2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)最新文献_第3页

An optimal genome reassembling technique by Artificial Bees System for small genome sequences 基于人工蜜蜂系统的小基因组重组优化技术

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813670

Susobhan Baidya, R. K. De

{"title":"An optimal genome reassembling technique by Artificial Bees System for small genome sequences","authors":"Susobhan Baidya, R. K. De","doi":"10.1109/ICRCICN.2016.7813670","DOIUrl":"https://doi.org/10.1109/ICRCICN.2016.7813670","url":null,"abstract":"Fragment assembling problem (FAP) is an NP-complete problem. The present article presents an Artificial Bees Colony (ABC) learning system to solve Genome sequence reassembling techniques. Reference Genome sequence which is taken 99% analogous to a Genome from same organism, because of the fact the sequences from the similar organism usually have approximately 99.9% resemblance. We have used the sequences from NCBI database2. Then we have cloned each sequence and shear the clone to a numeral short reads. Here, we have used a different perception in Genome reassembling by Synthetic Bees System where nectar amount is relative to the accuracy of assembled reads with some reference genome sequences inside the similar creature. For local heuristics information, we have introduced local alignment of short reads instead local overlapping among the reads. The outcome depict that our methodology is more accurate than an existing Bee Colony Algorithm. Genome reassembling methodology require a huge concurrency and vast storage because of size of Genome sequences of mammalian group is ~ 109bp, and ABC is inherently concurrent in nature. We have run LSBCO in 64 bit O.S in HP proliant server with 16GB RAM, 2-quad core processor. We have computed our methodology for the Genome length up to 127429bp. We have simulated hierarchical sequencing, and finally stitched the each segments to get back the actual Genome sequence.","PeriodicalId":254393,"journal":{"name":"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"12 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":"128215044","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: 0

A novel dictionary-based classification algorithm for opinion mining 一种新的基于词典的意见挖掘分类算法

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813652

Santanu Mandal, S. Gupta

{"title":"A novel dictionary-based classification algorithm for opinion mining","authors":"Santanu Mandal, S. Gupta","doi":"10.1109/ICRCICN.2016.7813652","DOIUrl":"https://doi.org/10.1109/ICRCICN.2016.7813652","url":null,"abstract":"There has been a rapid rise in the number of users getting connected online via social networking sites. To communicate with other users and share their thoughts and opinions, online users' tend to use texts in the form of blogs, posts, tweets, messages, reviews, comments etc. Thus, there has been an immense possibility complemented with a wide gamut of research in the field of Opinion Mining or Sentiment Analysis by using textual information from online communities. Hence, there is an extensive need for different text classification algorithms and approaches to classify texts and predict sentiments correctly so as to comprehend the emotional state of the user. We have varied algorithms for text classification for predicting emotional traits. In this paper, we are proposing a novel dictionary-based algorithm that uses lexicon-based approach for opinion mining and calculates the sentiment polarity levels. Our algorithm is different from other lexicon-based algorithms in the context that it uses the three degrees of comparisons viz. positive, comparative and superlative degrees on words; for each of the positive and negative sentiment words. Our system yields an Accuracy of 81% and an F-score of 0.874 on the test dataset which is quite moderate and can be fairly accepted.","PeriodicalId":254393,"journal":{"name":"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"26 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":"133872608","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: 8

Empirical survey of machine translation tools 机器翻译工具的实证调查

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813653

Sunita Chand

{"title":"Empirical survey of machine translation tools","authors":"Sunita Chand","doi":"10.1109/ICRCICN.2016.7813653","DOIUrl":"https://doi.org/10.1109/ICRCICN.2016.7813653","url":null,"abstract":"Machine Translation (MT) has progressively evolved since 1940's. It is a topic of active research now a days as the results found so far from machine translation tools are very unrealistic as compared to the human translation. Many different new approaches and techniques have evolved along with the new advent in machine translation. There are different paradigm of machine translation including Statistics Based Machine Translation (SBMT), Rule Based Machine Translation(RBMT), Hybrid machine translation(HMT). Besides these, Neural Network Based Systems have been developed for machine translation [1]. We have not yet imparted the human kind of translation capabilities to the machine. Various online MT tools when tested on various input paragraphs from literature, though performed remarkably good but could hardly translate the sentences comparable to us, the humans. This paper provides a comparative study based on the translation of paragraphs by various online machine translation tools. The tools tested for this research involves rule based systems(Angla Bharti and Anubaad), and statistical systems (Bing, Google translator, IM translate that is supported by Microsoft Translator, Google Translate, Babylon Translator and other MT engines). The results shows that though statistical MT systems outperform the rule based machine translation, but as of yet human mankind is far from achieving its dream of creating a “perfect” automatic translation tool.","PeriodicalId":254393,"journal":{"name":"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"31 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":"122874306","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: 24

A parallel technique for storage defragmentation in cloud 云存储碎片整理的并行技术

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813648

S. Sarkar, A. Kundu

引用次数: 2

A framework to mine communities using nature inspired algorithms 一个使用自然启发算法挖掘社区的框架

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813656

N. Arora, H. Banati

{"title":"A framework to mine communities using nature inspired algorithms","authors":"N. Arora, H. Banati","doi":"10.1109/ICRCICN.2016.7813656","DOIUrl":"https://doi.org/10.1109/ICRCICN.2016.7813656","url":null,"abstract":"Natural intelligence heuristic techniques have demonstrated their capability to provide acceptable solutions to many real life complex problems. Their potential to mine communities from complex networks has been successfully tested by many researchers. With the growing rate of development of new robust and efficient nature based algorithms, a strong need is felt for a generalized framework to evolve communities which can accommodate any existing or new nature based algorithm. This paper proposes a framework for applying natural intelligence based optimization strategies to detect communities using any nature inspired algorithm. The proposed framework can serve as an abstraction for evaluating a set of new/existing nature based methodologies for detecting communities at varied level of optimalities in order to select the most efficient algorithm. Extraction of communities at varied optimality levels by considered algorithms can reveal multiple grouping patterns prevailing in the complex network and can help in planning strategic decision. The framework consists of four prominent, independent phases: The Analysis, Initialization, Evolution and Result Generation Phase. Evaluation of any new/existing metaheuristic or evolutionary algorithm for community detection may be simply done by modifying the Evolution Phase. The framework thus provides an easy to use flexible platform for use by researchers in the domain of community detection.","PeriodicalId":254393,"journal":{"name":"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"15 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":"125381420","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: 0

A simple and efficient solar energy harvesting for wireless sensor node 一种简单高效的无线传感器节点太阳能采集技术

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813638

Manjusha Mangrulkar, S. Akojwar

引用次数: 9

Optimizing MANET routing in AODV: An hybridization approach of ACO and firefly algorithm AODV中MANET路由优化:蚁群算法与萤火虫算法的混合方法

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813643

Subhrapratim Nath, Samriddha Banik, A. Seal, S. Sarkar

{"title":"Optimizing MANET routing in AODV: An hybridization approach of ACO and firefly algorithm","authors":"Subhrapratim Nath, Samriddha Banik, A. Seal, S. Sarkar","doi":"10.1109/ICRCICN.2016.7813643","DOIUrl":"https://doi.org/10.1109/ICRCICN.2016.7813643","url":null,"abstract":"Rapid growth in usage of wireless devices over the year has led to an increased demand of Mobile Ad-Hoc Network (MANET) technology in connecting these devices over a distributed network. Routing in MANET becomes a more challenging area, where constant researches are being conducted to decrease losses and transmission delays between the source and the destination. A new breed of routing protocols based on metaheuristics like Ant-Colony Optimization (ACO) have emerged to provide an alternative solution to route discovery phase in MANET but with the dynamic structure of MANET it has limitation of premature convergence. In this paper we propose a hybridization of the Ant Colony Optimization (ACO) and the Firefly, swarming algorithm (FA) for Ad-Hoc On Demand Distance Vectoring (AODV) routing protocol to increase the efficiency in the transmission of the signals in a MANET system and thereby intending to substantially reduce the losses, so incurred using solely the AODV Routing Protocol and overcome drawbacks of ACO based AODV. We made comparative studies on the proposed hybrid algorithm with the existing routing algorithms (AODV and ACO based AODV) thereby ensuring reduction of network load by avoiding re-discovery attempts between the nodes.","PeriodicalId":254393,"journal":{"name":"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"190 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":"124215186","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: 19

Detecting hotspots in network data based on spectral graph theory 基于谱图理论的网络数据热点检测

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813549

N. RANGA SURI, V. Krishna, K. R. P. Kumar, S. Rakshit

{"title":"Detecting hotspots in network data based on spectral graph theory","authors":"N. RANGA SURI, V. Krishna, K. R. P. Kumar, S. Rakshit","doi":"10.1109/ICRCICN.2016.7813549","DOIUrl":"https://doi.org/10.1109/ICRCICN.2016.7813549","url":null,"abstract":"Detection of hotspots (also known as dense subgraphs) in network data is an important data analysis problem due to it's significance in many contemporary applications. Clique-based formulation of this problem employing maximum flow implementation turns out to be an optimization task limiting the solution to be an approximate one. On the other hand, an iterative method building the hotspots (dense sub-graphs) in an incremental manner starting from primitive graph entities looks more practical and more conducive to incorporating application specific characteristics of interest. Motivated by this idea, we propose a novel algorithm for detecting dense sub-graphs based on spectral graph theory. The underlying principle is that the largest eigenvalue of a graph is a numerical indicator of the inherent dense connectivity. Accordingly, our algorithm starts from the egonets (sub-graphs) of individual nodes and determines the dense egonets as the primitive entities based on their eigenvalues. It then discovers hotspots (dense sub-graphs) through iterative merging of the dense egonets in a controlled manner. Experimental evaluation on benchmark graph data sets demonstrates the efficacy of the proposed method.","PeriodicalId":254393,"journal":{"name":"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"321 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":"115227385","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: 1

Compressed sensing for optimising connectivity in FANET architecture 基于压缩感知的FANET结构连通性优化

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813639

Leena S. Parab, Preetida Vinayakray-Jani

{"title":"Compressed sensing for optimising connectivity in FANET architecture","authors":"Leena S. Parab, Preetida Vinayakray-Jani","doi":"10.1109/ICRCICN.2016.7813639","DOIUrl":"https://doi.org/10.1109/ICRCICN.2016.7813639","url":null,"abstract":"FANET is co-operative, reconfigurable, autonomous network of UAVs. The emerging technology of FANET has many applications in civilian and military field like search and rescue mission, surveillance, reconnaissance, monitoring etc. which create temporary mobile ad-hoc platform for communication and data collection. For such applications, main requirements are maintaining and sustaining connectivity with nodes and effective utilisation of limited resources like bandwidth. Further, as the UAVs are moving with very high velocity, their topology changes rapidly and hence connectivity among them may lose. To address this problem, usage of novel technique called compressed sensing is proposed. In compressed sensing method, instead of sampling the signal by Nyquist rate, signal is sampled by Sub-Nyquist rate i.e. sampling rate less than Nyquist rate. Thus, few samples are transmitted and signal can be recovered by using convex optimisation technique. In FANET, number of UAVs are few. Hence, number of frequencies occupied will be sparse as compared to available wide spectrum band. In this paper, sparsity in form of number of UAVs is exploited and compressed sensing is implemented on coordination information which is shared between nodes.","PeriodicalId":254393,"journal":{"name":"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"27 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":"128488171","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: 4

An approach towards image, audio and video steganography 图像、音频和视频隐写的一种方法

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813675

Kunal Hossain, R. Parekh

引用次数: 8