Analytical Investigation of the Effects of a Standing Ocean Wave in a Wave-Power Device OWC

In this work we study analytically and numerically the performance of the mean heave motion of an OWC coupled with the governing equation of the spreading ocean waves due to the wide variation in an open parabolic channel with constant depth. This paper considers that the ocean wave propagation is under the assumption of a shallow flow condition. In order to verify the effect of the waves in the OWC firstly we establish the analytical model in a non-dimensional form based on the energy equation. The proposed wave-power system has to aims: one is to perturb the ocean waves as a consequence of the channel shape in order to concentrate the maximum ocean wave amplitude in the neighborhood of the OWC and the second is to determine the pressure and volume oscillation of air inside the compression chamber.

The Exclusion of Consumer Rights in e-Auctions – Is an e-Auction Really an Auction at all?

This paper considers the exclusion of consumer rights by the New Zealand Consumer Guarantees Act 1993 in eauctions. The paper asserts that the absence of an individual auctioneer conducting each e-auction means that e-auctions may not be auctions at all. The paper also questions the justification for excluding consumer rights in e-auctions because the rationale for excluding consumer rights in traditional auctions does not fit with e-auctions due to the significant differences in the sale processes. The paper recommends reform by way of statutory amendment.

Three-Dimensional Modeling of a Twisted-Blade Darrieus Vertical-Axis Wind Turbine

A complete CAD procedure to model a twisted-bladed vertical-axis wind turbine (VAWT) is presented with the aim of determining some practical guidelines to be used for the generation of an easily-meshable CAD geometry to be adopted as the basis of both CFD and FEM numerical simulations.

A Cohesive Lagrangian Swarm and Its Application to Multiple Unicycle-like Vehicles

Swarm principles are increasingly being used to design controllers for the coordination of multi-robot systems or, in general, multi-agent systems. This paper proposes a two-dimensional Lagrangian swarm model that enables the planar agents, modeled as point masses, to swarm whilst effectively avoiding each other and obstacles in the environment. A novel method, based on an extended Lyapunov approach, is used to construct the model. Importantly, the Lyapunov method ensures a form of practical stability that guarantees an emergent behavior, namely, a cohesive and wellspaced swarm with a constant arrangement of individuals about the swarm centroid. Computer simulations illustrate this basic feature of collective behavior. As an application, we show how multiple planar mobile unicycle-like robots swarm to eventually form patterns in which their velocities and orientations stabilize.

Development of a 3D Mathematical Model for a Doxorubicin Controlled Release System using Pluronic Gel for Breast Cancer Treatment

Female breast cancer is the second in frequency after cervical cancer. Surgery is the most common treatment for breast cancer, followed by chemotherapy as a treatment of choice. Although effective, it causes serious side effects. Controlled-release drug delivery is an alternative method to improve the efficacy and safety of the treatment. It can release the dosage of drug between the minimum effect concentration (MEC) and minimum toxic concentration (MTC) within tumor tissue and reduce the damage of normal tissue and the side effect. Because an in vivo experiment of this system can be time-consuming and labor-intensive, a mathematical model is desired to study the effects of important parameters before the experiments are performed. Here, we describe a 3D mathematical model to predict the release of doxorubicin from pluronic gel to treat human breast cancer. This model can, ultimately, be used to effectively design the in vivo experiments.

Hospital Based Electrocardiogram Sensor Grid

The technological concepts such as wireless hospital and portable cardiac telemetry system require the development of physiological signal acquisition devices to be easily integrated into the hospital database. In this paper we present the low cost, portable wireless ECG acquisition hardware that transmits ECG signals to a dedicated computer.The front end of the system obtains and processes incoming signals, which are then transmitted via a microcontroller and wireless Bluetooth module. A monitoring purpose Bluetooth based end user application integrated with patient database management module is developed for the computers. The system will act as a continuous event recorder, which can be used to follow up patients who have been resuscitatedfrom cardiac arrest, ventricular tachycardia but also for diagnostic purposes for patients with arrhythmia symptoms. In addition, cardiac information can be saved into the patient-s database of the hospital.

Extraction of Knowledge Complexity in 3G Killer Application Construction for Telecommunications National Strategy

We review a knowledge extractor model in constructing 3G Killer Applications. The success of 3G is essential for Government as it became part of Telecommunications National Strategy. The 3G wireless technologies may reach larger area and increase country-s ICT penetration. In order to understand future customers needs, the operators require proper information (knowledge) lying inside. Our work approached future customers as complex system where the complex knowledge may expose regular behavior. The hidden information from 3G future customers is revealed by using fractal-based questionnaires. Afterward, further statistical analysis is used to match the results with operator-s strategic plan. The developments of 3G applications also consider its saturation time and further improvement of the application.

Cross Signal Identification for PSG Applications

The standard investigational method for obstructive sleep apnea syndrome (OSAS) diagnosis is polysomnography (PSG), which consists of a simultaneous, usually overnight recording of multiple electro-physiological signals related to sleep and wakefulness. This is an expensive, encumbering and not a readily repeated protocol, and therefore there is need for simpler and easily implemented screening and detection techniques. Identification of apnea/hypopnea events in the screening recordings is the key factor for the diagnosis of OSAS. The analysis of a solely single-lead electrocardiographic (ECG) signal for OSAS diagnosis, which may be done with portable devices, at patient-s home, is the challenge of the last years. A novel artificial neural network (ANN) based approach for feature extraction and automatic identification of respiratory events in ECG signals is presented in this paper. A nonlinear principal component analysis (NLPCA) method was considered for feature extraction and support vector machine for classification/recognition. An alternative representation of the respiratory events by means of Kohonen type neural network is discussed. Our prospective study was based on OSAS patients of the Clinical Hospital of Pneumology from Iaşi, Romania, males and females, as well as on non-OSAS investigated human subjects. Our computed analysis includes a learning phase based on cross signal PSG annotation.

Optimization of Enzymatic Activities in Malting of Oat

Malting is usually carried out on intact barley seed, while hull is still attached to it. In this study, oat grain with and without hull was subjected to controlled germination to optimize its enzymes activity, in such a way that lipase has the lowest and α- amylase and proteinase the highest activities. Since pH has a great impact on the activity of the enzymes, the pH of germination media was set up to 3 to 8. In dehulled oats, lipase and α-amylase had the lowest and highest activities in pHs 3 and 6, respectively whereas the highest proteinase activity was evidenced at pH 7 and 4 in the oats with and without hull respectively. While measurements indicated that the effect of hull on the enzyme activities particularly in lipase and amylase at each level of the pH are significantly different, the best results were obtained in those samples in which their hull had been removed. However, since the similar lipase activity in germinated dehulled oat were recorded at the pHs 4 and 5, therefore it was concluded that pH 5 in dehulled oat seed may provide the optimum enzyme activity for all the enzymes.

Adhesion Strength Evaluation Methods in Thermally Sprayed Coatings

The techniques for estimating the adhesive and cohesive strength in high velocity oxy fuel (HVOF) thermal spray coatings have been discussed and compared. The development trend and the last investigation have been studied. We will focus on benefits and limitations of these methods in different process and materials.

An Ontology Abstract Machine

As more people from non-technical backgrounds are becoming directly involved with large-scale ontology development, the focal point of ontology research has shifted from the more theoretical ontology issues to problems associated with the actual use of ontologies in real-world, large-scale collaborative applications. Recently the National Science Foundation funded a large collaborative ontology development project for which a new formal ontology model, the Ontology Abstract Machine (OAM), was developed to satisfy some unique functional and data representation requirements. This paper introduces the OAM model and the related algorithms that enable maintenance of an ontology that supports node-based user access. The successful software implementation of the OAM model and its subsequent acceptance by a large research community proves its validity and its real-world application value.

Performance Prediction of a 5MW Wind Turbine Blade Considering Aeroelastic Effect

In this study, aeroelastic response and performance analyses have been conducted for a 5MW-Class composite wind turbine blade model. Advanced coupled numerical method based on computational fluid dynamics (CFD) and computational flexible multi-body dynamics (CFMBD) has been developed in order to investigate aeroelastic responses and performance characteristics of the rotating composite blade. Reynolds-Averaged Navier-Stokes (RANS) equations with k-ω SST turbulence model were solved for unsteady flow problems on the rotating turbine blade model. Also, structural analyses considering rotating effect have been conducted using the general nonlinear finite element method. A fully implicit time marching scheme based on the Newmark direct integration method is applied to solve the coupled aeroelastic governing equations of the 3D turbine blade for fluid-structure interaction (FSI) problems. Detailed dynamic responses and instantaneous velocity contour on the blade surfaces which considering flow-separation effects were presented to show the multi-physical phenomenon of the huge rotating wind- turbine blade model.

A Novel Approach for Protein Classification Using Fourier Transform

Discovering new biological knowledge from the highthroughput biological data is a major challenge to bioinformatics today. To address this challenge, we developed a new approach for protein classification. Proteins that are evolutionarily- and thereby functionally- related are said to belong to the same classification. Identifying protein classification is of fundamental importance to document the diversity of the known protein universe. It also provides a means to determine the functional roles of newly discovered protein sequences. Our goal is to predict the functional classification of novel protein sequences based on a set of features extracted from each protein sequence. The proposed technique used datasets extracted from the Structural Classification of Proteins (SCOP) database. A set of spectral domain features based on Fast Fourier Transform (FFT) is used. The proposed classifier uses multilayer back propagation (MLBP) neural network for protein classification. The maximum classification accuracy is about 91% when applying the classifier to the full four levels of the SCOP database. However, it reaches a maximum of 96% when limiting the classification to the family level. The classification results reveal that spectral domain contains information that can be used for classification with high accuracy. In addition, the results emphasize that sequence similarity measures are of great importance especially at the family level.

Managerial Styles of Asian Executives: The Case of Thailand

This research project is developed in order to study managerial styles of modern Thai executives. The thorough understanding will lead to continuous improvement and efficient performance of Thai business organizations. Regarding managerial skills, Thai executives focus heavily upon human skills. Also, the negotiator roles are most emphasis in their management. In addition, Thai executives pay most attention to the fundamental management principles including Harmony and Unity of Direction of the organizations. Moreover, the management techniques, consisting of Team work and Career Planning are of their main concern. Finally, Thai executives wish to enhance their firms- image and employees- morale through conducting the ethical and socially responsible activities. The major tactic deployed to stimulate employees- ethical behaviors and mindset is Code of Ethics development.

Irrigation Scheduling for Maize and Indian-mustard based on Daily Crop Water Requirement in a Semi- Arid Region

Maize and Indian mustard are significant crops in semi-arid climate zones of India. Improved water management requires precise scheduling of irrigation, which in turn requires an accurate computation of daily crop evapotranspiration (ETc). Daily crop evapotranspiration comes as a product of reference evapotranspiration (ET0) and the growth stage specific crop coefficients modified for daily variation. The first objective of present study is to develop crop coefficients Kc for Maize and Indian mustard. The estimated values of Kc for maize at the four crop growth stages (initial, development, mid-season, and late season) are 0.55, 1.08, 1.25, and 0.75, respectively, and for Indian mustard the Kc values at the four growth stages are 0.3, 0.6, 1.12, and 0.35, respectively. The second objective of the study is to compute daily crop evapotranspiration from ET0 and crop coefficients. Average daily ETc of maize varied from about 2.5 mm/d in the early growing period to > 6.5 mm/d at mid season. The peak ETc of maize is 8.3 mm/d and it occurred 64 days after sowing at the reproductive growth stage when leaf area index was 4.54. In the case of Indian mustard, average ETc is 1 mm/d at the initial stage, >1.8 mm/d at mid season and achieves a peak value of 2.12 mm/d on 56 days after sowing. Improved schedules of irrigation have been simulated based on daily crop evapo-transpiration and field measured data. Simulation shows a close match between modeled and field moisture status prevalent during crop season.

Engine Power Effects on Support Interference

Renewed interest in propeller propulsion on aircraft configurations combined with higher propeller loads lead to the question how the effects of the propulsion on model support disturbances should be accounted for. In this paper, the determination of engine power effects on support interference of sting-mounted models is demonstrated by a measurement on a four-engine turboprop aircraft. CFD results on a more generic model are presented in order to clarify the possible mechanism behind engine power effects on support interference. The engine slipstream induces a local change in angle of sideslip at the model sting thereby influencing the sting near-field and far-field effects. Whether or not the net result of these changes in the disturbance pattern leads to a significant engine power effect depends on the configuration of the wind tunnel model and the test setup.

An Intelligent Optimization Model for Multi-objective Order Allocation Planning

This paper presents a multi-objective order allocation planning problem with the consideration of various real-world production features. A novel hybrid intelligent optimization model, integrating a multi-objective memetic optimization process, a Monte Carlo simulation technique and a heuristic pruning technique, is proposed to handle this problem. Experiments based on industrial data are conducted to validate the proposed model. Results show that (1) the proposed model can effectively solve the investigated problem by providing effective production decision-making solutions, which outperformsan NSGA-II-based optimization process and an industrial method.

A New Method for Contour Approximation Using Basic Ramer Idea

This paper presented two new efficient algorithms for contour approximation. The proposed algorithm is compared with Ramer (good quality), Triangle (faster) and Trapezoid (fastest) in this work; which are briefly described. Cartesian co-ordinates of an input contour are processed in such a manner that finally contours is presented by a set of selected vertices of the edge of the contour. In the paper the main idea of the analyzed procedures for contour compression is performed. For comparison, the mean square error and signal-to-noise ratio criterions are used. Computational time of analyzed methods is estimated depending on a number of numerical operations. Experimental results are obtained both in terms of image quality, compression ratios, and speed. The main advantages of the analyzed algorithm is small numbers of the arithmetic operations compared to the existing algorithms.

Comprehensive Hierarchy Evaluation of Power Quality Based on an Incentive Mechanism

In a liberalized electricity market, it is not surprising that different customers require different power quality (PQ) levels at different price. Power quality related to several power disturbances is described by many parameters, so how to define a comprehensive hierarchy evaluation system of power quality (PQCHES) has become a concerned issue. In this paper, based on four electromagnetic compatibility (EMC) levels, the numerical range of each power disturbance is divided into five grades (Grade I –Grade V), and the “barrel principle" of power quality is used for the assessment of overall PQ performance with only one grade indicator. A case study based on actual monitored data of PQ shows that the site PQ grade indicates the electromagnetic environment level and also expresses the characteristics of loads served by the site. The shortest plank principle of PQ barrel is an incentive mechanism, which can combine with the rewards/penalty mechanism (RPM) of consumed energy “on quality demand", to stimulate utilities to improve the overall PQ level and also stimulate end-user more “smart" under the infrastructure of future SmartGrid..

Neural Networks and Particle Swarm Optimization Based MPPT for Small Wind Power Generator

This paper proposes the method combining artificial neural network (ANN) with particle swarm optimization (PSO) to implement the maximum power point tracking (MPPT) by controlling the rotor speed of the wind generator. First, the measurements of wind speed, rotor speed of wind power generator and output power of wind power generator are applied to train artificial neural network and to estimate the wind speed. Second, the method mentioned above is applied to estimate and control the optimal rotor speed of the wind turbine so as to output the maximum power. Finally, the result reveals that the control system discussed in this paper extracts the maximum output power of wind generator within the short duration even in the conditions of wind speed and load impedance variation.