Search results for: Support Vector Domain Description

Authors: V. Kabeer, N.K.Narayanan

Abstract:

This paper reports a new pattern recognition approach for face recognition. The biological model of light receptors - cones and rods in human eyes and the way they are associated with pattern vision in human vision forms the basis of this approach. The functional model is simulated using CWD and WPD. The paper also discusses the experiments performed for face recognition using the features extracted from images in the AT & T face database. Artificial Neural Network and k- Nearest Neighbour classifier algorithms are employed for the recognition purpose. A feature vector is formed for each of the face images in the database and recognition accuracies are computed and compared using the classifiers. Simulation results show that the proposed method outperforms traditional way of feature extraction methods prevailing for pattern recognition in terms of recognition accuracy for face images with pose and illumination variations.

Keywords: Face recognition, Image analysis, Wavelet feature extraction, Pattern recognition, Classifier algorithms

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Authors: J. S. Nah, A. Y. Jeon, J. H. Ro, G. R. Jeon

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ECG analysis method was developed using ROC analysis of PVC detecting algorithm. ECG signal of MIT-BIH arrhythmia database was analyzed by MATLAB. First of all, the baseline was removed by median filter to preprocess the ECG signal. R peaks were detected for ECG analysis method, and normal VCG was extracted for VCG analysis method. Four PVC detecting algorithm was analyzed by ROC curve, which parameters are maximum amplitude of QRS complex, width of QRS complex, r-r interval and geometric mean of VCG. To set cut-off value of parameters, ROC curve was estimated by true-positive rate (sensitivity) and false-positive rate. sensitivity and false negative rate (specificity) of ROC curve calculated, and ECG was analyzed using cut-off value which was estimated from ROC curve. As a result, PVC detecting algorithm of VCG geometric mean have high availability, and PVC could be detected more accurately with amplitude and width of QRS complex.

Keywords: Vectorcardiogram (VCG), Premature Ventricular contraction (PVC), ROC (receiver operating characteristic) curve, ECG

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Authors: Ayman El-Garem, Riham Adel

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Digital transformation is about identifying the necessary changes of the entire business model, rethinking how to transform the traditional operations into digital ones that can create better value to its customers. Efforts are common across industries, but they often fail due to a lack of understanding of the factors required to focus on and change to be able to embark in digital transformation successfully. Further research is required to bridge the knowledge gap between academia and industry to support companies starting their digital transformation journey. To date there is no consensus on digital transformation key success factors. Therefore, the aim of this paper is to identify the success factors in digital transformation journey, throughout conducting a systematic literature review of 134 peer-reviewed articles to get better insights regarding the research progress in this field.  After completing the systematic literature review it will be followed by Delphi study to get experts consensus on the most significant factors affecting digital transformation implementation. The findings indicate that organizations undergoing digital transformation should focus mainly on (1) well managed digital transformation activities; (2) digital business strategy; (3) supportive culture; (4) top management support; (5) organizational change capabilities.

Keywords: Digital transformation, key success factors, literature review, Delphi study.

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Authors: K. Ben Khalifa, M.H. Bédoui, M. Dogui, F. Alexandre

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Several studies have been carried out, using various techniques, including neural networks, to discriminate vigilance states in humans from electroencephalographic (EEG) signals, but we are still far from results satisfactorily useable results. The work presented in this paper aims at improving this status with regards to 2 aspects. Firstly, we introduce an original procedure made of the association of two neural networks, a self organizing map (SOM) and a learning vector quantization (LVQ), that allows to automatically detect artefacted states and to separate the different levels of vigilance which is a major breakthrough in the field of vigilance. Lastly and more importantly, our study has been oriented toward real-worked situation and the resulting model can be easily implemented as a wearable device. It benefits from restricted computational and memory requirements and data access is very limited in time. Furthermore, some ongoing works demonstrate that this work should shortly results in the design and conception of a non invasive electronic wearable device.

Keywords: Electroencephalogram interpretation, artificialneural networks, vigilance states, hardware implementation

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Authors: J. Menčík

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Actual load, material characteristics and other quantities often differ from the design values. This can cause worse function, shorter life or failure of a civil engineering structure, a machine, vehicle or another appliance. The paper shows main causes of the uncertainties and deviations and presents a systematic approach and efficient tools for their elimination or mitigation of consequences. Emphasis is put on the design stage, which is most important for reliability ensuring. Principles of robust design and important tools are explained, including FMEA, sensitivity analysis and probabilistic simulation methods. The lifetime prediction of long-life objects can be improved by long-term monitoring of the load response and damage accumulation in operation. The condition evaluation of engineering structures, such as bridges, is often based on visual inspection and verbal description. Here, methods based on fuzzy logic can reduce the subjective influences.

Keywords: Design, fuzzy methods, Monte Carlo, reliability, robust design, sensitivity analysis, simulation, uncertainties.

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Authors: Rizwan Asghar, Dake Liu

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A hardware efficient, multi mode, re-configurable architecture of interleaver/de-interleaver for multiple standards, like DVB, WiMAX and WLAN is presented. The interleavers consume a large part of silicon area when implemented by using conventional methods as they use memories to store permutation patterns. In addition, different types of interleavers in different standards cannot share the hardware due to different construction methodologies. The novelty of the work presented in this paper is threefold: 1) Mapping of vital types of interleavers including convolutional interleaver onto a single architecture with flexibility to change interleaver size; 2) Hardware complexity for channel interleaving in WiMAX is reduced by using 2-D realization of the interleaver functions; and 3) Silicon cost overheads reduced by avoiding the use of small memories. The proposed architecture consumes 0.18mm2 silicon area for 0.12μm process and can operate at a frequency of 140 MHz. The reduced complexity helps in minimizing the memory utilization, and at the same time provides strong support to on-the-fly computation of permutation patterns.

Keywords: Hardware interleaver implementation, WiMAX, DVB, block interleaver, convolutional interleaver, hardwaremultiplexing.

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Authors: Pedro Padilha Gonçalves, Doris C. C. K. Kowaltowski, Benjamin Cleveland

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Trends in education affect schooling, needing incorporation into design concepts to support desired learning processes with appropriate and stimulating environments. A design process for school architecture demands research, debates, reflections, and efficient decision-making methods. This paper presents research on evidence-based design, related to middle schools, based on a systematic literature review and the elaboration of a set of architectural design patterns, through a graphic translation of new concepts for classroom configurations, to support programming debates and the synthesis phase of design. The investigation resulted in nine patterns that configure the concepts of boundaries, flexibility, levels of openness, mindsets, neighborhoods, movement and interaction, territories, opportunities for learning, and sightlines for classrooms. The research is part of a continuous investigation of design methods, on contemporary school architecture to produce an architectural pattern matrix based on scientific information translated into an insightful graphic design language.

Keywords: School architecture, design process, design patterns, evidence-based design.

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Authors: Justine Jun

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This study aims to reveal migrant women English instructors' workplace learning experiences in Canadian post-secondary institutions in Ontario. Migrant women English instructors in higher education are an understudied group of teachers. This study employs a qualitative research paradigm. Mezirow’s Transformative Learning Theory is an essential lens for the researcher to explain, analyze, and interpret the research data. It is a collaborative research project. The researcher and participants cooperatively create photographic or other artwork data responding to the research questions. Photovoice and arts-informed data collection methodology are the main methods. Research participants engage in the study as co-researchers and inquire about their own workplace learning experiences, actively utilizing their critical self-reflective and dialogic skills. Co-researchers individually select the forms of artwork they prefer to engage with to represent their transformative workplace learning experiences about the Canadian workplace cultures that they underwent while working with colleagues and administrators in the workplace. Once the co-researchers generate their cultural artifacts as research data, they collaboratively interpret their artworks with the researcher and other volunteer co-researchers. Co-researchers jointly investigate the themes emerging from the artworks. They also interpret the meanings of their own and others’ workplace learning experiences embedded in the artworks through interactive one-on-one or group interviews. The following are the research questions that the migrant women English instructor participants examine and answer: (1) What have they learned about their workplace culture and how do they explain their learning experiences? (2) How transformative have their learning experiences been at work? (3) How have their colleagues and administrators influenced their transformative learning? (4) What kind of support have they received? What supports have been valuable to them and what changes would they like to see? (5) What have their learning experiences transformed? (6) What has this arts-informed research process transformed? The study findings implicate English language instructor support currently practiced in post-secondary English language programs in Ontario, Canada, especially for migrant women English instructors. This research is a doctoral empirical study in progress. This study has the urgency to address the research problem that few studies have investigated migrant English instructors’ professional learning and support issues in the workplace, precisely that of English instructors working with adult learners in Canada. While appropriate social and professional support for migrant English instructors is required throughout the country, the present workplace realities in Ontario's English language programs need to be heard soon. For that purpose, the conceptualization of this study is crucial. It makes the investigation of under-represented instructors’ under-researched social phenomena, workplace learning and support, viable and rigorous. This paper demonstrates the robust theorization of English instructors’ workplace experiences using Mezirow’s Transformative Learning Theory in the English language teacher education field. 

Keywords: English teacher education, professional learning, transformative learning theory, workplace learning.

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Authors: Martina Perinkova, Lenka Kolarcikova, Marketa Twrda

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Brownfields are one of the most important problems that must be solved by today's cities. The topic of this article is description of developing a comprehensive transformation of postindustrial area of the former iron factory national cultural heritage lower Vítkovice. City of Ostrava used to be industrial superpower of the Czechoslovak Republic, especially in the area of coal mining and iron production, after declining industrial production and mining in the 80s left many unused areas of former factories generally brownfields and backfields. Since the late 90s we are observing how the city officials or private entities seeking to remedy this situation. Regeneration of brownfields is a very expensive and long-term process. The area is now rebuilt for tourists and residents of the city in the entertainment, cultural, and social center. It was necessary do the reconstruction of the industrial monuments. Equally important was the construction of new buildings, which helped reusing of the entire complex. This is a unique example of transformation of technical monuments and completion of necessary new objects, so that the area could start working again and reintegrate back into the urban system.

Keywords: Brownfields, conversion, historical and industrial buildings, reconstruction.

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Authors: K. Boumediene, S. E. Belhenniche

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This article presents a numerical analysis of a turbulent flow past DTMB 4119 marine propeller by the means of RANS approach; the propeller designed at David Taylor Model Basin in USA. The purpose of this study is to predict the hydrodynamic performance of the marine propeller, it aims also to compare the results obtained with the experiment carried out in open water tests; a periodical computational domain was created to reduce the unstructured mesh size generated. The standard kw turbulence model for the simulation is selected; the results were in a good agreement. Therefore, the errors were estimated respectively to 1.3% and 5.9% for KT and KQ.

Keywords: propeller flow, CFD simulation, hydrodynamic performance, RANS

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Authors: Maha Sharkas, Dahlia R. ElShafie, Nadder Hamdy

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Image watermarking has proven to be quite an efficient tool for the purpose of copyright protection and authentication over the last few years. In this paper, a novel image watermarking technique in the wavelet domain is suggested and tested. To achieve more security and robustness, the proposed techniques relies on using two nested watermarks that are embedded into the image to be watermarked. A primary watermark in form of a PN sequence is first embedded into an image (the secondary watermark) before being embedded into the host image. The technique is implemented using Daubechies mother wavelets where an arbitrary embedding factor α is introduced to improve the invisibility and robustness. The proposed technique has been applied on several gray scale images where a PSNR of about 60 dB was achieved.

Keywords: Image watermarking, Multimedia Security, Wavelets, Image Processing.

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Authors: P. Ramana , K. Alice Mary, M. Surya Kalavathi, M. Phani Kumar

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This paper discusses two observers, which are used for the estimation of parameters of PMSM. Former one, reduced order observer, which is used to estimate the inaccessible parameters of PMSM. Later one, full order observer, which is used to estimate all the parameters of PMSM even though some of the parameters are directly available for measurement, so as to meet with the insensitivity to the parameter variation. However, the state space model contains some nonlinear terms i.e. the product of different state variables. The asymptotic state observer, which approximately reconstructs the state vector for linear systems without uncertainties, was presented by Luenberger. In this work, a modified form of such an observer is used by including a non-linear term involving the speed. So, both the observers are designed in the framework of nonlinear control; their stability and rate of convergence is discussed.

Keywords: Permanent magnet synchronous motor, Mathematicalmodelling, Rotor reference frame, parameter estimation, Luenbergerobserver, reduced order observer, full order observer

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Authors: S.Jerald Jeba Kumar, M.Madheswaran

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The structure of retinal vessels is a prominent feature, that reveals information on the state of disease that are reflected in the form of measurable abnormalities in thickness and colour. Vascular structures of retina, for implementation of clinical diabetic retinopathy decision making system is presented in this paper. Retinal Vascular structure is with thin blood vessel, whose accuracy is highly dependent upon the vessel segmentation. In this paper the blood vessel thickness is automatically detected using preprocessing techniques and vessel segmentation algorithm. First the capture image is binarized to get the blood vessel structure clearly, then it is skeletonised to get the overall structure of all the terminal and branching nodes of the blood vessels. By identifying the terminal node and the branching points automatically, the main and branching blood vessel thickness is estimated. Results are presented and compared with those provided by clinical classification on 50 vessels collected from Bejan Singh Eye hospital..

Keywords: Diabetic retinopathy, Binarization, SegmentationClinical Decision Support Systems.

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Authors: S. Sarumathi, N. Shanthi

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Due to the fast and flawless technological innovation there is a tremendous amount of data dumping all over the world in every domain such as Pattern Recognition, Machine Learning, Spatial Data Mining, Image Analysis, Fraudulent Analysis, World Wide Web etc., This issue turns to be more essential for developing several tools for data mining functionalities. The major aim of this paper is to analyze various tools which are used to build a resourceful analytical or descriptive model for handling large amount of information more efficiently and user friendly. In this survey the diverse tools are illustrated with their extensive technical paradigm, outstanding graphical interface and inbuilt multipath algorithms in which it is very useful for handling significant amount of data more indeed.

Keywords: Classification, Clustering, Data Mining, Machine learning, Visualization.

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Authors: Revathi Venkataraman, M. Pushpalatha, T. Rama Rao

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The lack of any centralized infrastructure in mobile ad hoc networks (MANET) is one of the greatest security concerns in the deployment of wireless networks. Thus communication in MANET functions properly only if the participating nodes cooperate in routing without any malicious intention. However, some of the nodes may be malicious in their behavior, by indulging in flooding attacks on their neighbors. Some others may act malicious by launching active security attacks like denial of service. This paper addresses few related works done on trust evaluation and establishment in ad hoc networks. Related works on flooding attack prevention are reviewed. A new trust approach based on the extent of friendship between the nodes is proposed which makes the nodes to co-operate and prevent flooding attacks in an ad hoc environment. The performance of the trust algorithm is tested in an ad hoc network implementing the Ad hoc On-demand Distance Vector (AODV) protocol.

Keywords: AODV, Flooding, MANETs, trust estimation

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Authors: R. Asokan, A. M. Natarajan

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Mobile adhoc network (MANET) is a collection of mobile devices which form a communication network with no preexisting wiring or infrastructure. Multiple routing protocols have been developed for MANETs. As MANETs gain popularity, their need to support real time applications is growing as well. Such applications have stringent quality of service (QoS) requirements such as throughput, end-to-end delay, and energy. Due to dynamic topology and bandwidth constraint supporting QoS is a challenging task. QoS aware routing is an important building block for QoS support. The primary goal of the QoS aware protocol is to determine the path from source to destination that satisfies the QoS requirements. This paper proposes a new energy and delay aware protocol called energy and delay aware TORA (EDTORA) based on extension of Temporally Ordered Routing Protocol (TORA).Energy and delay verifications of query packet have been done in each node. Simulation results show that the proposed protocol has a higher performance than TORA in terms of network lifetime, packet delivery ratio and end-to-end delay.

Keywords: EDTORA, Mobile Adhoc Networks, QoS, Routing, TORA

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Authors: Shimal Das, Dibyendu Ghoshal

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The effect of directional search using iterated functional system has been studied on four images taken from databases. The images are portioned successively towards smaller dimension. Presented method provides the faster rate of convergence with respect to processing time in the flat region, but the same has been found to be slower at the border of the images and edges. It has also been revealed that the PSNR is lower at the edges and border portions of the image, and it is found to be higher in the uniform gray region, under the same external illumination and external noise environment.

Keywords: Iterated functional system, fractal compression, structural similarity index measure, fractal block coding, affine transformations.

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Authors: Noor A. Auzairy, Rubi Ahmad, Catherine S.F. Ho, Ros Z. Z. Sapian

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This paper is to explore the relationship and the level of stock market integration of the Asian countries, primarily concentrating on Malaysia, Thailand, Indonesia, and South Korea, with the world from January 1997 to December 2009. The degree of short-run and long-run stock market integration of those Asian countries are analyzed in order to determine the significance of series of regional and world financial crises, liberalization policies and other financial reforms in influencing the level of stock market integration. To test for cointegration, this paper applies coefficient correlation, univariate regression analyses, cointegration tests, and vector autoregressive models (VAR) by using the four Asian stock markets main indices and the MSCI World index. The empirical findings from this work reveal that there is no long-run stock market integration for the four countries and the world market. However, there is short run integration.

Keywords: Asia, integration, relationship, stock market.

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Authors: Ionel Zagan, Vasile Gheorghita Gaitan

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The development of CPUs and of real-time systems based on them made it possible to use time at increasingly low resolutions. Together with the scheduling methods and algorithms, time organizing has been improved so as to respond positively to the need for optimization and to the way in which the CPU is used. This presentation contains both a detailed theoretical description and the results obtained from research on improving the performances of the nMPRA (Multi Pipeline Register Architecture) processor by implementing specific functions in hardware. The proposed CPU architecture has been developed, simulated and validated by using the FPGA Virtex-7 circuit, via a SoC project. Although the nMPRA processor hardware structure with five pipeline stages is very complex, the present paper presents and analyzes the tests dedicated to the implementation of the CPU and of the memory on-chip for instructions and data. In order to practically implement and test the entire SoC project, various tests have been performed. These tests have been performed in order to verify the drivers for peripherals and the boot module named Bootloader.

Keywords: Hardware scheduler, nMPRA processor, real-time systems, scheduling methods.

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Authors: M.Pourmahmoud, M.Salmanzadeh, M.Mehrani, M.R.Isvandzibaei

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In this paper a study on the vibration of thin cylindrical shells with ring supports and made of functionally graded materials (FGMs) composed of stainless steel and nickel is presented. Material properties vary along the thickness direction of the shell according to volume fraction power law. The cylindrical shells have ring supports which are arbitrarily placed along the shell and impose zero lateral deflections. The study is carried out based on third order shear deformation shell theory (T.S.D.T). The analysis is carried out using Hamilton-s principle. The governing equations of motion of FGM cylindrical shells are derived based on shear deformation theory. Results are presented on the frequency characteristics, influence of ring support position and the influence of boundary conditions. The present analysis is validated by comparing results with those available in the literature.

Keywords: Vibration, FGM, Cylindrical shell, Hamilton'sprinciple, Ring support.

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Authors: Iliana Marinova, Valentin Mateev

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For investigations of electromagnetic field distributions in biological structures by Finite Element Method (FEM), a method for automatic 3D model building of human anatomical objects is developed. Models are made by meshed structures and specific electromagnetic material properties for each tissue type. Mesh is built according to specific FEM criteria for achieving good solution accuracy. Several FEM models of anatomical objects are built. Formulation using magnetic vector potential and scalar electric potential (A-V, A) is used for modeling of electromagnetic fields in human tissue objects. The developed models are suitable for investigations of electromagnetic field distributions in human tissues exposed in external fields during magnetic stimulation, defibrillation, impedance tomography etc.

Keywords: electromagnetic field, finite element method, humantissue.

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Authors: Sinarwati Mohamad Suhaili, Naomie Salim, Mohamad Nazim Jambli

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Sequence-to-sequence (seq2seq) models augmented with attention mechanisms are increasingly important in automated customer service. These models, adept at recognizing complex relationships between input and output sequences, are essential for optimizing chatbot responses. Central to these mechanisms are neural attention weights that determine the model’s focus during sequence generation. Despite their widespread use, there remains a gap in the comparative analysis of different attention weighting functions within seq2seq models, particularly in the context of chatbots utilizing the Customer Support Twitter (CST) dataset. This study addresses this gap by evaluating four distinct attention-scoring functions—dot, multiplicative/general, additive, and an extended multiplicative function with a tanh activation parameter — in neural generative seq2seq models. Using the CST dataset, these models were trained and evaluated over 10 epochs with the AdamW optimizer. Evaluation criteria included validation loss and BLEU scores implemented under both greedy and beam search strategies with a beam size of k = 3. Results indicate that the model with the tanh-augmented multiplicative function significantly outperforms its counterparts, achieving the lowest validation loss (1.136484) and the highest BLEU scores (0.438926 under greedy search, 0.443000 under beam search, k = 3). These findings emphasize the crucial influence of selecting an appropriate attention-scoring function to enhance the performance of seq2seq models for chatbots, particularly highlighting the model integrating tanh activation as a promising approach to improving chatbot quality in customer support contexts.

Keywords: Attention weight, chatbot, encoder-decoder, neural generative attention, score function, sequence-to-sequence.

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Authors: Josef Wolfartsberger, Michael Heiml, Georg Schwarz, Sabrina Egger

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Growing individualization and higher numbers of variants in industrial assembly products raise the complexity of manufacturing processes. Technical assistance systems considering both procedural and human factors allow for an increase in product quality and a decrease in required learning times by supporting workers with precise working instructions. Due to varying needs of workers, the presentation of working instructions leads to several challenges. This paper presents an approach for a multi-modal visualization application to support assembly work of complex parts. Our approach is integrated within an interconnected assistance system network and supports the presentation of cloud-streamed textual instructions, images, videos, 3D animations and audio files along with multi-modal user interaction, customizable UI, multi-platform support (e.g. tablet-PC, TV screen, smartphone or Augmented Reality devices), automated text translation and speech synthesis. The worker benefits from more accessible and up-to-date instructions presented in an easy-to-read way.

Keywords: Assembly, assistive technologies, augmented reality, manufacturing, visualization.

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Authors: Hamed Rajabi, Naser Nematbakhsh, Naser Movahediniya

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IP multicasting is a key technology for many existing and emerging applications on the Internet. Furthermore, with increasing popularity of wireless devices and mobile equipment, it is necessary to determine the best way to provide this service in a wireless environment. IETF Mobile IP, that provides mobility for hosts in IP networks, proposes two approaches for mobile multicasting, namely, remote subscription (MIP-RS) and bi-directional tunneling (MIP-BT). In MIP-RS, a mobile host re-subscribes to the multicast groups each time it moves to a new foreign network. MIP-RS suffers from serious packet losses while mobile host handoff occurs. In MIP-BT, mobile hosts send and receive multicast packets by way of their home agents (HAs), using Mobile IP tunnels. Therefore, it suffers from inefficient routing and wastage of system resources. In this paper, we propose a protocol called Mobile Multicast support using Old Foreign Agent (MMOFA) for Mobile Hosts. MMOFA is derived from MIP-RS and with the assistance of Mobile host's Old foreign agent, routes the missing datagrams due to handoff in adjacent network via tunneling. Also, we studied the performance of the proposed protocol by simulation under ns-2.27. The results demonstrate that MMOFA has optimal routing efficiency and low delivery cost, as compared to other approaches.

Keywords: Mobile Multicast, Mobile IP, MMOFA, NS-2. 27.

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Authors: Ririn Dewi Cahyani, Muh. Hisjam, Wahyudi Sutopo, Kuncoro Harto Widodo

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Availability of raw materials is important for Indonesia as a furniture exporting country. Teak log as raw materials is supplied to the furniture industry by Perum Perhutani (PP). PP needs to involve carbon trading for nature conservation. PP also has an obligation in the Corporate Social Responsibility program. PP and furniture industry also must prosecute the regulations related to ecological issues and labor rights. This study has the objective to create the relationship model between supplier and manufacturer to fulfill teak log demand that involving teak forest carbon sequestration. A model is formulated as Goal Programming to get the favorable solution for teak log procurement and support carbon sequestration that considering economical, ecological, and social aspects of both supplier and manufacturer. The results show that the proposed model can be used to determine the teak log quantity involving carbon trading to achieve the seven goals to be satisfied the sustainability considerations.

Keywords: Availability of teak log, support carbon sequestration, goal programming, sustainability consideration.

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Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda

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In the context of the handwriting recognition, we propose an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods. The Distribution parameters, the centered moments of the different projections of the different segments, the centered moments of the word image coding according to the directions of Freeman, and the Barr features applied binary image of the word and on its different segments. The classification is achieved by a multi layers perceptron. A detailed experiment is carried and satisfactory recognition results are reported.

Keywords: Handwritten word recognition, neural networks, image processing, pattern recognition, features extraction.

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Authors: A. Larabi, M. S. Boucherit

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In this paper, we show that the association of the PI regulators for the speed and stator currents with a control strategy using the linearization by state feedback for an induction machine without speed sensor, and with an adaptation of the rotor resistance. The rotor speed is estimated by using the model reference adaptive system approach (MRAS). This method consists of using two models: The first is the reference model and the second is an adjustable one in which two components of the stator flux, obtained from the measurement of the currents and stator voltages are estimated. The estimated rotor speed is then obtained by canceling the difference between stator-flux of the reference model and those of the adjustable one. Satisfactory results of simulation are obtained and discussed in this paper to highlight the proposed approach.

Keywords: Asynchronous actuator, PI Regulator, adaptivemethod with reference model, Vector control.

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Authors: Monis Akhlaq, M Noman Jafri, Muzammil A Khan, Baber Aslam

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The Ad Hoc on demand distance vector (AODV) routing protocol is designed for mobile ad hoc networks (MANETs). AODV offers quick adaptation to dynamic link conditions; it is characterized by low memory overhead and low network utilization. The security issues related to the protocol remain challenging for the wireless network designers. Numerous schemes have been proposed for establishing secure communication between end users, these schemes identify that the secure operation of AODV is a bi tier task (routing and secure exchange of information at separate levels). Our endeavor in this paper would focus on achieving the routing and secure data exchange in a single step. This will facilitate the user nodes to perform routing, mutual authentications, generation and secure exchange of session key in one step thus ensuring confidentiality, integrity and authentication of data exchange in a more suitable way.

Keywords: AODV, key management, security, wirelessnetworks.

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Authors: Michael Lissack

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We depend upon explanation in order to “make sense" out of our world. And, making sense is all the more important when dealing with change. But, what happens if our explanations are wrong? This question is examined with respect to two types of explanatory model. Models based on labels and categories we shall refer to as “representations." More complex models involving stories, multiple algorithms, rules of thumb, questions, ambiguity we shall refer to as “compressions." Both compressions and representations are reductions. But representations are far more reductive than compressions. Representations can be treated as a set of defined meanings – coherence with regard to a representation is the degree of fidelity between the item in question and the definition of the representation, of the label. By contrast, compressions contain enough degrees of freedom and ambiguity to allow us to make internal predictions so that we may determine our potential actions in the possibility space. Compressions are explanatory via mechanism. Representations are explanatory via category. Managers are often confusing their evocation of a representation (category inclusion) as the creation of a context of compression (description of mechanism). When this type of explanatory error occurs, more errors follow. In the drive for efficiency such substitutions are all too often proclaimed – at the manager-s peril..

Keywords: Coherence, Emergence, Reduction, Model

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

Abstract:

Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: Affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, Signal Detection Theory, student engagement.

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