A 'peer reviewed' journal indexed on Cabell's Directory, and also distributed by EBSCO and Proquest Database
It is a quarterly journal that publishes research papers on state-of-the-art Computing techniques and Encryption techniques; Computational problems; Artificial Intelligence; Cloud Computing; Databases; Algorithms and data structures; Cybernetics; Firewall techniques; Chip designing, Logic circuits and Software engineering; Programming techniques; Computer architecture; Neural networks, Machine Learning etc.
Optimized Link Stability and Cross-Layer Design for Secured Ad-Hoc Network
Maintainability and context awareness knowledge increase the requirement of cross-layer architecture. The wealth of cross-layer coordination examples from miscellaneous fields of networking are security, handoff, autonomic communication, routing, sensor networks, quality of service and energy. In the cognitive radio, selection of suitable wireless channels in the vicinity depends on application requirements and network conditions. Different static and dynamic cross-layer optimization heuristics are available in literature with different performance parameters. The paper discusses different cross-layer architecture and link optimization for improving the performance of network. The prime focus is on link prediction methodology for enhancement of the performance of network. Various performance parameters of protocols of software defined networks are compared. Throughput, end-to-end delay, jitter, PDR and goodput with different scenarios are observed and compared. It is observed that the performance of OLSR is better in different scenarios as compared to other protocols.
A Comparison of Some Metaheuristic Optimization Algorithms for Solving High Dimensional Benchmark Problems
With the emergence of Big Data, the existing optimization techniques need to be tested to find those that are not suitable to handle high dimensional problems. The number of natureinspired population-based metaheuristic optimization algorithms has been explored over the decade with new techniques being proposed constantly. A recent summary of existing algorithms has listed near about 134. A majority of these optimization algorithms have been designed and applied to solve real-parameter function optimization problems, each claimed to be superior to other methods in terms of performance. However, most of these algorithms have been tested on relatively low dimensional problems, i.e., problems involving less than 30 parameters. This paper presents different benchmark functions that are systematically analyzed and tested in detail for problems involving up to 100 parameters. Genetic Algorithms (GA), Biogeography-Based Optimization (BBO) and Particle Swarm Optimization (PSO) are compared in terms of accuracy and runtime using three high dimensional standard benchmark functions.
Cloud Computing for MATLAB and R Users: Part I – Creation of Virtual Computing Instance Using Amazon Web Services
Cloud-based computing has tremendous potential for academia in general and researchers in particular. The ability to store, read and manipulate large dataset is increasingly important to be on the cutting-edge of research. While most researchers have extensive programming skills, they generally are not computer scientists. A number of cloud-based and virtual work spaces have been developed which can bring enormous computing advantages over any desktop or laptop. However, the instructions to get up and running in the cloud are often overwhelming, and require a significant investment of time. There is an initial steep learning curve associated with developing a high performance computing environment that several times becomes an obstacle that prevents many to benefit the most from using the cloud. This paper seeks to demystify the process and get the reader up and running very quickly. Once this initial process is over and the reader is proficient on these issues, performing computational chores that would take days on a desktop can be done in minutes. We next show the way the readers can implement their research using two well-known computer programs: MATLAB and R.
A Proposal for Interactive Programming Language
The paper presents an idea for a programming language specifically designed for an interactive environment similar to a notebook. It aims at combining the power of a programming language with the usability of a spreadsheet. The comments presented could be modified as per needs.
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