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Journal Cover International Journal of Research in Computer and Communication Technology
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  This is an Open Access Journal Open Access journal
   ISSN (Print) 2320-5156 - ISSN (Online) 2278-5841
   Published by Suryansh Publications Homepage  [2 journals]
  • A Grid Tied SPV System with Adaptive DC Link Voltage for CPI Voltage
           Variations using Fuzzy Logic Control

    • Authors: Seetha Akella, S. Narasimha
      Abstract: -- This proposed model manages a three-stage two-organize grid tied SPV (sunlight based photograph voltaic) framework. The main stage is a help converter, which fills the need of MPPT (most extreme power point following) and sustaining the removed sunlight based vitality to the DC connection of the PV inverter, while the second stage is a two-level VSC (voltage source converter) serving as PV inverter which bolsters control from a support converter into the matrix. The point of this controller is to accomplish an ideal MPP operation without the need of barometrical conditions estimations and to improve the productivity of the PV control framework. This model likewise utilizes a versatile DC connect voltage which is made versatile by modifying reference DC interface voltage as per CPI (regular purpose of interconnection) voltage. The versatile DC connect voltage control helps in the decrease of exchanging force misfortunes. A sustain forward term for sun oriented commitment is utilized to enhance the dynamic reaction.   A photovoltaic (PV) framework can create wide scopes of voltage and current at terminal yield. Be that as it may, a PV cell is required to practically keep up a consistent direct present (DC) voltage at a craved level amid constant varieties . To get this objective, a DC/DC converter together with control plot topology is utilized. A versatile PI control plan is proposed to settle the yield voltage of the DC/DC converter, with a specific end goal to keep up and balance out the Adaptive DC-connect voltage in like manner to the progressions of voltage at the Common Point of Interconnection before the framework.   The Point of Common Coupling is a point in the electrical framework where various clients or numerous electrical burdens might be associated. This ought to be a guide which is open toward both the utility and the client for direct estimation. Extensive quantities of little scale sunlight based photovoltaic (PV) frameworks are being associated with the appropriation level of the power lattice PV frameworks are incorporated to the power network by means of force electronic converters. The model is tried considering reasonable matrix voltage varieties for under voltage varieties. This model is profitable not just in instances of incessant and managed under voltage (as in the instances of far outspread closures of Indian framework) additionally in the event of ordinary voltages at CPI. The THD (add up to music bending) of lattice current has been discovered well under the farthest point of an IEEE-519 standard. The approval of the proposed MPPT controller is appeared by MATLAB/SIMULINK reproduction.
      PubDate: 2017-01-04
      Issue No: Vol. 5 (2017)
  • Judicial Precedents Search Process supported by Similarity Measures

    • Authors: B.Basaveswar Rao, B.V. RamaKrishna, K. Chandan, K. Chandan
      Abstract: In this paper an attempt is made to improve the judicial precedent search process. One of the judicial precedents is legal documents generated based on previous judgments. The objective of this work is to suggest the top ten ready reference precedents among the precedent judgments for legal stakeholders, using Cosine and proposed Word Frequency similarity measures. This search refinement process, the Legal Bag-of-Word set is used to identify the most similar judgment for given dowry crime related FIR sheet (report made by an investigation officer for any cognitive offense). It helps the legal stake holders in decision making mechanism, which is effective from both the time and accuracy prospective. By using the Cosine and WFS similarity measures the top most 10 related word matched precedent judgments are arranged in a similarity measure rank order. The most high order similarity ranked precedent judgment is considered as best judgment for related to dowry crime. The similarity search process (SSP) results are assessed by legal experts about the coherence factor between the FIR investigation views and top ten ranked precedent judgment case notes with a 5-point scale. The paired T-test is adopted to identify the any significant difference between the experts opinion on degree of coherence factor and SSP results. This study suggest that the legal stakeholders adopted this BoW and apply the cosine or WFS similarity process to identify most related precedent judgments for their dowry related crime legal proceedings.
      PubDate: 2017-01-01
      Issue No: Vol. 5 (2017)
  • Recent Developments for Interference Mitigation in Cognitive Radio

    • Authors: Deepak Kumar Mahapatro, Ramesh Kumar Sahoo, Bichitra Mandal
      Abstract: Cognitive radio networks (CRNs) has emerged as a promising technology for wireless networks, in order to overcome the underutilization problem of the licensed spectrum bands. Its major difference from the traditional wireless networks is that here needy unlicensed users are allowed to access the channel. But they shouldn’t pose any type of harmful interference to the primary users i.e. the licensed users. But with this distinct feature of CRNs, an essential and challenging question raised, i.e. how to estimate interference accurately at the primary users end as well as from the secondary users side. Interference is an effect caused by the superposition of two systems of waves, such as a distortion on a broadcast signal due to atmospheric or other effects. In this paper, we studied about various factors those are causing interference to the wireless signals of cognitive radio networks and also different recent techniques developed for minimizing interference.
      PubDate: 2017-01-01
      Issue No: Vol. 5 (2017)
  • Optimized Cognitive Radio Network (CRN) using Genetic Algorithm: A Survey

    • Authors: Sangita Pal, Bichitra Mandal
      Abstract: Genetic algorithm technique based optimization depend on open relationships involving several reasons or criterion, interpretations and various constraints. It when implemented on cognitive radio, provides a criteria to put up the secondary users in best available space by communicating with the environment at real time.  In this paper genetic algorithm along with selection, crossover and mutation parameters are implemented in cognitive radio in order to obtain the optimum radio configurations and hence the performance increases. The main advantage of genetic algorithm is the capability of handling multiple objectives.
      PubDate: 2017-01-01
      Issue No: Vol. 5 (2017)
  • Solving Target Coverage Problem in Wireless Sensor Networks using Greedy

    • Authors: Jagadish Sahoo, Bibhudatta Sahoo, Saroja Nanda Mishra
      Abstract: One of the critical aspect of wireless sensor networks is network life time. In Wireless Sensor Networks (WSNs) a large number of  sensor nodes are deployed  for monitoring the environment. Sensors can collect data from the environment. The data collected are then forwarded to the base station(sink node).  Since these task of data collection and transmission is energy consuming, effective scheduling scheme can be used extend  lifetime of the network. Sometime deterministic deployment is not feasible to monitor targets. In this situation random deployment is used. Information about the sensor deployment position may loss in random deployment. To take care about this situation , density of deployed sensors can be increased. In our paper we propose an algorithm to extend the lifetime of WSNs. Lifetime can be increased by placing the sensors in different set covers. Sensors in different set covers may be in active state or in sleep mode Sensors in  active state are responsible for monitoring the targets. This problem is called Maximum Set Cover Problem. This is an optimization problem and is NP- complete. So, to get a suboptimal solution, we have proposed a greedy based heuristics for scheduling the sensors so that network lifetime can be maximized.
      PubDate: 2017-01-01
      Issue No: Vol. 5 (2017)
  • Scalable Big Data Analysis in Cloud Environment: A Review

    • Authors: Bichitra Mandal, Ramesh K. Sahoo, Srinivas Sethi
      Abstract: The mounting of industrial advancements have led to substantial quantity of data from unusual areas, like health care, user- generated data, internet, financial companies etc. The term big data was discovered to confine the significance of this rising trend. Due to its complete volume, big data exhibits exclusive personality as comparison to traditional data. Big data may be structured, unstructured or semi-structured which requires more analysis. Its processing is achieved due to its high volume, velocity, value, variety and veracity. It has a lot of Challenges. Thus, cloud computing is being deployed in order to regulate the big data requirements. The security and privacy is not well maintained in cloud. Big data systems are decomposed into four modules called data generation, data acquisition, data storage and data analysis. These modules are otherwise known as big data value chain. Big data is widely established in these recent years, and implemented Hadoop framework for addressing big data challenges.
      PubDate: 2017-01-01
      Issue No: Vol. 5 (2017)
  • Impact of Hurst parameter value in self-similarity behaviour of network

    • Authors: Lakhmi Priya Das, Sanjay Kumar Patra, Sarojananda Mishra
      Abstract: The internet performance is bounded to the properties of TCP [2]  and UDP protocols, jointly responsible for the delivery of the larger internet traffic. On internet, high self-similarity is fetched by multimedia data traffic. Self similar ofLRD properties can be articulatedwith the Hurst Parameter. Numerous current studies of real tele-traffic data in computer networks have made knownfacts of self-similarity. For self-similar processes, the Hurst parameter ‘H’ is essential. Hence, Hurst parameter estimation is a set of values with a sequence in vital estimation of self-similarity.The Hurst parameter has receivedgreat attention in recent review. In the text there are two fundamental methods described to calculate Hurst parameter, respectively R/S statistics analysis and Periodogram analysis. The analysis result we put in this paper.
      PubDate: 2017-01-01
      Issue No: Vol. 5 (2017)
  • Body Neural System Interfacing Techniques in Digital Forensics

    • Authors: Alok R. Prusty, Subhasmita Mishra
      Abstract: Digital forensics involves the technique in which it solves the crimes by using digital devices. Main aim of this method is to preserve any indication in its original form while performing investigation by gathering, ascertaining and authenticating the digital information for recognizing past events. Brain is such a part of the body neural system which generates, sends and receives enormous number of signals and controls many activities of body. Hence, to read the face of any activities or crime; reading and interfacing of brain is essential in crime and criminal detection process. This paper will focus some of such techniques.
      PubDate: 2017-01-01
      Issue No: Vol. 5 (2017)
  • Recognition and Enhancement of Speech under Noisy Conditions

    • Authors: Sai Rukmini Sahu, Janmejaya Rout
      Abstract: In this work we can see the influence of stress on speech signal and compare the features such as MFCC, LAR, LPC and recognize the speech using Vector Quantization (VQ) method under stressed or noisy conditions. The main objective of this paper is to robust the speech in diverse conditions and to get a robust speech we have to reduce the noise and enhance the speech. Here we have used Adaptive winner filter with DD,TSNR and HRNR methods for enhancement of noisy speech(car, babble, street noise) by considering SNR of 0 dB,5 dB and 10 dB conditions and compared the method by considering CD (Cepstral Distance) and segmental SNR.
      PubDate: 2017-01-01
      Issue No: Vol. 5 (2017)
  • The Optimization of Mining Association Rules in Distributed Databases

    • Authors: Eswara Venkata Sai Vimal Nath, K Satyanarayana Murthy
      Abstract: Data mining is utilized to separate critical learning from expansive datasets, yet in some cases these datasets are part among different gatherings. Affiliation standard mining is one of the data mining procedure utilized as a part of dispersed databases. This strategy uncover some intriguing relationship between locally huge and all around vast thing sets and proposes a calculation, fast distributed mining of association rules (FDM), which is an unsecured conveyed rendition used to produces a little number of applicant sets and significantly decreases the quantity of messages to be passed at mining affiliation rules. Furthermore, it is more straightforward and altogether more productive as far as correspondence rounds, correspondence cost and computational expense. The proposed work depicts the streamlining of Association Rule for the dispersed databases as far as pace, memory utilized while exchange of conveyance and in addition separating the data from different data sources in the system. The proposed work should including appropriation of data utilizing Association lead and guaranteeing the pursuit to be diverted to particular source in light of key qualities used to make the sub set in affiliation guideline. The accessibility should be tried by checking if the particular source is prepared or not if not the quest for that part might just be completed on the server itself.
      PubDate: 2016-12-25
      Issue No: Vol. 5 (2016)
  • Exploitation of Sentiment Analysis in Twitter Data utilizing Machine
           Learning Techniques

    • Authors: A.V.L.P Bharat, K Satyanarayana Murthy
      Abstract: Sentiment analysis is an extremely important procedure these days for social Network analysis. Sentiment analysis or assessment mining is the procedure of consequently separating information from notions or suppositions of others about some subject or issue. We can recognize suppositions in a substantial unstructured/organized information and investigate extremity of sentiments. Twitter is a vast and quickly becoming small scale blogging long range informal communication site where individuals express their assessments in short and straightforward way of expressions. Tweets can be broke down to perform conclusion analysis on different substances. In this paper we concentrate on various methodologies utilized for sentiment analysis of twitter information. Informal communication destinations like Twitter, Facebook, Google+ are quickly picking up fame as they permit individuals to share and express their perspectives about points, have talk with various groups, or post messages over the world. In this paper, we give a study and a relative analysis’s of existing methods for sentiment mining like machine learning and vocabulary based methodologies, together with assessment measurements. Utilizing different machine learning calculations like Naive Bayes, Max Entropy, and Support Vector Machine, we give research on twitter information streams. We have likewise talked about general difficulties and utilizations of Sentiment Analysis on Twitter.
      PubDate: 2016-12-25
      Issue No: Vol. 5 (2016)
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
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Fax: +00 44 (0)131 4513327
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