The system Galactica of free access is supplemented module for the Coulomb interaction. It is based on a high-precision method for solving differential equations of motion of N charged particles. The paper presents all the theoretical and practical issues required to use this module of system Galactica so that even the beginning researcher could study the motion of particles, atoms and molecules.

Acceptance of cloud systems as the future has given way to a large number of cloud application installations. They have their presence across domains be it banking, gaming, education and others. A cloud based solution brings down the cost of ownership and maintenance for the host organization. For the users a resilience to use any type of end device being it a workstation, laptop, netbook or even a smartphone to access the application. A typical cloud based LMS was developed with appropriate pedagogy to teach programming courses. Necessary software required are made available on the cloud, with a bare minimum hardware spec requirement at the user end. The paper highlights the adaptability to such pure online course by the students and their learning outcomes. The paper also discusses the issues and challenges both in terms of technology and pedagogy which needs to be addressed when such online courses are planned.

Data security is one of the biggest concerns in cloud computing environment. Although the advantages of storing data in cloud computing environment is extremely high, there arises a problem related to data missing. CyberLiveApp (CLA) supports secure application development between multiple users, even though cloud users distinguish their vision privileges during storing of data. But CyberLiveApp failed to integrate the system with certain cloud-based computing environments on multi-server. Environmental Decision Support Systems (EDSS) move away the technical load and focus mainly on decision-making activities. EDDS does not have a secure collaborative decision-making experience on cloud services. To integrate the security level for multi-server cloud infrastructure, Information Interpretation Code on Multi-Server (IICM-S) is proposed in this paper. To ensure the information with relevance to security on cloud-based computing environments, Information Interpretation Code (IIC) algorithm is initially developed. Thus, IIC guarantee that all information pertaining to cloud is in secured condition in order to prove the trustworthiness of data. In addition, the multi-sever cloud infrastructure in IIC provides access point for secure information recovery from cloud data server. The multi-server cloud infrastructure with IIC algorithm performs the recovery task on multi-server cloud infrastructure. The Multi-server Information (MI) scheme measures the integrity level with effective data recovery process. The integrity level on multi-server cloud infrastructure is ensured using two components, verifier and verify shifter. MI scheme proficiently check integrity using these two components so that not only the data integrity is provided as well as security is ensured in all cases using IICM-S. Experiment is conducted in the Cloudsim platform on the factors such as average integration time on multi-server, security level, recovery efficiency level.

Back propagation is one of the well known training algorithms for multilayer perceptron. However the rate of convergence in back propagation learning tends to be relatively slow, which in turn makes it computationally excruciating. Over the last years many modifications have been proposed to improve the efficiency and convergence speed of the back propagation algorithm. The main emphasis of this paper is on investigating the performance of improved versions of back propagation algorithm in training the neural network. All of them are assessed on different training sets and a comparative analysis is made. Results of computer simulations with standard benchmark problems such as XOR, 3 BIT PARITY, MODIFIED XOR and IRIS are presented. The training performance of these algorithms is evaluated in terms of percentage of accuracy, and convergence speed.

The role of network and information systems is increasing in our day today infrastructures that provide critical services like banking and commerce applications, telecommunications, distribution, transportation, etc. This increases the levels of dependability on such applications, which brings about several pros and cons as well. If these infrastructures are damaged, it can compromise the availability of the critical services. Thus, it is the need of the hour to secure the available network and information systems from malicious attacks. In this paper, we have proposed a secure technique named as Network Liability Detection (NLD) and a software we named as Network Liability Tool (NLT), that points out the liabilities or vulnerabilities of your system that can be exploited to compromise its security. We propose a model based approach where the behavior of each component of the system is carefully monitored to find out the well known as well as as-yet-unknown loopholes in the system. A prototype of the application is built in Windows Platform using Java, to demonstrate the entire functioning of this system and helps in solving the security related loopholes in the network servers. The speculative results affirm that the proposed technique is effective in detecting the liabilities of the network servers.

The social media networks have evolved rapidly and people frequently use these services to communicate with others and express themselves by sharing opinions, views, ideas etc. on different topics. The social media trend analysis is generally carried out by sifting the corresponding or interlinked events discussed on social media websites such as Twitter, Facebook etc. The fundamental objective behind such analyses is to determine the level of criticality with respect to criticism or appreciation described in the comments, tweets or blogs. The trend analysis techniques can also be systematically exploited for opinion making among the masses at large. The results of such analyses show how people think, assess, orate and opine about different issues. This paper primarily focuses on the trend detection and sentiment analysis techniques and their efficacy in the contextual information. We further discuss these techniques which are used to analyze the sentiments expressed within a particular sentence, paragraph or document etc. The analysis based on sentiments can pave way for automatic trend analysis, topic recognition and opinion mining etc. Furthermore, we can fairly estimate the degree of positivity and negativity of the opinions and sentiments based on the content obtained from a particular social media.

In 1989 Gerardo Beni and Jing Wang first proposed the name “Swarm Intelligence” in their paper “Swarm Intelligence in Cellular Robotic Systems”. Some remarkable observations of different researchers are studied in this paper, like the proximity principle, the quality principle, the principle of diverse response, the principle of stability, the principle of adaptability. To enhance the capabilities of robot and different systems, researchers started to exploit the behavior of natural systems. Swarm groups are governed by three rules, move in the same direction as your neighbor, remain close to your neighbor, and avoid collision with your neighbor .Characteristics of swarm groups are emergence and stigmergy. Different insects like ants, wasps, termites carry out a work locally for global goal with sufficient flexibility as they are not controlled centrally. In this paper the existing research works are analysed to show the behavior in social insects by using self-organization, positive feedback, negative feedback, amplification of fluctuation, multiple interactions. It has also been observed that these insects are almost blind and memoryless, still they communicate indirectly among themselves for stigmergic effect by using pheromone. Implementation of swarm intelligence in robotics i.e., swarm robots are narrated. The limitations of swarm robots as well as factors behind the success of swarm robotics have also been encompassed. Finally authors focus on swarm robots applications in telecommunication fields, civil engineering and digital image processing.