Search results for: Adaptive rood pattern search

Authors: P. P. S. Sifolo, M. J. Maimela M. P. Tladi

Abstract:

This article investigates technology used by Tshwane residents intended for tourism purposes. The aim is to contribute information for planning and management concerning technology within the tourism sector in the city of Tshwane, South Africa. This study identified the types of tourist related technologies used by the Tshwane residents, be it for business purposes or personal use. The study connected the exploitation of technology for tourism purposes through unpacking the tourism sector as it utilizes technology. Quantitative research methodology was used whereby self-completed questionnaires were chosen as research instruments. The research study carried out a search for knowledge on technology for tourism and the Tshwane residents; however the study revealed that technology has certainly imprinted tourism massively because of its effectiveness and efficiency. Technology has assisted tourism businesses stay abreast of competition with integrated communication technology (ICT) and because of that, SA is on the map as one of the economically performing countries in Africa. Moreover, technology and tourism make a meaningful impact on job creation and Gross Domestic Product (GDP).

Keywords: Information and Communication Technology, Technology for tourism, Tshwane residents.

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Authors: N. Pekin Alakoç, A. Apaydın

Abstract:

Quality control charts indicate out of control conditions if any nonrandom pattern of the points is observed or any point is plotted beyond the control limits. Nonrandom patterns of Shewhart control charts are tested with sensitizing rules. When the processes are defined with fuzzy set theory, traditional sensitizing rules are insufficient for defining all out of control conditions. This is due to the fact that fuzzy numbers increase the number of out of control conditions. The purpose of the study is to develop a set of fuzzy sensitizing rules, which increase the flexibility and sensitivity of fuzzy control charts. Fuzzy sensitizing rules simplify the identification of out of control situations that results in a decrease in the calculation time and number of evaluations in fuzzy control chart approach.

Keywords: Fuzzy set theory, Quality control charts, Run Rules, Unnatural patterns.

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Authors: Truong Quang Dang Khoa, Masahiro Nakagawa

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In this paper, a novel associative memory model will be proposed and applied to memory retrievals based on the conventional continuous time model. The conventional model presents memory capacity is very low and retrieval process easily converges to an equilibrium state which is very different from the stored patterns. Genetic Algorithms is well-known with the capability of global optimal search escaping local optimum on progress to reach a global optimum. Based on the well-known idea of Genetic Algorithms, this work proposes a heuristic rule to make a mutation when the state of the network is trapped in a spurious memory. The proposal heuristic associative memory show the stored capacity does not depend on the number of stored patterns and the retrieval ability is up to ~ 1.

Keywords: Artificial Intelligent, Soft Computing, NeuralNetworks, Genetic Algorithms, Hopfield Neural Networks, andAssociative Memories.

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Authors: S. H. R. Sadeghi, A. Sadoddin, A. Najafinejad

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Expansionism and ever-increasing population menace all different resources worldwide. The issue, hence, is critical in developing countries like Iran where new technologies are rapidly luxuriated and unguardedly applied, resulting in unexpected outcomes. However, uncommon and comprehensive approaches are introduced to take all the different aspects involved into consideration. In the last decade, few approaches such as community-based, stakeholders-oriented, adaptive and ultimately integrated management, have emerged and are developing for efficient, Co-management or best management, economic and sustainable development and management of watershed resources in Iran. In the present paper, an attempt has been made to focus on state-of-the-art approaches for the management of watershed resources applied in Iran. The study has been then supported by reports of some case studies conducted throughout the country involving previously mentioned approaches. Scrutinizing results of the researches verified a progressive tendency of the managerial approaches in watershed management strategies leading to a general approaching balance situation. The approaches are firmly rooted in educational, research, executive, legal and policy-making sectors leading to some recuperation at different levels. However, there is a long way ahead to naturalize detrimental effects of unscientific, illegal and over exploitation of the watershed resources in Iran.

Keywords: Comprehensive management, ecosystem balance, integrated watershed management, land resources optimization.

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Authors: Tang Hong, Zhang Lufeng, Chen Hua, Zhang Jianbo

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Today many developers use the Java components collected from the Internet as external LIBs to design and develop their own software. However, some unknown security bugs may exist in these components, such as SQL injection bug may comes from the components which have no specific check for the input string by users. To check these bugs out is very difficult without source code. So a novel method to check the bugs in Java bytecode based on points-to dataflow analysis is in need, which is different to the common analysis techniques base on the vulnerability pattern check. It can be used as an assistant tool for security analysis of Java bytecode from unknown softwares which will be used as extern LIBs.

Keywords: Java bytecode, points-to dataflow, vulnerability analysis

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Authors: Igor Astrov, Mikhail Pikkov

Abstract:

This paper focuses on a critical component of the situational awareness (SA), the neural control of depth flight of an autonomous underwater vehicle (AUV). Constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. With the SA strategy, we proposed a multirate neural control of an AUV trajectory using neural network model reference controller for a nontrivial mid-small size AUV "r2D4" stochastic model. This control system has been demonstrated and evaluated by simulation of diving maneuvers using software package Simulink. From the simulation results it can be seen that the chosen AUV model is stable in the presence of high noise, and also can be concluded that the fast SA of similar AUV systems with economy in energy of batteries can be asserted during the underwater missions in search-and-rescue operations.

Keywords: Autonomous underwater vehicles, multirate systems, neurocontrollers, situational awareness.

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Authors: Yi-Haur Shiau, Sun-In Lin, Shi-Wei Lo, Hsiu-Mei Chou, Yi-Hsuan Chen

Abstract:

This paper proposes a novel multi-format stream grid architecture for real-time image monitoring system. The system, based on a three-tier architecture, includes stream receiving unit, stream processor unit, and presentation unit. It is a distributed computing and a loose coupling architecture. The benefit is the amount of required servers can be adjusted depending on the loading of the image monitoring system. The stream receive unit supports multi capture source devices and multi-format stream compress encoder. Stream processor unit includes three modules; they are stream clipping module, image processing module and image management module. Presentation unit can display image data on several different platforms. We verified the proposed grid architecture with an actual test of image monitoring. We used a fast image matching method with the adjustable parameters for different monitoring situations. Background subtraction method is also implemented in the system. Experimental results showed that the proposed architecture is robust, adaptive, and powerful in the image monitoring system.

Keywords: Motion detection, grid architecture, image monitoring system, and background subtraction.

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Authors: Ahmet Baytak, Cenk Akbıyık

Abstract:

The purpose of this paper is to present teacher candidates- beliefs about technology integration in their field of study, which is classroom teaching in this case. The study was conducted among the first year students in college of education in Turkey. This study is based on both quantitative and qualitative data. For the quantitative data- Likert scale was used and for the qualitative data pattern matching was employed. The primary findings showed that students defined educational technology as technologies that improve learning with their visual, easily accessible, and productive features. They also believe these technologies could affect their future students- learning positively.

Keywords: Educational technology, classroom teacher candidates, technology integration, teacher education.

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Authors: Jain-Shing Liu

Abstract:

In this work, we study the problem of determining the minimum scheduling length that can satisfy end-to-end (ETE) traffic demand in scheduling-based multihop WSNs with cooperative multiple-input multiple-output (MIMO) transmission scheme. Specifically, we present a cross-layer formulation for the joint routing, scheduling and stream control problem by incorporating various power and rate adaptation schemes, and taking into account an antenna beam pattern model and the signal-to-interference-and-noise (SINR) constraint at the receiver. In the context, we also propose column generation (CG) solutions to get rid of the complexity requiring the enumeration of all possible sets of scheduling links.

Keywords: Wireless Sensor Networks, Cross-Layer Design, CooperativeMIMO System, Column Generation.

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Authors: I. Herraiz-Cardona, C. González-Buch, E. Ortega, V. Pérez-Herranz, J. García-Antón

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Hydrogen is considered to be the most promising candidate as a future energy carrier. One of the most used technologies for the electrolytic hydrogen production is alkaline water electrolysis. However, due to the high energy requirements, the cost of hydrogen produced in such a way is high. In continuous search to improve this process using advanced electrocatalytic materials for the hydrogen evolution reaction (HER), Ni type Raney and macro-porous Ni-Co electrodes were prepared on AISI 304 stainless steel substrates by electrodeposition. The developed electrodes were characterized by SEM and confocal laser scanning microscopy. HER on these electrodes was evaluated in 30 wt.% KOH solution by means of hydrogen discharge curves and galvanostatic tests. Results show that the developed electrodes present a most efficient behaviour for HER when comparing with the smooth Ni cathode. It has been reported a reduction in the energy consumption of the electrolysis cell of about 25% by using the developed coatings as cathodes.

Keywords: Alkaline water electrolysis, energy efficiency, porous nickel electrodes

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Authors: M. Zerikat, S. Chekroun

Abstract:

This paper proposes an effective adaptation learning algorithm based on artificial neural networks for speed control of an induction motor assumed to operate in a high-performance drives environment. The structure scheme consists of a neural network controller and an algorithm for changing the NN weights in order that the motor speed can accurately track of the reference command. This paper also makes uses a very realistic and practical scheme to estimate and adaptively learn the noise content in the speed load torque characteristic of the motor. The availability of the proposed controller is verified by through a laboratory implementation and under computation simulations with Matlab-software. The process is also tested for the tracking property using different types of reference signals. The performance and robustness of the proposed control scheme have evaluated under a variety of operating conditions of the induction motor drives. The obtained results demonstrate the effectiveness of the proposed control scheme system performances, both in steady state error in speed and dynamic conditions, was found to be excellent and those is not overshoot.

Keywords: Electric drive, Induction motor, speed control, Adaptive control, neural network, High Performance.

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Authors: G.T. Cirella, L. Tao

Abstract:

The index of sustainable functionality (ISF) is an adaptive, multi-criteria technique that is used to measure sustainability; it is a concept that can be transposed to many regions throughout the world. An ISF application of the Southern Regional Organisation of Councils (SouthROC) in South East Queensland (SEQ) – the fastest growing region in Australia – indicated over a 25 year period an increase of over 10% level of functionality from 58.0% to 68.3%. The ISF of SouthROC utilised methodologies that derived from an expert panel based approach. The overall results attained an intermediate level of functionality which amounted to related concerns of economic progress and lack of social awareness. Within the region, a solid basis for future testing by way of measured changes and developed trends can be established. In this regard as management tool, the ISF record offers support for regional sustainability practice and decision making alike. This research adaptively analyses sustainability – a concept that is lacking throughout much of the academic literature and any reciprocal experimentation. This lack of knowledge base has been the emphasis of where future sustainability research can grow from and prove useful in rapidly growing regions. It is the intentions of this research to help further develop the notions of index-based quantitative sustainability.

Keywords: Environmental engineering, index of sustainable functionality, sustainability indicators, sustainable development.

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Authors: Zulhamsyah Imran, Masahiro Yamao

Abstract:

Social resilience has role to govern the local community and coastal fisheries resources toward sustainable fisheries development in tsunami affected area. This paper asses, explore and investigates of indigenous institutions, external and internal facilitators toward strengthening social resilience. Identification of the genuine organizations role had been conducted twice by using Rapid Assessment Appraisal, Focus Group Discussion, and in-depth interview for collecting primary and secondary data. Local wisdom had a contribution and adaptable to rebound social resilience. The Panglima Laot Lhok (sea commander) had determined and adapted role on recovery of the fishing community, particularly facilitated aid delivery to fishermen, as shown in anchovy fisheries relief case in Krueng Raya Bay. Toke Bangku (financial trader) had stimulated for reinforcement of advance payment and market channel. The other institutions supported upon linking and bridging connectivity among stakeholders. Collaborative governance can avoid conflict, reduce donor dependency and strengthen social resilience within fishing community.

Keywords: Fishing community, indigenous institution, adaptive role, collaborative, social resilience.

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Authors: S. Adhirai, R. P. Mahapatra, Paramjit Singh

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Optimization is an important tool in making decisions and in analysing physical systems. In mathematical terms, an optimization problem is the problem of finding the best solution from among the set of all feasible solutions. The paper discusses the Whale Optimization Algorithm (WOA), and its applications in different fields. The algorithm is tested using MATLAB because of its unique and powerful features. The benchmark functions used in WOA algorithm are grouped as: unimodal (F1-F7), multimodal (F8-F13), and fixed-dimension multimodal (F14-F23). Out of these benchmark functions, we show the experimental results for F7, F11, and F19 for different number of iterations. The search space and objective space for the selected function are drawn, and finally, the best solution as well as the best optimal value of the objective function found by WOA is presented. The algorithmic results demonstrate that the WOA performs better than the state-of-the-art meta-heuristic and conventional algorithms.

Keywords: Optimization, optimal value, objective function, optimization problems, meta-heuristic optimization algorithms, Whale Optimization Algorithm, Implementation, MATLAB.

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Authors: M. Armenteros, A. Domínguez, M. Fernández, A. J. Benítez

Abstract:

The following paper describes the video database tool used by the Fédération Internationale de Football Association (FIFA) as part of the research project developed in collaboration with the Carlos III University of Madrid. The database project began in 2012, with the aim of creating an educational tool for the training of instructors, referees and assistant referees, and it has been used in all FUTURO III courses since 2013. The platform now contains 3,135 video clips of different match situations from FIFA competitions. It has 1,835 users (FIFA instructors, referees and assistant referees). In this work, the main features of the database are described, such as the use of a search tool and the creation of multimedia presentations and video quizzes. The database has been developed in MySQL, ActionScript, Ruby on Rails and HTML. This tool has been rated by users as "very good" in all courses, which prompt us to introduce it as an ideal tool for any other sport that requires the use of video analysis.

Keywords: Video database, FIFA, refereeing, e-learning.

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Authors: Elteyeb Eljack, Takashi Ohta

Abstract:

Proper orthogonal decomposition (POD) is used to reconstruct spatio-temporal data of a fully developed turbulent channel flow with density variation at Reynolds number of 150, based on the friction velocity and the channel half-width, and Prandtl number of 0.71. To apply POD to the fully developed turbulent channel flow with density variation, the flow field (velocities, density, and temperature) is scaled by the corresponding root mean square values (rms) so that the flow field becomes dimensionless. A five-vector POD problem is solved numerically. The reconstructed second-order moments of velocity, temperature, and density from POD eigenfunctions compare favorably to the original Direct Numerical Simulation (DNS) data.

Keywords: Pattern Recognition, POD, Coherent Structures, Low dimensional modelling.

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Authors: Ephraim Gower, Thato Tsalaile, Monageng Kgwadi, Malcolm Hawksford.

Abstract:

This paper introduces a new point estimation algorithm, with particular focus on coherent noise suppression, given several measurements of the device under test where it is assumed that 1) the noise is first-order stationery and 2) the device under test is linear and time-invariant. The algorithm exploits the robustness of the Pitman estimator of the Cauchy location parameter through the initial scaling of the test signal by a centred Gaussian variable of predetermined variance. It is illustrated through mathematical derivations and simulation results that the proposed algorithm is more accurate and consistently robust to outliers for different tailed density functions than the conventional methods of sample mean (coherent averaging technique) and sample median search.

Keywords: Central limit theorem, Fisher-Cramer Rao, gamma function, Pitman estimator.

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Authors: Sol-Kil Oh, Hye-Jin Lee, Jung-Han Song, Kyoung-Tae Kim, Nak-Kyu Lee, Jong-Ho Kim

Abstract:

This paper deals with a novel technique for the fabrication of Spiral grooves in a dynamic thrust bearing. The main scheme proposed in this paper is to fabricate the microgrooves using desktop forming system. This process has advantages compared to the conventional electro-chemical machining in the viewpoint of a higher productivity. For this reason, a new testing apparatus is designed and built for press forming microgrooves on a surface of the thrust bearing. The material used in this study is sintered Cu-Fe alloy. The effects of the forming load on the performance of micro press forming are experimentally investigated. From the experimental results, formed depths are closed to the target ones with increasing the forming load.

Keywords: Desktop forming system, Fluid dynamic bearing, Thrust bearing, Microgroove.

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Authors: Qasim Zafar, Matthew Anderson, Esteban Garcia, Steven Drager

Abstract:

Software failures can present an enormous detriment to people's lives and cost millions of dollars to repair when they are unexpectedly encountered in the wild. Despite a significant portion of the software development lifecycle and resources are dedicated to testing, software failures are a relatively frequent occurrence. Nevertheless, the evaluation of testing effectiveness remains at the forefront of ensuring high-quality software and software metrics play a critical role in providing valuable insights into quantifiable objectives to assess the level of assurance and confidence in the system. As the selection of appropriate metrics can be an arduous process, the goal of this paper is to shed light on the significance of software metrics by examining a range of testing techniques and metrics as well as identifying key areas for improvement. In doing so, this paper presents a method to compare the effectiveness of testing techniques with heterogeneous output metrics. Additionally, through this investigation, readers will gain a deeper understanding of how metrics can help to drive informed decision-making on delivering high-quality software and facilitate continuous improvement in testing practices.

Keywords: Software testing, software metrics, testing effectiveness, black box testing, random testing, adaptive random testing, combinatorial testing, fuzz testing, equivalence partition, boundary value analysis, white box testings.

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Authors: Michiharu Maeda, Shinya Tsuda

Abstract:

This paper presents an algorithm of particle swarm optimization with reduction for global optimization problems. Particle swarm optimization is an algorithm which refers to the collective motion such as birds or fishes, and a multi-point search algorithm which finds a best solution using multiple particles. Particle swarm optimization is so flexible that it can adapt to a number of optimization problems. When an objective function has a lot of local minimums complicatedly, the particle may fall into a local minimum. For avoiding the local minimum, a number of particles are initially prepared and their positions are updated by particle swarm optimization. Particles sequentially reduce to reach a predetermined number of them grounded in evaluation value and particle swarm optimization continues until the termination condition is met. In order to show the effectiveness of the proposed algorithm, we examine the minimum by using test functions compared to existing algorithms. Furthermore the influence of best value on the initial number of particles for our algorithm is discussed.

Keywords: Particle swarm optimization, Global optimization, Metaheuristics, Reduction.

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Authors: Sergio Pissanetzky

Abstract:

The ability of the brain to organize information and generate the functional structures we use to act, think and communicate, is a common and easily observable natural phenomenon. In object-oriented analysis, these structures are represented by objects. Objects have been extensively studied and documented, but the process that creates them is not understood. In this work, a new class of discrete, deterministic, dissipative, host-guest dynamical systems is introduced. The new systems have extraordinary self-organizing properties. They can host information representing other physical systems and generate the same functional structures as the brain does. A simple mathematical model is proposed. The new systems are easy to simulate by computer, and measurements needed to confirm the assumptions are abundant and readily available. Experimental results presented here confirm the findings. Applications are many, but among the most immediate are object-oriented engineering, image and voice recognition, search engines, and Neuroscience.

Keywords: AI, artificial intelligence, complex system, object oriented, OO, refactoring.

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Authors: Songdi Li, Louise Spry, Tony Woodall

Abstract:

Nowadays, Corporate Social responsibility (CSR) is becoming a buzz word, and more and more academics are putting efforts on CSR studies. It is believed that CSR could influence Corporate Reputation (CR), and they hold a favourable view that CSR leads to a positive CR. To be specific, the CSR related activities in the reputational context have been regarded as ways that associate to excellent financial performance, value creation, etc. Also, it is argued that CSR and CR are two sides of one coin; hence, to some extent, doing CSR is equal to establishing a good reputation. Still, there is no consensus of the CSR-CR relationship in the literature; thus, a systematic literature review is highly in need. This research conducts a systematic literature review with both bibliometric and content analysis. Data are selected from English language sources, and academic journal articles only, then, keyword combinations are applied to identify relevant sources. Data from Scopus and WoS are gathered for bibliometric analysis. Scopus search results were saved in RIS and CSV formats, and Web of Science (WoS) data were saved in TXT format and CSV formats in order to process data in the Bibexcel software for further analysis which later will be visualised by the software VOSviewer. Also, content analysis was applied to analyse the data clusters and the key articles. In terms of the topic of CSR-CR, this literature review with bibliometric analysis has made four achievements. First, this paper has developed a systematic study which quantitatively depicts the knowledge structure of CSR and CR by identifying terms closely related to CSR-CR (such as ‘corporate governance’) and clustering subtopics emerged in co-citation analysis. Second, content analysis is performed to acquire insight on the findings of bibliometric analysis in the discussion section. And it highlights some insightful implications for the future research agenda, for example, a psychological link between CSR-CR is identified from the result; also, emerging economies and qualitative research methods are new elements emerged in the CSR-CR big picture. Third, a multidisciplinary perspective presents through the whole bibliometric analysis mapping and co-word and co-citation analysis; hence, this work builds a structure of interdisciplinary perspective which potentially leads to an integrated conceptual framework in the future. Finally, Scopus and WoS are compared and contrasted in this paper; as a result, Scopus which has more depth and comprehensive data is suggested as a tool for future bibliometric analysis studies. Overall, this paper has fulfilled its initial purposes and contributed to the literature. To the author’s best knowledge, this paper conducted the first literature review of CSR-CR researches that applied both bibliometric analysis and content analysis; therefore, this paper achieves its methodological originality. And this dual approach brings advantages of carrying out a comprehensive and semantic exploration in the area of CSR-CR in a scientific and realistic method. Admittedly, its work might exist subjective bias in terms of search terms selection and paper selection; hence triangulation could reduce the subjective bias to some degree.

Keywords: Corporate social responsibility, corporate reputation, bibliometric analysis, software data analysis.

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Authors: Homayoon Zarshenas, Mahdi Bamdad, Hadi Grailu, Akbar A. Shakoori

Abstract:

In this study we focus on improvement performance of a cue based Motor Imagery Brain Computer Interface (BCI). For this purpose, data fusion approach is used on results of different classifiers to make the best decision. At first step Distinction Sensitive Learning Vector Quantization method is used as a feature selection method to determine most informative frequencies in recorded signals and its performance is evaluated by frequency search method. Then informative features are extracted by packet wavelet transform. In next step 5 different types of classification methods are applied. The methodologies are tested on BCI Competition II dataset III, the best obtained accuracy is 85% and the best kappa value is 0.8. At final step ordered weighted averaging (OWA) method is used to provide a proper aggregation classifiers outputs. Using OWA enhanced system accuracy to 95% and kappa value to 0.9. Applying OWA just uses 50 milliseconds for performing calculation.

Keywords: BCI, EEG, Classifier, Fuzzy operator, OWA.

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Authors: M. Nemissi, H. Seridi, H. Akdag

Abstract:

This paper presents and evaluates a new classification method that aims to improve classifiers performances and speed up their training process. The proposed approach, called labeled classification, seeks to improve convergence of the BP (Back propagation) algorithm through the addition of an extra feature (labels) to all training examples. To classify every new example, tests will be carried out each label. The simplicity of implementation is the main advantage of this approach because no modifications are required in the training algorithms. Therefore, it can be used with others techniques of acceleration and stabilization. In this work, two models of the labeled classification are proposed: the LMLP (Labeled Multi Layered Perceptron) and the LNFC (Labeled Neuro Fuzzy Classifier). These models are tested using Iris, wine, texture and human thigh databases to evaluate their performances.

Keywords: Artificial neural networks, Fusion of neural networkfuzzysystems, Learning theory, Pattern recognition.

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Authors: Pinfa Boonrong, Boonserm Kaewkamnerdpong

Abstract:

As nanotechnology advances, the use of nanotechnology for medical purposes in the field of nanomedicine seems more promising; the rise of nanorobots for medical diagnostics and treatments could be arriving in the near future. This study proposes a swarm intelligence based control mechanism for swarm nanorobots that operate as artificial platelets to search for wounds. The canonical particle swarm optimization algorithm is employed in this study. A simulation in the circulatory system is constructed and used for demonstrating the movement of nanorobots with essential characteristics to examine the performance of proposed control mechanism. The effects of three nanorobot capabilities including their perception range, maximum velocity and respond time are investigated. The results show that canonical particle swarm optimization can be used to control the early version nanorobots with simple behaviors and actions.

Keywords: Artificial platelets, canonical particle swarm optimization, nanomedicine, nanorobot, swarm intelligence.

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Authors: Rainer Schneider, Stephan Lau, Levin Kuhlmann, Simon Vogrin, Maciej Gratkowski, Mark Cook, Jens Haueisen

Abstract:

Cardiac pulse-related artifacts in the EEG recorded simultaneously with fMRI are complex and highly variable. Their effective removal is an unsolved problem. Our aim is to develop an adaptive removal algorithm based on the matching pursuit (MP) technique and to compare it to established methods using a visual evoked potential (VEP). We recorded the VEP inside the static magnetic field of an MR scanner (with artifacts) as well as in an electrically shielded room (artifact free). The MP-based artifact removal outperformed average artifact subtraction (AAS) and optimal basis set removal (OBS) in terms of restoring the EEG field map topography of the VEP. Subsequently, a dipole model was fitted to the VEP under each condition using a realistic boundary element head model. The source location of the VEP recorded inside the MR scanner was closest to that of the artifact free VEP after cleaning with the MP-based algorithm as well as with AAS. While none of the tested algorithms offered complete removal, MP showed promising results due to its ability to adapt to variations of latency, frequency and amplitude of individual artifact occurrences while still utilizing a common template.

Keywords: matching pursuit, ballistocardiogram, artifactremoval, EEG/fMRI.

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Authors: R. Xu, X. Zhao, X. Li, C. Kwan, C.-I Chang

Abstract:

An image texture analysis and target recognition approach of using an improved image texture feature coding method (TFCM) and Support Vector Machine (SVM) for target detection is presented. With our proposed target detection framework, targets of interest can be detected accurately. Cascade-Sliding-Window technique was also developed for automated target localization. Application to mammogram showed that over 88% of normal mammograms and 80% of abnormal mammograms can be correctly identified. The approach was also successfully applied to Synthetic Aperture Radar (SAR) and Ground Penetrating Radar (GPR) images for target detection.

Keywords: Image texture analysis, feature extraction, target detection, pattern classification.

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Authors: Perapong Vichitkraivin, Orachat Chitsobhuk

Abstract:

In this paper, an improvement of PDLZW implementation with a new dictionary updating technique is proposed. A unique dictionary is partitioned into hierarchical variable word-width dictionaries. This allows us to search through dictionaries in parallel. Moreover, the barrel shifter is adopted for loading a new input string into the shift register in order to achieve a faster speed. However, the original PDLZW uses a simple FIFO update strategy, which is not efficient. Therefore, a new window based updating technique is implemented to better classify the difference in how often each particular address in the window is referred. The freezing policy is applied to the address most often referred, which would not be updated until all the other addresses in the window have the same priority. This guarantees that the more often referred addresses would not be updated until their time comes. This updating policy leads to an improvement on the compression efficiency of the proposed algorithm while still keep the architecture low complexity and easy to implement.

Keywords: lossless data compression, LZW algorithm, PDLZW algorithm, WSC and dictionary update.

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Authors: Young-Seok Choi

Abstract:

It has been known that a characteristic Burst-Suppression (BS) pattern appears in EEG during the early recovery period following Cardiac Arrest (CA). Here, to explore the relationship between cortical and subcortical neural activities underlying BS, extracellular activity in the parietal cortex and the centromedian nucleus of the thalamus and extradural EEG were recorded in a rodent CA model. During the BS, the cortical firing rate is extraordinarily high, and that bursts in EEG correlate to dense spikes in cortical neurons. Newly observed phenomena are that 1) thalamic activity reemerges earlier than cortical activity following CA, and 2) the correlation coefficient of cortical and thalamic activities rises during BS period. These results would help elucidate the underlying mechanism of brain recovery after CA injury.

Keywords: Cortex, thalamus, cardiac arrest, burst-suppression.

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Authors: I. L. Ahmad, M. Mohamed, N. A. Ab. Ghani

Abstract:

This paper presents the work of signal discrimination specifically for Electrocardiogram (ECG) waveform. ECG signal is comprised of P, QRS, and T waves in each normal heart beat to describe the pattern of heart rhythms corresponds to a specific individual. Further medical diagnosis could be done to determine any heart related disease using ECG information. The emphasis on QRS Complex classification is further discussed to illustrate the importance of it. Pan-Tompkins Algorithm, a widely known technique has been adapted to realize the QRS Complex classification process. There are eight steps involved namely sampling, normalization, low pass filter, high pass filter (build a band pass filter), derivation, squaring, averaging and lastly is the QRS detection. The simulation results obtained is represented in a Graphical User Interface (GUI) developed using MATLAB.

Keywords: ECG, Pan Tompkins Algorithm, QRS Complex, Simulation

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