The Number of Rational Points on Elliptic Curves y2 = x3 + b2 Over Finite Fields

Let p be a prime number, Fpbe a finite field and let Qpdenote the set of quadratic residues in Fp. In the first section we givesome notations and preliminaries from elliptic curves. In the secondsection, we consider some properties of rational points on ellipticcurves Ep,b: y2= x3+ b2 over Fp, where b ∈ F*p. Recall that theorder of Ep,bover Fpis p + 1 if p ≡ 5(mod 6). We generalize thisresult to any field Fnp for an integer n≥ 2. Further we obtain someresults concerning the sum Σ[x]Ep,b(Fp) and Σ[y]Ep,b(Fp), thesum of x- and y- coordinates of all points (x, y) on Ep,b, and alsothe the sum Σ(x,0)Ep,b(Fp), the sum of points (x, 0) on Ep,b.

Using Degree of Adaptive (DOA) Model for Partner Selection in Supply Chain

In order to reduce cost, increase quality, and for timely supplying production systems has considerably taken the advantages of supply chain management and these advantages are also competitive. Selection of appropriate supplier has an important role in improvement and efficiency of systems. The models of supplier selection which have already been used by researchers have considered selection one or more suppliers from potential suppliers but in this paper selecting one supplier as partner from one supplier that have minimum one period supplying to buyer is considered. This paper presents a conceptual model for partner selection and application of Degree of Adoptive (DOA) model for final selection. The attributes weight in this model is prepared through AHP model. After making the descriptive model, determining the attributes and measuring the parameters of the adaptive is examined in an auto industry of Iran(Zagross Khodro co.) and results are presented.

Statistical Genetic Algorithm

Adaptive Genetic Algorithms extend the Standard Gas to use dynamic procedures to apply evolutionary operators such as crossover, mutation and selection. In this paper, we try to propose a new adaptive genetic algorithm, which is based on the statistical information of the population as a guideline to tune its crossover, selection and mutation operators. This algorithms is called Statistical Genetic Algorithm and is compared with traditional GA in some benchmark problems.

An Efficient Hardware Implementation of Extended and Fast Physical Addressing in Microprocessor-Based Systems Using Programmable Logic

This paper describes an efficient hardware implementation of a new technique for interfacing the data exchange between the microprocessor-based systems and the external devices. This technique, based on the use of software/hardware system and a reduced physical address, enlarges the interfacing capacity of the microprocessor-based systems, uses the Direct Memory Access (DMA) to increases the frequency of the new bus, and improves the speed of data exchange. While using this architecture in microprocessor-based system or in computer, the input of the hardware part of our system will be connected to the bus system, and the output, which is a new bus, will be connected to an external device. The new bus is composed of a data bus, a control bus and an address bus. A Xilinx Integrated Software Environment (ISE) 7.1i has been used for the programmable logic implementation.

Numerical Simulations of Flood and Inundation in Jobaru River Basin Using Laser Profiler Data

Laser Profiler (LP) data from aerial laser surveys have been increasingly used as topographical inputs to numerical simulations of flooding and inundation in river basins. LP data has great potential for reproducing topography, but its effective usage has not yet been fully established. In this study, flooding and inundation are simulated numerically using LP data for the Jobaru River basin of Japan’s Saga Plain. The analysis shows that the topography is reproduced satisfactorily in the computational domain with urban and agricultural areas requiring different grid sizes. A 2-D numerical simulation shows that flood flow behavior changes as grid size is varied.

Learning and Relationships in the Cyberspace

The cyberspace is an instrument through which internet users could get new experiences. It could contribute to foster one-s own growth, widening cognitive, creative and communicative abilities and promoting relationships. In the cyberspace, in fact, it is possible to create virtual learning communities where internet users improve their interpersonal sphere, knowledge and skills. The main element of e-learning is the establishment of online relationships, that are often collaborative.

Convergence of ICT and Education

Information and communication technology (ICT) has become, within a very short time, one of the basic building blocks of modern society. Many countries now understanding the importance of ICT and mastering the basic skills and concepts of it as part of the core of education. Organizations, experts and practitioners in the education sector increasingly recognizing the importance of ICT in supporting educational improvement and reform. This paper addresses the convergence of ICT and education. When two technologies are converging to each other, together they will generate some great opportunities and challenges. This paper focuses on these issues. In introduction section, it explains the ICT, education, and ICT-enhanced education. In next section it describes need of ICT in education, relationship between ICT skills and education, and stages of teaching learning process. The next two sections describe opportunities and challenges in integrating ICT in education. Finally the concluding section summaries the idea and its usefulness.

A Bayesian Kernel for the Prediction of Protein- Protein Interactions

Understanding proteins functions is a major goal in the post-genomic era. Proteins usually work in context of other proteins and rarely function alone. Therefore, it is highly relevant to study the interaction partners of a protein in order to understand its function. Machine learning techniques have been widely applied to predict protein-protein interactions. Kernel functions play an important role for a successful machine learning technique. Choosing the appropriate kernel function can lead to a better accuracy in a binary classifier such as the support vector machines. In this paper, we describe a Bayesian kernel for the support vector machine to predict protein-protein interactions. The use of Bayesian kernel can improve the classifier performance by incorporating the probability characteristic of the available experimental protein-protein interactions data that were compiled from different sources. In addition, the probabilistic output from the Bayesian kernel can assist biologists to conduct more research on the highly predicted interactions. The results show that the accuracy of the classifier has been improved using the Bayesian kernel compared to the standard SVM kernels. These results imply that protein-protein interaction can be predicted using Bayesian kernel with better accuracy compared to the standard SVM kernels.

Intelligent Design of Reconfigurable Machines

This paper presents methodologies for developing an intelligent CAD system assisting in analysis and design of reconfigurable special machines. It describes a procedure for determining feasibility of utilizing these machines for a given part and presents a model for developing an intelligent CAD system. The system analyzes geometrical and topological information of the given part to determine possibility of the part being produced by reconfigurable special machines from a technical point of view. Also feasibility of the process from a economical point of view is analyzed. Then the system determines proper positioning of the part considering details of machining features and operations needed. This involves determination of operation types, cutting tools and the number of working stations needed. Upon completion of this stage the overall layout of the machine and machining equipment required are determined.

Statistical Estimation of Spring-back Degree Using Texture Database

Using a texture database, a statistical estimation of spring-back was conducted in this study on the basis of statistical analysis. Both spring-back in bending deformation and experimental data related to the crystal orientation show significant dispersion. Therefore, a probabilistic statistical approach was established for the proper quantification of these values. Correlation was examined among the parameters F(x) of spring-back, F(x) of the buildup fraction to three orientations after 92° bending, and F(x) at an as-received part on the basis of the three-parameter Weibull distribution. Consequent spring-back estimation using a texture database yielded excellent estimates compared with experimental values.

The Research Report of Employment Trends in Printing Industry for Prepress

This research aims to study employment trends in printing industry for prepress support by Suan Sunandha University Fund. The objectives of this research are to explain the trends of the employment in Thai Printing Industry for prepress in Bangkok and the description of different personnel that prepress entrepreneur need and also the problems of employment. The population of prepress entrepreneurs is about 100 organizations in the area of Bangkok. The questionnaires has been taken and analyzed with SPSS program by using the average percentage and standard deviation. This research is multiple case studies. The conceptual framework is developed on the basis of the open systems theory. The research result show that 1. The most of prepress entrepreneur have trend to choose the employee by any sex, the age 25-29 years old, bachelor degree and have 1-2 years experience. 2. The most problems are the understanding in job, communication/relation and the understanding in new technology. 3. The trends aims to employment in 1-3 years have 57.8% for prepress industry in Bangkok. This research suggests that: 1. Thai printing industry for prepress in Bangkok need quality employee that expert in printing technology. 2. Prepress entrepreneur should have agreement to development with university for practice the employee. 3. Prepress entrepreneur should support personal to fulfill the knowledge.

Grooving Method to Postpone Debonding of FRP Sheets Used for Shear Strengthening

One of the most common practices for strengthening the reinforced concrete structures is the application of FRP (Fiber Reinforce Plastic) sheets to increase the flexural and shear strengths of the member. The elastic modulus of FRP is considerably higher than that of concrete. This will result in debonding between the FRP sheets and concrete surface. With conventional surface preparation of concrete, the ultimate capacity of the FRP sheets can hardly be achieved. New methods for preparation of the bonding surface have shown improvements in reducing the premature debonding of FRP sheets from concrete surface. The present experimental study focuses on the application of grooving method to postpone debonding of the FRP sheets attached to the side faces of concrete beams for shear strengthening. Comparison has also been made with conventional surface preparation method. This study clearly shows the efficiency of grooving method compared to surface preparation method, in preventing the debonding phenomenon and in increasing the load carrying capacity of FRP.

Cross-cultural Analysis of the Strategy of Tolerance in the Republic of Kazakhstan

The modern Kazakh society is characterized by strengthen cross-cultural communication, the emergence of new powerful subcultures, accelerated change in social systems and values. The socio-political reforms in all fields have changed the quality of social relationships and spiritual life.Cross-cultural approach involves the analysis of different types of behavior and communication, including the manifestation of the conflict, and the formation of marginal destructive stereotypes.

Fast Forecasting of Stock Market Prices by using New High Speed Time Delay Neural Networks

Fast forecasting of stock market prices is very important for strategic planning. In this paper, a new approach for fast forecasting of stock market prices is presented. Such algorithm uses new high speed time delay neural networks (HSTDNNs). The operation of these networks relies on performing cross correlation in the frequency domain between the input data and the input weights of neural networks. It is proved mathematically and practically that the number of computation steps required for the presented HSTDNNs is less than that needed by traditional time delay neural networks (TTDNNs). Simulation results using MATLAB confirm the theoretical computations.

Study of Cross Flow Air-Cooling Process via Water-Cooled Wing-Shaped Tubes in Staggered Arrangement at Different Angles of Attack, Part 2: Heat Transfer Characteristics and Thermal Performance Criteria

An experimental and numerical study has been conducted to clarify heat transfer characteristics and effectiveness of a cross-flow heat exchanger employing staggered wing-shaped tubes at different angels of attack. The water-side Rew and the air-side Rea were at 5 x 102 and at from 1.8 x 103 to 9.7 x 103, respectively. The tubes arrangements were employed with various angles of attack θ1,2,3 from 0° to 330° at the considered Rea range. Correlation of Nu, St, as well as the heat transfer per unit pumping power (ε) in terms of Rea, design parameters for the studied bundle were presented. The temperature fields around the staggered wing-shaped tubes bundle were predicted by using commercial CFD FLUENT 6.3.26 software package. Results indicated that the heat transfer was increased by increasing the angle of attack from 0° to 45°, while the opposite was true for angles of attack from 135° to 180°. The best thermal performance and hence η of studied bundle was occurred at the lowest Rea and/or zero angle of attack. Comparisons between the experimental and numerical results of the present study and those, previously, obtained for similar available studies showed good agreements.

Pervasive Computing in Healthcare Systems

The hospital and the health-care center of a community, as a place for people-s life-care and health-care settings, must provide more and better services for patients or residents. After Establishing Electronic Medical Record (EMR) system -which is a necessity- in the hospital, providing pervasive services is a further step. Our objective in this paper is to use pervasive computing in a case study of healthcare, based on EMR database that coordinates application services over network to form a service environment for medical and health-care. Our method also categorizes the hospital spaces into 3 spaces: Public spaces, Private spaces and Isolated spaces. Although, there are many projects about using pervasive computing in healthcare, but all of them concentrate on the disease recognition, designing smart cloths, or provide services only for patient. The proposed method is implemented in a hospital. The obtained results show that it is suitable for our purpose.

Modeling of Surface Roughness in Vibration Cutting by Artificial Neural Network

Development of artificial neural network (ANN) for prediction of aluminum workpieces' surface roughness in ultrasonicvibration assisted turning (UAT) has been the subject of the present study. Tool wear as the main cause of surface roughness was also investigated. ANN was trained through experimental data obtained on the basis of full factorial design of experiments. Various influential machining parameters were taken into consideration. It was illustrated that a multilayer perceptron neural network could efficiently model the surface roughness as the response of the network, with an error less than ten percent. The performance of the trained network was verified by further experiments. The results of UAT were compared with the results of conventional turning experiments carried out with similar machining parameters except for the vibration amplitude whence considerable reduction was observed in the built-up edge and the surface roughness.

Practical Aspects of Face Recognition

Current systems for face recognition techniques often use either SVM or Adaboost techniques for face detection part and use PCA for face recognition part. In this paper, we offer a novel method for not only a powerful face detection system based on Six-segment-filters (SSR) and Adaboost learning algorithms but also for a face recognition system. A new exclusive face detection algorithm has been developed and connected with the recognition algorithm. As a result of it, we obtained an overall high-system performance compared with current systems. The proposed algorithm was tested on CMU, FERET, UNIBE, MIT face databases and significant performance has obtained.

Reality and Preferences in Community Mopane (Colophospermum Mopane) Woodland Management in Zimbabwe and Namibia

There is increasing pressure on, and decline of mopane woodlands due to increasing use and competition for mopane resources in Zimbabwe in Namibia. Community management strategies, based largely on local knowledge are evidently unable to cope. Research has generated potentially useful information for mopane woodland management, but this information has not been utilized. The work reported in this paper sought to add value to research work conducted on mopane woodlands by developing effective community-based mopane woodland management regimes that were based on both local and scientific knowledge in Zimbabwe and Namibia. The conditions under which research findings were likely to be adopted for mopane woodland management by communities were investigated. The study was conducted at two sites each in Matobo and Omusati Districts in Zimbabwe and Namibia respectively. The mopane woodland resources in the two study areas were assessed using scientific ecological methods. A range of participatory methods was used to collect information on use of mopane woodland resources by communities, institutional arrangements governing access to and use of these resources and to evaluate scientific knowledge for applicability in local management regimes. Coppicing, thinning and pollarding were the research generated management methods evaluated. Realities such as availability of woodland resources and social roles and responsibilities influenced preferences for woodland management interventions

Radar Task Schedulers based on Multiple Queue

There are very complex communication systems, as the multifunction radar, MFAR (Multi-Function Array Radar), where functions are integrated all together, and simultaneously are performed the classic functions of tracking and surveillance, as all the functions related to the communication, countermeasures, and calibration. All these functions are divided into the tasks to execute. The task scheduler is a key element of the radar, since it does the planning and distribution of energy and time resources to be shared and used by all tasks. This paper presents schedulers based on the use of multiple queue. Several schedulers have been designed and studied, and it has been made a comparative analysis of different performed schedulers. The tests and experiments have been done by means of system software simulation. Finally a suitable set of radar characteristics has been selected to evaluate the behavior of the task scheduler working.