Search results for: Functional ability
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1690

Search results for: Functional ability

340 Computer Aided Docking Studies on Antiviral Drugs for SARS

Authors: Virupakshaiah DBM, Chandrakanth Kelmani, Rachanagouda Patil, Prasad Hegade

Abstract:

Severe acute respiratory syndrome (SARS) is a respiratory disease in humans which is caused by the SARS coronavirus. The treatment of coronavirus-associated SARS has been evolving and so far there is no consensus on an optimal regimen. The mainstream therapeutic interventions for SARS involve broad-spectrum antibiotics and supportive care, as well as antiviral agents and immunomodulatory therapy. The Protein- Ligand interaction plays a significant role in structural based drug designing. In the present work we have taken the receptor Angiotensin converting enzyme 2 and identified the drugs that are commonly used against SARS. They are Lopinavir, Ritonavir, Ribavirin, and Oseltamivir. The receptor Angiotensin converting enzyme 2 (ACE-2) was docked with above said drugs and the energy value obtained are as follows, Lopinavir (-292.3), Ritonavir (-325.6), Oseltamivir (- 229.1), Ribavirin (-208.8). Depending on the least energy value we have chosen the best two drugs out of the four conventional drugs. We tried to improve the binding efficiency and steric compatibility of the two drugs namely Ritonavir and Lopinavir. Several modifications were made to the probable functional groups (phenylic, ketonic groups in case of Ritonavir and carboxylic groups in case of Lopinavir respectively) which were interacting with the receptor molecule. Analogs were prepared by Marvin Sketch software and were docked using HEX docking software. Lopinavir analog 8 and Ritonavir analog 11 were detected with significant energy values and are probable lead molecule. It infers that some of the modified drugs are better than the original drugs. Further work can be carried out to improve the steric compatibility of the drug based upon the work done above for a more energy efficient binding of the drugs to the receptor.

Keywords: Protein data bank, Rasmol, Marvin sketch, Hexdocking.

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339 Computer Study of Cluster Mechanism of Anti-greenhouse Effect

Authors: A. Galashev

Abstract:

Absorption spectra of infra-red (IR) radiation of the disperse water medium absorbing the most important greenhouse gases: CO2 , N2O , CH4 , C2H2 , C2H6 have been calculated by the molecular dynamics method. Loss of the absorbing ability at the formation of clusters due to a reduction of the number of centers interacting with IR radiation, results in an anti-greenhouse effect. Absorption of O3 molecules by the (H2O)50 cluster is investigated at its interaction with Cl- ions. The splitting of ozone molecule on atoms near to cluster surface was observed. Interaction of water cluster with Cl- ions causes the increase of integrated intensity of emission spectra of IR radiation, and also essential reduction of the similar characteristic of Raman spectrum. Relative integrated intensity of absorption of IR radiation for small water clusters was designed. Dependences of the quantity of weight on altitude for vapor of monomers, clusters, droplets, crystals and mass of all moisture were determined. The anti-greenhouse effect of clusters was defined as the difference of increases of average global temperature of the Earth, caused by absorption of IR radiation by free water molecules forming clusters, and absorption of clusters themselves. The greenhouse effect caused by clusters makes 0.53 K, and the antigreenhouse one is equal to 1.14 K. The increase of concentration of CO2 in the atmosphere does not always correlate with the amplification of greenhouse effect.

Keywords: Greenhouse gases, infrared absorption and Raman spectra, molecular dynamics method, water clusters.

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338 Practical Design Procedures of 3D Reinforced Concrete Shear Wall-Frame Structure Based on Structural Optimization Method

Authors: H. Nikzad, S. Yoshitomi

Abstract:

This study investigates and develops the structural optimization method. The effect of size constraints on practical solution of reinforced concrete (RC) building structure with shear wall is proposed. Cross-sections of beam and column, and thickness of shear wall are considered as design variables. The objective function to be minimized is total cost of the structure by using a simple and efficient automated MATLAB platform structural optimization methodology. With modification of mathematical formulations, the result is compared with optimal solution without size constraints. The most suitable combination of section sizes is selected as for the final design application based on linear static analysis. The findings of this study show that defining higher value of upper bound of sectional sizes significantly affects optimal solution, and defining of size constraints play a vital role in finding of global and practical solution during optimization procedures. The result and effectiveness of proposed method confirm the ability and efficiency of optimal solutions for 3D RC shear wall-frame structure.

Keywords: Structural optimization, linear static analysis, ETABS, MATLAB, RC shear wall-frame structures.

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337 Designing an Editorialization Environment for Repeatable Self-Correcting Exercises

Authors: M. Kobylanski, D. Buskulic, P.-H. Duron, D. Revuz, F. Ruggieri, E. Sandier, C. Tijus

Abstract:

In order to design a cooperative e-learning platform, we observed teams of Teacher [T], Computer Scientist [CS] and exerciser's programmer-designer [ED] cooperating for the conception of a self-correcting exercise, but without the use of such a device in order to catch the kind of interactions a useful platform might provide. To do so, we first run a task analysis on how T, CS and ED should be cooperating in order to achieve, at best, the task of creating and implementing self-directed, self-paced, repeatable self-correcting exercises (RSE) in the context of open educational resources. The formalization of the whole process was based on the “objectives, activities and evaluations” theory of educational task analysis. Second, using the resulting frame as a “how-to-do it” guide, we run a series of three contrasted Hackathon of RSE-production to collect data about the cooperative process that could be later used to design the collaborative e-learning platform. Third, we used two complementary methods to collect, to code and to analyze the adequate survey data: the directional flow of interaction among T-CS-ED experts holding a functional role, and the Means-End Problem Solving analysis. Fourth, we listed the set of derived recommendations useful for the design of the exerciser as a cooperative e-learning platform. Final recommendations underline the necessity of building (i) an ecosystem that allows to sustain teams of T-CS-ED experts, (ii) a data safety platform although offering accessibility and open discussion about the production of exercises with their resources and (iii) a good architecture allowing the inheritance of parts of the coding of any exercise already in the data base as well as fast implementation of new kinds of exercises along with their associated learning activities.

Keywords: Distance open educational resources, pedagogical alignment, self-correcting exercises, teacher’s involvement, team roles.

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336 Impact of Flexibility on Patient Satisfaction and Behavioral Intention: A Critical Reassessment and Model Development

Authors: Pradeep Kumar, Shibashish Chakraborty, Sasadhar Bera

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In the anticipation of demand fluctuations, services cannot be inventoried and hence it creates a difficult problem in marketing of services. The inability to meet customers (patients) requirements in healthcare context has more serious consequences than other service sectors. In order to meet patient requirements in the current uncertain environment, healthcare organizations are seeking ways for improved service delivery. Flexibility provides a mechanism for reducing variability in service encounters and improved performance. Flexibility is defined as the ability of the organization to cope with changing circumstances or instability caused by the environment. Patient satisfaction is an important performance outcome of healthcare organizations. However, the paucity of information exists in healthcare delivery context to examine the impact of flexibility on patient satisfaction and behavioral intention. The present study is an attempt to develop a conceptual foundation for investigating overall impact of flexibility on patient satisfaction and behavioral intention. Several dimensions of flexibility in healthcare context are examined and proposed to have a significant impact on patient satisfaction and intention. Furthermore, the study involves a critical examination of determinants of patient satisfaction and development of a comprehensive view the relationship between flexibility, patient satisfaction and behavioral intention. Finally, theoretical contributions and implications for healthcare professionals are suggested from flexibility perspective.

Keywords: Healthcare, flexibility, patient satisfaction, behavioral intention.

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335 MPPT Operation for PV Grid-connected System using RBFNN and Fuzzy Classification

Authors: A. Chaouachi, R. M. Kamel, K. Nagasaka

Abstract:

This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW Photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three Radial Basis Function Neural Networks (RBFNN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated RBFNN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and non-linear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network.

Keywords: MPPT, neuro-fuzzy, RBFN, grid-connected, photovoltaic.

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334 Guidelines for Sustainable Urban Mobility in Historic Districts from International Experiences

Authors: Tamer ElSerafi

Abstract:

In recent approaches to heritage conservation, the whole context of historic areas becomes as important as the single historic building. This makes the provision of infrastructure and network of mobility an effective element in the urban conservation. Sustainable urban conservation projects consider the high density of activities, the need for a good quality access system to the transit system, and the importance of the configuration of the mobility network by identifying the best way to connect the different districts of the urban area through a complex unique system that helps the synergic development to achieve a sustainable mobility system. A sustainable urban mobility is a key factor in maintaining the integrity between socio-cultural aspects and functional aspects. This paper illustrates the mobility aspects, mobility problems in historic districts, and the needs of the mobility systems in the first part. The second part is a practical analysis for different mobility plans. It is challenging to find innovative and creative conservation solutions fitting modern uses and needs without risking the loss of inherited built resources. Urban mobility management is becoming an essential and challenging issue in the urban conservation projects. Depending on literature review and practical analysis, this paper tries to define and clarify the guidelines for mobility management in historic districts as a key element in sustainability of urban conservation and development projects. Such rules and principles could control the conflict between the socio–cultural and economic activities, and the different needs for mobility in these districts in a sustainable way. The practical analysis includes a comparison between mobility plans which have been implemented in four different cities; Freiburg in Germany, Zurich in Switzerland and Bray Town in Ireland. This paper concludes with a matrix of guidelines that considers both principles of sustainability and livability factors in urban historic districts.

Keywords: Sustainable mobility, urban mobility, mobility management, historic districts.

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333 The Effects of Mobile Phones in Mitigating Cultural Shock Amongst Refugees: Case of South Africa

Authors: Sarah Vuningoma, Maria Rosa Lorini, Wallace Chigona

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The potential of mobile phones is evident in their ability to address isolation and loneliness, support the improvement of interpersonal relations, and contribute to the facilitation of assimilation processes. Mobile phones can play a role in facilitating the integration of refugees into a new environment. This study aims to evaluate the impact of mobile phone use on helping refugees navigate the challenges posed by cultural differences in the host country. Semi-structured interviews were employed to collect data for the study, involving a sample size of 27 participants. Participants in the study were refugees based in South Africa, and thematic analysis was the chosen method for data analysis. The research highlights the numerous challenges faced by refugees in their host nation, including a lack of local cultural skills, the separation of family and friends from their countries of origin, hurdles in acquiring legal documentation, and the complexities of assimilating into the unfamiliar community. The use of mobile phones by refugees comes with several advantages, such as the advancement of language and cultural understanding, seamless integration into the host country, streamlined communication, and the exploration of diverse opportunities. Concurrently, mobile phones allow refugees in South Africa to manage the impact of culture shock.

Keywords: Mobile phones, culture shock, refugees, South Africa.

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332 EFL Teachers’ Metacognitive Awareness as a Predictor of Their Professional Success

Authors: Saeedeh Shafiee Nahrkhalaji

Abstract:

Metacognitive knowledge increases EFL students’ ability to be successful learners. Although this relationship has been investigated by a number of scholars, EFL teachers’ explicit awareness of their cognitive knowledge has not been sufficiently explored. The aim of this study was to examine the role of EFL teachers’ metacognitive knowledge in their pedagogical performance. Furthermore, the role played by years of their academic education and teaching experience was also studied. Fifty female EFL teachers were selected. They completed Metacognitive Awareness Inventory (MAI) that assessed six components of metacognition including procedural knowledge, declarative knowledge, conditional knowledge, planning, evaluating, and management strategies. Near the end of the academic semester, the students of each class filled in ‘the Language Teacher Characteristics Questionnaire’ to evaluate their teachers’ pedagogical performance. Four elements of MAI, declarative knowledge, planning, evaluating, and management strategies were found to be significantly correlated with EFL teachers’ pedagogical success. Significant correlation was also established between metacognitive knowledge and EFL teachers’ years of academic education and teaching experience. The findings obtained from this research have contributing implication for EFL teacher educators. The discussion concludes by setting out directions for future research.

Keywords: Metacognotive Knowledge, Pedagogical Performance, Language Teacher Characteristics Questionnaire, Metacognitive Awareness Inventory.

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331 Protein Production by Bacillus Subtilis Atcc 21332 in the Presence of Cymbopogon Essential Oils

Authors: Hanina M. N., Hairul Shahril M., Mohd Fazrullah Innsan M. F., Ismatul Nurul Asyikin I., Abdul Jalil A. K, Salina M. R., Ahmad I.B.

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Proteins levels produced by bacteria may be increased in stressful surroundings, such as in the presence of antibiotics. It appears that many antimicrobial agents or antibiotics, when used at low concentrations, have in common the ability to activate or repress gene transcription, which is distinct from their inhibitory effect. There have been comparatively few studies on the potential of antibiotics or natural compounds in nature as a specific chemical signal that can trigger a variety of biological functions. Therefore, this study was focusing on the effect of essential oils from Cymbopogon flexuosus and C. nardus in regulating proteins production by Bacillus subtilis ATCC 21332. The Minimum Inhibition Concentrations (MICs) of both essential oils on B. subtilis were determined by using microdilution assay, resulting 0.2% and 1.56% for each C. flexuosus and C. nardus subsequently. The bacteria were further exposed to each essential oils at concentration of 0.01XMIC for 2 days. The proteins were then isolated and analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). Protein profile showed that a band with approximate size of 250 kD was appeared for the treated bacteria with essential oils. Thus, Bacillus subtilis ATCC 21332 in stressful condition with the presence of essential oils at low concentration could induce the protein production.

Keywords: Bacillus subtilis ATCC 21332, Cymbopogon essential oils, protein

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330 The Impact of Motivation, Trust, and National Cultural Differences on Knowledge Sharing within the Context of Electronic Mail

Authors: Said Abdullah Al Saifi

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The goal of this research is to examine the impact of trust, motivation, and national culture on knowledge sharing within the context of electronic mail. This study is quantitative and survey based. In order to conduct the research, 200 students from a leading university in New Zealand were chosen randomly to participate in a questionnaire survey. Motivation and trust were found to be significantly and positively related to knowledge sharing. The research findings illustrated that face saving, face gaining, and individualism positively moderates the relationship between motivation and knowledge sharing. In addition, collectivism culture negatively moderates the relationship between motivation and knowledge sharing. Moreover, the research findings reveal that face saving, individualism, and collectivism culture positively moderate the relationship between trust and knowledge sharing. In addition, face gaining culture negatively moderates the relationship between trust and knowledge sharing. This study sets out several implications for researchers and practitioners. The study produces an integrative model that shows how attributes of national culture impact knowledge sharing through the use of emails. A better understanding of the relationship between knowledge sharing and trust, motivation, and national culture differences will increase individuals’ ability to make wise choices when sharing knowledge with those from different cultures.

Keywords: Knowledge sharing, motivation, national culture, trust.

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329 Atomic Force Microscopy (AFM)Topographical Surface Characterization of Multilayer-Coated and Uncoated Carbide Inserts

Authors: Samy E. Oraby, Ayman M. Alaskari

Abstract:

In recent years, scanning probe atomic force microscopy SPM AFM has gained acceptance over a wide spectrum of research and science applications. Most fields focuses on physical, chemical, biological while less attention is devoted to manufacturing and machining aspects. The purpose of the current study is to assess the possible implementation of the SPM AFM features and its NanoScope software in general machining applications with special attention to the tribological aspects of cutting tool. The surface morphology of coated and uncoated as-received carbide inserts is examined, analyzed, and characterized through the determination of the appropriate scanning setting, the suitable data type imaging techniques and the most representative data analysis parameters using the MultiMode SPM AFM in contact mode. The NanoScope operating software is used to capture realtime three data types images: “Height", “Deflection" and “Friction". Three scan sizes are independently performed: 2, 6, and 12 μm with a 2.5 μm vertical range (Z). Offline mode analysis includes the determination of three functional topographical parameters: surface “Roughness", power spectral density “PSD" and “Section". The 12 μm scan size in association with “Height" imaging is found efficient to capture every tiny features and tribological aspects of the examined surface. Also, “Friction" analysis is found to produce a comprehensive explanation about the lateral characteristics of the scanned surface. Configuration of many surface defects and drawbacks has been precisely detected and analyzed.

Keywords: SPM AFM contact mode, carbide inserts, scan size, surface defects, surface roughness, PSD.

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328 Meta Model for Optimum Design Objective Function of Steel Frames Subjected to Seismic Loads

Authors: Salah R. Al Zaidee, Ali S. Mahdi

Abstract:

Except for simple problems of statically determinate structures, optimum design problems in structural engineering have implicit objective functions where structural analysis and design are essential within each searching loop. With these implicit functions, the structural engineer is usually enforced to write his/her own computer code for analysis, design, and searching for optimum design among many feasible candidates and cannot take advantage of available software for structural analysis, design, and searching for the optimum solution. The meta-model is a regression model used to transform an implicit objective function into objective one and leads in turn to decouple the structural analysis and design processes from the optimum searching process. With the meta-model, well-known software for structural analysis and design can be used in sequence with optimum searching software. In this paper, the meta-model has been used to develop an explicit objective function for plane steel frames subjected to dead, live, and seismic forces. Frame topology is assumed as predefined based on architectural and functional requirements. Columns and beams sections and different connections details are the main design variables in this study. Columns and beams are grouped to reduce the number of design variables and to make the problem similar to that adopted in engineering practice. Data for the implicit objective function have been generated based on analysis and assessment for many design proposals with CSI SAP software. These data have been used later in SPSS software to develop a pure quadratic nonlinear regression model for the explicit objective function. Good correlations with a coefficient, R2, in the range from 0.88 to 0.99 have been noted between the original implicit functions and the corresponding explicit functions generated with meta-model.

Keywords: Meta-modal, objective function, steel frames, seismic analysis, design.

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327 The Risk Assessment of Nano-particles and Investigation of Their Environmental Impact

Authors: Nader Nabhani, Amir Tofighi

Abstract:

Nanotechnology is the science of creating, using and manipulating objects which have at least one dimension in range of 0.1 to 100 nanometers. In other words, nanotechnology is reconstructing a substance using its individual atoms and arranging them in a way that is desirable for our purpose. The main reason that nanotechnology has been attracting attentions is the unique properties that objects show when they are formed at nano-scale. These differing characteristics that nano-scale materials show compared to their nature-existing form is both useful in creating high quality products and dangerous when being in contact with body or spread in environment. In order to control and lower the risk of such nano-scale particles, the main following three topics should be considered: 1) First of all, these materials would cause long term diseases that may show their effects on body years after being penetrated in human organs and since this science has become recently developed in industrial scale not enough information is available about their hazards on body. 2) The second is that these particles can easily spread out in environment and remain in air, soil or water for very long time, besides their high ability to penetrate body skin and causing new kinds of diseases. 3) The third one is that to protect body and environment against the danger of these particles, the protective barriers must be finer than these small objects and such defenses are hard to accomplish. This paper will review, discuss and assess the risks that human and environment face as this new science develops at a high rate.

Keywords: Nanotechnology, risk assessment, environment.

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326 Influence of Culture Conditions on the Growth and Fatty Acid Composition of Green Microalgae Oocystis rhomboideus, Scenedesmus obliquus, Dictyochlorella globosa

Authors: Tatyana A. Karpenyuk, Saltanat B. Orazova, Yana S. Tzurkan, Alla V. Goncharova, Bakytzhan K. Kairat, Togzhan D. Mukasheva, Ludmila V. Ignatova, Ramza Z. Berzhanova

Abstract:

Microalgae due to the ability to accumulate high levels of practically valuable polyunsaturated fatty acids attract attention as a promising raw material for commercial products. The features of the growth processes of cells green protococcal microalgae Oocystis rhomboideus, Scenedesmus obliquus, Dictyochlorella globosa at cultivation in different nutritional mediums were determined. For the rapid accumulation of biomass, combined with high productivity of total lipids fraction yield recommended to use the Fitzgerald medium (Scenodesmus obliquus, Oocystis rhomboideus) and/or Bold medium (Dictyochlorella globosa). Productivity of lipids decreased in sequence Dictyochlorella globosa > Scenodesmus obliquus > Oocystis rhomboideus. The bulk of fatty acids fraction of the total lipids is unsaturated fatty acids, which ac­counts for 70 to 83% of the total number of fatty acids. The share of monoenic acids accounts from 18 to 34%, while the share of unsaturated fatty acids - from 44 to 62% of the total number of unsaturated fatty acids fraction. Among the un­saturated acids dominate α-linolenic acid (C18:3n-3), hexadecatetraenic acid (C16:4) and linoleic acid (C18:2).

Keywords: Fatty acids, lipids, microalgae.

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325 Comparison of Compression Ability Using DCT and Fractal Technique on Different Imaging Modalities

Authors: Sumathi Poobal, G. Ravindran

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Image compression is one of the most important applications Digital Image Processing. Advanced medical imaging requires storage of large quantities of digitized clinical data. Due to the constrained bandwidth and storage capacity, however, a medical image must be compressed before transmission and storage. There are two types of compression methods, lossless and lossy. In Lossless compression method the original image is retrieved without any distortion. In lossy compression method, the reconstructed images contain some distortion. Direct Cosine Transform (DCT) and Fractal Image Compression (FIC) are types of lossy compression methods. This work shows that lossy compression methods can be chosen for medical image compression without significant degradation of the image quality. In this work DCT and Fractal Compression using Partitioned Iterated Function Systems (PIFS) are applied on different modalities of images like CT Scan, Ultrasound, Angiogram, X-ray and mammogram. Approximately 20 images are considered in each modality and the average values of compression ratio and Peak Signal to Noise Ratio (PSNR) are computed and studied. The quality of the reconstructed image is arrived by the PSNR values. Based on the results it can be concluded that the DCT has higher PSNR values and FIC has higher compression ratio. Hence in medical image compression, DCT can be used wherever picture quality is preferred and FIC is used wherever compression of images for storage and transmission is the priority, without loosing picture quality diagnostically.

Keywords: DCT, FIC, PIFS, PSNR.

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324 Removal of Hydrogen Sulphide from Air by Means of Fibrous Ion Exchangers

Authors: H. Wasag

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The removal of hydrogen sulphide is required for reasons of health, odour problems, safety and corrosivity problems. The means of removing hydrogen sulphide mainly depend on its concentration and kind of medium to be purified. The paper deals with a method of hydrogen sulphide removal from the air by its catalytic oxidation to elemental sulphur with the use of Fe-EDTA complex. The possibility of obtaining fibrous filtering materials able to remove small concentrations of H2S from the air were described. The base of these materials is fibrous ion exchanger with Fe(III)- EDTA complex immobilized on their functional groups. The complex of trivalent iron converts hydrogen sulphide to elemental sulphur. Bivalent iron formed in the reaction is oxidized by the atmospheric oxygen, so complex of trivalent iron is continuously regenerated and the overall process can be accounted as pseudocatalytic. In the present paper properties of several fibrous catalysts based on ion exchangers with different chemical nature (weak acid,weak base and strong base) were described. It was shown that the main parameters affecting the process of catalytic oxidation are:concentration of hydrogen sulphide in the air, relative humidity of the purified air, the process time and the content of Fe-EDTA complex in the fibres. The data presented show that the filtering layers with anion exchange package are much more active in the catalytic processes of hydrogen sulphide removal than cation exchanger and inert materials. In the addition to the nature of the fibres relative air humidity is a critical factor determining efficiency of the material in the air purification from H2S. It was proved that the most promising carrier of the Fe-EDTA catalyst for hydrogen sulphide oxidation are Fiban A-6 and Fiban AK-22 fibres.

Keywords: hydrogen sulphide, catalytic oxidation, odour control, ion exchange, fibrous ion exchangers, air deodorization

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323 Improving Worm Detection with Artificial Neural Networks through Feature Selection and Temporal Analysis Techniques

Authors: Dima Stopel, Zvi Boger, Robert Moskovitch, Yuval Shahar, Yuval Elovici

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Computer worm detection is commonly performed by antivirus software tools that rely on prior explicit knowledge of the worm-s code (detection based on code signatures). We present an approach for detection of the presence of computer worms based on Artificial Neural Networks (ANN) using the computer's behavioral measures. Identification of significant features, which describe the activity of a worm within a host, is commonly acquired from security experts. We suggest acquiring these features by applying feature selection methods. We compare three different feature selection techniques for the dimensionality reduction and identification of the most prominent features to capture efficiently the computer behavior in the context of worm activity. Additionally, we explore three different temporal representation techniques for the most prominent features. In order to evaluate the different techniques, several computers were infected with five different worms and 323 different features of the infected computers were measured. We evaluated each technique by preprocessing the dataset according to each one and training the ANN model with the preprocessed data. We then evaluated the ability of the model to detect the presence of a new computer worm, in particular, during heavy user activity on the infected computers.

Keywords: Artificial Neural Networks, Feature Selection, Temporal Analysis, Worm Detection.

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322 Human Resource Development Strategy in Automotive Industry (Eco-Car) for ASEAN Hub

Authors: Phichak Phutrakhul

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The purposes of this research were to study concepts and strategies of human resource development in the automotive manufacturers and to articulate the proposals against the government about the human resource development for automotive industry. In the present study, qualitative study was an in-depth interview in which the qualitative data were collected from the executive or the executive of human resource division from five automotive companies - Toyota Motor (Thailand) Co., Ltd., Nissan Motor (Thailand) Co., Ltd., Mitsubishi Motors (Thailand) Co., Ltd., Honda Automobile (Thailand) Co., Ltd., and Suzuki Motor (Thailand) Co., Ltd. Qualitative data analysis was performed by using inter-coder agreement technique. The research findings were as follows: The external factors included the current conditions of the automotive industry, government’s policy related to the automotive industry, technology, labor market and human resource development systems of the country. The internal factors included management, productive management, organizational strategies, leadership, organizational culture and philosophy of human resource development. These factors were affected to the different concept of human resources development -the traditional human resource development and the strategies of human resource development. The organization focuses on human resources as intellectual capital and uses the strategies of human resource development in all development processes. The strategies of human resource development will enhance the ability of human resources in the organization and the country.

Keywords: Human Resource Development Strategy, Automotive industry, Eco-Cars, ASEAN.

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321 Investigating Elements of Identity of Traditional Neighborhoods in Isfahan and Using These Elements in the Design of Modern Neighborhoods

Authors: Saman Keshavarzi

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The process of planning, designing and building neighborhoods is a complex and multidimensional part of urban planning. Understanding the elements that give a neighborhood a sense of identity can lead to successful city planning and result in a cohesive and functional community where people feel a sense of belonging. These factors are important in ensuring that the needs of the urban population are met to live in a safe, pleasant and healthy society. This research paper aims to identify the elements of the identity of traditional neighborhoods in Isfahan and analyzes ways of using these elements in the design of modern neighborhoods to increase social interaction between communities and cultural reunification of people. The neighborhood of Jolfa in Isfahan has a unique socio-cultural identity as it dates back to the Safavid Dynasty of the 16th century, and most of its inhabitants are Christian Armenians of a religious minority. The elements of the identity of Jolfa were analyzed through the following research methods: field observations, distribution of questionnaires and qualitative analysis. The basic methodology that was used to further understand the Jolfa neighborhood and deconstruct the identity image that residents associate with their respective neighborhoods was a qualitative research method. This was done through utilizing questionnaires that respondents had to fill out in response to a series of research questions. From collecting these qualitative data, the major finding was that traditional neighborhoods that have elements of identity embedded in them are seen to have closer-knit communities whose residents have strong societal ties. This area of study in urban planning is vital to ensuring that new neighborhoods are built with concepts of social cohesion, community and inclusion in mind as they are what lead to strong, connected, and prosperous societies.

Keywords: Development, housing, identity, neighborhood, policy, urbanization.

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320 Embedded Semi-Fragile Signature Based Scheme for Ownership Identification and Color Image Authentication with Recovery

Authors: M. Hamad Hassan, S.A.M. Gilani

Abstract:

In this paper, a novel scheme is proposed for Ownership Identification and Color Image Authentication by deploying Cryptography & Digital Watermarking. The color image is first transformed from RGB to YST color space exclusively designed for watermarking. Followed by color space transformation, each channel is divided into 4×4 non-overlapping blocks with selection of central 2×2 sub-blocks. Depending upon the channel selected two to three LSBs of each central 2×2 sub-block are set to zero to hold the ownership, authentication and recovery information. The size & position of sub-block is important for correct localization, enhanced security & fast computation. As YS ÔèÑ T so it is suitable to embed the recovery information apart from the ownership and authentication information, therefore 4×4 block of T channel along with ownership information is then deployed by SHA160 to compute the content based hash that is unique and invulnerable to birthday attack or hash collision instead of using MD5 that may raise the condition i.e. H(m)=H(m'). For recovery, intensity mean of 4x4 block of each channel is computed and encoded upto eight bits. For watermark embedding, key based mapping of blocks is performed using 2DTorus Automorphism. Our scheme is oblivious, generates highly imperceptible images with correct localization of tampering within reasonable time and has the ability to recover the original work with probability of near one.

Keywords: Hash Collision, LSB, MD5, PSNR, SHA160

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319 Spatiotemporal Analysis of Visual Evoked Responses Using Dense EEG

Authors: Rima Hleiss, Elie Bitar, Mahmoud Hassan, Mohamad Khalil

Abstract:

A comprehensive study of object recognition in the human brain requires combining both spatial and temporal analysis of brain activity. Here, we are mainly interested in three issues: the time perception of visual objects, the ability of discrimination between two particular categories (objects vs. animals), and the possibility to identify a particular spatial representation of visual objects. Our experiment consisted of acquiring dense electroencephalographic (EEG) signals during a picture-naming task comprising a set of objects and animals’ images. These EEG responses were recorded from nine participants. In order to determine the time perception of the presented visual stimulus, we analyzed the Event Related Potentials (ERPs) derived from the recorded EEG signals. The analysis of these signals showed that the brain perceives animals and objects with different time instants. Concerning the discrimination of the two categories, the support vector machine (SVM) was applied on the instantaneous EEG (excellent temporal resolution: on the order of millisecond) to categorize the visual stimuli into two different classes. The spatial differences between the evoked responses of the two categories were also investigated. The results showed a variation of the neural activity with the properties of the visual input. Results showed also the existence of a spatial pattern of electrodes over particular regions of the scalp in correspondence to their responses to the visual inputs.

Keywords: Brain activity, dense EEG, evoked responses, spatiotemporal analysis, SVM, perception.

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318 A Two-Stage Adaptation towards Automatic Speech Recognition System for Malay-Speaking Children

Authors: Mumtaz Begum Mustafa, Siti Salwah Salim, Feizal Dani Rahman

Abstract:

Recently, Automatic Speech Recognition (ASR) systems were used to assist children in language acquisition as it has the ability to detect human speech signal. Despite the benefits offered by the ASR system, there is a lack of ASR systems for Malay-speaking children. One of the contributing factors for this is the lack of continuous speech database for the target users. Though cross-lingual adaptation is a common solution for developing ASR systems for under-resourced language, it is not viable for children as there are very limited speech databases as a source model. In this research, we propose a two-stage adaptation for the development of ASR system for Malay-speaking children using a very limited database. The two stage adaptation comprises the cross-lingual adaptation (first stage) and cross-age adaptation. For the first stage, a well-known speech database that is phonetically rich and balanced, is adapted to the medium-sized Malay adults using supervised MLLR. The second stage adaptation uses the speech acoustic model generated from the first adaptation, and the target database is a small-sized database of the target users. We have measured the performance of the proposed technique using word error rate, and then compare them with the conventional benchmark adaptation. The two stage adaptation proposed in this research has better recognition accuracy as compared to the benchmark adaptation in recognizing children’s speech.

Keywords: Automatic speech recognition system, children speech, adaptation, Malay.

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317 Combined Feature Based Hyperspectral Image Classification Technique Using Support Vector Machines

Authors: Mrs.K.Kavitha, S.Arivazhagan

Abstract:

A spatial classification technique incorporating a State of Art Feature Extraction algorithm is proposed in this paper for classifying a heterogeneous classes present in hyper spectral images. The classification accuracy can be improved if and only if both the feature extraction and classifier selection are proper. As the classes in the hyper spectral images are assumed to have different textures, textural classification is entertained. Run Length feature extraction is entailed along with the Principal Components and Independent Components. A Hyperspectral Image of Indiana Site taken by AVIRIS is inducted for the experiment. Among the original 220 bands, a subset of 120 bands is selected. Gray Level Run Length Matrix (GLRLM) is calculated for the selected forty bands. From GLRLMs the Run Length features for individual pixels are calculated. The Principle Components are calculated for other forty bands. Independent Components are calculated for next forty bands. As Principal & Independent Components have the ability to represent the textural content of pixels, they are treated as features. The summation of Run Length features, Principal Components, and Independent Components forms the Combined Features which are used for classification. SVM with Binary Hierarchical Tree is used to classify the hyper spectral image. Results are validated with ground truth and accuracies are calculated.

Keywords: Multi-class, Run Length features, PCA, ICA, classification and Support Vector Machines.

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316 Selected Ethnomedicinal Plants of Northern Surigao Del Sur: Their Antioxidant Activities in Terms of Total Phenolics, ABTS Radical Cation Decolorization Power, and Ferric Reducing Ability

Authors: Gemma A. Gruyal

Abstract:

Plants can contain a wide variety of substances with antioxidative properties which are associated with important health benefits. These positive health effects are of great importance at a time when the environment is laden with many toxic substances. Five selected herbal plants namely, Mimosa pudica, Phyllanthus niruri, Ceiba pentandra, Eleusine polydactyla and Trema amboinensi, were chosen for the experiment to investigate their total phenolics content and antioxidant activities using ABTS radical cation decolorization power, and ferric reducing antioxidant power. The total phenolic content of each herbal plants ranges from 0.84 to 42.59 mg gallic acid equivalent/g. The antioxidant activity in the ABTS radical cation decolorization power varies from 0.005 to 0.362 mg trolox equivalent/g and the FRAP ranges from 0.30 to 28.42 mg gallic acid equivalent/g. Among the five medicinal plants, Mimosa pudica has been an excellent performer in terms of the 3 parameters measured; it is followed by Phyllanthus niruri. The 5 herbal plants do not have equivalent antioxidant power. The relative high values for M. pudica and P. niruri supports the medicinal value of both plants. The total phenolics, ABTS and FRAP correlate strongly with one another.

Keywords: ABTS, FRAP, leaf extracts, phenol.

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315 Analysis of Entrepreneurship in Industrial Cluster

Authors: Wen-Hsiang Lai

Abstract:

Except for the internal aspects of entrepreneurship (i.e.motivation, opportunity perspective and alertness), there are external aspects that affecting entrepreneurship (i.e. the industrial cluster). By comparing the machinery companies located inside and outside the industrial district, this study aims to explore the cluster effects on the entrepreneurship of companies in Taiwan machinery clusters (TMC). In this study, three factors affecting the entrepreneurship in TMC are conducted as “competition”, “embedded-ness” and “specialized knowledge”. The “competition” in the industrial cluster is defined as the competitive advantages that companies gain in form of demand effects and diversified strategies; the “embedded-ness” refers to the quality of company relations (relational embedded-ness) and ranges (structural embedded-ness) with the industry components (universities, customers and complementary) that affecting knowledge transfer and knowledge generations; the “specialized knowledge” shares theinternal knowledge within industrial clusters. This study finds that when comparing to the companieswhich are outside the cluster, the industrial cluster has positive influence on the entrepreneurship. Additionally, the factor of “relational embedded-ness” has significant impact on the entrepreneurship and affects the adaptation ability of companies in TMC. Finally, the factor of “competition” reveals partial influence on the entrepreneurship.

Keywords: Entrepreneurship, Industrial Cluster, Industrial District, Economies of Agglomerations, Taiwan Machinery Cluster (TMC).

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314 Detection and Classification of Faults on Parallel Transmission Lines Using Wavelet Transform and Neural Network

Authors: V.S.Kale, S.R.Bhide, P.P.Bedekar, G.V.K.Mohan

Abstract:

The protection of parallel transmission lines has been a challenging task due to mutual coupling between the adjacent circuits of the line. This paper presents a novel scheme for detection and classification of faults on parallel transmission lines. The proposed approach uses combination of wavelet transform and neural network, to solve the problem. While wavelet transform is a powerful mathematical tool which can be employed as a fast and very effective means of analyzing power system transient signals, artificial neural network has a ability to classify non-linear relationship between measured signals by identifying different patterns of the associated signals. The proposed algorithm consists of time-frequency analysis of fault generated transients using wavelet transform, followed by pattern recognition using artificial neural network to identify the type of the fault. MATLAB/Simulink is used to generate fault signals and verify the correctness of the algorithm. The adaptive discrimination scheme is tested by simulating different types of fault and varying fault resistance, fault location and fault inception time, on a given power system model. The simulation results show that the proposed scheme for fault diagnosis is able to classify all the faults on the parallel transmission line rapidly and correctly.

Keywords: Artificial neural network, fault detection and classification, parallel transmission lines, wavelet transform.

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313 Intelligent Transport System: Classification of Traffic Signs Using Deep Neural Networks in Real Time

Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

Abstract:

Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: Multiclass classification, convolution neural network, OpenCV, Data Augmentation.

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312 Effect of Different Salts on Pseudomonas taetrolens’ Ability to Lactobionic Acid Production

Authors: I. Sarenkova, I. Ciprovica, I. Cinkmanis

Abstract:

Lactobionic acid is a disaccharide formed from gluconic acid and galactose, and produced by oxidation of lactose. Productivity of lactobionic acid by microbial synthesis can be affected by various factors, and one of them is a presence of potassium, magnesium and manganese ions. In order to extend lactobionic acid production efficiency, it is necessary to increase the yield of lactobionic acid by optimising the fermentation conditions and available substrates for Pseudomonas taetrolens growth. The object of the research was to determinate the application of K2HPO4, MnSO4, MgSO4 × 7H2O salts in different concentration for effective lactose oxidation to lactobionic acid by Pseudomonas taetrolens. Pseudomonas taetrolens NCIB 9396 (NCTC, England) and Pseudomonas taetrolens DSM 21104 (DSMZ, Germany) were used for the study. The acid whey was used as the study object. The content of lactose in whey samples was determined using MilcoScanTM Mars (Foss, Denmark) and high performance liquid chromatography (Shimadzu LC 20 Prominence, Japan). The content of lactobionic acid in whey samples was determined using the high performance liquid chromatography. The impact of studied salts differs, Mn2+ and Mg2+ ions enhanced fermentation instead of K+ ions. Results approved that Mn2+ and Mg2+ ions are necessary for Pseudomonas taetrolens growth. The study results will help to improve the effectiveness of lactobionic acid production with Pseudomonas taetrolens NCIB 9396 and DSM 21104.

Keywords: lactobionic acid, lactose oxidation, Pseudomonas taetrolens, whey.

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311 A Microcontroller Implementation of Constrained Model Predictive Control

Authors: Amira Kheriji Abbes, Faouzi Bouani, Mekki Ksouri

Abstract:

Model Predictive Control (MPC) is an established control technique in a wide range of process industries. The reason for this success is its ability to handle multivariable systems and systems having input, output or state constraints. Neverthless comparing to PID controller, the implementation of the MPC in miniaturized devices like Field Programmable Gate Arrays (FPGA) and microcontrollers has historically been very small scale due to its complexity in implementation and its computation time requirement. At the same time, such embedded technologies have become an enabler for future manufacturing enterprisers as well as a transformer of organizations and markets. In this work, we take advantage of these recent advances in this area in the deployment of one of the most studied and applied control technique in the industrial engineering. In this paper, we propose an efficient firmware for the implementation of constrained MPC in the performed STM32 microcontroller using interior point method. Indeed, performances study shows good execution speed and low computational burden. These results encourage to develop predictive control algorithms to be programmed in industrial standard processes. The PID anti windup controller was also implemented in the STM32 in order to make a performance comparison with the MPC. The main features of the proposed constrained MPC framework are illustrated through two examples.

Keywords: Embedded software, microcontroller, constrainedModel Predictive Control, interior point method, PID antiwindup, Keil tool, C/Cµ language.

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