Designing of Virtual Laboratories Based on Extended Event Driving Simulation Method

Here are many methods for designing and implementation of virtual laboratories, because of their special features. The most famous architectural designs are based on the events. This model of architecting is so efficient for virtual laboratories implemented on a local network. Later, serviceoriented architecture, gave the remote access ability to them and Peer-To-Peer architecture, hired to exchanging data with higher quality and more speed. Other methods, such as Agent- Based architecting, are trying to solve the problems of distributed processing in a complicated laboratory system. This study, at first, reviews the general principles of designing a virtual laboratory, and then compares the different methods based on EDA, SOA and Agent-Based architecting to present weaknesses and strengths of each method. At the end, we make the best choice for design, based on existing conditions and requirements.

Developing and Implementing Successful Key Performance Indicators

Measurement and the following evaluation of performance represent important part of management. The paper focuses on indicators as the basic elements of performance measurement system. It emphasizes a necessity of searching requirements for quality indicators so that they can become part of the useful system. It introduces standpoints for a systematic dividing of indicators so that they have as high as possible informative value of background sources for searching, analysis, designing and using of indicators. It draws attention to requirements for indicators' quality and at the same it deals with some dangers decreasing indicator's informative value. It submits a draft of questions that should be answered at the construction of indicator. It is obvious that particular indicators need to be defined exactly to stimulate the desired behavior in order to attain expected results. In the enclosure a concrete example of the defined indicator in the concrete conditions of a small firm is given. The authors of the paper pay attention to the fact that a quality indicator makes it possible to get to the basic causes of the problem and include the established facts into the company information system. At the same time they emphasize that developing of a quality indicator is a prerequisite for the utilization of the system of measurement in management.

Measurement of UHF Signal Strength Propagating from Road Surface with Vehicle Obstruction

Radio wave propagation on the road surface is a major problem on wireless sensor network for traffic monitoring. In this paper, we compare receiving signal strength on two scenarios 1) an empty road and 2) a road with a vehicle. We investigate the effect of antenna polarization and antenna height to the receiving signal strength. The transmitting antenna is installed on the road surface. The receiving signal is measured 360 degrees around the transmitting antenna with the radius of 2.5 meters. Measurement results show the receiving signal fluctuation around the transmitting antenna in both scenarios. Receiving signal with vertical polarization antenna results in higher signal strength than horizontal polarization antenna. The optimum antenna elevation is 1 meter for both horizon and vertical polarizations with the vehicle on the road. In the empty road, the receiving signal level is unvarying with the elevation when the elevation is greater than 1.5 meters.

Study of Mordenite ZSM-5 and NaY Zeolites,Containing Cr, Cs, Zn, Ni, Co, Li, Mn, to Control Hydrocarbon Cold-Start Emission

The implementation of Super-Ultra Low Emission Vehicle standards requires more efficient exhaust gas purification. To increase the efficiency of exhaust gas purification, an the adsorbent capable of holding hydrocarbons up to 250-300 ОС should be developed. The possibility to design such adsorbents by modification of zeolites of mordenite type, ZSM-5 and NaY, using different metals cations has been studied. It has been shown that introducing Cr, Cs, Zn, Ni, Co, Li, Mn in zeolites results in modification of the toluene TPD and toluene sorption capacity. 5%LiZSM-5 zeolite exhibits the most attractive TPD curve, with toluene desorption temperature ranging from 250 to 350ОС. The sorption capacity of 5%Li-ZSM-5 is 0.4 mmol/g. NaY zeolite has the highest sorption capacity, up to 2 mmol/g, and holds toluene up to 350ОС, but at 120ОС toluene desorption starts, which is not desirable, since the adsorbent of cold start hydrocarbons should retain them until 250-300ОС. Therefore 5%LiZSM-5 zeolite was found to be the most promising to control the cold-start hydrocarbon emissions among the samples studied.

A Study of Visitors, on Service Quality, Satisfaction and Loyal in Ya Tam San Bikeway

The main purpose of this study is to analyze the feelings of tourists for the service quality of the bikeway. In addition, this study also analyzed the causal relationship between service quality and satisfaction to visitor-s lane loyalty. In this study, the Ya Tam San bikeway visitor-s subjects, using the designated convenience sampling carried out the survey, a total of 651 questionnaires were validly. Valid questionnaires after statistical analysis, the following findings: 1. Visitor-s lane highest quality of service project: the routes through the region weather pleasant. Lane "with health and sports," the highest satisfaction various factors of service quality and satisfaction, loyal between correlations exist. 4. Guided tours of bikeways, the quality of the environment, and modeling imagery can effectively predict visitor satisfaction. 5. Quality of bikeway, public facilities, guided tours, and modeling imagery can effectively predict visitor loyalty. According to the above results, the study not only makes recommendations to the government units and the bicycle industry, also asked the research direction for future researchers.

Formal Verification of a Multicast Protocol in Mobile Networks

As computer network technology becomes increasingly complex, it becomes necessary to place greater requirements on the validity of developing standards and the resulting technology. Communication networks are based on large amounts of protocols. The validity of these protocols have to be proved either individually or in an integral fashion. One strategy for achieving this is to apply the growing field of formal methods. Formal methods research defines systems in high order logic so that automated reasoning can be applied for verification. In this research we represent and implement a formerly announced multicast protocol in Prolog language so that certain properties of the protocol can be verified. It is shown that by using this approach some minor faults in the protocol were found and repaired. Describing the protocol as facts and rules also have other benefits i.e. leads to a process-able knowledge. This knowledge can be transferred as ontology between systems in KQML format. Since the Prolog language can increase its knowledge base every time, this method can also be used to learn an intelligent network.

Efficiency Improvements of GaAs-based Solar Cells by Hydrothermally-deposited ZnO Nanostructure Array

ZnO nanostructures including nanowires, nanorods, and nanoneedles were successfully deposited on GaAs substrates, respectively, by simple two-step chemical method for the first time. A ZnO seed layer was firstly pre-coated on the O2-plasma treated substrate by sol-gel process, followed by the nucleation of ZnO nanostructures through hydrothermal synthesis. Nanostructures with different average diameter (15-250 nm), length (0.9-1.8 μm), density (0.9-16×109 cm-2) were obtained via adjusting the growth time and concentration of precursors. From the reflectivity spectra, we concluded ordered and taper nanostructures were preferential for photovoltaic applications. ZnO nanoneedles with an average diameter of 106 nm, a moderate length of 2.4 μm, and the density of 7.2×109 cm-2 could be synthesized in the concentration of 0.04 M for 18 h. Integrated with the nanoneedle array, the power conversion efficiency of single junction solar cell was increased from 7.3 to 12.2%, corresponding to a 67% improvement.

Correlating Site-Specific Meteorological Data and Power Availability for Small-Scale, Multi-Source Renewable Energy Systems

The paper presents a modelling methodology for small scale multi-source renewable energy systems. Using historical site-specific weather data, the relationships of cost, availability and energy form are visualised as a function of the sizing of photovoltaic arrays, wind turbines, and battery capacity. The specific dependency of each site on its own particular weather patterns show that unique solutions exist for each site. It is shown that in certain cases the capital component cost can be halved if the desired theoretical demand availability is reduced from 100% to 99%.

Design, Analysis and Modeling of Dual Band Microstrip Loop Antenna Using Defective Ground Plane

Present wireless communication demands compact and intelligent devices with multitasking capabilities at affordable cost. The focus in the presented paper is on a dual band antenna for wireless communication with the capability of operating at two frequency bands with same structure. Two resonance frequencies are observed with the second operation band at 4.2GHz approximately three times the first resonance frequency at 1.5GHz. Structure is simple loop of microstrip line with characteristic impedance 50 ohms. The proposed antenna is designed using defective ground structure (DGS) and shows the nearly one third reductions in size as compared to without DGS. This antenna was simulated on electromagnetic (EM) simulation software and fabricated using microwave integrated circuit technique on RT-Duroid dielectric substrate (εr= 2.22) of thickness (H=15 mils). The designed antenna was tested on automatic network analyzer and shows the good agreement with simulated results. The proposed structure is modeled into an equivalent electrical circuit and simulated on circuit simulator. Subsequently, theoretical analysis was carried out and simulated. The simulated, measured, equivalent circuit response, and theoretical results shows good resemblance. The bands of operation draw many potential applications in today’s wireless communication.

Quantity and Quality Aware Artificial Bee Colony Algorithm for Clustering

Artificial Bee Colony (ABC) algorithm is a relatively new swarm intelligence technique for clustering. It produces higher quality clusters compared to other population-based algorithms but with poor energy efficiency, cluster quality consistency and typically slower in convergence speed. Inspired by energy saving foraging behavior of natural honey bees this paper presents a Quality and Quantity Aware Artificial Bee Colony (Q2ABC) algorithm to improve quality of cluster identification, energy efficiency and convergence speed of the original ABC. To evaluate the performance of Q2ABC algorithm, experiments were conducted on a suite of ten benchmark UCI datasets. The results demonstrate Q2ABC outperformed ABC and K-means algorithm in the quality of clusters delivered.

Exploring the Combinatorics of Motif Alignments Foraccurately Computing E-values from P-values

In biological and biomedical research motif finding tools are important in locating regulatory elements in DNA sequences. There are many such motif finding tools available, which often yield position weight matrices and significance indicators. These indicators, p-values and E-values, describe the likelihood that a motif alignment is generated by the background process, and the expected number of occurrences of the motif in the data set, respectively. The various tools often estimate these indicators differently, making them not directly comparable. One approach for comparing motifs from different tools, is computing the E-value as the product of the p-value and the number of possible alignments in the data set. In this paper we explore the combinatorics of the motif alignment models OOPS, ZOOPS, and ANR, and propose a generic algorithm for computing the number of possible combinations accurately. We also show that using the wrong alignment model can give E-values that significantly diverge from their true values.

Scene Adaptive Shadow Detection Algorithm

Robustness is one of the primary performance criteria for an Intelligent Video Surveillance (IVS) system. One of the key factors in enhancing the robustness of dynamic video analysis is,providing accurate and reliable means for shadow detection. If left undetected, shadow pixels may result in incorrect object tracking and classification, as it tends to distort localization and measurement information. Most of the algorithms proposed in literature are computationally expensive; some to the extent of equalling computational requirement of motion detection. In this paper, the homogeneity property of shadows is explored in a novel way for shadow detection. An adaptive division image (which highlights homogeneity property of shadows) analysis followed by a relatively simpler projection histogram analysis for penumbra suppression is the key novelty in our approach.

A Community Compromised Approach to Combinatorial Coalition Problem

Buyer coalition with a combination of items is a group of buyers joining together to purchase a combination of items with a larger discount. The primary aim of existing buyer coalition with a combination of items research is to generate a large total discount. However, the aim is hard to achieve because this research is based on the assumption that each buyer completely knows other buyers- information or at least one buyer knows other buyers- information in a coalition by exchange of information. These assumption contrast with the real world environment where buyers join a coalition with incomplete information, i.e., they concerned only with their expected discounts. Therefore, this paper proposes a new buyer community coalition formation with a combination of items scheme, called the Community Compromised Combinatorial Coalition scheme, under such an environment of incomplete information. In order to generate a larger total discount, after buyers who want to join a coalition propose their minimum required saving, a coalition structure that gives a maximum total retail prices is formed. Then, the total discount division of the coalition is divided among buyers in the coalition depending on their minimum required saving and is a Pareto optimal. In mathematical analysis, we compare concepts of this scheme with concepts of the existing buyer coalition scheme. Our mathematical analysis results show that the total discount of the coalition in this scheme is larger than that in the existing buyer coalition scheme.

Modeling, Simulation and Monitoring of Nuclear Reactor Using Directed Graph and Bond Graph

The main objective developed in this paper is to find a graphic technique for modeling, simulation and diagnosis of the industrial systems. This importance is much apparent when it is about a complex system such as the nuclear reactor with pressurized water of several form with various several non-linearity and time scales. In this case the analytical approach is heavy and does not give a fast idea on the evolution of the system. The tool Bond Graph enabled us to transform the analytical model into graphic model and the software of simulation SYMBOLS 2000 specific to the Bond Graphs made it possible to validate and have the results given by the technical specifications. We introduce the analysis of the problem involved in the faults localization and identification in the complex industrial processes. We propose a method of fault detection applied to the diagnosis and to determine the gravity of a detected fault. We show the possibilities of application of the new diagnosis approaches to the complex system control. The industrial systems became increasingly complex with the faults diagnosis procedures in the physical systems prove to become very complex as soon as the systems considered are not elementary any more. Indeed, in front of this complexity, we chose to make recourse to Fault Detection and Isolation method (FDI) by the analysis of the problem of its control and to conceive a reliable system of diagnosis making it possible to apprehend the complex dynamic systems spatially distributed applied to the standard pressurized water nuclear reactor.

Computational Method for Annotation of Protein Sequence According to Gene Ontology Terms

Annotation of a protein sequence is pivotal for the understanding of its function. Accuracy of manual annotation provided by curators is still questionable by having lesser evidence strength and yet a hard task and time consuming. A number of computational methods including tools have been developed to tackle this challenging task. However, they require high-cost hardware, are difficult to be setup by the bioscientists, or depend on time intensive and blind sequence similarity search like Basic Local Alignment Search Tool. This paper introduces a new method of assigning highly correlated Gene Ontology terms of annotated protein sequences to partially annotated or newly discovered protein sequences. This method is fully based on Gene Ontology data and annotations. Two problems had been identified to achieve this method. The first problem relates to splitting the single monolithic Gene Ontology RDF/XML file into a set of smaller files that can be easy to assess and process. Thus, these files can be enriched with protein sequences and Inferred from Electronic Annotation evidence associations. The second problem involves searching for a set of semantically similar Gene Ontology terms to a given query. The details of macro and micro problems involved and their solutions including objective of this study are described. This paper also describes the protein sequence annotation and the Gene Ontology. The methodology of this study and Gene Ontology based protein sequence annotation tool namely extended UTMGO is presented. Furthermore, its basic version which is a Gene Ontology browser that is based on semantic similarity search is also introduced.

Performance Optimization of Data Mining Application Using Radial Basis Function Classifier

Text data mining is a process of exploratory data analysis. Classification maps data into predefined groups or classes. It is often referred to as supervised learning because the classes are determined before examining the data. This paper describes proposed radial basis function Classifier that performs comparative crossvalidation for existing radial basis function Classifier. The feasibility and the benefits of the proposed approach are demonstrated by means of data mining problem: direct Marketing. Direct marketing has become an important application field of data mining. Comparative Cross-validation involves estimation of accuracy by either stratified k-fold cross-validation or equivalent repeated random subsampling. While the proposed method may have high bias; its performance (accuracy estimation in our case) may be poor due to high variance. Thus the accuracy with proposed radial basis function Classifier was less than with the existing radial basis function Classifier. However there is smaller the improvement in runtime and larger improvement in precision and recall. In the proposed method Classification accuracy and prediction accuracy are determined where the prediction accuracy is comparatively high.

A Fair Non-transfer Exchange Protocol

Network exchange is now widely used. However, it still cannot avoid the problems evolving from network exchange. For example. A buyer may not receive the order even if he/she makes the payment. For another example, the seller possibly get nothing even when the merchandise is sent. Some studies about the fair exchange have proposed protocols for the design of efficiency and exploited the signature property to specify that two parties agree on the exchange. The information about purchased item and price are disclosed in this way. This paper proposes a new fair network payment protocol with off-line trusted third party. The proposed protocol can protect the buyers- purchase message from being traced. In addition, the proposed protocol can meet the proposed requirements. The most significant feature is Non-transfer property we achieved.

University Students Awareness on M-Learning

Mobile learning (M-learning) is the current technology that is becoming more popular. It uses the current mobile and wireless computing technology to complement the effectiveness of traditional learning process. The objective of this paper is presents a survey from 90 undergraduate students of Universiti Teknologi PETRONAS (UTP), to identify the students- perception on Mlearning. From the results, the students are willing to use M-learning. The acceptance level of the students is high, and the results obtained revealed that the respondents almost accept M-learning as one method of teaching and learning process and also able to improve the educational efficiency by complementing traditional learning in UTP.

A Feasibility-study of a Micro- Communications Sonobuoy Deployable by UAV Robots

This paper describes a feasibility study that is included with the research, development and testing of a micro communications sonobuoy deployable by Maritime Fixed wing Unmanned Aerial Vehicles (M-UAV) and rotor wing Quad Copters which are both currently being developed by the University of Adelaide. The micro communications sonobuoy is developed to act as a seamless communication relay between an Autonomous Underwater Vehicle (AUV) and an above water human operator some distance away. Development of such a device would eliminate the requirement of physical communication tethers attached to submersible vehicles for control and data retrieval.

Transmitting a Distance Training Model to the Community in the Upper Northeastern Region

The objective of this research seeks to transmit a distance training model to the community in the upper northeastern region. The group sampling consists of 60 community leaders in the municipality of sub-district Kumphawapi, Kumphawapi Disrict, Udonthani Province. The research tools rely on the following instruments, they are : 1) the achievement test of community leaders- training and 2) the satisfaction questionnaires of community leaders. The statistics used in data analysis takes the statistical mean, percentage, standard deviation, and statistical T-test. The resulted findings reveal : 1) the efficiency of the distance training developed by the researcher for the community leaders joining in the training received the average score between in-training and post-training period higher than the setup criterion, 2) the two groups of participants in the training achieved higher knowledge than their pre-training state, 3) the comparison of the achievements between the two group presented no different results, 4) the community leaders obtained the high-to-highest satisfaction.