Investigation of the Tattooed Skin by OCT

The intention of this lessons is to assess the probability of optical coherence tomography (OCT) for biometric recognition. The OCT is the foundation on an optical signal acquisition and processing method and has the micrometer-resolution. In this study, we used the porcine skin for verifying the abovementioned means. The porcine tissue was sound acknowledged for structural and immunohistochemical similarity with human skin, so it could be suitable for pre-clinical trial as investigational specimen. For this reason, it was tattooed by the tattoo machine with the tattoo-pigment. We detected the pattern of the tattooed skin by the OCT according to needle speed. The result was consistent with the histology images. This result showed that the OCT was effective to examine the tattooed skin section noninvasively. It might be available to identify morphological changes inside the skin.

Bandwidth Optimization through Dynamic Routing in ATM Networks: Genetic Algorithm and Tabu Search Approach

Asynchronous Transfer Mode (ATM) is widely used in telecommunications systems to send data, video and voice at a very high speed. In ATM network optimizing the bandwidth through dynamic routing is an important consideration. Previous research work shows that traditional optimization heuristics result in suboptimal solution. In this paper we have explored non-traditional optimization technique. We propose comparison of two such algorithms - Genetic Algorithm (GA) and Tabu search (TS), based on non-traditional Optimization approach, for solving the dynamic routing problem in ATM networks which in return will optimize the bandwidth. The optimized bandwidth could mean that some attractive business applications would become feasible such as high speed LAN interconnection, teleconferencing etc. We have also performed a comparative study of the selection mechanisms in GA and listed the best selection mechanism and a new initialization technique which improves the efficiency of the GA.

Numerical Method Based On Initial Value-Finite Differences for Free Vibration of Stepped Thickness Plates

The main objective of the present paper is to derive an easy numerical technique for the analysis of the free vibration through the stepped regions of plates. Based on the utilities of the step by step integration initial values IV and Finite differences FD methods, the present improved Initial Value Finite Differences (IVFD) technique is achieved. The first initial conditions are formulated in convenient forms for the step by step integrations while the upper and lower edge conditions are expressed in finite difference modes. Also compatibility conditions are created due to the sudden variation of plate thickness. The present method (IVFD) is applied to solve the fourth order partial differential equation of motion for stepped plate across two different panels under the sudden step compatibility in addition to different types of end conditions. The obtained results are examined and the validity of the present method is proved showing excellent efficiency and rapid convergence.

The Role of Cognitive Decision Effort in Electronic Commerce Recommendation System

The purpose of this paper is to explore the role of cognitive decision effort in recommendation system, combined with indicators "information quality" and "service quality" from IS success model to exam the awareness of the user for the "recommended system performance". A total of 411 internet user answered a questionnaire assessing their attention of use and satisfaction of recommendation system in internet book store. Quantitative result indicates following research results. First, information quality of recommended system has obvious influence in consumer shopping decision-making process, and the attitude to use the system. Second, in the process of consumer's shopping decision-making, the recommendation system has no significant influence for consumers to pay lower cognitive decision-making effort. Third, e-commerce platform provides recommendations and information is necessary, but the quality of information on user needs must be considered, or they will be other competitors offer homogeneous services replaced.

An Investigation into the Application of Artificial Neural Networks to the Prediction of Injuries in Sport

Artificial Neural Networks (ANNs) have been used successfully in many scientific, industrial and business domains as a method for extracting knowledge from vast amounts of data. However the use of ANN techniques in the sporting domain has been limited. In professional sport, data is stored on many aspects of teams, games, training and players. Sporting organisations have begun to realise that there is a wealth of untapped knowledge contained in the data and there is great interest in techniques to utilise this data. This study will use player data from the elite Australian Football League (AFL) competition to train and test ANNs with the aim to predict the onset of injuries. The results demonstrate that an accuracy of 82.9% was achieved by the ANNs’ predictions across all examples with 94.5% of all injuries correctly predicted. These initial findings suggest that ANNs may have the potential to assist sporting clubs in the prediction of injuries.

Large-Eddy Simulations of Subsonic Impinging Jets

We consider here the subsonic impinging jet representing the flow field of a vertical take-off aircraft or the initial stage of rocket launching. Implicit Large-Eddy Simulation (ILES) is used to calculate the time-dependent flow field and the radiate sound pressure associated with jet impinging. With proper boundary treatments and high-order numerical scheme, the near field sound pressure is successfully obtained. Results are presented for both a rectangular as well a circular jet.

A Real-time Computer Vision System for VehicleTracking and Collision Detection

Recent developments in automotive technology are focused on economy, comfort and safety. Vehicle tracking and collision detection systems are attracting attention of many investigators focused on safety of driving in the field of automotive mechatronics. In this paper, a vision-based vehicle detection system is presented. Developed system is intended to be used in collision detection and driver alert. The system uses RGB images captured by a camera in a car driven in the highway. Images captured by the moving camera are used to detect the moving vehicles in the image. A vehicle ahead of the camera is detected in daylight conditions. The proposed method detects moving vehicles by subtracting successive images. Plate height of the vehicle is determined by using a plate recognition algorithm. Distance of the moving object is calculated by using the plate height. After determination of the distance of the moving vehicle relative speed of the vehicle and Time-to-Collision are calculated by using distances measured in successive images. Results obtained in road tests are discussed in order to validate the use of the proposed method.

Enhancement of Biogas Production from Bakery Waste by Pseudomonas aeruginosa

Production of biogas from bakery waste was enhanced by additional bacterial cell. This study was divided into 2 steps. First step, grease waste from bakery industry-s grease trap was initially degraded by Pseudomonas aeruginosa. The concentration of byproduct, especially glycerol, was determined and found that glycerol concentration increased from 12.83% to 48.10%. Secondary step, 3 biodigesters were set up in 3 different substrates: non-degraded waste as substrate in first biodigester, degraded waste as substrate in secondary biodigester, and degraded waste mixed with swine manure in ratio 1:1 as substrate in third biodigester. The highest concentration of biogas was found in third biodigester that was 44.33% of methane and 63.71% of carbon dioxide. The lower concentration at 24.90% of methane and 18.98% of carbon dioxide was exhibited in secondary biodigester whereas the lowest was found in non-degraded waste biodigester. It was demonstrated that the biogas production was greatly increased with the initial grease waste degradation by Pseudomonas aeruginosa.

Using Data Mining for Learning and Clustering FCM

Fuzzy Cognitive Maps (FCMs) have successfully been applied in numerous domains to show relations between essential components. In some FCM, there are more nodes, which related to each other and more nodes means more complex in system behaviors and analysis. In this paper, a novel learning method used to construct FCMs based on historical data and by using data mining and DEMATEL method, a new method defined to reduce nodes number. This method cluster nodes in FCM based on their cause and effect behaviors.

Performance of Heat Pump Dryer for Kaffir Lime Leaves and Quality of Dried Products under Different Temperatures and Media

This research is to study the performance of heat pump dryer for drying of kaffir lime leaves under different media and to compare the color values and essential oil content of final products after drying. In the experiments, kaffir lime leaves were dried in the closed-loop system at drying temperatures of 40, 50 and 60 oC. The drying media used in this study were hot air, CO2 and N2 gases. The velocity of drying media in the drying chamber was 0.4 m/s with bypass ratio of 30%. The initial moisture content of kaffir lime leaves was approximately 180-190 % d.b. It was dried until down to a final moisture content of 10% d.b. From the experiments, the results showed that drying rate, the coefficient of performance (COP) and specific energy consumption (SEC) depended on drying temperature. While drying media did not affect on drying rate. The time for kaffir lime leaves drying at 40, 50 and 60 oC was 10, 5 and 3 hours, respectively. The performance of the heat pump system decreased with drying temperature in the range of 2.20-3.51. In the aspect of final product color, the greenness and overall color had a great change under drying temperature at 60 oC rather than drying at 40 and 50 oC. When compared among drying media, the greenness and overall color of product dried with hot air at 60 oC had a great change rather than dried with CO2 and N2.

The Theoretical Framework of the Necessity of Conducting Operational Auditing in Iran

Nowadays, efficiency, effectiveness and economy are regarded as the main objectives of managers and the secret of the continuity of an organization in competing economy. In such competing settings, it is essential that the management of an organization has not been neglected and been obliged to identify quickly the opportunities for improving the operation of organization and remove the shortcomings of their managed system in order to use the opportunities for development. Operational auditing is a useful tool for system adjustment and leading an organization toward its objectives. Operational auditing is indeed a viewpoint which identifies the causes of insufficiencies, weaknesses and deficiencies of system and plans to eliminate them. Operational auditing is useful in the effectiveness and optimization of executive managers- decisions and increasing the efficiency and economy of their performance in the future and prevents the waste and incorrect use of resources. Evidence shows that operational auditing is used at a limited level in Iran. This matter raises some questions like the following ones in the minds. Why do a limited number of corporations use operational auditing? Which factors can guarantee its full implementation? What obstacles are there in its implementation? The purpose of this article is to determine executive objectives, the operation domain of operational auditing, the components of operational auditing and the executive obstacles to operational auditing in Iran.

Closed Form Solution to problem of Calcium Diffusion in Cylindrical Shaped Neuron Cell

Calcium [Ca2+] dynamics is studied as a potential form of neuron excitability that can control many irregular processes like metabolism, secretion etc. Ca2+ ion enters presynaptic terminal and increases the synaptic strength and thus triggers the neurotransmitter release. The modeling and analysis of calcium dynamics in neuron cell becomes necessary for deeper understanding of the processes involved. A mathematical model has been developed for cylindrical shaped neuron cell by incorporating physiological parameters like buffer, diffusion coefficient, and association rate. Appropriate initial and boundary conditions have been framed. The closed form solution has been developed in terms of modified Bessel function. A computer program has been developed in MATLAB 7.11 for the whole approach.

Effect of Bentonite on the Properties of Liquid Insulating Oil

Bentonitic material from South Aswan, Egypt was evaluated in terms of mineral-ogy and chemical composition as bleaching clay in refining of transformer oil before and after acid activation and thermal treatment followed by acid leaching using HCl and H2SO4 for different contact times. Structural modification and refining power of bento-nite were investigated during modification by means of X-ray diffraction and infrared spectroscopy. The results revealed that the activated bentonite could be used for refining of transformer oil. The oil parameters such as; dielectric strength, viscosity and flash point had been improved. The dielectric breakdown strength of used oil increased from 29 kV for used oil treated with unactivated bentonite to 74 kV after treatment with activated bentonite. Kinematic Viscosity changed from 19 to 11 mm2 /s after treatment with activated bentonite. However, flash point achieved 149 ºC.

Using Knowledge Management and Critical Thinking to Understand Thai Perceptions and Decisions towards Work-Life Balance in a Multinational Software Development Firm

Work-life balance has been acknowledged and promoted for the sake of employee retention. It is essential for a manager to realize the human resources situation within a company to help employees work happily and perform at their best. This paper suggests knowledge management and critical thinking are useful to motivate employees to think about their work-life balance. A qualitative case study is presented, which aimed to discover the meaning of work-life balance-s meaning from the perspective of Thai knowledge workers and how it affects their decision-making towards work resignation. Results found three types of work-life balance dimensions; a work- life balance including a workplace and a private life setting, an organizational working life balance only, and a worklife balance only in a private life setting. These aspects all influenced the decision-making of the employees. Factors within a theme of an organizational work-life balance were involved with systematic administration, fair treatment, employee recognition, challenging assignments to gain working experience, assignment engagement, teamwork, relationship with superiors, and working environment, while factors concerning private life settings were about personal demands such as an increasing their salary or starting their own business.

Family Bonding and Self-Concept: An Indirect Effect Mediated by School Experiences among Students

School experiences, family bonding and self-concept had always been a crucial factor in influencing all aspects of a student-s development. The purpose of this study is to develop and to validate a priori model of self-concept among students. The study was tested empirically using Structural Equation Modeling (SEM) and Confirmatory Factor Analysis (CFA) to validate the structural model. To address these concerns, 1167 students were randomly selected and utilized the Cognitive Psycho-Social University of Malaya instrument (2009).Resulted demonstrated there is indirect effect from family bonding to self-concept through school experiences among secondary school students as a mediator. Besides school experiences, there is a direct effect from family bonding to self-concept and family bonding to school experiences among students.

Evolutionary Eigenspace Learning using CCIPCA and IPCA for Face Recognition

Traditional principal components analysis (PCA) techniques for face recognition are based on batch-mode training using a pre-available image set. Real world applications require that the training set be dynamic of evolving nature where within the framework of continuous learning, new training images are continuously added to the original set; this would trigger a costly continuous re-computation of the eigen space representation via repeating an entire batch-based training that includes the old and new images. Incremental PCA methods allow adding new images and updating the PCA representation. In this paper, two incremental PCA approaches, CCIPCA and IPCA, are examined and compared. Besides, different learning and testing strategies are proposed and applied to the two algorithms. The results suggest that batch PCA is inferior to both incremental approaches, and that all CCIPCAs are practically equivalent.

Using HMM-based Classifier Adapted to Background Noises with Improved Sounds Features for Audio Surveillance Application

Discrimination between different classes of environmental sounds is the goal of our work. The use of a sound recognition system can offer concrete potentialities for surveillance and security applications. The first paper contribution to this research field is represented by a thorough investigation of the applicability of state-of-the-art audio features in the domain of environmental sound recognition. Additionally, a set of novel features obtained by combining the basic parameters is introduced. The quality of the features investigated is evaluated by a HMM-based classifier to which a great interest was done. In fact, we propose to use a Multi-Style training system based on HMMs: one recognizer is trained on a database including different levels of background noises and is used as a universal recognizer for every environment. In order to enhance the system robustness by reducing the environmental variability, we explore different adaptation algorithms including Maximum Likelihood Linear Regression (MLLR), Maximum A Posteriori (MAP) and the MAP/MLLR algorithm that combines MAP and MLLR. Experimental evaluation shows that a rather good recognition rate can be reached, even under important noise degradation conditions when the system is fed by the convenient set of features.

Study of Coupled Lateral-Torsional Free Vibrations of Laminated Composite Beam: Analytical Approach

In this paper, an analytical approach is used to study the coupled lateral-torsional vibrations of laminated composite beam. It is known that in such structures due to the fibers orientation in various layers, any lateral displacement will produce a twisting moment. This phenomenon is modeled by the bending-twisting material coupling rigidity and its main feature is the coupling of lateral and torsional vibrations. In addition to the material coupling, the effects of shear deformation and rotary inertia are taken into account in the definition of the potential and kinetic energies. Then, the governing differential equations are derived using the Hamilton-s principle and the mathematical model matches the Timoshenko beam model when neglecting the effect of bending-twisting rigidity. The equations of motion which form a system of three coupled PDEs are solved analytically to study the free vibrations of the beam in lateral and rotational modes due to the bending, as well as the torsional mode caused by twisting. The analytic solution is carried out in three steps: 1) assuming synchronous motion for the kinematic variables which are the lateral, rotational and torsional displacements, 2) solving the ensuing eigenvalue problem which contains three coupled second order ODEs and 3) imposing different boundary conditions related to combinations of simply, clamped and free end conditions. The resulting natural frequencies and mode shapes are compared with similar results in the literature and good agreement is achieved.

Developing Damage Assessment Model for Bridge Surroundings: A Study of Disaster by Typhoon Morakot in Taiwan

This paper presents an integrated model that automatically measures the change of rivers, damage area of bridge surroundings, and change of vegetation. The proposed model is on the basis of a neurofuzzy mechanism enhanced by SOM optimization algorithm, and also includes three functions to deal with river imagery. High resolution imagery from FORMOSAT-2 satellite taken before and after the invasion period is adopted. By randomly selecting a bridge out of 129 destroyed bridges, the recognition results show that the average width has increased 66%. The ruined segment of the bridge is located exactly at the most scour region. The vegetation coverage has also reduced to nearly 90% of the original. The results yielded from the proposed model demonstrate a pinpoint accuracy rate at 99.94%. This study brings up a successful tool not only for large-scale damage assessment but for precise measurement to disasters.

On the Fast Convergence of DD-LMS DFE Using a Good Strategy Initialization

In wireless communication system, a Decision Feedback Equalizer (DFE) to cancel the intersymbol interference (ISI) is required. In this paper, an exact convergence analysis of the (DFE) adapted by the Least Mean Square (LMS) algorithm during the training phase is derived by taking into account the finite alphabet context of data transmission. This allows us to determine the shortest training sequence that allows to reach a given Mean Square Error (MSE). With the intention of avoiding the problem of ill-convergence, the paper proposes an initialization strategy for the blind decision directed (DD) algorithm. This then yields a semi-blind DFE with high speed and good convergence.