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Optimization of Response and Processing Time for smart Societies Using Particle Swarm Optimization and Levy Walk 33rd

Optimization of Response and Processing Time for Smart Socie...

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33rd international conference on Advanced Information Networking and Applications, AINA-2019

作者： Butt, Ayesha Anjum Khan, Zahoor Ali Javaid, Nadeem Chand, Annas Fatima, Aisha Islam, Muhammad Talha COMSATS University Islamabad Islamabad44000 Pakistan Computer Information Science Higher Colleges of Technology Fujairah4114 United Arab Emirates COMSATS University Islamabad Abbotabad22010 Pakistan

ISBN: (纸本)9783030150310

Reducing delay and latency in the cloud computing environment is a challenge for the present research community. This study performed a rigorous, comparative analysis of the fog computing paradigm and the conventional cloud computing paradigm in the context of the smart Grid (SG). To meet the consumers’ demand and optimize cloud services to achieve service level objectives is of great importance. The fog is introduced to enhance the efficiency of the cloud and to fulfill the consumer requests at the edge of the network. When the requests of smart Societies (SSs) are huge on fog, the increased demand for real-time response is becoming a challenge for the SG. In this study, Particle Swarm Optimization is implemented and compared with the proposed techniques: Improved PSO with Lewy Walk (IPSOLW). These load balancing algorithms are compared on the basis of Closest data Center (CDC) and Optimize Response Time (ORT). These proposed algorithms handle the load of SS on fog. The proposed IPSOLW handles more requests because of LW, the requests are directly allocated to best DC. © 2020, Springer Nature Switzerland AG.

关键词： Fog

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Large-Scale data Clustering Using Improved Artificial Bee Colony Algorithm 4th

Large-Scale Data Clustering Using Improved Artificial Bee Co...

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4th international conference on ICT for Sustainable Development, ICT4SD 2019

作者： Gaikwad, M.R. Umbarkar, A.J. Bamane, S.S. Department of Information Technology Walchand College of Engineering Shivaji University Sangli India

ISBN: (纸本)9789811509353

Clustering is grouping the similar data points in the clusters. Large-scale data grouping has discovered wide applications in many fields, particularly in big data analytics. Traditional clustering algorithms do not explore and exploit all feasible solutions of clustering. Artificial Bee Colony algorithm (ABC) is a metaheuristic algorithm applied for clustering. ABC suffers from slow convergence. Hence, Improved ABC (IABC) is used for experimentation. UCI datasets—wine and seed are modified to large scale and used for experimentation. Experimental results show that IABC give the quality clusters than ABC and K-mean for large-scale dataset. ABC gives the better clusters than K-mean. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Swarm intelligence

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Developing a Production Scheduling System for Modular Factory Using Constraint Programming 28th

Developing a Production Scheduling System for Modular Factor...

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28th international conference on Robotics in Alpe-Adria-Danube Region (RAAD)

作者： Park, Hoonseok Um, Jumyung Jung, Jae-Yoon Ruskowski, Martin Kyung Hee Univ Dept Ind & Management Syst Engn 1732 Deogyeong Daero Yongin Gyeonggi Do South Korea German Res Ctr Artificial Intelligence DFKI GmbH IFS Innovat Factory Syst Trippstadter Str 122 D-67663 Kaiserslautern Germany

ISBN: (纸本)9783030196486;9783030196479

This paper presents a production scheduling system that optimizes operations of a modular factory. The proposed system consists of a database, a scheduling optimizer and an interface connecting two other components. A scheduling model for optimal schedules plays a key role in the scheduling system. In this research, we aim to develop the scheduling model using constraint programming, and design a data mart storing the related operational data. In particular, we set the modular factory environment to the hybrid flow shop and apply the constraint programming for scheduling. We provide a case study to test the performance of the proposed scheduling model with the synthesized dataset based on a modular factory environment in smartFactory(KL).

关键词： smart factory Flexible manufacturing Production scheduling Hybrid flow shop Constraint programming

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Research on road traffic situation awareness system based on image big data

Research on road traffic situation awareness system based on...

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2020 international conference on Applied Physics and computing, ICAPC 2020

作者： Zhu, Yinghao Peng, Yangyang Wang, Shangzheng Shi, Shuimeng Ji, Nan Yisheng College North China University of Science and Technology Tangshan China College of Metallurgy and Energy North China University of Science and Technology Tangshan China College of Electrical Engineering North China University of Science and Technology Tangshan China College of Science North China University of Science and Technology Tangshan China

To promote the construction of intelligent and information technology in the field of road traffic is conducive to the construction of smart cities and the formulation of macro strategies and construction plans for urban traffic development. In view of the shortcomings of the current road traffic system, based on convolution neural network, situation awareness technology, database and other technologies, using CNN, R-CNN, fast R-CNN and fast R-CNN, this paper constructs a deep convolution neural network model based on the big data of road traffic image, and carries out the system demand analysis and system framework design and implementation. Through the analysis of the actual case and the feedback of the trial, the application effect of the road traffic situation awareness system is illustrated, in order to provide scientific reference and basis for the establishment of modern intelligent transportation system. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： Big data

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Effective Behavioural Analysis using Polystore data Catalog and intelligent Learning

Effective Behavioural Analysis using Polystore Data Catalog ...

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Simulation, Automation & smart Manufacturing (SASM), international conference on

作者： R Claudia Lois T N Akshaya Chelvi K Bhuvaneshwari M Krishnamurthy Department of Computer Science Engineering KCG College of Technology Chennai India Department of Artificial Intelligence and Data Science KCG College of Technology Chennai India

ISBN: (数字)9781665403573

ISBN: (纸本)9781665447768

This paper aims to design and implement an application usage behaviour analytics system to produce dynamic bundles personalized to each customer. A H2O Deep Learning model was first built to predict the list of products that are most likely to be reordered by each customer, on the basis of which bundle combinations were framed. The model was found to have an accuracy score of 83.04, a precision score of 84.7 and a recall score of 96.31. The products comprising each customer’s bundle were determined by a 3:1 ratio of products that the customer is most expected to purchase to the products that are less popular. This implementation starts with building a data lineage and catalog from multiple data sources with persistent data collected from transactions and product catalogs which was then used to identify, model, analyze behavioral patterns and collect insights in order to build the prediction model. This method of recommendation attempts to solve the cold-start effect of new products and to eliminate the popularity bias in bundle recommendation systems by producing personalized dynamic bundles in such a way that it improves the sales of unpopular products while also contributing to overall customer satisfaction. The technical stack that was used for implementing this idea includes Apache Spark, Mongodb Atlas and Apache H2O.

关键词： Water Analytical models Soft sensors Neural networks Cluster computing Predictive models data models

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A Framework for Integrating Cloud computing and Big data analytics into E-Governance Using Openstack Sahara 3rd

A Framework for Integrating Cloud Computing and Big Data Ana...

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3rd international conference on Information and Communication Technology for intelligent Systems (ICTIS)

作者： Jadhav, Bhushan Patankar, Archana B. Mumbai Univ Thadomal Shahani Engn Coll Mumbai Maharashtra India

ISBN: (纸本)9789811317477;9789811317460

The information and communication technologies (ICTs) have made significant development in its hardware, software, computing, storage, and communication technologies to leverage the modern-day computing. The E-governance uses ICT to deliver essential government services over the Internet. But due to the limited infrastructure, lack of funds, use of outdated technologies, the current E-governance solutions face many issues related to computing and data processing. The cloud computing is a recent advancement to traditional computing architectures which can overcome the challenges related to computing while big data analytics has emerged over the past data management technologies to solve the limitations related to data acquisition, storage, processing, and analytics. Therefore, the combination of cloud computing and big data analytics would be a welcome option in E-governance. The Openstack is an open-source cloud platform widely used inmost of the organizations because of its distinguished features over the existing computing architectures and having built-in support for big data analytics. The main objective of this paper is to propose a framework for E-governance based on Openstack that integrates cloud computing and big data analytics together to overcome the challenges in existing E-governance system.

关键词： E-governance Cloud computing Big data analytics

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Algorithm for Genrerating and Visualizing Routes of an intelligent Tourist Guide

Algorithm for Genrerating and Visualizing Routes of an Intel...

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2020 international conference Automatics and Informatics, ICAI 2020

作者： Kostadinov, Georgi Milev, Kristian Staynov, Stefan Stoyanova-Doycheva, Asya University of Plovdiv Paisii Hilendarski Faculty of Mathematics and Informatics Plovdiv Bulgaria

ISBN: (纸本)9781728193083

This article presents an intelligent tourist guide known as TG that takes into account various factors, such as the tourist's preferences, location, time available, and the presence and location of cultural and historical objects in the area in order to propose virtual or real cultural and historical routes. The TG is being implemented as an Internet of Thing (IoT) application. In the exposition of the article we have dwelled on the algorithm for generation and visualization tourist routes in detail. Cultural objects are presented as ambients to achieve the generation of real tourist routes. © 2020 IEEE.

关键词： Ambient-oriented Modeling Ontologies Personal Assistants Tourist routes generation Touristic Guides

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4th international conference on intelligent, Interactive Systems and Applications, IISA2019

4th International Conference on Intelligent, Interactive Sys...

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4th international conference on intelligent, Interactive Systems and Applications, IISA2019

ISBN: (纸本)9783030343866

The proceedings contain 102 papers. The special focus in this conference is on intelligent, Interactive Systems and Applications. The topics include: Research and Application of Process Object Modeling Method Based on Deep Learning;Security Issues for smart Grid EC System;a Novel smart Grid Model for Efficient Resources;The Idea of Deep Neural Network Algorithms Application in Sharing Economic Dynamic Value CO-creation Mechanism;performance Assessment of smart Electricity Meters Based on Max Margin Bayesian Classifiers;operating Performance Assessment of smart Meters Based on Bayesian Networks and Convex Evidence Theory;research on Object-Oriented Design Defect Detection Method Based on Machine Learning;design of Electromagnetic Energy-Saving intelligent Vehicle;new Energy Vehicle Reliability Research by Large data;One-Step Prediction for GM(1,1) with a Sliding data Window;evaluation on Well-Canal Combined Irrigation Modes for Cotton Fields in the South of Xinjiang, China Based on an Algorithm of Fuzzy Neutral Network;grape Downy Mildew On-line Detection Based on Accurate Image Processing Method Preformed on Embedded Ambient Intelligence System;an Improved Bisecting K-Means Text Clustering Method;research on intelligent Patent Classification Scheme Based on Title Analysis;PLC-Based Control System Design of intelligent and Efficient Multiple Parking Device;sparse Acceleration Algorithm Based on Likelihood Upper Bound;optimization Design of Quad-Rotor Flight Controller Based on Improved Particle Swarm Optimization Algorithm;diversified Development Path of Cultural Exhibition Industry: Perspective of Service Value Chain;Research on Text Classification Method Based on Word2vec and Improved TF-IDF;Research on Automatic Text Summarization Method Based on TF-IDF;message Transmission-Driven Infectious Disease Propagation Model.

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intelligent visual analysis in employee fraud detection

Intelligent visual analysis in employee fraud detection

引用

international conference on intelligent and Fuzzy Systems, INFUS 2019

作者： Doğan, Buket Öztayşi, Başar Department of Industrial Engineering Istanbul Technical University Istanbul34367 Turkey

ISBN: (纸本)9783030237554

The objective of this paper is to discover and prevent organized financial crimes among various entities such as applicants, guarantors, customers, staff, portfolio managers, beneficiaries, agencies, experts and services. A sophisticated visual analysis solution can help users to detect conspicuous links between different entities. Most of the institutions have been using business intelligence or reporting tools to examine employee fraud which are insufficient to discover and analyze organized crime. In this paper, we propose a visual analytics approach to this problem. A web based application is developed which works with on-demand data and enable users to navigate on the graph and move objects in order to make the complex relationships clearer. The users can also zoom-in and zoom-out and dynamically expand nodes to discover hidden relationships at deeper levels. Intelligence Visual Analysis solution is a sub module of end-to-end Internal Fraud Management solution. It is also a stand-a-alone solution which can be integrated to other fraud management solutions. © 2020, Springer Nature Switzerland AG.

关键词： Crime

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Organizing Named data Objects in Distributed Name Resolution System for Information-Centric Networks 4th

Organizing Named Data Objects in Distributed Name Resolution...

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4th international conference of Reliable Information and Communication Technology (IRICT)

作者： Elbrieki, Walid Hassan, Suhaidi Arlimatti, Shivaleela Habbal, Adib Univ Utara Malaysia Sch Comp InterNetWorks Res Lab Sintok 06010 Kedah Malaysia Shaikh Coll Engn & Technol Belgaum India Karabuk Univ Fac Engn Comp Engn Dept TR-78050 Karabuk Turkey

ISBN: (纸本)9783030335823;9783030335816

The Information-centric Networks (ICN), an important research direction of the future Internet architecture, has gained lot of attention from the research community. The aim is to improve the current Internet with a new architecture where the design is completely based on information instead of the host. The information is named and is called as Named data Object (NDO), utilized for data registration and name resolution, and the system that translates the object identifiers to network address is known as Name Resolution System (NRS). The random NRS distribution and network segregation are important and challenging issues in increasing NDO registration and storage. It is challenging for a single NRS to handle more than 10(15) expected NDO's with low latency and good throughput, along with the issues interest flooding and interest congestion. To overcome these problems NRS is distributed based on the location of routers. The mechanism is called Distributed Name Resolution Mechanism (DNRM). The NDO storage needs to be organized to increase the scalability of NRS. Distributed hash table and Bloom Filter have their own problems such as high latency in individual element searching and member deletion respectively. To overcome the above-mentioned issues the Balance Binary Tree (BBT) data structure is introduced to manage large NDO storage. The implementation results reduce the end-to-end delay by increasing network throughput. The contribution of this study is significant in promoting the use of NRS in ICN for handling the heterogeneity of the future Internet.

关键词： Name Resolution System Named data Objects Balanced Binary Tree Information-Centric Networks

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