Search results for: power allocation problem.

Authors: G. S. Ayyappan, Srinivas Kota, Jaffer R. C. Sheriff, C. Prakash Chandra Joshua

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In the present scenario of energy crises, energy conservation in the electrical machines is very important in the industries. In order to conserve energy, one needs to monitor the performance of an induction motor on-site and in-situ. The instruments available for this purpose are very meager and very expensive. This paper deals with the design and development of induction motor performance analyser on-line, on-site, and in-situ. The system measures only few electrical input parameters like input voltage, line current, power factor, frequency, powers, and motor shaft speed. These measured data are coupled to name plate details and compute the operating efficiency of induction motor. This system employs the method of computing motor losses with the help of equivalent circuit parameters. The equivalent circuit parameters of the concerned motor are estimated using the developed algorithm at any load conditions and stored in the system memory. The developed instrument is a reliable, accurate, compact, rugged, and cost-effective one. This portable instrument could be used as a handy tool to study the performance of both slip ring and cage induction motors. During the analysis, the data can be stored in SD Memory card and one can perform various analyses like load vs. efficiency, torque vs. speed characteristics, etc. With the help of the developed instrument, one can operate the motor around its Best Operating Point (BOP). Continuous monitoring of the motor efficiency could lead to Life Cycle Assessment (LCA) of motors. LCA helps in taking decisions on motor replacement or retaining or refurbishment.

Keywords: Energy conservation, equivalent circuit parameters, induction motor efficiency, life cycle assessment, motor performance analysis.

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Authors: Tshimangadzo Oscar Magadze

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For successful re-integration, the individual offender must adapt and transform, which requires that the offender should adopt and internalise socially approved norms, attitudes, values, and beliefs. However, the offender’s labelling and community stigmatisation decide the destination of the offender. Community involvement in ex-offenders’ re-integration is an important issue in efforts to reduce recidivism and to control overcrowding in our correctional facilities. Crime is a social problem that requires society to come together to fight against it. This study was conducted in the Limpopo Province in Vhembe District Municipality within four local municipalities, namely Musina, Makhado, Mutale, and Thulamela. A total number of 30 participants were interviewed, and all were members of the Community Corrections Forums. This was necessitated by the fact that Musina is a very small area, which compelled the Department of Correctional Services to combine the two (Musina and Makhado) into one social re-integration entity. This is a qualitative research study where participants were selected through the use of purposive sampling. Participants were selected based on the value they would add to this study in order to achieve the objectives. The data collection method of this study was the focus group, which comprised of three groups of 10 participants each. Thulamela and Mutale local municipalities formed a group with (10) participants each, whereas Musina (2) and Makhado (8) formed another. Results indicate that the current situation is not conducive for re-integration to be successful. Participants raised many factors that need serious redress, namely offenders’ discrimination, lack of forgiveness by members of the community, which is fuelled by lack of community awareness due to the failure of the Department of Correctional Services in educating communities on ex-offenders’ re-integration.

Keywords: Ex-offender, labelling, re-integration, stigmatisation.

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Authors: Dinabandhu Mahata, Amit Kumar, Ambarish Kumar Rai

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India is known as a country of diversity regarding the social, cultural and wide geographical variations. In the north and north-west part of the country, the strong patriarchal norms and the male dominance based social structure are the important constructs. Patriarchal social setup adversely affects the women’s social and economic wellbeing and hence in that social structure women are considered as second level citizen. Work participation rate of women has directly linked to the development of society or household. Haryana is one of the developed states of India, still being ahead in economic prosperity, much lagged behind in gender-based equality and male dominance in all dimensions of life. The position of women in the Haryana is no better than the other states of India. Haryana state has the great difference among the male-female sex ratio which is a serious concern for social science research as a demographic problem for the state. Now women are requiring for their holistic empowerment and that will take care of them for an enabling process that must lead to their economic as well as social transformation. Hence, the objective of the paper is to address the role of sex ratio, women literacy and her work participation in the process of their empowerment with special attention to the gender perspective. The study used the data from Census of India from 1991 to 2011. This paper will examine the regional disparity of sex ratio, literacy rate and female work participation and the improvement of empowerment of women in the state of Haryana. This paper will suggest the idea for focusing much intensively on the issues of women empowerment through enhancement of her education, workforce participation and social participation with people participation and holistic approach.

Keywords: Sex ratio, literacy rate, workforce participation rate, women empowerment, Haryana.

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Authors: Salah R. Al Zaidee, Ali S. Mahdi

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Except for simple problems of statically determinate structures, optimum design problems in structural engineering have implicit objective functions where structural analysis and design are essential within each searching loop. With these implicit functions, the structural engineer is usually enforced to write his/her own computer code for analysis, design, and searching for optimum design among many feasible candidates and cannot take advantage of available software for structural analysis, design, and searching for the optimum solution. The meta-model is a regression model used to transform an implicit objective function into objective one and leads in turn to decouple the structural analysis and design processes from the optimum searching process. With the meta-model, well-known software for structural analysis and design can be used in sequence with optimum searching software. In this paper, the meta-model has been used to develop an explicit objective function for plane steel frames subjected to dead, live, and seismic forces. Frame topology is assumed as predefined based on architectural and functional requirements. Columns and beams sections and different connections details are the main design variables in this study. Columns and beams are grouped to reduce the number of design variables and to make the problem similar to that adopted in engineering practice. Data for the implicit objective function have been generated based on analysis and assessment for many design proposals with CSI SAP software. These data have been used later in SPSS software to develop a pure quadratic nonlinear regression model for the explicit objective function. Good correlations with a coefficient, R², in the range from 0.88 to 0.99 have been noted between the original implicit functions and the corresponding explicit functions generated with meta-model.

Keywords: Meta-modal, objective function, steel frames, seismic analysis, design.

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Authors: Omid F. Valilai, Mahmoud Houshmand

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Nowadays companies strive to survive in a competitive global environment. To speed up product development/modifications, it is suggested to adopt a collaborative product development approach. However, despite the advantages of new IT improvements still many CAx systems work separately and locally. Collaborative design and manufacture requires a product information model that supports related CAx product data models. To solve this problem many solutions are proposed, which the most successful one is adopting the STEP standard as a product data model to develop a collaborative CAx platform. However, the improvement of the STEP-s Application Protocols (APs) over the time, huge number of STEP AP-s and cc-s, the high costs of implementation, costly process for conversion of older CAx software files to the STEP neutral file format; and lack of STEP knowledge, that usually slows down the implementation of the STEP standard in collaborative data exchange, management and integration should be considered. In this paper the requirements for a successful collaborative CAx system is discussed. The STEP standard capability for product data integration and its shortcomings as well as the dominant platforms for supporting CAx collaboration management and product data integration are reviewed. Finally a platform named LAYMOD to fulfil the requirements of CAx collaborative environment and integrating the product data is proposed. The platform is a layered platform to enable global collaboration among different CAx software packages/developers. It also adopts the STEP modular architecture and the XML data structures to enable collaboration between CAx software packages as well as overcoming the STEP standard limitations. The architecture and procedures of LAYMOD platform to manage collaboration and avoid contradicts in product data integration are introduced.

Keywords: CAx, Collaboration management, STEP applicationmodules, STEP standard, XML data structures

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Authors: Isao Taguchi, Yasuo Sugai

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This paper proposes an efficient learning method for the layered neural networks based on the selection of training data and input characteristics of an output layer unit. Comparing to recent neural networks; pulse neural networks, quantum neuro computation, etc, the multilayer network is widely used due to its simple structure. When learning objects are complicated, the problems, such as unsuccessful learning or a significant time required in learning, remain unsolved. Focusing on the input data during the learning stage, we undertook an experiment to identify the data that makes large errors and interferes with the learning process. Our method devides the learning process into several stages. In general, input characteristics to an output layer unit show oscillation during learning process for complicated problems. The multi-stage learning method proposes by the authors for the function approximation problems of classifying learning data in a phased manner, focusing on their learnabilities prior to learning in the multi layered neural network, and demonstrates validity of the multi-stage learning method. Specifically, this paper verifies by computer experiments that both of learning accuracy and learning time are improved of the BP method as a learning rule of the multi-stage learning method. In learning, oscillatory phenomena of a learning curve serve an important role in learning performance. The authors also discuss the occurrence mechanisms of oscillatory phenomena in learning. Furthermore, the authors discuss the reasons that errors of some data remain large value even after learning, observing behaviors during learning.

Keywords: data selection, function approximation problem, multistage leaning, neural network, voluntary oscillation.

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Authors: Bua Srikos, Phusit Phukamchanoad, Suwaree Yordchim

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The purpose is to study the model and characteristic of participation of the suitable community to lead to develop permanent water marketing in Bang Noi Floating Market, Bangkonti District, Samutsongkhram Province. A total of 342 survey questionnaire was administered to potential respondents. The researchers interviewed the leader of the community. Appreciation Influence Control (AIC) was used to talk with 20 villagers on arena. The findings revealed that overall, most people had the middle level of the participation in developing the durable Bang Noi Floating Market, Bangkonti, Samutsongkhram Province and in aspects of gaining benefits from developing it with atmosphere and a beautiful view for tourism. For example, the landscape is beautiful with public utilities. The participation in preserving and developing Bang Noi Floating Market remains in the former way of life. The basic factor of person affects to the participation of people such as age, level of education, career, and income per month. Most participants are the original hosts that have houses and shops located in the marketing and neighbor. These people involve with the benefits and have the power to make a water marketing strategy, the major role to set the information database. It also found that the leader and the villagers play the important role in setting a five-physical database. Data include level of information such as position of village, territory of village, road, river, and premises. Information of culture consists of a two-level of information, interesting point, and Itinerary. The information occurs from presenting and practicing by the leader and villagers in the community.All of phases are presented for listening and investigating database together in both the leader and villagers in the process of participation.

Keywords: Community Participation, Sustainable Development, Encouragement Tourism.

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Authors: Ahmed M. Khedr, Saad M. Abdelrahman, Kareem M. Tonbol

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Two geo-referenced sea level datasets (September 2008 – November 2010) and (April 2012 – January 2014) were recorded at Alexandria Western Harbour (AWH). Accurate re-definition of tidal datum, referred to the latest International Terrestrial Reference Frame (ITRF-2014), was discussed and updated to improve our understanding of the old predefined tidal datum at Alexandria. Tidal and non-tidal components of sea level were separated with the use of Delft-3D hydrodynamic model-tide suit (Delft-3D, 2015). Tidal characteristics at AWH were investigated and harmonic analysis showed the most significant 34 constituents with their amplitudes and phases. Tide was identified as semi-diurnal pattern as indicated by a “Form Factor” of 0.24 and 0.25, respectively. Principle tidal datums related to major tidal phenomena were recalculated referred to a meaningful geodetic height datum. The portion of residual energy (surge) out of the total sea level energy was computed for each dataset and found 77% and 72%, respectively. Power spectral density (PSD) showed accurate resolvability in high band (1–6) cycle/days for the nominated independent constituents, except some neighbouring constituents, which are too close in frequency. Wind and atmospheric pressure data, during the recorded sea level time, were analysed and cross-correlated with the surge signals. Moderate association between surge and wind and atmospheric pressure data were obtained. In addition, long-term sea level rise trend at AWH was computed and showed good agreement with earlier estimated rates.

Keywords: Alexandria, Delft-3D, Egypt, geodetic reference, harmonic analysis, sea level.

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Authors: B. Golchin, N. Riahi

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One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Keywords: emotion classification, sentiment analysis, social networks, deep neural networks

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Authors: Sajith Sajeev

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The application of Computational Fluid Dynamics (CFD) is widespread in engineering and industry, including aerospace, automotive, and energy. CFD simulations necessitate the use of intricate mathematical models and a substantial amount of computational power to accurately describe the behavior of fluids. The implementation of CFD projects can be difficult, and a well-structured approach to project management is required to assure the timely and cost-effective delivery of high-quality results. This paper's objective is to provide an overview of project management in CFD, including its problems, methodologies, and best practices. The study opens with a discussion of the difficulties connected with CFD project management, such as the complexity of the mathematical models, the need for extensive computational resources, and the difficulties associated with validating and verifying the results. In addition, the study examines the project management methodologies typically employed in CFD, such as the Traditional/Waterfall model, Agile and Scrum. Comparisons are made between the advantages and disadvantages of each technique, and suggestions are made for their effective implementation in CFD projects. The study concludes with a discussion of the best practices for project management in CFD, including the utilization of a well-defined project scope, a clear project plan, and effective teamwork. In addition, it highlights the significance of continuous process improvement and the utilization of metrics to monitor progress and discover improvement opportunities. This article is a resource for project managers, researchers, and practitioners in the field of CFD. It can aid in enhancing project outcomes, reducing risks, and enhancing the productivity of CFD projects. This paper provides a complete overview of project management in CFD and is a great resource for individuals who wish to implement efficient project management methods in CFD projects.

Keywords: Project management, Computational Fluid Dynamics, Traditional/Waterfall methodology, agile methodology, scrum methodology.

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Authors: S. Shakibaei, P. Alpkokin

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The railway network is one of the major components of a transportation system in a country which may be an indicator of the country’s level of economic improvement. Since 2000s on, revival of national railways and development of High Speed Rail (HSR) lines are one of the most remarkable policies of Turkish government in railway sector. Within this trend, the railway age is to be revived and coming decades will be a golden opportunity. Indubitably, major infrastructures such as road and railway networks require sizeable investment capital, precise maintenance and reparation. Traditionally, governments are held responsible for funding, operating and maintaining these infrastructures. However, lack or shortage of financial resources, risk responsibilities (particularly cost and time overrun), and in some cases inefficacy in constructional, operational and management phases persuade governments to find alternative options. Financial power, efficient experiences and background of private sector are the factors convincing the governments to make a collaboration with private parties to develop infrastructures. Public-Private Partnerships (PPP or 3P or P3) and related regulatory issues are born considering these collaborations. In Turkey, PPP approaches have attracted attention particularly during last decade and these types of investments have been accelerated by government to overcome budget limitations and cope with inefficacy of public sector in improving transportation network and its operation. This study mainly tends to present a comprehensive overview of PPP concept, evaluate the regulatory procedure in Europe and propose a general framework for Turkish State Railways (TCDD) as an outlook on privatization, liberalization and deregulation of railway network.

Keywords: Deregulation, high-speed rail, liberalization, privatization, public-private partnership.

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Authors: Azaz Zaman, Mirazur Rahman

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Capital market is a crucial financial market place where companies and the government can raise long-term funds and, at the same time, investors get the opportunity to invest in the listed companies. Capital markets play a vital role not only in shifting the funds from surplus entity to deficit for investment, but also in the overall economic development of any developing country like Bangladesh. Being the first and biggest capital market of Bangladesh, Dhaka Stock Exchange (DSE) is the prime bourse of the country. The differences in the investment preference— among three broad categories of investors in DSE including individual investors, institutional investors, and government— are easily observed. Authors of this article have used five categories of investors such as sponsors or directors of the company, institutional investors, foreign investors, government, and the general public in order to present a comparative analysis of their investment patterns. Obtaining data on the percentage of investment by these five types of investors in different sectors from the DSE website, this study aims to analyze the sector-wise investment preference of these investors using August 2018 data. The study has found that the sponsors or directors of the company have the highest percentage of investment in the textile industry which is close to 16%. The Bangladesh government, as an investor, has the highest percentage of investment in the fuel & power sector, approximately 32%. It has also found that the mutual funds' sector is mostly financed by institutional investors, nearly 28%. Foreign investors have their most investments in the banking sector, which is close to 22%. It has also revealed that the textile sector is mostly financed by the general public, close to 17%. Nevertheless, general public, surprisingly, has the lowest percentage of investment in the telecommunication sector, which is 0.10%.

Keywords: Stock market investment, Dhaka stock exchange, capital market, Bangladesh.

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Authors: Luiz G. Véras, Felipe L. Medeiros, Lamartine F. Guimarães

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This work approaches the automatic planning of paths for Unmanned Aerial Vehicles (UAVs) through the application of the Rapidly Exploring Random Tree Star-Smart (RRT*-Smart) algorithm. RRT*-Smart is a sampling process of positions of a navigation environment through a tree-type graph. The algorithm consists of randomly expanding a tree from an initial position (root node) until one of its branches reaches the final position of the path to be planned. The algorithm ensures the planning of the shortest path, considering the number of iterations tending to infinity. When a new node is inserted into the tree, each neighbor node of the new node is connected to it, if and only if the extension of the path between the root node and that neighbor node, with this new connection, is less than the current extension of the path between those two nodes. RRT*-smart uses an intelligent sampling strategy to plan less extensive routes by spending a smaller number of iterations. This strategy is based on the creation of samples/nodes near to the convex vertices of the navigation environment obstacles. The planned paths are smoothed through the application of the method called quintic pythagorean hodograph curves. The smoothing process converts a route into a dynamically-viable one based on the kinematic constraints of the vehicle. This smoothing method models the hodograph components of a curve with polynomials that obey the Pythagorean Theorem. Its advantage is that the obtained structure allows computation of the curve length in an exact way, without the need for quadratural techniques for the resolution of integrals.

Keywords: Path planning, path smoothing, Pythagorean hodograph curve, RRT*-Smart.

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Authors: Dante J. Dorantes-González, Aldrin Balsa-Yepes

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Existing learning techniques such as problem-based learning, project-based learning, or case study learning are learning techniques that focus mainly on technical details, but give no specific guidelines on learner’s experience and emotional learning aspects such as arousal salience and valence, being emotional states important factors affecting engagement and retention. Some approaches involving emotion in educational settings, such as social and emotional learning, lack neuroscientific rigorousness and use of specific neurobiological mechanisms. On the other hand, neurobiology approaches lack educational applicability. And educational approaches mainly focus on cognitive aspects and disregard conditioning learning. First, authors start explaining the reasons why it is hard to learn thoughtfully, then they use the method of neurobiological mapping to track the main limbic system functions, such as the reward circuit, and its relations with perception, memories, motivations, sympathetic and parasympathetic reactions, and sensations, as well as the brain cortex. The authors conclude explaining the major finding: The mechanisms of nonconscious learning and the triggers that guarantee long-term memory potentiation. Afterward, the educational framework for practical application and the instructors’ guidelines are established. An implementation example in engineering education is given, namely, the study of tuned-mass dampers for earthquake oscillations attenuation in skyscrapers. This work represents an original learning technique based on nonconscious learning mechanisms to enhance long-term memories that complement existing cognitive learning methods.

Keywords: Emotion, emotion-enhanced memory, learning technique, STEM.

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Authors: M. R. Homaeinezhad, E. Tavakkoli, M. Habibi, S. A. Atyabi, A. Ghaffari

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This paper describes a new supervised fusion (hybrid) electrocardiogram (ECG) classification solution consisting of a new QRS complex geometrical feature extraction as well as a new version of the learning vector quantization (LVQ) classification algorithm aimed for overcoming the stability-plasticity dilemma. Toward this objective, after detection and delineation of the major events of ECG signal via an appropriate algorithm, each QRS region and also its corresponding discrete wavelet transform (DWT) are supposed as virtual images and each of them is divided into eight polar sectors. Then, the curve length of each excerpted segment is calculated and is used as the element of the feature space. To increase the robustness of the proposed classification algorithm versus noise, artifacts and arrhythmic outliers, a fusion structure consisting of five different classifiers namely as Support Vector Machine (SVM), Modified Learning Vector Quantization (MLVQ) and three Multi Layer Perceptron-Back Propagation (MLP–BP) neural networks with different topologies were designed and implemented. The new proposed algorithm was applied to all 48 MIT–BIH Arrhythmia Database records (within–record analysis) and the discrimination power of the classifier in isolation of different beat types of each record was assessed and as the result, the average accuracy value Acc=98.51% was obtained. Also, the proposed method was applied to 6 number of arrhythmias (Normal, LBBB, RBBB, PVC, APB, PB) belonging to 20 different records of the aforementioned database (between– record analysis) and the average value of Acc=95.6% was achieved. To evaluate performance quality of the new proposed hybrid learning machine, the obtained results were compared with similar peer– reviewed studies in this area.

Keywords: Feature Extraction, Curve Length Method, SupportVector Machine, Learning Vector Quantization, Multi Layer Perceptron, Fusion (Hybrid) Classification, Arrhythmia Classification, Supervised Learning Machine.

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Authors: Tholokuhle T. Ntshakala, Seraphin D. Eyono Obono

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Nations are still finding it quite difficult to win mega sport competitions despite the major contribution of sport to society in terms of social and economic development, personal health, and in education. Even though the world of sports has been transformed into a huge global economy, it is important to note that the first step of sport is usually its introduction to children at school through physical education or PE. In other words, nations who do not win mega sport competitions also suffer from a weak and neglected PE system. This problem of the neglect of PE systems is the main motivation of this research aimed at examining the factors affecting the perceived awareness of physical education teachers on the ICTs that are adoptable for the teaching and learning of physical education. Two types of research objectives will materialize this aim: relevant theories will be identified in relation to the analysis of the perceived ICT awareness of PE teachers and subsequent models will be compiled and designed from existing literature; the empirical testing of such theories and models will also be achieved through the survey of PE teachers from the Camperdown magisterial district of the KwaZulu-Natal province of South Africa. The main hypothesis at the heart of this study is the relationship between the demographics of PE teachers, their behavior both as individuals and as social entities, and their perceived awareness of the ICTs that are adoptable for PE, as postulated by existing literature; except that this study categorizes human behavior under performance expectancy, computer attitude, and social influence. This hypothesis was partially confirmed by the survey conducted by this research in the sense that performance expectancy and teachers’ age, gender, computer usage, and class size were found to be the only factors affecting their awareness of ICTs for physical education.

Keywords: Human Behavior, ICT Awareness, Physical Education, Teachers.

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Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L Duan

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The conditional density characterizes the distribution of a response variable y given other predictor x, and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts a motivating starting point. In this work, we extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zP , zN]. The zP component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zN component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach, coined Augmented Posterior CDE (AP-CDE), only requires a simple modification on the common normalizing flow framework, while significantly improving the interpretation of the latent component, since zP represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of x-related variations due to factors such as lighting condition and subject id, from the other random variations. Further, the experiments show that an unconditional NF neural network, based on an unsupervised model of z, such as Gaussian mixture, fails to generate interpretable results.

Keywords: Conditional density estimation, image generation, normalizing flow, supervised dimension reduction.

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Authors: Li-Ping Hsiao, Feng-Chuan Pan

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Leave of absence is important in maintaining a good status of human resource quality. Allowing the employees temporarily free from the routine assignments can vitalize the workers- morality and productivity. This is particularly critical to secure a satisfactory service quality for healthcare professionals of which were typically featured with labor intensive and complicated works to perform. As one of the veteran hospitals that were found and operated by the Veteran Department of Taiwan, the nursing staff of the case hospital was squeezed to an extreme minimum level under the pressure of a tight budgeting. Leave of absence on schedule became extremely difficult, especially for the intensive care units (ICU), in which required close monitoring over the cared patients, and that had more easily driven the ICU nurses nervous. Even worse, the deferred leaves were more than 10 days at any time in the ICU because of a fluctuating occupancy. As a result, these had brought a bad setback to this particular nursing team, and consequently defeated the job performance and service quality. To solve this problem and accordingly to strengthen their morality, a project team was organized across different departments specific for this. Sufficient information regarding jobs and positions requirements, labor resources, and actual working hours in detail were collected and analyzed in the team meetings. Several alternatives were finalized. These included job rotating, job combination, leave on impromptu and cross-departmental redeployment. Consequently, the deferred leave days sharply reduced 70% to a level of 3 or less days. This improvement had not only provided good shelter for the ICU nurses that improved their job performance and patient safety but also encouraged the nurses active participating of a project and learned the skills of solving problems with colleagues.

Keywords: Information, job rotating, human resource, intensive care unit.

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Authors: Teka Haile, Behailu Hawulte, Solomon Alemayehu

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Background: HIV virological failure still remains a problem in HV/AIDS treatment and care. This study aimed to describe the prevalence and identify the factors associated with viral non-suppression among HIV-positive adult patients on antiretroviral therapy in Woliso Town, Oromia, Ethiopia. Methods: A retrospective cross-sectional study was conducted among 424 HIV-positive patient’s attending antiretroviral therapy (ART) in Woliso Town during the period from August 25, 2020 to August 30, 2020. Data collected from patient medical records were entered into Epi Info version 2.3.2.1 and exported to SPSS version 21.0 for analysis. Logistic regression analysis was done to identify factors associated with viral load non-suppression, and statistical significance of odds ratios were declared using 95% confidence interval and p-value < 0.05. Results: A total of 424 patients were included in this study. The mean age (± SD) of the study participants was 39.88 (± 9.995) years. The prevalence of HIV viral load non-suppression was 55 (13.0%) with 95% CI (9.9-16.5). Second-line ART treatment regimen (Adjusted Odds Ratio (AOR) = 8.98, 95% Confidence Interval (CI): 2.64, 30.58) and routine viral load testing (AOR = 0.01, 95% CI: 0.001, 0.02) were significantly associated with virological non-suppression. Conclusion: Virological non-suppression was high, which hinders the achievement of the third global 95 target. The second-line regimen and routine viral load testing were significantly associated with virological non-suppression. It suggests the need to assess the effectiveness of antiretroviral drugs for epidemic control. It also clearly shows the need to decentralize third-line ART treatment for those patients in need.

Keywords: Virological non-suppression, HIV-positive, ART, Woliso Town, Ethiopia.

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Authors: Joseph Zernik

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Validity, integrity, and impacts of the IT systems of the US federal courts have been studied as part of the Human Rights Alert-NGO (HRA) submission for the 2015 Universal Periodic Review (UPR) of human rights in the United States by the Human Rights Council (HRC) of the United Nations (UN). The current report includes overview of IT system analysis, data-mining and case studies. System analysis and data-mining show: Development and implementation with no lawful authority, servers of unverified identity, invalidity in implementation of electronic signatures, authentication instruments and procedures, authorities and permissions; discrimination in access against the public and unrepresented (pro se) parties and in favor of attorneys; widespread publication of invalid judicial records and dockets, leading to their false representation and false enforcement. A series of case studies documents the impacts on individuals' human rights, on banking regulation, and on international matters. Significance is discussed in the context of various media and expert reports, which opine unprecedented corruption of the US justice system today, and which question, whether the US Constitution was in fact suspended. Similar findings were previously reported in IT systems of the State of California and the State of Israel, which were incorporated, subject to professional HRC staff review, into the UN UPR reports (2010 and 2013). Solutions are proposed, based on the principles of publicity of the law and the separation of power: Reliance on US IT and legal experts under accountability to the legislative branch, enhancing transparency, ongoing vigilance by human rights and internet activists. IT experts should assume more prominent civic duties in the safeguard of civil society in our era.

Keywords: E-justice, federal courts, United States, human rights, banking regulation.

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Authors: Zoi Konsoula

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Antioxidant-rich extracts were prepared from pomegranate peels, seeds and juice using methanol and ethanol and their antioxidant activity was evaluated by the 1,1-diphenyl-2-picrylhydrazine (DPPH) radical scavenging and Ferric Reducing Antioxidant Power (FRAP) method. Both analytical methods indicated a higher antioxidant activity in extracts prepared from peels, which was comparable to that of butylated hydroxytoluene (BHT). Furthermore, the antioxidant activity was correlated to the phenolic and flavonoid content of the various extracts. The antioxidant effectiveness of the extracts was also assessed using corn oil as the oxidation substrate. More specifically, preheated corn oil samples stabilized with extracts at a concentration of 250 ppm, 500 ppm or 1,000 ppm were subjected to accelerated aging (100 oC, 10 days) and the extent of oxidative alteration was followed by the measurement of the peroxide, conjugated dienes and trienes, as well as p-aniside value. BHT at its legal limit (200 ppm) served as standard besides the control sample. Results from the different parameters were in agreement with each other suggesting that pomegranate extracts can stabilize corn oil effectively under accelerated conditions, at all concentrations tested. However, the magnitude of oil stabilization depended strongly on the amount of extract added and this was positively correlated with their phenolic content. Pomegranate peel extracts, which exhibited the highest not only phenolic and flavonoid content but also antioxidant activity, were more potent in inhibiting oxidative deterioration. Both methanolic and ethanolic peel extracts at a concentration of 500 ppm exerted a stabilizing effect comparable to that of BHT, while at a concentration of 1000 ppm they exhibited higher stabilization efficiency in comparison to BHT. Finally, heating oil samples resulted in a time dependent decrease in their antioxidant capacity. Samples containing peel extracts appeared to retain their antioxidant capacity for a longer period, indicating that these extracts contained active compounds that offered superior antioxidant protection to corn oil.

Keywords: Antioxidant activity, corn oil, oxidative deterioration, pomegranate.

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Authors: Mohamed Ammar Abbassi, Kamel Guedri, Mohamed Naceur Borjini, Kamel Halouani, Belkacem Zeghmati

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The radiative heat transfer problem is investigated numerically for 2D complex geometry biomass pyrolysis reactor composed of two pyrolysis chambers and a heat recuperator. The fumes are a mixture of carbon dioxide and water vapor charged with absorbing and scattering particles and soot. In order to increase gases residence time and heat transfer, the heat recuperator is provided with many inclined, vertical, horizontal, diffuse and grey baffles of finite thickness and has a complex geometry. The Finite Volume Method (FVM) is applied to study radiative heat transfer. The blocked-off region procedure is used to treat the geometrical irregularities. Eight cases are considered in order to demonstrate the effect of adding baffles on the walls of the heat recuperator and on the walls of the pyrolysis rooms then choose the best case giving the maximum heat flux transferred to the biomass in the pyrolysis chambers. Ray effect due to the presence of baffles is studied and demonstrated to have a crucial effect on radiative heat flux on the walls of the pyrolysis rooms. Shadow effect caused by the presence of the baffles is also studied. The non grey radiative heat transfer is studied for the real existent configuration. The Weighted Sum of The Grey Gases (WSGG) Model of Kim and Song is used as non grey model. The effect of soot volumetric fraction on the non grey radiative heat flux is investigated and discussed.

Keywords: Baffles, Blocked-off region procedure, FVM, Heat recuperation, Radiative heat transfer, Shadow effect.

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Authors: Sultan Alharby, Nick Harris, Alex Weddell, Jeff Reeve

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The concept of the Internet of Things (IoT) has received much attention over the last five years. It is predicted that the IoT will influence every aspect of our lifestyles in the near future. Wireless Sensor Networks are one of the key enablers of the operation of IoTs, allowing data to be collected from the surrounding environment. However, due to limited resources, nature of deployment and unattended operation, a WSN is vulnerable to various types of attack. Security is paramount for reliable and safe communication between IoT embedded devices, but it does, however, come at a cost to resources. Nodes are usually equipped with small batteries, which makes energy conservation crucial to IoT devices. Nevertheless, security cost in terms of energy consumption has not been studied sufficiently. Previous research has used a security specification of 802.15.4 for IoT applications, but the energy cost of each security level and the impact on quality of services (QoS) parameters remain unknown. This research focuses on the cost of security at the IoT media access control (MAC) layer. It begins by studying the energy consumption of IEEE 802.15.4 security levels, which is followed by an evaluation for the impact of security on data latency and throughput, and then presents the impact of transmission power on security overhead, and finally shows the effects of security on memory footprint. The results show that security overhead in terms of energy consumption with a payload of 24 bytes fluctuates between 31.5% at minimum level over non-secure packets and 60.4% at the top security level of 802.15.4 security specification. Also, it shows that security cost has less impact at longer packet lengths, and more with smaller packet size. In addition, the results depicts a significant impact on data latency and throughput. Overall, maximum authentication length decreases throughput by almost 53%, and encryption and authentication together by almost 62%.

Keywords: Internet of Things, IEEE 802.15.4, security cost evaluation, wireless sensor network, energy consumption.

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Authors: Farooq A. Al-Sheikh, Carol Moralejo, Mark Pritzker, William A. Anderson, Ali Elkamel

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Ammonia in mining wastewater is a significant problem, and treatment can be especially difficult in cold climates where biological treatment is not feasible. An adsorption process is one of the alternative processes that can be used to reduce ammonia concentrations to acceptable limits, and therefore a LEWATIT resin strongly acidic H+ form ion exchange resin and a Bowie Chabazite Na form AZLB-Na zeolite were tested to assess their effectiveness. For these adsorption tests, two packed bed columns (a mini-column constructed from a 32-cm long x 1-cm diameter piece of glass tubing, and a 60-cm long x 2.5-cm diameter Ace Glass chromatography column) were used containing varying quantities of the adsorbents. A mining wastewater with ammonia concentrations of 22.7 mg/L was fed through the columns at controlled flowrates. In the experimental work, maximum capacities of the LEWATIT ion exchange resin were 0.438, 0.448, and 1.472 mg/g for 3, 6, and 9 g respectively in a mini column and 1.739 mg/g for 141.5 g in a larger Ace column while the capacities for the AZLB-Na zeolite were 0.424, and 0.784 mg/g for 3, and 6 g respectively in the mini column and 1.1636 mg/g for 38.5 g in the Ace column. In the theoretical work, Thomas, Adams-Bohart, and Yoon-Nelson models were constructed to describe a breakthrough curve of the adsorption process and find the constants of the above-mentioned models. In the regeneration tests, 5% hydrochloric acid, HCl (v/v) and 10% sodium hydroxide, NaOH (w/v) were used to regenerate the LEWATIT resin and AZLB-Na zeolite with 44 and 63.8% recovery, respectively. In conclusion, continuous flow adsorption using a LEWATIT ion exchange resin and an AZLB-Na zeolite is efficient when using a co-flow technique for removal of the ammonia from wastewater. Thomas, Adams-Bohart, and Yoon-Nelson models satisfactorily fit the data with R² closer to 1 in all cases.

Keywords: AZLB-Na zeolite, continuous adsorption, LEWATIT resin, models, regeneration.

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Authors: К. R. Aida–Zade, C. Ardil, S. S. Rustamov

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Statement of the automatic speech recognition problem, the assignment of speech recognition and the application fields are shown in the paper. At the same time as Azerbaijan speech, the establishment principles of speech recognition system and the problems arising in the system are investigated. The computing algorithms of speech features, being the main part of speech recognition system, are analyzed. From this point of view, the determination algorithms of Mel Frequency Cepstral Coefficients (MFCC) and Linear Predictive Coding (LPC) coefficients expressing the basic speech features are developed. Combined use of cepstrals of MFCC and LPC in speech recognition system is suggested to improve the reliability of speech recognition system. To this end, the recognition system is divided into MFCC and LPC-based recognition subsystems. The training and recognition processes are realized in both subsystems separately, and recognition system gets the decision being the same results of each subsystems. This results in decrease of error rate during recognition. The training and recognition processes are realized by artificial neural networks in the automatic speech recognition system. The neural networks are trained by the conjugate gradient method. In the paper the problems observed by the number of speech features at training the neural networks of MFCC and LPC-based speech recognition subsystems are investigated. The variety of results of neural networks trained from different initial points in training process is analyzed. Methodology of combined use of neural networks trained from different initial points in speech recognition system is suggested to improve the reliability of recognition system and increase the recognition quality, and obtained practical results are shown.

Keywords: Speech recognition, cepstral analysis, Voice activation detection algorithm, Mel Frequency Cepstral Coefficients, features of speech, Cepstral Mean Subtraction, neural networks, Linear Predictive Coding.

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Authors: Annur Suhadi, Haris B. Harahap, Zaim Arrosyidi, Epan, Darmapala

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Oilfields under waterflood often face the problem of plugging injectors either by internal filtration or external filter cake built up inside pore throats. The content of suspended solids shall be reduced to required level of filtration since corrective action of plugging is costly expensive. The performance of nutshell filters, where filtration takes place, is good using pecan and walnut shells. Candlenut shells were used instead of pecan and walnut shells since they were abundant in Indonesia, Malaysia, and East Africa. Physical and chemical properties of walnut, pecan, and candlenut shells were tested and the results were compared. Testing, using full-scale nutshell filters, was conducted to determine the oil content, turbidity, and suspended solid removal, which was based on designed flux rate. The performance of candlenut shells, which were deeply bedded in nutshell filters for filtration process, was monitored. Cleaned water outgoing nutshell filters had total suspended solids of 17 ppm, while oil content could be reduced to 15.1 ppm. Turbidity, using candlenut shells, was below the specification for injection water, which was less than 10 Nephelometric Turbidity Unit (NTU). Turbidity of water, outgoing nutshell filter, was ranged from 1.7-5.0 NTU at various dates of operation. Walnut, pecan, and candlenut shells had moisture content of 8.98 wt%, 10.95 wt%, and 9.95 wt%, respectively. The porosity of walnut, pecan, and candlenut shells was significantly affected by moisture content. Candlenut shells had property of toluene solubility of 7.68 wt%, which was much higher than walnut shells, reflecting more crude oil adsorption. The hardness of candlenut shells was 2.5-3 Mohs, which was close to walnut shells’ hardness. It was advantage to guarantee the cleaning filter cake by fluidization process during backwashing.

Keywords: Candlenut shells, walnut shells, pecan shells, nutshell filter, filtration.

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Authors: Raghavi Janaswamy, Saraswathi K. Vasudev

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Music is ubiquitous in human lives. Ever since the foetus hears the sound inside the mother’s womb and later upon birth the baby experiences alluring sounds, the curiosity of learning emanates and evokes exploration. Music is an education than a mere entertainment. The intricate balance between music, education and entertainment has well been recognized by the scientific community and is being explored as a viable tool to understand and improve the human cognition. There are seven basic swaras (notes) Sa, Ri, Ga, Ma, Pa, Da and Ni in the Carnatic music system that are analogous to C, D, E, F, G, A and B of the western system. The Carnatic music builds on the conscious use of microtones, gamakams (oscillation) and rendering styles that evolved over centuries and established its stance. The complex but erudite raga system has been designed with elaborate experiments on srutis (musical sounds) and human perception abilities. In parallel, ‘rasa’- the emotions evoked by certain srutis and hence the ragas been solidified along with the power of language in combination with the musical sounds. The Carnatic music branches out as Kalpita sangeetam (pre-composed music) and Manodharma sangeetam (improvised music). This article explores the Manodharma sangeetam and its subdivisions such as raga alapana, swara kalpana, neraval and ragam-tanam-pallavi (RTP). The intrinsic mathematical strategies in its practice methods toward improvising the music have been discussed in detail with concert examples. The techniques on swara weaving for swara kalpana rendering and methods on the alapana development are also discussed at length with an emphasis on the impact on the human cognitive abilities. The articulation of the outlined conscious practice methods not only helps to leave a long-lasting melodic impression on the listeners but also onsets cognitive developments.

Keywords: Carnatic, Manodharmam, music cognition, Alapana.

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Authors: Sugandhi, Parteek Kumar, Sanmeet Kaur

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Sign Language (SL) is used by deaf and other people who cannot speak but can hear or have a problem with spoken languages due to some disability. It is a visual gesture language that makes use of either one hand or both hands, arms, face, body to convey meanings and thoughts. SL automation system is an effective way which provides an interface to communicate with normal people using a computer. In this paper, an avatar based dictionary has been proposed for text to Indian Sign Language (ISL) generation system. This research work will also depict a literature review on SL corpus available for various SL s over the years. For ISL generation system, a written form of SL is required and there are certain techniques available for writing the SL. The system uses Hamburg sign language Notation System (HamNoSys) and Signing Gesture Mark-up Language (SiGML) for ISL generation. It is developed in PHP using Web Graphics Library (WebGL) technology for 3D avatar animation. A multilingual ISL dictionary is developed using HamNoSys for both English and Hindi Language. This dictionary will be used as a database to associate signs with words or phrases of a spoken language. It provides an interface for admin panel to manage the dictionary, i.e., modification, addition, or deletion of a word. Through this interface, HamNoSys can be developed and stored in a database and these notations can be converted into its corresponding SiGML file manually. The system takes natural language input sentence in English and Hindi language and generate 3D sign animation using an avatar. SL generation systems have potential applications in many domains such as healthcare sector, media, educational institutes, commercial sectors, transportation services etc. This research work will help the researchers to understand various techniques used for writing SL and generation of Sign Language systems.

Keywords: Avatar, dictionary, HamNoSys, hearing-impaired, Indian Sign Language, sign language.

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Authors: L.A du Plessis

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South Africa is facing a crisis with not being able to produce enough graduates in the scarce skills areas to sustain economic growth. The crisis is fuelled by a school system that does not produce enough potential students with Mathematics, Accounting and Science. Since the introduction of the new school curriculum in 2008, there is no longer an option to take pure maths on a standard grade level. Instead, only two mathematical subjects are offered: pure maths (which is on par with higher grade maths) and mathematical literacy. It is compulsory to take one or the other. As a result, lees student finishes Grade 12 with pure mathematics every year. This national problem needs urgent attention if South Africa is to make any headway in critical skills development as mathematics is a gateway to scarce skills professions. Higher education institutions initiated several initiatives in an attempt to address the above, including preparatory courses, bridging programmes and extended curricula with foundation provisions. In view of the above, and government policy directives to broaden access in the scarce skills areas to increase student throughput, foundation provision was introduced for Commerce and Information Technology programmes at the Vaal Triangle Campus (VTC) of North-West University (NWU) in 2010. Students enrolling for extended programmes do not comply with the minimum prerequisites for the normal programmes. The question then arises as to whether these programmes have the intended impact? This paper reports the results of a two year longitudinal study, tracking the first year academic achievement of the two cohorts of enrolments since 2010. The results provide valuable insight into the structuring of an extended programme and its potential impact.

Keywords: Access, extended programmes, foundation provision, mathematics.

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Authors: Hijun Kim, Jungkeun Sung, Seungwoo Kim

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In this paper, a Smart Home Service Robot, McBot II, which performs mess-cleanup function etc. in house, is designed much more optimally than other service robots. It is newly developed in much more practical system than McBot I which we had developed two years ago. One characteristic attribute of mobile platforms equipped with a set of dependent wheels is their omni- directionality and the ability to realize complex translational and rotational trajectories for agile navigation in door. An accurate coordination of steering angle and spinning rate of each wheel is necessary for a consistent motion. This paper develops trajectory controller of 3-wheels omni-directional mobile robot using fuzzy azimuth estimator. A specialized anthropomorphic robot manipulator which can be attached to the housemaid robot McBot II, is developed in this paper. This built-in type manipulator consists of both arms with 3 DOF (Degree of Freedom) each and both hands with 3 DOF each. The robotic arm is optimally designed to satisfy both the minimum mechanical size and the maximum workspace. Minimum mass and length are required for the built-in cooperated-arms system. But that makes the workspace so small. This paper proposes optimal design method to overcome the problem by using neck joint to move the arms horizontally forward/backward and waist joint to move them vertically up/down. The robotic hand, which has two fingers and a thumb, is also optimally designed in task-based concept. Finally, the good performance of the developed McBot II is confirmed through live tests of the mess-cleanup task.

Keywords: Holonomic Omni-wheeled Mobile Robot, Special-purpose, Manipulation, Home Service Robot

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