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Smart Villages: IoT Technology Based Transformation

Journal of Physics: Conference Series 2021年第1期2070卷

作者： Pankaj Mudholkar Megha Mudholkar B S Puneeth Kumar V Dankan Gowda S. Srinivasulu Raju Assistant Professor Department of Master of Computer Applications. Thakur Institute of Management Studies Career Development and Research Mumbai Maharashtra (State) INDIA Assistant Professor Department of Computer Science. St. Joseph's College (Autonomous) Bangalore Karnataka (State) INDIA Assistant Professor Department of Electronics and Communication Engineering. B.M.S. Institute of Technology and Management Bangalore Karnataka (State) INDIA Department of Electronics and Instrumentation Engineering. Velagapudi Ramakrishna Siddhartha Engineering College Vijayawada Andhra Pradesh(State) INDIA

In recent years, large-scale urbanisation has been on the rise with cities being the hubs for growth, but rural business continues to play an important role in any country's overall development. A recent report reveals that almost 69 percent of India's population resides in their villages, accounting for almost 50 percent of the nation's GDP. This agricultural region varies from small towns with less than 500 residents to small towns. There are also similar situations in western nations. Despite their economic contribution, smaller villages seem to earn fewer in terms of infrastructural expenditure. The major problems addressed in these small towns include shortage of adequate public transit, emergency care and limited knowledge on federal subsidies for rural areas. Our vision is to expand the Smart city to Smart village by allowing use of recent technical advances and giving more attention to the problems in rural areas. The approach in this chapter is to bring IoT technology to Villages by literally showing a network of linked sensors and knowledge dissemination devices, controlling energy use and ensuring infrastructure protection. It gives a wide-ranging vision of enhancing the standard of living in villages and encourages them to meet the essential needs of domestic villagers.

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Computing Multiplicative Spanners Efficiently for a Class of Simple Graphs

Computing Multiplicative Spanners Efficiently for a Class of...

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International Conference on Data science & engineering (ICDSE)

作者： Yashwanth Veluri P Jayakumar Jyothisha J Nair Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Amritapuri India Department of Computer Science and Applications Amrita Vishwa Vidyapeetham Amritapuri India

The notion of a multiplicative t - spanner was defined by David Peleg and Alejandro Scha̅fer in 1989. A vertexspanning sub graph S, of a simple graph H(V, E) in which the pairwise distance between any two vertices is less than or equal to t times that in H is called a puerly multiplicative t - spanner. The real valued parameter t (> 1) denotes the maximum possible multiplicative stretch of u-v distances in the spanner S. Although the combinatorial construction of a t-spanner with m or fewer edges for a given m and t (MTS problem henceforth) is known to be difficult, it is possible to construct MTS efficiently for graphs which satisfies certain properties. In this paper we characterize an infinite family of graph for which the MTS problem can be solved efficiently. Based on the characterization we posit a (n) algorithm for constructing an MTS.

关键词： Clustering algorithms Partitioning algorithms computer science Image segmentation Data science Complexity theory Wireless sensor networks

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Non-sequential partitioning approaches to decision tree classifier

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Future Computing and Informatics Journal 2018年第2期3卷 275-285页

作者： Shankru Guggari Vijayakumar Kadappa V. Umadevi Dept. of Computer Science and Engineering B.M.S. College of Engineering Bengaluru 560019 India Dept. of Computer Applications B.M.S. College of Engineering Bengaluru 560019 India

Decision tree is a well-known classifier which is widely used in real-world applications. It is easy to interpret, however it suffers from instability and lower classification performance for high-dimensionality datasets due to curse of dimensionality. Feature set partitioning is a novel concept to address the higher dimensionality problem by dividing the feature set into subsets (blocks). Many of the existing partitioning based decision tree approaches are sequential in nature, which lack logical relationships amongst the features. In this work, we propose novel non-sequential feature set partitioning methods by exploiting the ideas of Ferrer Diagram and Bell Triangle to create feature blocks with a mix of low, medium, and high correlation features. The experimental results on 11 UCI and KEEL datasets demonstrate the superiority of the proposed partitioning methods, upto 5% higher classification accuracy, over NBTree, BFTree, Serial-CMFP partitioning method, and classical decision tree techniques. The proposed methods also exhibit improved stability as compared to other decision tree methods.

关键词： Decision tree Correlation Ferrer diagram Bell triangle Partitioning

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Monolithic integration of MoS2-based visible detectors and GaN-based UV detectors

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Photonics Research 2019年第10期7卷 1127-1133页

作者： YOU WU ZHIWEN LI KAH-WEE ANG YUPING JIA ZHIMING SHI ZHI HUANG WENJIE YU XIAOJUAN SUN XINKE LIU DABING LI State Key Laboratory of Luminescence and Applications Changchun Institute of OpticsFine Mechanics and PhysicsChinese Academy of SciencesChangchun 130033China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Shenzhen Castle Security Technology Co. Ltd.Shenzhen 518000China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China

With the increasing demand for high integration and multi-color photodetection for both military and civilian applications, the research of multi-wavelength detectors has become a new research hotspot. However, current research has been mainly in visible dual-or multi-wavelength detectors, while integration of both visible light and ultraviolet(UV) dual-wavelength detectors has rarely been studied. In this work, large-scale and high-quality monolayer MoS2 was grown by the chemical vapor deposition method on transparent free-standing GaN substrate. Monolithic integration of MoS2-based visible detectors and GaN-based UV detectors was demonstrated using common semiconductor fabrication technologies such as photolithography, argon plasma etching, and metal deposition. High performance of a 280 nm and 405 nm dual-wavelength photodetector was *** responsivity of the UV detector reached 172.12 A/W, while that of the visible detector reached 17.5 A/***, both photodetectors achieved high photocurrent gain, high external quantum efficiency, high normalized detection rate, and low noise equivalent power. Our study extends the future application of dual-wavelength detectors for image sensing and optical communication.

关键词： visible integration ultraviolet

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PSVM: a preference-enhanced SVM model using preference data for classification

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science China(Information sciences) 2017年第12期60卷 165-178页

作者： Lerong MA Dandan SONG Lejian LIAO Jingang WANG Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications School of Computer Science and Technology Beijing Institute of Technology College of Mathematics and Computer Science Yan'an University Search Business Department Alibaba Group

Classification is an essential task in data mining, machine learning and pattern recognition *** classification models focus on distinctive samples from different categories. There are fine-grained differences between data instances within a particular category. These differences form the preference information that is essential for human learning, and, in our view, could also be helpful for classification models. In this paper, we propose a preference-enhanced support vector machine(PSVM), that incorporates preference-pair data as a specific type of supplementary information into SVM. Additionally, we propose a two-layer heuristic sampling method to obtain effective preference-pairs, and an extended sequential minimal optimization(SMO)algorithm to fit PSVM. To evaluate our model, we use the task of knowledge base acceleration-cumulative citation recommendation(KBA-CCR) on the TREC-KBA-2012 dataset and seven other datasets from UCI,Stat Lib and ***. The experimental results show that our proposed PSVM exhibits high performance with official evaluation metrics.

关键词： preference SVM classification sampling sequential minimal optimization(SMO)

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Optimisation Using Rearrangement of Order of BGP and TLBO Approach

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Procedia computer science 2018年 125卷 282-289页

作者： Sahil Saharan J.S. Lather R. Radhakrishnan Department of Computer Applications National Institute of Technology Kurukshetra India Department of Electrical Engineering National Institute of Technology Kurukshetra India Department of Computer Science and Engineering ABES Ghaziabad(Uttar Pradesh) India

Semantic Web data is increasing day by day. The important issue of this web is to handle inordinate volume of information that has many other challenges like query processing and optimisation over widely distributed RDF data. The proposed approach use the reduced querying cost, and hereby optimising the execution time of the query. Optimization of query is one of the most popular problems existing in RDF data which is among the hardest combinatorial optimization problem. Our finding and experimental result concludes that TLBO(Teaching Learning Based Optimisation) outperforms in terms of execution time of the query when compare with ACO variants. In experiment, different types of queries are taken into account like chain, star to show the results of execution time taken by query. This approach centered on main-memory RDF data model.

关键词： RDF query optimisation Teaching Learning Based Optimisation(TLBO) SPARQL

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Relay Node Selection Strategy for Wireless Sensor Network 4th

Relay Node Selection Strategy for Wireless Sensor Network

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4th Euro-China Conference on Intelligent Data Analysis and applications, ECC 2017

作者： Kong, Lingping Pan, Jeng-Shyang Chu, Shu-Chuan Roddick, John F. Innovative Information Industry Research Center Harbin Institute of Technology Shenzhen Graduate School Shenzhen China Fujian Provincial Key Laboratory of Big Data Mining and Applications College of Information Science and Engineering Fujian University of Technology Fujian China School of Computer Science Engineering and Mathematics Flinders University Adelaide Australia

ISBN: (纸本)9783319685267

In the past few years, people have experienced advanced interest in the potential use of wireless sensor network in applications such as environment surveillance, military field protection and medical treatment. Usually hundreds even thousands of sensors are scattered randomly in remote environment. In generally, for the scalability of sensor network, cluster techniques are often used to group nodes into several sets. And in this paper, we proposed a new method called GF_CENTER to select the positions of centers, which is also a kind of k-center problem. And a new fitness function is presented for optimize the resolution. We compare our method with two other algorithms. GF_CENTER method minimizes the number of centers in the network. From the experiments, GF_CENTER find smaller number of centers than the other methods, which lower the construction fee of network. © 2018, Springer International Publishing AG.

关键词： Genetic algorithms

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Preface

Smart Innovation, Systems and Technologies

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Smart Innovation, Systems and Technologies 2020年 159卷 ix-x页

作者： Satapathy, Suresh Chandra Mohanty, J.R. Bhateja, Vikrant Udgata, Siba K. School of Computer Engineering KIIT Deemed to be University BhubaneswarOdisha India School of Computer Applications KIIT University BhubaneswarOdisha India Department of Electronics and Communication Engineering Shri Ramswaroop Memorial Group of Professional Colleges LucknowUttar Pradesh India School of Computer and Information Science University of Hyderabad HyderabadTelangana India

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The Influence of Dust and Black Carbon on Clouds, in Africa

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Journal of computer and Communications 2018年第11期6卷 342-352页

作者： Gerard Rushingabigwi Jiahua Zhang Tarak Bachagha Wilson Kalisa Malak Henchiri Ali Shahzad Philibert Nsengiyumva Cesar Nduwayo Bugingo Department of Computer Science and Technology Computer Applications in Remote Sensing Qingdao University Qingdao China Department of Electrical and Electronic Engineering Electronics and Telecommunication University of Rwanda Kigali Rwanda

The aerosol can change the clouds properties;the clouds, however, affect the normal behavior of aerosol optical depth. Considerable effects arise while the interaction of aerosol and clouds unavoidably encounters the presence of greenhouse gases (GHGs) in atmosphere. This research discusses the influence of two selected aerosol types, on the clouds in Africa, over the selected sub-time series in the years 1980-2018. Sahara desert’s dust is mainly constituted by hematite minerals;which, in return, is mainly composed by the iron oxides, a powerful solar and infra-red radiation absorbing matter and thus a strong and direct radiative forcing agent. For that reason, together with the fact that it is windblown over the biggest region that surrounds the desert, dust is one of the strongly considered aerosol in this research. Besides, black carbon (BC), mostly from the anthropogenic biomass burning process in the mid latitude’s African savanna, is the second aerosol type selected for this research: it is one of the abundantly available aerosol types and it is one of the strongest atmospheric radiant energy absorbers. For sake of valid and trustworthy results, the data is collected from multiple satellite remote sensing tools and instruments, all targeting the aerosol-cloud interaction and effects. In this research, different measurements were carried out;those are the spatiotemporal averaged cloud cover, the aerosol (dust and BC) extinction optical thickness (AOT), the anomaly of aerosol optical depth (AAOD) as well as different scatter plots’ correlation analysis. For findings: the direct influence of hydrophilic BC on clouds formation in central African sub-region is experimentally demonstrated;the dust aerosol highly influences the North African sub-region’s cloud formation.

关键词： Aerosol Africa Cloud-Aerosol Interaction Anomaly of Aerosol Optical Depth

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Directional shuffled frog leaping algorithm 1st

Directional shuffled frog leaping algorithm

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1st International Conference on Smart Vehicular Technology, Transportation, Communication and applications, VTCA 2017

作者： Kong, Lingping Pan, Jeng-Shyang Chu, Shu-Chuan Roddick, John F. Innovative Information Industry Research Center Harbin Institute of Technology Shenzhen Graduate School Shenzhen China Fujian Provincial Key Laboratory of Big Data Mining and Applications College of Information Science and Engineering Fujian University of Technology FuzhouFujian China School of Computer Science Engineering and Mathematics Flinders University Adelaide Australia

ISBN: (纸本)9783319707297

Shuffled frog leaping algorithm is one of the popular used optimization algorithms. This algorithm includes the local search and global search two solving modes, but in this method only the worst frog from divided group is considered for improving location. In this paper, we propose a directional shuffled frog leaping algorithm (DSFLA) by introducing the directional updating and real-time interacting concepts. A direction flag is set for a frog before moving, if the frog goes better in a certain direction, it will get better in a big probability by moving a little further along that direction. The movement counter is set for preventing the frog move forward infinite. Real-time interacting works by sharing the currently optimal positions from the other groups. There should have some similarities among the best ones, and the worst individual could be improved by using those similarities. The experimental results show that the proposed approach is a very effective method for solving test functions. © Springer International Publishing AG 2018.

关键词： Swarm intelligence

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