Pub Date : 2014-12-01DOI: 10.1109/ICCCT2.2014.7066711
M. Ramana Rao, T. Adilakshmi
Routing in Wireless Sensor Networks (WSNs) is an emerging research area. This paper presents a survey of routing techniques in WSNs which support node mobility. In recent years, advancement in WSNs lead to the development of many routing protocols specifically designed for WSNs. The routing protocols discussed in this paper in general can be four main category such as Network structure, Communication model, Topology based and reliable routing. Existing routing protocols in WSNs mostly addresses static nodes. This paper presents routing protocols which support Node mobility and compares them with certain criteria. Finally, the paper concludes with future research related to network layer issues such as routing with node mobility.
{"title":"A limelight on routing techniques in Wireless Sensor Networks with node mobility","authors":"M. Ramana Rao, T. Adilakshmi","doi":"10.1109/ICCCT2.2014.7066711","DOIUrl":"https://doi.org/10.1109/ICCCT2.2014.7066711","url":null,"abstract":"Routing in Wireless Sensor Networks (WSNs) is an emerging research area. This paper presents a survey of routing techniques in WSNs which support node mobility. In recent years, advancement in WSNs lead to the development of many routing protocols specifically designed for WSNs. The routing protocols discussed in this paper in general can be four main category such as Network structure, Communication model, Topology based and reliable routing. Existing routing protocols in WSNs mostly addresses static nodes. This paper presents routing protocols which support Node mobility and compares them with certain criteria. Finally, the paper concludes with future research related to network layer issues such as routing with node mobility.","PeriodicalId":6860,"journal":{"name":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"44 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76905591","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}
Pub Date : 2014-12-01DOI: 10.1109/ICCCT2.2014.7066728
N. Pujari, M. Kothari
Security and its related ecosystem have always been given priority in the form of procedures, policies, technology and research. Technology as an assisting component in case of security plays a major role in identifying lapses, loopholes and thus prevent situations to turn into catastrophes. Video surveillance these days has gained significant importance for keeping any place secure. Video cameras are being installed in public places such as malls, theatres, railway stations, super markets, airports and so on. Security personnel monitor these camera feeds from the control centre to observe unobvious entities and manually label the suspected frames. This sometimes turn into lapses due to oversight, fatigue, and negligence because of manual surveillance. This work carried out attempts to overcome these limitations by automating identification of unobvious entities from real time and offline video streams by using the proposed computer vision algorithm. It also proposes to indicate the relative suspicious activity in each frame on a scale of 1 to 10 using the concept of suspectMeter. In addition this algorithm also proposes to reduce the space required for storing suspected frame(s).
{"title":"A novel approach to identify unobvious entities from real time and offline video streaming","authors":"N. Pujari, M. Kothari","doi":"10.1109/ICCCT2.2014.7066728","DOIUrl":"https://doi.org/10.1109/ICCCT2.2014.7066728","url":null,"abstract":"Security and its related ecosystem have always been given priority in the form of procedures, policies, technology and research. Technology as an assisting component in case of security plays a major role in identifying lapses, loopholes and thus prevent situations to turn into catastrophes. Video surveillance these days has gained significant importance for keeping any place secure. Video cameras are being installed in public places such as malls, theatres, railway stations, super markets, airports and so on. Security personnel monitor these camera feeds from the control centre to observe unobvious entities and manually label the suspected frames. This sometimes turn into lapses due to oversight, fatigue, and negligence because of manual surveillance. This work carried out attempts to overcome these limitations by automating identification of unobvious entities from real time and offline video streams by using the proposed computer vision algorithm. It also proposes to indicate the relative suspicious activity in each frame on a scale of 1 to 10 using the concept of suspectMeter. In addition this algorithm also proposes to reduce the space required for storing suspected frame(s).","PeriodicalId":6860,"journal":{"name":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"68 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90955060","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}
Pub Date : 2014-12-01DOI: 10.1109/ICCCT2.2014.7066710
S. Nallagonda, Mahendar Gajula, Sanjay Dhar Roy, S. Kundu
In the present article, the cooperative spectrum sensing with a weighted fusion (WCSS) scheme has been analyzed in Rayleigh fading. Cognitive radio (CR) uses an improved energy detector (IED) with several antennas. Antenna selection diversity combining (SC) is performed at each CR on the basis of the values of decision statistics measured from different antennas at IED. Every CR takes 1-bit decision regarding primary user (PU) and sends its decision to fusion center (FC) with binary phase shift keying (BPSK) signaling if FC selects that CR to send. The FC estimates weight factors of selected CRs with the help of a profile of average SNRs and incorporated with decisions of each selected CR. The missed detection performance is evaluated for different values of improved detector parameter with different number of antennas, average SNRs of sensing (S) and reporting (R) channels. WCSS with censoring performance is also analyzed for perfect and imperfect estimation cases. Combined censoring and weighted fusion significantly improves the spectrum sensing performance.
{"title":"Combined censoring and weighted fusion based spectrum sensing with improved energy detector","authors":"S. Nallagonda, Mahendar Gajula, Sanjay Dhar Roy, S. Kundu","doi":"10.1109/ICCCT2.2014.7066710","DOIUrl":"https://doi.org/10.1109/ICCCT2.2014.7066710","url":null,"abstract":"In the present article, the cooperative spectrum sensing with a weighted fusion (WCSS) scheme has been analyzed in Rayleigh fading. Cognitive radio (CR) uses an improved energy detector (IED) with several antennas. Antenna selection diversity combining (SC) is performed at each CR on the basis of the values of decision statistics measured from different antennas at IED. Every CR takes 1-bit decision regarding primary user (PU) and sends its decision to fusion center (FC) with binary phase shift keying (BPSK) signaling if FC selects that CR to send. The FC estimates weight factors of selected CRs with the help of a profile of average SNRs and incorporated with decisions of each selected CR. The missed detection performance is evaluated for different values of improved detector parameter with different number of antennas, average SNRs of sensing (S) and reporting (R) channels. WCSS with censoring performance is also analyzed for perfect and imperfect estimation cases. Combined censoring and weighted fusion significantly improves the spectrum sensing performance.","PeriodicalId":6860,"journal":{"name":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"1 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91345085","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}
Pub Date : 2014-12-01DOI: 10.1109/ICCCT2.2014.7066697
N. P. Jilhedar, S. Shirgave
Web sites have abundant web usage log which provides useful information that can be used for user navigation improvisation. Traditional web site does not use this rich web usage data for any investigation. It can be used to generate efficient frequent patterns which can support in user navigation improvisation. It can also be help in re-organizing web site for efficient navigation. In this paper we propose a frequent pattern generation approach using semantic relations with user web usage data. The quality of web usage pattern generated is measured with standards methods for evaluation. Experiment results show that more precise presentation using user pattern generation can improve user navigation measures.
{"title":"User Web Usage Mining for navigation improvisation using semantic related frequent patterns","authors":"N. P. Jilhedar, S. Shirgave","doi":"10.1109/ICCCT2.2014.7066697","DOIUrl":"https://doi.org/10.1109/ICCCT2.2014.7066697","url":null,"abstract":"Web sites have abundant web usage log which provides useful information that can be used for user navigation improvisation. Traditional web site does not use this rich web usage data for any investigation. It can be used to generate efficient frequent patterns which can support in user navigation improvisation. It can also be help in re-organizing web site for efficient navigation. In this paper we propose a frequent pattern generation approach using semantic relations with user web usage data. The quality of web usage pattern generated is measured with standards methods for evaluation. Experiment results show that more precise presentation using user pattern generation can improve user navigation measures.","PeriodicalId":6860,"journal":{"name":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"46 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79101824","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}
Pub Date : 2014-12-01DOI: 10.1109/ICCCT2.2014.7066748
E. B. Krishna, B. Rama, A. Nagaraju
Extraction of interesting negative association rules from large data sets is measured as a key feature of data mining. Many researchers discovered numerous algorithms and methods to find out negative and positive association rules. From the existing approaches, the frequent pattern growth (FP-Growth) approach is well-organized and capable method for finding the item sets which are frequent, without the generation of candidate item sets. The drawback of FP-Growth is it discovers a huge amount of conditional FP-Tree. We propose a novel, improved FP-Tree for extracting negative association rules without generating conditional FP-Tree.
{"title":"Mining of negative association rules using improved frequent pattern tree","authors":"E. B. Krishna, B. Rama, A. Nagaraju","doi":"10.1109/ICCCT2.2014.7066748","DOIUrl":"https://doi.org/10.1109/ICCCT2.2014.7066748","url":null,"abstract":"Extraction of interesting negative association rules from large data sets is measured as a key feature of data mining. Many researchers discovered numerous algorithms and methods to find out negative and positive association rules. From the existing approaches, the frequent pattern growth (FP-Growth) approach is well-organized and capable method for finding the item sets which are frequent, without the generation of candidate item sets. The drawback of FP-Growth is it discovers a huge amount of conditional FP-Tree. We propose a novel, improved FP-Tree for extracting negative association rules without generating conditional FP-Tree.","PeriodicalId":6860,"journal":{"name":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"9 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73315748","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}
Pub Date : 2014-12-01DOI: 10.1109/ICCCT2.2014.7066723
B. Surekha, B. Ravi, G. Swamy
Digital image copyright protection techniques have drawn substantial interest from the research community for the last two decades. In particular, Copyright Protection schemes based on Visual Cryptography (CPVC) are designed to protect sensitive images without degrading the quality of host images. In this paper, the security of one such CPVC scheme proposed by A. Nag et al. is analyzed. We demonstrate that this technique is insecure as it leads to high ambiguity in detecting the right owner. This is proved by means of theoretical analysis and by conducting false positive tests.
{"title":"Security analysis of ‘A novel copyright protection scheme using Visual Cryptography’","authors":"B. Surekha, B. Ravi, G. Swamy","doi":"10.1109/ICCCT2.2014.7066723","DOIUrl":"https://doi.org/10.1109/ICCCT2.2014.7066723","url":null,"abstract":"Digital image copyright protection techniques have drawn substantial interest from the research community for the last two decades. In particular, Copyright Protection schemes based on Visual Cryptography (CPVC) are designed to protect sensitive images without degrading the quality of host images. In this paper, the security of one such CPVC scheme proposed by A. Nag et al. is analyzed. We demonstrate that this technique is insecure as it leads to high ambiguity in detecting the right owner. This is proved by means of theoretical analysis and by conducting false positive tests.","PeriodicalId":6860,"journal":{"name":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"11 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80278090","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}
Pub Date : 2014-12-01DOI: 10.1109/ICCCT2.2014.7066707
Kartheek Boddireddy, B. P. Kumar, C. Paidimarry
Adders play an important role in digital circuits. Logarithmic adders are efficient in delay reduction of carry generation/propagation in contrary to linear adders. It is found from simulations that even logarithmic adders suffer from delay, chip area over head and additional latches in the presence of ripple carry adders at the time of FPGA realization. The main motive of this work is to design and develop optimizeddelay free adders by introducing the proposed leaf adder module. In this work, we propose optimized Kogge-Stone and Spanning tree adders based on carry-tree architecture. Our designs are simulated using Verilog HDL and implemented on Xilinx Virtex-5 FPGA for real time verification. Performance metrics such as delay and chip area are evaluated using our numerical simulations. It is shown from results that our optimized Kogge-Stone and Spanning tree adders achieve 13.9% and 1.5 % reduction in delay: 24% and26.5% in LUT reduction; and 25.9% and 23.8% in slice reduction respectively, compared to existing tree adders.
{"title":"Design and implementation of area and delay optimized carry tree adders using FPGA","authors":"Kartheek Boddireddy, B. P. Kumar, C. Paidimarry","doi":"10.1109/ICCCT2.2014.7066707","DOIUrl":"https://doi.org/10.1109/ICCCT2.2014.7066707","url":null,"abstract":"Adders play an important role in digital circuits. Logarithmic adders are efficient in delay reduction of carry generation/propagation in contrary to linear adders. It is found from simulations that even logarithmic adders suffer from delay, chip area over head and additional latches in the presence of ripple carry adders at the time of FPGA realization. The main motive of this work is to design and develop optimizeddelay free adders by introducing the proposed leaf adder module. In this work, we propose optimized Kogge-Stone and Spanning tree adders based on carry-tree architecture. Our designs are simulated using Verilog HDL and implemented on Xilinx Virtex-5 FPGA for real time verification. Performance metrics such as delay and chip area are evaluated using our numerical simulations. It is shown from results that our optimized Kogge-Stone and Spanning tree adders achieve 13.9% and 1.5 % reduction in delay: 24% and26.5% in LUT reduction; and 25.9% and 23.8% in slice reduction respectively, compared to existing tree adders.","PeriodicalId":6860,"journal":{"name":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"22 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85819465","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}
Pub Date : 2014-12-01DOI: 10.1109/ICCCT2.2014.7066747
R. Raj, G. Raju
Many tools and frameworks have been developed to process data on distributed data centers. MapReduce most prominent among such frameworks has emerged as a popular distributed data processing model for processing vast amount of data in parallel on large clusters of commodity machines. The JobTracker in MapReduce framework is responsible for both managing the cluster's resources and executing the MapReduce jobs, a constraint that limits scalability, resource utilization. YARN the next-generation execution layer for Hadoop splits processing and resource management capabilities of JobTracker into separate entities and eliminates the dependency of Hadoop on MapReduce. This new model is more isolated and scalable compared to MapReduce, providing improved features and functionality. This paper discusses the design of YARN and significant advantages over traditional MapReduce.
{"title":"An approach for optimization of resource management in Hadoop","authors":"R. Raj, G. Raju","doi":"10.1109/ICCCT2.2014.7066747","DOIUrl":"https://doi.org/10.1109/ICCCT2.2014.7066747","url":null,"abstract":"Many tools and frameworks have been developed to process data on distributed data centers. MapReduce most prominent among such frameworks has emerged as a popular distributed data processing model for processing vast amount of data in parallel on large clusters of commodity machines. The JobTracker in MapReduce framework is responsible for both managing the cluster's resources and executing the MapReduce jobs, a constraint that limits scalability, resource utilization. YARN the next-generation execution layer for Hadoop splits processing and resource management capabilities of JobTracker into separate entities and eliminates the dependency of Hadoop on MapReduce. This new model is more isolated and scalable compared to MapReduce, providing improved features and functionality. This paper discusses the design of YARN and significant advantages over traditional MapReduce.","PeriodicalId":6860,"journal":{"name":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"13 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88772235","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}
Pub Date : 2014-12-01DOI: 10.1109/ICCCT2.2014.7066696
Sunitha Vanamala, L. P. Sree, S. Bhavani
The immense volumes of data is populated into repositories from various applications. More over data arrives into the repositories continuously i.e. stream of data that cannot be stored into repository due to its varying characteristics. Frequent itemset mining is thoroughly studied by many researchers but important rare items are not discovered by these algorithms. In many cases, the contradictions or exceptions also offers useful associations. In the recent past the researchers started to focus on the discovery of such kind of associations called rare associations. Rare itemsets can be obtained by setting low support but generates huge number of rules. The rare association rule mining is a challenging area of research on data streams. In this paper we proposed an idea to analyze the data stream to identify interesting rare association rules. Rare association rule mining is the process of identifying associations that are having low support but occurs with high confidence. The rare association rules are useful for many applications such as fraudulent credit card usage, anomaly detection in networks, detection of network failures, educational data, medical diagnosis etc. The proposed rare association rule mining algorithm for data stream is implemented using sliding window technique over a stream of data, data is represented in vertical bit sequence format. The advantage of proposed algorithm is that it requires single scan to discover all rare associations. The proposed algorithm outperforms both in terms of memory and time.
{"title":"Rare association rule mining for data stream","authors":"Sunitha Vanamala, L. P. Sree, S. Bhavani","doi":"10.1109/ICCCT2.2014.7066696","DOIUrl":"https://doi.org/10.1109/ICCCT2.2014.7066696","url":null,"abstract":"The immense volumes of data is populated into repositories from various applications. More over data arrives into the repositories continuously i.e. stream of data that cannot be stored into repository due to its varying characteristics. Frequent itemset mining is thoroughly studied by many researchers but important rare items are not discovered by these algorithms. In many cases, the contradictions or exceptions also offers useful associations. In the recent past the researchers started to focus on the discovery of such kind of associations called rare associations. Rare itemsets can be obtained by setting low support but generates huge number of rules. The rare association rule mining is a challenging area of research on data streams. In this paper we proposed an idea to analyze the data stream to identify interesting rare association rules. Rare association rule mining is the process of identifying associations that are having low support but occurs with high confidence. The rare association rules are useful for many applications such as fraudulent credit card usage, anomaly detection in networks, detection of network failures, educational data, medical diagnosis etc. The proposed rare association rule mining algorithm for data stream is implemented using sliding window technique over a stream of data, data is represented in vertical bit sequence format. The advantage of proposed algorithm is that it requires single scan to discover all rare associations. The proposed algorithm outperforms both in terms of memory and time.","PeriodicalId":6860,"journal":{"name":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"28 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91013614","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}
Pub Date : 2014-12-01DOI: 10.1109/ICCCT2.2014.7066724
K. Shreedhar, D. Bhukya, Shubham Hariom
The focus on R&D planning is gaining importance due to the ever increasing investments made in the sector as realisation has dawned upon the decision makers that investments are bound to generate benefits at a later stage. For better R&D planning, it is imperative that tools and mechanisms, particularly with the explosion of data due to the advancement in information and communication technologies (ICT), need to be developed and adopted, systematically. This paper aims to introduce Plan-Informatics approach to R&D planning that would help a nation in devising a framework for evidence based planning in R&D .The proposed Plan-Informatics approach would be more suitable in the era of big data and data centric `fourth paradigm' of scientific discovery. The Plan-Informatics will capture, accurate, analyse and visualise the big data and provide an approach towards holistic decision making and action for a long-term R&D plan of a nation.The paper also attempts to develop a Plan-Informatics framework for government sector to better utilise big data and near to real time data for effective decision making.
{"title":"R&D Plan-Informatics in the era of big data","authors":"K. Shreedhar, D. Bhukya, Shubham Hariom","doi":"10.1109/ICCCT2.2014.7066724","DOIUrl":"https://doi.org/10.1109/ICCCT2.2014.7066724","url":null,"abstract":"The focus on R&D planning is gaining importance due to the ever increasing investments made in the sector as realisation has dawned upon the decision makers that investments are bound to generate benefits at a later stage. For better R&D planning, it is imperative that tools and mechanisms, particularly with the explosion of data due to the advancement in information and communication technologies (ICT), need to be developed and adopted, systematically. This paper aims to introduce Plan-Informatics approach to R&D planning that would help a nation in devising a framework for evidence based planning in R&D .The proposed Plan-Informatics approach would be more suitable in the era of big data and data centric `fourth paradigm' of scientific discovery. The Plan-Informatics will capture, accurate, analyse and visualise the big data and provide an approach towards holistic decision making and action for a long-term R&D plan of a nation.The paper also attempts to develop a Plan-Informatics framework for government sector to better utilise big data and near to real time data for effective decision making.","PeriodicalId":6860,"journal":{"name":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"9 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82894298","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}
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