2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)最新文献_第5页

PSO and GA parameters estimation for digital watermarking algorithm 数字水印算法中的粒子群算法和遗传算法参数估计

2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2016-09-01 DOI: 10.1109/ICRITO.2016.7784985

Varsha Parashar, Garima Mehta

引用次数: 2

Design of power feeding circuit for Wi-Fi devices operating at 2.4 GHz standard 2.4 GHz标准下Wi-Fi设备馈电电路设计

2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2016-09-01 DOI: 10.1109/ICRITO.2016.7784991

Prashant Jha, Hitesh Poddar, K. Shambavi

引用次数: 0

Design and implementation of a robust system for recognizing alphabets using artifical neural network 基于人工神经网络的鲁棒字母识别系统的设计与实现

2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2016-09-01 DOI: 10.1109/ICRITO.2016.7785026

Shubhankar Kapoor, Ashish Singh, Utkarsha Goswami, Saswat Kumar, G. Chitranshi

引用次数: 3

Evaluating risks in cloud computing: Security perspective 评估云计算中的风险:安全视角

2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2016-09-01 DOI: 10.1109/ICRITO.2016.7785013

Amit Dhingra, D. Rai

引用次数: 1

Pairwise sequence alignment of biological database using soft computing approach 基于软计算方法的生物数据库成对序列比对

2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2016-09-01 DOI: 10.1109/ICRITO.2016.7784929

Harleen Kaur, L. Chand

{"title":"Pairwise sequence alignment of biological database using soft computing approach","authors":"Harleen Kaur, L. Chand","doi":"10.1109/ICRITO.2016.7784929","DOIUrl":"https://doi.org/10.1109/ICRITO.2016.7784929","url":null,"abstract":"A Biological sequence alignment is the cornerstone of bioinformatics. The sequence alignment is carried out to extrapolate the evolutionary relationship among the living species which can help to characterize the functionality of unidentified sequences. The overall objective of pairwise alignment is to determine the uttermost alikeness among residues. Dynamic programming (DP) is the most popular technique for pairwise alignment but the downside of this approach is the proliferation of space and time complexity while handling considerable biological sequence. Various soft computing algorithms such as GA, PSO, ACO, GSA and many more, are in trend from past few years. These algorithms are inspired by natural evolution which helps to find near optimal solutions for optimization problem in reasonable amount of time. In this paper pairwise sequence alignment of protein is done using hybrid approach of soft computing algorithms which subsume Gravitational Search Algorithm (GSA) and Particle Swarm Optimization (PSO). The enactment of this hybrid approach is examined by comparing the simulation results with the DP based algorithms.","PeriodicalId":377611,"journal":{"name":"2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122732604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A novel approach for improving recommender system 一种改进推荐系统的新方法

2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2016-09-01 DOI: 10.1109/ICRITO.2016.7785025

S. Khatri, Sonam Gupta

引用次数: 1

Semantic similarity between terms for query suggestion 术语之间的语义相似度用于查询建议

2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2016-09-01 DOI: 10.1109/ICRITO.2016.7784959

Mamta Kathuria, Payal, C. K. Nagpal, Neelam Duhan

引用次数: 5

A soft computing approach for obesity assessment 肥胖评估的软计算方法

2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2016-09-01 DOI: 10.1109/ICRITO.2016.7784946

Jawed Ahmed, M. A. Alam, Abdul Mobin, Shahla Tarannum

引用次数: 1

Multi-stage diffusion dynamics based on optimal control theory 基于最优控制理论的多阶段扩散动力学

2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2016-09-01 DOI: 10.1109/ICRITO.2016.7784934

Adarsh Anand, Shakshi Singhal, Ompal Singh

{"title":"Multi-stage diffusion dynamics based on optimal control theory","authors":"Adarsh Anand, Shakshi Singhal, Ompal Singh","doi":"10.1109/ICRITO.2016.7784934","DOIUrl":"https://doi.org/10.1109/ICRITO.2016.7784934","url":null,"abstract":"In this relentlessly innovative market, product diffusion has a pre-eminent importance for any firm. The comprehend study of the adoption process assists the manufacturer to facilitate the growth of their product. It is observed that the adoption of the product goes through multiple stages before the actual adoption occurs. As market shows dynamic behavior, the fluctuating price acts as a vital characteristic in the consumer buying decisions. In the present paper, a multi-stage innovation diffusion model is formulated where the evolution of sales takes place in three stages, namely, development of innovation awareness, motivation and ultimate adoption. The proposed model showcases the impact of dynamic pricing policy of the product on the motivation for actual adoption by the potential consumers. For this purpose, an optimization model based on optimal control theory problem is formulated. In addition, analytical results for the optimal pricing policy for an innovation are also investigated. The proposed model is further tested on different real life sales data sets for validation purpose and results provide empirical support to the model. The paper also provides the numerical illustration of the discrete model of proposed problem to evaluate the influence of price, the marketing factor on the company's new product introduction approach.","PeriodicalId":377611,"journal":{"name":"2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126483982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Assessment of defect prediction models using machine learning techniques for object-oriented systems 使用面向对象系统的机器学习技术评估缺陷预测模型

2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2016-09-01 DOI: 10.1109/ICRITO.2016.7785021

R. Malhotra, Shivani Shukla, Geet Sawhney

{"title":"Assessment of defect prediction models using machine learning techniques for object-oriented systems","authors":"R. Malhotra, Shivani Shukla, Geet Sawhney","doi":"10.1109/ICRITO.2016.7785021","DOIUrl":"https://doi.org/10.1109/ICRITO.2016.7785021","url":null,"abstract":"Software development is an essential field today. The advancement in software systems leads to risk of them being exposed to defects. It is important to predict the defects well in advance in order to help the researchers and developers to build cost effective and reliable software. Defect prediction models extract information about the software from its past releases and predict the occurrence of defects in future releases. A number of Machine Learning (ML) algorithms proposed and used in the literature to efficiently develop defect prediction models. What is required is the comparison of these ML techniques to quantify the advantage in performance of using a particular technique over another. This study scrutinizes and compares the performances of 17 ML techniques on the selected datasets to find the ML technique which gives the best performance for determining defect prone classes in an Object-Oriented(OO) software. Also, the superiority of the best ML technique is statistically evaluated. The result of this study demonstrates the predictive capability of ML techniques and advocates the use of Bagging as the best ML technique for defect prediction.","PeriodicalId":377611,"journal":{"name":"2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127023398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7