Search results for: Machine design

Authors: Syadiah Nor Wan Shamsuddin, Valerie Lesk , Hassan Ugail

Abstract:

Early detection of dementia by testing the spatial memory can be applied using a virtual environment. This paper presents guidelines on how to design a virtual environment specifically for elderly in early detection of dementia. The specific design needs to be considered because the effectiveness of the technology relies on the ability of the end user to use it. The primary goal of these guidelines is to promote accessibility. Based on these guidelines, a virtual simulation was developed and evaluated. The results on usability of acceptance and satisfaction that are tested on young (control group) and elderly participants indicate that these guidelines are reliable and useful for use with elderly people.

Keywords: Virtual Environment, spatial memory, design, guidelines

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Authors: Eakong Atiptamvaree, Twittie Senivongse

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Process-oriented software development is a new software development paradigm in which software design is modeled by a business process which is in turn translated into a process execution language for execution. The building blocks of this paradigm are software units that are composed together to work according to the flow of the business process. This new paradigm still exhibits the characteristic of the applications built with the traditional software component technology. This paper discusses an approach to apply a traditional technique for software component fabrication to the design of process-oriented software units, called process components. These process components result from decomposing a business process of a particular application domain into subprocesses, and these process components can be reused to design the business processes of other application domains. The decomposition considers five managerial goals, namely cost effectiveness, ease of assembly, customization, reusability, and maintainability. The paper presents how to design or decompose process components from a business process model and measure some technical features of the design that would affect the managerial goals. A comparison between the measurement values from different designs can tell which process component design is more appropriate for the managerial goals that have been set. The proposed approach can be applied in Web Services environment which accommodates process-oriented software development.

Keywords: Business Process Model, Managerial Goals, ProcessComponent.

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Authors: S. Zappacosta, C. Bove, M. Carmela Marinelli, P. di Lauro, K. Spasenovic, L. Ostano, G. Aiello, M. Pietrosanto

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This paper proposes a neural network approach for assessing flood hazard mapping. The core of the model is a machine learning component fed by frequency ratios, namely statistical correlations between flood event occurrences and a selected number of topographic properties. The classification capability was compared with the flood hazard mapping River Basin Plans (Piani Assetto Idrogeologico, acronimed as PAI) designed by the Italian Institute for Environmental Research and Defence, ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale), encoding four different increasing flood hazard levels. The study area of Piemonte, an Italian region, has been considered without loss of generality. The frequency ratios may be used as a standalone block to model the flood hazard mapping. Nevertheless, the mixture with a neural network improves the classification power of several percentage points, and may be proposed as a basic tool to model the flood hazard map in a wider scope.

Keywords: flood modeling, hazard map, neural networks, hydrogeological risk, flood risk assessment

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Authors: P. Wlodarczak, J. Soar, M. Ally

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The dramatic rise in the use of Social Media (SM) platforms such as Facebook and Twitter provide access to an unprecedented amount of user data. Users may post reviews on products and services they bought, write about their interests, share ideas or give their opinions and views on political issues. There is a growing interest in the analysis of SM data from organisations for detecting new trends, obtaining user opinions on their products and services or finding out about their online reputations. A recent research trend in SM analysis is making predictions based on sentiment analysis of SM. Often indicators of historic SM data are represented as time series and correlated with a variety of real world phenomena like the outcome of elections, the development of financial indicators, box office revenue and disease outbreaks. This paper examines the current state of research in the area of SM mining and predictive analysis and gives an overview of the analysis methods using opinion mining and machine learning techniques.

Keywords: Social Media, text mining, knowledge discovery, predictive analysis, machine learning.

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Authors: Santosh Kr. Choudhary

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In this article, LQR based PID controller design for 3DOF helicopter system is investigated. The 3-DOF helicopter system is a benchmark laboratory model having strongly nonlinear characteristics and unstable dynamics which make the control of such system a challenging task. This article first presents the mathematical model of the 3DOF helicopter system and then illustrates the basic idea and technical formulation for controller design. The paper explains the simple approach for the approximation of PID design parameters from the LQR controller gain matrix. The simulation results show that the investigated controller has both static and dynamic performance, therefore the stability and the quick control effect can be obtained simultaneously for the 3DOF helicopter system.

Keywords: 3DOF helicopter system, PID controller, LQR controller, modeling, simulation.

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Authors: Mohammad S. Laghari, Qurban A. Memon, Gulzar A. Khuwaja

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The paper describes a knowledge based system for analysis of microscopic wear particles. Wear particles contained in lubricating oil carry important information concerning machine condition, in particular the state of wear. Experts (Tribologists) in the field extract this information to monitor the operation of the machine and ensure safety, efficiency, quality, productivity, and economy of operation. This procedure is not always objective and it can also be expensive. The aim is to classify these particles according to their morphological attributes of size, shape, edge detail, thickness ratio, color, and texture, and by using this classification thereby predict wear failure modes in engines and other machinery. The attribute knowledge links human expertise to the devised Knowledge Based Wear Particle Analysis System (KBWPAS). The system provides an automated and systematic approach to wear particle identification which is linked directly to wear processes and modes that occur in machinery. This brings consistency in wear judgment prediction which leads to standardization and also less dependence on Tribologists.

Keywords: Computer vision, knowledge based systems, morphology, wear particles.

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Authors: Indra Budi, Rizal Fathoni Aji, Agus Widodo

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Prediction of future research topics by using time series analysis either statistical or machine learning has been conducted previously by several researchers. Several methods have been proposed to combine the forecasting results into single forecast. These methods use fixed combination of individual forecast to get the final forecast result. In this paper, quite different approach is employed to select the forecasting methods, in which every point to forecast is calculated by using the best methods used by similar validation dataset. The dataset used in the experiment is time series derived from research report in Garuda, which is an online sites belongs to the Ministry of Education in Indonesia, over the past 20 years. The experimental result demonstrates that the proposed method may perform better compared to the fix combination of predictors. In addition, based on the prediction result, we can forecast emerging research topics for the next few years.

Keywords: Combination, emerging topics, ensemble, forecasting, machine learning, prediction, research topics, similarity measure, time series.

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Authors: C. Alexandru, P. Alexandru

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The paper presents the virtual model of the active suspension system used for improving the dynamic behavior of a motor vehicle. The study is focused on the design of the control system, the purpose being to minimize the effect of the road disturbances (which are considered as perturbations for the control system). The analysis is performed for a quarter-car model, which corresponds to the suspension system of the front wheel, by using the DFC (Design for Control) software solution EASY5 (Engineering Analysis Systems) of MSC Software. The controller, which is a PIDbased device, is designed through a parametric optimization with the Matrix Algebra Tool (MAT), considering the gain factors as design variables, while the design objective is to minimize the overshoot of the indicial response.

Keywords: Active suspension, Controller, Dynamics, Vehicle

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Authors: Z. Zhou, Q. Chen, S. Wu

Abstract:

Population diversification phenomena becomes quite common in villages located in China’s developed coastal area. Based on the analysis of the traditional rural society and its landscape characteristics, and in consideration of diversified landscape requirements due to the population diversification, with dual ideas of heritage and innovation, methods for rural landscape design were explored by taking Duxuao Village in Zhejiang Province of China as an example.

Keywords: Rural landscape, Population diversification, Landscape design.

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Authors: Adel Aloraini

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Financial forecasting using machine learning techniques has received great efforts in the last decide . In this ongoing work, we show how machine learning of graphical models will be able to infer a visualized causal interactions between different banks in the Saudi equities market. One important discovery from such learned causal graphs is how companies influence each other and to what extend. In this work, a set of graphical models named Gaussian graphical models with developed ensemble penalized feature selection methods that combine ; filtering method, wrapper method and a regularizer will be shown. A comparison between these different developed ensemble combinations will also be shown. The best ensemble method will be used to infer the causal relationships between banks in Saudi equities market.

Keywords: Causal interactions , banks, feature selection, regularizere,

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Authors: Pitsanu Tongkhow, Pichet Jiraprasertwong

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This research investigates risk factors for defective products in autoparts factories. Under a Bayesian framework, a generalized linear mixed model (GLMM) in which the dependent variable, the number of defective products, has a Poisson distribution is adopted. Its performance is compared with the Poisson GLM under a Bayesian framework. The factors considered are production process, machines, and workers. The products coded RT50 are observed. The study found that the Poisson GLMM is more appropriate than the Poisson GLM. For the production Process factor, the highest risk of producing defective products is Process 1, for the Machine factor, the highest risk is Machine 5, and for the Worker factor, the highest risk is Worker 6.

Keywords: Defective autoparts products, Bayesian framework, Generalized linear mixed model (GLMM), Risk factors.

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Authors: Arunesh Chandra, Pankaj Chandna

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Virtual reality (VR) is a rapidly emerging computer interface that attempts to immerse the user completely within an experimental recreation; thereby, greatly enhancing the overall impact and providing a much more intuitive link between the computer and the human participants. The main objective of this study is to design tractor trailer capable of meeting the customers’ requirements and suitable for rough conditions to be used in combination with a farm tractor in India. The final concept is capable of providing arrangements for attaching the trailer to the tractor easily by pickup hitch, stronger and lighter supporting frame, option of spare tyre etc. Furthermore, the resulting product design can be sent via the Internet to customers for comments or marketing purposes. The virtual prototyping (VP) system therefore facilitates advanced product design and helps reduce product development time and cost significantly.

Keywords: Conceptual design, Trailer, Virtual prototyping, Virtual reality.

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Authors: A. Ouanane, A. Serir

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In this paper, a novel algorithm based on Ridgelet Transform and support vector machine is proposed for human action recognition. The Ridgelet transform is a directional multi-resolution transform and it is more suitable for describing the human action by performing its directional information to form spatial features vectors. The dynamic transition between the spatial features is carried out using both the Principal Component Analysis and clustering algorithm K-means. First, the Principal Component Analysis is used to reduce the dimensionality of the obtained vectors. Then, the kmeans algorithm is then used to perform the obtained vectors to form the spatio-temporal pattern, called set-of-labels, according to given periodicity of human action. Finally, a Support Machine classifier is used to discriminate between the different human actions. Different tests are conducted on popular Datasets, such as Weizmann and KTH. The obtained results show that the proposed method provides more significant accuracy rate and it drives more robustness in very challenging situations such as lighting changes, scaling and dynamic environment

Keywords: Human action, Ridgelet Transform, PCA, K-means, SVM.

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Authors: M. T. Yazdani Sabouni, Rasaratnam Logendran

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We consider a typical problem in the assembly of printed circuit boards (PCBs) in a two-machine flow shop system to simultaneously minimize the weighted sum of weighted tardiness and weighted flow time. The investigated problem is a group scheduling problem in which PCBs are assembled in groups and the interest is to find the best sequence of groups as well as the boards within each group to minimize the objective function value. The type of setup operation between any two board groups is characterized as carryover sequence-dependent setup time, which exactly matches with the real application of this problem. As a technical constraint, all of the boards must be kitted before the assembly operation starts (kitting operation) and by kitting staff. The main idea developed in this paper is to completely eliminate the role of kitting staff by assigning the task of kitting to the machine operator during the time he is idle which is referred to as integration of internal (machine) and external (kitting) setup times. Performing the kitting operation, which is a preparation process of the next set of boards while the other boards are currently being assembled, results in the boards to continuously enter the system or have dynamic arrival times. Consequently, a dynamic PCB assembly system is introduced for the first time in the assembly of PCBs, which also has characteristics similar to that of just-in-time manufacturing. The problem investigated is computationally very complex, meaning that finding the optimal solutions especially when the problem size gets larger is impossible. Thus, a heuristic based on Genetic Algorithm (GA) is employed. An example problem on the application of the GA developed is demonstrated and also numerical results of applying the GA on solving several instances are provided.

Keywords: Genetic algorithm, Dynamic PCB assembly, Carryover sequence-dependent setup times, Multi-objective.

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Authors: Chunguang Wang, Krishna Shankar, Evgeny V. Morozov

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The use of composite materials in offshore engineering for deep sea oil production riser systems has drawn considerable interest due to the potential weight savings and improvement in durability. The design of composite risers consists of two stages: (1) local design based on critical local load cases, and (2) global analysis of the full length composite riser under global loads and assessment of critical locations. In the first stage, eight different material combinations were selected and their laminate configurations optimised under local load considerations. Stage two includes a final local stress analysis of the critical sections of the riser under the combined loads determined in the global analysis. This paper describes two design methodologies of the composite riser to provide minimum structural weight and shows that the use of off angle fibre orientations in addition to axial and hoop reinforcements offer substantial weight savings and ensure the structural capacity.

Keywords: Composite Riser, Composite Tubular, Finite Element Modelling, Global Design, Local Design, Offshore Engineering.

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Authors: P. Sawatnatee, S. Udomsuk, K-N. Areerak, K-L. Areerak, A. Srikaew

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The paper presents how to design the indirect vector control of three-phase induction motor drive systems using the artificial intelligence technique called the adaptive tabu search. The results from the simulation and the experiment show that the drive system with the controller designed from the proposed method can provide the best output speed response compared with those of the conventional method. The controller design using the proposed technique can be used to create the software package for engineers to achieve the optimal controller design of the induction motor speed control based on the indirect vector concept.

 

Keywords: Indirect Vector Control, Induction Motor, Adaptive Tabu Search, Control Design, Artificial Intelligence.

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Authors: Bruce K. Ferguson

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The design requirements for successful human accommodation in urban spaces are well known; and the range of facilities available for meeting urban water quality and quantity requirements is also well established. Their competing requirements must be reconciled in order for urban spaces to be successful for both. This paper outlines the separate human and water imperatives and their interactions in urban spaces. Stormwater management facilities- relative potential contributions to urban spaces are contrasted, and design choices for achieving those potentials are described. This study uses human success of urban space as the evaluative criterion of stormwater amenity: human values call on stormwater facilities to contribute to successful human spaces. Placing water-s contribution under the overall idea of successful urban space is an evolution from previous subjective evaluations. The information is based on photographs and notes from approximately 1,000 stormwater facilities and urban sites collected during the last 35 years in North America and overseas, and the author-s experience on multi-disciplinary design teams. This conceptual study combines the disciplinary roles of engineering, landscape architecture, and sociology in effecting successful urban design.

Keywords: Stormwater, SUDS, Urban design, Values, Urban space.

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Authors: Orestis Κ. Efthymiou, Stavros T. Ponis

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In the last decade, a new industrial revolution seems to be emerging, supported -once again- by the rapid advancements of Information Technology in the areas of Machine-to-Machine (M2M) communication permitting large numbers of intelligent devices, e.g. sensors to communicate with each other and take decisions without any or minimum indirect human intervention. The advent of these technologies have triggered the emergence of a new category of hybrid (cyber-physical) manufacturing systems, combining advanced manufacturing techniques with innovative M2M applications based on the Internet of Things (IoT), under the umbrella term Industry 4.0. Even though the topic of Industry 4.0 has attracted much attention during the last few years, the attempts of providing a systematic literature review of the subject are scarce. In this paper, we present the authors’ initial study of the field with a special focus on the use and applications of Industry 4.0 principles in material handling automations and in-house logistics. Research shows that despite the vivid discussion and attractiveness of the subject, there are still many challenges and issues that have to be addressed before Industry 4.0 becomes standardized and widely applicable.

Keywords: Industry 4.0, internet of things, manufacturing systems, material handling, logistics.

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Authors: Chi Jung Kim, Mincheol Whang, Eui Chul Lee

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In this paper, we propose a new method to distinguish between arousal and relaxation states by using multiple features acquired from a photoplethysmogram (PPG) and support vector machine (SVM). To induce arousal and relaxation states in subjects, 2 kinds of sound stimuli are used, and their corresponding biosignals are obtained using the PPG sensor. Two features–pulse to pulse interval (PPI) and pulse amplitude (PA)–are extracted from acquired PPG data, and a nonlinear classification between arousal and relaxation is performed using SVM. This methodology has several advantages when compared with previous similar studies. Firstly, we extracted 2 separate features from PPG, i.e., PPI and PA. Secondly, in order to improve the classification accuracy, SVM-based nonlinear classification was performed. Thirdly, to solve classification problems caused by generalized features of whole subjects, we defined each threshold according to individual features. Experimental results showed that the average classification accuracy was 74.67%. Also, the proposed method showed the better identification performance than the single feature based methods. From this result, we confirmed that arousal and relaxation can be classified using SVM and PPG features.

Keywords: Support Vector Machine, PPG, Emotion Recognition, Arousal, Relaxation

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Authors: Abeer Aljohani

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The COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred as corona virus which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as Omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. Numerous COVID-19 cases have produced a huge burden on hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease based on the symptoms and medical history of the patient. As machine learning is a widely accepted area and gives promising results for healthcare, this research presents an architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard University of California Irvine (UCI) dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques on the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and Principal Component Analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, Receiver Operating Characteristic (ROC) and Area under Curve (AUC). The results depict that Decision tree, Random Forest and neural networks outperform all other state-of-the-art ML techniques. This result can be used to effectively identify COVID-19 infection cases.

Keywords: Supervised machine learning, COVID-19 prediction, healthcare analytics, Random Forest, Neural Network.

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Authors: Mohamed A. Azab

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Over the early years of the 21st century, cities throughout the Middle East, particularly in the Gulf region have expanded more rapidly than ever before. Given the presence of a large volume of high-rise buildings allover the region, the local authority aims to set a new standard for sustainable development; with an integrated approach to maintain a balance between economy, quality, environmental protection and safety of life. In the very near future, as mandatory requirements, sustainability will be the criteria that should be included in all building projects. It is well known in the building sustainability topics that structural design engineers do not have a key role in this matter. In addition, the LEED (Leadership in Energy and Environmental Design) has looked almost exclusively on the environmental components and materials specifications. The objective of this paper is to focus and establish groundwork for sustainability techniques and applications related to the RC high-rise buildings design, from the structural point of view. A set of recommendations related to local conditions, structural modeling and analysis is given, and some helpful suggestions for structural design team work are addressed. This paper attempts to help structural engineers in identifying the building sustainability design, in order to meet local needs and achieve alternative solutions at an early stage of project design.

Keywords: Building, Design, High-rise, Middle East, Structural, Sustainability.

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Authors: Hadia Abdel Aziz, Raghda El Ebrashi

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Business models are shaped by their design space or the environment they are designed to be implemented in. The rapidly changing economic, technological, political, regulatory and market external environment severely affects business logic. This is particularly true for social enterprises whose core mission is to transform their environments, and thus, their whole business logic revolves around the interchange between the enterprise and the environment. The context in which social business operates imposes different business design constraints while at the same time, open up new design opportunities. It is also affected to a great extent by the impact that successful enterprises generate; a continuous loop of interaction that needs to be managed through a dynamic capability in order to generate a lasting powerful impact. This conceptual research synthesizes and analyzes literature on social enterprise, social enterprise business models, business model innovation, business model design, and the open system view theory to propose a new business model design process for social enterprises that takes into account the critical role of environmental factors. This process would help the social enterprise develop a dynamic capability that ensures the alignment of its business model to its environmental context, thus, maximizing its probability of success.

Keywords: Social enterprise, business model, business model design.

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Authors: Pimploi Tirastittam, Suppara Charoenpoom

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Nowadays the asynchronous learning has granted the permission to the anywhere and anything learning via the technology and E-media which give the learner more convenient. This research is about the design of the blended and online learning for the asynchronous learning of the process management subject in order to create the prototype of this subject asynchronous learning which will create the easiness and increase capability in the learning. The pattern of learning is the integration between the in-class learning and online learning via the internet. This research is mainly focused on the online learning and the online learning can be divided into 5 parts which are virtual classroom, online content, collaboration, assessment and reference material. After the system design was finished, it was evaluated and tested by 5 experts in blended learning design and 10 students which the user’s satisfaction level is good. The result is as good as the assumption so the system can be used in the process management subject for a real usage.

Keywords: Blended Learning, Asynchronous Learning, Design, Process Management.

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Authors: Ahmed N. Shmroukh, Ahmed Hamza H. Ali, Ali K. Abel-Rahman

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Adsorption refrigeration working pair is a vital and is the main component in the adsorption refrigeration machine. Therefore the development key is laying on the adsorption pair that leads to the improvement of the adsorption refrigeration machine. In this study the state-of-the-art in the application of the adsorption refrigeration working pairs in both classical and modern adsorption pairs are presented, compared and summarized. It is found that the maximum adsorption capacity for the classical working pairs was 0.259kg/kg for activated carbon/methanol and that for the modern working pairs was 2kg/kg for maxsorb III/R-134a. The study concluded that, the performances of the adsorption working pairs of adsorption cooling systems are still need further investigations as well as developing adsorption pairs having higher sorption capacity with low or no impact on environmental, to build compact, efficient, reliable and long life performance adsorption chillier. Also, future researches need to be focused on designing the adsorption system that provide efficient heating and cooling for the adsorbent materials through distributing the adsorbent material over heat exchanger surface, to allow good heat and mass transfer between the adsorbent and the refrigerant.

Keywords: Adsorption, Adsorbent/Adsorbate Pairs, Refrigeration.

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Authors: Dimitrie Marinceu

Abstract:

The newest Canadian Used Fuel Container (UFC)- (called also “Mark II”) modifies the design approach for its Assembly Robotic Cell (ARC) in the Canadian Used (Nuclear) Fuel Packing Plant (UFPP). Some of the robotic design solutions are presented in this paper. The design indicates that robots and manipulators are expected to be used in the Canadian UFPP. As normally, the UFPP design will incorporate redundancy of all equipment to allow expedient recovery from any postulated upset conditions. Overall, this paper suggests that robot usage will have a significant positive impact on nuclear safety, quality, productivity, and reliability.

Keywords: Used fuel packing plant, robotic assembly cell, used fuel container, deep geological repository.

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Authors: Ratima Damkham, Natasha Dejdumrong, Priyakorn Pusawiro

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This paper explored the solution in game design to help game designers in the educational game designing using digital educational game model canvas (DEGMC) and digital educational game form (DEGF) based on Outcome-based Education program. DEGMC and DEGF can help designers develop an overview of the game while designing and planning their own game. The way to clearly assess players’ ability from learning outcomes and support their game learning design is by using the tools. Designers can balance educational content and entertainment in designing a game by using the strategies of the Business Model Canvas and design the gameplay and players’ ability assessment from learning outcomes they need by referring to the Constructive Alignment. Furthermore, they can use their design plan in this research to write their Game Design Document (GDD). The success of the research was evaluated by four experts’ perspectives in the education and computer field. From the experiments, the canvas and form helped the game designers model their game according to the learning outcomes and analysis of their own game elements. This method can be a path to research an educational game design in the future.

Keywords: Constructive alignment, constructivist theory, educational game, outcome-based education.

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Authors: K. Sakthivel, R. Nallusamy, C. Kavitha

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The goal of image segmentation is to cluster pixels into salient image regions. Segmentation could be used for object recognition, occlusion boundary estimation within motion or stereo systems, image compression, image editing, or image database lookup. In this paper, we present a color image segmentation using support vector machine (SVM) pixel classification. Firstly, the pixel level color and texture features of the image are extracted and they are used as input to the SVM classifier. These features are extracted using the homogeneity model and Gabor Filter. With the extracted pixel level features, the SVM Classifier is trained by using FCM (Fuzzy C-Means).The image segmentation takes the advantage of both the pixel level information of the image and also the ability of the SVM Classifier. The Experiments show that the proposed method has a very good segmentation result and a better efficiency, increases the quality of the image segmentation compared with the other segmentation methods proposed in the literature.

Keywords: Image Segmentation, Support Vector Machine, Fuzzy C–Means, Pixel Feature, Texture Feature, Homogeneity model, Gabor Filter.

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Authors: Mahsa Karimpour, Martin Belusko, Ke Xing, Frank Bruno

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Traditionally, the embodied energy of design choices which reduce operational energy were assumed to have a negligible impact on the life cycle energy of buildings. However with new buildings having considerably lower operational energy, the significance of embodied energy increases. A life cycle assessment of a population of house designs was conducted in a mild and mixed climate zone. It was determined not only that embodied energy dominates life cycle energy, but that the impact on embodied of design choices was of equal significance to the impact on operational energy.

Keywords: Building life cycle energy, embodied energy, energy design measures, low energy buildings.

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Authors: Shuen-Tai Wang, Yu-Ching Lin, Hsi-Ya Chang

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Virtualization technologies are experiencing a renewed interest as a way to improve system reliability, and availability, reduce costs, and provide flexibility. This paper presents the development on leverage existing cloud infrastructure and virtualization tools. We adopted some virtualization technologies which improve portability, manageability and compatibility of applications by encapsulating them from the underlying operating system on which they are executed. Given the development of application virtualization, it allows shifting the user’s applications from the traditional PC environment to the virtualized environment, which is stored on a remote virtual machine rather than locally. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. Users no longer need to burden the platform maintenances and drastically reduces the overall cost of hardware and software licenses. Moreover, this flexible and web-based application virtualization service represents the next significant step to the mobile workplace, and it lets user executes their applications from virtually anywhere. 

Keywords: Cloud service, application virtualization, virtual machine, elastic environment.

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Authors: N. Mahendran, S. Vishwaja

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The Carry Select Adder (CSLA) is a fast adder which improves the speed of addition. From the structure of the CSLA, it is clear that there is opportunity for reducing the area. The logic operations involved in conventional CSLA and binary to excess-1 converter (BEC) based CSLA are analyzed to make a study on the data dependence and to identify redundant logic operations. In the existing adder design, the carry select (CS) operation is scheduled before the final-sum, which is different from the conventional CSLA design. In the presented scheme, Kogge stone parallel adder approach is used instead of existing adder design it will generate fast carry for intermediate stages and also improves the speed of addition. When compared to existing adder design the delay is less in the proposed adder design.

Keywords: Binary to excess-1 converter, delay, carry select adder, Kogge stone adder, speed.

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