A Comparative CFD Study on Solar Dimple Plate Collector with Flat Plate Collector to Augment the Thermal Performance

It is well known that surface enhancements play an important role in augmenting the thermal performance of flat plate solar collector. In this paper, an attempt is made to explain in a comparative way the effect of surface geometry of solar collector having dimple geometry with that of a flat plate solar collector of the same size. A CFD analysis was carried out for the two cases, subjected to a constant heat flux of 600W/m2 and 1000W/m2. It can be inferred from the study that the absorber plate temperature shows a rise of average surface temperature of about 50C for the dimple solar collector when compared to a flat plate solar collector. Most importantly, the average exit water temperature shows a marked improvement of about 5.50C for a dimple solar collector as compared to that of a flat plate solar collector.

Distributed Estimation Using an Improved Incremental Distributed LMS Algorithm

In this paper we consider the problem of distributed adaptive estimation in wireless sensor networks for two different observation noise conditions. In the first case, we assume that there are some sensors with high observation noise variance (noisy sensors) in the network. In the second case, different variance for observation noise is assumed among the sensors which is more close to real scenario. In both cases, an initial estimate of each sensor-s observation noise is obtained. For the first case, we show that when there are such sensors in the network, the performance of conventional distributed adaptive estimation algorithms such as incremental distributed least mean square (IDLMS) algorithm drastically decreases. In addition, detecting and ignoring these sensors leads to a better performance in a sense of estimation. In the next step, we propose a simple algorithm to detect theses noisy sensors and modify the IDLMS algorithm to deal with noisy sensors. For the second case, we propose a new algorithm in which the step-size parameter is adjusted for each sensor according to its observation noise variance. As the simulation results show, the proposed methods outperforms the IDLMS algorithm in the same condition.

Load Flow Analysis: An Overview

The load flow study in a power system constitutes a study of paramount importance. The study reveals the electrical performance and power flows (real and reactive) for specified condition when the system is operating under steady state. This paper gives an overview of different techniques used for load flow study under different specified conditions.

The Effect of Sport Specific Exercises on the Visual Skills of Rugby Players

Introduction: Visual performance is an important factor in sport excellence. Visual involvement in a sport varies according to environmental demands associated with that sport. These environmental demands are matched by a task specific motor response. The purpose of this study was to determine if sport specific exercises will improve the visual performance of male rugby players, in order to achieve maximal results on the sports field. Materials & Methods: Twenty six adult male rugby players, aged 16-22, were chosen as subjects. In order to evaluate the effect of sport specific exercises on visual skills, a pre-test - post-test experimental group design was adopted for the study. Results: Significant differences (p≤0.05) were seen in the focussing, tracking, vergence, sequencing, eye-hand coordination and visualisation components Discussion & Conclusions: Sport specific exercises improved visual skills in rugby players which may provide them with an advantage over their opponents. This study suggests that these training programs and participation in regular on-line EyeDrills sports vision exercises (www.eyedrills.co.za) aimed at improving the athlete-s visual coordination, concentration, focus, hand-eye co-ordination, anticipation and motor response should be incorpotated in the rugby players exercise regime.

Optimization of a Hybrid Wind-Pv-Diesel Standalone System: Case Chlef, Algeria

In this work, an attempt is made to design an optimal wind/pv/diesel hybrid power system for a village of Ain Merane, Chlef, Algeria, where the wind speed and solar radiation measurements were made. The aim of this paper is the optimization of a hybrid wind/solar/diesel system applied in term of technical and economic feasibility by simulation using HOMER. A comparison was made between the performance of wind/pv/diesel system and the classic connecting system.

Quantification of Technology Innovation Usinga Risk-Based Framework

There is significant interest in achieving technology innovation through new product development activities. It is recognized, however, that traditional project management practices focused only on performance, cost, and schedule attributes, can often lead to risk mitigation strategies that limit new technology innovation. In this paper, a new approach is proposed for formally managing and quantifying technology innovation. This approach uses a risk-based framework that simultaneously optimizes innovation attributes along with traditional project management and system engineering attributes. To demonstrate the efficacy of the new riskbased approach, a comprehensive product development experiment was conducted. This experiment simultaneously managed the innovation risks and the product delivery risks through the proposed risk-based framework. Quantitative metrics for technology innovation were tracked and the experimental results indicate that the risk-based approach can simultaneously achieve both project deliverable and innovation objectives.

Effect of Dynamic Stall, Finite Aspect Ratio and Streamtube Expansion on VAWT Performance Prediction using the BE-M Model

A multiple-option analytical model for the evaluation of the energy performance and distribution of aerodynamic forces acting on a vertical-axis Darrieus wind turbine depending on both rotor architecture and operating conditions is presented. For this purpose, a numerical algorithm, capable of generating the desired rotor conformation depending on design geometric parameters, is coupled to a Single/Double-Disk Multiple-Streamtube Blade Element – Momentum code. Both single and double-disk configurations are analyzed and model predictions are compared to literature experimental data in order to test the capability of the code for predicting rotor performance. Effective airfoil characteristics based on local blade Reynolds number are obtained through interpolation of literature low-Reynolds airfoil databases. Some corrections are introduced inside the original model with the aim of simulating also the effects of blade dynamic stall, rotor streamtube expansion and blade finite aspect ratio, for which a new empirical relationship to better fit the experimental data is proposed. In order to predict also open field rotor operation, a freestream wind shear profile is implemented, reproducing the effect of atmospheric boundary layer.

Wormhole Attack Detection in Wireless Sensor Networks

The nature of wireless ad hoc and sensor networks make them very attractive to attackers. One of the most popular and serious attacks in wireless ad hoc networks is wormhole attack and most proposed protocols to defend against this attack used positioning devices, synchronized clocks, or directional antennas. This paper analyzes the nature of wormhole attack and existing methods of defending mechanism and then proposes round trip time (RTT) and neighbor numbers based wormhole detection mechanism. The consideration of proposed mechanism is the RTT between two successive nodes and those nodes- neighbor number which is needed to compare those values of other successive nodes. The identification of wormhole attacks is based on the two faces. The first consideration is that the transmission time between two wormhole attack affected nodes is considerable higher than that between two normal neighbor nodes. The second detection mechanism is based on the fact that by introducing new links into the network, the adversary increases the number of neighbors of the nodes within its radius. This system does not require any specific hardware, has good performance and little overhead and also does not consume extra energy. The proposed system is designed in ad hoc on-demand distance vector (AODV) routing protocol and analysis and simulations of the proposed system are performed in network simulator (ns-2).

Analysis of Bit Error Rate Improvement in MFSK Communication Link

Data rate, tolerable bit error rate or frame error rate and range & coverage are the key performance requirement of a communication link. In this paper performance of MFSK link is analyzed in terms of bit error rate, number of errors and total number of data processed. In the communication link model proposed, which is implemented using MATLAB block set, an improvement in BER is observed. Different parameters which effects and enables to keep BER low in M-ary communication system are also identified.

Motion Control of TUAV having Eight Rotors for Enhanced Situational Awareness

This paper focuses on a critical component of the situational awareness (SA), the control of autonomous vertical flight for tactical unmanned aerial vehicle (TUAV). With the SA strategy, we proposed a two stage flight control procedure using two autonomous control subsystems to address the dynamics variation and performance requirement difference in initial and final stages of flight trajectory for a nontrivial nonlinear eight-rotor helicopter model. This control strategy for chosen model of mini-TUAV has been verified by simulation of hovering maneuvers using software package Simulink and demonstrated good performance for fast stabilization of engines in hovering, consequently, fast SA with economy in energy of batteries can be asserted during search-andrescue operations.

Shape Error Concealment for Shape Independent Transform Coding

Arbitrarily shaped video objects are an important concept in modern video coding methods. The techniques presently used are not based on image elements but rather video objects having an arbitrary shape. In this paper, spatial shape error concealment techniques to be used for object-based image in error-prone environments are proposed. We consider a geometric shape representation consisting of the object boundary, which can be extracted from the α-plane. Three different approaches are used to replace a missing boundary segment: Bézier interpolation, Bézier approximation and NURBS approximation. Experimental results on object shape with different concealment difficulty demonstrate the performance of the proposed methods. Comparisons with proposed methods are also presented.

Effectiveness and Equity: New Challenges for Social Recognition in Higher Education

Today, Higher Education in a global scope is subordinated to the greater institutional controls through the policies of the Quality of Education. These include processes of over evaluation of all the academic activities: students- and professors- performance, educational logistics, managerial standards for the administration of institutions of higher education, as well as the establishment of the imaginaries of excellence and prestige as the foundations on which universities of the XXI century will focus their present and future goals and interests. But at the same time higher education systems worldwide are facing the most profound crisis of sense and meaning and attending enormous mutations in their identity. Based in a qualitative research approach, this paper shows the social configurations that the scholars at the Universities in Mexico build around the discourse of the Quality of Education, and how these policies put in risk the social recognition of these individuals.

Solving a New Mixed-Model Assembly LineSequencing Problem in a MTO Environment

In the last decades to supply the various and different demands of clients, a lot of manufacturers trend to use the mixedmodel assembly line (MMAL) in their production lines, since this policy make possible to assemble various and different models of the equivalent goods on the same line with the MTO approach. In this article, we determine the sequence of (MMAL) line, with applying the kitting approach and planning of rest time for general workers to reduce the wastages, increase the workers effectiveness and apply the sector of lean production approach. This Multi-objective sequencing problem solved in small size with GAMS22.2 and PSO meta heuristic in 10 test problems and compare their results together and conclude that their results are very similar together, next we determine the important factors in computing the cost, which improving them cost reduced. Since this problem, is NPhard in large size, we use the particle swarm optimization (PSO) meta-heuristic for solving it. In large size we define some test problems to survey it-s performance and determine the important factors in calculating the cost, that by change or improved them production in minimum cost will be possible.

Analysis of Noise Level Effects on Signal-Averaged Electrocardiograms

Noise level has critical effects on the diagnostic performance of signal-averaged electrocardiogram (SAECG), because the true starting and end points of QRS complex would be masked by the residual noise and sensitive to the noise level. Several studies and commercial machines have used a fixed number of heart beats (typically between 200 to 600 beats) or set a predefined noise level (typically between 0.3 to 1.0 μV) in each X, Y and Z lead to perform SAECG analysis. However different criteria or methods used to perform SAECG would cause the discrepancies of the noise levels among study subjects. According to the recommendations of 1991 ESC, AHA and ACC Task Force Consensus Document for the use of SAECG, the determinations of onset and offset are related closely to the mean and standard deviation of noise sample. Hence this study would try to perform SAECG using consistent root-mean-square (RMS) noise levels among study subjects and analyze the noise level effects on SAECG. This study would also evaluate the differences between normal subjects and chronic renal failure (CRF) patients in the time-domain SAECG parameters. The study subjects were composed of 50 normal Taiwanese and 20 CRF patients. During the signal-averaged processing, different RMS noise levels were adjusted to evaluate their effects on three time domain parameters (1) filtered total QRS duration (fQRSD), (2) RMS voltage of the last QRS 40 ms (RMS40), and (3) duration of the low amplitude signals below 40 μV (LAS40). The study results demonstrated that the reduction of RMS noise level can increase fQRSD and LAS40 and decrease the RMS40, and can further increase the differences of fQRSD and RMS40 between normal subjects and CRF patients. The SAECG may also become abnormal due to the reduction of RMS noise level. In conclusion, it is essential to establish diagnostic criteria of SAECG using consistent RMS noise levels for the reduction of the noise level effects.

The Effects of Immersion on Visual Attention and Detection of Signals Performance for Virtual Reality Training Systems

The Virtual Reality (VR) is becoming increasingly important for business, education, and entertainment, therefore VR technology have been applied for training purposes in the areas of military, safety training and flying simulators. In particular, the superior and high reliability VR training system is very important in immersion. Manipulation training in immersive virtual environments is difficult partly because users must do without the hap contact with real objects they rely on in the real world to orient themselves and their manipulated. In this paper, we create a convincing questionnaire of immersion and an experiment to assess the influence of immersion on performance in VR training system. The Immersion Questionnaire (IQ) included spatial immersion, Psychological immersion, and Sensory immersion. We show that users with a training system complete visual attention and detection of signals. Twenty subjects were allocated to a factorial design consisting of two different VR systems (Desktop VR and Projector VR). The results indicated that different VR representation methods significantly affected the participants- Immersion dimensions.

Full-genomic Network Inference for Non-model organisms: A Case Study for the Fungal Pathogen Candida albicans

Reverse engineering of full-genomic interaction networks based on compendia of expression data has been successfully applied for a number of model organisms. This study adapts these approaches for an important non-model organism: The major human fungal pathogen Candida albicans. During the infection process, the pathogen can adapt to a wide range of environmental niches and reversibly changes its growth form. Given the importance of these processes, it is important to know how they are regulated. This study presents a reverse engineering strategy able to infer fullgenomic interaction networks for C. albicans based on a linear regression, utilizing the sparseness criterion (LASSO). To overcome the limited amount of expression data and small number of known interactions, we utilize different prior-knowledge sources guiding the network inference to a knowledge driven solution. Since, no database of known interactions for C. albicans exists, we use a textmining system which utilizes full-text research papers to identify known regulatory interactions. By comparing with these known regulatory interactions, we find an optimal value for global modelling parameters weighting the influence of the sparseness criterion and the prior-knowledge. Furthermore, we show that soft integration of prior-knowledge additionally improves the performance. Finally, we compare the performance of our approach to state of the art network inference approaches.

A Methodology for Quality Problems Diagnosis in SMEs

This article proposes a new methodology to be used by SMEs (Small and Medium enterprises) to characterize their performance in quality, highlighting weaknesses and area for improvement. The methodology aims to identify the principal causes of quality problems and help to prioritize improvement initiatives. This is a self-assessment methodology that intends to be easy to implement by companies with low maturity level in quality. The methodology is organized in six different steps which includes gathering information about predetermined processes and subprocesses of quality management, defined based on the well-known Juran-s trilogy for quality management (Quality planning, quality control and quality improvement) and, predetermined results categories, defined based on quality concept. A set of tools for data collecting and analysis, such as interviews, flowcharts, process analysis diagrams and Failure Mode and effects Analysis (FMEA) are used. The article also presents the conclusions obtained in the application of the methodology in two cases studies.

Numerical Investigation of Baffle Effect on the Flow in a Rectangular Primary Sedimentation Tank

It is essential to have a uniform and calm flow field for a settling tank to have high performance. In general, the recirculation zones always occurred in sedimentation tanks. The presence of these regions may have different effects. The nonuniformity of the velocity field, the short-circuiting at the surface and the motion of the jet at the bed of the tank that occurs because of the recirculation in the sedimentation layer, are affected by the geometry of the tank. There are some ways to decrease the size of these dead zones, which would increase the performance. One of the ways is to use a suitable baffle configuration. In this study, the presence of baffle with different position has been investigated by a finite volume method, with VOF (Volume of Fluid) model. Besides, the k-ε turbulence model is used in the numerical calculations. The results indicate that the best position of the baffle is obtained when the volume of the recirculation region is minimized or is divided to smaller part and the flow field trend to be uniform in the settling zone.

Microwave Imaging by Application of Information Theory Criteria in MUSIC Algorithm

The performance of time-reversal MUSIC algorithm will be dramatically degrades in presence of strong noise and multiple scattering (i.e. when scatterers are close to each other). This is due to error in determining the number of scatterers. The present paper provides a new approach to alleviate such a problem using an information theoretic criterion referred as minimum description length (MDL). The merits of the novel approach are confirmed by the numerical examples. The results indicate the time-reversal MUSIC yields accurate estimate of the target locations with considerable noise and multiple scattering in the received signals.

Consumer Product Demand Forecasting based on Artificial Neural Network and Support Vector Machine

The nature of consumer products causes the difficulty in forecasting the future demands and the accuracy of the forecasts significantly affects the overall performance of the supply chain system. In this study, two data mining methods, artificial neural network (ANN) and support vector machine (SVM), were utilized to predict the demand of consumer products. The training data used was the actual demand of six different products from a consumer product company in Thailand. The results indicated that SVM had a better forecast quality (in term of MAPE) than ANN in every category of products. Moreover, another important finding was the margin difference of MAPE from these two methods was significantly high when the data was highly correlated.