The Galactica System is intended for resolving N-body interaction problems. It is based on a high-precision method for solving differential equations of motion of bodies whose interaction forces are inversely proportional to the squared distance. The differential equations of motion and their solution method are given in paper. The structure of the input file, the files of initial conditions and output files are described. The examples of these files for different solved tasks are presented. The actions of executable files are explained. The paper describes all the theoretical and practical issues so that even a novice researcher could use Galactica System in his/her works.

In this paper, we introduce a face recognition algorithm based on doubly truncated multivariate Gaussian mixture model with Discrete Cosine Transform (DCT) and Local binary pattern (LBP). Here, the input face image is transformed to the local binary pattern domain. The obtained local binary pattern image is divided into non-overlapping blocks. Then from each block the DCT coefficients are computed and feature vector is extracted. Assigning that the feature vector follows a doubly truncated multivariate Gaussian mixture distribution, the face image is modelled. By using the Expectation-Maximization algorithm the model parameters are estimated. The initialization of the model parameters is done by using either K-means algorithm or hierarchical clustering algorithm and moment method of estimation. The face recognition system is developed with the likelihood function under Bayesian frame. The efficiency of the developed face recognition system is evaluated by conducting experimentation with JNTUK and Yale face image databases. The performance measures like half total error rate, recognition rates are computed along with plotting the ROC curves. A comparative study of the developed algorithm with some of the earlier existing algorithm revealed that this system perform better since, it utilizes local and global information of the face.

Project-based learning (PBL) was proven to be a very useful model to give students hands on experiences and allow them to be active learners rather than passive listeners. In this paper we introduce a tool to help enhance the project development experiences for information technology (IT) students. The main purpose of this tool is to help reuse web information to enable IT projects for students. This tool is called InetRetriever and it can be easily used by students to retrieve, in real-time, any required real information from the web and to implement, execute, and test their projects with real life data. As PBL is becoming an integral part of many information technology (IT) courses, and in many cases real data is essential for many types of projects, it becomes important to make such data available and accessible easily. In various cases, students focus gets shifted from the real objectives of a project when they spend a lot of their time trying to find data or create methods to get them this data. Furthermore, many projects fail and cannot demonstrate their real capabilities when they are tested and demonstrated using small sets of sample data or some fabricated data sets because the students could not include real data available on the Internet. Another possibility here is that students could not even complete their projects because of the difficulties in retrieving the required data and the excess amount of time they spend on that tasks rather than on the real tasks in the project. Therefore, InetRetriever was developed to overcome this obstacle. It was tested in different information technology courses to enable effective and realistic project-based learning. Using this tool we observed increased student interest in the project development and higher levels of interactions and learning.

The purpose of this paper is to prove a common fixed theorem for R-weakly commuting mappings via an implicit relation in fuzzy metric space. While proving our result, we utilize the idea of property (E.A.) due to Aamri and El. Moutawakil [1] together with common (E.A.) property due to Liu, Wu and Li [2].

It is important to study learning styles because recent studies have shown that a match between teaching and learning styles helps to motivate students´ process of learning. That is why teachers should identify their own teaching styles as well as their learning styles to obtain better results in the classroom. The aim is to have a balanced teaching style and to adapt activities to meet students´ style and to involve teachers in this type of research to assure the results found in this research study. Over 100 students complete a questionnaire to determine if their learning styles are auditory, visual, or kinesthetic. Discovering these learning styles will allow the students to determine their own personal strengths and weaknesses and learn from them. Teachers can incorporate learning styles into their classroom by identifying the learning styles of each of their students, matching teaching styles to learning styles for difficult tasks, strengthening weaker learning styles. The purpose of this study is to explain learning styles, teaching styles match or mismatch between learning and teaching styles, visual, auditory, and kinesthetic learning styles among Iranian learners, and pedagogical implications for the EFL/ESL classroom. A review of the literature along with analysis of the data will determine how learning styles match the teaching styles.

Biometrics is playing an important role for person recognition. The Biometrics identification of an individual is can be done by physiological or behavioral characteristics; where the palm print of an individual can be captured by using sensors and is one of among physiological characteristics of an individual. Palm print is a unique and reliable biometric characteristic with high usability. A palm print refers to an image acquired of the palm region of the hand. The biometric use of palm prints uses ridge patterns to identify an individual. Palm print recognition system is most promising to recognize an individual based on statistical properties of palm print image. It is rich in its features: principal lines, wrinkles, ridges, singular points and minutiae points. This paper proposes a Biometric Palm print lines extraction using image processing morphological operation. The proposed work discusses the significance; since both the palm print and hand shape images are proposed to extract from the single hand image acquired from a sensor. The basic statistical properties can be computed and are useful for biometric recognition of individual. This result and analysis will result into Total Success Rate (TSR) of experiment is 100%. This paper discusses proposed work for biometric recognition of individual by using basic statistical properties of palm print image. The experiment is carried out by using MATLAB software image processing toolbox.

Biometrics is an advanced way of person recognition as it establishes more direct and explicit link with humans than passwords, since biometrics use measurable physiological and behavioural features of a person. In this paper gender recognition from human gait in image sequence have been successfully investigated. Silhouette of 15 males and 15 females from the database collected from CASIR site have been extracted. The computer vision based gender classification is then carried out on the basis of standard deviation, centre of mass and height from head to toe using Feed Forward Back Propagation Network with TRAINLM as training functions, LEARNGD as adaptation learning function and MSEREG as performance function. Experimental results demonstrate that the present gender recognition system achieve recognition performance of 93.4%, 94.6%, and 94.7% with 2 layers/20 neurons, 3 layers/30 neurons and 4 layers/30 neurons respectively. When the performance function is replaced with SSE the recognition performance is increased by 2%, 2.4% and 3% respectively for 2 layers/20 neurons, 3 layers/30 neurons and 4 layers/30 neurons.The above study indicates that Gait based gender recognition is one of the best reliable biometric technology that can be used to monitor people without their cooperation. Controlled environments such as banks, military installations and even airports need to quickly detect threats and provide differing levels of access to different user groups.

This study aims to identify the attitudes of the sample individuals from students that have used the electronic assessments (e-assessments) system at Isra University in Jordan. These attitudes describe the relationship between the availability of the requirements for e-assessments applications and the success of its implementation. Analytical descriptive method and sample research have been used. The samples included 246 students from 5 colleges covered by the research sample. The instrument of the study was a questionnaire which consisted of many variables that measured influential relationship among them. The research concluded that there is a relationship effect between the availability of the requirements and the success of the implementation process of the e-assessments system. There is a difference in the members attitudes of the research samples over the impact of which variables are most influenced. The results showed that there is a variation in the attitudes on all variables.