsu Oh

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For the communication between human and computer in an interactive computing environment, the gesture recognition is studied vigorously. Therefore, a lot of studies have proposed efficient methods about the recognition algorithm using 2D camera captured images. However, there is a limitation to these methods, such as the extracted features cannot fully represent the object in real world. Although many studies used 3D features instead of 2D features for more accurate gesture recognition, the problem, such as the processing time to generate 3D objects, is still unsolved in related researches. Therefore we propose a method to extract the 3D features combined with the 3D object reconstruction. This method uses the modified GPU-based visual hull generation algorithm which disables unnecessary processes, such as the texture calculation to generate three kinds of 3D projection maps as the 3D feature: a nearest boundary, a farthest boundary, and a thickness of the object projected on the base-plane. In the section of experimental results, we present results of proposed method on eight human postures: T shape, both hands up, right hand up, left hand up, hands front, stand, sit and bend, and compare the computational time of the proposed method with that of the previous methods.

Keywords: Fast 3D Feature Extraction, Gesture Recognition, Computer Vision.

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Authors: Yi-Pin Hsu, Shin-Yu Lin

Abstract:

An efficient parallel form in digital signal processor can improve the algorithm performance. The butterfly structure is an important role in fast Fourier transform (FFT), because its symmetry form is suitable for hardware implementation. Although it can perform a symmetric structure, the performance will be reduced under the data-dependent flow characteristic. Even though recent research which call as novel memory reference reduction methods (NMRRM) for FFT focus on reduce memory reference in twiddle factor, the data-dependent property still exists. In this paper, we propose a parallel-computing approach for FFT implementation on digital signal processor (DSP) which is based on data-independent property and still hold the property of low-memory reference. The proposed method combines final two steps in NMRRM FFT to perform a novel data-independent structure, besides it is very suitable for multi-operation-unit digital signal processor and dual-core system. We have applied the proposed method of radix-2 FFT algorithm in low memory reference on TI TMSC320C64x DSP. Experimental results show the method can reduce 33.8% clock cycles comparing with the NMRRM FFT implementation and keep the low-memory reference property.

Keywords: Parallel-computing, FFT, low-memory reference, TIDSP.

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Authors: Philip Speranza

Abstract:

As everyday transit options are shifting from autocentric to pedestrian and bicycle oriented modes for healthy living, downtown streets are becoming more attractive places to live. However, tools and methods to measure the natural environment at the small scale of streets do not exist. Fortunately, a combination of mobile data collection technology and parametric urban design software now allows an interface to relate urban ecological conditions. This paper describes creation of an interactive tool to measure urban phenomena of air, water, and heat/light at the scale of new three-by-three block pedestrianized areas in Barcelona called Superilles. Each Superilla limits transit to the exterior of the blocks and to create more walkable and bikeable interior streets for healthy living. The research will describe the integration of data collection, analysis, and design output via a live interface using parametric software Rhino Grasshopper and the Human User Interface (UI) plugin.

Keywords: Transit, urban design, GIS, parametric design, Superilles, Barcelona, urban ecology.

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Authors: David C. White

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This paper describes the architectural design considerations for building a new class of application, a Personal Knowledge Integrator and a particular example a Knowledge Theatre. It then supports this description by describing a scenario of a child acquiring knowledge and how this process could be augmented by the proposed architecture and design of a Knowledge Theatre. David Merrill-s first “principles of instruction" are kept in focus to provide a background to view the learning potential.

Keywords: Knowledge, personal, open data, visualization, learning, teaching

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Authors: Paola Lecca, Lorenzo Dematte, Corrado Priami

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The present models and simulation algorithms of intracellular stochastic kinetics are usually based on the premise that diffusion is so fast that the concentrations of all the involved species are homogeneous in space. However, recents experimental measurements of intracellular diffusion constants indicate that the assumption of a homogeneous well-stirred cytosol is not necessarily valid even for small prokaryotic cells. In this work a mathematical treatment of diffusion that can be incorporated in a stochastic algorithm simulating the dynamics of a reaction-diffusion system is presented. The movement of a molecule A from a region i to a region j of the space is represented as a first order reaction Ai k- ! Aj , where the rate constant k depends on the diffusion coefficient. The diffusion coefficients are modeled as function of the local concentration of the solutes, their intrinsic viscosities, their frictional coefficients and the temperature of the system. The stochastic time evolution of the system is given by the occurrence of diffusion events and chemical reaction events. At each time step an event (reaction or diffusion) is selected from a probability distribution of waiting times determined by the intrinsic reaction kinetics and diffusion dynamics. To demonstrate the method the simulation results of the reaction-diffusion system of chaperoneassisted protein folding in cytoplasm are shown.

Keywords: Reaction-diffusion systems, diffusion coefficient, stochastic simulation algorithm.

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Authors: Xiang Yu, Chuntao Feng, Lu Yang, Meiyang Song, Wenhao Zhou

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The existing two-dimensional micro-Doppler features extraction ignores the correlation information between the spatial and temporal dimension features. For the range-Doppler map, the time dimension is introduced, and a frequency modulation continuous wave (FMCW) radar human fall detection algorithm based on time-varying range-Doppler features is proposed. Firstly, the range-Doppler sequence maps are generated from the echo signals of the continuous motion of the human body collected by the radar. Then the three-dimensional data cube composed of multiple frames of range-Doppler maps is input into the three-dimensional Convolutional Neural Network (3D CNN). The spatial and temporal features of time-varying range-Doppler are extracted by the convolution layer and pool layer at the same time. Finally, the extracted spatial and temporal features are input into the fully connected layer for classification. The experimental results show that the proposed fall detection algorithm has a detection accuracy of 95.66%.

Keywords: FMCW radar, fall detection, 3D CNN, time-varying range-Doppler features.

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Authors: Serafettin Ekinci, Kursat Zuhtuogullari

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This paper proposes a Fuzzy Expert System design to determine the wearing properties of nitrided and non nitrided steel. The proposed Fuzzy Expert System approach helps the user and the manufacturer to forecast the wearing properties of nitrided and non nitrided steel under specified laboratory conditions. Surfaces of the engineering components are often nitrided for improving wear, corosion, fatigue specifications. A major property of nitriding process is reducing distortion and wearing of the metalic alloys. A Fuzzy Expert System was developed for determining the wearing and durability properties of nitrided and non nitrided steels that were tested under different loads and different sliding speeds in the laboratory conditions.

Keywords: Fuzzy Expert System Design, Rule Based Systems, Fatigue, Corrosion

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Authors: K. Djellabi, M. E. H. Latreche

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Induction heating computer simulation is a powerful tool for process design and optimization, induction coil design, equipment selection, as well as education and business presentations. The authors share their vast experience in the practical use of computer simulation for different induction heating and heat treating processes. In this paper treated with mathematical modeling and numerical simulation of induction heating furnaces with axisymmetric geometries for the numerical solution, we propose finite element methods combined with boundary (FEM) for the electromagnetic model using COMSOL® Multiphysics Software. Some numerical results for an industrial furnace are shown with high frequency.

Keywords: Numerical methods, Induction furnaces, Induction Heating, Finite element method, Comsol Multiphysics software.

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Authors: Vishal Naranje, S. Kumar

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In this paper a low cost knowledge base system (KBS) framework is proposed for design of deep drawing die and procedure for developing system modules. The task of building the system is structured into different modules for major activities of design of deep drawing die. A manufacturability assessment module of the proposed framework is developed to check the manufacturability of deep drawn parts. The technological knowledge is represented by using IF- THEN rules and it is coded in AutoLISP language. The module is designed to be loaded into the prompt area of AutoCAD. The cost of implementation of proposed system makes it affordable for small and medium scale sheet metal industries.

Keywords: Knowledge base system, Deep drawing die, Manufacturability, Sheet metal.

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Authors: T. Valdbjørn Rasmussen

Abstract:

Design criteria for achieving an acceptable indoor radon concentration are presented in this paper. The paper suggests three design criteria. These criteria have to be considered at the early stage of the building design phase to meet the latest recommendations from the World Health Organization in most countries. The three design criteria are; first, establishing a radon barrier facing the ground; second, lowering the air pressure in the lower zone of the slab on ground facing downwards; third, diluting the indoor air with outdoor air. The first two criteria can prevent radon from infiltrating from the ground, and the third criteria can dilute the indoor air. By combining these three criteria, the indoor radon concentration can be lowered achieving an acceptable level. In addition, a cheap and reliable method for measuring the radon concentration in the indoor air is described. The provision on radon in the Danish Building Regulations complies with the latest recommendations from the World Health Organization. Radon can cause lung cancer and it is not known whether there is a lower limit for when it is not harmful to human beings. Therefore, it is important to reduce the radon concentration as much as possible in buildings. Airtightness is an important factor when dealing with buildings. It is important to avoid air leakages in the building envelope both facing the atmosphere, e.g. in compliance with energy requirements, but also facing the ground, to meet the requirements to ensure and control the indoor environment. Infiltration of air from the ground underneath a building is the main providing source of radon to the indoor air.

Keywords: Radon, natural radiation, barrier, pressure lowering, ventilation.

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Authors: Porntip Ruengtam

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This article is an extension of previous research presenting the relevant factors related to environmental perceptions, residential community, and the design of a healing environment, which have effects on the well-being and requirements of Thai elderly. Research methodology began with observations and interviews in three case studies in terms of the management processes and environment design of similar existing projects in Thailand. The interview results were taken to summarize with related theories and literature. A questionnaire survey was designed for data collection to confirm the factors of requirements in a residential community intended for the Thai elderly. A structural equation model (SEM) was formulated to explain the cause-effect factors for the requirements of a residential community for Thai elderly. The research revealed that the requirements of a residential community for Thai elderly were classified into three groups when utilizing a technique for exploratory factor analysis. The factors were comprised of (1) requirements for general facilities and activities, (2) requirements for facilities related to health and security, and (3) requirements for facilities related to physical exercise in the residential community. The results from the SEM showed the background of elderly people had a direct effect on their requirements for a residential community from various aspects. The results should lead to the formulation of policies for design and management of residential communities for the elderly in order to enhance quality of life as well as both the physical and mental health of the Thai elderly.

Keywords: Elderly, environmental design, residential community, structural equation modeling.

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Authors: Leong Lee, Cyriac Kandoth, Jennifer L. Leopold, Ronald L. Frank

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Protein 3D structure prediction has always been an important research area in bioinformatics. In particular, the prediction of secondary structure has been a well-studied research topic. Despite the recent breakthrough of combining multiple sequence alignment information and artificial intelligence algorithms to predict protein secondary structure, the Q3 accuracy of various computational prediction algorithms rarely has exceeded 75%. In a previous paper [1], this research team presented a rule-based method called RT-RICO (Relaxed Threshold Rule Induction from Coverings) to predict protein secondary structure. The average Q3 accuracy on the sample datasets using RT-RICO was 80.3%, an improvement over comparable computational methods. Although this demonstrated that RT-RICO might be a promising approach for predicting secondary structure, the algorithm-s computational complexity and program running time limited its use. Herein a parallelized implementation of a slightly modified RT-RICO approach is presented. This new version of the algorithm facilitated the testing of a much larger dataset of 396 protein domains [2]. Parallelized RTRICO achieved a Q3 score of 74.6%, which is higher than the consensus prediction accuracy of 72.9% that was achieved for the same test dataset by a combination of four secondary structure prediction methods [2].

Keywords: data mining, protein secondary structure prediction, parallelization.

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Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: Cyber-security, Intrusion Detection Systems, Temporal Graph Network, Anomaly Detection.

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Authors: Parvinder S. Sandhu, Hardeep Singh

Abstract:

The requirement to improve software productivity has promoted the research on software metric technology. There are metrics for identifying the quality of reusable components but the function that makes use of these metrics to find reusability of software components is still not clear. These metrics if identified in the design phase or even in the coding phase can help us to reduce the rework by improving quality of reuse of the component and hence improve the productivity due to probabilistic increase in the reuse level. CK metric suit is most widely used metrics for the objectoriented (OO) software; we critically analyzed the CK metrics, tried to remove the inconsistencies and devised the framework of metrics to obtain the structural analysis of OO-based software components. Neural network can learn new relationships with new input data and can be used to refine fuzzy rules to create fuzzy adaptive system. Hence, Neuro-fuzzy inference engine can be used to evaluate the reusability of OO-based component using its structural attributes as inputs. In this paper, an algorithm has been proposed in which the inputs can be given to Neuro-fuzzy system in form of tuned WMC, DIT, NOC, CBO , LCOM values of the OO software component and output can be obtained in terms of reusability. The developed reusability model has produced high precision results as expected by the human experts.

Keywords: CK-Metric, ID3, Neuro-fuzzy, Reusability.

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Authors: Sara Ansari, Mohammad Hadi Sadreddini

Abstract:

The increasing importance of data stream arising in a wide range of advanced applications has led to the extensive study of mining frequent patterns. Mining data streams poses many new challenges amongst which are the one-scan nature, the unbounded memory requirement and the high arrival rate of data streams. In this paper, we propose a new approach for mining itemsets on data stream. Our approach SFIDS has been developed based on FIDS algorithm. The main attempts were to keep some advantages of the previous approach and resolve some of its drawbacks, and consequently to improve run time and memory consumption. Our approach has the following advantages: using a data structure similar to lattice for keeping frequent itemsets, separating regions from each other with deleting common nodes that results in a decrease in search space, memory consumption and run time; and Finally, considering CPU constraint, with increasing arrival rate of data that result in overloading system, SFIDS automatically detect this situation and discard some of unprocessing data. We guarantee that error of results is bounded to user pre-specified threshold, based on a probability technique. Final results show that SFIDS algorithm could attain about 50% run time improvement than FIDS approach.

Keywords: Data stream, frequent itemset, stream mining.

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