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An Improved smart Wheat Health Monitor for smart Farming Application Using Deep Residual Learning Framework 12th

An Improved Smart Wheat Health Monitor for Smart Farming App...

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12th international conference on Soft computing and Pattern Recognition, SoCPaR 2020 and 16th international conference on Information Assurance and Security, IAS 2020

作者： Elidrissi, Mohammed Elbeqqali, Omar Riffi, Jamal Sidi Mohamed Ben Abdellah University B.P. 1796 Fez-Atlas30003 Morocco

ISBN: (纸本)9783030736880

In this paper, we propose a classification model called SWHM (smart Wheat Health Monitor) that aims to help farmers in wheat plants health monitoring task using residual learning framework. Training a very deep network of CNN (Convolutional Neural Network) creates a vanishing gradient problem, which is interpreted as a loss of information during training process, because learned features in the later layers vanish while being sent back to the early layers, in some other words, when updating the weights by backpropagation in a deep neural network, the multiple derivation of the loss function (gradient) may make the gradient disappear. We chose residual learning because it allows us to go deeper in the training process by extending the number of layers to achieve a few hundreds of layers without being worry about vanishing gradient or model complexity issues. proposed amelioration allows us to achieve 83.33% of accuracy, and minimize error rate to 16.67%, within a reasonable time of training. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

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Analysis and Comparison of Routing Protocols in Wireless Sensor Networks

Analysis and Comparison of Routing Protocols in Wireless Sen...

引用

international conference on Application of intelligent Systems in Multi-modal Information analytics, MMIA 2020

作者： Yu, Binbin College of Computer Science and Technology Jilin University Changchun130012 China College of Computer Science and Technology Beihua University Jilin132013 China Jilin Provincial Department of Education Key Laboratory of Intelligent Data Analysis and Processing Jilin132013 China

ISBN: (纸本)9783030514303

With the continuous development of wireless sensor technology, wireless network, big data, cloud computing and other new generation of information technology, wireless sensor networks has become a research hotspot in the field of information security and an indispensable part of people’s lives. Wireless sensor networks are extensive applied into agriculture, forestry, military, medical health, urban rail transit and other fields. Energy saving and power consumption reduction are the key technologies to be solved in wireless sensor networks. Wireless Sensor Networks take common perception and acquisition of the information of the objects to be perceived as the main purpose. In the article, firstly, the classical routing protocols for wireless sensor networks are introduced. Secondly, the relevant effective energy-saving routing protocols are analyzed and compared. Finally, the future development trend of this research is prospected. © 2021, Springer Nature Switzerland AG.

关键词： Routing protocols

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Research on Teaching Management of Applied University Based on Big data

Research on Teaching Management of Applied University Based ...

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international conference on Cyber Security Intelligence and analytics, CSIA 2021

作者： Qian, Tingting Zhang, Qiang Changshu Institute of Technology Changshu Jiangsu China

ISBN: (纸本)9783030699987

In recent years, with the rapid development of university education, more and more attention has been paid to the campus network system engineering design, which is an important part of the campus engineering construction data in the era. The establishment of a safe, convenient, environmental protection, open smart campus, to achieve university teaching, information management and life, is inseparable from the campus network infrastructure support. Big data, cloud computing and Internet of things are emerging computer technology, and the growth of data brings new challenges to management. Aiming at these problems, this paper first expounds the concept of big data, then analyzes the development status of big data, gives the application of big data in teaching management, and finally puts forward the key technology of constructing big data teaching resource sharing system. The distributed computing technology is used to realize the four basic educational administration functions in the educational administration management system, including student status management, teaching plan management, achievement management and online course selection. At the same time, in order to highlight the characteristics of online education, the functions of intelligent education cloud classroom, off campus online teaching platform docking and big data sharing knowledge base function are designed. Through the information, intelligence and standardization of the educational administration system, the Internet plus education service and resource sharing have been realized, and the purpose of breakthrough and innovation in educational administration has been achieved. Through the comparison of academic grades, it is concluded that there are 1000 students in total, 999 in practice and 1 absent. The passing rate of this grade is 98%. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

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Some thoughts on ‘intelligent campus’ of military academy

Some thoughts on ‘intelligent campus’ of military academy

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1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

作者： Liu, Jun Zhang, Xuexin Jin, Meng Basic Department Changchun Institute of Engineering and Technology Changchun China

ISBN: (纸本)9789811525674

In recent years, smart campus is gradually prevailing in our country, many colleges and universities and even primary and secondary schools have carried out the construction of ‘smart campus’. In recent years, military academies have begun to carry out exploratory construction of ‘smart campus’, but the pace of construction is slow due to various reasons. This paper puts forward some Suggestions and reflections on the construction of ‘smart campus’ in military academies. © Springer Nature Singapore Pte Ltd. 2020.

关键词： intelligent campus intelligent terminal Military education

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Camera-Based Edge analytics for Drilling Optimization 13

Camera-Based Edge Analytics for Drilling Optimization

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4th IEEE international conference on Edge computing (IEEE EDGE) / IEEE World Congress on Services (SERVICES)

作者： Gooneratne, Chinthaka P. Magana-Mora, Arturo Affleck, Michael Otalvora, William Contreras Zhan, Guodong (David) Moellendick, Timothy E. Saudi Aramco Dhahran Saudi Arabia

ISBN: (纸本)9781728182544

Hydrocarbon exploration and production involve drilling through rock formations to reach and access target hydrocarbon reservoirs deep below the ground in the safest and most efficient manner. However, drilling operations represent a challenging environment due to downhole natural uncertainties, machinery, and human factors. This study describes the development and field implementation of an intelligent monitoring and performance optimization system of drilling rig components and their associated processes. The deployed system combines smart cameras, artificial intelligence algorithms, and edge computing to pave the way for drilling automation, digitalization, and standardization. Moreover, the system is minimally invasive/non-invasive to current established drilling operations, critical for enabling a seamless integration without incurring additional operation costs.

关键词： drilling oil and gas camera-based analytics edge analytics internet of things artificial intelligence

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Computer Audit Quality Control in Big data Era

Computer Audit Quality Control in Big Data Era

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international conference on Machine Learning and Big data analytics for IoT Security and Privacy, SPIoT 2020

作者： Jiang, Lingling School of Accounting Harbin University of Commerce Harbin China

ISBN: (纸本)9783030627454

In the process of the rapid development of the Internet, the degree of informatization has continued to deepen, and it is compatible with the arrival of the era of big data. In the era of big data, some problems can be found in time by using computer networks and data collection and processing. At this stage, the use of computer-based audit quality control analysis can quickly find some omissions in the audit process, and at the same time can efficiently and targetedly resolve existing problems, so computer audits are widely used. The use and achieved good results, the importance of computer audit quality control analysis in the era of big data is more prominent. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

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Joint Resource Allocation and Scheduling for Wireless Power Transfer Aided Federated Learning 31

Joint Resource Allocation and Scheduling for Wireless Power ...

引用

31st Wireless and Optical Communications conference (WOCC)

作者： Song, Yuxiao Ji, Guangyuan Dai, Minghui Wu, Yuan Qian, Liping Lin, Bin Univ Macau State Key Lab Internet Things Smart City Macau Peoples R China Zhuhai UM Sci & Technol Res Inst Zhuhai Peoples R China Zhejiang Univ Technol Coll Informat Engn Hangzhou Peoples R China Dalian Maritime Univ Dept Commun Engn Dalian Peoples R China

ISBN: (数字)9781665469500

ISBN: (纸本)9781665469500

A promising distributed learning framework called federated learning (FL) can preserve users' local data privacy. Nevertheless, training machine learning (ML) model is a difficult task for energy-limited wireless devices (WDs). This paper studies the wireless power transfer (WPT) aided FL in which the cellular base station (BS) is responsible for charging the WDs via WPT as well as receiving WDs' locally trained model for model aggregation in each round of FL iteration. Specifically, as the WDs are charged by the BS in sequence, we consider that each WD can adopt the individual number of local iterations to generate the local model with different accuracy. We formulate a joint optimization of the each WD's processing rate, WPT-duration for the BS to charge each WD as well as each WD's number of local iterations, with the goal of minimizing the overall latency of FL iterations until reaching the convergence condition. In spite of its non-convexity, we decompose it into two subproblems and propose a simulated annealing based algorithm to solve them in sequence efficiently. Simulation results are given to show the effectiveness of our proposed algorithm and illustrate the advantages of our proposed scheme in comparison with some baseline schemes.

关键词： Federated learning wireless power transfer latency minimization

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Calculating AQI Using Secondary Pollutants for smart Air Management System 3rd

Calculating AQI Using Secondary Pollutants for Smart Air Man...

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international conference on data Management, analytics and Innovation (ICDMAI)

作者： Jyoti, Gautam Nitima, Malsa Vikas, Singhal Komal, Malsa JSS Acad Tech Educ Noida India

ISBN: (纸本)9789811393648;9789811393631

With the onslaught of the industrial revolution, the environment is suffering from severe pollution leading to major imbalances. Air Quality Dispersion Modelling can be done through one of the most efficient model "Eulerian Grid based model". Various existing methods of prediction work on the basis of models resulting in satisfactory outcomes but with some certain loopholes. This project involves methods of predicting pollutants' concentration and air quality using machine learning. The data of different sites are collected and the pollutants contributing maximum to the pollution is elucidated using machine learning based methods. Also in this project, a user-friendly, smart application system is developed which can be used to monitor the pollution produced at an individual level. The analysis of the feature stimulating the pollution level (to reach at a dangerous level) can be done with the help of machine learning tools. This paper involves calculating the amount of harmful pollutants released by any individual during their journey. Further solutions can be identified at government level to reduce these pollutants raising the pollution level.

关键词： Air pollutants AQI Eulerian grid based model Machine learning smart air pollution system

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Barriers to SMEs Adoption of Big data analytics for Competitive Advantage 4

Barriers to SMEs Adoption of Big Data Analytics for Competit...

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4th international conference on intelligent computing in data Sciences (ICDS)

作者： Willetts, Matthew Atkins, Anthony S. Stanier, Clare Staffordshire Univ Sch Digital Technol & Arts Stoke On Trent Staffs England

ISBN: (纸本)9781728180847

Small and medium-sized enterprises (SMEs) (which includes micro companies employing <;10) make a significant contribution to the UK economy accounting for 99.9% of all businesses, employing 60% of the work force and generates 2,168 pound billion;this represents 52% of the turnover of all businesses in the UK [1]. Big data analytics is rapidly being utilised by large companies on a global scale to gain competitive advantage which is well documented in the literature. However, the evidence from the literature indicates that SMEs are underutilising this technology for a variety of reasons, for example lack for expertise and cost implications. The intention of this paper is to identify barriers to the adoption of Big data analytics by SMEs to help them overcome the challenges and to exploit the benefits of Big data analytics to improve their competitive advantage which will benefit the wealth of the country particularly in the aftermath of Covid-19.

关键词： Big data Big data analytics SMEs Barriers to Big data analytics Adoption Competitive Advantage Covid-19

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international conference on Machine Intelligence and Soft computing, ICMISC 2020

International Conference on Machine Intelligence and Soft Co...

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international conference on Machine Intelligence and Soft computing, ICMISC 2020

ISBN: (纸本)9789811595158

The proceedings contain 41 papers. The special focus in this conference is on Machine Intelligence and Soft computing. The topics include: intelligent Assistive Algorithm for Detection of Osteoarthritis in Wrist X-Ray Images Based on JSW Measurement;blockchain Embedded Congestion Control Model for Improving Packet Delivery Rate in Ad Hoc Networks;predicting Student Admissions Rate into University Using Machine Learning Models;ACP: A Deep Learning Approach for Aspect-category Sentiment Polarity Detection;performance Analysis of Different Classification Techniques to Design the Predictive Model for Risk Prediction and Diagnose Diabetes Mellitus at an Early Stage;Development of an Automated CGPBI Model Suitable for HEIs in India;Range-Doppler ISAR Imaging Using SFCW and Chirp Pulse;secure Communication in Internet of Things Based on Packet Analysis;performance Investigation of Cloud computing Applications Using Steady-State Queuing Models;a Survey on Techniques for Android Malware Detection;a Random Forest-Based Leaf Classification Using Multiple Features;a Two-Level Hybrid Intrusion Detection Learning Method;Supervised Learning Breast Cancer data Set Analysis in MATLAB Using Novel SVM Classifier;Retrieving TOR Browser Digital Artifacts for Forensic Evidence;Post-COVID-19 Emerging Challenges and Predictions on People, Process, and Product by Metaheuristic Deep Learning Algorithm;An analytics Overview & LSTM-Based Predictive Modeling of Covid-19: A Hardheaded Look Across India;studies on Optimal Traffic Flow in Two-Node Tandem Communication Networks;design and Implementation of a Modified H-Bridge Multilevel Inverter with Reduced Component Count;private Cloud for data Storing and Maintain Integrity Using Raspberry Pi;efficient Cryptographic Technique to Secure data in Cloud Environment.

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