Nonlinear Solitary Structures of Electron Plasma Waves in a Finite Temperature Quantum Plasma

Nonlinear solitary structures of electron plasma waves have been investigated by using nonlinear quantum fluid equations for electrons with an arbitrary temperature. It is shown that the electron degeneracy parameter has significant effects on the linear and nonlinear properties of electron plasma waves. Depending on its value both compressive and rarefactive solitons can be excited in the model plasma under consideration.

Quality Monitoring and Dynamic Pricing in Cold Chain Management

This paper presents a cold chain monitoring system which focuses on assessment of quality and dynamic pricing information about food in cold chain. Cold chain is composed of many actors and stages; however it can be seen as a single entity since a breakdown in temperature control at any stage can impact the final quality of the product. In a cold chain, the shelf life, quality, and safety of perishable food throughout the supply chain is greatly impacted by environmental factors especially temperature. In this paper, a prototype application is implemented to retrieve timetemperature history, the current quality and the dynamic price setting according to changing quality impacted by temperature fluctuations in real-time.

Evaluation of Radiation Synthesized β-Glucan Hydrogel Wound Dressing using Rat Models

In this study, hydrogels consisted of polyvinyl alcohol, propylene glycol and β-glucan were developed by radiation technique for wound dressing. The prepared hydrogels were characterized by examining of physical properties such as gel fraction and absorption ratio. The gel fraction and absorption ratio were dependent on the crosslinking density. On observing the wound healing of rat skin, the resulting hydrogels accelerated the wound healing comparing to cotton gauze. Therefore, the PVA/propylene glycol/β-glucan blended hydrogels can greatly accelerate the healing without causing irritation.

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.

Communication and Human Resource Management and its Compliance with Culture

According to the conception of personnel management, human resource management requires efficient use of human resources. This is ensured by various activities directed towards the area of management. Among these activities there are for example the recruitment of employees, development, strengthening of relations, mutual inspiring, implementation of correct working processes and systems used by individuals or groups.

Restartings: A Technique to Improve Classic Genetic Algorithms Performance

In this contribution, a way to enhance the performance of the classic Genetic Algorithm is proposed. The idea of restarting a Genetic Algorithm is applied in order to obtain better knowledge of the solution space of the problem. A new operator of 'insertion' is introduced so as to exploit (utilize) the information that has already been collected before the restarting procedure. Finally, numerical experiments comparing the performance of the classic Genetic Algorithm and the Genetic Algorithm with restartings, for some well known test functions, are given.

Performance Characteristics of a Closed Circuit Cooling Tower with Multi Path

The experimental thermal performance of two heat exchangers in closed-wet cooling tower (CWCT) was investigated in this study. The test sections are heat exchangers which have multi path that is used as the entrance of cooling water and are consisting of bare-type copper tubes between 15.88mm and 19.05mm. The process fluids are the cooling water that flows from top part of heat exchanger to bottom side in the inner side of tube, and spray water that flows gravitational direction in the outer side of it. Air contacts its outer side of that as it counterflows. Heat and mass transfer coefficients and cooling capacity were calculated with variations of process fluids, multi path and different diameter tubes to figure out the performance of characteristics of CWCT. The main results were summarized as follows: The results show this experiment is reliable with values of heat and mass transfer coefficients comparing to values of correlations. Heat and mass transfer coefficients and cooling capacity of two paths are higher than these with one path using 15.88 and 19.05mm tubes. Cooling capacity per unit volume with 15.88mm tube using one and two paths are higher than 19.05mm tube due to increase of surface area per unit volume.

Ecological Risk Assessment of Polycyclic Aromatic Hydrocarbons in the Northwest of the Persian Gulf

This study investigated the presence of polycyclic aromatic hydrocarbons (PAHs) in the sediments of the Musa Bay (around the PETZONE coastal area) from Feb 2010 to Jun 2010. Concentrations of PAHs recorded in the Musa Bay sediments ranged from 537.89 to 26,659.06 ng/g dry weight with a mean value of 3990.74 ng/g. the highest concentration of PAHs was observed at station 4, which is located near the aromatic outlet of Imam Khomeini petrochemical company (station 4: BI-PC Aromatic effluent outlet) in which its concentration level was more than the NOAA sediment quality guideline value (ERL= 4022 ng/g dry weight). Owing to the concentration of PAHs in the study area, its concentration level was still meet the NOAA sediment quality guideline value (ERL: 4022 ng/g dry weight); however, according to the PELq factor, slightly adverse biological effects are associated with the exposure to PAHs levels in the study area (0.1< PELq= 0.24 > 0.5).

Linear Cryptanalysis for a Chaos-Based Stream Cipher

Linear cryptanalysis methods are rarely used to improve the security of chaotic stream ciphers. In this paper, we apply linear cryptanalysis to a chaotic stream cipher which was designed by strictly using the basic design criterion of cryptosystem – confusion and diffusion. We show that this well-designed chaos-based stream cipher is still insecure against distinguishing attack. This distinguishing attack promotes the further improvement of the cipher.

The Citizen Participation in Preventing Illegal Drugs Program in Bangkok, Thailand

The purposes of this research were to study the citizen participation in preventing illegal drugs in one of a poor and small community of Bangkok, Thailand and to compare the level of participation and concern of illegal drugs problem by using demographic variables. This paper drew upon data collected from a local citizens survey conducted in Bangkok, Thailand during summer of 2012. A total of 200 respondents were elicited as data input for, and one way ANOVA test. The findings revealed that the overall citizen participation was in the level of medium. The mean score showed that benefit from the program was ranked as the highest and the decision to participate was ranked as second while the follow-up of the program was ranked as the lowest. In terms of the difference in demographic such as gender, age, level of education, income, and year of residency, the hypothesis testing’s result disclosed that there were no difference in their level of participation. However, difference in occupation showed a difference in their level of participation and concern which was significant at the 0.05 confidence level.

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.

Experimental Investigation on the Effect of CO2 and WAG Injection on Permeability Reduction Induced by Asphaltene Precipitation in Light Oil

Permeability reduction induced by asphaltene precipitation during gas injection is one of the serious problems in the oil industry. This problem can lead to formation damage and decrease the oil production rate. In this work, Malaysian light oil sample has been used to investigate the effect CO2 injection and Water Alternating Gas (WAG) injection on permeability reduction. In this work, dynamic core flooding experiments were conducted to study the effect of CO2 and WAG injection on the amount of asphaltene precipitated. Core properties after displacement were inspected for any permeability reduction to study the effect of asphaltene precipitation on rock properties. The results showed that WAG injection gave less asphaltene precipitation and formation damage compared to CO2 injection. The study suggested that WAG injection can be one of the important factors of managing asphaltene precipitation.

Certain Data Dimension Reduction Techniques for application with ANN based MCS for Study of High Energy Shower

Cosmic showers, from their places of origin in space, after entering earth generate secondary particles called Extensive Air Shower (EAS). Detection and analysis of EAS and similar High Energy Particle Showers involve a plethora of experimental setups with certain constraints for which soft-computational tools like Artificial Neural Network (ANN)s can be adopted. The optimality of ANN classifiers can be enhanced further by the use of Multiple Classifier System (MCS) and certain data - dimension reduction techniques. This work describes the performance of certain data dimension reduction techniques like Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Self Organizing Map (SOM) approximators for application with an MCS formed using Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN) and Probabilistic Neural Network (PNN). The data inputs are obtained from an array of detectors placed in a circular arrangement resembling a practical detector grid which have a higher dimension and greater correlation among themselves. The PCA, ICA and SOM blocks reduce the correlation and generate a form suitable for real time practical applications for prediction of primary energy and location of EAS from density values captured using detectors in a circular grid.

Concept Indexing using Ontology and Supervised Machine Learning

Nowadays, ontologies are the only widely accepted paradigm for the management of sharable and reusable knowledge in a way that allows its automatic interpretation. They are collaboratively created across the Web and used to index, search and annotate documents. The vast majority of the ontology based approaches, however, focus on indexing texts at document level. Recently, with the advances in ontological engineering, it became clear that information indexing can largely benefit from the use of general purpose ontologies which aid the indexing of documents at word level. This paper presents a concept indexing algorithm, which adds ontology information to words and phrases and allows full text to be searched, browsed and analyzed at different levels of abstraction. This algorithm uses a general purpose ontology, OntoRo, and an ontologically tagged corpus, OntoCorp, both developed for the purpose of this research. OntoRo and OntoCorp are used in a two-stage supervised machine learning process aimed at generating ontology tagging rules. The first experimental tests show a tagging accuracy of 78.91% which is encouraging in terms of the further improvement of the algorithm.

A New Construction of 16-QAM Codewords with Low Peak Power

We present a novel construction of 16-QAM codewords of length n = 2k . The number of constructed codewords is 162×[4k-1×k-k+1] . When these constructed codewords are utilized as a code in OFDM systems, their peak-to-mean envelope power ratios (PMEPR) are bounded above by 3.6 . The principle of our scheme is illustrated with a four subcarrier example.

Material Defects Identification in Metal Ceramic Fixed Partial Dentures by En-Face Polarization Sensitive Optical Coherence Tomography

The fixed partial dentures are mainly used in the frontal part of the dental arch because of their great esthetics. There are several factors that are associated with the stress state created in ceramic restorations, including: thickness of ceramic layers, mechanical properties of the materials, elastic modulus of the supporting substrate material, direction, magnitude and frequency of applied load, size and location of occlusal contact areas, residual stresses induced by processing or pores, restoration-cement interfacial defects and environmental defects. The purpose of this study is to evaluate the capability of Polarization Sensitive Optical Coherence Tomography (PSOCT) in detection and analysis of possible material defects in metal-ceramic and integral ceramic fixed partial dentures. As a conclusion, it is important to have a non invasive method to investigate fixed partial prostheses before their insertion in the oral cavity in order to satisfy the high stress requirements and the esthetic function.

A Petri Net Representation of a Web-Service- Based Emergency Management System in Railway Station

Railway Stations are prone to emergency due to various reasons and proper monitor of railway stations are of immense importance from various angles. A Petri-net representation of a web-service-based Emergency management system has been proposed in this paper which will help in monitoring situation of train, track, signal etc. and in case of any emergency, necessary resources can be dispatched.

Elections, Checks and Balances, and Government Expenditures: Empirical Evidence for Japan, South Korea, and Taiwan

Previous studies on political budget cycles (PBCs) implicitly assume the executive has full discretion power over fiscal policy, neglecting the role of checks and balances of the legislature. This paper goes beyond traditional PBCs models and sheds light on the case study of Japan, South Korea, and Taiwan over the 1988-2007 periods. Based on the results, we find no evidence of electoral impacts on the public expenditures in South Korean and Taiwan's congressional elections. We also noted that PBCs are found on Taiwan-s government expenditures during our sample periods. Furthermore, the results also show that Japan-s legislature has a significant checks and balances on government-s expenditures. However, empirical results show that the legislature veto player in Taiwan neither has effect on the reduction of public expenditures, nor has the moderating effect over Taiwan-s political budget cycles, albeit that they are statistically insignificant.We suggest that the existence of PBCs in Taiwan is due to a weaker systemof checks and balances. Our conjecture is that Taiwan either has no legislative veto player or has observed low compliance to the law during the time period examined in our study.

Comparison between Minimum Direct and Indirect Jerks of Linear Dynamic Systems

Both the minimum energy consumption and smoothness, which is quantified as a function of jerk, are generally needed in many dynamic systems such as the automobile and the pick-and-place robot manipulator that handles fragile equipments. Nevertheless, many researchers come up with either solely concerning on the minimum energy consumption or minimum jerk trajectory. This research paper proposes a simple yet very interesting relationship between the minimum direct and indirect jerks approaches in designing the time-dependent system yielding an alternative optimal solution. Extremal solutions for the cost functions of direct and indirect jerks are found using the dynamic optimization methods together with the numerical approximation. This is to allow us to simulate and compare visually and statistically the time history of control inputs employed by minimum direct and indirect jerk designs. By considering minimum indirect jerk problem, the numerical solution becomes much easier and yields to the similar results as minimum direct jerk problem.

A Fast Neural Algorithm for Serial Code Detection in a Stream of Sequential Data

In recent years, fast neural networks for object/face detection have been introduced based on cross correlation in the frequency domain between the input matrix and the hidden weights of neural networks. In our previous papers [3,4], fast neural networks for certain code detection was introduced. It was proved in [10] that for fast neural networks to give the same correct results as conventional neural networks, both the weights of neural networks and the input matrix must be symmetric. This condition made those fast neural networks slower than conventional neural networks. Another symmetric form for the input matrix was introduced in [1-9] to speed up the operation of these fast neural networks. Here, corrections for the cross correlation equations (given in [13,15,16]) to compensate for the symmetry condition are presented. After these corrections, it is proved mathematically that the number of computation steps required for fast neural networks is less than that needed by classical neural networks. Furthermore, there is no need for converting the input data into symmetric form. Moreover, such new idea is applied to increase the speed of neural networks in case of processing complex values. Simulation results after these corrections using MATLAB confirm the theoretical computations.