Determination of Severe Loading Condition at Critical System Cascading Collapse Considering the Effect of Protection System Hidden Failure

Hidden failure in a protection system has been recognized as one of the main reasons which may cause to a power system instability leading to a system cascading collapse. This paper presents a computationally systematic approach used to obtain the estimated average probability of a system cascading collapse by considering the effect of probability hidden failure in a protection system. The estimated average probability of a system cascading collapse is then used to determine the severe loading condition contributing to the higher risk of critical system cascading collapse. This information is essential to the system utility since it will assist the operator to determine the highest point of increased system loading condition prior to the event of critical system cascading collapse.

An Agent-Based Approach to Vehicle Routing Problem

The paper proposes and validates a new method of solving instances of the vehicle routing problem (VRP). The approach is based on a multiple agent system paradigm. The paper contains the VRP formulation, an overview of the multiple agent environment used and a description of the proposed implementation. The approach is validated experimentally. The experiment plan and the discussion of experiment results follow.

English Language Learning Strategies Used by University Students: A Case Study of English and Business English Major at Suan Sunandha Rajabhat in Bangkok

The purposes of this research are 1) to study English language learning strategies used by the fourth-year students majoring in English and Business English, 2) to study the English language learning strategies which have an affect on English learning achievement, and 3) to compare the English language learning strategies used by the students majoring in English and Business English. The population and sampling comprise of 139 university students of the Suan Sunandha Rajabhat University. Research instruments are language learning strategies questionnaire which was constructed by the researcher and improved on by three experts and the transcripts that show the results of English learning achievement. The questionnaire includes 1) Language Practice Strategy 2)Memory Strategy 3) Communication Strategy 4)Making an Intelligent Guess or Compensation Strategy 5) Self-discipline in Learning Management Strategy 6) Affective Strategy 7)Self-Monitoring Strategy 8) Self-studySkill Strategy. Statistics used in the study are mean, standard deviation, T-test and One Way ANOVA, Pearson product moment correlation coefficient and Regression Analysis. The results of the findings reveal that the English language learning strategies most frequently used by the students are affective strategy, making an intelligent guess or compensation strategy, self-studyskill strategy and self-monitoring strategy respectively. The aspect of making an intelligent guess or compensation strategy had the most significant affect on English learning achievement. It is found that the English language learning strategies mostly used by the Business English major students and moderately used by the English major students. Their language practice strategies uses were significantly different at the 0.05 level and their communication strategies uses were significantly different at the 0.01 level. In addition, it is found that the poor students and the fair ones most frequently used affective strategy while the good ones most frequently used making an intelligent guess or compensation strategy. KeywordsEnglish language, language learning strategies, English learning achievement, and students majoring in English, Business English. Pranee Pathomchaiwat is an Assistant Professor in Business English Program, Suan Sunandha Rajabhat University, Bangkok, Thailand (e-mail: [email protected]).

An Images Monitoring System based on Multi-Format Streaming Grid Architecture

This paper proposes a novel multi-format stream grid architecture for real-time image monitoring system. The system, based on a three-tier architecture, includes stream receiving unit, stream processor unit, and presentation unit. It is a distributed computing and a loose coupling architecture. The benefit is the amount of required servers can be adjusted depending on the loading of the image monitoring system. The stream receive unit supports multi capture source devices and multi-format stream compress encoder. Stream processor unit includes three modules; they are stream clipping module, image processing module and image management module. Presentation unit can display image data on several different platforms. We verified the proposed grid architecture with an actual test of image monitoring. We used a fast image matching method with the adjustable parameters for different monitoring situations. Background subtraction method is also implemented in the system. Experimental results showed that the proposed architecture is robust, adaptive, and powerful in the image monitoring system.

Spray Combustion Dynamics under Thermoacoustic Oscillations

Thermoacoustic instabilities in combustors have remained a topic of investigation for over a few decades due to the challenges it posses to the operation of low emission gas turbines. For combustors burning liquid fuel, understanding the cause-andeffect relationship between spray combustion dynamics and thermoacoustic oscillations is imperative for the successful development of any control methodology for its mitigation. The paper presents some very unique operating characteristics of a kerosene-fueled diffusion type combustor undergoing limit-cycle oscillations. Combustor stability limits were mapped using three different-sized injectors. The results show that combustor instability depends on the characteristics of the fuel spray. A simple analytic analysis is also reported in support of a plausible explanation for the unique combustor behavior. The study indicates that high amplitude acoustic pressure in the combustor may cause secondary breakdown of fuel droplets resulting in premixed pre-vaporized type burning of the diffusion type combustor.

Effect of Vibration Intervention on Leg-press Exercise

Many studies have emphasized the importance of resistive exercise to maintain a healthy human body, particular in prevention of weakening of physical strength. Recently, some studies advocated that an application of vibration as a supplementary means in a regular training was effective in encouraging physical strength. Aim of the current study was, therefore, to identify if an application of vibration in a resistive exercise was effective in encouraging physical strength as that in a regular training. A 3-dimensional virtual lower extremity model for a healthy male and virtual leg-press model were generated and synchronized. Dynamic leg-press exercises on a slide machine with/without extra load and on a footboard with vibration as well as on a slide machine with extra load were analyzed. The results of the current indicated that the application of the vibration on the dynamic leg-press exercise might be not greatly effective in encouraging physical strength, compared with the dynamic leg press exercise with extra load. It was, however, thought that the application of the vibration might be helpful to elderly individuals because the reduced maximum muscle strength appeared by the effect of the vibration may avoid a muscular spasm, which can be driven from a high muscle strength sometimes produced during the leg-press exercise with extra load.

Modeling of Crude Oil Blending via Discrete-Time Neural Networks

Crude oil blending is an important unit operation in petroleum refining industry. A good model for the blending system is beneficial for supervision operation, prediction of the export petroleum quality and realizing model-based optimal control. Since the blending cannot follow the ideal mixing rule in practice, we propose a static neural network to approximate the blending properties. By the dead-zone approach, we propose a new robust learning algorithm and give theoretical analysis. Real data of crude oil blending is applied to illustrate the neuro modeling approach.

Effect of Acid Adaptation on the Survival of Three Vibrio parahaemolyticus Strains under Simulated Gastric Condition and their Protein Expression Profiles

In this study, three strains of Vibrio parahaemolyticus (690, BCRC 13023 and BCRC 13025) were subjected to acid adaptation at pH 5.5 for 90 min. The survival of acid-adapted and non-adapted V. parahaemolyticus strains under simulated gastric condition and their protein expression profiles were investigated. Results showed that acid adaptation increased the survival of the test V. parahaemolyticus strains after exposure to simulated gastric juice (pH 3). Additionally, acid adaptation also affected the protein expression in these V. parahaemolyticus strains. Nine proteins, identified as atpA, atpB, DnaK, GroEL, OmpU, enolase, fructose-bisphosphate aldolase, phosphoglycerate kinase and triosephosphate isomerase, were induced by acid adaptation in two or three of the test strains. These acid-adaptive proteins may play important regulatory roles in the acid tolerance response (ATR) of V. parahaemolyticus.

Influence of Supplemental Glutamine on Nutrient Digestibility and Utilization, Small Intestinal Morphology and Gastrointestinal Tract and Immune Organ Developments of Broiler Chickens

This study was conducted to investigate the optimum levels of glutamine (Gln) supplementation in broiler diets. A total of 32 one-day-old male chicks with initial body weight 41.5 g were segregated into 4 groups (8 chicks per group) and subsequently distributed to individual cages. Feed and water were provided ad libitum for 21 days. Four dietary treatments were as follows: control and supplemented Gln at 1, 2 and 3%, respectively. The results found that the addition Gln had no negative effects on dry matter, organic matter, ash digestibility or nitrogen retention. Birds fed with 1% Gln had significantly higher villi wide and villi height : crypt depth ratio in duodenum than the control chicks and 2 and 3% Gln chicks. It is suggested that the addition of Gln at 1% indicated a beneficial effect on improving small intestinal morphology, in addition Gln may stimulate immune organ development of broiler chickens.

Overcoming Barriers to Open Innovation at Apple, Nintendo and Nokia

This is a conceptual paper on the application of open innovation in three case examples of Apple, Nintendo, and Nokia. Utilizing key concepts from research into managerial and organizational cognition, we describe how each company overcame barriers to utilizing open innovation strategy in R&D and commercialization projects. We identify three levels of barriers: cognitive, behavioral, and institutional, and describe the companies balanced between internal and external resources to launch products that were instrumental in companies reinventing themselves in mature markets.

Reliability of Digital FSO Links in Europe

The paper deals with an analysis of visibility records collected from 210 European airports to obtain a realistic estimation of the availability of Free Space Optical (FSO) data links. Commercially available optical links usually operate in the 850nm waveband. Thus the influence of the atmosphere on the optical beam and on the visible light is similar. Long-term visibility records represent an invaluable source of data for the estimation of the quality of service of FSO links. The model used characterizes both the statistical properties of fade depths and the statistical properties of individual fade durations. Results are presented for Italy, France, and Germany.

Determining Cluster Boundaries Using Particle Swarm Optimization

Self-organizing map (SOM) is a well known data reduction technique used in data mining. Data visualization can reveal structure in data sets that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOMs, but they generally do not take into account the distribution of code vectors; this may lead to unsatisfactory clustering and poor definition of cluster boundaries, particularly where the density of data points is low. In this paper, we propose the use of a generic particle swarm optimization (PSO) algorithm for finding cluster boundaries directly from the code vectors obtained from SOMs. The application of our method to unlabeled call data for a mobile phone operator demonstrates its feasibility. PSO algorithm utilizes U-matrix of SOMs to determine cluster boundaries; the results of this novel automatic method correspond well to boundary detection through visual inspection of code vectors and k-means algorithm.

Instructional Design Using the Virtual Ecological Pond for Science Education in Elementary Schools

Ecological ponds can be a good teaching tool for science teachers, but they must be built and maintained properly to provide students with a safe and suitable learning environment. Hence, many schools do not have the ability to build an ecological pond. This study used virtual reality technology to develop a webbased virtual ecological pond. Supported by situated learning theory and the instructional design of “Aquatic Life" learning unit, elementary school students can actively explore in the virtual ecological pond to observe aquatic animals and plants and learn about the concept of ecological conservation. A teaching experiment was conducted to investigate the learning effectiveness and practicability of this instructional design, and the results showed that students improved a great deal in learning about aquatic life. They found the virtual ecological pond interesting, easy to operate and helpful to understanding the aquatic ecological system. Therefore, it is useful in elementary science education.

Two-Phase Optimization for Selecting Materialized Views in a Data Warehouse

A data warehouse (DW) is a system which has value and role for decision-making by querying. Queries to DW are critical regarding to their complexity and length. They often access millions of tuples, and involve joins between relations and aggregations. Materialized views are able to provide the better performance for DW queries. However, these views have maintenance cost, so materialization of all views is not possible. An important challenge of DW environment is materialized view selection because we have to realize the trade-off between performance and view maintenance. Therefore, in this paper, we introduce a new approach aimed to solve this challenge based on Two-Phase Optimization (2PO), which is a combination of Simulated Annealing (SA) and Iterative Improvement (II), with the use of Multiple View Processing Plan (MVPP). Our experiments show that 2PO outperform the original algorithms in terms of query processing cost and view maintenance cost.

Vortex-Induced Vibration Characteristics of an Elastic Circular Cylinder

A numerical simulation of vortex-induced vibration of a 2-dimensional elastic circular cylinder with two degree of freedom under the uniform flow is calculated when Reynolds is 200. 2-dimensional incompressible Navier-Stokes equations are solved with the space-time finite element method, the equation of the cylinder motion is solved with the new explicit integral method and the mesh renew is achieved by the spring moving mesh technology. Considering vortex-induced vibration with the low reduced damping parameter, the variety trends of the lift coefficient, the drag coefficient, the displacement of cylinder are analyzed under different oscillating frequencies of cylinder. The phenomena of locked-in, beat and phases-witch were captured successfully. The evolution of vortex shedding from the cylinder with time is discussed. There are very similar trends in characteristics between the results of the one degree of freedom cylinder model and that of the two degree of freedom cylinder model. The streamwise vibrations have a certain effect on the lateral vibrations and their characteristics.

Organic Thin Film Transistors based Oligothiophine Derivatives using DZ-Dihexyl(quarter- and sexi-)Thiophene

End-substitution of quarterthiophene and sexithiophene with hexyl groups leads to highly soluble conjugated oligomers,DZ-dihexylquarterthiophene (DH-4T) and DZ-dihexylsexithiophene (DH-6T). We have characterized these oligomers for optical and electrical properties. We fabricated an organic thin film transistor (OTFT) using the above two air-stable p-type organic semiconductor materials. We obtained a stable characteristic curve. The field effect mobility, Pwas calculated to be 3.2910-4 cm2/Vs for DH-6T based OTFT; while the DH-4T based OTFT had 1.8810-5 cm2/Vs.KeywordsOrganic thin film transistor, DZ-dihexylquarterthiophene, DZ-dihexylsexithiophene.

Genetic-Based Multi Resolution Noisy Color Image Segmentation

Segmentation of a color image composed of different kinds of regions can be a hard problem, namely to compute for an exact texture fields. The decision of the optimum number of segmentation areas in an image when it contains similar and/or un stationary texture fields. A novel neighborhood-based segmentation approach is proposed. A genetic algorithm is used in the proposed segment-pass optimization process. In this pass, an energy function, which is defined based on Markov Random Fields, is minimized. In this paper we use an adaptive threshold estimation method for image thresholding in the wavelet domain based on the generalized Gaussian distribution (GGD) modeling of sub band coefficients. This method called Normal Shrink is computationally more efficient and adaptive because the parameters required for estimating the threshold depend on sub band data energy that used in the pre-stage of segmentation. A quad tree is employed to implement the multi resolution framework, which enables the use of different strategies at different resolution levels, and hence, the computation can be accelerated. The experimental results using the proposed segmentation approach are very encouraging.

Auto Tuning PID Controller based on Improved Genetic Algorithm for Reverse Osmosis Plant

An optimal control of Reverse Osmosis (RO) plant is studied in this paper utilizing the auto tuning concept in conjunction with PID controller. A control scheme composing an auto tuning stochastic technique based on an improved Genetic Algorithm (GA) is proposed. For better evaluation of the process in GA, objective function defined newly in sense of root mean square error has been used. Also in order to achieve better performance of GA, more pureness and longer period of random number generation in operation are sought. The main improvement is made by replacing the uniform distribution random number generator in conventional GA technique to newly designed hybrid random generator composed of Cauchy distribution and linear congruential generator, which provides independent and different random numbers at each individual steps in Genetic operation. The performance of newly proposed GA tuned controller is compared with those of conventional ones via simulation.

A Systems Modeling Approach to Support Environmentally Sustainable Business Development in Manufacturing SMEs

Small and Medium Sized Enterprises (SMEs) play an important role in many economies. In New Zealand, for example, 97% of all manufacturing companies employ less than 100 staff, and generate the predominant part of this industry sector-s economic output. Manufacturing SMEs as a group also have a significant impact on the environment. This situation is similar in many developed economies, including the European Union. Sustainable economic development therefore needs to strongly consider the role of manufacturing SMEs, who generally find it challenging to move towards more environmentally friendly business practices. This paper presents a systems thinking approach to modelling and understanding the factors which have an influence on the successful uptake of environmental practices in small and medium sized manufacturing companies. It presents a number of causal loop diagrams which have been developed based on primary action research, and a thorough understanding of the literature in this area. The systems thinking model provides the basis for further development of a strategic framework for the successful uptake of environmental innovation in manufacturing SMEs.

Java Based Automatic Curriculum Generator for Children with Trisomy 21

Early Intervention Program (EIP) is required to improve the overall development of children with Trisomy 21 (Down syndrome). In order to help trainer and parent in the implementation of EIP, a support system has been developed. The support system is able to screen data automatically, store and analyze data, generate individual EIP (curriculum) with optimal training duration and to generate training automatically. The system consists of hardware and software where the software has been implemented using Java language and Linux Fedora. The software has been tested to ensure the functionality and reliability. The prototype has been also tested in Down syndrome centers. Test result shows that the system is reliable to be used for generation of an individual curriculum which includes the training program to improve the motor, cognitive, and combination abilities of Down syndrome children under 6 years.