Determining the Online Purchasing Loyalty for Thai Herbal Products

The objective of this study is to identify the factors that influence the online purchasing loyalty for Thai herbal products. Survey research is used to gather data from Thai herb online merchants to assess factors that have impacts on enhancing loyalty. Data were collected from 300 online customers who had experience in online purchasing of Thai Herbal products. Prior experience consists of data from previous usage of online herbs, herb purchase and internet usage. E-Quality data consists of information quality, system quality, service quality and the product quality of Thai herbal products sold online. The results suggest that prior experience, Equality, attitude toward purchase and trust in online merchant have major impacts on loyalty. The good attitude and E-Quality of purchasing Thai herbal product online are the most significant determinants affecting loyalty.

Photon Localization inside a Waveguide Modeled by Uncertainty Principle

In the present work, an attempt is made to understand electromagnetic field confinement in a subwavelength waveguide structure using concepts of quantum mechanics. Evanescent field in the waveguide is looked as inability of the photon to get confined in the waveguide core and uncertainty of position is assigned to it. The momentum uncertainty is calculated from position uncertainty. Schrödinger wave equation for the photon is written by incorporating position-momentum uncertainty. The equation is solved and field distribution in the waveguide is obtained. The field distribution and power confinement is compared with conventional waveguide theory. They were found in good agreement with each other.

Identification of Most Frequently Occurring Lexis in Winnings-announcing Unsolicited Bulke-mails

e-mail has become an important means of electronic communication but the viability of its usage is marred by Unsolicited Bulk e-mail (UBE) messages. UBE consists of many types like pornographic, virus infected and 'cry-for-help' messages as well as fake and fraudulent offers for jobs, winnings and medicines. UBE poses technical and socio-economic challenges to usage of e-mails. To meet this challenge and combat this menace, we need to understand UBE. Towards this end, the current paper presents a content-based textual analysis of nearly 3000 winnings-announcing UBE. Technically, this is an application of Text Parsing and Tokenization for an un-structured textual document and we approach it using Bag Of Words (BOW) and Vector Space Document Model techniques. We have attempted to identify the most frequently occurring lexis in the winnings-announcing UBE documents. The analysis of such top 100 lexis is also presented. We exhibit the relationship between occurrence of a word from the identified lexisset in the given UBE and the probability that the given UBE will be the one announcing fake winnings. To the best of our knowledge and survey of related literature, this is the first formal attempt for identification of most frequently occurring lexis in winningsannouncing UBE by its textual analysis. Finally, this is a sincere attempt to bring about alertness against and mitigate the threat of such luring but fake UBE.

ADABeV: Automatic Detection of Abnormal Behavior in Video-surveillance

Intelligent Video-Surveillance (IVS) systems are being more and more popular in security applications. The analysis and recognition of abnormal behaviours in a video sequence has gradually drawn the attention in the field of IVS, since it allows filtering out a large number of useless information, which guarantees the high efficiency in the security protection, and save a lot of human and material resources. We present in this paper ADABeV, an intelligent video-surveillance framework for event recognition in crowded scene to detect the abnormal human behaviour. This framework is attended to be able to achieve real-time alarming, reducing the lags in traditional monitoring systems. This architecture proposal addresses four main challenges: behaviour understanding in crowded scenes, hard lighting conditions, multiple input kinds of sensors and contextual-based adaptability to recognize the active context of the scene.

Performance Monitoring of the Refrigeration System with Minimum Set of Sensors

This paper describes a methodology for remote performance monitoring of retail refrigeration systems. The proposed framework starts with monitoring of the whole refrigeration circuit which allows detecting deviations from expected behavior caused by various faults and degradations. The subsequent diagnostics methods drill down deeper in the equipment hierarchy to more specifically determine root causes. An important feature of the proposed concept is that it does not require any additional sensors, and thus, the performance monitoring solution can be deployed at a low installation cost. Moreover only a minimum of contextual information is required, which also substantially reduces time and cost of the deployment process.

Accurate Time Domain Method for Simulation of Microstructured Electromagnetic and Photonic Structures

A time-domain numerical model within the framework of transmission line modeling (TLM) is developed to simulate electromagnetic pulse propagation inside multiple microcavities forming photonic crystal (PhC) structures. The model developed is quite general and is capable of simulating complex electromagnetic problems accurately. The field quantities can be mapped onto a passive electrical circuit equivalent what ensures that TLM is provably stable and conservative at a local level. Furthermore, the circuit representation allows a high level of hybridization of TLM with other techniques and lumped circuit models of components and devices. A photonic crystal structure formed by rods (or blocks) of high-permittivity dieletric material embedded in a low-dielectric background medium is simulated as an example. The model developed gives vital spatio-temporal information about the signal, and also gives spectral information over a wide frequency range in a single run. The model has wide applications in microwave communication systems, optical waveguides and electromagnetic materials simulations.

Application of Data Mining Tools to Predicate Completion Time of a Project

Estimation time and cost of work completion in a project and follow up them during execution are contributors to success or fail of a project, and is very important for project management team. Delivering on time and within budgeted cost needs to well managing and controlling the projects. To dealing with complex task of controlling and modifying the baseline project schedule during execution, earned value management systems have been set up and widely used to measure and communicate the real physical progress of a project. But it often fails to predict the total duration of the project. In this paper data mining techniques is used predicting the total project duration in term of Time Estimate At Completion-EAC (t). For this purpose, we have used a project with 90 activities, it has updated day by day. Then, it is used regular indexes in literature and applied Earned Duration Method to calculate time estimate at completion and set these as input data for prediction and specifying the major parameters among them using Clem software. By using data mining, the effective parameters on EAC and the relationship between them could be extracted and it is very useful to manage a project with minimum delay risks. As we state, this could be a simple, safe and applicable method in prediction the completion time of a project during execution.

An Empirical Quest for Linkages between HPWS and Employee Behaviors – a Perspective from the Non Managerial Employees in Japanese Organizations

High Performance Work Systems (HPWS) generally give rise to positive impacts on employees by increasing their commitments in workplaces. While some argued this actually have considerable negative impacts on employees with increasing possibilities of imposing strains caused by stress and intensity of such work places. Do stressful workplaces hamper employee commitment? The author has tried to find the answer by exploring linkages between HPWS practices and its impact on employees in Japanese organizations. How negative outcomes like job intensity and workplaces and job stressors can influence different forms of employees- commitments which can be a hindrance to their performance. Design: A close ended questionnaire survey was conducted amongst 16 large, medium and small sized Japanese companies from diverse industries around Chiba, Saitama, and Ibaraki Prefectures and in Tokyo from the month of October 2008 to February 2009. Questionnaires were aimed to the non managerial employees- perceptions of HPWS practices, their behavior, working life experiences in their work places. A total of 227 samples are used for analysis in the study. Methods: Correlations, MANCOVA, SEM Path analysis using AMOS software are used for data analysis in this study. Findings: Average non-managerial perception of HPWS adoption is significantly but negatively correlated to both work place Stressors and Continuous commitment, but positively correlated to job Intensity, Affective, Occupational and Normative commitments in different workplaces at Japan. The path analysis by SEM shows significant indirect relationship between Stressors and employee Affective organizational commitment and Normative organizational commitments. Intensity also has a significant indirect effect on Occupational commitments. HPWS has an additive effect on all the outcomes variables. Limitations: The sample size in this study cannot be a representative to the entire population of non-managerial employees in Japan. There were no respondents from automobile, pharmaceuticals, finance industries. The duration of the survey coincided in a period when Japan as most of the other countries is under going recession. Biases could not be ruled out completely. We must take cautions in interpreting the results of studies as they cannot be generalized. And the path analysis cannot provide the complete causality of the inter linkages between the variables used in the study. Originality: There have been limited studies on linkages in HPWS adoptions and their impacts on employees- behaviors and commitments in Japanese workplaces. This study may provide some ingredients for further research in the fields of HRM policies and practices and their linkages on different forms of employees- commitments.

Eco-Innovation as a New Sustainable Development Strategy: Case Studies

Sustainable development is one of the most debated issues, recently. In terms of providing more livable Earth continuity, while Production activities are going on, on the other hand protecting the environment has importance. As a strategy for sustainable development, eco-innovation is the application of innovations to reduce environmental burdens. Endeavors to understand ecoinnovation processes have been affected from environmental economics and innovation economics from neoclassical economics, and evolutionary economics other than neoclassical economics. In the light of case study analyses, this study aims to display activities in this field through case studies after explaining the theoretical framework of eco-innovations. This study consists of five sections including introduction and conclusion. In the second part of the study identifications of the concepts related with eco-innovation are described and eco-innovations are classified. Third section considers neoclassical and evolutionary approaches from neoclassical economics and evolutionary economics, respectively. Fourth section gives the case studies of successful eco-innovations. Last section is the conclusion part and offers suggestions for future eco-innovation research according to the theoretical framework and the case studies.

Relationship between Gender, BMI, and Lifestyle with Bone Mineral Density of Adolescent in Urban Areas

The purpose of this study was to analyze relationship between gender, BMI, and lifestyle with bone mineral density (BMD) of adolescent in urban areas . The place of this study in Jakarta State University, Indonesia. The number of samples involved as many as 200 people, consisting of 100 men and 100 women. BMD was measured using Quantitative Ultrasound Bone Densitometry. While the questionnaire used to collect data on age, gender, and lifestyle (calcium intake, smoking habits, alcohol consumption, tea, coffee, sports, and sun exposure). Mean age of men and women, respectively as much as 20.7 ± 2.18 years and 21 ± 1.61 years. Mean BMD values of men was 1.084 g/cm ² ± 0.11 while women was 0.976 g/cm ² ± 0.10. Men and women with normal BMD respectively as much as 46.7% and 16.7%. Men and women affected by osteopenia respectively as much as 50% and 80%. Men and women affected by osteoporosis respectively as much as 3.3% and 3.3%. Mean BMI of men and women, respectively as much as 21.4 ± 2.07 kg/m2 and 20.9 ± 2.06 kg/m2. Mean lifestyle score of men and women , respectively as much as 71.9 ± 5.84 and 70.1 ± 5.67 (maximum score 100). Based on Spearman and Pearson Correlation test, there were relationship significantly between gender and lifestyle with BMD.

Developing New Processes and Optimizing Performance Using Response Surface Methodology

Response surface methodology (RSM) is a very efficient tool to provide a good practical insight into developing new process and optimizing them. This methodology could help engineers to raise a mathematical model to represent the behavior of system as a convincing function of process parameters. Through this paper the sequential nature of the RSM surveyed for process engineers and its relationship to design of experiments (DOE), regression analysis and robust design reviewed. The proposed four-step procedure in two different phases could help system analyst to resolve the parameter design problem involving responses. In order to check accuracy of the designed model, residual analysis and prediction error sum of squares (PRESS) described. It is believed that the proposed procedure in this study can resolve a complex parameter design problem with one or more responses. It can be applied to those areas where there are large data sets and a number of responses are to be optimized simultaneously. In addition, the proposed procedure is relatively simple and can be implemented easily by using ready-made standard statistical packages.

Use of Radial Basis Function Neural Network for Bearing Pressure Prediction of Strip Footing on Reinforced Granular Bed Overlying Weak Soil

Earth reinforcing techniques have become useful and economical to solve problems related to difficult grounds and provide satisfactory foundation performance. In this context, this paper uses radial basis function neural network (RBFNN) for predicting the bearing pressure of strip footing on reinforced granular bed overlying weak soil. The inputs for the neural network models included plate width, thickness of granular bed and number of layers of reinforcements, settlement ratio, water content, dry density, cohesion and angle of friction. The results indicated that RBFNN model exhibited more than 84 % prediction accuracy, thereby demonstrating its application in a geotechnical problem.

A Text Clustering System based on k-means Type Subspace Clustering and Ontology

This paper presents a text clustering system developed based on a k-means type subspace clustering algorithm to cluster large, high dimensional and sparse text data. In this algorithm, a new step is added in the k-means clustering process to automatically calculate the weights of keywords in each cluster so that the important words of a cluster can be identified by the weight values. For understanding and interpretation of clustering results, a few keywords that can best represent the semantic topic are extracted from each cluster. Two methods are used to extract the representative words. The candidate words are first selected according to their weights calculated by our new algorithm. Then, the candidates are fed to the WordNet to identify the set of noun words and consolidate the synonymy and hyponymy words. Experimental results have shown that the clustering algorithm is superior to the other subspace clustering algorithms, such as PROCLUS and HARP and kmeans type algorithm, e.g., Bisecting-KMeans. Furthermore, the word extraction method is effective in selection of the words to represent the topics of the clusters.

Mathematical Models for Overall Gas Transfer Coefficient Using Different Theories and Evaluating Their Measurement Accuracy

Oxygen transfer, the process by which oxygen is transferred from the gaseous to liquid phase, is a vital part of the waste water treatment process. Because of low solubility of oxygen and consequent low rate of oxygen transfer, sufficient oxygen to meet the requirement of aerobic waste does not enter through normal surface air water interface. Many theories have come up in explaining the mechanism of gas transfer and absorption of non-reacting gases in a liquid, of out of which, Two film theory is important. An exiting mathematical model determines approximate value of Overall Gas Transfer coefficient. The Overall Gas Transfer coefficient, in case of Penetration theory, is 1.13 time more than that obtained in case of Two film theory. The difference is due to the difference in assumptions in the two theories. The paper aims at development of mathematical model which determines the value of Overall Gas Transfer coefficient with greater accuracy than the existing model.

IT/IS Outsourcing Relationship Factors in Higher Education Institution: Behavioral Dimensions from Client Perspectives

Higher education institutions are increasingly opting to outsourcing methods in order to sustain themselves and this creates a gap of literature in terms of how they perceive the relationship. This research paper attempts to identify the behavioral and psychological factors that exist in the engagement thus providing valuable information to practicing and potential clients, and vendors. The determinants were gathered from previous literatures and analyzed to formulate the factors. This study adopts the case study and survey approaches in which interviews and questionnaires are deployed on employees of IT-related department in a Malaysian higher education institution.

Detecting Community Structure in Amino Acid Interaction Networks

In this paper we introduce the notion of protein interaction network. This is a graph whose vertices are the protein-s amino acids and whose edges are the interactions between them. Using a graph theory approach, we observe that according to their structural roles, the nodes interact differently. By leading a community structure detection, we confirm this specific behavior and describe thecommunities composition to finally propose a new approach to fold a protein interaction network.

Numerical Studies on Thrust Vectoring Using Shock Induced Supersonic Secondary Jet

Numerical studies have been carried out using a validated two-dimensional RNG k-epsilon turbulence model for the design optimization of a thrust vector control system using shock induced supersonic secondary jet. Parametric analytical studies have been carried out with various secondary jets at different divergent locations, jet interaction angles, jet pressures. The results from the parametric studies of the case on hand reveal that the primary nozzle with a small divergence angle, downstream injections with a distance of 2.5 times the primary nozzle throat diameter from the primary nozzle throat location warrant higher efficiency over a certain range of jet pressures and jet angles. We observed that the supersonic secondary jet opposing the core flow with jets interaction angle of 40o to the axis far downstream of the nozzle throat facilitates better thrust vectoring than the secondary jet with same direction as that of core flow with various interaction angles. We concluded that fixing of the supersonic secondary jet nozzle pointing towards the throat direction with suitable angle at a distance 2 to 4 times of the primary nozzle throat diameter, as the case may be, from the primary nozzle throat location could facilitate better thrust vectoring for the supersonic aerospace vehicles.

Biorecognizable Nanoparticles Based On Hyaluronic Acid/Poly(ε-Caprolactone) Block Copolymer

Since hyaluronic acid (HA) receptor such as CD44 is over-expressed at sites of cancer cells, HA can be used as a targeting vehicles for anti-cancer drugs. The aim of this study is to synthesize block copolymer composed of hyaluronic acid and poly(ε-caprolactone) (HAPCL) and to fabricate polymeric micelles for anticancer drug targeting against CD44 receptor of tumor cells. Chemical composition of HAPCL was confirmed using 1H NMR spectroscopy. Doxorubicin (DOX) was incorporated into polymeric micelles of HAPCL. The diameters of HAPHS polymeric micelles were changed around 80nm and have spherical shapes. Targeting potential was investigated using CD44-overexpressing. When DOX-incorporated polymeric micelles was added to KB cells, they revealed strong red fluorescence color while blocking of CD44 receptor by pretreatment of free HA resulted in reduced intensity, indicating that HAPCL polymeric micelles have targetability against CD44 receptor.

Numerical Investigation of the Optimal Spatial Domain Discretization for the 2-D Analysis of a Darrieus Vertical-Axis Water Turbine

The optimal grid spacing and turbulence model for the 2D numerical analysis of a vertical-axis water turbine (VAWaterT) operating in a 2 m/s freestream current has been investigated. The results of five different spatial domain discretizations and two turbulence models (k-ω SST and k-ε RNG) have been compared, in order to gain the optimal y+ parameter distribution along the blade walls during a full rotor revolution. The resulting optimal mesh has appeared to be quite similar to that obtained for the numerical analysis of a vertical-axis wind turbine.

Tensorial Transformations of Double Gai Sequence Spaces

The precise form of tensorial transformations acting on a given collection of infinite matrices into another ; for such classical ideas connected with the summability field of double gai sequence spaces. In this paper the results are impose conditions on the tensor g so that it becomes a tensorial transformations from the metric space χ2 to the metric space C