Search results for: machine tool.

Authors: C. Gunavathi, K. Premalatha

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Tumor classification is a key area of research in the field of bioinformatics. Microarray technology is commonly used in the study of disease diagnosis using gene expression levels. The main drawback of gene expression data is that it contains thousands of genes and a very few samples. Feature selection methods are used to select the informative genes from the microarray. These methods considerably improve the classification accuracy. In the proposed method, Genetic Algorithm (GA) is used for effective feature selection. Informative genes are identified based on the T-Statistics, Signal-to-Noise Ratio (SNR) and F-Test values. The initial candidate solutions of GA are obtained from top-m informative genes. The classification accuracy of k-Nearest Neighbor (kNN) method is used as the fitness function for GA. In this work, kNN and Support Vector Machine (SVM) are used as the classifiers. The experimental results show that the proposed work is suitable for effective feature selection. With the help of the selected genes, GA-kNN method achieves 100% accuracy in 4 datasets and GA-SVM method achieves in 5 out of 10 datasets. The GA with kNN and SVM methods are demonstrated to be an accurate method for microarray based tumor classification.

Keywords: F-Test, Gene Expression, Genetic Algorithm, k- Nearest-Neighbor, Microarray, Signal-to-Noise Ratio, Support Vector Machine, T-statistics, Tumor Classification.

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Authors: Jameela Ali Alkrimi, Loay E. George, Azizah Suliman, Abdul Rahim Ahmad, Karim Al-Jashamy

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Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. Anemia is a lack of RBCs is characterized by its level compared to the normal hemoglobin level. In this study, a system based image processing methodology was developed to localize and extract RBCs from microscopic images. Also, the machine learning approach is adopted to classify the localized anemic RBCs images. Several textural and geometrical features are calculated for each extracted RBCs. The training set of features was analyzed using principal component analysis (PCA). With the proposed method, RBCs were isolated in 4.3secondsfrom an image containing 18 to 27 cells. The reasons behind using PCA are its low computation complexity and suitability to find the most discriminating features which can lead to accurate classification decisions. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network RBFNN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained within short time period, and the results became better when PCA was used.

Keywords: Red blood cells, pre-processing image algorithms, classification algorithms, principal component analysis PCA, confusion matrix, kappa statistical parameters, ROC.

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Authors: Michael Amberg, Dipl. Kfm. Johannes C. Panitz

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Compliance requires an effective communication within an enterprise as well as towards a company-s external environment. This requirement commences with the implementation of compliance within large scale compliance projects and still persists in the compliance reporting within standard operations. On the one hand the understanding of compliance necessities within the organization is promoted. On the other hand reduction of asymmetric information with compliance stakeholders is achieved. To reach this goal, a central reporting must provide a consolidated view of different compliance efforts- statuses. A concept which could be adapted for this purpose is the balanced scorecard by Kaplan / Norton. This concept has not been analyzed in detail concerning its adequacy for a holistic compliance reporting starting in compliance projects until later usage in regularly compliance operations. At first, this paper evaluates if a holistic compliance reporting can be designed by using the balanced scorecard concept. The current status of compliance reporting clearly shows that scorecards are generally accepted as a compliance reporting tool and are already used for corporate governance reporting. Additional specialized compliance IT - solutions exist in the market. After the scorecard-s adequacy is thoroughly examined and proofed, an example strategy map as the basis to derive a compliance balanced scorecard is defined. This definition answers the question on proceeding in designing a compliance reporting tool.

Keywords: Balanced Scorecard, Compliance, ComplianceReporting, Compliance Scorecard.

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Authors: D. E. Gourgoulis, C. G. Yakinthos, M. G. Vassiliadou

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With high speed vessels getting ever more sophisti-cated, travelling at higher and higher speeds and operating in With high speed vessels getting ever more sophisticated, travelling at higher and higher speeds and operating in areas of high maritime traffic density, training becomes of the highest priority to ensure that safety levels are maintained, and risks are adequately mitigated. Training onboard the actual craft on the actual route still remains the most effective way for crews to gain experience. However, operational experience and incidents during the last 10 years demonstrate the need for supplementary training whether in the area of simulation or man to man, man/ machine interaction. Training and familiarisation of the crew is the most important aspect in preventing incidents. The use of simulator, computer and web based training systems in conjunction with onboard training focusing on critical situations will improve the man machine interaction and thereby reduce the risk of accidents. Today, both ship simulator and bridge teamwork courses are now becoming the norm in order to improve further emergency response and crisis management skills. One of the main causes of accidents is the human factor. An efficient way to reduce human errors is to provide high-quality training to the personnel and to select the navigators carefully.areas of high maritime traffic density, training becomes of the highest priority to ensure that safety levels are maintained, and risks are adequately mitigated. Training onboard the actual craft on the actual route still remains the most effective way for crews to gain experience. How-ever, operational experience and incidents during the last 10 years demonstrate the need for supplementary training whether in the area of simulation or man to man, man/ machine interaction. Training and familiarisation of the crew is the most important aspect in preventing incidents. The use of simulator, computer and web based training systems in conjunction with onboard training focusing on critical situations will improve the man machine interaction and thereby reduce the risk of accidents. Today, both ship simulator and bridge teamwork courses are now becoming the norm in order to improve further emergency response and crisis management skills. One of the main causes of accidents is the human factor. An efficient way to reduce human errors is to provide high-quality training to the person-nel and to select the navigators carefully. KeywordsCBT - WBT systems, Human factors.

Keywords: CBT - WBT systems, Human factors.

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Authors: Ali Sarosh, Dong Yun-Feng, Muhammad Umer

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Fully reusable spaceplanes do not exist as yet. This implies that design-qualification for optimized highly-integrated forebody-inlet configuration of booster-stage vehicle cannot be based on archival data of other spaceplanes. Therefore, this paper proposes a novel TIPSO-SVM expert system methodology. A non-trivial problem related to optimization and classification of hypersonic forebody-inlet configuration in conjunction with mass-model of the two-stage-to-orbit (TSTO) vehicle is solved. The hybrid-heuristic machine learning methodology is based on two-step improved particle swarm optimizer (TIPSO) algorithm and two-step support vector machine (SVM) data classification method. The efficacy of method is tested by first evolving an optimal configuration for hypersonic compression system using TIPSO algorithm; thereafter, classifying the results using two-step SVM method. In the first step extensive but non-classified mass-model training data for multiple optimized configurations is segregated and pre-classified for learning of SVM algorithm. In second step the TIPSO optimized mass-model data is classified using the SVM classification. Results showed remarkable improvement in configuration and mass-model along with sizing parameters.

Keywords: TIPSO-SVM expert system, TIPSO algorithm, two-step SVM method, aerothermodynamics, mass-modeling, TSTO vehicle.

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Authors: Mia Sorensen

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The introduction of haptic elements in a graphic user interfaces are becoming more widespread. Since haptics are being introduced rapidly into computational tools, investigating how these models affect Human-Computer Interaction would help define how to integrate and model new modes of interaction. The interest of this paper is to discuss and investigate the issues surrounding Haptic and Graphic User Interface designs (GUI) as separate systems, as well as understand how these work in tandem. The development of these systems is explored from a psychological perspective, based on how usability is addressed through learning and affordances, defined by J.J. Gibson. Haptic design can be a powerful tool, aiding in intuitive learning. The problems discussed within the text is how can haptic interfaces be integrated within a GUI without the sense of frivolity. Juxtaposing haptics and Graphic user interfaces has issues of motivation; GUI tends to have a performatory process, while Haptic Interfaces use affordances to learn tool use. In a deeper view, it is noted that two modes of perception, foveal and ambient, dictate perception. These two modes were once thought to work in tandem, however it has been discovered that these processes work independently from each other. Foveal modes interpret orientation is space which provide for posture, locomotion, and motor skills with variations of the sensory information, which instructs perceptions of object-task performance. It is contended, here, that object-task performance is a key element in the use of Haptic Interfaces because exploratory learning uses affordances in order to use an object, without meditating an experience cognitively. It is a direct experience that, through iteration, can lead to skill-sets. It is also indicated that object-task performance will not work as efficiently without the use of exploratory or kinesthetic learning practices. Therefore, object-task performance is not as congruently explored in GUI than it is practiced in Haptic interfaces.

Keywords: Affordances, Graphic User Interface, HapticInterfaces, Tool-Use, Object-Naming, Object-Task Performance

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Authors: Gurinder Singh Brar, Sarbjeet Singh, Harry Garg

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Wire Electric Discharge Machining (WEDM) is thermal machining process capable of machining very hard electrically conductive material irrespective of their hardness. WEDM is being widely used to machine micro scale parts with the high dimensional accuracy and surface finish. The objective of this paper is to optimize the process parameters of wire EDM to fabricate the micro channels and to calculate the surface finish and material removal rate of micro channels fabricated using wire EDM. The material used is aluminum 6061 alloy. The experiments were performed using CNC wire cut electric discharge machine. The effect of various parameters of WEDM like pulse on time (TON) with the levels (100, 150, 200), pulse off time (TOFF) with the levels (25, 35, 45) and current (IP) with the levels (105, 110, 115) were investigated to study the effect on output parameter i.e. Surface Roughness and Material Removal Rate (MRR). Each experiment was conducted under different conditions of pulse on time, pulse off time and peak current. For material removal rate, TON and Ip were the most significant process parameter. MRR increases with the increase in TON and Ip and decreases with the increase in TOFF. For surface roughness, TON and Ip have the maximum effect and TOFF was found out to be less effective.

Keywords: Micro Channels, Wire Electric Discharge Machining (WEDM), Metal Removal Rate (MRR), Surface Finish.

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Authors: Mahnaz Hosseinzadeh, Shaghayegh Rezaee Amiri

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This paper presents a methodology for serial production planning problem in wire and cable manufacturing process that addresses the problem of input-output imbalance in different consecutive stations, hoping to minimize the halt of machines in each stage. To this end, a linear Goal Programming (GP) model is developed, in which four main categories of constraints as per the number of runs per machine, machines’ sequences, acceptable inventories of machines at the end of each period, and the necessity of fulfillment of the customers’ orders are considered. The model is formulated based upon on the real data obtained from IKO TAK Company, an important supplier of wire and cable for oil and gas and automotive industries in Iran. By solving the model in GAMS software the optimal number of runs, end-of-period inventories, and the possible minimum idle time for each machine are calculated. The application of the numerical results in the target company has shown the efficiency of the proposed model and the solution in decreasing the lead time of the end product delivery to the customers by 20%. Accordingly, the developed model could be easily applied in wire and cable companies for the aim of optimal production planning to reduce the halt of machines in manufacturing stages.

Keywords: Serial manufacturing process, production planning, wire and cable industry, goal programming approach.

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Authors: D. Zabala, Y. Cárdenas, G. Núñez

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In this work the numerical simulation of transient heat transfer in a cylindrical probe is done. An experiment was conducted introducing a steel cylinder in a heating chamber and registering its surface temperature along the time during one hour. In parallel, a mathematical model was solved for one dimension transient heat transfer in cylindrical coordinates, considering the boundary conditions of the test. The model was solved using finite difference method, because the thermal conductivity in the cylindrical steel bar and the convection heat transfer coefficient used in the model are considered temperature dependant functions, and both conditions prevent the use of the analytical solution. The comparison between theoretical and experimental results showed the average deviation is below 2%. It was concluded that numerical methods are useful in order to solve engineering complex problems. For constant k and h, the experimental methodology used here can be used as a tool for teaching heat transfer in mechanical engineering, using mathematical simplified models with analytical solutions.

Keywords: Heat transfer experiment, thermal conductivity, finite difference, engineering education.

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Authors: Suppara Charoenpoom

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The objectives of this research was to design and develop a quality management of the school buildings and environment. A quantitative and qualitative mixed research methodology was used. The population sample included 14 directors of primary schools. Two research tools were used. The first research tool included an in-depth interview and questionnaire. The second research tool included the Quality Business Process and Quality Work Procedure, and a Key Performance Indicator of each activity. The statistics included mean and standard deviation. The findings for the development of a quality management process of buildings and environment administration of the basic schools consisted of one quality business process (QBP) and seven quality work processes (QWP). The result from the experts’ evaluation revealed that the process and implementation of quality management of the school buildings and environment has passed the inspection process with consensus. This implies that the process of quality management of the school buildings and environment is suitable for implementation. Moreover, the level of agreement in the feasibility of the implementation of this plan had the mean in the range of 0.64-1.00 which suggests the design of the new plan is acceptable.

Keywords: Process, Building, Environment.

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Authors: Obaidullah Nadeem, Rizwan Hameed

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The preparation of good-quality Environmental Impact Assessment (EIA) reports contribute to enhancing overall effectiveness of EIA. This component of the EIA process becomes more important in situation where public participation is weak and there is lack of expertise on the part of the competent authority. In Pakistan, EIA became mandatory for every project likely to cause adverse environmental impacts from July 1994. The competent authority also formulated guidelines for preparation and review of EIA reports in 1997. However, EIA is yet to prove as a successful decision support tool to help in environmental protection. One of the several reasons of this ineffectiveness is the generally poor quality of EIA reports. This paper critically reviews EIA reports of some randomly selected projects. Interviews of EIA consultants, project proponents and concerned government officials have also been conducted to underpin the root causes of poor quality of EIA reports. The analysis reveals several inadequacies particularly in areas relating to identification, evaluation and mitigation of key impacts and consideration of alternatives. The paper identifies some opportunities and suggests measures for improving the quality of EIA reports and hence making EIA an effective tool to help in environmental protection.

Keywords: Environmental Impact Assessment, EIA Guidelines, EIA Reports, Pakistan.

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Authors: Jiří Pavelka

Abstract:

The study is based on the assumption that media products are appropriate subjects for the exploration of social and cultural identities as a keystone of value orientations of their authors, producers and target audiences. The research object of the study is the title page of the book cover of a professional publication that serves as a medium of marketing, scientific and intercultural communication, which is the result of semiotic and intercultural transfer. The study aims to answer the question whether the book cover is an expression of conceptualization and tool for social identity construction. It attempts to determine what value orientations and what concepts of social and cultural identities are hidden in the narrative structures of the book cover of the Czech translation of the book by G. Ritzer The McDonaldization of Society (1993), issued after the fall of the iron curtain in 1996 in the Czech Republic.

Keywords: Social and cultural identity, book cover, marketing communication, semiotic and intercultural transfer, narrative structure, the McDonaldisation of Society.

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Authors: Z. M. Najmi

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Over the years, the question around Artificial Intelligence has always been one with many answers. Whether by means of use in business and industry or complicated algorithmic programming, management of these technologies has always been the core focus. More recently, technologies have been questioned in industry and society alike as to whether they have improved human-centred design, assisted choices and objectives, and had a hand in systematic processes across the board. With these questions the answer may lie within AI technologies, and the steps needed in removing common human error. Elements such as Machine Learning, Deep Learning, Recommender Systems and Natural Language Processing will all be features to consider moving forward. Our previous intervention with AI applications has resulted in increased productivity, however, raised concerns for the continuation of traditional human-centred occupations. Emerging technologies such as Augmented Reality and Virtual Reality have all played a part in this during AI’s prominent rise. As mentioned, AI has been constantly under the microscope; the benefits and drawbacks may seem endless is wide, but AI is something we must take notice of and adapt into our everyday lives. The aim of this paper is to give an overview of the technologies surrounding A.I. and its’ related technologies. A comprehensive review has been written as a timeline of the developing events and key points in the history of Artificial Intelligence. This research is gathered entirely from secondary research, academic statements of knowledge and gathered to produce an understanding of the timeline of AI.

Keywords: Artificial Intelligence, Deep Learning, Augmented Reality, Reinforcement Learning, Machine Learning, Supervised Learning.

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Authors: Kemal Polat

Abstract:

In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset.

Keywords: Fuzzy C-means clustering, Fuzzy C-means clustering based attribute weighting, Pima Indians diabetes dataset, SVM.

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Authors: Lambros V. Skarlas, Grigorios N. Beligiannis, Efstratios F. Georgopoulos, Adam V. Adamopoulos

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The aim of this contribution is to present a new approach in modeling the electrical activity of the human heart. A recurrent artificial neural network is being used in order to exhibit a subset of the dynamics of the electrical behavior of the human heart. The proposed model can also be used, when integrated, as a diagnostic tool of the human heart system. What makes this approach unique is the fact that every model is being developed from physiological measurements of an individual. This kind of approach is very difficult to apply successfully in many modeling problems, because of the complexity and entropy of the free variables describing the complex system. Differences between the modeled variables and the variables of an individual, measured at specific moments, can be used for diagnostic purposes. The sensor fusion used in order to optimize the utilization of biomedical sensors is another point that this paper focuses on. Sensor fusion has been known for its advantages in applications such as control and diagnostics of mechanical and chemical processes.

Keywords: Artificial Neural Networks, Diagnostic System, Health Condition Modeling Tool, Heart Diagnostics Model, Heart Electricity Model.

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Authors: Thitaporn Thoopputra, Tipaporn Pongmesa, Shuchuen Li

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Aims: To evaluate the application of non-invasive diabetes risk assessment tool in community pharmacy setting. Methods: Thai diabetes risk score was applied to assess individuals at risk of developing type 2 diabetes. Interactive computer-based risk screening (IT) and paper-based risk screening (PT) tools were applied. Participants aged over 25 years with no known diabetes were recruited in six participating pharmacies. Results: A total of 187 clients, mean aged (+SD) was 48.6 (+10.9) years. 35% were at high risk. The mean value of willingness-to-pay for the service fee in IT group was significantly higher than PT group (p=0.013). No significant difference observed for the satisfaction between groups. Conclusions: Non-invasive risk assessment tool, whether paper-based or computerized-based can be applied in community pharmacy to support the enhancing role of pharmacists in chronic disease management. Long term follow up is needed to determine the impact of its application in clinical, humanistic and economic outcomes.

Keywords: Community pharmacy, intervention, prevention, risk assessment, type 2 diabetes.

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Authors: Wafa' S.Al-Sharafat, Reyadh Naoum

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Society has grown to rely on Internet services, and the number of Internet users increases every day. As more and more users become connected to the network, the window of opportunity for malicious users to do their damage becomes very great and lucrative. The objective of this paper is to incorporate different techniques into classier system to detect and classify intrusion from normal network packet. Among several techniques, Steady State Genetic-based Machine Leaning Algorithm (SSGBML) will be used to detect intrusions. Where Steady State Genetic Algorithm (SSGA), Simple Genetic Algorithm (SGA), Modified Genetic Algorithm and Zeroth Level Classifier system are investigated in this research. SSGA is used as a discovery mechanism instead of SGA. SGA replaces all old rules with new produced rule preventing old good rules from participating in the next rule generation. Zeroth Level Classifier System is used to play the role of detector by matching incoming environment message with classifiers to determine whether the current message is normal or intrusion and receiving feedback from environment. Finally, in order to attain the best results, Modified SSGA will enhance our discovery engine by using Fuzzy Logic to optimize crossover and mutation probability. The experiments and evaluations of the proposed method were performed with the KDD 99 intrusion detection dataset.

Keywords: MSSGBML, Network Intrusion Detection, SGA, SSGA.

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Authors: S. Lgarch, M. Khalidi Idrissi, S. Bennani

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For best collaboration, Asynchronous tools and particularly the discussion forums are the most used thanks to their flexibility in terms of time. To convey only the messages that belong to a theme of interest of the tutor in order to help him during his tutoring work, use of a tool for classification of these messages is indispensable. For this we have proposed a semantics classification tool of messages of a discussion forum that is based on LSA (Latent Semantic Analysis), which includes a thesaurus to organize the vocabulary. Benefits offered by formal ontology can overcome the insufficiencies that a thesaurus generates during its use and encourage us then to use it in our semantic classifier. In this work we propose the use of some functionalities that a OWL ontology proposes. We then explain how functionalities like “ObjectProperty", "SubClassOf" and “Datatype" property make our classification more intelligent by way of integrating new terms. New terms found are generated based on the first terms introduced by tutor and semantic relations described by OWL formalism.

Keywords: Classification of messages, collaborative communication tools, discussion forum, e-learning, formal description, latente semantic analysis, ontology, owl, semantic relations, semantic web, thesaurus, tutoring.

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Authors: J. P. Dubois, O. M. Abdul-Latif

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Support Vector Machine (SVM) is a recent class of statistical classification and regression techniques playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM is applied to an infrared (IR) binary communication system with different types of channel models including Ricean multipath fading and partially developed scattering channel with additive white Gaussian noise (AWGN) at the receiver. The structure and performance of SVM in terms of the bit error rate (BER) metric is derived and simulated for these channel stochastic models and the computational complexity of the implementation, in terms of average computational time per bit, is also presented. The performance of SVM is then compared to classical binary signal maximum likelihood detection using a matched filter driven by On-Off keying (OOK) modulation. We found that the performance of SVM is superior to that of the traditional optimal detection schemes used in statistical communication, especially for very low signal-to-noise ratio (SNR) ranges. For large SNR, the performance of the SVM is similar to that of the classical detectors. The implication of these results is that SVM can prove very beneficial to IR communication systems that notoriously suffer from low SNR at the cost of increased computational complexity.

Keywords: Least square-support vector machine, on-off keying, matched filter, maximum likelihood detector, wireless infrared communication.

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Authors: Arun Goel

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The present paper attempts to investigate the prediction of air entrainment rate and aeration efficiency of a free overfall jets issuing from a triangular sharp crested weir by using regression based modelling. The empirical equations, Support vector machine (polynomial and radial basis function) models and the linear regression techniques were applied on the triangular sharp crested weirs relating the air entrainment rate and the aeration efficiency to the input parameters namely drop height, discharge, and vertex angle. It was observed that there exists a good agreement between the measured values and the values obtained using empirical equations, Support vector machine (Polynomial and rbf) models and the linear regression techniques. The test results demonstrated that the SVM based (Poly & rbf) model also provided acceptable prediction of the measured values with reasonable accuracy along with empirical equations and linear regression techniques in modelling the air entrainment rate and the aeration efficiency of a free overfall jets issuing from triangular sharp crested weir. Further sensitivity analysis has also been performed to study the impact of input parameter on the output in terms of air entrainment rate and aeration efficiency.

Keywords: Air entrainment rate, dissolved oxygen, regression, SVM, weir.

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Authors: Kawpong Polyorat, Nathamon Buaprommee

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Because of the outbreak of mad cow disease and bird flu, consumers have become more concerned with quality and safety of meat and poultry. As a consequence, meat traceability has been implemented as a tool to raise the standard in the meat production industry. In Thailand, while traceability is relatively common among the manufacturer-wholesaler-retailers cycle, it is rarely used as a marketing tool specifically designed to persuade consumers who are the actual meat endusers. Therefore, the present study attempts to understand what influences consumers to spread their words-of-mouth (WOM) regarding meat with traceability by conducting a study in Thailand where research in this area is rather scant. Data were collected from one hundred and sixty-seven consumers in the northeastern region and analyzed with SEM. The study results reveal that perceived usefulness of traceability system, social norms, and product class knowledge are significant antecedents where consumers spread positive words regarding meat with traceability system. A number of theoretical and managerial implications as well as future study directions are offered at the end of this study report.

Keywords: Perceived usefulness, product knowledge, social norms, traceability, word-of-mouth,

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Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

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Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD, as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches, such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: Autism spectrum disorder, clustering, optimization, unsupervised machine learning.

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Authors: Md. Anayet U. Patwari, Mohammad Ahsan Habib, Md. Tanzib Ehsan, Md Golam Ahnaf, Md. S. I. Chowdhury

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Surface roughness is one of the key quality parameters of the finished product. During any machining operation, high temperatures are generated at the tool-chip interface impairing surface quality and dimensional accuracy of products. Cutting fluids are generally applied during machining to reduce temperature at the tool-chip interface. However, usages of cutting fluids give rise to problems such as waste disposal, pollution, high cost, and human health hazard. Researchers, now-a-days, are opting towards dry machining and other cooling techniques to minimize use of coolants during machining while keeping surface roughness of products within desirable limits. In this paper, a concept of using peltier cooling effects during aluminium milling operation has been presented and adopted with an aim to improve surface roughness of the machined surface. Experimental evidence shows that peltier cooling effect provides better surface roughness of the machined surface compared to dry machining.

Keywords: Aluminium, surface roughness, Peltier cooling effect, milling operation.

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Authors: Priya Sepaha

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Social media has loomed as the most effective tool in recent times to flag the causes, contents, opinions and direction of any social movement and has demonstrated that it will have a far-reaching effect on government as well. This study focuses on India which has emerged as the fastest growing community on social media. Social movement activists, in particular, have extensively utilized the power of digital social media to streamline the effectiveness of social protest on a particular issue through extensive successful mass mobilizations. This research analyses the role and impact of social media as a power to catalyze the social movements in India and further seeks to describe how certain social movements are resisted, subverted, co-opted and/or deployed by social media. The impact assessment study has been made with the help of cases, policies and some social movement which India has witnessed the assertion of numerous social issues perturbing the public which eventually paved the way for remarkable judicial decisions. The paper concludes with the observations that despite its pros and cons, the impacts of social media on the functioning of the Indian Government have demonstrated that it has already become an indispensable tool in the hands of social media-suave Indians who are committed to bring about a desired change.

Keywords: Impact, Indian government, misuse, social media, social movement.

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Authors: Ahmad Fadel Klaib, Zurinahni Zainol, Nurul Hashimah Ahamed, Rosma Ahmad, Wahidah Hussin

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Bioinformatics and Cheminformatics use computer as disciplines providing tools for acquisition, storage, processing, analysis, integrate data and for the development of potential applications of biological and chemical data. A chemical database is one of the databases that exclusively designed to store chemical information. NMRShiftDB is one of the main databases that used to represent the chemical structures in 2D or 3D structures. SMILES format is one of many ways to write a chemical structure in a linear format. In this study we extracted Antimicrobial Structures in SMILES format from NMRShiftDB and stored it in our Local Data Warehouse with its corresponding information. Additionally, we developed a searching tool that would response to user-s query using the JME Editor tool that allows user to draw or edit molecules and converts the drawn structure into SMILES format. We applied Quick Search algorithm to search for Antimicrobial Structures in our Local Data Ware House.

Keywords: Exact String-matching Algorithms, NMRShiftDB, SMILES Format, Antimicrobial Structures.

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Authors: Talbi Mourad, Salhi Lotfi, Chérif Adnen

Abstract:

In this work, we are interested in developing a speech denoising tool by using a discrete wavelet packet transform (DWPT). This speech denoising tool will be employed for applications of recognition, coding and synthesis. For noise reduction, instead of applying the classical thresholding technique, some wavelet packet nodes are set to zero and the others are thresholded. To estimate the non stationary noise level, we employ the spectral entropy. A comparison of our proposed technique to classical denoising methods based on thresholding and spectral subtraction is made in order to evaluate our approach. The experimental implementation uses speech signals corrupted by two sorts of noise, white and Volvo noises. The obtained results from listening tests show that our proposed technique is better than spectral subtraction. The obtained results from SNR computation show the superiority of our technique when compared to the classical thresholding method using the modified hard thresholding function based on u-law algorithm.

Keywords: Enhancement, spectral subtraction, SNR, discrete wavelet packet transform, spectral entropy Histogram

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Authors: P. R. Prabhu, S. M. Kulkarni, S. S. Sharma

Abstract:

Deep cold rolling (DCR) is a cold working process, which easily produces a smooth and work-hardened surface by plastic deformation of surface irregularities. In the present study, the influence of main deep cold rolling process parameters on the surface roughness and the hardness of AISI 4140 steel were studied by using fractional factorial design of experiments. The assessment of the surface integrity aspects on work material was done, in terms of identifying the predominant factor amongst the selected parameters, their order of significance and setting the levels of the factors for minimizing surface roughness and/or maximizing surface hardness. It was found that the ball diameter, rolling force, initial surface roughness and number of tool passes are the most pronounced parameters, which have great effects on the work piece-s surface during the deep cold rolling process. A simple, inexpensive and newly developed DCR tool, with interchangeable collet for using different ball diameters, was used throughout the experimental work presented in this paper.

Keywords: Deep cold rolling, design of experiments, surface hardness, surface roughness

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Authors: Zainal Abidin Akasah, Maizam Alias, Azuin Ramli

Abstract:

The safety and health performances aspects of a building are the most challenging aspect of facility management. It requires a deep understanding by the building managers on the factors that contribute to health and safety performances. This study attempted to develop an explanatory architectural safety performance model for stratified low-cost housing in Malaysia. The proposed Building Safety and Health Performance (BSHP) model was tested empirically through a survey on 308 construction practitioners using partial least squares (PLS) and structural equation modelling (SEM) tool. Statistical analysis results supports the conclusion that architecture, building services, external environment, management approaches and maintenance management have positive influence on safety and health performance of stratified low-cost housing in Malaysia. The findings provide valuable insights for construction industry to introduce BSHP model in the future where the model could be used as a guideline for training purposes of managers and better planning and implementation of building management.

Keywords: Building management, stratified low-cost housing, Safety and health model

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Authors: M. K. Pradhan, C. K. Biswas

Abstract:

In this research, Response Surface Methodology (RSM) is used to investigate the effect of four controllable input variables namely: discharge current, pulse duration, pulse off time and applied voltage Surface Roughness (SR) of on Electrical Discharge Machined surface. To study the proposed second-order polynomial model for SR, a Central Composite Design (CCD) is used to estimation the model coefficients of the four input factors, which are alleged to influence the SR in Electrical Discharge Machining (EDM) process. Experiments were conducted on AISI D2 tool steel with copper electrode. The response is modeled using RSM on experimental data. The significant coefficients are obtained by performing Analysis of Variance (ANOVA) at 5% level of significance. It is found that discharge current, pulse duration, and pulse off time and few of their interactions have significant effect on the SR. The model sufficiency is very satisfactory as the Coefficient of Determination (R2) is found to be 91.7% and adjusted R2-statistic (R2 adj ) 89.6%.

Keywords: Electrical discharge machining, surface roughness, response surface methodology, ANOVA, central composite design.

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Authors: R. Bernaoui, P. Ohly

Abstract:

Our research shows the use of the mobile phone that consolidates the relationship between veterinarians, and that between breeders and veterinarians. On the other hand it asserts that the tool in question is a means of economic development. The results of our survey reveal a positive return to the veterinary community, which shows that the mobile phone has become an effective means of sustainable development through the transfer of a rapid and punctual information inheritance via social networks; including many Internet applications. Our results show that almost all veterinarians use the mobile phone for interprofessional communication. We therefore believe that the use of the mobile phone by livestock operators has greatly improved the working conditions, just as the use of this tool contributes to a better management of the exploitation as long as it allows limit travel but also save time. These results show that we are witnessing a growth in the use of mobile telephony technologies that impact is as much in terms of sustainable development. Allowing access to information, especially technical information, the mobile phone, and Information and Communication of Technology (ICT) in general, give livestock sector players not only security, by limiting losses, but also an efficiency that allows them a better production and productivity.

Keywords: Algeria, Breeder-veterinarian, Digital Heritage, Networking, Mobile phone.

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