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20th international conference on Hybrid intelligent Systems, HIS 2020 and 12th World Congress on Nature and Biologically Inspired computing, NaBIC 2020

20th International Conference on Hybrid Intelligent Systems,...

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20th international conference on Hybrid intelligent Systems, HIS 2020 and 12th World Congress on Nature and Biologically Inspired computing, NaBIC 2020

ISBN: (纸本)9783030730499

The proceedings contain 78 papers. The special focus in this conference is on Hybrid intelligent Systems. The topics include: Text Classification Using Convolution Neural Networks with FastText Embedding;deep Convolutional Neural Network Based on Wavelet Transform for Super Image Resolution;optimizing Instance Selection Strategies in Interactive Machine Learning: An Application to Fraud Detection;building IoT analytics and Machine Learning with Open Source Software for Prediction of Environmental data;ANFIS-Based Inverse Kinematics and Forward Dynamics of 3 DOF Serial Manipulator;design and Development of intelligent Pesticide Spraying System for Agricultural Robot;solving Dynamic Bag-of-Tasks Scheduling Problem in Heterogeneous Multi-cloud Environment Using Hybrid Bi-Level Optimization Model;Caching Mechanisms Evolution in CCN Architectures;SentiLSTM: A Deep Learning Approach for Sentiment Analysis of Restaurant Reviews;auto-Encoder Based Wavelet and Extreme Learning Machine for Face Recognition;characterizing Antennas’ Radiation Pattern Using Bernoulli Lemniscates;analysis of Metaheuristics Feature Selection Algorithm for Classification;hybrid Genetic Algorithms to Solve the Traveling Salesman Problem;hybridization of Adaboost with Random Forest for Real-Time Prediction of Online Shoppers’ Purchasing Intention;change Detection in Satellite Imagery: A Multi-label Approach Using Convolutional Neural Network;inverse Neural Control of a Magnetic Levitation System: Experimental Results;COVID-19 Detection Using Deep Learning;an Isolation Forest Learning Based Outlier Detection Approach for Effectively Classifying Cyber Anomalies;an Effective Heart Disease Prediction Model Based on Machine Learning Techniques;optimal Design of Fuzzy Controllers Using the Multiverse Optimizer;sparse Wavelet Auto-encoder for Covid-19 Cases Identification;a New Bi-objective Classic Transportation Model Considering Social Justice;emotion Recognition Using Multimodalities.

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Individualized Cultivation Path of Mixed Teaching of Multimedia Technology Course Based on data Analysis

Individualized Cultivation Path of Mixed Teaching of Multime...

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international conference on Multi-modal Information analytics, MMIA 2021

作者： Fan, Jing Department of Information Engineering Heilongjiang International University Harbin Heilongjiang150000 China

ISBN: (纸本)9783030748135

With the promotion and implementation of "Internet + Education", the organic combination of two teaching organization forms online teaching platform and traditional education can lead learners to shift from shallow learning to deep learning. Multimedia Technology is a compulsory course for digital media technology majors. This course implements teaching reform in terms of curriculum design, teaching organization and teaching evaluation. In addition, this course manages student learning in three aspects: warm-up, in-class supervision and post-class reflection, which generates a large amount of learning data. By analyzing and classifying students’ learning data and exploring the learning status, strengths and weaknesses of students, this course can provide a variety of teaching programs and individualized cultivation. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Teaching

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Age-Aware Query Evaluation for Big data analytics in Mobile Edge Clouds 22

Age-Aware Query Evaluation for Big Data Analytics in Mobile ...

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22nd IEEE international conference on High Performance computing and Communications, 18th IEEE international conference on smart City and 6th IEEE international conference on data Science and Systems, HPCC-smartCity-DSS 2020

作者： Xia, Qiufen Ren, Wenhao Li, Mingchu Ren, Jiankang Dalian University of Technology International School of Information Science and Engineering Dalian116621 China Dalian University of Technology School of Software Dalian116621 China Dalian University of Technology School of Computer Science and Technology Dalian116024 China

ISBN: (纸本)9781728176499

The advancement of 5G technology and extensive usage of smart devices have led to a deluge of data. It is invaluable to analyze such big data by issuing queries to derive real-Time business insights for better, smarter and fact-based decisions. Timely big data analytics are crucial in many service domains, thus the age of data (AoD) required by queries is emerging as a novel metric that measures the freshness of data and evaluates the quality of data analytics. Traditional big data analytics that are performed in remote clouds cannot satisfy the AoD requirements of queries, due to the congested core networks and long transmission latency between users and clouds. The technique of mobile edge computing (MEC) is expected to reduce the age and guarantee the timeliness of queries for big data analytics, by processing data at edge cloudlets close to users. In this paper, we investigate a problem of age-Aware query evaluation for big data analytics in a mobile edge cloud network. We first formulate the problem with certain data processing latency as an Integer Linear Program (ILP). We then develop an online learning algorithm for the problem with uncertain data processing latency. We finally evaluate the performance of proposed algorithms against existing studies by simulations and testbed implementations. Evaluation results show that the proposed algorithms outperform existing works by achieving 20% lower AoD. © 2020 IEEE.

关键词： data analytics

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Comparison Between the Statistical Method Models for Better Time Series Sales Forecasting Model 3rd

Comparison Between the Statistical Method Models for Better ...

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3rd international conference on computing and Communication, IC3 2020

作者： Ponniah, Theviya Darshini Ahmad, Sharifah Sakinah Binti Syed Borah, Samarjeet Universiti Teknikal Malaysia Melaka Malaysia Sikkim Manipal Institute of Technology Sikkim Manipal University Sikkim India

ISBN: (纸本)9789811573934

Time series analysis contains strategies for studying time series data a good way to extract significant facts and different traits of the information. Paperion of the time series is the use of a model to forecast future values based on formerly predicted values. Time series are extensively used for non-stationary statistics, like economic, weather, stock price, and retail income on this put up. This paper is to investigate on comparison between the traditional statistical method models which are ARMA, ARIMA, and ARIMAX model using the dataset provided in Kaggle competition webpage. Three numbers of time series were implemented on the validation, and comparison is done in terms of performance. As a result, the following month’s forecast for the total monthly sales for every shop within the next month will be determined and predicted. This paper will provide a step-by-step guide for fitting the traditional statistical method models using Jupyter Notebook. The methodology used in the paper is data analytics lifecycle which is a technique used to understand the data and apply statistics to get insights for an achievable objective. By end of this paper, the main aim to be achieved is to understand and analyze the data, then to do the overall revenue prediction for each store over the next month. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： data analytics

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data Analytic Tools An Overview

Data Analytic Tools An Overview

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2020 international conference on smart Innovations in Design, Environment, Management, Planning and computing, ICSIDEMPC 2020

作者： Janardhanan, Jitha Umamaheswari, S. Dr.G.R.Damodaran College of Science Department of Computer Science Coimbatore India

ISBN: (纸本)9781728159706

The process of extracting interesting patterns from vast database hiding is known as data mining the choice of best one among abundant data mining tools accessible in the sooqis not easy. A numeral factors demand to be contemplated before formulating a financing in any commercial solution. This article stretches the complete and hypothetical analysis of a few open source data mining tools. The data mining tools and their utilities comparison are conferred here. The paper also discusses about data analytics and its importance © 2020 IEEE.

关键词： data analytics

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smart Healthy intelligent Room: Headcount through Air Quality Monitoring 6

Smart Healthy Intelligent Room: Headcount through Air Qualit...

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6th IEEE international conference on smart computing (smartCOMP)

作者： Cicceri, Giovanni Scaffidi, Carlo Benomar, Zakaria Distefano, Salvatore Puliafito, Antonio Tricomi, Giuseppe Merlino, Giovanni Univ Messina Messina Italy CINI Natl Interuniv Consortium Informat Rome Italy

ISBN: (纸本)9781728169972

In this work, we propose a low-cost smart and Healthy intelligent Room System (SHIRS), able to monitor Indoor Air Quality (IAQ) by enhancing edge-based computation. SHIRS exploits the ability to run Machine Learning (ML) algorithms to infer humans presence (headcount) from environmental data analysis. Experimental results show the validity of the proposed approach, demonstrate the potential of edge-based computing and push towards the adoption of smart integrated Cloud-IoT frameworks for environmental monitoring and control.

关键词： Indoor Air Quality IoT Machine Learning Cloud Edge computing

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Review paper on fourth industrial revolution and its impact on humans 8th

Review paper on fourth industrial revolution and its impact ...

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8th international conference on Frontiers of intelligent computing: Theory and Applications, FICTA 2020

作者： Srija Harshika, D. Cyient Ltd. Madhapur Hyderabad India

ISBN: (纸本)9789811556784

The fourth industrial revolution, a term instituted by Klaus Schwab, organizer and official executive of the World Financial Gathering, depicts an existence where people move between computerized areas and disconnected reality with the utilization of associated innovation to empower and deal with their lives (Mill operator 2015, 3). The principal mechanical upheaval transformed us and economy from an agrarian and handiwork economy to one ruled by industry and machine fabricating. Oil and power encouraged large-scale manufacturing in the second mechanical insurgency. In the third modern unrest, data innovation was utilized to mechanize creation. Albeit each mechanical unrest is regularly viewed as a different occasion, together they can be better comprehended as a progression of occasions heaps of the past unrest and prompting further developed types of creation. Another technological development zone as of late has been analytics. Financial organizations track and gather a wide range of information on customers, for example, what customers purchase, how they get it, and when they do their shopping. Mobile phones are another key player in enormous information since they can likewise follow shopping information, just as information on media utilization and even your area for the duration of the day. This article examines the significant highlights of the four mechanical insurgencies, the chances of the fourth modern transformation, and the difficulties of the fourth industrial unrest. With so much information accessible, what job will it have in the up and coming fourth industrial transformation? © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.

关键词： data analytics

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An Internet of Things-based Economical Agricultural Integrated System for Farmers: A Review

An Internet of Things-based Economical Agricultural Integrat...

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international conference on intelligent computing and Control Systems (ICICCS)

作者： Devi, R. Kanniga Muthukannan, M. Kalasalingam Acad Res & Educ Dept Comp Sci & Engn Virudunagar Tamil Nadu India Kalasalingam Acad Res & Educ Dept Civil Engn Virudunagar Tamil Nadu India

ISBN: (纸本)9781728148762

The traditional agricultural activities need digitized transformation to feed the ever-increasing human population of this world. The digitized transformation of agriculture makes it smart and eases the farmers from the heavy physical agricultural activities. This paper aims to review the application of IoT in various agricultural activities and to make agriculture smart, this paper also suggests the development of an Integrated System, S-AGRO using Internet of Things technology, which can remotely monitor the agricultural activities and make smart decisions to improve the agricultural productivity. Besides, this paper extensively studied the IoT system for agricultural activities based on IoT platform, sensors used, power supply used, communication technology, information storage and processing and information alert/control techniques. The various methodologies used globally are also reviewed and it was observed that are no single system, which addresses all the agricultural activities. The development of an integrated system, S-AGRO which comprises of soil analysis, irrigation, weather forecasting, field monitoring, energy management, data analytics and reporting subsystems have been proposed. The S-AGRO system would help the farmers to improve the agricultural productivity without much physical effort.

关键词： smart agriculture Internet of Things [IoT] integrated system sensors cloud

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Predictive data analytics for Breast Cancer Prognosis 3rd

Predictive Data Analytics for Breast Cancer Prognosis

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3rd international conference on Advanced computing and intelligent Engineering (ICACIE)

作者： Chauhan, Ritu Kumar, Neeraj Amity Inst Biotechnol AUUP Sec 125 Noida India

ISBN: (纸本)9789811510816;9789811510809

The leading healthcare explosion in datasets has created furious interest among the researchers and scientists to determine automated technology for clinical future implications. Hence, data mining in the past decade has resolved and discovered hidden information and knowledge from large-scale databases. data mining tends to be widely anticipated technology which is utilized in varied application domain for retrieval of patterns for future decision-making. In the past several research studies are based on the prevalence and prognosis of breast cancer in females, but our proposed discuss the interception of disease for both the genders. Hence, we integrate the cancer data with predictive data analytics to determine the incidence and mortality rate of breast cancer both in males and females from the year 1990 to 2014.

关键词： Predictive data analytics data mining Breast cancer Spectral analysis

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Fuzzy cloud-fog computing approach application for human activity recognition in smart homes

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JOURNAL OF intelligent & FUZZY SYSTEMS 2020年第1期38卷 709-721页

作者： Lopez-Medina, M. A. Espinilla, M. Cleland, I. Nugent, C. Medina, J. Council Hlth Andalucian Hlth Serv Av Constituc Seville Spain Univ Jaen Comp Sci Campus Las Lagunillas Jaen 23071 Spain Ulster Univ Sch Comp Jordanstown BT37 0QB Antrim North Ireland

Fog computing is an approach involving smart devices. These devices carry out data processing to provide collaborative services to reach a common goal, usually, in the cloud. In the fog computing paradigm, uncertainty and vagueness are inherent to the data processing due to the limitations of computational and communication capabilities of the smart devices. Fuzzy logic and protoforms represent a powerful tool to model and compute imprecise data presented within the fog-computing paradigm. In this paper, we present a fuzzy cloud-fog approach based on fuzzy temporal windows and fuzzy aggregation. The innovations of this paper are: i) to model the uncertainty involved in fog nodes linguistically, ii) to compute and distribute relevant linguistic information (protoforms), and iii) to publish the computed protoforms in the cloud to generate complex protoforms, which reach the common goal. This new fuzzy cloud-fog approach is applied to the problem of activity recognition in smart homes. In this context, the smart devices in a smart home are represented by fog nodes, which cooperate for activity recognition using a fuzzy cloud-fog computing approach to provide solutions in ambient-assisted living. Finally, to demonstrate the effectiveness of the proposal in handling situations/environments where multiple and heterogeneous devices are involved (such as UWB beacons, smart objects and smart wearable devices), a case study of the proposed fuzzy cloud-fog approach is implemented in the smart lab of the University of Jaen. So, the results obtained with the proposed approach in the case study are compared to the results obtained with a non-fuzzy approach with the aim of showing the advantages of the fuzzy methodology.

关键词： Fuzzy fog computing fuzzy cloud computing smart devices UWB technology activity recognition protoforms fuzzy temporal windows fuzzy aggregation

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