Search results for: Social Support

Authors: Alyaa M. Younes, Nermine Harraz, Mohammad H. Elwany

Abstract:

Lithium ion batteries are currently used for many applications including satellites, electric vehicles and mobile electronics. Their ability to store relatively large amount of energy in a limited space make them most appropriate for critical applications. Evaluation of the life of these batteries and their reliability becomes crucial to the systems they support. Reliability of Li-Ion batteries has been mainly considered based on its lifetime. However, another important factor that can be considered critical in many applications such as in electric vehicles is the cycle duration. The present work presents the results of an experimental investigation on the degradation behavior of a Laptop Li-ion battery (type TKV2V) and the effect of applied load on the battery cycle time. The reliability was evaluated using an accelerated life test. Least squares linear regression with median rank estimation was used to estimate the Weibull distribution parameters needed for the reliability functions estimation. The probability density function, failure rate and reliability function under each of the applied loads were evaluated and compared. An inverse power model is introduced that can predict cycle time at any stress level given.

Keywords: Accelerated life test, inverse power law, lithium ion battery, reliability evaluation, Weibull distribution.

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Authors: H. Iranmanesh, M. R. Skandari, M. Allahverdiloo

Abstract:

Project managers are the ultimate responsible for the overall characteristics of a project, i.e. they should deliver the project on time with minimum cost and with maximum quality. It is vital for any manager to decide a trade-off between these conflicting objectives and they will be benefited of any scientific decision support tool. Our work will try to determine optimal solutions (rather than a single optimal solution) from which the project manager will select his desirable choice to run the project. In this paper, the problem in project scheduling notated as (1,T|cpm,disc,mu|curve:quality,time,cost) will be studied. The problem is multi-objective and the purpose is finding the Pareto optimal front of time, cost and quality of a project (curve:quality,time,cost), whose activities belong to a start to finish activity relationship network (cpm) and they can be done in different possible modes (mu) which are non-continuous or discrete (disc), and each mode has a different cost, time and quality . The project is constrained to a non-renewable resource i.e. money (1,T). Because the problem is NP-Hard, to solve the problem, a meta-heuristic is developed based on a version of genetic algorithm specially adapted to solve multi-objective problems namely FastPGA. A sample project with 30 activities is generated and then solved by the proposed method.

Keywords: FastPGA, Multi-Execution Activity Mode, ParetoOptimality, Project Scheduling, Time-Cost-Quality Trade-Off.

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Authors: Andrés C. Cuervo Pinilla, Christian G. Quintero M., Chinthaka Premachandra

Abstract:

This paper considers people’s driving skills diagnosis under real driving conditions. In that sense, this research presents an approach that uses GPS signals which have a direct correlation with driving maneuvers. Besides, it is presented a novel expert-driving-criteria approximation using fuzzy logic which seeks to analyze GPS signals in order to issue an intelligent driving diagnosis. Based on above, this works presents in the first section the intelligent driving diagnosis system approach in terms of its own characteristics properties, explaining in detail significant considerations about how an expert-driving-criteria approximation must be developed. In the next section, the implementation of our developed system based on the proposed fuzzy logic approach is explained. Here, a proposed set of rules which corresponds to a quantitative abstraction of some traffics laws and driving secure techniques seeking to approach an expert-driving- criteria approximation is presented. Experimental testing has been performed in real driving conditions. The testing results show that the intelligent driving diagnosis system qualifies driver’s performance quantitatively with a high degree of reliability.

Keywords: Driver support systems, intelligent transportation systems, fuzzy logic, real time data processing.

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Authors: Luís Antonio de Almeida Rodriguez, José Maria Parente de Oliveira, Ednelson Oliveira

Abstract:

In the last two decades, the world’s aviation authorities have made several attempts to create consensus about a global and accepted approach for applying semantics to web services registry descriptions. This problem has led communities to face a fat and disorganized infrastructure to describe aeronautical web services. It is usual for developers to implement ad-hoc connections among consumers and providers and manually create non-standardized service compositions, which need some particular approach to compose and semantically discover a desired web service. Current practices are not precise and tend to focus on lightweight specifications of some parts of the OWL-S and embed them into syntactic descriptions (SOAP artifacts and OWL language). It is necessary to have the ability to manage the use of both technologies. This paper presents an implementation of the ontology OWL-S that describes a Brazilian Aeronautical Web Service Registry, which makes it able to publish, advertise, make multi-criteria semantic discovery aligned with the ideas of the System Wide Information Management (SWIM) Program, and invoke web services within the Air Traffic Management context. The proposal’s best finding is a generic approach to describe semantic web services. The paper also presents a set of functional requirements to guide the ontology development and to compare them to the results to validate the implementation of the OWL-S Ontology.

Keywords: Aeronautical Web Services, OWL-S, Semantic Web Services Discovery, Ontologies.

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Authors: José Neves, M. Rosário Martins, Fátima Candeias, Diana Ferreira, Sílvia Arantes, Júlio Cruz-Morais, Guida Gomes, Joaquim Macedo, António Abelha, Henrique Vicente

Abstract:

Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

Keywords: Artificial neuronal networks, essential oils, knowledge representation and reasoning, logic programming, Schinus molle L, Schinus terebinthifolius raddi.

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Authors: Methawee Yuttapongtada

Abstract:

Intensifier is the linguistic term and device that is generally found in different languages in order to enhance and give additional quantity, quality or emotion to the words of each language. In fact, each language in the world has both of the similar and dissimilar intensifying device. More specially, the wide variety of intensifying device is used for Thai language and one of those is usage of the impolite word or the word that used to mean something negative as intensifier. The data collection in this study was done throughout the spoken language style by collecting from intensifiers regarded as impolite words because these words as employed in the other contexts will be held as the rude, swear words or the words with negative meaning. Then, backward study to the past was done in order to consider the historical change. Explanation of the original meaning and the contexts of words use from the past till the present time were done by use of both textual documents and dictionaries available in different periods. It was found that regarding the semantics and pragmatic aspects, subjectification also is the significant motivation that changed the impolite words to intensifiers. At last, it can explain pathway of the semantic change of these very words undoubtedly. Moreover, it is found that use tendency in the impolite word or the word that used to mean something negative will more be increased and this phenomenon is commonly found in many languages in the world and results of this research may support to the belief that human language in the world is universal and the same still reflected that human has the fundamental thought as the same to each other basically.

Keywords: Impolite word, intensifier, Thai, semantic change.

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Authors: Carolijn Van Noort

Abstract:

The aim of this research is to understand how the emerging power bloc BRICS employs infrastructure development narratives to construct a new world order. BRICS is an international body consisting of five emerging countries that collaborate on economic and political issues: Brazil, Russia, India, China, and South Africa. This study explores the projection of infrastructure development narratives through an analysis of BRICS’ attention to infrastructure investment and financing, its support of the New Partnership on African Development and the establishment of the New Development Bank in Shanghai. The theory of Strategic Narratives is used to explore BRICS’ commitment to infrastructure development and to distinguish three layers: system narratives (BRICS as a global actor to propose development reform), identity narratives (BRICS as a collective identity joining efforts to act upon development aspirations) and issue narratives (BRICS committed to a range of issues of which infrastructure development is prominent). The methodology that is employed is a narrative analysis of BRICS’ official documents, media statements, and website imagery. A comparison of these narratives illuminates tensions at the three layers and among the five member states. Identifying tensions among development infrastructure narratives provides an indication of how policymaking for infrastructure development could be improved. Subsequently, it advances BRICS’ ability to act as a global actor to construct a new world order.

Keywords: BRICS, emerging powers, infrastructural development, strategic narratives.

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Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

Abstract:

Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine (SVM), Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis (LDA), and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: Student performance, supervised machine learning, prediction, classification, cross-validation.

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Authors: Nuraddin Sadykov, Altynai Zhussipova, Omirkhan Abdimanuly

Abstract:

Major social changes in the last century had significant impact on the Kazakh literature. Participants of the World War II, writers and poets imprisoned during the war, formed the Kazakh literature in emigration within the framework of 'Turkistan Legion'. This was a topic which remained closed until Kazakhstan gained its independence, though even after the independence, there were few research works done about the literature in emigration. The article studies the formation of the Kazakh literature in emigration, its prominent figures, its artistic heritage, and notes of emigration in works of poets and writers.

Keywords: Literature in emigration, 'Turkistan legion', pseudonym, periodicals.

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Authors: Amir Farkhonde

Abstract:

The major objective of this study was to devise a method for solving mathematical problems. Three concepts including faculty of understanding, faculty of guess, and free mind or beginner's mind provided the foundation for this method. An explanatory approach along with a hermeneutic process was taken in this study to support the assumption that mathematical knowledge is constantly developing and it seems essential for students to solve math problems on their own using their faculty of understanding (interpretive dialogue) and faculty of guess. For doing so, a kind of movement from the mathematical problem to mathematical knowledge should be adopted for teaching students a new math topic. The research method of this paper is review, descriptive and conception development. This paper first reviews the research findings on the NRICH’S project (NRICH is part of the family of activities in the Millennium Mathematics Project) with the aim that these findings form the theoretical basis of the problem-solving method. Then, the curriculum, the conceptual structure of the new method, how to design the problem and an example of it are discussed. In this way, students are immersed in the story of discovering and understanding the problem formula, and interpretive dialogue with the text continues by following the questions posed by the problem and constantly reconstructing the answer to find a formula or solution to solve the problem.

Keywords: Interpretive dialogue, NRICH, inventing, a method of problem solving.

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Authors: H. Iranmanesh, M. R. Skandari, M. Allahverdiloo

Abstract:

Project managers are the ultimate responsible for the overall characteristics of a project, i.e. they should deliver the project on time with minimum cost and with maximum quality. It is vital for any manager to decide a trade-off between these conflicting objectives and they will be benefited of any scientific decision support tool. Our work will try to determine optimal solutions (rather than a single optimal solution) from which the project manager will select his desirable choice to run the project. In this paper, the problem in project scheduling notated as (1,T|cpm,disc,mu|curve:quality,time,cost) will be studied. The problem is multi-objective and the purpose is finding the Pareto optimal front of time, cost and quality of a project (curve:quality,time,cost), whose activities belong to a start to finish activity relationship network (cpm) and they can be done in different possible modes (mu) which are non-continuous or discrete (disc), and each mode has a different cost, time and quality . The project is constrained to a non-renewable resource i.e. money (1,T). Because the problem is NP-Hard, to solve the problem, a meta-heuristic is developed based on a version of genetic algorithm specially adapted to solve multi-objective problems namely FastPGA. A sample project with 30 activities is generated and then solved by the proposed method.

Keywords: FastPGA, Multi-Execution Activity Mode, Pareto Optimality, Project Scheduling, Time-Cost-Quality Trade-Off.

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Authors: Mingwei Yi, Liujie Guo, Zongjun Pan, Xiang Lin, Xiaoming Yi

Abstract:

With the rapid expansion of road construction mileage in China, the scale of road maintenance needs has concurrently escalated. As the service life of roads extends, the design of pavement repair and maintenance emerges as a crucial component in preserving the excellent performance of the pavement. The remaining service life of asphalt pavement structure is a vital parameter in the lifecycle maintenance design of asphalt pavements. Based on an analysis of pavement structural integrity, this study presents a characterization and assessment of the remaining life of existing asphalt pavement structures. It proposes indicators such as the transverse crack spacing and the length of longitudinal cracks. The transverse crack spacing decreases with an increase in maintenance intervals and with the extended use of semi-rigid base layer structures, although this trend becomes less pronounced after maintenance intervals exceed 4 years. The length of longitudinal cracks increases with longer maintenance intervals, but this trend weakens after five years. This system can support the enhancement of standardization and scientific design in highway maintenance decision-making processes.

Keywords: Structural integrity, highways, pavement evaluation, asphalt concrete pavement.

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Authors: Beata Hornickova, Sona Lorencova

Abstract:

The study deals with the presentation of the results of qualitatively oriented research, which was carried out in the scope of determining the attitudes of parents to preschool education in the Czech Republic. The research is conceived as an entry into the field of the researched issue and aimed to support the effectiveness of the items of the questionnaire, which was subsequently created based on the parents’ statements from interviews. The research method was interview with 15 parents of preschool children. The main aim of the interviews was to find out their views on the compulsory attendance of their children in kindergarten. Compulsory pre-school attendance has been introduced in the Czech Republic since 2017/18 with the aim of reducing delays in the entry of children into primary school and eliminating subsequent school failures. The findings offered a look at the differing views on compulsory kindergarten school influenced by the different socio-economic status of parents. Parents with a higher socio-economic status attached greater importance to the educational component of compulsory preschool attendance as a preparation for primary school, while parents with a lower socio-economic status emphasized the educational component. An interesting finding is also a statement from interviews of a parent who does not find benefits in compulsory preschool attendance.

Keywords: Compulsory pre-school education, education of preschool children, kindergarten, parents’ opinions on pre-school education.

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Authors: Fernando Alonso, Rafael Fernandez, Sonia Frutos, Javier Soriano

Abstract:

CIM is the standard formalism for modeling management information developed by the Distributed Management Task Force (DMTF) in the context of its WBEM proposal, designed to provide a conceptual view of the managed environment. In this paper, we propose the inclusion of formal knowledge representation techniques, based on Description Logics (DLs) and the Web Ontology Language (OWL), in CIM-based conceptual modeling, and then we examine the benefits of such a decision. The proposal is specified as a CIM metamodel level mapping to a highly expressive subset of DLs capable of capturing all the semantics of the models. The paper shows how the proposed mapping can be used for automatic reasoning about the management information models, as a design aid, by means of new-generation CASE tools, thanks to the use of state-of-the-art automatic reasoning systems that support the proposed logic and use algorithms that are sound and complete with respect to the semantics. Such a CASE tool framework has been developed by the authors and its architecture is also introduced. The proposed formalization is not only useful at design time, but also at run time through the use of rational autonomous agents, in response to a need recently recognized by the DMTF.

Keywords: CIM, Knowledge-based Information Models, Ontology Languages, OWL, Description Logics, Integrated Network Management, Intelligent Agents, Automatic Reasoning Techniques.

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Authors: Gheida J. Shahrour, Martin J. Russell

Abstract:

The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to their culture. We arranged each group into pairs and each pair communicated with each other about different topics. A state-of-art recognition system is applied to the problems of person, culture, and topic recognition. We borrowed modeling, classification, and normalization techniques from speech recognition. We used Gaussian Mixture Modeling (GMM) as the main technique for building our three systems, obtaining 77.78%, 55.47%, and 39.06% from the person, culture, and topic recognition systems respectively. In addition, we combined the above GMM systems with Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and 40.63% accuracy for person, culture, and topic recognition respectively. Although direct comparison among these three recognition systems is difficult, it seems that our person recognition system performs best for both GMM and GMM-SVM, suggesting that intersubject differences (i.e. subject’s personality traits) are a major source of variation. When removing these traits from culture and topic recognition systems using the Nuisance Attribute Projection (NAP) and the Intersession Variability Compensation (ISVC) techniques, we obtained 73.44% and 46.09% accuracy from culture and topic recognition systems respectively.

Keywords: Person Recognition, Topic Recognition, Culture Recognition, 3D Body Movement Signals, Variability Compensation.

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Authors: E. Bruno, F. Lacarbonara, M. C. Placentino, D. Gramegna

Abstract:

Environmental decision making, particularly about hazardous waste management, is inherently exposed to a high potential conflict, principally because of the trade-off between sociopolitical, environmental, health and economic factors. The need to plan complex contexts has led to an increasing request for decision analytic techniques as support for the decision process. In this work, alternative systems of asbestos-containing waste management (ACW) in Puglia (Southern Italy) were explored by a multi-criteria decision analysis. In particular, through Analytic Hierarchy Process five alternatives management have been compared and ranked according to their performance and efficiency, taking into account environmental, health and socio-economic aspects. A separated valuation has been performed for different temporal scale. For short period results showed a narrow deviation between the disposal alternatives “mono-material landfill in public quarry" and “dedicate cells in existing landfill", with the best performance of the first one. While for long period “treatment plant to eliminate hazard from asbestos-containing waste" was prevalent, although high energy demand required to achieve the change of crystalline structure. A comparison with results from a participative approach in valuation process might be considered as future development of method application to ACW management.

Keywords: Multi-criteria decision analysis, Hazardous wastemanagement, Asbestos.

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Authors: I. Benning

Abstract:

Using technology to expand the learning space is critical for a productive mathematical discourse. This is a case study of two teachers who developed and enacted GeoGebra-based mathematics lessons following their engagement in a two-year professional development. The didactical and semiotic affordance of GeoGebra in widening the learning space for a productive mathematical discourse was explored. The approach of thematic analysis was used for lesson artefact, lesson observation, and interview data. The results indicated that constructing tools in GeoGebra provided a didactical milieu where students used them to explore mathematical concepts with little or no support from their teacher. The prompt feedback from the GeoGebra motivated students to practice mathematical concepts repeatedly in which they privately rethink their solutions before comparing their answers with that of their colleagues. The constructing tools enhanced self-discovery, team spirit, and dialogue among students. With regards to the semiotic construct, the tools widened the physical and psychological atmosphere of the classroom by providing animations that served as virtual concrete to enhance the recording, manipulation, testing of a mathematical idea, construction, and interpretation of geometric objects. These findings advance the discussion of widening the classroom for a productive mathematical discourse within the context of the mathematics curriculum of Ghana and similar sub-Saharan African countries.

Keywords: GeoGebra, theory of didactical situation, semiotic mediation, mathematics laboratory, mathematical discussion.

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Authors: Samira Vafaye Eslahi

Abstract:

BCI (Brain Computer Interface) is a communication machine that translates brain massages to computer commands. These machines with the help of computer programs can recognize the tasks that are imagined. Feature extraction is an important stage of the process in EEG classification that can effect in accuracy and the computation time of processing the signals. In this study we process the signal in three steps of active segment selection, fractal feature extraction, and classification. One of the great challenges in BCI applications is to improve classification accuracy and computation time together. In this paper, we have used student’s 2D sample t-statistics on continuous wavelet transforms for active segment selection to reduce the computation time. In the next level, the features are extracted from some famous fractal dimension estimation of the signal. These fractal features are Katz and Higuchi. In the classification stage we used ANFIS (Adaptive Neuro-Fuzzy Inference System) classifier, FKNN (Fuzzy K-Nearest Neighbors), LDA (Linear Discriminate Analysis), and SVM (Support Vector Machines). We resulted that active segment selection method would reduce the computation time and Fractal dimension features with ANFIS analysis on selected active segments is the best among investigated methods in EEG classification.

Keywords: EEG, Student’s t- statistics, BCI, Fractal Features, ANFIS, FKNN.

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Authors: Mauricio Terceros, Jann-Eike Saathoff, Martin Achmus

Abstract:

In non-cohesive soil, onshore wind turbines are often found on shallow foundations with a circular or octagonal shape. For the current generation of wind turbines, shallow foundations with very large breadths are required. The foundation support costs thus represent a considerable portion of the total construction costs. Therefore, an economic optimization of the type of foundation is highly desirable. A conceivable alternative foundation type would be a pier foundation, which combines the load transfer over the foundation area at the pier base with the transfer of horizontal loads over the shaft surface of the pier. The present study aims to evaluate the load-bearing behavior of a pier foundation based on comprehensive parametric studies. Thereby, three-dimensional numerical simulations of both pier and shallow foundations are developed. The evaluation of the results focuses on the rotational stiffnesses of the proposed soil-foundation systems. In the design, the initial rotational stiffness is decisive for consideration of natural frequencies, whereas the rotational secant stiffness for a maximum load is decisive for serviceability considerations. A systematic analysis of the results at different load levels shows that the application of the typical pier foundation is presumably limited to relatively small onshore wind turbines.

Keywords: Onshore wind foundation, pier foundation, rotational stiffness of soil-foundation system, shallow foundation.

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Authors: Enrique Barra, Aldo Gordillo, Juan Quemada

Abstract:

This paper presents the Virtual Science Hub platform. It is an open source platform that combines a social network, an e-learning authoring tool, a videoconference service and a learning object repository for science teaching enrichment. These four main functionalities fit very well together. The platform was released in April 2012 and since then it has not stopped growing. Finally we present the results of the surveys conducted and the statistics gathered to validate this approach.

Keywords: E-learning, platform, authoring tool, science teaching.

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Authors: Christiono Utomo, Arazi Idrus, Madzlan Napiah, Mohd. Faris Khamidi

Abstract:

This paper presents a conceptual model of agreement options for negotiation support in multi-person decision on optimizing high-rise building columns. The decision is complicated since many parties involved in choosing a single alternative from a set of solutions. There are different concern caused by differing preferences, experiences, and background. Such building columns as alternatives are referred to as agreement options which are determined by identifying the possible decision maker group, followed by determining the optimal solution for each group. The group in this paper is based on three-decision makers preferences that are designer, programmer, and construction manager. Decision techniques applied to determine the relative value of the alternative solutions for performing the function. Analytical Hierarchy Process (AHP) was applied for decision process and game theory based agent system for coalition formation. An n-person cooperative game is represented by the set of all players. The proposed coalition formation model enables each agent to select individually its allies or coalition. It further emphasizes the importance of performance evaluation in the design process and value-based decision.

Keywords: Agreement options, coalition, group choice, game theory, building columns selection.

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Authors: Hussin K. Ragb, Vijayan K. Asari

Abstract:

In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: Pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor.

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

Abstract:

With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: Activities of daily living, classification, internet of things, machine learning, smart home.

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Authors: Ntokozo Mthembu

Abstract:

Access to relevant health indicates people’s likelihood of survival, including craft of indigenous healing and its related practitioners- izinyanga. However, the emergence of a dreaded novel corona virus - COVID-19 that has engulfed almost the whole world has necessitated the need to revisit the state of traditional healers in South Africa. This circumstance tended to expose the reality of social settings in various social structures and related policies including the manner coloniality reveal its ugly head when it comes treatment between western and African based therapeutic practices in this country. In attempting to gain a better understanding of such experiences, primary and secondary sources were consulted when collecting data that perusal of various literature in this instance including face-to-face interviews with traditional healers working on the street of Tshwane Municipality in South Africa. Preliminary findings revealed that the emergence of this deadly virus coincided with the moment when the government agenda was focussed on fulfilment of its promise of addressing the past inequity practices, including the transformation of medical sector. This scenario can be witnessed by the manner in which government and related agencies such as health department keeps on undermining indigenous healing practice irrespective of its historical record in terms of healing profession and fighting various diseases before times of father of medicine, Imhotep. Based on these preliminary findings, it is recommended that the government should hasten the incorporation of African knowledge systems especially medicine to offer alternatives and diverse to assess the underutilised indigenous African therapeutic approach and relevant skills that could be useful in combating ailments such as COVID 19. Perhaps, the plural medical systems should be recognized and related policies are formulated to guarantee mutual respect among citizens and the incorporation of healing practices in South African health sector, Africa and in the broader global community.

Keywords: Indigenous healing practice, inyanga, COVID-19, therapeutic, urban, experience.

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Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

Abstract:

This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: River stage-discharge process, LSSVM, discrete wavelet transform (DWT), ensemble empirical decomposition mode (EEMD), multi-station modeling.

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Authors: Suby Khanam, Jamshed Siddiqui, Faisal Talib

Abstract:

Total Quality Management (TQM) is a managerial approach that improves the competitiveness of the industry, meanwhile Information technology (IT) was introduced with TQM for handling the technical issues which is supported by quality experts for fulfilling the customers’ requirement. Present paper aims to utilise AHP (Analytic Hierarchy Process) methodology to priorities and rank the hierarchy levels of TQM enablers and IT resource together for its successful implementation in the Information and Communication Technology (ICT) industry. A total of 17 TQM enablers (nine) and IT resources (eight) were identified and partitioned into 3 categories and were prioritised by AHP approach. The finding indicates that the 17 sub-criteria can be grouped into three main categories namely organizing, tools and techniques, and culture and people. Further, out of 17 sub-criteria, three sub-criteria: top management commitment and support, total employee involvement, and continuous improvement got highest priority whereas three sub-criteria such as structural equation modelling, culture change, and customer satisfaction got lowest priority. The result suggests a hierarchy model for ICT industry to prioritise the enablers and resources as well as to improve the TQM and IT performance in the ICT industry. This paper has some managerial implication which suggests the managers of ICT industry to implement TQM and IT together in their organizations to get maximum benefits and how to utilize available resources. At the end, conclusions, limitation, future scope of the study are presented.

Keywords: Analytic Hierarchy Process, Information Technology, Information and Communication Technology, Prioritization, Total Quality Management.

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Authors: Napisporn Memongkol, Runchana Sinthavalai, Nattapong Seneeratanaprayune Weerawat Ounsaneha, Chanisada Choosuk

Abstract:

The objective of this research is to develop the performance indicators (PIs) in operational level for the Pre-hospital Emergency Medical Service (EMS) system employing in Thailand. This research started with ascertaining the current pre-hospital care system. The team analyzed the strategies of Narerthorn, a government unit under the ministry of public health, and the existing PIs of the pre-hospital care. Afterwards, the current National Strategic Plan of EMS development (2008-2012) of the Emergency Medical Institute of Thailand (EMIT) was considered using strategic analysis to developed Strategy Map (SM) and identified the Success Factors (SFs). The analysis results from strategy map and SFs were used to develop the Performance Indicators (PIs). To verify the set of PIs, the team has interviewed with the relevant practitioners for the possibilities to implement the PIs. To this paper, it was to ascertain that all the developed PIs support the objectives of the strategic plan. Nevertheless, the results showed that the operational level PIs suited only with the first dimension of National Strategic Plan (infrastructure and information technology development). Besides, the SF was the infrastructure development (to contribute the EMS system to people throughout with standard and efficiency both in normally and disaster conditions). Finally, twenty-nine indicators were developed from the analysis results of SM and SFs.

Keywords: Emergency Medical Service, Performance Indicator, Success Factor, Thailand

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Authors: B. T. Sayed, Nafaâ Jabeur, M. Aref

Abstract:

Creation and maintenance of knowledge management systems has been recognized as an important research area. Consecutively lack of accurate results from knowledge management systems limits the organization to apply their knowledge management processes. This leads to a failure in getting the right information to the right people at the right time thus followed by a deficiency in decision making processes. An Intranet offers a powerful tool for communication and collaboration, presenting data and information, and the means that creates and shares knowledge, all in one easily accessible place. This paper proposes an archetype describing how a knowledge management system, with the support of intranet capabilities, could very much increase the accuracy of capturing, storing and retrieving knowledge based processes thereby increasing the efficiency of the system. This system will expect a critical mass of usage, by the users, for intranet to function as knowledge management systems. This prototype would lead to a design of an application that would impose creation and maintenance of an effective knowledge management system through intranet. The aim of this paper is to introduce an effective system to handle capture, store and distribute knowledge management in a form that may not lead to any failure which exists in most of the systems. The methodology used in the system would require all the employees, in the organization, to contribute the maximum to deliver the system to a successful arena. The system is still in its initial mode and thereby the authors are under the process to practically implement the ideas, as mentioned in the system, to produce satisfactory results.

Keywords: Knowledge Management Systems, Intranet, Methodology.

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Authors: Vasiliki Vlachou, Christos Kontzinos, Ourania Markaki, Panagiotis Kokkinakos, Vagelis Karakolis, John Psarras

Abstract:

Higher Education is resisting the pull of technology, especially as this concerns the issuance and verification of degrees and certificates. It is widely known that education certificates are largely produced in paper form making them vulnerable to damage while holders of such certificates are dependent on the universities and other issuing organisations. QualiChain is an EU Horizon 2020 (H2020) research project aiming to transform and revolutionise the domain of public education and its ties with the job market by leveraging blockchain, analytics and decision support to develop a platform for the verification and sharing of education certificates. Blockchain plays an integral part in the QualiChain solution in providing a trustworthy environment to store, share and manage such accreditations. Under the context of this paper, three prominent blockchain platforms (Ethereum, Hyperledger Fabric, Hyperledger Iroha) were considered as a means of experimentation for creating a system with the basic functionalities that will be needed for trustworthy degree verification. The methodology and respective system developed and presented in this paper used Hyperledger Iroha and proved that this specific platform can be used to easily develop decentralize applications. Future papers will attempt to further experiment with other blockchain platforms and assess which has the best potential.

Keywords: Blockchain, degree verification, higher education certificates, Hyperledger Iroha.

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Authors: Dakshina Ranjan Kisku, Hunny Mehrotra, Jamuna Kanta Sing, Phalguni Gupta

Abstract:

Identity verification of authentic persons by their multiview faces is a real valued problem in machine vision. Multiview faces are having difficulties due to non-linear representation in the feature space. This paper illustrates the usability of the generalization of LDA in the form of canonical covariate for face recognition to multiview faces. In the proposed work, the Gabor filter bank is used to extract facial features that characterized by spatial frequency, spatial locality and orientation. Gabor face representation captures substantial amount of variations of the face instances that often occurs due to illumination, pose and facial expression changes. Convolution of Gabor filter bank to face images of rotated profile views produce Gabor faces with high dimensional features vectors. Canonical covariate is then used to Gabor faces to reduce the high dimensional feature spaces into low dimensional subspaces. Finally, support vector machines are trained with canonical sub-spaces that contain reduced set of features and perform recognition task. The proposed system is evaluated with UMIST face database. The experiment results demonstrate the efficiency and robustness of the proposed system with high recognition rates.

Keywords: Biometrics, Multiview face Recognition, Gaborwavelets, LDA, SVM.

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