Search results for: online learning environment.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4890

Search results for: online learning environment.

3240 A Simple Qos Scheduler for Mobile Wimax

Authors: Komala Kalyanam, Pushpam Indumathi

Abstract:

WiMAX is defined as Worldwide Interoperability for Microwave Access by the WiMAX Forum, formed in June 2001 to promote conformance and interoperability of the IEEE 802.16 standard, officially known as WirelessMAN. The attractive features of WiMAX technology are very high throughput and Broadband Wireless Access over a long distance. A detailed simulation environment is demonstrated with the UGS, nrtPS and ertPS service classes for throughput, delay and packet delivery ratio for a mixed environment of fixed and mobile WiMAX. A simple mobility aspect is considered for the mobile WiMAX and the PMP mode of transmission is considered in TDD mode. The Network Simulator 2 (NS-2) is the tool which is used to simulate the WiMAX network scenario. A simple Priority Scheduler and Weighted Round Robin Schedulers are the WiMAX schedulers used in the research work

Keywords: ertPS, Mobile WiMAX, scheduler.

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3239 A Study on the Cloud Simulation with a Network Topology Generator

Authors: Jun-Kwon Jung, Sung-Min Jung, Tae-Kyung Kim, Tai-Myoung Chung

Abstract:

CloudSim is a useful tool to simulate the cloud environment. It shows the service availability, the power consumption, and the network traffic of services on the cloud environment. Moreover, it supports to calculate a network communication delay through a network topology data easily. CloudSim allows inputting a file of topology data, but it does not provide any generating process. Thus, it needs the file of topology data generated from some other tools. The BRITE is typical network topology generator. Also, it supports various type of topology generating algorithms. If CloudSim can include the BRITE, network simulation for clouds is easier than existing version. This paper shows the potential of connection between BRITE and CloudSim. Also, it proposes the direction to link between them.

Keywords: Cloud, simulation, topology, BRITE, network.

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3238 Lean Thinking Process in the Determination of Design Suggestions to Optimize Treatment of WEEE

Authors: Anastasia Katsamaki, Nikolaos Bilalis, Vassilis Dedoussis

Abstract:

This work proposes a set of actions to assist redesign procedure in existing products of Electric and Electronic Equipment (EEE). The aim is to improve their environmental behavior after their withdrawal in the End-of-Life (EOL) phase. In the beginning data collection takes place. Then follows selection and implementation of the optimal EOL Treatment Strategy (EOL_TS) and its results- evaluation concerning the environment. In parallel, product design characteristics that can be altered are selected based on their significance for the environment in the EOL stage. All results from the previous stages are combined and possible redesign actions are formulated for further examination and afterwards configuration in the design stage. The applied method to perform these tasks is Lean Thinking (LT). At the end, results concerning the application of the proposed method on a distribution transformer are presented.

Keywords: End-of-life treatment, Lean thinking, WEEE

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3237 Stagnation in Brownfield Redevelopment

Authors: B. Glumac, Q. Han, W. Schaefer

Abstract:

Purpose of this paper is two-folded. At first it explains the major problems that are causing stagnation in brownfield redevelopment. In addition, these problems given the context of the present multi-actor built environment are becoming more complex to observe. Therefore, this paper suggests also a prospective decisionmaking approach that is the most appropriate to observe and react on the given stagnation problems. Such an approach should be regarded as prescriptive-interactive decision-making approach, a barely established branch. This approach should offer models that have prescriptive as well as an interactive component enabling them to successfully cope with the multi-actor environment. Overall, this paper provides up-to-date insight on the brownfield stagnation by gradually introducing the nowadays major problems and offers a prospective decision-making approach how these problems could be tackled.

Keywords: BR, decision-making approach, stagnation, the Netherlands.

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3236 Autonomous Control of a Mobile Manipulator

Authors: Shonal Singh, Bibhya Sharma, Jito Vanualailai

Abstract:

This paper considers the design of a motion planner that will simultaneously accomplish control and motion planning of a n-link nonholonomic mobile manipulator, wherein, a n-link holonomic manipulator is coupled with a nonholonomic mobile platform, within an obstacle-ridden environment. This planner, derived from the Lyapunov-based control scheme, generates collision-free trajectories from an initial configuration to a final configuration in a constrained environment cluttered with stationary solid objects of different shapes and sizes. We demonstrate the efficiency of the control scheme and the resulting acceleration controllers of the mobile manipulator with results through computer simulations of an interesting scenario.

Keywords: Artificial potential fields, Lyapunov-based control scheme, Lyapunov stability, nonholonomic manipulator, minimum distance technique, kinodynamic constraints.

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3235 Comparative Evaluation of Accuracy of Selected Machine Learning Classification Techniques for Diagnosis of Cancer: A Data Mining Approach

Authors: Rajvir Kaur, Jeewani Anupama Ginige

Abstract:

With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: Artificial neural networks, breast cancer, cancer dataset, classifiers, cervical cancer, F-score, logistic regression, machine learning, precision, recall, support vector machine.

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3234 The Effect of Molybdate on Corrosion Behaviour of AISI 316Ti Stainless Steel in Chloride Environment

Authors: Viera Zatkalíková, Lenka Markovičová, Aneta Tor-Swiatek

Abstract:

The effect of molybdate addition to chloride environment on resistance of AISI 316Ti stainless steel to pitting corrosion was studied. Potentiodynamic polarisation tests were performed in 1 M and 0.1 M chloride acidified solutions with various additions of sodium molybdate at room temperature. The presented results compare the effect of molybdate anions on quality of passive film (expressed by the pitting potential) in both chloride solutions. The pitting potential increases with the increase inhibitor concentration. The inhibitive effect of molybdate ions is stronger in chloride solution of lower aggressiveness (0.1M).

Keywords: AISI 316Ti steel, molybdate inhibitor, pitting corrosion, pitting potential, potentiodynamic polarization.

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3233 Preliminary Survey on MATLAB Learning among Power Electronics Students in Technical Education: A Case Study

Authors: Muhammad Mujtaba Asad, Razali Bin Hassan, Fahad Sherwani, Insaf Ali Siming

Abstract:

This paper discusses about the findings of preliminary survey on MATLAB software learning among power electronics students. One of the main focuses of power electronics course is on DC to DC boost convertors, because boost convertors are generally used in different industrial and non industrial applications. Population samples of this study were randomly selected final year bachelor of electronics and electrical engineering students from University Tun Hussein Onn Malaysia (UTHM).As per the results from the survey questioner analysis, almost eighty percent students are facing problem and difficulties in Dc to Dc boost convertors experimental understanding without using MATLAB simulink package. As per finding of this study it is clear that MATLAB play an effective and efficient function for better understanding of boost convertors experimental work among power electronics learners.

Keywords: MATLAB, Simulation, Power Electronics, Experimental Work.

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3232 Cumulative Learning based on Dynamic Clustering of Hierarchical Production Rules(HPRs)

Authors: Kamal K.Bharadwaj, Rekha Kandwal

Abstract:

An important structuring mechanism for knowledge bases is building clusters based on the content of their knowledge objects. The objects are clustered based on the principle of maximizing the intraclass similarity and minimizing the interclass similarity. Clustering can also facilitate taxonomy formation, that is, the organization of observations into a hierarchy of classes that group similar events together. Hierarchical representation allows us to easily manage the complexity of knowledge, to view the knowledge at different levels of details, and to focus our attention on the interesting aspects only. One of such efficient and easy to understand systems is Hierarchical Production rule (HPRs) system. A HPR, a standard production rule augmented with generality and specificity information, is of the following form Decision If < condition> Generality Specificity . HPRs systems are capable of handling taxonomical structures inherent in the knowledge about the real world. In this paper, a set of related HPRs is called a cluster and is represented by a HPR-tree. This paper discusses an algorithm based on cumulative learning scenario for dynamic structuring of clusters. The proposed scheme incrementally incorporates new knowledge into the set of clusters from the previous episodes and also maintains summary of clusters as Synopsis to be used in the future episodes. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested incremental structuring of clusters would be useful in mining data streams.

Keywords: Cumulative learning, clustering, data mining, hierarchical production rules.

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3231 A Survey of Response Generation of Dialogue Systems

Authors: Yifan Fan, Xudong Luo, Pingping Lin

Abstract:

An essential task in the field of artificial intelligence is to allow computers to interact with people through natural language. Therefore, researches such as virtual assistants and dialogue systems have received widespread attention from industry and academia. The response generation plays a crucial role in dialogue systems, so to push forward the research on this topic, this paper surveys various methods for response generation. We sort out these methods into three categories. First one includes finite state machine methods, framework methods, and instance methods. The second contains full-text indexing methods, ontology methods, vast knowledge base method, and some other methods. The third covers retrieval methods and generative methods. We also discuss some hybrid methods based knowledge and deep learning. We compare their disadvantages and advantages and point out in which ways these studies can be improved further. Our discussion covers some studies published in leading conferences such as IJCAI and AAAI in recent years.

Keywords: Retrieval, generative, deep learning, response generation, knowledge.

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3230 Studying the Environmental Effects of using Biogas Energy in Iran

Authors: Kambiz Tahvildari, Shakila ila Motamedi

Abstract:

Presently and in line with the United Nations (EPA), human thinking system has shifted towards clean fuels so as to maintain a cleaner environment and to save our planet earth. One of the most successful studies in order to achieve new energies includes the use of animal wastes and their organic residues, and the result of these researches has been represented in the form of very simple and cheap methods called biogas technology. Biogas technology has developed a lot in the recent decades; its reason is the high cost of fossil fuels and the greater attention of countries to the environmental pollutions due to the consumption of this kind of fuels. IRAN is ready for the optimized application of renewable energies, having much enriched resources of this kind of energies; so a special place could be considered for it when making programs. The purpose of biogas technology is the recovery of energy and finally the protection of the environment, which is much appropriate for the third world farmers with respect to their technical abilities and economic potentials. Studies show that the production and consumption of biogas is appropriate and economic in IRAN, because of the high amount of waste in the agriculture sector, the significant amount of animal and human excrement production, the great volume of garbage produced and the most important the specific social, climatic and agricultural conditions in IRAN, in order to proceed towards the reduction of pollution due to the use of fossil fuels.

Keywords: Agriculture, Biogas, Energy, Environment.

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3229 Methods of Forming Informational Culture Students

Authors: Altynbek Moshkalov

Abstract:

Along with the basic features of students\' culture information, with its widely usage oriented on implementation of the new information technologies in educational process that determines the search for ways of pointing to the similarity of interdisciplinary connections content, aims and objectives of the study. In this regard, the article questions about students\' information culture, and also presented information about the aims and objectives of the information culture process among students. In the formation of a professional interest in relevant information, which is an opportunity to assist in informing the professional activities of the essence of effective use of interactive methods and innovative technologies in the learning process. The result of the experiment proves the effectiveness of the information culture process of students in training the system of higher education based on the credit technology. The main purpose of this paper is a comprehensive review of students\' information culture.

Keywords: Information culture, methods of information culture of students, educational system of the credit technology, distance learning, information of interest, information and communication technologies and tools.

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3228 Prediction-Based Midterm Operation Planning for Energy Management of Exhibition Hall

Authors: Doseong Eom, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

Large exhibition halls require a lot of energy to maintain comfortable atmosphere for the visitors viewing inside. One way of reducing the energy cost is to have thermal energy storage systems installed so that the thermal energy can be stored in the middle of night when the energy price is low and then used later when the price is high. To minimize the overall energy cost, however, we should be able to decide how much energy to save during which time period exactly. If we can foresee future energy load and the corresponding cost, we will be able to make such decisions reasonably. In this paper, we use machine learning technique to obtain models for predicting weather conditions and the number of visitors on hourly basis for the next day. Based on the energy load thus predicted, we build a cost-optimal daily operation plan for the thermal energy storage systems and cooling and heating facilities through simulation-based optimization.

Keywords: Building energy management, machine learning, simulation-based optimization, operation planning.

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3227 Correlation-based Feature Selection using Ant Colony Optimization

Authors: M. Sadeghzadeh, M. Teshnehlab

Abstract:

Feature selection has recently been the subject of intensive research in data mining, specially for datasets with a large number of attributes. Recent work has shown that feature selection can have a positive effect on the performance of machine learning algorithms. The success of many learning algorithms in their attempts to construct models of data, hinges on the reliable identification of a small set of highly predictive attributes. The inclusion of irrelevant, redundant and noisy attributes in the model building process phase can result in poor predictive performance and increased computation. In this paper, a novel feature search procedure that utilizes the Ant Colony Optimization (ACO) is presented. The ACO is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It looks for optimal solutions by considering both local heuristics and previous knowledge. When applied to two different classification problems, the proposed algorithm achieved very promising results.

Keywords: Ant colony optimization, Classification, Datamining, Feature selection.

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3226 Using Daily Light Integral Concept to Construct the Ecological Plant Design Strategy of Urban Landscape

Authors: Chuang-Hung Lin, Cheng-Yuan Hsu, Jia-Yan Lin

Abstract:

It is an indispensible strategy to adopt greenery approach on architectural bases so as to improve ecological habitats, decrease heat-island effect, purify air quality, and relieve surface runoff as well as noise pollution, all of which are done in an attempt to achieve sustainable environment. How we can do with plant design to attain the best visual quality and ideal carbon dioxide fixation depends on whether or not we can appropriately make use of greenery according to the nature of architectural bases. To achieve the goal, it is a need that architects and landscape architects should be provided with sufficient local references. Current greenery studies focus mainly on the heat-island effect of urban with large scale. Most of the architects still rely on people with years of expertise regarding the adoption and disposition of plantation in connection with microclimate scale. Therefore, environmental design, which integrates science and aesthetics, requires fundamental research on landscape environment technology divided from building environment technology. By doing so, we can create mutual benefits between green building and the environment. This issue is extremely important for the greening design of the bases of green buildings in cities and various open spaces. The purpose of this study is to establish plant selection and allocation strategies under different building sunshade levels. Initially, with the shading of sunshine on the greening bases as the starting point, the effects of the shades produced by different building types on the greening strategies were analyzed. Then, by measuring the PAR (photosynthetic active radiation), the relative DLI (daily light integral) was calculated, while the DLI Map was established in order to evaluate the effects of the building shading on the established environmental greening, thereby serving as a reference for plant selection and allocation. The discussion results were to be applied in the evaluation of environment greening of greening buildings and establish the “right plant, right place” design strategy of multi-level ecological greening for application in urban design and landscape design development, as well as the greening criteria to feedback to the eco-city greening buildings.

Keywords: Daily light integral, plant design, urban open space.

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3225 Mobile Collaboration Learning Technique on Students in Developing Nations

Authors: Amah Nnachi Lofty, Oyefeso Olufemi, Ibiam Udu Ama

Abstract:

New and more powerful communications technologies continue to emerge at a rapid pace and their uses in education are widespread and the impact remarkable in the developing societies. This study investigates Mobile Collaboration Learning Technique (MCLT) on learners’ outcome among students in tertiary institutions of developing nations (a case of Nigeria students). It examines the significance of retention achievement scores of students taught using mobile collaboration and conventional method. The sample consisted of 120 students using Stratified random sampling method. Five research questions and hypotheses were formulated, and tested at 0.05 level of significance. A student achievement test (SAT) was made of 40 items of multiple-choice objective type, developed and validated for data collection by professionals. The SAT was administered to students as pre-test and post-test. The data were analyzed using t-test statistic to test the hypotheses. The result indicated that students taught using MCLT performed significantly better than their counterparts using the conventional method of instruction. Also, there was no significant difference in the post-test performance scores of male and female students taught using MCLT. Based on the findings, the following submissions was made that: Mobile collaboration system be encouraged in the institutions to boost knowledge sharing among learners, workshop and training should be organized to train teachers on the use of this technique, schools and government should consistently align curriculum standard to trends of technological dictates and formulate policies and procedures towards responsible use of MCLT.

Keywords: Education, communication, learning, mobile collaboration, technology.

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3224 Improved Artificial Immune System Algorithm with Local Search

Authors: Ramin Javadzadeh., Zahra Afsahi, MohammadReza Meybodi

Abstract:

The Artificial immune systems algorithms are Meta heuristic optimization method, which are used for clustering and pattern recognition applications are abundantly. These algorithms in multimodal optimization problems are more efficient than genetic algorithms. A major drawback in these algorithms is their slow convergence to global optimum and their weak stability can be considered in various running of these algorithms. In this paper, improved Artificial Immune System Algorithm is introduced for the first time to overcome its problems of artificial immune system. That use of the small size of a local search around the memory antibodies is used for improving the algorithm efficiently. The credibility of the proposed approach is evaluated by simulations, and it is shown that the proposed approach achieves better results can be achieved compared to the standard artificial immune system algorithms

Keywords: Artificial immune system, Cellular Automata, Cellular learning automata, Cellular learning automata, , Local search, Optimization.

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3223 Artificial Intelligence-Based Chest X-Ray Test of COVID-19 Patients

Authors: Dhurgham Al-Karawi, Nisreen Polus, Shakir Al-Zaidi, Sabah Jassim

Abstract:

The management of COVID-19 patients based on chest imaging is emerging as an essential tool for evaluating the spread of the pandemic which has gripped the global community. It has already been used to monitor the situation of COVID-19 patients who have issues in respiratory status. There has been increase to use chest imaging for medical triage of patients who are showing moderate-severe clinical COVID-19 features, this is due to the fast dispersal of the pandemic to all continents and communities. This article demonstrates the development of machine learning techniques for the test of COVID-19 patients using Chest X-Ray (CXR) images in nearly real-time, to distinguish the COVID-19 infection with a significantly high level of accuracy. The testing performance has covered a combination of different datasets of CXR images of positive COVID-19 patients, patients with viral and bacterial infections, also, people with a clear chest. The proposed AI scheme successfully distinguishes CXR scans of COVID-19 infected patients from CXR scans of viral and bacterial based pneumonia as well as normal cases with an average accuracy of 94.43%, sensitivity 95%, and specificity 93.86%. Predicted decisions would be supported by visual evidence to help clinicians speed up the initial assessment process of new suspected cases, especially in a resource-constrained environment.

Keywords: COVID-19, chest x-ray scan, artificial intelligence, texture analysis, local binary pattern transform, Gabor filter.

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3222 Autonomous Virtual Agent Navigation in Virtual Environments

Authors: Jafreezal Jaafar, Eric McKenzie

Abstract:

This paper presents a solution for the behavioural animation of autonomous virtual agent navigation in virtual environments. We focus on using Dempster-Shafer-s Theory of Evidence in developing visual sensor for virtual agent. The role of the visual sensor is to capture the information about the virtual environment or identifie which part of an obstacle can be seen from the position of the virtual agent. This information is require for vitual agent to coordinate navigation in virtual environment. The virual agent uses fuzzy controller as a navigation system and Fuzzy α - level for the action selection method. The result clearly demonstrates the path produced is reasonably smooth even though there is some sharp turn and also still not diverted too far from the potential shortest path. This had indicated the benefit of our method, where more reliable and accurate paths produced during navigation task.

Keywords: Agent, Navigation, Demster Shafer, Fuzzy Logic.

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3221 A Survey on Life Science Database Citation Frequency in Scientific Literatures

Authors: Hendry Muljadi, Jiro Araki, Satoru Miyazaki, Asao Fujiyama

Abstract:

There are so many databases of various fields of life sciences available online. To find well-used databases, a survey to measure life science database citation frequency in scientific literatures is done. The survey is done by measuring how many scientific literatures which are available on PubMed Central archive cited a specific life science database. This paper presents and discusses the results of the survey.

Keywords: Life science, database, metadatabase, PubMedCentral.

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3220 Avoiding Catastrophic Forgetting by a Dual-Network Memory Model Using a Chaotic Neural Network

Authors: Motonobu Hattori

Abstract:

In neural networks, when new patterns are learned by a network, the new information radically interferes with previously stored patterns. This drawback is called catastrophic forgetting or catastrophic interference. In this paper, we propose a biologically inspired neural network model which overcomes this problem. The proposed model consists of two distinct networks: one is a Hopfield type of chaotic associative memory and the other is a multilayer neural network. We consider that these networks correspond to the hippocampus and the neocortex of the brain, respectively. Information given is firstly stored in the hippocampal network with fast learning algorithm. Then the stored information is recalled by chaotic behavior of each neuron in the hippocampal network. Finally, it is consolidated in the neocortical network by using pseudopatterns. Computer simulation results show that the proposed model has much better ability to avoid catastrophic forgetting in comparison with conventional models.

Keywords: catastrophic forgetting, chaotic neural network, complementary learning systems, dual-network

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3219 Using a Semantic Self-Organising Web Page-Ranking Mechanism for Public Administration and Education

Authors: Marios Poulos, Sozon Papavlasopoulos, V. S. Belesiotis

Abstract:

In the proposed method for Web page-ranking, a novel theoretic model is introduced and tested by examples of order relationships among IP addresses. Ranking is induced using a convexity feature, which is learned according to these examples using a self-organizing procedure. We consider the problem of selforganizing learning from IP data to be represented by a semi-random convex polygon procedure, in which the vertices correspond to IP addresses. Based on recent developments in our regularization theory for convex polygons and corresponding Euclidean distance based methods for classification, we develop an algorithmic framework for learning ranking functions based on a Computational Geometric Theory. We show that our algorithm is generic, and present experimental results explaining the potential of our approach. In addition, we explain the generality of our approach by showing its possible use as a visualization tool for data obtained from diverse domains, such as Public Administration and Education.

Keywords: Computational Geometry, Education, e-Governance, Semantic Web.

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3218 Comparing Occupants’ Satisfaction in LEED Certified Office Buildings and Non LEED Certified Office Buildings - A Case Study of Office Buildings in Egypt and Turkey

Authors: Amgad A. Farghal, Dina I. El Desouki

Abstract:

Energy consumption and users’ satisfaction were compared in three LEED certified office buildings in turkey and an office building in Egypt. The field studies were conducted in summer 2012. The measured environmental parameters in the four buildings were indoor air temperature, relative humidity, CO2 percentage and light intensity. The traditional building is located in Smart Village in Abu Rawash, Cairo, Egypt. The building was studied for 7 days resulting in 84 responds. The three rated buildings are in Istanbul; Turkey. A Platinum LEED certified office building is owned by BASF and gained a platinum certificate for new construction and major renovation. The building was studied for 3 days resulting in 13 responds. A Gold LEED certified office building is owned by BASF and gained a gold certificate for new construction and major renovation. The building was studied for 2 days resulting in 10 responds. A silver LEED certified office building is owned by Unilever and gained a silver certificate for commercial interiors. The building was studied for 7 days resulting in 84 responds. The results showed that all buildings had no significant difference regarding occupants’ satisfaction with the amount of lighting, noise level, odor and access to the outdoor view. There was significant difference between occupants’ satisfaction in LEED certified buildings and the traditional building regarding the thermal environment and the perception of the general environment (colors, carpet and decoration. The findings suggest that careful design could lead to a certified building that enhances the thermal environment and the perception of the indoor environment leading to energy consumption without scarifying occupants’ satisfaction.

Keywords: Energy consumption, occupants’ satisfaction, rating systems.

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3217 Connectionist Approach to Generic Text Summarization

Authors: Rajesh S.Prasad, U. V. Kulkarni, Jayashree.R.Prasad

Abstract:

As the enormous amount of on-line text grows on the World-Wide Web, the development of methods for automatically summarizing this text becomes more important. The primary goal of this research is to create an efficient tool that is able to summarize large documents automatically. We propose an Evolving connectionist System that is adaptive, incremental learning and knowledge representation system that evolves its structure and functionality. In this paper, we propose a novel approach for Part of Speech disambiguation using a recurrent neural network, a paradigm capable of dealing with sequential data. We observed that connectionist approach to text summarization has a natural way of learning grammatical structures through experience. Experimental results show that our approach achieves acceptable performance.

Keywords: Artificial Neural Networks (ANN); Computational Intelligence (CI); Connectionist Text Summarizer ECTS (ECTS); Evolving Connectionist systems; Evolving systems; Fuzzy systems (FS); Part of Speech (POS) disambiguation.

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3216 Robot Technology Impact on Dyslexic Students’ English Learning

Authors: Khaled Hamdan, Abid Amorri, Fatima Hamdan

Abstract:

Involving students in English language learning process and achieving an adequate English language proficiency in the target language can be a great challenge for both teachers and students. This can prove even a far greater challenge to engage students with special needs (Dyslexia) if they have physical impairment and inadequate mastery of basic communicative language competence/proficiency in the target language. From this perspective, technology like robots can probably be used to enhance learning process for the special needs students who have extensive communication needs, who face continuous struggle to interact with their peers and teachers and meet academic requirements. Robots, precisely NAO, can probably provide them with the perfect opportunity to practice social and communication skills, and meet their English academic requirements. This research paper aims to identify to what extent robots can be used to improve students’ social interaction and communication skills and to understand the potential for robotics-based education in motivating and engaging UAEU dyslexic students to meet university requirements. To reach this end, the paper will explore several factors that come into play – Motion Level-involving cognitive activities, Interaction Level-involving language processing, Behavior Level -establishing a close relationship with the robot and Appraisal Level- focusing on dyslexia students’ achievement in the target language.

Keywords: Dyslexia, robot technology, motion, interaction, behavior and appraisal levels, social and communication skills.

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3215 Prioritizing Influential Factors on the Promotion of Virtual Training System

Authors: Nader Gharibnavaz, Mostafa Mosadeghi, Naser Gharibnavaz

Abstract:

In today's world where everything is rapidly changing and information technology is high in development, many features of culture, society, politic and economy has changed. The advent of information technology and electronic data transmission lead to easy communication and fields like e-learning and e-commerce, are accessible for everyone easily. One of these technologies is virtual training. The "quality" of such kind of education systems is critical. 131 questionnaires were prepared and distributed among university student in Toba University. So the research has followed factors that affect the quality of learning from the perspective of staff, students, professors and this type of university. It is concluded that the important factors in virtual training are the quality of professors, the quality of staff, and the quality of the university. These mentioned factors were the most prior factors in this education system and necessary for improving virtual training.

Keywords: Training , Virtual Training, Strategic Positioning, Positioning Mapping, Unique Selling Proposition, Strong Brands, Indoors industry

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3214 Combined Analysis of Sudoku Square Designs with Same Treatments

Authors: A. Danbaba

Abstract:

Several experiments are conducted at different environments such as locations or periods (seasons) with identical treatments to each experiment purposely to study the interaction between the treatments and environments or between the treatments and periods (seasons). The commonly used designs of experiments for this purpose are randomized block design, Latin square design, balanced incomplete block design, Youden design, and one or more factor designs. The interest is to carry out a combined analysis of the data from these multi-environment experiments, instead of analyzing each experiment separately. This paper proposed combined analysis of experiments conducted via Sudoku square design of odd order with same experimental treatments.

Keywords: Sudoku designs, combined analysis, multi-environment experiments, common treatments.

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3213 A Secure Mobile OTP Authentication Scheme for User Mobility Cloud VDI Environment

Authors: Jong-won Lee

Abstract:

Since Cloud environment has appeared as the most powerful keyword in the computing industry, the growth in VDI (Virtual Desktop Infrastructure) became remarkable in domestic market. In recent years, with the trend that mobile devices such as smartphones and pads spread so rapidly, the strengths of VDI that allows people to access and perform business on the move along with companies' office needs expedite more rapid spread of VDI. In this paper, mobile OTP (One-Time Password) authentication method is proposed to secure mobile device portability through rapid and secure authentication using mobile devices such as mobile phones or pads, which does not require additional purchase or possession of OTP tokens of users. To facilitate diverse and wide use of Services in the future, service should be continuous and stable, and above all, security should be considered the most important to meet advanced portability and user accessibility, the strengths of VDI.

Keywords: Cloud, VDI, OTP, Mobility

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3212 Computer Modeling and Plant-Wide Dynamic Simulation for Industrial Flare Minimization

Authors: Sujing Wang, Song Wang, Jian Zhang, Qiang Xu

Abstract:

Flaring emissions during abnormal operating conditions such as plant start-ups, shut-downs, and upsets in chemical process industries (CPI) are usually significant. Flare minimization can help to save raw material and energy for CPI plants, and to improve local environmental sustainability. In this paper, a systematic methodology based on plant-wide dynamic simulation is presented for CPI plant flare minimizations under abnormal operating conditions. Since off-specification emission sources are inevitable during abnormal operating conditions, to significantly reduce flaring emission in a CPI plant, they must be either recycled to the upstream process for online reuse, or stored somewhere temporarily for future reprocessing, when the CPI plant manufacturing returns to stable operation. Thus, the off-spec products could be reused instead of being flared. This can be achieved through the identification of viable design and operational strategies during normal and abnormal operations through plant-wide dynamic scheduling, simulation, and optimization. The proposed study includes three stages of simulation works: (i) developing and validating a steady-state model of a CPI plant; (ii) transiting the obtained steady-state plant model to the dynamic modeling environment; and refining and validating the plant dynamic model; and (iii) developing flare minimization strategies for abnormal operating conditions of a CPI plant via a validated plant-wide dynamic model. This cost-effective methodology has two main merits: (i) employing large-scale dynamic modeling and simulations for industrial flare minimization, which involves various unit models for modeling hundreds of CPI plant facilities; (ii) dealing with critical abnormal operating conditions of CPI plants such as plant start-up and shut-down. Two virtual case studies on flare minimizations for start-up operation (over 50% of emission savings) and shut-down operation (over 70% of emission savings) of an ethylene plant have been employed to demonstrate the efficacy of the proposed study.

Keywords: Flare minimization, large-scale modeling and simulation, plant shut-down, plant start-up.

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3211 Discriminant Analysis as a Function of Predictive Learning to Select Evolutionary Algorithms in Intelligent Transportation System

Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Daniel Vélez-Díaz, Edith Olaco García

Abstract:

In this paper, we present the use of the discriminant analysis to select evolutionary algorithms that better solve instances of the vehicle routing problem with time windows. We use indicators as independent variables to obtain the classification criteria, and the best algorithm from the generic genetic algorithm (GA), random search (RS), steady-state genetic algorithm (SSGA), and sexual genetic algorithm (SXGA) as the dependent variable for the classification. The discriminant classification was trained with classic instances of the vehicle routing problem with time windows obtained from the Solomon benchmark. We obtained a classification of the discriminant analysis of 66.7%.

Keywords: Intelligent transportation systems, data-mining techniques, evolutionary algorithms, discriminant analysis, machine learning.

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