Search results for: balance training
390 A Subtractive Clustering Based Approach for Early Prediction of Fault Proneness in Software Modules
Authors: Ramandeep S. Sidhu, Sunil Khullar, Parvinder S. Sandhu, R. P. S. Bedi, Kiranbir Kaur
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In this paper, subtractive clustering based fuzzy inference system approach is used for early detection of faults in the function oriented software systems. This approach has been tested with real time defect datasets of NASA software projects named as PC1 and CM1. Both the code based model and joined model (combination of the requirement and code based metrics) of the datasets are used for training and testing of the proposed approach. The performance of the models is recorded in terms of Accuracy, MAE and RMSE values. The performance of the proposed approach is better in case of Joined Model. As evidenced from the results obtained it can be concluded that Clustering and fuzzy logic together provide a simple yet powerful means to model the earlier detection of faults in the function oriented software systems.
Keywords: Subtractive clustering, fuzzy inference system, fault proneness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2570389 Development of Performance Measures for the Implementation of Total Quality Management in Indian Industry
Authors: Perminderjit Singh, Sukhvir Singh
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Total Quality Management (TQM) refers to management methods used to enhance quality and productivity in business organizations. Total Quality Management (TQM) has become a frequently used term in discussions concerning quality. Total Quality management has brought rise in demands on the organizations policy and the customers have gained more importance in the organizations focus. TQM is considered as an important management tool, which helps the organizations to satisfy their customers. In present research critical success factors includes management commitment, customer satisfaction, continuous improvement, work culture and environment, supplier quality management, training and development, employee satisfaction and product/process design are studied. A questionnaire is developed to implement these critical success factors in implementation of total quality management in Indian industry. Questionnaires filled by consulting different industrial organizations. Data collected from questionnaires is analyzed by descriptive and importance indexes.
Keywords: Total quality management, critical success factor, employee satisfaction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1968388 Development of NOx Emission Model for a Tangentially Fired Acid Incinerator
Authors: Elangeshwaran Pathmanathan, Rosdiazli Ibrahim, Vijanth Sagayan Asirvadam
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This paper aims to develop a NOx emission model of an acid gas incinerator using Nelder-Mead least squares support vector regression (LS-SVR). Malaysia DOE is actively imposing the Clean Air Regulation to mandate the installation of analytical instrumentation known as Continuous Emission Monitoring System (CEMS) to report emission level online to DOE . As a hardware based analyzer, CEMS is expensive, maintenance intensive and often unreliable. Therefore, software predictive technique is often preferred and considered as a feasible alternative to replace the CEMS for regulatory compliance. The LS-SVR model is built based on the emissions from an acid gas incinerator that operates in a LNG Complex. Simulated Annealing (SA) is first used to determine the initial hyperparameters which are then further optimized based on the performance of the model using Nelder-Mead simplex algorithm. The LS-SVR model is shown to outperform a benchmark model based on backpropagation neural networks (BPNN) in both training and testing data.Keywords: artificial neural networks, industrial pollution, predictive algorithms, support vector machines
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1965387 Information Technologies in Human Resources Management - Selected Examples
Authors: A. Karasek
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Rapid growth of Information Technologies (IT) has had huge influence on enterprises, and it has contributed to its promotion and increasingly extensive use in enterprises. Information Technologies have to a large extent determined the processes taking place in an enterprise; what is more, IT development has brought the need to adopt a brand new approach to human resources management in an enterprise. The use of IT in human resource management (HRM) is of high importance due to the growing role of information and information technologies. The aim of this paper is to evaluate the use of information technologies in human resources management in enterprises. These practices will be presented in the following areas: recruitment and selection, development and training, employee assessment, motivation, talent management, personnel service. Results of conducted survey show diversity of solutions applied in particular areas of human resource management. In the future, further development in this area should be expected, as well as integration of individual HRM areas, growing mobile-enabled HR processes and their transfer into the cloud. Presented IT solutions applied in HRM are highly innovative, which is of great significance due to their possible implementation in other enterprises.Keywords: E-HR, human resources management, HRM practices, HRMS, information technologies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5511386 Tactical Urbanism and Sustainability: Tactical Experiences in the Promotion of Active Transportation
Authors: Aline Fernandes Barata, Adriana Sansão Fontes
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The overvaluation of the use of automobile has detrimentally affected the importance of pedestrians within the city and consequently its public spaces. As a way of treating contemporary urban paradigms, Tactical Urbanism aims to recover and activate spaces through fast and easily-applied actions that demonstrate the possibility of large-scale and long-term changes in cities. Tactical interventions have represented an important practice of redefining public spaces and urban mobility. The concept of Active Transportation coheres with the idea of sustainable urban mobility, characterizing the means of transportation through human propulsion, such as walking and cycling. This paper aims to debate the potential of Tactical Urbanism in promoting Active Transportation by revealing opportunities of transformation in the urban space of contemporary cities through initiatives that promote the protection and valorization of the presence of pedestrians and cyclists in cities, and that subvert the importance of motorized vehicles. In this paper, we present the character of these actions in two different ways: when they are used as tests for permanent interventions and when they have pre-defined start and end periods. Using recent initiatives to illustrate, we aim to discuss the role of small-scale actions in promoting and incentivizing a more active, healthy, sustainable and responsive urban way of life, presenting how some of them have developed through public policies. For that, we will present some examples of tactical actions that illustrate the encouragement of Active Transportation and trials to balance the urban opportunities for pedestrians and cyclists. These include temporary closure of streets, the creation of new alternatives and more comfortable areas for walking and cycling, and the subversion of uses in public spaces where the usage of cars are predominant.
Keywords: Tactical urbanism, active transportation, sustainable mobility, non-motorized means.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1340385 Enhancing Multi-Frame Images Using Self-Delaying Dynamic Networks
Authors: Lewis E. Hibell, Honghai Liu, David J. Brown
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This paper presents the use of a newly created network structure known as a Self-Delaying Dynamic Network (SDN) to create a high resolution image from a set of time stepped input frames. These SDNs are non-recurrent temporal neural networks which can process time sampled data. SDNs can store input data for a lifecycle and feature dynamic logic based connections between layers. Several low resolution images and one high resolution image of a scene were presented to the SDN during training by a Genetic Algorithm. The SDN was trained to process the input frames in order to recreate the high resolution image. The trained SDN was then used to enhance a number of unseen noisy image sets. The quality of high resolution images produced by the SDN is compared to that of high resolution images generated using Bi-Cubic interpolation. The SDN produced images are superior in several ways to the images produced using Bi-Cubic interpolation.Keywords: Image Enhancement, Neural Networks, Multi-Frame.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1183384 The Appraisal of Construction Sites Productivity: In Kendall’s Concordance
Authors: Abdulkadir Abu Lawal
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For the dearth of reliable cardinal numerical data, the linked phenomena in productivity indices such as operational costs and company turnovers, etc. could not be investigated. This would not give us insight to the root of productivity problems at unique sites. So, ordinal ranking by professionals who were most directly involved with construction sites was applied for Kendall’s concordance. Responses gathered from independent architects, builders/engineers, and quantity surveyors were herein analyzed. They were responses based on factors that affect sites productivity, and these factors were categorized as head office factors, resource management effectiveness factors, motivational factors, and training/skill development factors. It was found that productivity is low and has to be improved in order to facilitate Nigerian efforts in bridging its infrastructure deficit. The significance of this work is underlined with the Kendall’s coefficient of concordance of 0.78, while remedial measures must be emphasized to stimulate better productivity. Further detailed study can be undertaken by using Fuzzy logic analysis on wider Delphi survey.
Keywords: Factors, Kendall’s coefficient of concordance, magnitude of agreement, percentage magnitude of dichotomy, ranking variables.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 965383 Deep Reinforcement Learning for Optimal Decision-making in Supply Chains
Authors: Nitin Singh, Meng Ling, Talha Ahmed, Tianxia Zhao, Reinier van de Pol
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We propose the use of Reinforcement Learning (RL) as a viable alternative for optimizing supply chain management, particularly in scenarios with stochasticity in product demands. RL’s adaptability to changing conditions and its demonstrated success in diverse fields of sequential decision-making make it a promising candidate for addressing supply chain problems. We investigate the impact of demand fluctuations in a multi-product supply chain system and develop RL agents with learned generalizable policies. We provide experimentation details for training RL agents and a statistical analysis of the results. We study generalization ability of RL agents for different demand uncertainty scenarios and observe superior performance compared to the agents trained with fixed demand curves. The proposed methodology has the potential to lead to cost reduction and increased profit for companies dealing with frequent inventory movement between supply and demand nodes.
Keywords: Inventory Management, Reinforcement Learning, Supply Chain Optimization, Uncertainty.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 330382 The Change in Management Accounting from an Institutional and Contingency Perspective: A Case Study for a Romanian Company
Authors: Gabriel Jinga, Madalina Dumitru
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The objective of this paper is to present the process of change in management accounting in Romania, a former communist country from Eastern Europe. In order to explain this process, we used the contingency and institutional theories. We focused on the following directions: the presentation of the scientific context and motivation of this research and the case study. We presented the state of the art in the process of change in the management accounting from the international and national perspective. We also described the evolution of management accounting in Romania in the context of economic and political changes. An important moment was the fall of communism in 1989. This represents a starting point for a new economic environment and for new management accounting. Accordingly, we developed a case study which presented this evolution. The conclusion of our research was that the changes in the management accounting system of the company analysed occurred in the same time with the institutionalisation of some elements (e.g. degree of competition, training and competencies in management accounting). The management accounting system was modelled by the contingencies specific to this company (e.g. environment, industry, strategy).Keywords: Management accounting, change, Romania, contingency and institutional theory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2318381 Interactive Shadow Play Animation System
Authors: Bo Wan, Xiu Wen, Lingling An, Xiaoling Ding
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The paper describes a Chinese shadow play animation system based on Kinect. Users, without any professional training, can personally manipulate the shadow characters to finish a shadow play performance by their body actions and get a shadow play video through giving the record command to our system if they want. In our system, Kinect is responsible for capturing human movement and voice commands data. Gesture recognition module is used to control the change of the shadow play scenes. After packaging the data from Kinect and the recognition result from gesture recognition module, VRPN transmits them to the server-side. At last, the server-side uses the information to control the motion of shadow characters and video recording. This system not only achieves human-computer interaction, but also realizes the interaction between people. It brings an entertaining experience to users and easy to operate for all ages. Even more important is that the application background of Chinese shadow play embodies the protection of the art of shadow play animation.
Keywords: Gesture recognition, Kinect, shadow play animation, VRPN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2692380 Threshold Concepts in TESOL: A Thematic Analysis of Disciplinary Guiding Principles
Authors: Neil Morgan
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The notion of Threshold Concepts has offered a fertile new perspective on the transformative effects of mastery of particular concepts on student understanding of subject matter and their developing identities as inductees into disciplinary discourse communities. Only by successfully traversing essential knowledge thresholds can neophytes achieve the more sophisticated understandings of subject matter possessed by mature members of a discipline. This paper uses thematic analysis of disciplinary guiding principles to identify nine candidate Threshold Concepts that appear to underpin effective TESOL practice. The relationship between these candidate TESOL Threshold Concepts, TESOL principles, and TESOL instructional techniques appears to be amenable to a schematic representation based on superordinate categories of TESOL practitioner concern and, as such, offers an alternative to the view of Threshold Concepts as a privileged subset of disciplinary core concepts. The paper concludes by exploring the potential of a Threshold Concepts framework to productively inform TESOL initial teacher education (ITE) and in-service education and training (INSET).
Keywords: TESOL, threshold concepts, TESOL principles, TESOL ITE/INSET, community of practice.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 718379 Evolution of Fuzzy Neural Networks Using an Evolution Strategy with Fuzzy Genotype Values
Authors: Hidehiko Okada
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Evolution strategy (ES) is a well-known instance of evolutionary algorithms, and there have been many studies on ES. In this paper, the author proposes an extended ES for solving fuzzy-valued optimization problems. In the proposed ES, genotype values are not real numbers but fuzzy numbers. Evolutionary processes in the ES are extended so that it can handle genotype instances with fuzzy numbers. In this study, the proposed method is experimentally applied to the evolution of neural networks with fuzzy weights and biases. Results reveal that fuzzy neural networks evolved using the proposed ES with fuzzy genotype values can model hidden target fuzzy functions even though no training data are explicitly provided. Next, the proposed method is evaluated in terms of variations in specifying fuzzy numbers as genotype values. One of the mostly adopted fuzzy numbers is a symmetric triangular one that can be specified by its lower and upper bounds (LU) or its center and width (CW). Experimental results revealed that the LU model contributed better to the fuzzy ES than the CW model, which indicates that the LU model should be adopted in future applications of the proposed method.
Keywords: Evolutionary algorithm, evolution strategy, fuzzy number, feedforward neural network, neuroevolution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1539378 Incidence of Disasters and Coping Mechanism among Farming Households in South West Nigeria
Authors: Fawehinmi Olabisi Alaba, Adeniyi O. R.
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Farming households faces lots of disaster which contribute to endemic poverty. Anticipated increases in extreme weather events will exacerbate this. Primary data was administered to farming household using multi-stage random sampling technique. The result of the analysis shows that majority of the respondents (69.9%) are male, have mean household size, years of formal education and age of 5±1.14, 6±3.41, and 51.06±10.43 respectively. The major (48.9%) type of disaster experienced is flooding. Major coping mechanism adopted is sourcing for support from family and friends. Age, education, experience, access to extension agent, and mitigation control method contribute significantly to vulnerability to disaster. The major adaptation method (62.3%) is construction of drainage.
The study revealed that the coping mechanisms employed may become less effective as increasingly fragile livelihood systems struggle to withstand disaster shocks. Thus there is need for training of the farmers on measures to adapt to mitigate the shock from disasters
Keywords: Adaptation, Disasters, Flooding, Vulnerability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2115377 Land Use Change Detection Using Remote Sensing and GIS
Authors: Naser Ahmadi Sani, Karim Solaimani, Lida Razaghnia, Jalal Zandi
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In recent decades, rapid and incorrect changes in land-use have been associated with consequences such as natural resources degradation and environmental pollution. Detecting changes in land-use is one of the tools for natural resource management and assessment of changes in ecosystems. The target of this research is studying the land-use changes in Haraz basin with an area of 677000 hectares in a 15 years period (1996 to 2011) using LANDSAT data. Therefore, the quality of the images was first evaluated. Various enhancement methods for creating synthetic bonds were used in the analysis. Separate training sites were selected for each image. Then the images of each period were classified in 9 classes using supervised classification method and the maximum likelihood algorithm. Finally, the changes were extracted in GIS environment. The results showed that these changes are an alarm for the HARAZ basin status in future. The reason is that 27% of the area has been changed, which is related to changing the range lands to bare land and dry farming and also changing the dense forest to sparse forest, horticulture, farming land and residential area.
Keywords: HARAZ Basin, Change Detection, Land-use, Satellite Data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2309376 Analysis and Classification of Hiv-1 Sub- Type Viruses by AR Model through Artificial Neural Networks
Authors: O. Yavuz, L. Ozyilmaz
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HIV-1 genome is highly heterogeneous. Due to this variation, features of HIV-I genome is in a wide range. For this reason, the ability to infection of the virus changes depending on different chemokine receptors. From this point of view, R5 HIV viruses use CCR5 coreceptor while X4 viruses use CXCR5 and R5X4 viruses can utilize both coreceptors. Recently, in Bioinformatics, R5X4 viruses have been studied to classify by using the experiments on HIV-1 genome. In this study, R5X4 type of HIV viruses were classified using Auto Regressive (AR) model through Artificial Neural Networks (ANNs). The statistical data of R5X4, R5 and X4 viruses was analyzed by using signal processing methods and ANNs. Accessible residues of these virus sequences were obtained and modeled by AR model since the dimension of residues is large and different from each other. Finally the pre-processed data was used to evolve various ANN structures for determining R5X4 viruses. Furthermore ROC analysis was applied to ANNs to show their real performances. The results indicate that R5X4 viruses successfully classified with high sensitivity and specificity values training and testing ROC analysis for RBF, which gives the best performance among ANN structures.Keywords: Auto-Regressive Model, HIV, Neural Networks, ROC Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1175375 NonStationary CMA for Decision Feedback Equalization of Markovian Time Varying Channels
Authors: S. Cherif, M. Turki-Hadj Alouane
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In this paper, we propose a modified version of the Constant Modulus Algorithm (CMA) tailored for blind Decision Feedback Equalizer (DFE) of first order Markovian time varying channels. The proposed NonStationary CMA (NSCMA) is designed so that it explicitly takes into account the Markovian structure of the channel nonstationarity. Hence, unlike the classical CMA, the NSCMA is not blind with respect to the channel time variations. This greatly helps the equalizer in the case of realistic channels, and avoids frequent transmissions of training sequences. This paper develops a theoretical analysis of the steady state performance of the CMA and the NSCMA for DFEs within a time varying context. Therefore, approximate expressions of the mean square errors are derived. We prove that in the steady state, the NSCMA exhibits better performance than the classical CMA. These new results are confirmed by simulation. Through an experimental study, we demonstrate that the Bit Error Rate (BER) is reduced by the NSCMA-DFE, and the improvement of the BER achieved by the NSCMA-DFE is as significant as the channel time variations are severe.Keywords: Time varying channel, Markov model, Blind DFE, CMA, NSCMA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1288374 A Comparative Study of Malware Detection Techniques Using Machine Learning Methods
Authors: Cristina Vatamanu, Doina Cosovan, Dragoş Gavriluţ, Henri Luchian
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In the past few years, the amount of malicious software increased exponentially and, therefore, machine learning algorithms became instrumental in identifying clean and malware files through (semi)-automated classification. When working with very large datasets, the major challenge is to reach both a very high malware detection rate and a very low false positive rate. Another challenge is to minimize the time needed for the machine learning algorithm to do so. This paper presents a comparative study between different machine learning techniques such as linear classifiers, ensembles, decision trees or various hybrids thereof. The training dataset consists of approximately 2 million clean files and 200.000 infected files, which is a realistic quantitative mixture. The paper investigates the above mentioned methods with respect to both their performance (detection rate and false positive rate) and their practicability.Keywords: Detection Rate, False Positives, Perceptron, One Side Class, Ensembles, Decision Tree, Hybrid methods, Feature Selection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3272373 Investigation of the Possibility to Prepare Supervised Classification Map of Gully Erosion by RS and GIS
Authors: Ali Mohammadi Torkashvand, Hamid Reza Alipour
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This study investigates the possibility providing gully erosion map by the supervised classification of satellite images (ETM+) in two mountainous and plain land types. These land types were the part of Varamin plain, Tehran province, and Roodbar subbasin, Guilan province, as plain and mountain land types, respectively. The position of 652 and 124 ground control points were recorded by GPS respectively in mountain and plain land types. Soil gully erosion, land uses or plant covers were investigated in these points. Regarding ground control points and auxiliary points, training points of gully erosion and other surface features were introduced to software (Ilwis 3.3 Academic). The supervised classified map of gully erosion was prepared by maximum likelihood method and then, overall accuracy of this map was computed. Results showed that the possibility supervised classification of gully erosion isn-t possible, although it need more studies for results generalization to other mountainous regions. Also, with increasing land uses and other surface features in plain physiography, it decreases the classification of accuracy.Keywords: Supervised classification, Gully erosion, Map.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1811372 Transformation Building of Micro- Entrepreneurs: A Conceptual Model
Authors: Abu Bakar Sedek Abdul Jamak, Saridan Abu Bakar, Zulkipli Ghazali, Roselind Wan
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The majority of micro-entrepreneurs in Malaysia operate very small-scaled business activities such as food stalls, burger stalls, night market hawkers, grocery stores, constructions, rubber and oil palm small holders, and other agro-based services and activities. Why are they venturing into entrepreneurship - is it for survival, out of interest or due to encouragement and assistance from the local government? And why is it that some micro-entrepreneurs are lagging behind in entrepreneurship, and what do they need to rectify this situation so that they are able to progress further? Furthermore, what are the skills that the micro entrepreneurs should developed to transform them into successful micro-enterprises and become small and medium-sized enterprises (SME)? This paper proposes a 7-Step approach that can serve as a basis for identification of critical entrepreneurial success factors that enable policy makers, practitioners, consultants, training managers and other agencies in developing tools to assist micro business owners. This paper also highlights the experience of one of the successful companies in Malaysia that has transformed from micro-enterprise to become a large organization in less than 10 years.Keywords: Entrepreneurship, Micro-entrepreneurs, Transformation, Customers
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2376371 Ethical Perspectives on Implementation of Computer Aided Design Curriculum in Architecture in Nigeria: A Case Study of Chukwuemeka Odumegwu Ojukwu University, Uli
Authors: Kelechi E. Ezeji
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The use of Computer Aided Design (CAD) technologies has become pervasive in the Architecture, Engineering and Construction (AEC) industry. This has led to its inclusion as an important part of the training module in the curriculum for Architecture Schools in Nigeria. This paper examines the ethical questions that arise in the implementation of Computer Aided Design (CAD) Content of the curriculum for Architectural education. Using existing literature, it begins this scrutiny from the propriety of inclusion of CAD into the education of the architect and the obligations of the different stakeholders in the implementation process. It also examines the questions raised by the negative use of computing technologies as well as perceived negative influence of the use of CAD on design creativity. Survey methodology was employed to gather data from the Department of Architecture, Chukwuemeka Odumegwu Ojukwu University Uli, which has been used as a case study on how the issues raised are being addressed. The paper draws conclusions on what will make for successful ethical implementation.Keywords: Computer aided design, curriculum, education, ethics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2232370 Neural Network Based Icing Identification and Fault Tolerant Control of a 340 Aircraft
Authors: F. Caliskan
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This paper presents a Neural Network (NN) identification of icing parameters in an A340 aircraft and a reconfiguration technique to keep the A/C performance close to the performance prior to icing. Five aircraft parameters are assumed to be considerably affected by icing. The off-line training for identifying the clear and iced dynamics is based on the Levenberg-Marquard Backpropagation algorithm. The icing parameters are located in the system matrix. The physical locations of the icing are assumed at the right and left wings. The reconfiguration is based on the technique known as the control mixer approach or pseudo inverse technique. This technique generates the new control input vector such that the A/C dynamics is not much affected by icing. In the simulations, the longitudinal and lateral dynamics of an Airbus A340 aircraft model are considered, and the stability derivatives affected by icing are identified. The simulation results show the successful NN identification of the icing parameters and the reconfigured flight dynamics having the similar performance before the icing. In other words, the destabilizing icing affect is compensated.Keywords: Aircraft Icing, Stability Derivatives, Neural NetworkIdentification, Reconfiguration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1696369 Feature Selection with Kohonen Self Organizing Classification Algorithm
Authors: Francesco Maiorana
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In this paper a one-dimension Self Organizing Map algorithm (SOM) to perform feature selection is presented. The algorithm is based on a first classification of the input dataset on a similarity space. From this classification for each class a set of positive and negative features is computed. This set of features is selected as result of the procedure. The procedure is evaluated on an in-house dataset from a Knowledge Discovery from Text (KDT) application and on a set of publicly available datasets used in international feature selection competitions. These datasets come from KDT applications, drug discovery as well as other applications. The knowledge of the correct classification available for the training and validation datasets is used to optimize the parameters for positive and negative feature extractions. The process becomes feasible for large and sparse datasets, as the ones obtained in KDT applications, by using both compression techniques to store the similarity matrix and speed up techniques of the Kohonen algorithm that take advantage of the sparsity of the input matrix. These improvements make it feasible, by using the grid, the application of the methodology to massive datasets.Keywords: Clustering algorithm, Data mining, Feature selection, Grid, Kohonen Self Organizing Map.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3042368 Voice Driven Applications in Non-stationary and Chaotic Environment
Authors: C. Kwan, X. Li, D. Lao, Y. Deng, Z. Ren, B. Raj, R. Singh, R. Stern
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Automated operations based on voice commands will become more and more important in many applications, including robotics, maintenance operations, etc. However, voice command recognition rates drop quite a lot under non-stationary and chaotic noise environments. In this paper, we tried to significantly improve the speech recognition rates under non-stationary noise environments. First, 298 Navy acronyms have been selected for automatic speech recognition. Data sets were collected under 4 types of noisy environments: factory, buccaneer jet, babble noise in a canteen, and destroyer. Within each noisy environment, 4 levels (5 dB, 15 dB, 25 dB, and clean) of Signal-to-Noise Ratio (SNR) were introduced to corrupt the speech. Second, a new algorithm to estimate speech or no speech regions has been developed, implemented, and evaluated. Third, extensive simulations were carried out. It was found that the combination of the new algorithm, the proper selection of language model and a customized training of the speech recognizer based on clean speech yielded very high recognition rates, which are between 80% and 90% for the four different noisy conditions. Fourth, extensive comparative studies have also been carried out.
Keywords: Non-stationary, speech recognition, voice commands.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1524367 Optimizing the Capacity of a Convolutional Neural Network for Image Segmentation and Pattern Recognition
Authors: Yalong Jiang, Zheru Chi
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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.Keywords: CNN, capsule network, capacity optimization, character recognition, data augmentation; semantic segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 687366 Analyzing Behaviour of the Utilization of the Online News Clipping Database: Experience in Suan Sunandha Rajabhat University
Authors: Siriporn Poolsuwan, Kanyarat Bussaban
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This research aims to investigate and analyze user’s behaviour towards the utilization of the online news clipping database at Suan Sunandha Rajabhat University, Thailand. Data is gathered from 214 lecturers and 380 undergraduate students by using questionnaires. Findings show that most users knew the online news clipping service from their friends, library’s website and their teachers. The users learned how to use it by themselves and others learned by training of SSRU library. Most users used the online news clipping database one time per month at home and always used the service for general knowledge, up-to-date academic knowledge and assignment reference. Moreover, the results of using the online news clipping service problems include the users themselves, service management, service device- computer and tools – and the network, service provider, and publicity. This research would be benefit for librarians and teachers for planning and designing library services in their works and organization
Keywords: Online Database, User Behaviour.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1614365 Manodharmam: A Scientific Methodology for Improvisation and Cognition in Carnatic Music
Authors: Raghavi Janaswamy, Saraswathi K. Vasudev
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Music is ubiquitous in human lives. Ever since the foetus hears the sound inside the mother’s womb and later upon birth the baby experiences alluring sounds, the curiosity of learning emanates and evokes exploration. Music is an education than a mere entertainment. The intricate balance between music, education and entertainment has well been recognized by the scientific community and is being explored as a viable tool to understand and improve the human cognition. There are seven basic swaras (notes) Sa, Ri, Ga, Ma, Pa, Da and Ni in the Carnatic music system that are analogous to C, D, E, F, G, A and B of the western system. The Carnatic music builds on the conscious use of microtones, gamakams (oscillation) and rendering styles that evolved over centuries and established its stance. The complex but erudite raga system has been designed with elaborate experiments on srutis (musical sounds) and human perception abilities. In parallel, ‘rasa’- the emotions evoked by certain srutis and hence the ragas been solidified along with the power of language in combination with the musical sounds. The Carnatic music branches out as Kalpita sangeetam (pre-composed music) and Manodharma sangeetam (improvised music). This article explores the Manodharma sangeetam and its subdivisions such as raga alapana, swara kalpana, neraval and ragam-tanam-pallavi (RTP). The intrinsic mathematical strategies in its practice methods toward improvising the music have been discussed in detail with concert examples. The techniques on swara weaving for swara kalpana rendering and methods on the alapana development are also discussed at length with an emphasis on the impact on the human cognitive abilities. The articulation of the outlined conscious practice methods not only helps to leave a long-lasting melodic impression on the listeners but also onsets cognitive developments.
Keywords: Carnatic, Manodharmam, music cognition, Alapana.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 605364 Awareness Level of Green Computing among Computer Users in Kebbi State, Nigeria
Authors: A. Mubarak, A. I. Augie
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This study investigated the awareness level of green computing possessed by computer users in Kebbi state. Survey method was employed to carry out the study. The study involved computer users from ICT business/training centers around Argungu and Birnin Kebbi areas of Kebbi state. Purposive sampling method was used to draw 156 respondents that volunteer to answer the questionnaire administered for gathering the data of the study. Out of the 156 questionnaires distributed, 121 were used for data analysis. In all, 79 respondents were from Argungu, while 42 were from Birnin Kebbi. The two research questions of the study were answered with descriptive statistic (percentage), and inferential statistics (ANOVA). The findings showed that the most of the computer users do not possess adequate awareness on conscious use of computing system. Also, the study showed that there is no significant difference regarding the consciousness of green computing possesses among computer users in Argungu and Birnin Kebbi. Based on these findings, the study suggested among others an aggressive campaign on green computing practice among computer users in Kebbi state.
Keywords: Green computing, awareness, information technology, Energy Star.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 635363 Determining Factors for ISO14001 EMS Implementation among SMEs in Malaysia: A Resource Based View
Authors: Goh Yen Nee
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This research aimed to find out the determining factors for ISO 14001 EMS implementation among SMEs in Malaysia from the Resource based view. A cross-sectional approach using survey was conducted. A research model been proposed which comprises of ISO 14001 EMS implementation as the criterion variable while physical capital resources (i.e. environmental performance tracking and organizational infrastructures), human capital resources (i.e. top management commitment and support, training and education, employee empowerment and teamwork) and organizational capital resources (i.e. recognition and reward, organizational culture and organizational communication) as the explanatory variables. The research findings show that only environmental performance tracking, top management commitment and support and organizational culture are found to be positively and significantly associated with ISO 14001 EMS implementation. It is expected that this research will shed new knowledge and provide a base for future studies about the role played by firm-s internal resources.Keywords: ISO 14001 Environmental Management System, Malaysia, Resource based view, SMEs
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3530362 Using Support Vector Machine for Prediction Dynamic Voltage Collapse in an Actual Power System
Authors: Muhammad Nizam, Azah Mohamed, Majid Al-Dabbagh, Aini Hussain
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This paper presents dynamic voltage collapse prediction on an actual power system using support vector machines. Dynamic voltage collapse prediction is first determined based on the PTSI calculated from information in dynamic simulation output. Simulations were carried out on a practical 87 bus test system by considering load increase as the contingency. The data collected from the time domain simulation is then used as input to the SVM in which support vector regression is used as a predictor to determine the dynamic voltage collapse indices of the power system. To reduce training time and improve accuracy of the SVM, the Kernel function type and Kernel parameter are considered. To verify the effectiveness of the proposed SVM method, its performance is compared with the multi layer perceptron neural network (MLPNN). Studies show that the SVM gives faster and more accurate results for dynamic voltage collapse prediction compared with the MLPNN.Keywords: Dynamic voltage collapse, prediction, artificial neural network, support vector machines
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1804361 Improvement in Power Transformer Intelligent Dissolved Gas Analysis Method
Authors: S. Qaedi, S. Seyedtabaii
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Non-Destructive evaluation of in-service power transformer condition is necessary for avoiding catastrophic failures. Dissolved Gas Analysis (DGA) is one of the important methods. Traditional, statistical and intelligent DGA approaches have been adopted for accurate classification of incipient fault sources. Unfortunately, there are not often enough faulty patterns required for sufficient training of intelligent systems. By bootstrapping the shortcoming is expected to be alleviated and algorithms with better classification success rates to be obtained. In this paper the performance of an artificial neural network, K-Nearest Neighbour and support vector machine methods using bootstrapped data are detailed and shown that while the success rate of the ANN algorithms improves remarkably, the outcome of the others do not benefit so much from the provided enlarged data space. For assessment, two databases are employed: IEC TC10 and a dataset collected from reported data in papers. High average test success rate well exhibits the remarkable outcome.Keywords: Dissolved gas analysis, Transformer incipient fault, Artificial Neural Network, Support Vector Machine (SVM), KNearest Neighbor (KNN)
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