Retention is an issue that has been faced by many engineering colleges due to the difficulties and lack of knowledge about what it really is to be an engineer. The first 3 years of the course are particularly intense ...
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In this paper, we propose an adaptive fast playback framework where multi-features are used to support arbitrary frame-rate video playback. We introduce a Jenson noise-based difference (JSND) as a distance measure bet...
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作者:
Li-Gang LiuKai XuProfessor
School of Mathematical Sciences University of Science and Technology of China Hefei Associate Professor
School of Computer National University of Defense Technology Changsha
The International Conference on computer-Aided Design and computergraphics (CAD/graphics) is a bian- nual international conference since 1989, which is affiliated with the Chinese computer Federation (CCF). The c...
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The International Conference on computer-Aided Design and computergraphics (CAD/graphics) is a bian- nual international conference since 1989, which is affiliated with the Chinese computer Federation (CCF). The conference is intended to provide an ideal forum for international researchers and developers to exchange new ideas on computer-aided design and computergraphics, electronic design automation, and visualization, to explore new ideas and trends.
In the orthognathic surgery, dental splints are important and necessary to help the surgeon reposition the maxilla or mandible. However, the traditional methods of manual design of dental splints are difficult and tim...
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It has become increasingly evident that large scale cyber systems can be brittle and may exhibit unpredictable behavior when faced with unexpected disturbances. Even weak and innocuous disturbances can bring down the ...
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ISBN:
(纸本)9781509021376
It has become increasingly evident that large scale cyber systems can be brittle and may exhibit unpredictable behavior when faced with unexpected disturbances. Even weak and innocuous disturbances can bring down the system inoperative and may introduce catastrophic disasters to the society. The goal of this research is to provide effective mechanisms to enhance the resilience of large scale cyber systems. Process interactions will be modeled and the relationship between interaction and system resilience will be analyzed. The effectiveness of modularization on resilience enhancement will be illustrated. A dynamic programming algorithm based solution will be developed to provide a solution to enhance system resilience through system modularization.
Software quality is regarded as the highly important factors for assessing the global competitive position of any software product. To assure quality, and to assess the reliability of software products, many software ...
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Software quality is regarded as the highly important factors for assessing the global competitive position of any software product. To assure quality, and to assess the reliability of software products, many software quality prediction models have been proposed in the past decades. In this proposed method we have utilized a hybrid method for quality prediction. The prediction is done with the help of the Advanced Neural network which is incorporated with Hybrid Cuckoo search (HCS) optimization algorithm for better prediction accuracy. The application software is first subjected to test case generation and once the test cases are generated they are applied to advanced neural network for the prediction of quality. The neural network is improved by utilizing HCS which optimizes the weight factor for improving the prediction. The quality metrics like maintainability and reliability are estimated for predicting the software quality and the results are compared with other existing techniques to verify the effectiveness of our proposed method.
A tremendous growth and progress has shown the potential of big data (i.e structured, unstructured and semi-structured) to extract valuable information and do reliable prediction for several industries. Social network...
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ISBN:
(纸本)9781509032082
A tremendous growth and progress has shown the potential of big data (i.e structured, unstructured and semi-structured) to extract valuable information and do reliable prediction for several industries. Social networking data has created additional opportunities for data scientists and researchers to utilize the data points to advance the predictive and mining models and techniques. However, predictive analysis in field of academics is at its infancy. In this paper, we present a framework to implement a recommender system to improve academic choice process for new students. The framework is based on our ongoing research for Predicting Educational Relevance For an Efficient Classification of Talent (PERFECT Algorithm Engine), that utilizes stochastic probability distribution based modeling. We present an algorithm and math construct to support our work along with providing graphical results for various parameters that help the recommendation and decision process for individuals. We show related study and conclude with future work.
作者:
K P N V Satyasree DrB Lalitha Kumari DrK S N V Jyotsna DeviS M Roy ChoudriK Pratap JoshiAssociate Professor
Department of Computer Science & Engineering Vignan's Nirula Institute of Technology & Science for Women Palakaluru Guntur A.P. India Associate Professor
scientist-grade-1 Srimaharshi Research Institute Of Vedic Technology Syamala Nagar Guntur A.P India Assistant Professor
Department of Computer Science & Engineering Rajamahendri Institute of Engineering & Technology Bhoopalapatnam Rajahmundry A.P India Associate Professor
Department of Computer Science & Engineering Usha Rama College of Engineering and Technology Telaprolu Vijayawada A.P India Associate Professor
Department of Computer Science & Engineering Hindu College of Engineering and Technology Amaravathi Road Guntur A.P. India.
Text-mining is one of the best potential way of automatically extracting information from the huge biological literature. To exploit its prospective, the knowledge encrypted in the text should be converted to some sem...
Text-mining is one of the best potential way of automatically extracting information from the huge biological literature. To exploit its prospective, the knowledge encrypted in the text should be converted to some semantic representation such as entities and relations, which could be analyzed by machines. But large-scale practical systems for this purpose are rare. But text mining could be helpful for generating or validating predictions. Cellulases have abundant applications in various industries. Cellulose degrading enzymes are cellulases and the same producing bacteria – Bacillus subtilis & fungus Pseudomonas putida were isolated from top soil of Guntur Dt. A.P. India. Absolute cultures were conserved on potato dextrose agar medium for molecular studies. In this paper, we presented how well the text mining concepts can be used to analyze cellulase producing bacteria and fungi, their comparative structures are also studied with the aid of well-establised, high quality standard bioinformatic tools such as Bioedit, Swissport, Protparam, EMBOSSwin with which a complete data on Cellulases like structure, constituents of the enzyme has been obtained.
In Fall 2014, a large Midwestern land-grant research university piloted a competency-based model as the foundation for an undergraduate transdisciplinary program focusing on connecting engineering and technology with ...
Cloud computing provides an effective way to dynamically provide numerous resources to meet customer demands. A major challenging problem for cloud providers is designing efficient mechanisms for optimal virtual machi...
Cloud computing provides an effective way to dynamically provide numerous resources to meet customer demands. A major challenging problem for cloud providers is designing efficient mechanisms for optimal virtual machine Placement (OVMP). Such mechanisms enable the cloud providers to effectively utilize their available resources and obtain higher profits. In order to provide appropriate resources to the clients an optimal virtual machine placement algorithm is proposed. Virtual machine placement is NP-Hard problem. Such NP-Hard problem can be solved using heuristic algorithm. In this paper, Ant Colony Optimization based virtual machine placement is proposed. Our proposed system focuses on minimizing the cost spending in each plan for hosting virtual machines in a multiple cloud provider environment and the response time of each cloud provider is monitored periodically, in such a way to minimize delay in providing the resources to the users. The performance of the proposed algorithm is compared with greedy mechanism. The proposed algorithm is simulated in Eclipse IDE. The results clearly show that the proposed algorithm minimizes the cost, response time and also number of migrations.
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