Development of Mobile EEF Learning System (MEEFLS) for Mobile Learning Implementation in Kolej Poly-Tech MARA (KPTM)

Mobile learning (m-learning) is a new method in teaching and learning process which combines technology of mobile device with learning materials. It can enhance student's engagement in learning activities and facilitate them to access the learning materials at anytime and anywhere. In Kolej Poly-Tech Mara (KPTM), this method is seen as an important effort in teaching practice and to improve student learning performance. The aim of this paper is to discuss the development of m-learning application called Mobile EEF Learning System (MEEFLS) to be implemented for Electric and Electronic Fundamentals course using Flash, XML (Extensible Markup Language) and J2ME (Java 2 micro edition). System Development Life Cycle (SDLC) was used as an application development approach. It has three modules in this application such as notes or course material, exercises and video. MEELFS development is seen as a tool or a pilot test for m-learning in KPTM.

Harmonic Comparison between Fluorescent and WOLED (White Organic LED) Lamps

Fluorescent and WOLED are widely used because it consumes less energy. However, both lamps cause a harmonics because it has semiconductors components. Harmonic is a distorted sinusoidal electric wave and cause excess heat. This study compares the amount of harmonics generated by both lamps. The test shows that both lamps have THDv(Total Harmonics Distortion of Voltage) almost the same with average 2.5% while the average of WOLED's THDi(Total Harmonics Distortion of Current) is lower than fluorescent has. The average WOLED's THDi is 29.10 % and fluorescent's 'THDi is 87. 23 %.

Discrete Polyphase Matched Filtering-based Soft Timing Estimation for Mobile Wireless Systems

In this paper we present a soft timing phase estimation (STPE) method for wireless mobile receivers operating in low signal to noise ratios (SNRs). Discrete Polyphase Matched (DPM) filters, a Log-maximum a posterior probability (MAP) and/or a Soft-output Viterbi algorithm (SOVA) are combined to derive a new timing recovery (TR) scheme. We apply this scheme to wireless cellular communication system model that comprises of a raised cosine filter (RCF), a bit-interleaved turbo-coded multi-level modulation (BITMM) scheme and the channel is assumed to be memory-less. Furthermore, no clock signals are transmitted to the receiver contrary to the classical data aided (DA) models. This new model ensures that both the bandwidth and power of the communication system is conserved. However, the computational complexity of ideal turbo synchronization is increased by 50%. Several simulation tests on bit error rate (BER) and block error rate (BLER) versus low SNR reveal that the proposed iterative soft timing recovery (ISTR) scheme outperforms the conventional schemes.

Project Complexity Indices based on Topology Features

The heuristic decision rules used for project scheduling will vary depending upon the project-s size, complexity, duration, personnel, and owner requirements. The concept of project complexity has received little detailed attention. The need to differentiate between easy and hard problem instances and the interest in isolating the fundamental factors that determine the computing effort required by these procedures inspired a number of researchers to develop various complexity measures. In this study, the most common measures of project complexity are presented. A new measure of project complexity is developed. The main privilege of the proposed measure is that, it considers size, shape and logic characteristics, time characteristics, resource demands and availability characteristics as well as number of critical activities and critical paths. The degree of sensitivity of the proposed measure for complexity of project networks has been tested and evaluated against the other measures of complexity of the considered fifty project networks under consideration in the current study. The developed measure showed more sensitivity to the changes in the network data and gives accurate quantified results when comparing the complexities of networks.

Cascaded ANN for Evaluation of Frequency and Air-gap Voltage of Self-Excited Induction Generator

Self-Excited Induction Generator (SEIG) builds up voltage while it enters in its magnetic saturation region. Due to non-linear magnetic characteristics, the performance analysis of SEIG involves cumbersome mathematical computations. The dependence of air-gap voltage on saturated magnetizing reactance can only be established at rated frequency by conducting a laboratory test commonly known as synchronous run test. But, there is no laboratory method to determine saturated magnetizing reactance and air-gap voltage of SEIG at varying speed, terminal capacitance and other loading conditions. For overall analysis of SEIG, prior information of magnetizing reactance, generated frequency and air-gap voltage is essentially required. Thus, analytical methods are the only alternative to determine these variables. Non-existence of direct mathematical relationship of these variables for different terminal conditions has forced the researchers to evolve new computational techniques. Artificial Neural Networks (ANNs) are very useful for solution of such complex problems, as they do not require any a priori information about the system. In this paper, an attempt is made to use cascaded neural networks to first determine the generated frequency and magnetizing reactance with varying terminal conditions and then air-gap voltage of SEIG. The results obtained from the ANN model are used to evaluate the overall performance of SEIG and are found to be in good agreement with experimental results. Hence, it is concluded that analysis of SEIG can be carried out effectively using ANNs.

On the EM Algorithm and Bootstrap Approach Combination for Improving Satellite Image Fusion

This paper discusses EM algorithm and Bootstrap approach combination applied for the improvement of the satellite image fusion process. This novel satellite image fusion method based on estimation theory EM algorithm and reinforced by Bootstrap approach was successfully implemented and tested. The sensor images are firstly split by a Bayesian segmentation method to determine a joint region map for the fused image. Then, we use the EM algorithm in conjunction with the Bootstrap approach to develop the bootstrap EM fusion algorithm, hence producing the fused targeted image. We proposed in this research to estimate the statistical parameters from some iterative equations of the EM algorithm relying on a reference of representative Bootstrap samples of images. Sizes of those samples are determined from a new criterion called 'hybrid criterion'. Consequently, the obtained results of our work show that using the Bootstrap EM (BEM) in image fusion improve performances of estimated parameters which involve amelioration of the fused image quality; and reduce the computing time during the fusion process.

Evolutionary Techniques Based Combined Artificial Neural Networks for Peak Load Forecasting

This paper presents a new approach using Combined Artificial Neural Network (CANN) module for daily peak load forecasting. Five different computational techniques –Constrained method, Unconstrained method, Evolutionary Programming (EP), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) – have been used to identify the CANN module for peak load forecasting. In this paper, a set of neural networks has been trained with different architecture and training parameters. The networks are trained and tested for the actual load data of Chennai city (India). A set of better trained conventional ANNs are selected to develop a CANN module using different algorithms instead of using one best conventional ANN. Obtained results using CANN module confirm its validity.

The Index of Sustainable Functionality: An Application for Measuring Sustainability

The index of sustainable functionality (ISF) is an adaptive, multi-criteria technique that is used to measure sustainability; it is a concept that can be transposed to many regions throughout the world. An ISF application of the Southern Regional Organisation of Councils (SouthROC) in South East Queensland (SEQ) – the fastest growing region in Australia – indicated over a 25 year period an increase of over 10% level of functionality from 58.0% to 68.3%. The ISF of SouthROC utilised methodologies that derived from an expert panel based approach. The overall results attained an intermediate level of functionality which amounted to related concerns of economic progress and lack of social awareness. Within the region, a solid basis for future testing by way of measured changes and developed trends can be established. In this regard as management tool, the ISF record offers support for regional sustainability practice and decision making alike. This research adaptively analyses sustainability – a concept that is lacking throughout much of the academic literature and any reciprocal experimentation. This lack of knowledge base has been the emphasis of where future sustainability research can grow from and prove useful in rapidly growing regions. It is the intentions of this research to help further develop the notions of index-based quantitative sustainability.

Combined Sewer Overflow forecasting with Feed-forward Back-propagation Artificial Neural Network

A feed-forward, back-propagation Artificial Neural Network (ANN) model has been used to forecast the occurrences of wastewater overflows in a combined sewerage reticulation system. This approach was tested to evaluate its applicability as a method alternative to the common practice of developing a complete conceptual, mathematical hydrological-hydraulic model for the sewerage system to enable such forecasts. The ANN approach obviates the need for a-priori understanding and representation of the underlying hydrological hydraulic phenomena in mathematical terms but enables learning the characteristics of a sewer overflow from the historical data. The performance of the standard feed-forward, back-propagation of error algorithm was enhanced by a modified data normalizing technique that enabled the ANN model to extrapolate into the territory that was unseen by the training data. The algorithm and the data normalizing method are presented along with the ANN model output results that indicate a good accuracy in the forecasted sewer overflow rates. However, it was revealed that the accurate forecasting of the overflow rates are heavily dependent on the availability of a real-time flow monitoring at the overflow structure to provide antecedent flow rate data. The ability of the ANN to forecast the overflow rates without the antecedent flow rates (as is the case with traditional conceptual reticulation models) was found to be quite poor.

Optimal Sizing of a Hybrid Wind/PV Plant Considering Reliability Indices

The utilization of renewable energy sources in electric power systems is increasing quickly because of public apprehensions for unpleasant environmental impacts and increase in the energy costs involved with the use of conventional energy sources. Despite the application of these energy sources can considerably diminish the system fuel costs, they can also have significant influence on the system reliability. Therefore an appropriate combination of the system reliability indices level and capital investment costs of system is vital. This paper presents a hybrid wind/photovoltaic plant, with the aim of supplying IEEE reliability test system load pattern while the plant capital investment costs is minimized by applying a hybrid particle swarm optimization (PSO) / harmony search (HS) approach, and the system fulfills the appropriate level of reliability.

Improving Image Quality in Remote Sensing Satellites using Channel Coding

Among other factors that characterize satellite communication channels is their high bit error rate. We present a system for still image transmission over noisy satellite channels. The system couples image compression together with error control codes to improve the received image quality while maintaining its bandwidth requirements. The proposed system is tested using a high resolution satellite imagery simulated over the Rician fading channel. Evaluation results show improvement in overall system including image quality and bandwidth requirements compared to similar systems with different coding schemes.

Technological Innovation Persistence Organizational Innovation Matters

Organizational innovation favors technological innovation, but does it also influence technological innovation persistence? This article investigates empirically the pattern of technological innovation persistence and tests the potential impact of organizational innovation using firm-level data from three waves of the French Community Innovation Surveys. Evidence shows a positive effect of organizational innovation on technological innovation persistence, according to various measures of organizational innovation. Moreover, this impact is more significant for complex innovators (i.e., those who innovate in both products and processes). These results highlight the complexity of managing organizational practices with regard to the firm-s technological innovation. They also add to comprehension of the drivers of innovation persistence, through a focus on an often forgotten dimension of innovation in a broader sense.

A New Rigid Fistulectomy Set for Minimally Invasive “Core-Out“ Excision of High Anal Fistulas

In this article, we propose a new surgical device for circumferentially excision of high anal fistulas in a minimally invasive manner. The new apparatus works on the basis of axially rotating and moving a tubular blade along a fistulous tract straightened using a rigid straight guidewire. As the blade moves along the tract, its sharp circular cutting edge circumferentially separates approximately 2.25 mm thickness of tract encircling the rigid guidewire. We used the new set to excise two anal fistulas in a 62-year-old male patient, an extrasphincteric type and a long tract with no internal opening. With regard to the results of this test, the new device can be considered as a sphincter preserving mechanism for treatment of high anal fistulas. Consequently, a major reduction in the risk of fecal incontinence, recurrence rate, convalescence period and patient morbidity may be achieved using the new device for treatment of fistula-in-ano.

Objectivity, Reliability and Validity of the 90º Push-Ups Test Protocol Among Male and Female Students of Sports Science Program

This study was conducted to determine the objectivity, reliability and validity of the 90º push-ups test protocol among male and female students of Sports Science Program, Faculty of Sports Science and Coaching Sultan Idris University of Education. Samples (n = 300), consisted of males (n = 168) and females (n = 132) students were randomly selected for this study. Researchers tested the 90º push-ups on the sample twice in a single trial, test and re-test protocol in the bench press test. Pearson-Product Moment Correlation method's was used to determine the value of objectivity, reliability and validity testing. The findings showed that the 900 pushups test protocol showed high consistency between the two testers with a value of r = .99. Likewise, The reliability value between test and re-test for the 90º push-ups test for the male (r=.93) and female (r=.93) students was also high. The results showed a correlation between 90º push-ups test and bench press test for boys was r = .64 and girls was r = .28. This finding indicates that the use of the 90º push-ups to test muscular strength and endurance in the upper body of males has a higher validity values than female students.

Effects of a Methanol Fraction of the Leaves of Leonotis leonurus on the Blood Pressure and Heart Rate of Normotensive Male Wistar Rats

Leonotisleonurus a shrub indigenous to Southern Africa is widely used in traditional medicine to treat a variety of conditions ranging from skin diseases and cough to epileptic fits and ‘heart problems’. Studies on the aqueous extract of the leaves have indicated cycloxegenase enzyme inhibitory activity and an antihypertensive effect. Five methanol leaf extract fractions (MLEa - MLEe) of L. leonurus were tested on anaesthetized normotensive male Wistar rats (AWR) and isolated perfused working rat hearts (IWH). Fraction MLEc (0.01mg/kg – 0.05mg/kg) induced significant increases in BP and HR in AWR and positive chronotropic and inotropic effects in IWH (1.0mg/ml – 5.0mg/ml). Pre-administration of atenolol (2.0mg/kg) and prazosin (60μg/kg) significantly inhibited MLEc effect on HR and MAP respectively in vivo, while atenolol (7.0mg/ml) pre-perfusion significantly inhibited MLEc effect in vitro. The hypertensive effect of MLEc is probably via β1agonism. Results also indicate the presence of multiple cardioactive compounds in L. leonurus.

Digital filters for Hot-Mix Asphalt Complex Modulus Test Data Using Genetic Algorithm Strategies

The dynamic or complex modulus test is considered to be a mechanistically based laboratory test to reliably characterize the strength and load-resistance of Hot-Mix Asphalt (HMA) mixes used in the construction of roads. The most common observation is that the data collected from these tests are often noisy and somewhat non-sinusoidal. This hampers accurate analysis of the data to obtain engineering insight. The goal of the work presented in this paper is to develop and compare automated evolutionary computational techniques to filter test noise in the collection of data for the HMA complex modulus test. The results showed that the Covariance Matrix Adaptation-Evolutionary Strategy (CMA-ES) approach is computationally efficient for filtering data obtained from the HMA complex modulus test.

Modeling and Analysis of SVPWM Based Dynamic Voltage Restorer

In this paper the modeling and analysis of Space Vector Pulse Width Modulation (SVPWM) based Dynamic Voltage Restorer (DVR) using PSCAD/EMTDC software will be presented in details. The simulation includes full modeling of the SVPWM technique used to control the DVR inverter. A test power system composed of three phase voltage source, sag generator, DVR and three phase resistive load is used to demonstrate restoration capability of the DVR. The simulation results of the presented DVR proved excellent voltage sag mitigation to protect sensitive loads.

A FEM Study of Explosive Welding of Double Layer Tubes

Explosive welding is a process which uses explosive detonation to move the flyer plate material into the base material to produce a solid state joint. Experimental tests have been carried out by other researchers; have been considered to explosively welded aluminium 7039 and steel 4340 tubes in one step. The tests have been done using various stand-off distances and explosive ratios. Various interface geometries have been obtained from these experiments. In this paper, all the experiments carried out were simulated using the finite element method. The flyer plate and collision velocities obtained from the analysis were validated by the pin-measurement experiments. The numerical results showed that very high localized plastic deformation produced at the bond interface. The Ls_dyna_971 FEM has been used for all simulation process.

Durability of LDPE Geomembrane within Sealing System of MSW (Landfill)

Analyse of locally manufactured Low Density Polyethylene (LDPE) durability, used within lining systems at bottom of Municipal Solid Waste (landfill), is done in the present work. For this end, short and middle time creep behavior under tension of the analyzed material is carried out. The locally manufactured material is tested and compared to the European one (LDPE-CE). Both materials was tested in 03 various mediums: ambient and two aggressive (salty water and foam water), using three specimens in each case. A testing campaign is carried out using an especially designed and achieved testing bench. Moreover, characterisation tests were carried out to evaluate the medium effect on the mechanical properties of the tested material (LDPE). Furthermore, experimental results have been used to establish a law regression which can be used to predict creep behaviour of the analyzed material. As a result, the analyzed LDPE material has showed a good stability in different ambient and aggressive mediums; as well, locally manufactured LDPE seems more flexible, compared with the European one. This makes it more useful to the desired application.

Evolving a Fuzzy Rule-Base for Image Segmentation

A new method for color image segmentation using fuzzy logic is proposed in this paper. Our aim here is to automatically produce a fuzzy system for color classification and image segmentation with least number of rules and minimum error rate. Particle swarm optimization is a sub class of evolutionary algorithms that has been inspired from social behavior of fishes, bees, birds, etc, that live together in colonies. We use comprehensive learning particle swarm optimization (CLPSO) technique to find optimal fuzzy rules and membership functions because it discourages premature convergence. Here each particle of the swarm codes a set of fuzzy rules. During evolution, a population member tries to maximize a fitness criterion which is here high classification rate and small number of rules. Finally, particle with the highest fitness value is selected as the best set of fuzzy rules for image segmentation. Our results, using this method for soccer field image segmentation in Robocop contests shows 89% performance. Less computational load is needed when using this method compared with other methods like ANFIS, because it generates a smaller number of fuzzy rules. Large train dataset and its variety, makes the proposed method invariant to illumination noise