Use of Ecommerce Websites in Developing Countries

The purpose of this study is to investiagte the use of the ecommerce website in Indonesia as a developing country. The ecommerce website has been identified having the significant impact on business activities in particular solving the geographical problem for islanded countries likes Indonesia. Again, website is identified as a crucial marketing tool. This study presents the effect of quality and features on the use and user satisfaction employing ecommerce websites. Survey method for 115 undergraduate students of Management Department in Andalas University who are attending Management Information Systems (SIM) class have been undertaken. The data obtained is analyzed using Structural Equation Modeling (SEM) using SmartPLS program. This result found that quality of system and information, feature as well satisfaction influencing the use ecommerce website in Indonesia contexts.

ANN Models for Microstrip Line Synthesis and Analysis

Microstrip lines, widely used for good reason, are broadband in frequency and provide circuits that are compact and light in weight. They are generally economical to produce since they are readily adaptable to hybrid and monolithic integrated circuit (IC) fabrication technologies at RF and microwave frequencies. Although, the existing EM simulation models used for the synthesis and analysis of microstrip lines are reasonably accurate, they are computationally intensive and time consuming. Neural networks recently gained attention as fast and flexible vehicles to microwave modeling, simulation and optimization. After learning and abstracting from microwave data, through a process called training, neural network models are used during microwave design to provide instant answers to the task learned.This paper presents simple and accurate ANN models for the synthesis and analysis of Microstrip lines to more accurately compute the characteristic parameters and the physical dimensions respectively for the required design specifications.

Objective Assessment of Psoriasis Lesion Thickness for PASI Scoring using 3D Digital Imaging

Psoriasis is a chronic inflammatory skin condition which affects 2-3% of population around the world. Psoriasis Area and Severity Index (PASI) is a gold standard to assess psoriasis severity as well as the treatment efficacy. Although a gold standard, PASI is rarely used because it is tedious and complex. In practice, PASI score is determined subjectively by dermatologists, therefore inter and intra variations of assessment are possible to happen even among expert dermatologists. This research develops an algorithm to assess psoriasis lesion for PASI scoring objectively. Focus of this research is thickness assessment as one of PASI four parameters beside area, erythema and scaliness. Psoriasis lesion thickness is measured by averaging the total elevation from lesion base to lesion surface. Thickness values of 122 3D images taken from 39 patients are grouped into 4 PASI thickness score using K-means clustering. Validation on lesion base construction is performed using twelve body curvature models and show good result with coefficient of determinant (R2) is equal to 1.

Alertness States Classification By SOM and LVQ Neural Networks

Several studies have been carried out, using various techniques, including neural networks, to discriminate vigilance states in humans from electroencephalographic (EEG) signals, but we are still far from results satisfactorily useable results. The work presented in this paper aims at improving this status with regards to 2 aspects. Firstly, we introduce an original procedure made of the association of two neural networks, a self organizing map (SOM) and a learning vector quantization (LVQ), that allows to automatically detect artefacted states and to separate the different levels of vigilance which is a major breakthrough in the field of vigilance. Lastly and more importantly, our study has been oriented toward real-worked situation and the resulting model can be easily implemented as a wearable device. It benefits from restricted computational and memory requirements and data access is very limited in time. Furthermore, some ongoing works demonstrate that this work should shortly results in the design and conception of a non invasive electronic wearable device.

Analytical and Experimental Methods of Design for Supersonic Two-Stage Ejectors

In this paper the supersonic ejectors are experimentally and analytically studied. Ejector is a device that uses the energy of a fluid to move another fluid. This device works like a vacuum pump without usage of piston, rotor or any other moving component. An ejector contains an active nozzle, a passive nozzle, a mixing chamber and a diffuser. Since the fluid viscosity is large, and the flow is turbulent and three dimensional in the mixing chamber, the numerical methods consume long time and high cost to analyze the flow in ejectors. Therefore this paper presents a simple analytical method that is based on the precise governing equations in fluid mechanics. According to achieved analytical relations, a computer code has been prepared to analyze the flow in different components of the ejector. An experiment has been performed in supersonic regime 1.5

Object Tracking System Using Camshift, Meanshift and Kalman Filter

This paper presents a implementation of an object tracking system in a video sequence. This object tracking is an important task in many vision applications. The main steps in video analysis are two: detection of interesting moving objects and tracking of such objects from frame to frame. In a similar vein, most tracking algorithms use pre-specified methods for preprocessing. In our work, we have implemented several object tracking algorithms (Meanshift, Camshift, Kalman filter) with different preprocessing methods. Then, we have evaluated the performance of these algorithms for different video sequences. The obtained results have shown good performances according to the degree of applicability and evaluation criteria.

Developing a Research Framework for Investigating the Transparency of ePortfolios

This paper describes the evolution of strategies to evaluate ePortfolios in an online Master-s of Education (M.Ed.) degree in Instructional Technology. The ePortfolios are required as a culminating activity for students in the program. By using Web 2.0 tools to develop the ePortfolios, students are able to showcase their technical skills, integrate national standards, demonstrate their professional understandings, and reflect on their individual learning. Faculty have created assessment strategies to evaluate student achievement of these skills. To further develop ePortfolios as a tool promoting authentic learning, faculty are moving toward integrating transparency as part of the evaluation process.

Design Optimization for Efficient Erbium-Doped Fiber Amplifiers

The exact gain shape profile of erbium doped fiber amplifiers (EDFA`s) are depends on fiber length and Er3 ion densities. This paper optimized several of erbium doped fiber parameters to obtain high performance characteristic at pump wavelengths of λp= 980 nm and λs= 1550 nm for three different pump powers. The maximum gain obtained for pump powers (10, 30 and 50mw) is nearly (19, 30 and 33 dB) at optimizations. The required numerical aperture NA to obtain maximum gain becomes less when pump power increased. The amplifier gain is increase when Er+3doped near the center of the fiber core. The simulation has been done by using optisystem 5.0 software (CAD for Photonics, a license product of a Canadian based company) at 2.5 Gbps.

Virtual Reality for Mutual Understanding in Landscape Planning

This paper argues that fostering mutual understanding in landscape planning is as much about the planners educating stakeholder groups as the stakeholders educating the planners. In other words it is an epistemological agreement as to the meaning and nature of place, especially where an effort is made to go beyond the quantitative aspects, which can be achieved by the phenomenological experience of the Virtual Reality (VR) environment. This education needs to be a bi-directional process in which distance can be both temporal as well as spatial separation of participants, that there needs to be a common framework of understanding in which neither 'side' is disadvantaged during the process of information exchange and it follows that a medium such as VR offers an effective way of overcoming some of the shortcomings of traditional media by taking advantage of continuing technological advances in Information, Technology and Communications (ITC). In this paper we make particular reference to this as an extension to Geographical Information Systems (GIS). VR as a two-way communication tool offers considerable potential particularly in the area of Public Participation GIS (PPGIS). Information rich virtual environments that can operate over broadband networks are now possible and thus allow for the representation of large amounts of qualitative and quantitative information 'side-by-side'. Therefore, with broadband access becoming standard for households and enterprises alike, distributed virtual reality environments have great potential to contribute to enabling stakeholder participation and mutual learning within the planning context.

Extensiveness and Effectiveness of Corporate Governance Regulations in South-Eastern Europe

The purpose of the article is to illustrate the main characteristics of the corporate governance challenge facing the countries of South-Eastern Europe (SEE) and to subsequently determine and assess the extensiveness and effectiveness of corporate governance regulations in these countries. Therefore, we start with an overview on the subject of the key problems of corporate governance in transition. We then address the issue of corporate governance measurement for SEE countries. To this end, we include a review of the methodological framework for determining both the extensiveness and the effectiveness of corporate governance legislation. We then focus on the actual analysis of the quality of corporate governance codes, as well as of legal institutions effectiveness and provide a measure of corporate governance in Romania and other SEE emerging markets. The paper concludes by emphasizing the corporate governance enforcement gap and by identifying research issues that require further study.

Fuzzy Rules Emulated Network Adaptive Controller with Unfixed Learning Rate for a Class of Unknown Discrete-time Nonlinear Systems

A direct adaptive controller for a class of unknown nonlinear discrete-time systems is presented in this article. The proposed controller is constructed by fuzzy rules emulated network (FREN). With its simple structure, the human knowledge about the plant is transferred to be if-then rules for setting the network. These adjustable parameters inside FREN are tuned by the learning mechanism with time varying step size or learning rate. The variation of learning rate is introduced by main theorem to improve the system performance and stabilization. Furthermore, the boundary of adjustable parameters is guaranteed through the on-line learning and membership functions properties. The validation of the theoretical findings is represented by some illustrated examples.

A Functional Interpretation of Quantum Theory

In this paper a functional interpretation of quantum theory (QT) with emphasis on quantum field theory (QFT) is proposed. Besides the usual statements on relations between a functions initial state and final state, a functional interpretation also contains a description of the dynamic evolution of the function. That is, it describes how things function. The proposed functional interpretation of QT/QFT has been developed in the context of the author-s work towards a computer model of QT with the goal of supporting the largest possible scope of QT concepts. In the course of this work, the author encountered a number of problems inherent in the translation of quantum physics into a computer program. He came to the conclusion that the goal of supporting the major QT concepts can only be satisfied, if the present model of QT is supplemented by a "functional interpretation" of QT/QFT. The paper describes a proposal for that

A Study on the Least Squares Reduced Parameter Approximation of FIR Digital Filters

Rounding of coefficients is a common practice in hardware implementation of digital filters. Where some coefficients are very close to zero or one, as assumed in this paper, this rounding action also leads to some computation reduction. Furthermore, if the discarded coefficient is of high order, a reduced order filter is obtained, otherwise the order does not change but computation is reduced. In this paper, the Least Squares approximation to rounded (or discarded) coefficient FIR filter is investigated. The result also succinctly extended to general type of FIR filters.

Neural Networks: From Black Box towards Transparent Box Application to Evapotranspiration Modeling

Neural networks are well known for their ability to model non linear functions, but as statistical methods usually does, they use a no parametric approach thus, a priori knowledge is not obvious to be taken into account no more than the a posteriori knowledge. In order to deal with these problematics, an original way to encode the knowledge inside the architecture is proposed. This method is applied to the problem of the evapotranspiration inside karstic aquifer which is a problem of huge utility in order to deal with water resource.

A Hybrid Metaheuristic Framework for Evolving the PROAFTN Classifier

In this paper, a new learning algorithm based on a hybrid metaheuristic integrating Differential Evolution (DE) and Reduced Variable Neighborhood Search (RVNS) is introduced to train the classification method PROAFTN. To apply PROAFTN, values of several parameters need to be determined prior to classification. These parameters include boundaries of intervals and relative weights for each attribute. Based on these requirements, the hybrid approach, named DEPRO-RVNS, is presented in this study. In some cases, the major problem when applying DE to some classification problems was the premature convergence of some individuals to local optima. To eliminate this shortcoming and to improve the exploration and exploitation capabilities of DE, such individuals were set to iteratively re-explored using RVNS. Based on the generated results on both training and testing data, it is shown that the performance of PROAFTN is significantly improved. Furthermore, the experimental study shows that DEPRO-RVNS outperforms well-known machine learning classifiers in a variety of problems.

Complex Dynamics of Bertrand Duopoly Games with Bounded Rationality

A dynamic of Bertrand duopoly game is analyzed, where players use different production methods and choose their prices with bounded rationality. The equilibriums of the corresponding discrete dynamical systems are investigated. The stability conditions of Nash equilibrium under a local adjustment process are studied. The stability conditions of Nash equilibrium under a local adjustment process are studied. The stability of Nash equilibrium, as some parameters of the model are varied, gives rise to complex dynamics such as cycles of higher order and chaos. On this basis, we discover that an increase of adjustment speed of bounded rational player can make Bertrand market sink into the chaotic state. Finally, the complex dynamics, bifurcations and chaos are displayed by numerical simulation.

Medical Image Segmentation Based On Vigorous Smoothing and Edge Detection Ideology

Medical image segmentation based on image smoothing followed by edge detection assumes a great degree of importance in the field of Image Processing. In this regard, this paper proposes a novel algorithm for medical image segmentation based on vigorous smoothening by identifying the type of noise and edge diction ideology which seems to be a boom in medical image diagnosis. The main objective of this algorithm is to consider a particular medical image as input and make the preprocessing to remove the noise content by employing suitable filter after identifying the type of noise and finally carrying out edge detection for image segmentation. The algorithm consists of three parts. First, identifying the type of noise present in the medical image as additive, multiplicative or impulsive by analysis of local histograms and denoising it by employing Median, Gaussian or Frost filter. Second, edge detection of the filtered medical image is carried out using Canny edge detection technique. And third part is about the segmentation of edge detected medical image by the method of Normalized Cut Eigen Vectors. The method is validated through experiments on real images. The proposed algorithm has been simulated on MATLAB platform. The results obtained by the simulation shows that the proposed algorithm is very effective which can deal with low quality or marginal vague images which has high spatial redundancy, low contrast and biggish noise, and has a potential of certain practical use of medical image diagnosis.

Hospitality Program Postgraduate Theses: What Hinders Their Accomplishment?

Postgraduate education is generally aimed at providing in-depth knowledge and understanding that include general philosophy in the world sciences, management, technologies, applications and other elements closely related to specific areas. In most universities, besides core and non-core subjects, a thesis is one of the requirements for the postgraduate student to accomplish before graduating. This paper reports on the empirical investigation into attributes that are associated with the obstacles to thesis accomplishment among postgraduate students. Using the quantitative approach the experiences of postgraduate students were tapped. Findings clearly revealed that information seeking, writing skills and other factors which refer to supervisor and time management, in particular, are recognized as contributory factors which positively or negatively influence postgraduates’ thesis accomplishment. Among these, writing skills dimensions were found to be the most difficult process in thesis accomplishment compared to information seeking and other factors. This pessimistic indication has provided some implications not only for the students but supervisors and institutions as a whole.

Development of a Catchment Water Quality Model for Continuous Simulations of Pollutants Build-up and Wash-off

Estimation of runoff water quality parameters is required to determine appropriate water quality management options. Various models are used to estimate runoff water quality parameters. However, most models provide event-based estimates of water quality parameters for specific sites. The work presented in this paper describes the development of a model that continuously simulates the accumulation and wash-off of water quality pollutants in a catchment. The model allows estimation of pollutants build-up during dry periods and pollutants wash-off during storm events. The model was developed by integrating two individual models; rainfall-runoff model, and catchment water quality model. The rainfall-runoff model is based on the time-area runoff estimation method. The model allows users to estimate the time of concentration using a range of established methods. The model also allows estimation of the continuing runoff losses using any of the available estimation methods (i.e., constant, linearly varying or exponentially varying). Pollutants build-up in a catchment was represented by one of three pre-defined functions; power, exponential, or saturation. Similarly, pollutants wash-off was represented by one of three different functions; power, rating-curve, or exponential. The developed runoff water quality model was set-up to simulate the build-up and wash-off of total suspended solids (TSS), total phosphorus (TP) and total nitrogen (TN). The application of the model was demonstrated using available runoff and TSS field data from road and roof surfaces in the Gold Coast, Australia. The model provided excellent representation of the field data demonstrating the simplicity yet effectiveness of the proposed model.

A Retrospective of High-Lift Device Technology

The present paper deals with the most adopted technical solutions for the enhancement of the lift force of a wing. In fact, during several flight conditions (such as take off and landing), the lift force needs to be dramatically enhanced. Both trailing edge devices (such as flaps) and leading edge ones (such as slats) are described. Finally, the most advanced aerodynamic solutions to avoid the separation of the boundary layer from aircraft wings at high angles of attack are reviewed.