A New Face Recognition Method using PCA, LDA and Neural Network

In this paper, a new face recognition method based on PCA (principal Component Analysis), LDA (Linear Discriminant Analysis) and neural networks is proposed. This method consists of four steps: i) Preprocessing, ii) Dimension reduction using PCA, iii) feature extraction using LDA and iv) classification using neural network. Combination of PCA and LDA is used for improving the capability of LDA when a few samples of images are available and neural classifier is used to reduce number misclassification caused by not-linearly separable classes. The proposed method was tested on Yale face database. Experimental results on this database demonstrated the effectiveness of the proposed method for face recognition with less misclassification in comparison with previous methods.

A New Efficient Scalable BIST Full Adder using Polymorphic Gates

Among various testing methodologies, Built-in Self- Test (BIST) is recognized as a low cost, effective paradigm. Also, full adders are one of the basic building blocks of most arithmetic circuits in all processing units. In this paper, an optimized testable 2- bit full adder as a test building block is proposed. Then, a BIST procedure is introduced to scale up the building block and to generate a self testable n-bit full adders. The target design can achieve 100% fault coverage using insignificant amount of hardware redundancy. Moreover, Overall test time is reduced by utilizing polymorphic gates and also by testing full adder building blocks in parallel.

Cubic Trigonometric B-Spline Applied to Linear Two-Point Boundary Value Problems of Order Two

Linear two-point boundary value problems of order two are solved using cubic trigonometric B-spline interpolation method (CTBIM). Cubic trigonometric B-spline is a piecewise function consisting of trigonometric equations. This method is tested on some problems and the results are compared with cubic B-spline interpolation method (CBIM) from the literature. CTBIM is found to approximate the solution slightly more accurately than CBIM if the problems are trigonometric.

Fabrication of Single Crystal of Mg Alloys Containing Rare Earth Elements

Single crystals of Magnesium alloys such as Mg-1Al, Mg-1Zn-0.5Y, Mg-3Li, and AZ31 alloys were successfully fabricated in this study by employing the modified Bridgman method. Single crystals of pure Mg were also made in this study. To determine the exact orientation of crystals, Laue back-reflection method and pole figure measurement were carried out on each single crystal. Dimensions of single crystals were 10 mm in diameter and 120 mm in length. Hardness and compression tests were conducted and the results revealed that hardness and the strength strongly depended on the orientation. The closer to basal one the orientation was, the higher hardness and compressive strength were. The effect of alloying was not higher than that of orientation. After compressive deformation of single crystals, the orientation of the crystals was found to rotate and to be parallel to the basal orientation.

Hybrid Artificial Immune System for Job Shop Scheduling Problem

The job shop scheduling problem (JSSP) is a notoriously difficult problem in combinatorial optimization. This paper presents a hybrid artificial immune system for the JSSP with the objective of minimizing makespan. The proposed approach combines the artificial immune system, which has a powerful global exploration capability, with the local search method, which can exploit the optimal antibody. The antibody coding scheme is based on the operation based representation. The decoding procedure limits the search space to the set of full active schedules. In each generation, a local search heuristic based on the neighborhood structure proposed by Nowicki and Smutnicki is applied to improve the solutions. The approach is tested on 43 benchmark problems taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.

Assessment of Microbial Pollution of the Dental Chairs Water System (Pseudomonas aeruginosa) in the City of Tripoli, Libya

This study mainly aims at assessing the level of microbial pollution of the water used in the chair system in dental clinics. For this purpose 36 samples have been randomly collected from a number of dental surgeries in the city of Tripoli in Libya. However, 32 of the samples have tested positive to microbial pollution including 13 of the samples, which have tested positives to Pseudomonas aeruginosa. Based on the results of the test a further investigation of the biofilms incorporated within the dental chair system has been conducted. The laboratory tests of biofilms with similar design to those found in dental chairs have proved that bacterial pollution takes place through saliva of the patients who use the chairs, and that this saliva is rich with nutrients which provides a suitable breeding ground for all types of bacteria.

Generating Normally Distributed Clusters by Means of a Self-organizing Growing Neural Network– An Application to Market Segmentation –

This paper presents a new growing neural network for cluster analysis and market segmentation, which optimizes the size and structure of clusters by iteratively checking them for multivariate normality. We combine the recently published SGNN approach [8] with the basic principle underlying the Gaussian-means algorithm [13] and the Mardia test for multivariate normality [18, 19]. The new approach distinguishes from existing ones by its holistic design and its great autonomy regarding the clustering process as a whole. Its performance is demonstrated by means of synthetic 2D data and by real lifestyle survey data usable for market segmentation.

The Influence of User Involvement and Personal Innovativeness on User Behavior

The search for factors that influence user behavior has remained an important theme for both the academic and practitioner Information Systems Communities. In this paper we examine relevant user behaviors in the phase after adoption and investigate two factors that are expected to influence such behaviors, namely User Involvement (UI) and Personal Innovativeness in IT (PIIT). We conduct a field study to examine how these factors influence postadoption behavior and how they are interrelated. Building on theoretical premises and prior empirical findings, we propose and test two alternative models of the relationship between these factors. Our results reveal that the best explanation of post-adoption behavior is provided by the model where UI and PIIT independently influence post-adoption behavior. Our findings have important implications for research and practice. To that end, we offer directions for future research.

The Comparison of Form Drag and Profile Dragof a Wind Turbine Blade Section in Pitching Oscillation

Extensive wind tunnel tests have been conducted to investigate the unsteady flow field over and behind a 2D model of a 660 kW wind turbine blade section in pitching motion. The surface pressure and wake dynamic pressure variation at a distance of 1.5 chord length from trailing edge were measured by pressure transducers during several oscillating cycles at 3 reduced frequencies and oscillating amplitudes. Moreover, form drag and linear momentum deficit are extracted and compared at various conditions. The results show that the wake velocity field and surface pressure of the model have similar behavior before and after the airfoil beyond the static stall angle of attack. In addition, the effects of reduced frequency and oscillation amplitudes are discussed.

Optimum Neural Network Architecture for Precipitation Prediction of Myanmar

Nowadays, precipitation prediction is required for proper planning and management of water resources. Prediction with neural network models has received increasing interest in various research and application domains. However, it is difficult to determine the best neural network architecture for prediction since it is not immediately obvious how many input or hidden nodes are used in the model. In this paper, neural network model is used as a forecasting tool. The major aim is to evaluate a suitable neural network model for monthly precipitation mapping of Myanmar. Using 3-layerd neural network models, 100 cases are tested by changing the number of input and hidden nodes from 1 to 10 nodes, respectively, and only one outputnode used. The optimum model with the suitable number of nodes is selected in accordance with the minimum forecast error. In measuring network performance using Root Mean Square Error (RMSE), experimental results significantly show that 3 inputs-10 hiddens-1 output architecture model gives the best prediction result for monthly precipitation in Myanmar.

An Experimental Investigation of Heating in Induction Motors

The ability to predict an accurate temperature distribution requires the knowledge of the losses, the thermal characteristics of the materials, and the cooling conditions, all of which are very difficult to quantify. In this paper, the impact of the effects of iron and copper losses are investigated separately and their effects on the heating in various points of the stator of an induction motor, is highlighted by using two simple tests. In addition, the effect of a defect, such as an open circuit in a phase of the stator, on the heating is also obtained by a no-load test. The squirrel cage induction motor is rated at 2.2 kW; 380 V; 5.2 A; Δ connected; 50 Hz; 1420 rpm and the class of insulation F, has been thermally tested under several load conditions. Several thermocouples were placed in strategic points of the stator.

Downtrend Algorithm and Hedging Strategy in Futures Market

The paper investigates downtrend algorithm and trading strategy based on chart pattern recognition and technical analysis in futures market. The proposed chart formation is a pattern with the lowest low in the middle and one higher low on each side. The contribution of this paper lies in the reinforcement of statements about the profitability of momentum trend trading strategies. Practical benefit of the research is a trading algorithm in falling markets and back-test analysis in futures markets. When based on daily data, the algorithm has generated positive results, especially when the market had downtrend period. Downtrend algorithm can be applied as a hedge strategy against possible sudden market crashes. The proposed strategy can be interesting for futures traders, hedge funds or scientific researchers performing technical or algorithmic market analysis based on momentum trend trading.

Developing Efficient Testing and Unloading Procedures for a Local Sewage Holding Pit

A local municipality has decided to build a sewage pit to receive residential sewage waste arriving by tank trucks. Daily accumulated waste are to be pumped to a nearby waste water treatment facility to be re-consumed for agricultural and construction projects. A discrete-event simulation model using Arena Software was constructed to assist in defining the capacity of the system in cubic meters, number of tank trucks to use the system, number of unload docks required, number of standby areas needed and manpower required for data collection at entrance checkpoint and truck tank load toxicity testing. The results of the model are statistically validated. Simulation turned out to be an excellent tool in the facility planning effort for the pit project, as it insured smooth flow lines of tank trucks load discharge and best utilization of facilities on site.

Lateral Behavior of Concrete

Lateral expansion is a factor defining the level of confinement in reinforced concrete columns. Therefore, predicting the lateral strain relationship with axial strain becomes an important issue. Measuring lateral strains in experiments is difficult and only few report experimental lateral strains. Among the existing analytical formulations, two recent models are compared with available test results in this paper with shortcomings highlighted. A new analytical model is proposed here for lateral strain axial strain relationship and is based on the supposition that the concrete behaves linear elastic in the early stages of loading and then nonlinear hardening up to the peak stress and then volumetric expansion. The proposal for the lateral strain axial strain relationship after the peak stress is mainly based on the hypothesis that the plastic lateral strain varies linearly with the plastic axial strain and it is shown that this is related to the lateral confinement level.

Perturbation Based Search Method for Solving Unconstrained Binary Quadratic Programming Problem

This paper presents a perturbation based search method to solve the unconstrained binary quadratic programming problem. The proposed algorithm was tested with some of the standard test problems and the results are reported for 10 instances of 50, 100, 250, & 500 variable problems. A comparison of the performance of the proposed algorithm with other heuristics and optimization software is made. Based on the results, it was found that the proposed algorithm is computationally inexpensive and the solutions obtained match the best known solutions for smaller sized problems. For larger instances, the algorithm is capable of finding a solution within 0.11% of the best known solution. Apart from being used as a stand-alone method, this algorithm could also be incorporated with other heuristics to find better solutions.

Investigation on the Antimicrobial Effect of Ammonyx on Some Pathogenic Microbes Observed on Sweatshirt Sport

In this research, the main aim is to investigate the antimicrobial effectiveness of ammonyx solutions finishing on Sweatshirt Sport with immersion method. 60 Male healthy subjects (football player) participated in this study. They were dressed in a Sweatshirt for 14 days and some microbes found on them were investigated. The antimicrobial effect of different ammonyx solutions(1/100, 1/500, 1/1000, 1/2000 v/v solutions of Ammonyx) on the identified microbes was studied by the zone inhabitation method in vitro. In the next step the Sweatshirt Sports were treated with the same different solutions of ammonyx and the antimicrobial effectiveness was assessed by colony count method in different times and the results were compared whit untreated ones. Some mechanical properties of treated cotton/polyester yarn that used in Sweatshirt Sport were measured after 30 days and were compared with untreated one. Finally after finishing, scanning electron microscopy (SEM) was used to compare the surfaces of the finished and unfinished specimens. The results showed the presence of five pathogenic microbes on Sweatshirt Sports such as Escherichia coli, Staphylococcus aureus, Aspergillus, Mucor and Candida. The inhalation time for treated on Sweatshirt Sports improved. The amount of colony growth on treated clothes reduced considerably and moreover the mechanical tests results showed no significant deterioration effect of studies properties in comparison to the untreated yarn. The visual examination of the SEM indicated that the antimicrobial treatments were applied usefully to fabrics.

On Convergence of Affine Thin Plate Bending Element

In the present paper the displacement-based nonconforming quadrilateral affine thin plate bending finite element ARPQ4 is presented, derived directly from non-conforming quadrilateral thin plate bending finite element RPQ4 proposed by Wanji and Cheung [19]. It is found, however, that element RPQ4 is only conditionally unisolvent. The new element is shown to be inherently unisolvent. This convenient property results in the element ARPQ4 being more robust and thus better suited for computations than its predecessor. The convergence is proved and the rate of convergence estimated. The mathematically rigorous proof of convergence presented in the paper is based on Stummel-s generalized patch test and the consideration of the element approximability condition, which are both necessary and sufficient for convergence.

Mathematical Correlation for Brake Thermal Efficiency and NOx Emission of CI Engine using Ester of Vegetable Oils

The aim of this study is to develop mathematical relationships for the performance parameter brake thermal efficiency (BTE) and emission parameter nitrogen oxides (NOx) for the various esters of vegetable oils used as CI engine fuel. The BTE is an important performance parameter defining the ability of engine to utilize the energy supplied and power developed similarly it is indication of efficiency of fuels used. The esters of cottonseed oil, soybean oil, jatropha oil and hingan oil are prepared using transesterification process and characterized for their physical and main fuel properties including viscosity, density, flash point and higher heating value using standard test methods. These esters are tried as CI engine fuel to analyze the performance and emission parameters in comparison to diesel. The results of the study indicate that esters as a fuel does not differ greatly with that of diesel in properties. The CI engine performance with esters as fuel is in line with the diesel where as the emission parameters are reduced with the use of esters. The correlation developed between BTE and brake power(BP), gross calorific value(CV), air-fuel ratio(A/F), heat carried away by cooling water(HCW). Another equation is developed between the NOx emission and CO, HC, smoke density (SD), exhaust gas temperature (EGT). The equations are verified by comparing the observed and calculated values which gives the coefficient of correlation of 0.99 and 0.96 for the BTE and NOx equations respectively.

Analysis on Influence of Gravity on Convection Heat Transfer in Manned Spacecraft during Terrestrial Test

How to simulate experimentally the air flow and heat transfer under microgravity on the ground is important, which has not been completely solved so far. Influence of gravity on air natural convection results in convection heat transfer on ground difference from that on orbit. In order to obtain air temperature and velocity deviations of manned spacecraft during terrestrial thermal test, dimensionless number analysis and numerical simulation analysis are performed. The calculated temperature distribution and velocity distribution of the horizontal test cases are compared to the vertical cases. The results show that the influence of gravity is neglected for facility drawer racks and more obvious for vertical cabins.

A Meta-Analytic Path Analysis of e-Learning Acceptance Model

This study reports results of a meta-analytic path analysis e-learning Acceptance Model with k = 27 studies, Databases searched included Information Sciences Institute (ISI) website. Variables recorded included perceived usefulness, perceived ease of use, attitude toward behavior, and behavioral intention to use e-learning. A correlation matrix of these variables was derived from meta-analytic data and then analyzed by using structural path analysis to test the fitness of the e-learning acceptance model to the observed aggregated data. Results showed the revised hypothesized model to be a reasonable, good fit to aggregated data. Furthermore, discussions and implications are given in this article.