A Specification-Based Approach for Retrieval of Reusable Business Component for Software Reuse

Software reuse can be considered as the most realistic and promising way to improve software engineering productivity and quality. Automated assistance for software reuse involves the representation, classification, retrieval and adaptation of components. The representation and retrieval of components are important to software reuse in Component-Based on Software Development (CBSD). However, current industrial component models mainly focus on the implement techniques and ignore the semantic information about component, so it is difficult to retrieve the components that satisfy user-s requirements. This paper presents a method of business component retrieval based on specification matching to solve the software reuse of enterprise information system. First, a business component model oriented reuse is proposed. In our model, the business data type is represented as sign data type based on XML, which can express the variable business data type that can describe the variety of business operations. Based on this model, we propose specification match relationships in two levels: business operation level and business component level. In business operation level, we use input business data types, output business data types and the taxonomy of business operations evaluate the similarity between business operations. In the business component level, we propose five specification matches between business components. To retrieval reusable business components, we propose the measure of similarity degrees to calculate the similarities between business components. Finally, a business component retrieval command like SQL is proposed to help user to retrieve approximate business components from component repository.

A High-Speed and Low-Energy Ternary Content Addressable Memory Design Using Feedback in Match-Line Sense Amplifier

In this paper we present an energy efficient match-line (ML) sensing scheme for high-speed ternary content-addressable memory (TCAM). The proposed scheme isolates the sensing unit of the sense amplifier from the large and variable ML capacitance. It employs feedback in the sense amplifier to successfully detect a match while keeping the ML voltage swing low. This reduced voltage swing results in large energy saving. Simulation performed using 130nm 1.2V CMOS logic shows at least 30% total energy saving in our scheme compared to popular current race (CR) scheme for similar search speed. In terms of speed, dynamic energy, peak power consumption and transistor count our scheme also shows better performance than mismatch-dependant (MD) power allocation technique which also employs feedback in the sense amplifier. Additionally, the implementation of our scheme is simpler than CR or MD scheme because of absence of analog control voltage and programmable delay circuit as have been used in those schemes.

Effect of Cladding and Secondary Members on the Elastic Stability of Main Columns

The corrugated steel cladding used to cover most of steel buildings is considered as non-structural element. This research will reflect the effect of cladding as a shear diaphragm in increasing the normal elastic capacity of columns. This study is important because of the lack of information of the behavior of cladding and secondary members in various codes. Mathematical models for six different cases are carried by software. The results extracted from the program have been plotted showing the effects of different variables on the ultimate load of column. The variables considered in our research are the spacing between columns and the thickness of the corrugated sheet representing the sheet stiffness.

An Alternative Method for Generating Almost Infinite Sequence of Gaussian Variables

Most of the well known methods for generating Gaussian variables require at least one standard uniform distributed value, for each Gaussian variable generated. The length of the random number generator therefore, limits the number of independent Gaussian distributed variables that can be generated meanwhile the statistical solution of complex systems requires a large number of random numbers for their statistical analysis. We propose an alternative simple method of generating almost infinite number of Gaussian distributed variables using a limited number of standard uniform distributed random numbers.

Analytical Modelling of Average Bond Stress within the Anchorage of Tensile Reinforcing Bars in Reinforced Concrete Members

A reliable estimate of the average bond stress within the anchorage of steel reinforcing bars in tension is critically important for the design of reinforced concrete member. This paper describes part of a recently completed experimental research program in the Centre for Infrastructure Engineering and Safety (CIES) at the University of New South Wales, Sydney, Australia aimed at assessing the effects of different factors on the anchorage requirements of modern high strength steel reinforcing bars. The study found that an increase in the anchorage length and bar diameter generally leads to a reduction of the average ultimate bond stress. By the extension of a well established analytical model of bond and anchorage, it is shown here that the differences in the average ultimate bond stress for different anchorage lengths is associated with the variable degree of plastic deformation in the tensile zone of the concrete surrounding the bar.

ORank: An Ontology Based System for Ranking Documents

Increasing growth of information volume in the internet causes an increasing need to develop new (semi)automatic methods for retrieval of documents and ranking them according to their relevance to the user query. In this paper, after a brief review on ranking models, a new ontology based approach for ranking HTML documents is proposed and evaluated in various circumstances. Our approach is a combination of conceptual, statistical and linguistic methods. This combination reserves the precision of ranking without loosing the speed. Our approach exploits natural language processing techniques for extracting phrases and stemming words. Then an ontology based conceptual method will be used to annotate documents and expand the query. To expand a query the spread activation algorithm is improved so that the expansion can be done in various aspects. The annotated documents and the expanded query will be processed to compute the relevance degree exploiting statistical methods. The outstanding features of our approach are (1) combining conceptual, statistical and linguistic features of documents, (2) expanding the query with its related concepts before comparing to documents, (3) extracting and using both words and phrases to compute relevance degree, (4) improving the spread activation algorithm to do the expansion based on weighted combination of different conceptual relationships and (5) allowing variable document vector dimensions. A ranking system called ORank is developed to implement and test the proposed model. The test results will be included at the end of the paper.

Dynamic Visualization on Student's Performance, Retention and Transfer of Procedural Learning

This study examined the effects of two dynamic visualizations on 60 Malaysian primary school student-s performance (time on task), retention and transference. The independent variables in this study were the two dynamic visualizations, the video and the animated instructions. The dependent variables were the gain score of performance, retention and transference. The results showed that the students in the animation group significantly outperformed the students in the video group in retention. There were no significant differences in terms of gain scores in the performance and transference among the animation and the video groups, although the scores were slightly higher in the animation group compared to the video group. The conclusion of this study is that the animation visualization is superior compared to the video in the retention for a procedural task.

Dynamics of Phytoplankton Blooms in the Baltic Sea – Numerical Simulations

Dynamic of phytoplankton blooms in the Baltic Sea has been analyzed applying the numerical ecosystem model 3D CEMBS. The model consists of the hydrodynamic model (POP, version 2.1) and the ice model (CICE, version 4.0), which are imposed by the atmospheric data model (DATM7). The 3D model has an ecosystem module, activated in 2012 in the operational mode. The ecosystem model consists of 11 main variables: biomass of small-size phytoplankton and large-size phytoplankton and cyanobacteria, zooplankton biomass, dissolved and molecular detritus, dissolved oxygen concentration, as well as concentrations of nutrients, including: nitrates, ammonia, phosphates and silicates. The 3D-CEMBS model is an effective tool for solving problems related to phytoplankton blooms dynamic in the Baltic Sea

Affine Radial Basis Function Neural Networks for the Robust Control of Hyperbolic Distributed Parameter Systems

In this work, a radial basis function (RBF) neural network is developed for the identification of hyperbolic distributed parameter systems (DPSs). This empirical model is based only on process input-output data and used for the estimation of the controlled variables at specific locations, without the need of online solution of partial differential equations (PDEs). The nonlinear model that is obtained is suitably transformed to a nonlinear state space formulation that also takes into account the model mismatch. A stable robust control law is implemented for the attenuation of external disturbances. The proposed identification and control methodology is applied on a long duct, a common component of thermal systems, for a flow based control of temperature distribution. The closed loop performance is significantly improved in comparison to existing control methodologies.

Tourist Awareness of Environmental and Recreational Behaviors at the Guandu Wetland, North Taiwan

The aim of this study is to discuss the relationship between tourist awareness of environmental issues and their own recreational behaviors in the Taipei Guandu Wetland. A total of 392 questionnaires were gathered for data analysis using descriptive statistics, t-testing, one-way analysis of variance (ANOVA) and least significant difference (LSD) post hoc comparisons. The results showed that most of the visitors there enjoying the beautiful scenery are 21 to 30 years old with a college education. The means and standard deviations indicate that tourists express a positive degree of cognition of environmental issues and recreational behaviors. They suggest that polluting the environment is harmful to the natural ecosystem and that the natural resources of ecotourism are fragile, as well as expressing a high degree of recognition of the need to protect wetlands. Most of respondents are cognizant of the regulations proposed by the Guandu Wetland administration which asks that users exercise self-control and follow recommended guidelines when traveling the wetland. There were significant differences in the degree of cognition related to the variables of age, number of visits and reasons for visiting. We found that most respondents with relatively high levels of education would like to learn more about the wetland and are supportive of its conservation.

Info-participation of the Disabled Using the Mixed Preference Data in Improving Their Travel Quality

Today, the preferences and participation of the TD groups such as the elderly and disabled is still lacking in decision-making of transportation planning, and their reactions to certain type of policies are not well known. Thus, a clear methodology is needed. This study aimed to develop a method to extract the preferences of the disabled to be used in the policy-making stage that can also guide to future estimations. The method utilizes the combination of cluster analysis and data filtering using the data of the Arao city (Japan). The method is a process that follows: defining the TD group by the cluster analysis tool, their travel preferences in tabular form from the household surveys by policy variableimpact pairs, zones, and by trip purposes, and the final outcome is the preference probabilities of the disabled. The preferences vary by trip purpose; for the work trips, accessibility and transit system quality policies with the accompanying impacts of modal shifts towards public mode use as well as the decreasing travel costs, and the trip rate increase; for the social trips, the same accessibility and transit system policies leading to the same mode shift impact, together with the travel quality policy area leading to trip rate increase. These results explain the policies to focus and can be used in scenario generation in models, or any other planning purpose as decision support tool.

Mobile Robot Path Planning in a 2-Dimentional Mesh

A topologically oriented neural network is very efficient for real-time path planning for a mobile robot in changing environments. When using a recurrent neural network for this purpose and with the combination of the partial differential equation of heat transfer and the distributed potential concept of the network, the problem of obstacle avoidance of trajectory planning for a moving robot can be efficiently solved. The related dimensional network represents the state variables and the topology of the robot's working space. In this paper two approaches to problem solution are proposed. The first approach relies on the potential distribution of attraction distributed around the moving target, acting as a unique local extreme in the net, with the gradient of the state variables directing the current flow toward the source of the potential heat. The second approach considers two attractive and repulsive potential sources to decrease the time of potential distribution. Computer simulations have been carried out to interrogate the performance of the proposed approaches.

Sensorless Sliding Power Control of Doubly Fed Induction Wind Generator Based on MRAS Observer

In this paper present a sensorless maximum wind power extraction for variable speed constant frequency (VSCF) wind power generation systems with a doubly-fed induction generators (DFIG), to ensure stability and to impose the ideal feedback control solution despite of model uncertainties , using the principles of an active and reactive power controller (DPC) a robust sliding mode power control has been proposed to guarantees fast response times and precise control actions for control the active and reactive power independently. The simulation results in MATLAB/Simulink platform confirmed the good dynamic performance of power control approach for DFIGbased variable speed wind turbines.

Feasibility of the Evolutionary Algorithm using Different Behaviours of the Mutation Rate to Design Simple Digital Logic Circuits

The evolutionary design of electronic circuits, or evolvable hardware, is a discipline that allows the user to automatically obtain the desired circuit design. The circuit configuration is under the control of evolutionary algorithms. Several researchers have used evolvable hardware to design electrical circuits. Every time that one particular algorithm is selected to carry out the evolution, it is necessary that all its parameters, such as mutation rate, population size, selection mechanisms etc. are tuned in order to achieve the best results during the evolution process. This paper investigates the abilities of evolution strategy to evolve digital logic circuits based on programmable logic array structures when different mutation rates are used. Several mutation rates (fixed and variable) are analyzed and compared with each other to outline the most appropriate choice to be used during the evolution of combinational logic circuits. The experimental results outlined in this paper are important as they could be used by every researcher who might need to use the evolutionary algorithm to design digital logic circuits.

Synchronization of Non-Identical Chaotic Systems with Different Orders Based On Vector Norms Approach

A new strategy of control is formulated for chaos synchronization of non-identical chaotic systems with different orders using the Borne and Gentina practical criterion associated with the Benrejeb canonical arrow form matrix, to drift the stability property of dynamic complex systems. The designed controller ensures that the state variables of controlled chaotic slave systems globally synchronize with the state variables of the master systems, respectively. Numerical simulations are performed to illustrate the efficiency of the proposed method.

Real-Time Specific Weed Recognition System Using Histogram Analysis

Information on weed distribution within the field is necessary to implement spatially variable herbicide application. Since hand labor is costly, an automated weed control system could be feasible. This paper deals with the development of an algorithm for real time specific weed recognition system based on Histogram Analysis of an image that is used for the weed classification. This algorithm is specifically developed to classify images into broad and narrow class for real-time selective herbicide application. The developed system has been tested on weeds in the lab, which have shown that the system to be very effectiveness in weed identification. Further the results show a very reliable performance on images of weeds taken under varying field conditions. The analysis of the results shows over 95 percent classification accuracy over 140 sample images (broad and narrow) with 70 samples from each category of weeds.

U.S. Supreme Court Decision Making in the Area of Religion, 1987-2011

There are many views on how human decision makers behave. In this work, the Justices of the United States Supreme Court will be viewed in terms of constrained maximization and cognitivecybernetic theory. This paper will integrate research in such fields as law, political science, psychology, economics and decision making theory. It will be argued that due to its heavy workload, the Supreme Court is forced to make decisions in a boundedly rational manner. The ideas and theory put forward here will be tested in the area of the Court’s decisions involving religion. Therefore, the cases involving the U.S. Constitution’s Free Exercise Clause and Establishment Clause will be analyzed. Also, variables such as the U.S. government’s involvement in these cases will be considered. The years to be studied will be 1987-2011.

Adoptability Issues of GPS in Public Sector in Pakistan

This study discusses the stumbling blocks stifling the adoption of GPS technology in the public sector of Pakistan. This study has been carried out in order to describe the value of GPS technology and its adoption at various public sector organisations in Pakistan. Sample size for the research conducted was 200; personnel working in public sector having age above 29 years were surveyed. Data collected for this research has been quantitatively analysed with the help of SPSS. Regression analysis, correlation and cross tabulation were the techniques used to determine the strength of relationship between key variables. Findings of this research indicate that main hurdles in GPS adoption in the public sector of Pakistan are lack of awareness about GPS among masses in general and the stakeholders in particular, lack of initiative on part of government in promoting new technologies, unavailability of GPS infrastructure in Pakistan and prohibitions on map availability because of security reasons.

Variable Rough Set Model and Its Knowledge Reduction for Incomplete and Fuzzy Decision Information Systems

The information systems with incomplete attribute values and fuzzy decisions commonly exist in practical problems. On the base of the notion of variable precision rough set model for incomplete information system and the rough set model for incomplete and fuzzy decision information system, the variable rough set model for incomplete and fuzzy decision information system is constructed, which is the generalization of the variable precision rough set model for incomplete information system and that of rough set model for incomplete and fuzzy decision information system. The knowledge reduction and heuristic algorithm, built on the method and theory of precision reduction, are proposed.

Regret, Choice, and Outcome

In two studies we challenged the well consolidated position in regret literature according to which the necessary condition for the emergence of regret is a bad outcome ensuing from free decisions. Without free choice, and, consequently, personal responsibility, other emotions, such as disappointment, but not regret, are supposed to be elicited. In our opinion, a main source of regret is being obliged by circumstance out of our control to chose an undesired option. We tested the hypothesis that regret resulting from a forced choice is more intense than regret derived from a free choice and that the outcome affects the latter, not the former. Besides, we investigated whether two other variables – the perception of the level of freedom of the choice and the choice justifiability – mediated the relationships between choice and regret, as well as the other four emotions we examined: satisfaction, anger toward oneself, disappointment, anger towards circumstances. The two studies were based on the scenario methodology and implied a 2 x 2 (choice x outcome) between design. In the first study the foreseen short-term effects of the choice were assessed; in the second study the experienced long-term effects of the choice were assessed. In each study 160 students of the Second University of Naples participated. Results largely corroborated our hypotheses. They were discussed in the light of the main theories on regret and decision making.