The Television Morning News for Thai Undergraduate Students: Information Exposure, Uses and Gratifications

The purposes of the study are to study and to investigate the relationship among exposure, uses and gratifications of television morning news among undergraduate students in Bangkok. This study also compares differences in information exposure, uses and gratifications of television morning news among these students. The research methodology employed a questionnaire as a quantitative method. The respondents were undergraduate students at public and private universities in Bangkok. Totally, 400 usable questionnaires were received. Descriptive and inferential statistics were used in data analysis. The results indicated that information exposure of undergraduate students in Bangkok was at a high level. Students’ uses and gratifications were also at high level. Information exposure was positively correlated with uses and gratifications. Uses of information were positively correlated with satisfaction with information. The results also showed that students with differences in sex and type of university were not significantly different in information exposure, and uses and gratifications.

An Intelligent Human-Computer Interaction System for Decision Support

This paper proposes a novel architecture for developing decision support systems. Unlike conventional decision support systems, the proposed architecture endeavors to reveal the decision-making process such that humans' subjectivity can be incorporated into a computerized system and, at the same time, to preserve the capability of the computerized system in processing information objectively. A number of techniques used in developing the decision support system are elaborated to make the decisionmarking process transparent. These include procedures for high dimensional data visualization, pattern classification, prediction, and evolutionary computational search. An artificial data set is first employed to compare the proposed approach with other methods. A simulated handwritten data set and a real data set on liver disease diagnosis are then employed to evaluate the efficacy of the proposed approach. The results are analyzed and discussed. The potentials of the proposed architecture as a useful decision support system are demonstrated.

A Classification Scheme for Game Input and Output

Computer game industry has experienced exponential growth in recent years. A game is a recreational activity involving one or more players. Game input is information such as data, commands, etc., which is passed to the game system at run time from an external source. Conversely, game outputs are information which are generated by the game system and passed to an external target, but which is not used internally by the game. This paper identifies a new classification scheme for game input and output, which is based on player-s input and output. Using this, relationship table for game input classifier and output classifier is developed.

Simulation of Ethical Behavior in Urban Transportation

For controlling urban transportations, traffic lights show similar behavior for different kinds of vehicles at intersections. Emergency vehicles need special behavior at intersections, so traffic lights should behave in different manner when emergency vehicles approach them. At the present time, intelligent traffic lights control urban transportations intelligently. In this paper the ethical aspect of this topic is considered. A model is proposed for adding special component to emergency vehicles and traffic lights for controlling traffic in ethical manner. The proposed model is simulated by JADE.

Learning User Keystroke Patterns for Authentication

Keystroke authentication is a new access control system to identify legitimate users via their typing behavior. In this paper, machine learning techniques are adapted for keystroke authentication. Seven learning methods are used to build models to differentiate user keystroke patterns. The selected classification methods are Decision Tree, Naive Bayesian, Instance Based Learning, Decision Table, One Rule, Random Tree and K-star. Among these methods, three of them are studied in more details. The results show that machine learning is a feasible alternative for keystroke authentication. Compared to the conventional Nearest Neighbour method in the recent research, learning methods especially Decision Tree can be more accurate. In addition, the experiment results reveal that 3-Grams is more accurate than 2-Grams and 4-Grams for feature extraction. Also, combination of attributes tend to result higher accuracy.

Fretting Fatigue behavior of Bolted Single Lap Joints of Aluminum Alloys

In this paper, the effect of bolt clamping force on the fatigue behavior of bolted single lap joints of aluminum alloy 2024- T3 have been studied using numerical finite element method. To do so, a three dimensional model according to the bolted single lap joint has been created and numerical analysis has been carried out using finite element based package. Then the stress distribution and also the slip amplitudes have been calculated in the critical regions and the outcome have been compared with the available experimental fatigue tests results. The numerical results show that in low applied clamping force, the fatigue failure of the specimens occur around the stress concentration location (the bolted hole edge) due to the tensile stresses and thus fatigue crack propagation, but with increase of the clamping force, the fatigue life increases and the cracks nucleate and propagate far from the hole edge because of fretting fatigue. In other words, with the further increase of clamping force value of the joint, the fatigue life reduces due to occurrence of the fretting fatigue in the critical location where the slip amplitude is within its critical occurs earlier.

Impact of Combustion of Water in Fuel on Polycyclic Aromatic Hydrocarbon (Pah-s)Precursors- Formation

Some of the polycyclic aromatic hydrocarbons (PAHs) are the strongest known carcinogens compounds; the majority of them are mostly produced by the incomplete combustion of fossil fuels; Motor vehicles are a significant source of polycyclic aromatic hydrocarbon (PAH) where diesel emission is one of the main sources of such compounds available in the ambient air. There is a big concern about the increasing concentration of PAHs in the environment. Researchers are trying to explore optimal methods to reduce those pollutants and improve the quality of air. Water blended fuel is one of the possible approaches to reduce emission of PAHs from the combustion of diesel in urban and domestic vehicles. In this work a modeling study was conducted using CHEMKIN-PRO software to simulate spray combustion at similar diesel engine conditions. Surrogate fuel of (80 % n-heptane and 20 % toluene) was used due to detailed kinetic and thermodynamic data needed for modeling is available for this kind of fuel but not available for diesel. An emulsified fuel with 3, 5, 8, 10 and 20 % water by volume is used as an engine feed for this study. The modeling results show that water has a significant effect on reducing engine soot and PAHs precursors formation up to certain extent.

Comparative Analysis of Different Control Strategies for Electro-hydraulic Servo Systems

The main goal of the study is to analyze all relevant properties of the electro hydraulic systems and based on that to make a proper choice of the control strategy that may be used for the control of the servomechanism system. A combination of electronic and hydraulic systems is widely used since it combines the advantages of both. Hydraulic systems are widely spread because of their properties as accuracy, flexibility, high horsepower-to-weight ratio, fast starting, stopping and reversal with smoothness and precision, and simplicity of operations. On the other hand, the modern control of hydraulic systems is based on control of the circuit fed to the inductive solenoid that controls the position of the hydraulic valve. Since this circuit may be easily handled by PWM (Pulse Width Modulation) signal with a proper frequency, the combination of electrical and hydraulic systems became very fruitful and usable in specific areas as airplane and military industry. The study shows and discusses the experimental results obtained by the control strategy (classical feedback (PID) & neural network) using MATLAB and SIMULINK [1]. Finally, the special attention was paid to the possibility of neuro-controller design and its application to control of electro-hydraulic systems and to make comparative with classical control.

Reliability Optimization for 3G Cellular Access Networks

This paper address the network reliability optimization problem in the optical access network design for the 3G cellular systems. We presents a novel 0-1 integer programming model for designing optical access network topologies comprised of multi-rings with common-edge in order to guarantee always-on services. The results show that the proposed model yields access network topologies with the optimal reliablity and satisfies both network cost limitations and traffic demand requirements.

Regional Differences in the Effect of Immigration on Poverty Rates in Spain

This paper explores the extent of the gap in poverty rates between immigrant and native households in Spanish regions and assess to what extent regional differences in individual and contextual characteristics can explain the divergences in such a gap. By using multilevel techniques and European Union Survey on Income and Living Conditions, we estimate immigrant households experiments an increase of 76 per cent in the odds of being poor compared with a native one when we control by individual variables. In relation to regional differences in the risk of poverty, regionallevel variables have higher effect in the reduction of these differences than individual variables.

Mixed Model Assembly Line Sequencing In Make to Order System with Available to Promise Consideration

Mixed model assembly lines (MMAL) are a type of production line where a variety of product models similar in product characteristics are assembled. The effective design of these lines requires that schedule for assembling the different products is determined. In this paper we tried to fit the sequencing problem with the main characteristics of make to order (MTO) environment. The problem solved in this paper is a multiple objective sequencing problem in mixed model assembly lines sequencing using weighted Sum Method (WSM) using GAMS software for small problem and an effective GA for large scale problems because of the nature of NP-hardness of our problem and vast time consume to find the optimum solution in large problems. In this problem three practically important objectives are minimizing: total utility work, keeping a constant production rate variation, and minimizing earliness and tardiness cost which consider the priority of each customer and different due date which is a real situation in mixed model assembly lines and it is the first time we consider different attribute to prioritize the customers which help the company to reduce the cost of earliness and tardiness. This mechanism is a way to apply an advance available to promise (ATP) in mixed model assembly line sequencing which is the main contribution of this paper.

The Determinants of Voluntary Disclosure in Croatia

Study investigates the level and extent of voluntary disclosure practice in Croatia. The research was conducted on the sample of 130 medium and large companies. Findings indicate that two thirds of the companies analyzed disclose below-average number of additional information. The explanatory analyses has shown that firm size, listing status and industrial sector significantly and positively affect the level and extent of voluntary disclosure in the annual report of Croatian companies. On the other hand, profitability and ownership structure were found statistically insignificant. Unlike previous studies, this paper deals with level of voluntary disclosure of medium and large companies, as well as companies whose shares are not listed on the organized capital market, which can be found as our contribution. Also, the research makes contribution by providing the insights into voluntary disclosure practices in Croatia, as a case of macro-oriented accounting system economy, i.e. bank oriented economy with an emerging capital market.

EEG-Based Fractal Analysis of Different Motor Imagery Tasks using Critical Exponent Method

The objective of this paper is to characterize the spontaneous Electroencephalogram (EEG) signals of four different motor imagery tasks and to show hereby a possible solution for the present binary communication between the brain and a machine ora Brain-Computer Interface (BCI). The processing technique used in this paper was the fractal analysis evaluated by the Critical Exponent Method (CEM). The EEG signal was registered in 5 healthy subjects,sampling 15 measuring channels at 1024 Hz.Each channel was preprocessed by the Laplacian space ltering so as to reduce the space blur and therefore increase the spaceresolution. The EEG of each channel was segmented and its Fractaldimension (FD) calculated. The FD was evaluated in the time interval corresponding to the motor imagery and averaged out for all the subjects (each channel). In order to characterize the FD distribution,the linear regression curves of FD over the electrodes position were applied. The differences FD between the proposed mental tasks are quantied and evaluated for each experimental subject. The obtained results of the proposed method are a substantial fractal dimension in the EEG signal of motor imagery tasks and can be considerably utilized as the multiple-states BCI applications.

Morphology and Risk Factors for Blunt Aortic Trauma in Car Accidents - An Autopsy Study

Background: Blunt aortic trauma (BAT) includes various morphological changes that occur during deceleration, acceleration and/or body compression in traffic accidents. The various forms of BAT, from limited laceration of the intima to complete transection of the aorta, depends on the force acting on the vessel wall and the tolerance of the aorta to injury. The force depends on the change in velocity, the dynamics of the accident and of the seating position in the car. Tolerance to aortic injury depends on the anatomy, histological structure and pathomorphological alterations due to aging or disease of the aortic wall. An overview of the literature and medical documentation reveals that different terms are used to describe certain forms of BAT, which can lead to misinterpretation of findings or diagnoses. We therefore, propose a classification that would enable uniform systematic screening of all forms of BAT. We have classified BAT into three morphologycal types: TYPE I (intramural), TYPE II (transmural) and TYPE III (multiple) aortic ruptures with appropriate subtypes. Methods: All car accident casualties examined at the Institute of Forensic Medicine from 2001 to 2009 were included in this retrospective study. Autopsy reports were used to determine the occurrence of each morphological type of BAT in deceased drivers, front seat passengers and other passengers in cars and to define the morphology of BAT in relation to the accident dynamics and the age of the fatalities. Results: A total of 391 fatalities in car accidents were included in the study. TYPE I, TYPE II and TYPE III BAT were observed in 10,9%, 55,6% and 33,5%, respectively. The incidence of BAT in drivers, front seat and other passengers was 36,7%, 43,1% and 28,6%, respectively. In frontal collisions, the incidence of BAT was 32,7%, in lateral collisions 54,2%, and in other traffic accidents 29,3%. The average age of fatalities with BAT was 42,8 years and of those without BAT 39,1 years. Conclusion: Identification and early recognition of the risk factors of BAT following a traffic accident is crucial for successful treatment of patients with BAT. Front seat passengers over 50 years of age who have been injured in a lateral collision are the most at risk of BAT.

CASTE: a Cloud-Based Automatic Software Test Environment

This paper presents the design and implementation of CASTE, a Cloud-based automatic software test environment. We first present the architecture of CASTE, then the main packages and classes of it are described in detail. CASTE is built upon a private Infrastructure as a Service platform. Through concentrated resource management of virtualized testing environment and automatic execution control of test scripts, we get a better solution to the testing resource utilization and test automation problem. Experiments on CASTE give very appealing results.

Exergy Analysis of Combined Cycle of Air Separation and Natural Gas Liquefaction

This paper presented a novel combined cycle of air separation and natural gas liquefaction. The idea is that natural gas can be liquefied, meanwhile gaseous or liquid nitrogen and oxygen are produced in one combined cryogenic system. Cycle simulation and exergy analysis were performed to evaluate the process and thereby reveal the influence of the crucial parameter, i.e., flow rate ratio through two stages expanders β on heat transfer temperature difference, its distribution and consequent exergy loss. Composite curves for the combined hot streams (feeding natural gas and recycled nitrogen) and the cold stream showed the degree of optimization available in this process if appropriate β was designed. The results indicated that increasing β reduces temperature difference and exergy loss in heat exchange process. However, the maximum limit value of β should be confined in terms of minimum temperature difference proposed in heat exchanger design standard and heat exchanger size. The optimal βopt under different operation conditions corresponding to the required minimum temperature differences was investigated.

A Robust Method for Hand Tracking Using Mean-shift Algorithm and Kalman Filter in Stereo Color Image Sequences

Real-time hand tracking is a challenging task in many computer vision applications such as gesture recognition. This paper proposes a robust method for hand tracking in a complex environment using Mean-shift analysis and Kalman filter in conjunction with 3D depth map. The depth information solve the overlapping problem between hands and face, which is obtained by passive stereo measuring based on cross correlation and the known calibration data of the cameras. Mean-shift analysis uses the gradient of Bhattacharyya coefficient as a similarity function to derive the candidate of the hand that is most similar to a given hand target model. And then, Kalman filter is used to estimate the position of the hand target. The results of hand tracking, tested on various video sequences, are robust to changes in shape as well as partial occlusion.

Designing the Concrete-Framework Building and Examining its Behavior under the Explosion Load

These Nowadays the explosion of bombs or explosive materials such as gas and oil near or inside the buildings cause some losses in installations and building components. This has made the engineers to make the buildings and their components resistance against the effects of explosion. These activities lead to provide regulations and different methods. The above regulations are mostly focused on the explosion effects resulting from the vehicles around the buildings. Therefore, the explosion resulting from the vehicles outside the buildings will be studied in this research. In the present study, the main goals are to investigate the explosion load effects on the structures located on the piles with the specific quantity of plasticity and observing the permissible response of these structures. The concentrated mass system and the spring with two degree of freedom will be used to study the structural system.

Revised PLWAP Tree with Non-frequent Items for Mining Sequential Pattern

Sequential pattern mining is a challenging task in data mining area with large applications. One among those applications is mining patterns from weblog. Recent times, weblog is highly dynamic and some of them may become absolute over time. In addition, users may frequently change the threshold value during the data mining process until acquiring required output or mining interesting rules. Some of the recently proposed algorithms for mining weblog, build the tree with two scans and always consume large time and space. In this paper, we build Revised PLWAP with Non-frequent Items (RePLNI-tree) with single scan for all items. While mining sequential patterns, the links related to the nonfrequent items are not considered. Hence, it is not required to delete or maintain the information of nodes while revising the tree for mining updated transactions. The algorithm supports both incremental and interactive mining. It is not required to re-compute the patterns each time, while weblog is updated or minimum support changed. The performance of the proposed tree is better, even the size of incremental database is more than 50% of existing one. For evaluation purpose, we have used the benchmark weblog dataset and found that the performance of proposed tree is encouraging compared to some of the recently proposed approaches.

Proposal of Additional Fuzzy Membership Functions in Smoothing Transition Autoregressive Models

In this paper we present, propose and examine additional membership functions for the Smoothing Transition Autoregressive (STAR) models. More specifically, we present the tangent hyperbolic, Gaussian and Generalized bell functions. Because Smoothing Transition Autoregressive (STAR) models follow fuzzy logic approach, more fuzzy membership functions should be tested. Furthermore, fuzzy rules can be incorporated or other training or computational methods can be applied as the error backpropagation or genetic algorithm instead to nonlinear squares. We examine two macroeconomic variables of US economy, the inflation rate and the 6-monthly treasury bills interest rates.