Auto-Parking System via Intelligent Computation Intelligence

In this paper, an intelligent automatic parking control method is proposed. First, the dynamical equation of the rear parking control is derived. Then a fuzzy logic control is proposed to perform the parking planning process. Further, a rear neural network is proposed for the steering control. Through the simulations and experiments, the intelligent auto-parking mode controllers have been shown to achieve the demanded goals with satisfactory control performance and to guarantee the system robustness under parametric variations and external disturbances. To improve some shortcomings and limitations in conventional parking mode control and further to reduce consumption time and prime cost.

Approaches and Schemes for Storing DTDIndependent XML Data in Relational Databases

The volume of XML data exchange is explosively increasing, and the need for efficient mechanisms of XML data management is vital. Many XML storage models have been proposed for storing XML DTD-independent documents in relational database systems. Benchmarking is the best way to highlight pros and cons of different approaches. In this study, we use a common benchmarking scheme, known as XMark to compare the most cited and newly proposed DTD-independent methods in terms of logical reads, physical I/O, CPU time and duration. We show the effect of Label Path, extracting values and storing in another table and type of join needed for each method-s query answering.

An MCDM Approach to Selection Scheduling Rule in Robotic Flexibe Assembly Cells

Multiple criteria decision making (MCDM) is an approach to ranking the solutions and finding the best one when two or more solutions are provided. In this study, MCDM approach is proposed to select the most suitable scheduling rule of robotic flexible assembly cells (RFACs). Two MCDM approaches, Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are proposed for solving the scheduling rule selection problem. The AHP method is employed to determine the weights of the evaluation criteria, while the TOPSIS method is employed to obtain final ranking order of scheduling rules. Four criteria are used to evaluate the scheduling rules. Also, four scheduling policies of RFAC are examined to choose the most appropriate one for this purpose. A numerical example illustrates applications of the suggested methodology. The results show that the methodology is practical and works in RFAC settings.

An Augmented Automatic Choosing Control with Constrained Input Using Weighted Gradient Optimization Automatic Choosing Functions

In this paper we consider a nonlinear feedback control called augmented automatic choosing control (AACC) for nonlinear systems with constrained input using weighted gradient optimization automatic choosing functions. Constant term which arises from linearization of a given nonlinear system is treated as a coefficient of a stable zero dynamics. Parameters of the control are suboptimally selected by maximizing the stable region in the sense of Lyapunov with the aid of a genetic algorithm. This approach is applied to a field excitation control problem of power system to demonstrate the splendidness of the AACC. Simulation results show that the new controller can improve performance remarkably well.

Simulated Annealing Application for Structural Optimization

Several methods are available for weight and shape optimization of structures, among which Evolutionary Structural Optimization (ESO) is one of the most widely used methods. In ESO, however, the optimization criterion is completely case-dependent. Moreover, only the improving solutions are accepted during the search. In this paper a Simulated Annealing (SA) algorithm is used for structural optimization problem. This algorithm differs from other random search methods by accepting non-improving solutions. The implementation of SA algorithm is done through reducing the number of finite element analyses (function evaluations). Computational results show that SA can efficiently and effectively solve such optimization problems within short search time.

System Identification with General Dynamic Neural Networks and Network Pruning

This paper presents an exact pruning algorithm with adaptive pruning interval for general dynamic neural networks (GDNN). GDNNs are artificial neural networks with internal dynamics. All layers have feedback connections with time delays to the same and to all other layers. The structure of the plant is unknown, so the identification process is started with a larger network architecture than necessary. During parameter optimization with the Levenberg- Marquardt (LM) algorithm irrelevant weights of the dynamic neural network are deleted in order to find a model for the plant as simple as possible. The weights to be pruned are found by direct evaluation of the training data within a sliding time window. The influence of pruning on the identification system depends on the network architecture at pruning time and the selected weight to be deleted. As the architecture of the model is changed drastically during the identification and pruning process, it is suggested to adapt the pruning interval online. Two system identification examples show the architecture selection ability of the proposed pruning approach.

Framework of TAZ_OPT Model for Ambulance Location and Allocation Problem

Our study is concerned with the development of an Emergency Medical Services (EMS) ambulance location and allocation model called the Time-based Ambulance Zoning Optimization Model (TAZ_OPT). This paper presents the framework of the study. The model is formulated using the goal programming (GP), where the goals are to determine the satellite locations of ambulances and the number of ambulances to be allocated at these locations. The model aims at maximizing the expected demand coverage based on probability of reaching the emergency location within targetted time, and minimizing the ambulance busyness likelihood value. Among the benefits of the model is the increased accessibility and availability of ambulances, thus, enhanced quality of the EMS ambulance services.

New Multipath Node-Disjoint Routing Based on AODV Protocol

Today, node-disjoint routing becomes inessential technique in communication of packets among various nodes in networks. Meanwhile AODV (Ad Hoc On-demand Multipath Distance Vector) creates single-path route between a pair of source and destination nodes. Some researches has done so far to make multipath node-disjoint routing based on AODV protocol. But however their overhead and end-to-end delay are relatively high, while the detail of their code is not available too. This paper proposes a new approach of multipath node-disjoint routing based on AODV protocol. Then the algorithm of analytical model is presented. The extensive results of this algorithm will be presented in the next paper.

Learning Paradigms for Educating a New Generation of Computer Science Students

In this paper challenges associated with a new generation of Computer Science students are examined. The mode of education in tertiary institutes has progressed slowly while the needs of students have changed rapidly in an increasingly technological world. The major learning paradigms and learning theories within these paradigms are studied to find a suitable strategy for educating modern students. These paradigms include Behaviourism, Constructivism, Humanism and Cogntivism. Social Learning theory and Elaboration theory are two theories that are further examined and a survey is done to determine how these strategies will be received by students. The results and findings are evaluated and indicate that students are fairly receptive to a method that incorporates both Social Learning theory and Elaboration theory, but that some aspects of all paradigms need to be implemented to create a balanced and effective strategy with technology as foundation.

Making Businesses Work Smarter with Mobile Business Intelligence

Through the course of this paper we outline how mobile Business Intelligence (m-BI) can help businesses to work smarter and to improve their agility. When we analyze the industry from the usage perspective or how interaction with the enterprise BI system happens via mobile devices, we may easily understand that there are two major types of mobile BI: passive and active. Active mobile BI gives provisions for users to interact with the BI systems on-the-fly. Active mobile business intelligence often works as a combination of both “push and pull" techniques. Some mistakes were done in the up-to-day progress of mobile technologies and mobile BI, as well as some problems that still have to be resolved. We discussed in the paper rather broadly.

Comparison of Evolutionary Algorithms and their Hybrids Applied to MarioAI

Researchers have been applying artificial/ computational intelligence (AI/CI) methods to computer games. In this research field, further researchesare required to compare AI/CI methods with respect to each game application. In thispaper, we report our experimental result on the comparison of evolution strategy, genetic algorithm and their hybrids, applied to evolving controller agents for MarioAI. GA revealed its advantage in our experiment, whereas the expected ability of ES in exploiting (fine-tuning) solutions was not clearly observed. The blend crossover operator and the mutation operator of GA might contribute well to explore the vast search space.

Bangla Vowel Characterization Based on Analysis by Synthesis

Bangla Vowel characterization determines the spectral properties of Bangla vowels for efficient synthesis as well as recognition of Bangla vowels. In this paper, Bangla vowels in isolated word have been analyzed based on speech production model within the framework of Analysis-by-Synthesis. This has led to the extraction of spectral parameters for the production model in order to produce different Bangla vowel sounds. The real and synthetic spectra are compared and a weighted square error has been computed along with the error in the formant bandwidths for efficient representation of Bangla vowels. The extracted features produced good representation of targeted Bangla vowel. Such a representation also plays essential role in low bit rate speech coding and vocoders.

A Markov Chain Approximation for ATS Modeling for the Variable Sampling Interval CCC Control Charts

The cumulative conformance count (CCC) charts are widespread in process monitoring of high-yield manufacturing. Recently, it is found the use of variable sampling interval (VSI) scheme could further enhance the efficiency of the standard CCC charts. The average time to signal (ATS) a shift in defect rate has become traditional measure of efficiency of a chart with the VSI scheme. Determining the ATS is frequently a difficult and tedious task. A simple method based on a finite Markov Chain approach for modeling the ATS is developed. In addition, numerical results are given.

Measuring Teachers- Beliefs about Mathematics: A Fuzzy Set Approach

This paper deals with the application of a fuzzy set in measuring teachers- beliefs about mathematics. The vagueness of beliefs was transformed into standard mathematical values using a fuzzy preferences model. The study employed a fuzzy approach questionnaire which consists of six attributes for measuring mathematics teachers- beliefs about mathematics. The fuzzy conjoint analysis approach based on fuzzy set theory was used to analyze the data from twenty three mathematics teachers from four secondary schools in Terengganu, Malaysia. Teachers- beliefs were recorded in form of degrees of similarity and its levels of agreement. The attribute 'Drills and practice is one of the best ways of learning mathematics' scored the highest degree of similarity at 0. 79860 with level of 'strongly agree'. The results showed that the teachers- beliefs about mathematics were varied. This is shown by different levels of agreement and degrees of similarity of the measured attributes.

Applications of High-Order Compact Finite Difference Scheme to Nonlinear Goursat Problems

Several numerical schemes utilizing central difference approximations have been developed to solve the Goursat problem. However, in a recent years compact discretization methods which leads to high-order finite difference schemes have been used since it is capable of achieving better accuracy as well as preserving certain features of the equation e.g. linearity. The basic idea of the new scheme is to find the compact approximations to the derivative terms by differentiating centrally the governing equations. Our primary interest is to study the performance of the new scheme when applied to two Goursat partial differential equations against the traditional finite difference scheme.

Factors Influencing the Success of Mobile Phone Entrepreneurs at Central Plaza

The purpose of this research was to study the factors that influenced the success of mobile phone entrepreneurs at Central Plaza. The sample group included 187 entrepreneurs at Central Plaza. A questionnaire was utilized as a tool to collect data. Statistics used in this research included frequency, percentage, mean, and standard deviation. Independent- sample t- test, one way ANOVA, and multiple regression analysis. Data were analyzed by using Statistical Package for the Social Sciences.The findings disclosed that the majority of respondents were male between 25-40 years old, and held an undergraduate degree. The average income of respondents was between 15,001-25,000 baht. The majority of respondents had less than 5 years of working experience. In terms of personality, the findings revealed that expression and agreement were ranked at the highest level. Whereas, emotion stability, consciousness, open to new experience were ranked at high. From the hypotheses testing, the findings revealed that different genders had different success in their mobile phone business with different income from the last 6 months. However, difference in age, income, level of education, and experience affected the success in terms of income, number of customers, and overall success of business. Moreover, the factors of personalities included expression, agreement, emotion stability, consciousness, open to new experience, and competitive strategy. From the findings, these factors were able to predict mobile phone business success at 66.9 percent.

Chemical Compositions and Physico-Chemical Properties of Malted Sorghum Flour and Characteristics of Gluten Free Bread

This study investigated the effect of germination on chemical compositions, physio-chemical properties of malted (germinated) red sorghum flours and evaluated characteristics of gluten free breads from sorghum flour. Results showed that germinated sorghum flour had higher amylase activity, swelling power and solubility at 95°C, but lower in the peak, break down, final and set back viscosities than ungerminated sample (p≤0.05). Five gluten free breads made from sorghum flour blends, with different ratios of ungerminated and germinated sorghum flour, were compared for the physical properties with those made from wheat flour. Crumb hardness, cohesiveness, gumminess and chewiness of sorghum breads were found significantly higher than those of wheat bread. With increasing of ungerminated flour proportion, the bread hardness increased while the cohesiveness declined. Sorghum breads appeared red to human eyes with a*values of 10.41-15.77.Their crust and crumb colors differed significantly from those of wheat bread.

The Biomechanical Properties of the Different Modalities of Surgically Corrected Coarctation of the Aorta in Neonates and Infants

Biomechanical properties of infantile aorta in vitro in cases of different standard anastomoses: end-to-end (ETE), extended anastomosis end-to-end (EETE) and subclavian flap aortoplasty (SFA) used for surgical correction of coarctation were analyzed to detect the influence of the method on the biomechanics of infantile aorta and possible changes in haemodinamics. 10 specimens of native aorta, 3 specimens with ETE, 4 EEET and 3 SFA were investigated. The experiments showed a non-linear relationship between stress and strain in the infantile aorta, the modulus of elasticity of the aortic wall increased with the increase of inner pressure. In the case of anastomosis end-to-end the modulus was almost constant, relevant to the modulus of elasticity of the aorta with the inner pressure 100-120 mmHg. The anastomoses EETE and SFA showed elastic properties closer to native aorta, the stiffness of ETE did not change with the changes in inner pressure.

Application of Adaptive Network-Based Fuzzy Inference System in Macroeconomic Variables Forecasting

In this paper we apply an Adaptive Network-Based Fuzzy Inference System (ANFIS) with one input, the dependent variable with one lag, for the forecasting of four macroeconomic variables of US economy, the Gross Domestic Product, the inflation rate, six monthly treasury bills interest rates and unemployment rate. We compare the forecasting performance of ANFIS with those of the widely used linear autoregressive and nonlinear smoothing transition autoregressive (STAR) models. The results are greatly in favour of ANFIS indicating that is an effective tool for macroeconomic forecasting used in academic research and in research and application by the governmental and other institutions

Histogenesis of Rabbit Vallate Papillae

The gustatory system allows animals to distinguish varieties of food and affects greatly the consumption of food, hence the health and growth of animals. In the current study, we investigated the histogenesis of vallate papillae (VLP) in the rabbit tongue using light and scanning electron microscopy. Samples were obtained from rabbit embryos at the embryonic days 16-30 (E16-30), and from newborns until maturity; 6 months. At E16, the first primordia of vallate papillae were observed as small pits on the surface epithelium of the tongue-s root. At E18, the caudal part was prominent with loose mesenchymal tissue core; meanwhile the rostral part of the papilla was remained as a thick mass of epithelial cells. At E20-24, the side epithelium formed the primitive annular groove. At E26, the primitive taste buds appeared only at the papillary surface and reached their maturity by E28. The annular groove started to appear at E26 became more defined at E28. The definitive vallate papillae with substantial number of apparently mature taste buds were observed by the end of the second week. We conclude that the vallate papillae develop early and mature during the early postnatal life.