Search results for: learning theory

Authors: R. Gary Black, Abolhassan Astaneh-Asl

Abstract:

The International Building Code (IBC) and the  California Building Code (CBC) both recognize four basic types of  steel seismic resistant frames; moment frames, concentrically braced  frames, shear walls and eccentrically braced frames. Based on  specified geometries and detailing, the seismic performance of these  steel frames is well understood. In 2011, the authors designed an  innovative steel braced frame system with tapering members in the  general shape of a branching tree as a seismic retrofit solution to an  existing four story “lift-slab” building. Located in the seismically  active San Francisco Bay Area of California, a frame of this  configuration, not covered by the governing codes, would typically  require model or full scale testing to obtain jurisdiction approval.  This paper describes how the theories, protocols, and code  requirements of eccentrically braced frames (EBFs) were employed  to satisfy the 2009 International Building Code (IBC) and the 2010  California Building Code (CBC) for seismically resistant steel frames  and permit construction of these nonconforming geometries.

 

Keywords: Eccentrically Braced Frame, Lift Slab Construction, Seismic Retrofit, Shear Link, Steel Design.

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Authors: Moeiz Miraoui, Chakib Tadj, Chokri ben Amar

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Devices in a pervasive computing system (PCS) are characterized by their context-awareness. It permits them to provide proactively adapted services to the user and applications. To do so, context must be well understood and modeled in an appropriate form which enhance its sharing between devices and provide a high level of abstraction. The most interesting methods for modeling context are those based on ontology however the majority of the proposed methods fail in proposing a generic ontology for context which limit their usability and keep them specific to a particular domain. The adaptation task must be done automatically and without an explicit intervention of the user. Devices of a PCS must acquire some intelligence which permits them to sense the current context and trigger the appropriate service or provide a service in a better suitable form. In this paper we will propose a generic service ontology for context modeling and a context-aware service adaptation based on a service oriented definition of context.

Keywords: Pervasive computing system, context, contextawareness, service, context modeling, ontology, adaptation, machine learning.

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Authors: Mohsen A. Bakouri, Andrey V. Savkin, Abdul-Hakeem H. Alomari, Robert F. Salamonsen, Einly Lim, Nigel H. Lovell

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Physiological control of a left ventricle assist device (LVAD) is generally a complicated task due to diverse operating environments and patient variability. In this work, a tracking control algorithm based on sliding mode and feed forward control for a class of discrete-time single input single output (SISO) nonlinear uncertain systems is presented. The controller was developed to track the reference trajectory to a set operating point without inducing suction in the ventricle. The controller regulates the estimated mean pulsatile flow Qp and mean pulsatility index of pump rotational speed PIω that was generated from a model of the assist device. We recall the principle of the sliding mode control theory then we combine the feed-forward control design with the sliding mode control technique to follow the reference trajectory. The uncertainty is replaced by its upper and lower boundary. The controller was tested in a computer simulation covering two scenarios (preload and ventricular contractility). The simulation results prove the effectiveness and the robustness of the proposed controller

Keywords: robust control system, discrete-sliding mode, left ventricularle assist devicse, pulsatility index.

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Authors: Jui-Pui Hung, Yu-Sheng Lai, Tzuo-Liang Luo, Kung-Da Wu, Yun-Ji Zhan

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This study presented the investigation of the influence of the tool holder interface stiffness on the dynamic characteristics of a spindle tool system. The interface stiffness was produced by drawbar force on the tool holder, which tends to affect the spindle dynamics. In order to assess the influence of interface stiffness on the vibration characteristic of spindle unit, we first created a three dimensional finite element model of a high speed spindle system integrated with tool holder. The key point for the creation of FEM model is the modeling of the rolling interface within the angular contact bearings and the tool holder interface. The former can be simulated by a introducing a series of spring elements between inner and outer rings. The contact stiffness was calculated according to Hertz contact theory and the preload applied on the bearings. The interface stiffness of the tool holder was identified through the experimental measurement and finite element modal analysis. Current results show that the dynamic stiffness was greatly influenced by the tool holder system. In addition, variations of modal damping, static stiffness and dynamic stiffness of the spindle tool system were greatly determined by the interface stiffness of the tool holder which was in turn dependent on the draw bar force applied on the tool holder. Overall, this study demonstrates that identification of the interface characteristics of spindle tool holder is of very importance for the refinement of the spindle tooling system to achieve the optimum machining performance.

Keywords: Dynamic stiffness, Drawbar force, Interface stiffness, Spindle-tool holder.

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Authors: Rujijan Vichivanives

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This research aims to create a knowledge-based system as a database for self-healthcare analysis, diagnosis of simple illnesses, and the use of Thai herbs instead of modern medicine by using principles of Thai traditional medication theory. These were disseminated by website network programs within Suan Sunandha Rajabhat University. The population used in this study was divided into two groups: the first group consisted of four experts of Thai traditional medication and the second group was 300 website users. The methods used for collecting data were paper questionnaires and poll questionnaires on the website. The statistics used for analyzing data was at an average level. The results were divided into three parts: the first part was the development of a knowledge-based system and the second part was applied programs on website. Both parts could be fulfilled and achieved according to the set goal. The third part was the evaluation of the study: The evaluation of the viewpoints of the experts towards website designs were evaluated at a good level of 4.20. The satisfaction evaluation of the users was found at a good level of average satisfactory level at 4.24. It was found that the young population of those under the age of 16 had less cares about their health than the population of other teenagers, working age adults and those of older age. The research findings should be extended in order to encourage the lifestyle modifications to people of all ages by using the self-healthcare principles.

Keywords: Developing, Herbs, Knowledge-based system, Medical treatment.

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Authors: Elizabeth B. Varghese, M. Wilscy

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A face recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame. A lot of algorithms have been proposed for face recognition. Vector Quantization (VQ) based face recognition is a novel approach for face recognition. Here a new codebook generation for VQ based face recognition using Integrated Adaptive Fuzzy Clustering (IAFC) is proposed. IAFC is a fuzzy neural network which incorporates a fuzzy learning rule into a competitive neural network. The performance of proposed algorithm is demonstrated by using publicly available AT&T database, Yale database, Indian Face database and a small face database, DCSKU database created in our lab. In all the databases the proposed approach got a higher recognition rate than most of the existing methods. In terms of Equal Error Rate (ERR) also the proposed codebook is better than the existing methods.

Keywords: Face Recognition, Vector Quantization, Integrated Adaptive Fuzzy Clustering, Self Organization Map.

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Authors: Ziya Uddin

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This paper deals with the theoretical and numerical investigation of magneto hydrodynamic boundary layer flow of a nanofluid past a wedge shaped wick in heat pipe used for the cooling of electronic components and different type of machines. To incorporate the effect of nanoparticle diameter, concentration of nanoparticles in the pure fluid, nanothermal layer formed around the nanoparticle and Brownian motion of nanoparticles etc., appropriate models are used for the effective thermal and physical properties of nanofluids. To model the rotation of nanoparticles inside the base fluid, microfluidics theory is used. In this investigation ethylene glycol (EG) based nanofluids, are taken into account. The non-linear equations governing the flow and heat transfer are solved by using a very effective particle swarm optimization technique along with Runge-Kutta method. The values of heat transfer coefficient are found for different parameters involved in the formulation viz. nanoparticle concentration, nanoparticle size, magnetic field and wedge angle etc. It is found that, the wedge angle, presence of magnetic field, nanoparticle size and nanoparticle concentration etc. have prominent effects on fluid flow and heat transfer characteristics for the considered configuration.

Keywords: Heat transfer, Heat pipe, numerical modeling, nanofluid applications, particle swarm optimization, wedge shaped wick.

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Authors: Tomás Speziale

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This paper aims to analyse how Ian Hacking states the theoretical basis of his research on the classification of people. Although all his early philosophical education had been based in Foucault, it is also true that Erving Goffman’s perspective provided him with epistemological and methodological tools for understanding face-to-face relationships. Hence, all his works must be thought of as social science texts that combine the research on how the individuals are constituted ‘top-down’ (as in Foucault), with the inquiry into how people renegotiate ‘bottom-up’ the classifications about them. Thus, Hacking´s proposal constitutes a middle ground between the French Philosopher and the American Sociologist. Placing himself between both authors allows Hacking to build a frame that is expected to adjust to Social Sciences’ main particularity: the fact that they study interactive kinds. These are kinds of people, which imply that those who are classified can change in certain ways that prompt the need for changing previous classifications themselves. It is all about the interaction between the labelling of people and the people who are classified. Consequently, understanding the way in which Hacking uses Foucault’s and Goffman’s theories is essential to fully comprehend the social dynamic between individuals and concepts, what Bert Hansen had called dialectical realism. His theoretical proposal, therefore, is not only valuable because it combines diverse perspectives, but also because it constitutes an utterly original and relevant framework for Sociological theory and particularly for Criminology.

Keywords: Classification of people, Foucault`s archaeology, Goffman`s interpersonal sociology, interactive kinds.

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Authors: Abd Latif Abdul Rahman, Adnan Jamaludin, Zamalia Mahmud

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Unified Theory of Acceptance and Use of Technology (UTAUT) model has demonstrated the influencing factors for generic information systems use such as tablet personal computer (TPC) and mobile communication. However, in the context of digital library system, there has been very little effort to determine factors affecting the intention to use digital library based on the UTAUT model. This paper investigates factors that are expected to influence the intention of postgraduate students to use digital library based on modified UTAUT model. The modified model comprises of constructs represented by several latent variables, namely performance expectancy (PE), effort expectancy (EE), information quality (IQ) and service quality (SQ) and moderated by age, gender and experience in using digital library. Results show that performance expectancy, effort expectancy and information quality are positively related to the intention to use digital library, while service quality is negatively related to the intention to use digital library. Age and gender have shown no evidence of any significant interactions, while experience in using digital library significantly interacts with effort expectancy and intention to use digital library. This has provided the evidence of a moderating effect of experience in the intention to use digital library. It is expected that this research will shed new lights into research of acceptance and intention to use the library in a digital environment.

Keywords: Intention to use digital library, UTAUT model, performance expectancy, effort expectancy, information quality, service quality.

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Authors: Li Ni, Pen ManMan, Li KenLi

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Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.

Keywords: Chemical reaction optimization, expectation maximization, initial, objective function clustering.

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Authors: Berna Cantürk-Günhan, Esra Bukova-Güzel

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The purpose of the study is to determine the primary mathematics student teachers- views related to use instructional technology tools in course of the learning process and to reveal how the sample presentations towards different mathematical concepts affect their views. This is a qualitative study involving twelve mathematics students from a public university. The data gathered from two semi-structural interviews. The first one was realized in the beginning of the study. After that the representations prepared by the researchers were showed to the participants. These representations contain animations, Geometer-s Sketchpad activities, video-clips, spreadsheets, and power-point presentations. The last interview was realized at the end of these representations. The data from the interviews and content analyses were transcribed and read and reread to explore the major themes. Findings revealed that the views of the students changed in this process and they believed that the instructional technology tools should be used in their classroom.

Keywords: Integrating Technology, Mathematics Education, Primary Education, Teacher Education.

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Authors: R. Bremananth

Abstract:

Biometric authentication is an essential task for any kind of real-life applications. In this paper, we contribute two primary paradigms to Iris recognition such as Robust Eyelash Detection (RED) using pathway kernels and hair curve fitting synthesized model. Based on these two paradigms, rotation invariant iris recognition is enhanced. In addition, the presented framework is tested with real-life iris data to provide the authentication for LRC (Learning Resource Center) users. Recognition performance is significantly improved based on the contributed schemes by evaluating real-life irises. Furthermore, the framework has been implemented using Java programming language. Experiments are performed based on 1250 diverse subjects in different angles of variations on the authentication process. The results revealed that the methodology can deploy in the process on LRC management system and other security required applications.

Keywords: Authentication, biometric, eye lashes detection, iris scanning, LRC security, secure access.

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Authors: Hossein Heidari Tabrizi, Azizeh Chalak

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The present study examined how translation teachers develop final tests as measures for checking on the quality of students’ academic translation in Iranian context. To achieve this goal, thirty experienced male and female translation teachers from the four types of the universities offering the program were invited to an in-depth 30-minute one-session semi-structured interview. The responses provided showed how much discrepancy exists among the Iranian translation teachers (as developers of final translation tests), who are least informed with the current translation evaluation methods. It was also revealed that the criteria they use for developing such tests and scoring student translations are not theory-driven but are highly subjective, mainly based on their personal experience and intuition. Hence, the quality and accountability of such tests are under serious question. The results also confirmed that the dominant method commonly and currently practiced is the purely essay-type format. To remedy the situation, some suggestions are in order. As part of the solution, to improve the reliability and validity of such tests, the present summative, product-oriented evaluation should be accompanied with some formative, process-oriented methods of evaluation. Training the teachers and helping them get acquainted with modern principles of translation evaluation as well as the existing models, and rating scales does improve the quality of academic translation evaluation.

Keywords: Iranian universities, students’ academic translations, translation final tests, undergraduate translation programs.

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Authors: Yunyoung Nam, Junghun Ryu, Yoo-Joo Choi, We-Duke Cho

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This paper presents a novel approach for representing the spatio-temporal topology of the camera network with overlapping and non-overlapping fields of view (FOVs). The topology is determined by tracking moving objects and establishing object correspondence across multiple cameras. To track people successfully in multiple camera views, we used the Merge-Split (MS) approach for object occlusion in a single camera and the grid-based approach for extracting the accurate object feature. In addition, we considered the appearance of people and the transition time between entry and exit zones for tracking objects across blind regions of multiple cameras with non-overlapping FOVs. The main contribution of this paper is to estimate transition times between various entry and exit zones, and to graphically represent the camera topology as an undirected weighted graph using the transition probabilities.

Keywords: Surveillance, multiple camera, people tracking, topology.

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Authors: Kusumaphorn Sompong, Helen Lawton Smith, Barbara Igel

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This paper provides a key driver-based conceptual framework that can be used to improve a firm-s success in commercializing technology and in new product innovation resulting from collaboration with other organizations through strategic alliances. Based on a qualitative study using an interview approach, strategic alliances of entrepreneurs in the food processing industry in Thailand are explored. This paper describes factors affecting decisions to collaborate through alliances. It identifies four issues: maintaining the efficiency of the value chain for production capability, adapting to present and future competition, careful assessment of value of outcomes, and management of innovation. We consider five driving factors: resource orientation, assessment of risk, business opportunity, sharing of benefits and confidence in alliance partners. These factors will be of interest to entrepreneurs and policy makers with regard to further understanding of the direction of business strategies.

Keywords: Managing collaboration, strategic alliance, technology commercialization, innovation.

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Authors: N. M. Nawi, R. S. Ransing, M. R. Ransing

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The conjugate gradient optimization algorithm is combined with the modified back propagation algorithm to yield a computationally efficient algorithm for training multilayer perceptron (MLP) networks (CGFR/AG). The computational efficiency is enhanced by adaptively modifying initial search direction as described in the following steps: (1) Modification on standard back propagation algorithm by introducing a gain variation term in the activation function, (2) Calculation of the gradient descent of error with respect to the weights and gains values and (3) the determination of a new search direction by using information calculated in step (2). The performance of the proposed method is demonstrated by comparing accuracy and computation time with the conjugate gradient algorithm used in MATLAB neural network toolbox. The results show that the computational efficiency of the proposed method was better than the standard conjugate gradient algorithm.

Keywords: Adaptive gain variation, back-propagation, activation function, conjugate gradient, search direction.

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Authors: Richard Lewis

Abstract:

The following assumptions of the Big Bang theory are challenged and found to be false: the cosmological principle, the assumption that all matter formed at the same time and the assumption regarding the cause of the cosmic microwave background radiation. The evolution of the universe is described based on the conclusion that the universe is finite with a space boundary. This conclusion is reached by ruling out the possibility of an infinite universe or a universe which is finite with no boundary. In a finite universe, the centre of the universe can be located with reference to our home galaxy (The Milky Way) using the speed relative to the Cosmic Microwave Background (CMB) rest frame and Hubble's law. This places our home galaxy at a distance of approximately 26 million light years from the centre of the universe. Because we are making observations from a point relatively close to the centre of the universe, the universe appears to be isotropic and homogeneous but this is not the case. The CMB is coming from a source located within the event horizon of the universe. There is sufficient mass in the universe to create an event horizon at the Schwarzschild radius. Galaxies form over time due to the energy released by the expansion of space. Conservation of energy must consider total energy which is mass (+ve) plus energy (+ve) plus spacetime curvature (-ve) so that the total energy of the universe is always zero. The predominant position of galaxy formation moves over time from the centre of the universe towards the boundary so that today the majority of new galaxy formation is taking place beyond our horizon of observation at 14 billion light years.

Keywords: Cosmic microwave background, dark energy, dark matter, evolution of the universe.

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Authors: A. Ghodbane, M. Saad, J.-F. Boland, C. Thibeault

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Historically, actuators’ redundancy was used to deal with faults occurring suddenly in flight systems. This technique was generally expensive, time consuming and involves increased weight and space in the system. Therefore, nowadays, the on-line fault diagnosis of actuators and accommodation plays a major role in the design of avionic systems. These approaches, known as Fault Tolerant Flight Control systems (FTFCs) are able to adapt to such sudden faults while keeping avionics systems lighter and less expensive. In this paper, a (FTFC) system based on the Geometric Approach and a Reconfigurable Flight Control (RFC) are presented. The Geometric approach is used for cosmic ray fault reconstruction, while Sliding Mode Control (SMC) based on Lyapunov stability theory is designed for the reconfiguration of the controller in order to compensate the fault effect. Matlab®/Simulink® simulations are performed to illustrate the effectiveness and robustness of the proposed flight control system against actuators’ faulty signal caused by cosmic rays. The results demonstrate the successful real-time implementation of the proposed FTFC system on a non-linear 6 DOF aircraft model.

Keywords: Actuators’ faults, Fault detection and diagnosis, Fault tolerant flight control, Sliding mode control, Geometric approach for fault reconstruction, Lyapunov stability.

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Authors: Ora Geiger

Abstract:

This paper discusses the question whether a person diagnosed with dyslexia will necessarily have difficulty in reading musical notes. The author specifies the characteristics of alphabet reading in comparison to musical notation reading, and concludes that there should be no contra-indication for teaching standard music reading to children with dyslexia if an appropriate process is offered. This conclusion is based on a long term case study and relies on two main characteristics of music reading: (1) musical notation system is a systematic, logical, relative set of symbols written on a staff; and (2) music reading learning connected with playing a musical instrument is a multi-sensory activity that combines sight, hearing, touch, and movement. The paper describes music reading teaching procedures, using soprano recorders, and provides unique teaching methods that have been found to be effective for students who were diagnosed with dyslexia. It provides theoretical explanations in addition to guidelines for music education practices.

Keywords: Alphabet reading, music reading, multisensory teaching method, dyslexia, recorder playing.

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Authors: Teerawach Khamkorn, Laongtip Mathurasa, Savittree Rochanasmita Arnold, Witthaya Mekhum

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This research is aimed at studying the nature of problems and demands of the training for community leaders in the upper northeastern region of Thailand. Population and group samplings are based on 360 community leaders in the region who have experienced prior training from the Udonthani Rajabhat University. Stratified random samplings have been drawn upon 186 participants. The research tools is questionnaires. The frequency, percentage and standard deviation are employed in data analysis. The findings indicate that most of community leaders are males and senior adults. The problems in training are associated with the inconveniences of long-distance travelling to training locations, inadequacy of learning centers and training sites and high training costs. The demand of training is basically motivated by a desire for self-development in modern knowledge in keeping up-to-date with the changing world and the need for technological application and facilitation in shortening the distance to training locations and in limiting expensive training costs.

Keywords: Community leaders, Distance Training, Management, Technology.

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Authors: Mohammad M. Toufigh, Ahad Ouria

Abstract:

This paper presents an analytical method to solve governing consolidation parabolic partial differential equation (PDE) for inelastic porous Medium (soil) with consideration of variation of equation coefficient under cyclic loading. Since under cyclic loads, soil skeleton parameters change, this would introduce variable coefficient of parabolic PDE. Classical theory would not rationalize consolidation phenomenon in such condition. In this research, a method based on time space mapping to a virtual time space along with superimposing rule is employed to solve consolidation of inelastic soils in cyclic condition. Changes of consolidation coefficient applied in solution by modification of loading and unloading duration by introducing virtual time. Mapping function is calculated based on consolidation partial differential equation results. Based on superimposing rule a set of continuous static loads in specified times used instead of cyclic load. A set of laboratory consolidation tests under cyclic load along with numerical calculations were performed in order to verify the presented method. Numerical solution and laboratory tests results showed accuracy of presented method.

Keywords: Mapping, Consolidation, Inelastic porous medium, Cyclic loading, Superimposing rule.

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Authors: Frank Emmert-Streib, Matthias Dehmer

Abstract:

Inferring the network structure from time series data is a hard problem, especially if the time series is short and noisy. DNA microarray is a technology allowing to monitor the mRNA concentration of thousands of genes simultaneously that produces data of these characteristics. In this study we try to investigate the influence of the experimental design on the quality of the result. More precisely, we investigate the influence of two different types of random single gene perturbations on the inference of genetic networks from time series data. To obtain an objective quality measure for this influence we simulate gene expression values with a biologically plausible model of a known network structure. Within this framework we study the influence of single gene knock-outs in opposite to linearly controlled expression for single genes on the quality of the infered network structure.

Keywords: Dynamic Bayesian networks, microarray data, structure learning, Markov chain Monte Carlo.

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Authors: M. Anidha, K. Premalatha

Abstract:

Feature Selection is significant in order to perform constructive classification in the area of cancer diagnosis. However, a large number of features compared to the number of samples makes the task of classification computationally very hard and prone to errors in microarray gene expression datasets. In this paper, we present an innovative method for selecting highly informative gene subsets of gene expression data that effectively classifies the cancer data into tumorous and non-tumorous. The hybrid gene selection technique comprises of combined Mutual Information and Fisher score to select informative genes. The gene selection is validated by classification using Support Vector Machine (SVM) which is a supervised learning algorithm capable of solving complex classification problems. The results obtained from improved Mutual Information and F-Score with SVM as a classifier has produced efficient results.

Keywords: Gene selection, mutual information, Fisher score, classification, SVM.

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Authors: G. Lingam, N. Lingam, K. Raghuwaiya

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The reported study focuses on pre-service teachers’ professional development during the teaching practice. The cohort studied comprised participants in their final year in the Bachelor of Arts and Bachelor of Science with Graduate Certificate in Education programmes of a university in Fiji. Analysis of the data obtained using a survey questionnaire indicates that overall, the pre-service teachers were satisfied with the practicum experience. This is assumed to demonstrate that the practicum experience contributed well towards their professional preparation for work expected of them in Fiji secondary schools. Participants also identified some concerns as needing attention. To conclude, the paper provides suggestions for improving the preparation of teachers by strengthening the identified areas of the practicum offered by the university. The study has implications for other teacher education providers in small developing island states and even beyond for the purpose of enhancing learning in student teachers’ for future work.

Keywords: Pre-service, teacher education, practicum, teachers’ world of work, student teachers.

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Authors: Choon Ling Sia, Yani Shi, Jiaqi Yan, Huaping Chen

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With the development of the Internet, E-commerce is growing at an exponential rate, and lots of online stores are built up to sell their goods online. A major factor influencing the successful adoption of E-commerce is consumer-s trust. For new or unknown Internet business, consumers- lack of trust has been cited as a major barrier to its proliferation. As web sites provide key interface for consumer use of E-Commerce, we investigate the design of web site to build trust in E-Commerce from a design science approach. A conceptual model is proposed in this paper to describe the ontology of online transaction and human-computer interaction. Based on this conceptual model, we provide a personalized webpage design approach using Bayesian networks learning method. Experimental evaluation are designed to show the effectiveness of web personalization in improving consumer-s trust in new or unknown online store.

Keywords: Trust, Web site design, Human-ComputerInteraction, E-Commerce, Design science, Bayesian network.

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Authors: P. Acharjee, S. K. Goswami

Abstract:

Particle Swarm Optimization (PSO) with elite PSO parameters has been developed for power flow analysis under practical constrained situations. Multiple solutions of the power flow problem are useful in voltage stability assessment of power system. A method of determination of multiple power flow solutions is presented using a hybrid of Particle Swarm Optimization (PSO) and local search technique. The unique and innovative learning factors of the PSO algorithm are formulated depending upon the node power mismatch values to be highly adaptive with the power flow problems. The local search is applied on the pbest solution obtained by the PSO algorithm in each iteration. The proposed algorithm performs reliably and provides multiple solutions when applied on standard and illconditioned systems. The test results show that the performances of the proposed algorithm under critical conditions are better than the conventional methods.

Keywords: critical conditions, ill-conditioned systems, localsearch technique, multiple power flow solutions, particle swarmoptimization.

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Authors: Li Kewen, Su Zhaoxin, Wang Xingmou, Zhu Jian Bing

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Conventional reservoir prediction methods ar not sufficient to explore the implicit relation between seismic attributes, and thus data utilization is low. In order to improve the predictive classification accuracy of reservoir lithology, this paper proposes a deep learning lithology prediction method based on ResNet (Residual Neural Network) and SENet (Squeeze-and-Excitation Neural Network). The neural network model is built and trained by using seismic attribute data and lithology data of Shengli oilfield, and the nonlinear mapping relationship between seismic attribute and lithology marker is established. The experimental results show that this method can significantly improve the classification effect of reservoir lithology, and the classification accuracy is close to 70%. This study can effectively predict the lithology of undrilled area and provide support for exploration and development.

Keywords: Convolutional neural network, lithology, prediction of reservoir lithology, seismic attributes.

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Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

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Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: Artificial Neural Network, Data Mining, Electroencephalogram, Epilepsy, Feature Extraction, Seizure Detection, Signal Processing.

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Authors: R. Sinthavalai, N. Memongkol, N. Patthanaprechawong, J. Viriyanantavong, C. Choosuk

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In Thailand, the practice of pre-hospital Emergency Medical Service (EMS) in each area reveals the different growth rates and effectiveness of the practices. Those can be found as the diverse quality and quantity. To shorten the learning curve prior to speed-up the practices in other areas, story telling and lessons learnt from the effective practices are valued as meaningful knowledge. To this paper, it was to ascertain the factors, lessons learnt and best practices that have impact as contributing to the success of prehospital EMS system. Those were formulized as model prior to speedup the practice in other areas. To develop the model, Malcolm Baldrige National Quality Award (MBNQA), which is widely recognized as a framework for organizational quality assessment and improvement, was chosen as the discussion framework. Remarkably, this study was based on the consideration of knowledge capture; however it was not to complete the loop of knowledge activities. Nevertheless, it was to highlight the recognition of knowledge capture, which is the initiation of knowledge management.

Keywords: Emergency Medical Service, Modeling, MBNQA, Thailand.

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Authors: Yang Zhang, Jian He

Abstract:

Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper presents sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for CHD prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, coronary heart disease, ECG, electrocardiogram, ResNet, sliding window.

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