Search results for: learning process

Authors: Daniel Siahaan, Aditya Prapanca

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The emerging Semantic Web has been attracted many researchers and developers. New applications have been developed on top of Semantic Web and many supporting tools introduced to improve its software development process. Metadata modeling is one of development process where supporting tools exists. The existing tools are lack of readability and easiness for a domain knowledge expert to graphically models a problem in semantic model. In this paper, a metadata modeling tool called RDFGraph is proposed. This tool is meant to solve those problems. RDFGraph is also designed to work with modern database management systems that support RDF and to improve the performance of the query execution process. The testing result shows that the rules used in RDFGraph follows the W3C standard and the graphical model produced in this tool is properly translated and correct.

Keywords: CASE tool, data modeling, semantic web

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Authors: Samir A. Emam, Ali El Domiaty

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Friction-stir welding has received a huge interest in the last few years. The many advantages of this promising process have led researchers to present different theoretical and experimental explanation of the process. The way to quantitatively and qualitatively control the different parameters of the friction-stir welding process has not been paved. In this study, a refined energybased model that estimates the energy generated due to friction and plastic deformation is presented. The effect of the plastic deformation at low energy levels is significant and hence a scale factor is introduced to control its effect. The predicted heat energy and the obtained maximum temperature using our model are compared to the theoretical and experimental results available in the literature and a good agreement is obtained. The model is applied to AA6000 and AA7000 series.

Keywords: Friction-stir welding, Energy, Aluminum Alloys.

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Authors: Manirath Wongsim, Pawornprat Hongsakon

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Information Quality (IQ) has become a critical, strategic issue in Accounting Information Systems (AIS) adoption. In order to implement AIS adoption successfully, it is important to consider the quality of information use throughout the adoption process, which seriously impacts the effectiveness of AIS adoption practice and the optimisation of AIS adoption decisions. There is a growing need for research to provide insights into issues and solutions related to IQ in AIS adoption. The need for an integrated approach to improve IQ in AIS adoption, as well as the unique characteristics of accounting data, demands an AIS adoption specific IQ framework. This research aims to explore ways of managing information quality and AIS adoption to investigate the relationship between the IQ issues and AIS adoption process. This study has led to the development of a framework for understanding IQ management in AIS adoption. This research was done on 44 respondents as ten organisations from manufacturing firms in Thailand. The findings of the research’s empirical evidence suggest that IQ dimensions in AIS adoption to provide assistance in all process of decision making. This research provides empirical evidence that information quality of AIS adoption affect decision making and suggests that these variables should be considered in adopting AIS in order to improve the effectiveness of AIS.

Keywords: Information quality, information quality dimensions, accounting information systems, accounting Information system adoption.

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Authors: Ora Geiger

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

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

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Authors: Geir Sigurðsson

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This paper compares ancient Daoist and Confucian approaches to the human body as a locus for learning, edification or personal cultivation. While pointing out some major differences between ancient Chinese and mainstream Western visions of the body, it seeks at the same time inspiration in some seminal Western phenomenological and post-structuralist writings, in particular from Maurice Merleau-Ponty and Pierre Bourdieu. By clarifying the somewhat dissimilar scopes of foci found in Daoist and Confucian philosophies with regard to the role of and attitude to the body, the conclusion is nevertheless that their approaches are comparable, and that both traditions take the physical body to play a vital role in the cultivation of excellence. Lastly, it will be argued that cosmological underpinnings prevent the Confucian li from being rigid and invariable and that it rather emerges as a flexible learning device to train through active embodiment a refined sensibility for one’s cultural environment.

Keywords: Body, Confucianism, Daoism, li, phenomenology, ritual.

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Authors: Liang Wang, Wei Zhang

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Nowadays sustainable development has increasingly become an important research topic of engineering education all over the world. Engineering Education for Sustainable Development (EESD) highlighted the importance of addressing sustainable development in engineering practice. However, whether and how the professional engineering learning and experience affect those perceptions is an interesting research topic especially in Chinese context. Our study fills this gap by investigating perceptions bias of EESD among first-grade engineering students, fourth-grade engineering students and experienced engineers using a triple-dimensional model. Our goal is to find the effect of engineering learning and experience on sustainable development and make these learning and experiences more accessible for students and engineers in school and workplace context. The data (n = 138) came from a Likert questionnaire based on the triple-dimensional model of EESD adopted from literature reviews and the data contain 48 first-grade students, 56 fourth-grade students and 34 engineers with rich working experience from Environmental Engineering, Energy Engineering, Chemical Engineering and Civil Engineering in or graduated from Zhejiang University, China. One-way ANOVA analysis was used to find the difference in different dimensions among the three groups. The statistical results show that both engineering students and engineers have a well understanding of sustainable development in ecology dimension of EESD while there are significant differences among three groups as to the socio-economy and value rationality dimensions of EESD. The findings provide empirical evidence that both engineering learning and professional engineering experience are helpful to cultivate the cognition and perception of sustainable development in engineering education. The results of this work indicate that more practical content should be added to students’ engineering education while more theoretical content should be added to engineers’ training in order to promote the engineering students’ and engineers’ perceptions of sustainable development. In addition, as to the design of engineering courses and professional practice system for sustainable development, we should not only pay attention to the ecological aspects, but also emphasize the coordination of ecological, socio-economic and human-centered sustainable development (e.g., engineer's ethical responsibility).

Keywords: Engineering education, sustainable development, experienced engineers, engineering students.

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Authors: N. Areerachakul

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The surface water used in this study was collected from the Chao Praya River at the lower part at the Nonthaburi bridge. It was collected and used throughout the experiment. TOC (also known as DOC) in the range between 2.5 to 5.6 mg/l were investigated in this experiment. The use of conventional treatment methods such as FeCl3 and PAC showed that TOC removal was 65% using FeCl3 and 78% using PAC (powder activated carbon). The advanced oxidation process alone showed only 35% removal of TOC. Coupling advanced oxidation with a small amount of PAC (0.05g/L) increased efficiency by upto 55%. The combined BAC with advanced oxidation process and small amount of PAC demonstrated the highest efficiency of up to 95% of TOC removal and lower sludge production compared with other methods.

Keywords: Advanced oxidation process, TOC, PAC

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Authors: Roberto Boselli, Mirko Cesarini, Mario Mezzanzanica

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The paper is concerned with relationships between SSME and ICTs and focuses on the role of Web 2.0 tools in the service development process. The research presented aims at exploring how collaborative technologies can support and improve service processes, highlighting customer centrality and value coproduction. The core idea of the paper is the centrality of user participation and the collaborative technologies as enabling factors; Wikipedia is analyzed as an example. The result of such analysis is the identification and description of a pattern characterising specific services in which users collaborate by means of web tools with value co-producers during the service process. The pattern of collaborative co-production concerning several categories of services including knowledge based services is then discussed.

Keywords: Service Interaction Patterns, Services Science, Web2.0 tools, Service Development Process.

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Authors: Zina Benouaret, Djamil Aissani

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In this work, we introduce the qualitative and quantitative concept of the strong stability method in the risk process modeling two lines of business of the same insurance company or an insurance and re-insurance companies that divide between them both claims and premiums with a certain proportion. The approach proposed is based on the identification of the ruin probability associate to the model considered, with a stationary distribution of a Markov random process called a reversed process. Our objective, after clarifying the condition and the perturbation domain of parameters, is to obtain the stability inequality of the ruin probability which is applied to estimate the approximation error of a model with disturbance parameters by the considered model. In the stability bound obtained, all constants are explicitly written.

Keywords: Markov chain, risk models, ruin probabilities, strong stability analysis.

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Authors: Helen Zhang

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Accurate segmentation of the airways from CT scans is crucial for early diagnosis of lung cancer. However, the existing airway segmentation algorithms often rely on thin-slice CT scans, which can be inconvenient and costly. This paper presents a set of machine learning-based 3D super-resolution algorithms along heterogenous dimensions to improve the resolution of thicker CT scans to reduce the reliance on thin-slice scans. To evaluate the efficacy of the super-resolution algorithms, quantitative assessments using PSNR (Peak Signal to Noise Ratio) and SSIM (Structural SIMilarity index) were performed. The impact of super-resolution on airway segmentation accuracy is also studied. The proposed approach has the potential to make airway segmentation more accessible and affordable, thereby facilitating early diagnosis and treatment of lung cancer.

Keywords: 3D super-resolution, airway segmentation, thin-slice CT scans, machine learning.

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Authors: Abdelrahman A. Ramzy, Bassel S. Abdallah, Mohamed E. Bahgat, Sarah M. Abdelkader, Sherif H. ElGohary

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Attention-Deficit/Hyperactivity Disorder (ADHD), epilepsy, and autism affect millions of children worldwide, many of which are undiagnosed despite the fact that all of these disorders are detectable in early childhood. Late diagnosis can cause severe problems due to the late treatment and to the misconceptions and lack of awareness as a whole towards these disorders. Moreover, electroencephalography (EEG) has played a vital role in the assessment of neural function in children. Therefore, quantitative EEG measurement will be utilized as a tool for use in the evaluation of patients who may have ADHD, epilepsy, and autism. We propose a screening tool that uses EEG signals and machine learning algorithms to detect these disorders at an early age in an automated manner. The proposed classifiers used with epilepsy as a step taken for the work done so far, provided an accuracy of approximately 97% using SVM, Naïve Bayes and Decision tree, while 98% using KNN, which gives hope for the work yet to be conducted.

Keywords: ADHD, autism, epilepsy, EEG, SVM.

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Authors: W. Zekri

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This paper explores Zohra Drif’s memoir, Inside the Battle of Algiers, which narrates her desires as a student to become a revolutionary activist. She exemplified, in her narrative, the different roles, she and her fellows performed as combatants in the Casbah during the Algerian Revolution 1954-1962. This book review aims to evaluate the concept of women’s agency through education and language learning, and its impact on empowering women’s desires. Close-reading method and thematic analysis are used to explore the text. The analysis identified themes that refine the meaning of agency which are social and cultural supports, education, and language proficiency. These themes aim to contribute to the representation in Inside the Battle of Algiers of a woman guerrilla who engaged herself to perform national acts of resistance.

Keywords: Agency, education, learning, women.

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Authors: Meriem Bahij, Ahmed Nafidi, Boujemâa Achchab, Sílvio M. A. Gama, José A. O. Matos

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Stochastic modeling concerns the use of probability to model real-world situations in which uncertainty is present. Therefore, the purpose of stochastic modeling is to estimate the probability of outcomes within a forecast, i.e. to be able to predict what conditions or decisions might happen under different situations. In the present study, we present a model of a stochastic diffusion process based on the bi-Weibull distribution function (its trend is proportional to the bi-Weibull probability density function). In general, the Weibull distribution has the ability to assume the characteristics of many different types of distributions. This has made it very popular among engineers and quality practitioners, who have considered it the most commonly used distribution for studying problems such as modeling reliability data, accelerated life testing, and maintainability modeling and analysis. In this work, we start by obtaining the probabilistic characteristics of this model, as the explicit expression of the process, its trends, and its distribution by transforming the diffusion process in a Wiener process as shown in the Ricciaardi theorem. Then, we develop the statistical inference of this model using the maximum likelihood methodology. Finally, we analyse with simulated data the computational problems associated with the parameters, an issue of great importance in its application to real data with the use of the convergence analysis methods. Overall, the use of a stochastic model reflects only a pragmatic decision on the part of the modeler. According to the data that is available and the universe of models known to the modeler, this model represents the best currently available description of the phenomenon under consideration.

Keywords: Diffusion process, discrete sampling, likelihood estimation method, simulation, stochastic diffusion equation, trends functions, bi-parameters Weibull density function.

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Authors: Watcharawalee Lertlum, Borworn Papasratorn

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Previous researches found that conventional WBL is effective for meaningful learner, because rote learner learn by repeating without thinking or trying to understand. It is impossible to have full benefit from conventional WBL. Understanding of rote learner-s intention and what influences it becomes important. Poorly designed user interface will discourage rote learner-s cultivation and intention to use WBL. Thus, user interface design is an important factor especially when WBL is used as comprehensive replacement of conventional teaching. This research proposes the influencing factors that can enhance learner-s intention to use the system. The enhanced TAM is used for evaluating the proposed factors. The research result points out that factors influencing rote learner-s intention are Perceived Usefulness of Homepage Content Structure, Perceived User Friendly Interface, Perceived Hedonic Component, and Perceived (homepage) Visual Attractiveness.

Keywords: Web-Based learning, Electronic learning, Intentionto use, Rote learner, Influencing

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Authors: Pushpendra S. Bharti, S. Maheshwari

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Electric discharge machining (EDM) is one of the most widely used non-conventional manufacturing process to shape difficult-to-cut materials. The process yield, in terms of material removal rate, surface roughness and tool wear rate, of EDM may considerably be improved by selecting the optimal combination(s) of process parameters. This paper employs Multi-response signal-to-noise (MRSN) ratio technique to find the optimal combination(s) of the process parameters during EDM of Inconel 718. Three cases v.i.z. high cutting efficiency, high surface finish, and normal machining have been taken and the optimal combinations of input parameters have been obtained for each case. Analysis of variance (ANOVA) has been employed to find the dominant parameter(s) in all three cases. The experimental verification of the obtained results has also been made. MRSN ratio technique found to be a simple and effective multi-objective optimization technique.

Keywords: EDM, material removal rate, multi-response signal-to-noise ratio, optimization, surface roughness.

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Authors: Hassan Haghighi, Sajad Ghorbani, Maryam Mohebati, Mohammad Mahdi Javanmard

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One of the most important aspects expected from ERP systems is to integrate various operations existing in administrative, financial, commercial, human resources, and production departments of the consumer organization. Also, it is often needed to integrate the new ERP system with the organization legacy systems when implementing the ERP package in the organization. Without relying on an appropriate software architecture to realize the required integration, ERP implementation processes become error prone and time consuming; in some cases, the ERP implementation may even encounters serious risks. In this paper, we propose a new architecture that is based on the agent oriented vision and supplies the integration expected from ERP systems using several independent but cooperator agents. Besides integration which is the main issue of this paper, the presented architecture will address some aspects of intelligence and learning capabilities existing in ERP systems

Keywords: enterprise resource planning, software architecture, agent oriented architecture, integration, intelligence, learning.

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Authors: Roberto Iglesias, Theocharis Kyriacou, Ulrich Nehmzow, Steve Billings

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Fundamental sensor-motor couplings form the backbone of most mobile robot control tasks, and often need to be implemented fast, efficiently and nevertheless reliably. Machine learning techniques are therefore often used to obtain the desired sensor-motor competences. In this paper we present an alternative to established machine learning methods such as artificial neural networks, that is very fast, easy to implement, and has the distinct advantage that it generates transparent, analysable sensor-motor couplings: system identification through nonlinear polynomial mapping. This work, which is part of the RobotMODIC project at the universities of Essex and Sheffield, aims to develop a theoretical understanding of the interaction between the robot and its environment. One of the purposes of this research is to enable the principled design of robot control programs. As a first step towards this aim we model the behaviour of the robot, as this emerges from its interaction with the environment, with the NARMAX modelling method (Nonlinear, Auto-Regressive, Moving Average models with eXogenous inputs). This method produces explicit polynomial functions that can be subsequently analysed using established mathematical methods. In this paper we demonstrate the fidelity of the obtained NARMAX models in the challenging task of robot route learning; we present a set of experiments in which a Magellan Pro mobile robot was taught to follow four different routes, always using the same mechanism to obtain the required control law.

Keywords: Mobile robotics, system identification, non-linear modelling, NARMAX.

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Authors: Halil Ibrahim Demir, Abdullah Hulusi Kokcam, Fuat Simsir, Özer Uygun

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Traditionally, three important manufacturing functions which are process planning, scheduling and due-date assignment are performed sequentially and separately. Although there are numerous works on the integration of process planning and scheduling and plenty of works focusing on scheduling with due date assignment, there are only a few works on integrated process planning, scheduling and due-date assignment. Although due-dates are determined without taking into account of weights of the customers in the literature, here weighted due-date assignment is employed to get better performance. Jobs are scheduled according to weighted earliest due date dispatching rule and due dates are determined according to some popular due date assignment methods by taking into account of the weights of each job. Simulated Annealing, Evolutionary Strategies, Random Search, hybrid of Random Search and Simulated Annealing, and hybrid of Random Search and Evolutionary Strategies, are applied as solution techniques. Three important manufacturing functions are integrated step-by-step and higher integration levels are found better. Search meta-heuristics are found to be very useful while improving performance measure.

Keywords: Evolutionary strategies, hybrid searches, process planning, simulated annealing, weighted due-date assignment, weighted scheduling.

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Authors: V. Prasannavenkadesan, A. Elango, S. Chockalingam

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During machining process, chatter is an unavoidable phenomenon. Boring bars possess the cantilever shape and due to this, it is subjected to chatter. The adverse effect of chatter includes the increase in temperature which will leads to excess tool wear. To overcome these problems, in this investigation, Cartridge brass (Cu – 70% and Zn – 30%) is passively fixed on the boring bar and also clearance is provided in order to reduce the displacement, tool wear and cutting temperature. A conventional all geared lathe is attached with vibrometer and pyrometer is used to measure the displacement and temperature. The influence of input parameters such as cutting speed, depth of cut and clearance on temperature, tool wear and displacement are investigated for various cutting conditions. From the result, the optimum conditions to obtain better damping in boring process for chatter reduction is identified.

Keywords: Boring, chatter, mass damping, passive damping.

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Authors: George Yungchih Wang

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Real options theory suggests that managerial flexibility embedded within irreversible investments can account for a significant value in project valuation. Although the argument has become the dominant focus of capital investment theory over decades, yet recent survey literature in capital budgeting indicates that corporate practitioners still do not explicitly apply real options in investment decisions. In this paper, we explore how real options decision criteria can be transformed into equivalent capital budgeting criteria under the consideration of uncertainty, assuming that underlying stochastic process follows a geometric Brownian motion (GBM), a mixed diffusion-jump (MX), or a mean-reverting process (MR). These equivalent valuation techniques can be readily decomposed into conventional investment rules and “option impacts", the latter of which describe the impacts on optimal investment rules with the option value considered. Based on numerical analysis and Monte Carlo simulation, three major findings are derived. First, it is shown that real options could be successfully integrated into the mindset of conventional capital budgeting. Second, the inclusion of option impacts tends to delay investment. It is indicated that the delay effect is the most significant under a GBM process and the least significant under a MR process. Third, it is optimal to adopt the new capital budgeting criteria in investment decision-making and adopting a suboptimal investment rule without considering real options could lead to a substantial loss in value.

Keywords: real options, capital budgeting, geometric Brownianmotion, mixed diffusion-jump, mean-reverting process

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Authors: Lavanya Annadi, Fahimeh Jafari

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Transportation brings immense benefits to society, but it also has its costs. Costs include the cost of infrastructure, personnel, and equipment, but also the loss of life and property in traffic accidents on the road, delays in travel due to traffic congestion, and various indirect costs in terms of air transport. This research aims to predict the probabilistic crash prediction of vehicles using Machine Learning due to natural and structural reasons by excluding spontaneous reasons, like overspeeding, etc., in the United States. These factors range from meteorological elements such as weather conditions, precipitation, visibility, wind speed, wind direction, temperature, pressure, and humidity, to human-made structures, like road structure components such as Bumps, Roundabouts, No Exit, Turning Loops, Give Away, etc. The probabilities are categorized into ten distinct classes. All the predictions are based on multiclass classification techniques, which are supervised learning. This study considers all crashes in all states collected by the US government. The probability of the crash was determined by employing Multinomial Expected Value, and a classification label was assigned accordingly. We applied three classification models, including multiclass Logistic Regression, Random Forest and XGBoost. The numerical results show that XGBoost achieved a 75.2% accuracy rate which indicates the part that is being played by natural and structural reasons for the crash. The paper has provided in-depth insights through exploratory data analysis.

Keywords: Road safety, crash prediction, exploratory analysis, machine learning.

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Authors: A. Miss May Thu Zar Myint, B. Dr. Kay Thi Lwin

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This research focuses on the effect of weight percentage variation and size variation of MgFeSi added, gating system design and reaction chamber design on inmold process. By using inmold process, well-known problem of fading is avoided because the liquid iron reacts with magnesium in the mold and not, as usual, in the ladle. During the pouring operation, liquid metal passes through the chamber containing the magnesium, where the reaction of the metal with magnesium proceeds in the absence of atmospheric oxygen [1].In this paper, the results of microstructural characteristic of ductile iron on this parameters are mentioned. The mechanisms of the inmold process are also described [2]. The data obtained from this research will assist in producing the vehicle parts and other machinery parts for different industrial zones and government industries and in transferring the technology to all industrial zones in Myanmar. Therefore, the inmold technology offers many advantages over traditional treatment methods both from a technical and environmental, as well as an economical point of view. The main objective of this research is to produce ductile iron castings in all industrial sectors in Myanmar more easily with lower costs. It will also assist the sharing of knowledge and experience related to the ductile iron production.

Keywords: ductile iron, inmold process, magnesiumtreatment, microstructural characteristics.

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Authors: Inam Shamsher, Zaheer Ahmad, Jehanzeb Khan Orakzai, Awais Adnan

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This paper deals with an Optical Character Recognition system for printed Urdu, a popular Pakistani/Indian script and is the third largest understandable language in the world, especially in the subcontinent but fewer efforts are made to make it understandable to computers. Lot of work has been done in the field of literature and Islamic studies in Urdu, which has to be computerized. In the proposed system individual characters are recognized using our own proposed method/ algorithms. The feature detection methods are simple and robust. Supervised learning is used to train the feed forward neural network. A prototype of the system has been tested on printed Urdu characters and currently achieves 98.3% character level accuracy on average .Although the system is script/ language independent but we have designed it for Urdu characters only.

Keywords: Algorithm, Feed Forward Neural Networks, Supervised learning, Pattern Matching.

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Authors: G. Kehl, P. Wagner

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A novel simulation method to determine the displacements of machine tools due to thermal factors is presented. The specific characteristic of this method is the employment of original CAD data from the design process chain, which is interpreted by an algorithm in terms of geometry-based allocation of convection and radiation parameters. Furthermore analogous models relating to the thermal behaviour of machine elements are automatically implemented, which were gained by extensive experimental testing with thermography imaging. With this a transient simulation of the thermal field and in series of the displacement of the machine tool is possible simultaneously during the design phase. This method was implemented and is already used industrially in the design of machining centres in order to improve the quality of herewith manufactured workpieces.

Keywords: Accuracy, design process, finite element analysis, machine tools, thermal simulation.

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Authors: Insung Jung, Gi-Nam Wang

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In this paper, we present user pattern learning algorithm based MDSS (Medical Decision support system) under ubiquitous. Most of researches are focus on hardware system, hospital management and whole concept of ubiquitous environment even though it is hard to implement. Our objective of this paper is to design a MDSS framework. It helps to patient for medical treatment and prevention of the high risk patient (COPD, heart disease, Diabetes). This framework consist database, CAD (Computer Aided diagnosis support system) and CAP (computer aided user vital sign prediction system). It can be applied to develop user pattern learning algorithm based MDSS for homecare and silver town service. Especially this CAD has wise decision making competency. It compares current vital sign with user-s normal condition pattern data. In addition, the CAP computes user vital sign prediction using past data of the patient. The novel approach is using neural network method, wireless vital sign acquisition devices and personal computer DB system. An intelligent agent based MDSS will help elder people and high risk patients to prevent sudden death and disease, the physician to get the online access to patients- data, the plan of medication service priority (e.g. emergency case).

Keywords: Neural network, U-healthcare, MDSS, CAP, DSS.

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Authors: Noor Asma Husain, Mohd Shafry Mohd Rahim, Abdullah Bade

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Subdivision surfaces were applied to the entire meshes in order to produce smooth surfaces refinement from coarse mesh. Several schemes had been introduced in this area to provide a set of rules to converge smooth surfaces. However, to compute and render all the vertices are really inconvenient in terms of memory consumption and runtime during the subdivision process. It will lead to a heavy computational load especially at a higher level of subdivision. Adaptive subdivision is a method that subdivides only at certain areas of the meshes while the rest were maintained less polygons. Although adaptive subdivision occurs at the selected areas, the quality of produced surfaces which is their smoothness can be preserved similar as well as regular subdivision. Nevertheless, adaptive subdivision process burdened from two causes; calculations need to be done to define areas that are required to be subdivided and to remove cracks created from the subdivision depth difference between the selected and unselected areas. Unfortunately, the result of adaptive subdivision when it reaches to the higher level of subdivision, it still brings the problem with memory consumption. This research brings to iterative process of adaptive subdivision to improve the previous adaptive method that will reduce memory consumption applied on triangular mesh. The result of this iterative process was acceptable better in memory and appearance in order to produce fewer polygons while it preserves smooth surfaces.

Keywords: Subdivision surfaces, adaptive subdivision, selectioncriteria, handle cracks, smooth surface

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Authors: Barenten Suciu

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In this paper, effectiveness of a machine design process is evaluated on the basis of the specific output calculus. Concretely, a screw-worm gear mechanical transmission is designed by using the classical and the 3D-CAD methods. Strength analysis and drawing of the designed parts is substantially aided by employing the SolidWorks software. Quality of the design process is assessed by manufacturing (printing) the parts, and by computing the efficiency, specific load, as well as the specific output (work) of the mechanical transmission. Influence of the stroke, travelling velocity and load on the mechanical output, is emphasized. Optimal design of the mechanical transmission becomes possible by the appropriate usage of the acquired results.

Keywords: Mechanical transmission, design, screw, worm-gear, efficiency, specific output, 3D-printing.

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Authors: Boon Yih Mah

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Web-based Cognitive Writing Instruction (WeCWI) is a hybrid e-framework for the development of a web-based instruction (WBI), which contributes towards instructional design and language development. WeCWI divides its contribution in instructional design into macro and micro perspectives. In macro perspective, being a 21st century educator by disseminating knowledge and sharing ideas with the in-class and global learners is initiated. By leveraging the virtue of technology, WeCWI aims to transform an educator into an aggregator, curator, publisher, social networker and ultimately, a web-based instructor. Since the most notable contribution of integrating technology is being a tool of teaching as well as a stimulus for learning, WeCWI focuses on the use of contemporary web tools based on the multiple roles played by the 21st century educator. The micro perspective in instructional design draws attention to the pedagogical approaches focusing on three main aspects: reading, discussion, and writing. With the effective use of pedagogical approaches through free reading and enterprises, technology adds new dimensions and expands the boundaries of learning capacity. Lastly, WeCWI also imparts the fundamental theories and models for web-based instructors’ awareness such as interactionist theory, cognitive information processing (CIP) theory, computer-mediated communication (CMC), e-learning interactionalbased model, inquiry models, sensory mind model, and leaning styles model.

Keywords: WeCWI, instructional discovery, technological discovery, pedagogical discovery, theoretical discovery.

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Authors: F. Salehuddin, I. Ahmad, F. A. Hamid, A. Zaharim, H. A. Elgomati, B. Y. Majlis, P. R. Apte

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In this study, the Taguchi method was used to optimize the effect of HALO structure or halo implant variations on threshold voltage (VTH) and leakage current (ILeak) in 45nm p-type Metal Oxide Semiconductor Field Effect Transistors (MOSFETs) device. Besides halo implant dose, the other process parameters which used were Source/Drain (S/D) implant dose, oxide growth temperature and silicide anneal temperature. This work was done using TCAD simulator, consisting of a process simulator, ATHENA and device simulator, ATLAS. These two simulators were combined with Taguchi method to aid in design and optimize the process parameters. In this research, the most effective process parameters with respect to VTH and ILeak are halo implant dose (40%) and S/D implant dose (52%) respectively. Whereas the second ranking factor affecting VTH and ILeak are oxide growth temperature (32%) and halo implant dose (34%) respectively. The results show that after optimizations approaches is -0.157V at ILeak=0.195mA/μm.

Keywords: Optimization, p-type MOSFETs device, HALO Structure, Taguchi Method.

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Authors: A. Kampker, K. Kreisköther, C. Reinders

Abstract:

Since additive manufacturing technologies constantly advance, the use of this technology in mold making seems reasonable. Many manufacturers of additive manufacturing machines, however, do not offer any suggestions on how to parameterize the machine to achieve optimal results for mold making. The purpose of this research is to determine the interdependencies of different materials and parameters within the PolyJet process by using design of experiments (DoE), to additively manufacture molds, e.g. for thermoforming and injection molding applications. Therefore, the general requirements of thermoforming molds, such as heat resistance, surface quality and hardness, have been identified. Then, different materials and parameters of the PolyJet process, such as the orientation of the printed part, the layer thickness, the printing mode (matte or glossy), the distance between printed parts and the scaling of parts, have been examined. The multifactorial analysis covers the following properties of the printed samples: Tensile strength, tensile modulus, bending strength, elongation at break, surface quality, heat deflection temperature and surface hardness. The key objective of this research is that by joining the results from the DoE with the requirements of the mold making, optimal and tailored molds can be additively manufactured with the PolyJet process. These additively manufactured molds can then be used in prototyping processes, in process testing and in small to medium batch production.

Keywords: Additive manufacturing, design of experiments, mold making, PolyJet.

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