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Sakthivel, S.
- Streaming the Media Files on Heterogeneous Wireless Networks (HWN's)
Abstract Views :131 |
PDF Views:3
Authors
S. Sakthivel
1,
E. Kannan
1
Affiliations
1 Vel Tech Dr.RR & Dr.SR Technical University, Avadi, Chennai-62, IN
1 Vel Tech Dr.RR & Dr.SR Technical University, Avadi, Chennai-62, IN
Source
Wireless Communication, Vol 4, No 12 (2012), Pagination: 674-679Abstract
Heterogeneous wireless network with multi-home clients combine various wireless technologies and provide universal access. Nowadays these wireless networks which is accessed by portable devices with multiple interfaces to access Internet. Recently previous work has mainly focused on reducing access delay and power consumption for data broadcast in wireless network. In this paper, we propose a new data broadcast mechanism with network coding in heterogeneous wireless networks. Our mechanism adaptively clusters the mobile hosts in fewer cells to minimize the bandwidth consumption. In addition, we adaptively code the data according to the data temporarily stored in each mobile host with a distributed manner. Our mechanism allows each delivered message to be coded from only a subset of data to further reduce the number of required messages. We formulate the cell selection and broadcast coding problem with integer programming and prove that the problem is NP-hard. We design a distributed algorithm based on LaGrange and relaxation. Our algorithm needs no server to record the location, queried, and stored information of receivers. Moreover, our algorithm is adaptive to the dynamic group membership, mobility, queried, and stored data of receivers.Keywords
Cell Selection Problem (Cop), Broadcast Coding Problem (Bop), Data Broadcast Mechanism, Bandwidth Consumption and Streaming.
- Performance Analysis of Adaptive Hysteresis Current Controlled Inverter for Solar Power Applications
Abstract Views :164 |
PDF Views:4
Authors
Affiliations
1 EEE Department, Kalasalingam University, Virudhunagar District, Tamilnadu, IN
2 PSNA College of Engineering, Dindugal, Tamilnadu, IN
1 EEE Department, Kalasalingam University, Virudhunagar District, Tamilnadu, IN
2 PSNA College of Engineering, Dindugal, Tamilnadu, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 4, No 6 (2012), Pagination: 374-379Abstract
Inverters are used in solar photovoltaic (PV) system to convert the D.C power produced by the solar photovoltaic cell into AC. This paper presents a novel Adaptive Hysteresis Current Controller to control the inverter used in the solar photovoltaic system. The proposed controller is capable of reducing the total harmonic distortion and to provide constant switching frequency. The mathematical model of Photovoltaic array is developed using Newton’s method. The modeled Photovoltaic array is interfaced with DC-DC boost converter, AC-DC inverter and load. A DC-DC boost converter is used to step up the input DC voltage, the inverter converts the DC voltage into AC. The inverter is controlled by the proposed current controller. The performance of the proposed controller is evaluated through MATLAB/Simulation. The results obtained with the proposed algorithm are compared with those obtained when using conventional fixed hysteresis current controller in terms of THD and switching frequency.Keywords
Photovoltaic Cell, Adaptive Hysteresis Controller, Boost Converter, Inverter.- Multilevel Modeling in Heterogeneous Wireless Sensor Network for Improved Energy Efficiency
Abstract Views :186 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science and Engineering, Gnanamani College Technology, IN
1 Department of Computer Science and Engineering, Gnanamani College Technology, IN
Source
ICTACT Journal on Communication Technology, Vol 10, No 1 (2019), Pagination: 1958-1963Abstract
In this paper, two primary and secondary parameters are proposed for a heterogeneous network model (HNM). In such a model, the heterogeneous network describes nodes with a finite energy level based on the parameter value. It evaluates the performance of the proposed HNM protocol and further tests the HNM multilevel protocol. For a finite heterogeneity level MHNM protocol is denoted by MLHNM-n. The secondary parameter determines the total nodes at each level of heterogeneity. The proposed protocol provides two parameters for determining the energy and density of the cluster heads of residual nodes. The proposed protocol will be tested by six level networks. The energy dissipation decreases and results in an increase in network life.Keywords
Network Lifetime, Multi Heterogeneity, Number of Rounds, Clustering.References
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- D. Kumar, “Performance Analysis of Energy Efficient Clustering Protocols for Maximising Lifetime of Wireless Sensor Networks”, IET Wireless Sensor Systems, Vol. 4, No. 1, pp. 9-16, 2014.
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- Adaptive Word Embedding to Reduce the Dimensionality of the Document to Vector Representation
Abstract Views :136 |
PDF Views:0
Authors
Affiliations
1 Assistant Professor, Department of Information Technology, M.Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
2 UG Scholar, Department of Information Technology, M.Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
1 Assistant Professor, Department of Information Technology, M.Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
2 UG Scholar, Department of Information Technology, M.Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
Source
International Journal of Emerging Trends in Science & Technology, Vol 6, No 2 (2020), Pagination: 38-41Abstract
Sentiment Analysis is a methodology of detecting the emotions from the text. It is an application of Natural Language Processing (NLP) methodology. The NLP enables us to know the common day to day language of the people. This will helps to decipher the sentiments of the users and hence explain liking and disliking of the people. The traditional bag-of-words models lack the accuracy of sentiment classifications. The intention of this project is to improve the accuracy of the sentiment classification by employing the concept of dimensionality reduction. Reducing the dimensionality of a large document helps to reduce the computational cost and increase efficiency. Word embedding methods capture the context of a word in a document which helps to reduce the dimensionality of text data. Vector representation of the words using a technique like Word2Vector proves to be very effective in interpreting the meaning and hence the sentiments. The words in the document will be converted into vectors. Each word is assigned a unique value (vectors) such that these vectors represent its context, meaning, and semantics. The resulting word vectors are wont to train machine learning algorithms within the sort of classifiers for sentiment classification. We use the Machine Learning classifier Naive Bayes to analyze the sentiment from the given pre-processed dataset (word vectors). Our experiments on real-world datasets show the improvement in the accuracy of sentiment classification using the word embedding techniques.Keywords
Dimensionality Reduction, Sentiment Analysis, Vector Representation, Word EmbeddingReferences
- B. Pang, and L. Lee, “Opinion mining and sentiment analysis,” Foundations and Trends in Information Retrieval, vol. 2, no. 1-2, pp. 1-135, 2008.
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- R. Mehra, M. K. Bedi, G. Singh, R. Arora, T. Bala, and S. Saxena, “Sentimental analysis using fuzzy and Naïve Bayes,” 2017 International Conference on Computing Methodologies and Communication (ICCMC), Jul. 2017.
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- H. Parveen, and S. Pandey “Sentiment analysis on twitter data-set using Naïve Bayes algorithm,” 2016 2nd International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT), Bangalore, India, Jul. 21-23, 2016.
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- N. Zainuddin, and A. Selamat, “Sentiment analysis using support vector machine,” 2014 International Conference on Computer, Communications, and Control Technology (I4CT), Langkawi, Malaysia, Sept. 2-4, 2014.
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