Effects of TiO2 and Nb2O5 on Hydrogen Desorption of Mg(BH4)2

In this work, effects of catalysts (TiO2, and Nb2O5) were investigated on the hydrogen desorption of Mg(BH4)2. LiBH4 and MgCl2 with 2:1 molar ratio were mixed by using ball milling to prepare Mg(BH4)2. The desorption behaviors were measured by thermo-volumetric apparatus. The hydrogen desorption capacity of the mixed sample milled for 2 h was 4.78 wt% with a 2-step released. The first step occurred at 214 °C and the second step appeared at 374 °C. The addition of 16 wt% Nb2O5 decreased the desorption temperature in the second step about 66 °C and increased the hydrogen desorption capacity to 4.86 wt% hydrogen. The addition of TiO2 also improved the desorption temperature in the second step and the hydrogen desorption capacity. It decreased the desorption temperature about 71°C and showed a high amount of hydrogen, 5.27 wt%, released from the mixed sample. The hydrogen absorption after desorption of Mg(BH4)2 was also studied under 9.5 MPa and 350 °C for 12 h.

A Multiagent System for Distributed Systems Management

The demand for autonomous resource management for distributed systems has increased in recent years. Distributed systems require an efficient and powerful communication mechanism between applications running on different hosts and networks. The use of mobile agent technology to distribute and delegate management tasks promises to overcome the scalability and flexibility limitations of the currently used centralized management approach. This work proposes a multiagent system that adopts mobile agents as a technology for tasks distribution, results collection, and management of resources in large-scale distributed systems. A new mobile agent-based approach for collecting results from distributed system elements is presented. The technique of artificial intelligence based on intelligent agents giving the system a proactive behavior. The presented results are based on a design example of an application operating in a mobile environment.

Decision Algorithm for Smart Airbag Deployment Safety Issues

Airbag deployment has been known to be responsible for huge death, incidental injuries and broken bones due to low crash severity and wrong deployment decisions. Therefore, the authorities and industries have been looking for more innovative and intelligent products to be realized for future enhancements in the vehicle safety systems (VSSs). Although the VSSs technologies have advanced considerably, they still face challenges such as how to avoid unnecessary and untimely airbag deployments that can be hazardous and fatal. Currently, most of the existing airbag systems deploy without regard to occupant size and position. As such, this paper will focus on the occupant and crash sensing performances due to frontal collisions for the new breed of so called smart airbag systems. It intends to provide a thorough discussion relating to the occupancy detection, occupant size classification, occupant off-position detection to determine safe distance zone for airbag deployment, crash-severity analysis and airbag decision algorithms via a computer modeling. The proposed system model consists of three main modules namely, occupant sensing, crash severity analysis and decision fusion. The occupant sensing system module utilizes the weight sensor to determine occupancy, classify the occupant size, and determine occupant off-position condition to compute safe distance for airbag deployment. The crash severity analysis module is used to generate relevant information pertinent to airbag deployment decision. Outputs from these two modules are fused to the decision module for correct and efficient airbag deployment action. Computer modeling work is carried out using Simulink, Stateflow, SimMechanics and Virtual Reality toolboxes.

How Learning Efficiency Affects Job Performance Effectiveness

The purpose of this research was to study the influence of learning efficiency on local accountants’ job performance effectiveness. This paper drew upon the survey data collected from 335 local accountants survey conducted at Nakhon Ratchasima province, Thailand. The statistics utilized in this paper included percentage, mean, standard deviation, and regression analysis. The findings revealed that the majority of samples were between 31-40 years old, married, held an undergraduate degree, and had an average income between 10,000-15,000 baht. The majority of respondents had less than five years of accounting experience and worked for local administrations. The overall learning efficiency score was in the highest level while the local accountants’ job performance effectiveness score was also in the high level. The hypothesis testing’s result disclosed that learning efficiency factors which were knowledge, Skill, and Attitude had an influence on local accountants’ job the performance effectiveness.

Study of Compost Maturity during Humification Process using UV-Spectroscopy

The increments of aromatic structures are widely used to monitor the degree of humification. Compost derived from mix manures mixed with agricultural wastes was studied. The compost collected at day 0, 7, 14, 21, 28, 35, 49, 77, 91, 105, and 119 was divided into 3 stages, initial stage at day 0, thermophilic stage during day 1-48, and mature stage during day 49-119. The change of highest absorptions at wavelength range between 210-235 nm during day 0- 49 implied that small molecules such as nitrates and carboxylic occurred faster than the aromatic molecules that were found at wavelength around 280 nm. The ratio of electron-transfer band at wavelength 253 nm by the benzonoid band at wavelength 230 nm (E253/E230) also gradually increased during the fermenting period indicating the presence of O-containing functional groups. This was in agreement with the shift change from aliphatic to aromatic structures as shown by the relationship with C/N and H/C ratios (r = - 0.631 and -0.717, p< 0.05) since both were decreasing. Although the amounts of humic acid (HA) were not different much during the humification process, the UV spectral deconvolution showed better qualitative characteristics to help in determining the compost quality. From this study, the compost should be used at day 49 and should not be kept longer than 3 months otherwise the quality of HA would decline regardless of the amounts of HA that might be rising. This implied that other processes, such as mineralization had an influence on the humification process changing HA-s structure and its qualities.

Efficient Real-time Remote Data Propagation Mechanism for a Component-Based Approach to Distributed Manufacturing

Manufacturing Industries face a crucial change as products and processes are required to, easily and efficiently, be reconfigurable and reusable. In order to stay competitive and flexible, situations also demand distribution of enterprises globally, which requires implementation of efficient communication strategies. A prototype system called the “Broadcaster" has been developed with an assumption that the control environment description has been engineered using the Component-based system paradigm. This prototype distributes information to a number of globally distributed partners via an adoption of the circular-based data processing mechanism. The work highlighted in this paper includes the implementation of this mechanism in the domain of the manufacturing industry. The proposed solution enables real-time remote propagation of machine information to a number of distributed supply chain client resources such as a HMI, VRML-based 3D views and remote client instances regardless of their distribution nature and/ or their mechanisms. This approach is presented together with a set of evaluation results. Authors- main concentration surrounds the reliability and the performance metric of the adopted approach. Performance evaluation is carried out in terms of the response times taken to process the data in this domain and compared with an alternative data processing implementation such as the linear queue mechanism. Based on the evaluation results obtained, authors justify the benefits achieved from this proposed implementation and highlight any further research work that is to be carried out.

Multilevel Activation Functions For True Color Image Segmentation Using a Self Supervised Parallel Self Organizing Neural Network (PSONN) Architecture: A Comparative Study

The paper describes a self supervised parallel self organizing neural network (PSONN) architecture for true color image segmentation. The proposed architecture is a parallel extension of the standard single self organizing neural network architecture (SONN) and comprises an input (source) layer of image information, three single self organizing neural network architectures for segmentation of the different primary color components in a color image scene and one final output (sink) layer for fusion of the segmented color component images. Responses to the different shades of color components are induced in each of the three single network architectures (meant for component level processing) by applying a multilevel version of the characteristic activation function, which maps the input color information into different shades of color components, thereby yielding a processed component color image segmented on the basis of the different shades of component colors. The number of target classes in the segmented image corresponds to the number of levels in the multilevel activation function. Since the multilevel version of the activation function exhibits several subnormal responses to the input color image scene information, the system errors of the three component network architectures are computed from some subnormal linear index of fuzziness of the component color image scenes at the individual level. Several multilevel activation functions are employed for segmentation of the input color image scene using the proposed network architecture. Results of the application of the multilevel activation functions to the PSONN architecture are reported on three real life true color images. The results are substantiated empirically with the correlation coefficients between the segmented images and the original images.

Constraint Active Contour Model with Application to Automated Three-Dimensional Airway Wall Segmentation

For evaluating the severity of Chronic Obstructive Pulmonary Disease (COPD), one is interested in inspecting the airway wall thickening due to inflammation. Although airway segmentations have being well developed to reconstruct in high order, airway wall segmentation remains a challenge task. While tackling such problem as a multi-surface segmentation, the interrelation within surfaces needs to be considered. We propose a new method for three-dimensional airway wall segmentation using spring structural active contour model. The method incorporates the gravitational field of the image and repelling force field of the inner lumen as the soft constraint and the geometric spring structure of active contour as the hard constraint to approximate a three-dimensional coupled surface readily for thickness measurements. The results show the preservation of topology constraints of coupled surfaces. In conclusion, our springy, soft-tissue-like structure ensures the globally optimal solution and waives the shortness following by the inevitable improper inner surface constraint.

Electrical Impedance Imaging Using Eddy Current

Electric impedance imaging is a method of reconstructing spatial distribution of electrical conductivity inside a subject. In this paper, a new method of electrical impedance imaging using eddy current is proposed. The eddy current distribution in the body depends on the conductivity distribution and the magnetic field pattern. By changing the position of magnetic core, a set of voltage differences is measured with a pair of electrodes. This set of voltage differences is used in image reconstruction of conductivity distribution. The least square error minimization method is used as a reconstruction algorithm. The back projection algorithm is used to get two dimensional images. Based on this principle, a measurement system is developed and some model experiments were performed with a saline filled phantom. The shape of each model in the reconstructed image is similar to the corresponding model, respectively. From the results of these experiments, it is confirmed that the proposed method is applicable in the realization of electrical imaging.

The Service Failure and Recovery in the Information Technology Services

It is important to retain customer satisfaction in information technology services. When a service failure occurs, companies need to take service recovery action to recover their customer satisfaction. Although companies cannot avoid all problems and complaints, they should try to make up. Therefore, service failure and service recovery have become an important and challenging issue for companies. In this paper, the literature and the problems in the information technology services were reviewed. An integrated model of profit driven for the service failure and service recovery was established in view of the benefit of customer and enterprise. Moreover, the interaction between service failure and service recovery strategy was studied, the result of which verified the matching principles of the service recovery strategy and the type of service failure. In addition, the relationship between the cost of service recovery and customer-s cumulative value of service after recovery was analyzed with the model. The result attributes to managers in deciding on appropriate resource allocations for recovery strategies.

Solar Thermal Aquaculture System Controller Based on Artificial Neural Network

Temperature is one of the most principle factors affects aquaculture system. It can cause stress and mortality or superior environment for growth and reproduction. This paper presents the control of pond water temperature using artificial intelligence technique. The water temperature is very important parameter for shrimp growth. The required temperature for optimal growth is 34oC, if temperature increase up to 38oC it cause death of the shrimp, so it is important to control water temperature. Solar thermal water heating system is designed to supply an aquaculture pond with the required hot water in Mersa Matruh in Egypt. Neural networks are massively parallel processors that have the ability to learn patterns through a training experience. Because of this feature, they are often well suited for modeling complex and non-linear processes such as those commonly found in the heating system. Artificial neural network is proposed to control water temperature due to Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques. They have been used to solve complicated practical problems. Moreover this paper introduces a complete mathematical modeling and MATLAB SIMULINK model for the aquaculture system. The simulation results indicate that, the control unit success in keeping water temperature constant at the desired temperature by controlling the hot water flow rate.

Persistence of Termination for Non-Overlapping Term Rewriting Systems

A property is called persistent if for any many-sorted term rewriting system , has the property if and only if term rewriting system , which results from by omitting its sort information, has the property. In this paper,we show that termination is persistent for non-overlapping term rewriting systems and we give the example as application of this result. Furthermore we obtain that completeness is persistent for non-overlapping term rewriting systems.

System Module for Student Idol

Malaysia government had been trying hard in order to find the most efficient methods in learning. However, it is hard to actually access and evaluate students whom will then be called an excellent student. It is because in our realties student who excellent is only excel in academic. This evaluation becomes a problem because it not balances in our real life interm of to get an excellent student in whole area in their involvement of curiculum and cocuriculum. To overcome this scenario, we designed a module for Student Idol to evaluate student through three categories which are academic, co-curiculum and leadership. All the categories have their own merit point. Using this method, student will be evaluated more accurate compared to the previously. So, teacher can easily evaluate their student without having any emotion factor, relation factor and others. As conclusion this system module will helps the development of student evaluation more accurate and valid in Student Idol.

Multi-Enterprise Tie and Co-Operation Mechanism in Mexican Agro Industry SME's

The aim of this paper is to explain what a multienterprise tie is, what evidence its analysis provides and how does the cooperation mechanism influence the establishment of a multienterprise tie. The study focuses on businesses of smaller dimension, geographically dispersed and whose businessmen are learning to cooperate in an international environment. The empirical evidence obtained at this moment permits to conclude the following: The tie is not long-lasting, it has an end; opportunism is an opportunity to learn; the multi-enterprise tie is a space to learn about the cooperation mechanism; the local tie permits a businessman to alternate between competition and cooperation strategies; the disappearance of a tie is an experience of learning for a businessman, diminishing the possibility of failure in the next tie; the cooperation mechanism tends to eliminate hierarchical relations; the multienterprise tie diminishes the asymmetries and permits SME-s to have a better position when they negotiate with large companies; the multi-enterprise tie impacts positively on the local system. The collection of empirical evidence was done trough the following instruments: direct observation in a business encounter to which the businesses attended in 2003 (202 Mexican agro industry SME-s), a survey applied in 2004 (129), a questionnaire applied in 2005 (86 businesses), field visits to the businesses during the period 2006-2008 and; a survey applied by telephone in 2008 (55 Mexican agro industry SME-s).

Automotive 3-Microphone Noise Canceller in a Frequently Moving Noise Source Environment

A combined three-microphone voice activity detector (VAD) and noise-canceling system is studied to enhance speech recognition in an automobile environment. A previous experiment clearly shows the ability of the composite system to cancel a single noise source outside of a defined zone. This paper investigates the performance of the composite system when there are frequently moving noise sources (noise sources are coming from different locations but are not always presented at the same time) e.g. there is other passenger speech or speech from a radio when a desired speech is presented. To work in a frequently moving noise sources environment, whilst a three-microphone voice activity detector (VAD) detects voice from a “VAD valid zone", the 3-microphone noise canceller uses a “noise canceller valid zone" defined in freespace around the users head. Therefore, a desired voice should be in the intersection of the noise canceller valid zone and VAD valid zone. Thus all noise is suppressed outside this intersection of area. Experiments are shown for a real environment e.g. all results were recorded in a car by omni-directional electret condenser microphones.

Continuous and Discontinuous Shock Absorber Control through Skyhook Strategy in Semi-Active Suspension System (4DOF Model)

Active vibration isolation systems are less commonly used than passive systems due to their associated cost and power requirements. In principle, semi-active isolation systems can deliver the versatility, adaptability and higher performance of fully active systems for a fraction of the power consumption. Various semi-active control algorithms have been suggested in the past. This paper studies the 4DOF model of semi-active suspension performance controlled by on–off and continuous skyhook damping control strategy. The frequency and transient responses of model are evaluated in terms of body acceleration, roll angle and tire deflection and are compared with that of a passive damper. The results show that the semi-active system controlled by skyhook strategy always provides better isolation than a conventional passively damped system except at tire natural frequencies.

Pay Differentials and Employee Retention in the State Colleges of Education in the South-South Zone, Nigeria

The study examined the influence of pay differentials on employee retention in the State Colleges of Education in the South-South Region of Nigeria. 275 subjects drawn from members of the wage negotiating teams in the Colleges were administered questionnaires constructed for study. Analysis of Variance revealed that the observed pay differentials significantly influenced retainership, f(5,269 = 6.223, P< 0.05). However, the Multiple Classification Analysis and Post-Hoc test indicated that employees in two of the Colleges with slightly lower and higher pay levels may probably remain with their employers while employees in other Colleges with the least and highest pay levels suggested quitting. Based on these observations, the influence of pay on employee retention seems inconclusive. Generally, employees in the colleges studied are dissatisfied with current pay levels. Management should confront these challenges by improving pay packages to encourage employees to remain and be dedicated to duty.

Optimization of Unweighted Minimum Vertex Cover

The Minimum Vertex Cover (MVC) problem is a classic graph optimization NP - complete problem. In this paper a competent algorithm, called Vertex Support Algorithm (VSA), is designed to find the smallest vertex cover of a graph. The VSA is tested on a large number of random graphs and DIMACS benchmark graphs. Comparative study of this algorithm with the other existing methods has been carried out. Extensive simulation results show that the VSA can yield better solutions than other existing algorithms found in the literature for solving the minimum vertex cover problem.

Measuring Cognitive Load - A Solution to Ease Learning of Programming

Learning programming is difficult for many learners. Some researches have found that the main difficulty relates to cognitive load. Cognitive overload happens in programming due to the nature of the subject which is intrinisicly over-bearing on the working memory. It happens due to the complexity of the subject itself. The problem is made worse by the poor instructional design methodology used in the teaching and learning process. Various efforts have been proposed to reduce the cognitive load, e.g. visualization softwares, part-program method etc. Use of many computer based systems have also been tried to tackle the problem. However, little success has been made to alleviate the problem. More has to be done to overcome this hurdle. This research attempts at understanding how cognitive load can be managed so as to reduce the problem of overloading. We propose a mechanism to measure the cognitive load during pre instruction, post instruction and in instructional stages of learning. This mechanism is used to help the instruction. As the load changes the instruction is made to adapt itself to ensure cognitive viability. This mechanism could be incorporated as a sub domain in the student model of various computer based instructional systems to facilitate the learning of programming.

Flexible Wormhole-Switched Network-on-chip with Two-Level Priority Data Delivery Service

A synchronous network-on-chip using wormhole packet switching and supporting guaranteed-completion best-effort with low-priority (LP) and high-priority (HP) wormhole packet delivery service is presented in this paper. Both our proposed LP and HP message services deliver a good quality of service in term of lossless packet completion and in-order message data delivery. However, the LP message service does not guarantee minimal completion bound. The HP packets will absolutely use 100% bandwidth of their reserved links if the HP packets are injected from the source node with maximum injection. Hence, the service are suitable for small size messages (less than hundred bytes). Otherwise the other HP and LP messages, which require also the links, will experience relatively high latency depending on the size of the HP message. The LP packets are routed using a minimal adaptive routing, while the HP packets are routed using a non-minimal adaptive routing algorithm. Therefore, an additional 3-bit field, identifying the packet type, is introduced in their packet headers to classify and to determine the type of service committed to the packet. Our NoC prototypes have been also synthesized using a 180-nm CMOS standard-cell technology to evaluate the cost of implementing the combination of both services.