Development of a Thrust Measurement System

KSLV-I(Korea Space Launch Vehicle-I) is designed as a launch vehicle to enter a 100 kg-class satellite to the LEO(Low Earth Orbit). Attitude angles of the upper-stage, including roll, pitch and yaw are controlled by the cold gas thruster system using nitrogen gas. The cold gas thruster is an actuator in the RCS(Reaction Control System). To design an attitude controller for the upper-stage, thrust measurement in vacuum condition is required. In this paper, the new thrust measurement system and calibration mechanism are developed and measurement errors and signal processing method are presented.

Prediction of the Characteristics of Transformer Oil under Different Operation Conditions

Power systems and transformer are intrinsic apparatus, therefore its reliability and safe operation is important to determine their operation conditions, and the industry uses quality control tests in the insulation design of oil filled transformers. Hence the service period effect on AC dielectric strength is significant. The effect of aging on transformer oil physical, chemical and electrical properties was studied using the international testing methods for the evaluation of transformer oil quality. The study was carried out on six transformers operate in the field and for monitoring periods over twenty years. The properties which are strongly time dependent were specified and those which have a great impact on the transformer oil acidity, breakdown voltage and dissolved gas analysis were defined. Several tests on the transformers oil were studied to know the time of purifying or changing it, moreover prediction of the characteristics of it under different operation conditions.

Real Time Compensation of Machining Errors for Machine Tools NC based on Systematic Dispersion

Manufacturing tolerancing is intended to determine the intermediate geometrical and dimensional states of the part during its manufacturing process. These manufacturing dimensions also serve to satisfy not only the functional requirements given in the definition drawing, but also the manufacturing constraints, for example geometrical defects of the machine, vibration and the wear of the cutting tool. In this paper, an experimental study on the influence of the wear of the cutting tool (systematic dispersions) is explored. This study was carried out on three stages .The first stage allows machining without elimination of dispersions (random, systematic) so the tolerances of manufacture according to total dispersions. In the second stage, the results of the first stage are filtered in such way to obtain the tolerances according to random dispersions. Finally, from the two previous stages, the systematic dispersions are generated. The objective of this study is to model by the least squares method the error of manufacture based on systematic dispersion. Finally, an approach of optimization of the manufacturing tolerances was developed for machining on a CNC machine tool

Collaborative Business Strategy of PTT Energy Trading Co. Ltd. for LNG form of Coal Bed Methane in B2B Transaction to Japanese Shareholder, Especially to Electricity and Power Supply Companies

A research study was conducted with an objective to propose a collaborative business strategy of a oil and gas trading company, representing PPT Energy Trading Co., Ltd., with its shareholder, especially electricity and power supply companies for LNG Form of Coal Bed Methane in B2B Transaction. Collaborative business strategy is a strategy to collaborate with other organizations due to have future benefits in both parties, or achieve the business objective through the collaboration of business, its strategy and partners. A structured interview was established to collect the required primary data from the company. Not only interview, but also company’s business plan and annual report were collected and analyzed for the company’s current condition. As the result, this research shows a recommendation to propose a new collaborative strategy with limiting its target market, diversifying product, conducting new business model, and considering other stakeholders.

Clustering Protein Sequences with Tailored General Regression Model Technique

Cluster analysis divides data into groups that are meaningful, useful, or both. Analysis of biological data is creating a new generation of epidemiologic, prognostic, diagnostic and treatment modalities. Clustering of protein sequences is one of the current research topics in the field of computer science. Linear relation is valuable in rule discovery for a given data, such as if value X goes up 1, value Y will go down 3", etc. The classical linear regression models the linear relation of two sequences perfectly. However, if we need to cluster a large repository of protein sequences into groups where sequences have strong linear relationship with each other, it is prohibitively expensive to compare sequences one by one. In this paper, we propose a new technique named General Regression Model Technique Clustering Algorithm (GRMTCA) to benignly handle the problem of linear sequences clustering. GRMT gives a measure, GR*, to tell the degree of linearity of multiple sequences without having to compare each pair of them.

Earthquake Analysis of Reinforce Concrete Framed Structures with Added Viscous Dampers

This paper describes the development of a numerical finite element algorithm used for the analysis of reinforced concrete structure equipped with shakes energy absorbing device subjected to earthquake excitation. For this purpose a finite element program code for analysis of reinforced concrete frame buildings is developed. The performance of developed program code is evaluated by analyzing of a reinforced concrete frame buildings model. The results are show that using damper device as seismic energy dissipation system effectively can reduce the structural response of framed structure during earthquake occurrence.

Robot Task-Level Programming Language and Simulation

This paper presents the development of a software application for Off-line robot task programming and simulation. Such application is designed to assist in robot task planning and to direct manipulator motion on sensor based programmed motion. The concept of the designed programming application is to use the power of the knowledge base for task accumulation. In support of the programming means, an interactive graphical simulation for manipulator kinematics was also developed and integrated into the application as the complimentary factor to the robot programming media. The simulation provides the designer with useful, inexpensive, off-line tools for retain and testing robotics work cells and automated assembly lines for various industrial applications.

Transformation Building of Micro- Entrepreneurs: A Conceptual Model

The majority of micro-entrepreneurs in Malaysia operate very small-scaled business activities such as food stalls, burger stalls, night market hawkers, grocery stores, constructions, rubber and oil palm small holders, and other agro-based services and activities. Why are they venturing into entrepreneurship - is it for survival, out of interest or due to encouragement and assistance from the local government? And why is it that some micro-entrepreneurs are lagging behind in entrepreneurship, and what do they need to rectify this situation so that they are able to progress further? Furthermore, what are the skills that the micro entrepreneurs should developed to transform them into successful micro-enterprises and become small and medium-sized enterprises (SME)? This paper proposes a 7-Step approach that can serve as a basis for identification of critical entrepreneurial success factors that enable policy makers, practitioners, consultants, training managers and other agencies in developing tools to assist micro business owners. This paper also highlights the experience of one of the successful companies in Malaysia that has transformed from micro-enterprise to become a large organization in less than 10 years.

The Use of Complex Contourlet Transform on Fusion Scheme

Image fusion aims to enhance the perception of a scene by combining important information captured by different sensors. Dual-Tree Complex Wavelet (DT-CWT) has been thouroughly investigated for image fusion, since it takes advantages of approximate shift invariance and direction selectivity. But it can only handle limited direction information. To allow a more flexible directional expansion for images, we propose a novel fusion scheme, referred to as complex contourlet transform (CCT). It successfully incorporates directional filter banks (DFB) into DT-CWT. As a result it efficiently deal with images containing contours and textures, whereas it retains the property of shift invariance. Experimental results demonstrated that the method features high quality fusion performance and can facilitate many image processing applications.

Performance of Dual MRC Receiver for M-ary Modulations over Correlated Nakagami-m Fading Channels with Non-identical and Arbitrary Fading Parameter

Performance of a dual maximal ratio combining receiver has been analyzed for M-ary coherent and non-coherent modulations over correlated Nakagami-m fading channels with nonidentical and arbitrary fading parameter. The classical probability density function (PDF) based approach is used for analysis. Expressions for outage probability and average symbol error performance for M-ary coherent and non-coherent modulations have been obtained. The obtained results are verified against the special case published results and found to be matching. The effect of the unequal fading parameters, branch correlation and unequal input average SNR on the receiver performance has been studied.

Expansion of A Finit Size Partially Ionized Laser-Plasma

The expansion mechanism of a partially ionized plasma produced by laser interaction with solid target (copper) is studied. For this purpose we use a hydrodynamical model which includes a source term combined with Saha's equation. The obtained self-similar solution in the limit of quasi-neutrality shows that the expansion, at the earlier stage, is driven by the combination of thermal pressure and electrostatic potential. They are of the same magnitude. The initial ionized fraction and the temperature are the leading parameters of the expanding profiles,

ISCS (Information Security Check Service) for the Safety and Reliability of Communications

Recent widespread use of information and communication technology has greatly changed information security risks that businesses and institutions encounter. Along with this situation, in order to ensure security and have confidence in electronic trading, it has become important for organizations to take competent information security measures to provide international confidence that sensitive information is secure. Against this backdrop, the approach to information security checking has come to an important issue, which is believed to be common to all countries. The purpose of this paper is to introduce the new system of information security checking program in Korea and to propose synthetic information security countermeasures under domestic circumstances in order to protect physical equipment, security management and technology, and the operation of security check for securing services on ISP(Internet Service Provider), IDC(Internet Data Center), and e-commerce(shopping malls, etc.)

Fault Zone Detection on Advanced Series Compensated Transmission Line using Discrete Wavelet Transform and SVM

In this paper a novel method for finding the fault zone on a Thyristor Controlled Series Capacitor (TCSC) incorporated transmission line is presented. The method makes use of the Support Vector Machine (SVM), used in the classification mode to distinguish between the zones, before or after the TCSC. The use of Discrete Wavelet Transform is made to prepare the features which would be given as the input to the SVM. This method was tested on a 400 kV, 50 Hz, 300 Km transmission line and the results were highly accurate.

Behavior Model Mapping and Transformation using Model-Driven Architecture

Model mapping and transformation are important processes in high level system abstractions, and form the cornerstone of model-driven architecture (MDA) techniques. Considerable research in this field has devoted attention to static system abstraction, despite the fact that most systems are dynamic with high frequency changes in behavior. In this paper we provide an overview of work that has been done with regard to behavior model mapping and transformation, based on: (1) the completeness of the platform independent model (PIM); (2) semantics of behavioral models; (3) languages supporting behavior model transformation processes; and (4) an evaluation of model composition to effect the best approach to describing large systems with high complexity.

Indoor and Outdoor Concentration of Particulate Matter at Domestic Homes

Particulate matter (PM) in ambient air is responsible for adverse health effects in adults and children. Relatively little is known about the concentrations, sources and health effects of PM in indoor air. A monitoring study was conducted in Ankara by three campaigns in order to measure PM levels in indoor and outdoor environments to identify and quantify associations between sources and concentrations. Approximately 82 homes (1st campaign for 42, 2nd campaign for 12, and 3rd campaign for 28), three rooms (living room, baby-s room and living room used as a baby-s room) and outdoor ambient at each home were sampled with Grimm Environmental Dust Monitoring (EDM) 107, during different seasonal periods of 2011 and 2012. In this study, the relationship between indoor and outdoor PM levels for particulate matter less than 10 micrometer (.m) (PM10), particulate matter less than 2.5.m (PM2.5) and particulate matter less than 1.0.m (PM1) were investigated. The mean concentration of PM10, PM2.5, and PM1.0 at living room used as baby-s room is higher than living and baby-s room (or bedroom) for three sampling campaigns. It is concluded that the household activities and environmental conditions are very important for PM concentrations in the indoor environments during the sampling periods. The amount of smokers, being near a main street and/or construction activities increased the PM concentration. This study is based on the assessment the relationship between indoor and outdoor PM levels and the household activities and environmental conditions

Artificial Intelligence Techniques applied to Biomedical Patterns

Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.

Quantification of Heart Rate Variability: A Measure based on Unique Heart Rates

It is established that the instantaneous heart rate (HR) of healthy humans keeps on changing. Analysis of heart rate variability (HRV) has become a popular non invasive tool for assessing the activities of autonomic nervous system. Depressed HRV has been found in several disorders, like diabetes mellitus (DM) and coronary artery disease, characterised by autonomic nervous dysfunction. A new technique, which searches for pattern repeatability in a time series, is proposed specifically for the analysis of heart rate data. These set of indices, which are termed as pattern repeatability measure and pattern repeatability ratio are compared with approximate entropy and sample entropy. In our analysis, based on the method developed, it is observed that heart rate variability is significantly different for DM patients, particularly for patients with diabetic foot ulcer.

Multiple Object Tracking using Particle Swarm Optimization

This paper presents a particle swarm optimization (PSO) based approach for multiple object tracking based on histogram matching. To start with, gray-level histograms are calculated to establish a feature model for each of the target object. The difference between the gray-level histogram corresponding to each particle in the search space and the target object is used as the fitness value. Multiple swarms are created depending on the number of the target objects under tracking. Because of the efficiency and simplicity of the PSO algorithm for global optimization, target objects can be tracked as iterations continue. Experimental results confirm that the proposed PSO algorithm can rapidly converge, allowing real-time tracking of each target object. When the objects being tracked move outside the tracking range, global search capability of the PSO resumes to re-trace the target objects.

An Improved Resource Discovery Approach Using P2P Model for Condor: A Grid Middleware

Resource Discovery in Grids is critical for efficient resource allocation and management. Heterogeneous nature and dynamic availability of resources make resource discovery a challenging task. As numbers of nodes are increasing from tens to thousands, scalability is essentially desired. Peer-to-Peer (P2P) techniques, on the other hand, provide effective implementation of scalable services and applications. In this paper we propose a model for resource discovery in Condor Middleware by using the four axis framework defined in P2P approach. The proposed model enhances Condor to incorporate functionality of a P2P system, thus aim to make Condor more scalable, flexible, reliable and robust.

A Semi-Classical Signal Analysis Method for the Analysis of Turbomachinery Flow Unsteadiness

This paper presents the use of a semi-classical signal analysis method that has been developed recently for the analysis of turbomachinery flow unsteadiness. We will focus on the correlation between theSemi-Classical Signal Analysis parameters and some physical parameters in relation with turbomachinery features. To demonstrate the potential of the proposed approach, a static pressure signal issued from a rotor/stator interaction of a centrifugal pump is studied. Several configurations of the pump are compared.