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journal engineering and applied computer science
Volume: 02, Issue: 07, July 2017
Jie Xiong, Caiyun Liu
Xiong and C. Liu, “Improved Parallel PSO Inversion for the MT Sounding Data,” International Journal of Engineering and Applied Computer Science, vol. 02, no. 07, pp. 202–205, Aug. 2017.
Abstract—The magnetotelluric (MT) method has become more widely used in hydrocarbon exploration. The inversion of MT data, which can determine the electrical structure of subsurface, is a nonlinear and multimodal optimization problem. Particle swarm optimization (PSO) algorithm is a good solver for this geophysical inversion problem, whereas it has a shortage of heavy computation time. An improved parallel adaptive PSO inversion algorithm for MT data is proposed in order to decrease the computation time. The performance of the proposed algorithm was evaluated on the Dawn 4000L supercomputer using the synthetic MT data of 1D layered geo-electrical models of three and four layers. The numeric results show that the proposed algorithm can obtain the as good solution as the serious PSO inversion algorithm, and can reduce the computation time obviously when more computing nodes been employed. This result indicates that proposed improved parallel inversion algorithm can deal with the computation time problem and provide theory and technology support the MT data non-linear inversion based on PSO.
Jie Xiong, Caiyun Liu
Xiong and C. Liu, “Solving the Power Purchase Cost Optimization Problem with Improved DE Algorithm,” International Journal of Engineering and Applied Computer Science, vol. 02, no. 07, pp. 206–211, Aug. 2017.
Abstract—Under the deregulation of generation market in China, all distributed generators will particular in electric power bidding. Therefore power purchase cost optimization (PPCO) problem has been getting more attention of power grid Company. However, under the competition principle, they can purchase power from several of power plants, therefor, there exist continuous and integral variables in purchase cost model, which is difficult to solve by classical linear optimization method. An improved differential evolution algorithm is proposed and employed to solve the PPCO problem, which targets on minimum purchase cost, considering the supply and demand balance, generation and transfer capability as constraints. It yields the global optimum solution of the PPCO problem. The numerical results show that the proposed algorithm can solve the PPCO problem and saves the costs of power purchase. It has a widely practical value of application.
Kuldeep N. Shukla, Anjali Potnis, Prashant Dwivedy, Shahbaz Soofi
K. N. Shukla, “Detection and Tracking of Objects: A Detailed Study,” International Journal of Engineering and Applied Computer Science, vol. 02, no. 07, pp. 212–216, Aug. 2017.
Abstract—Detecting and tracking objects are the most widespread and challenging tasks that a surveillance system must achieve to determine expressive events and activities, and automatically interpret and recover video content. An object can be a queue of people, a human, a head or a face. The goal of this article is to state the Detecting and tracking methods, classify them into different categories, and identify new trends, we introduce main trends and provide method to give a perception to fundamental ideas as well as to show their limitations in the object detection and tracking for more effective video analytics.
M. RAHMOUNI and S. MBARKI, “Model-Driven Generation of MVC2 Web Applications: From Models to Code,” International Journal of Engineering and Applied Computer Science, vol. 02, no. 07, pp. 217–231, Aug. 2017.
Abstract—Computer systems engineering is based, increasingly, on models. These models permit to describe the systems under development and their environment at different abstraction levels. These abstractions allow us to conceive applications independently of target platforms. For a long time, models have only constituted a help for human users, allow to manually develop the final code of computer applications. The Model-Driven Engineering approach (MDE) consists of programming at the level of models, represented as an instance of a meta-model, and using them for generating the end code of applications. The MDA (Model-Driven Architecture) is a typical model-driven engineering approach to application design. MDA is based on the UML standard to define models and on the meta-modeling environment (MOF) for model-level programming and code generation. The code generation operation is the subject of this paper. Thus, in this work, we explain the code generation of MVC2 Web application by using the M2M transformation (ATL transformation language) then the M2T transformation. To implement this latter we use the Acceleo generator which is a generator language. In the M2T transformation, we use the PSM model of Struts2 already generated by M2M transformation as an input model of Acceleo generator. This transformation is validated by a case study. The main goal of this paper is to achieve the end-to-end code generation.
Kuldeep Narayan Shukla, Anjali Potnis, Prashant Dwivedy
K. N. Shukla, “A Review on Image Enhancement Techniques,” International Journal of Engineering and Applied Computer Science, vol. 02, no. 07, pp. 232–235, Aug. 2017.
Abstract—Image enhancement is one of the challenging issues in image processing. The objective of Image enhancement is to process an image so that result is more suitable than original image for specific application. Digital image enhancement techniques provide a lot of choices for improving the visual quality of images. Appropriate choice of such techniques is very important. This paper will provide an overview and analysis of different techniques commonly used for image enhancement. Image enhancement plays a fundamental role in vision applications. Recently much work is completed in the field of images enhancement. Many techniques have previously been proposed up to now for enhancing the digital images. In this paper, a survey on various image enhancement techniques has been done.
Oluwole O. Oyetoke, Omolola Peace Dayo-Odukoya
O. O. Oyetoke and O. P. Dayo-Odukoya, “Sensor Networks and its Application in Electronic Medicine: Detailed Analysis of its Prospects, Challenges, and Socio-Economic Impact,” International Journal of Engineering and Applied Computer Science, vol. 02, no. 07, pp. 236–244, Aug. 2017.
Abstract—In recent times, there has been a tectonic shift in the manner through which medical services are being rendered and the organization of the practice of Medicine as a whole. This tremendous diversification in the techniques employed for medical service delivery has noticeably been achieved through the integration of Engineering with medical sciences and the efficient latch of Medicine on constant improvements across the field of Computer and Electronic Engineering. Treatment of patients, medical research, education, disease tracking and monitoring of public health have been efficiently optimized through innovations in Engineering. To this effect, medical practices in advanced countries have now transitioned from being largely one-to-one/human-to-human interactivity to a characteristic distributed healthcare delivery system whereby patients can receive both remote health advice as well as remote medical treatments usually through electronic gadgets operating within a standardized Sensor Network (SN) architecture. This paper seeks to explore the concept behind Sensor Networks, the technology framework, its application in the field of Electronic Medicine, prospects, challenges, ethical issues and a thorough analysis of the socio-economic impact of this new application of Electronic and Computer Engineering in Medicine.

computer science journal, engineering journal