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检索条件"任意字段=International Conference on Intelligent and Smart Computing in Data Analytics, ISCDA 2020"

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A big data compatible naive measure for estimating the landscape dynamics using open geospatial datasets

A big data compatible naive measure for estimating the lands...

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

作者： Ghosh, Suddhasheel Dey, Saurav Jawaharlal Nehru Engineering College Department of Civil Engineering Aurangabad India Associate Research Analyst P. E. Analytics Gurgaon India

ISBN: (纸本)9781728159706

The process of urbanisation has been reported to be a driver of global climatic change. Rapid urbanisation is leading to a drastic change in the land use and land cover (LULC) pattern of any urban area. Urban LULC dynamics can be understood through the use of multi-Temporal geospatial datasets. The existence of multi-sensor and multi-Temporal remote sensing datasets enable the understanding of LULC dynamics. In this paper, we take Aurangabad as a pilot project for study. Aurangabad is a city located in the Marathwada region of the Maharashtra state in India, and is faced with the juxtaposition of the growing industry and the cultural heritage. The city has has been included in the list of 100 smart cities to be developed in India, by the Indian government. This paper proposes a new metric and area based method for the measurement of urban dynamics, and identification of hotspots. The superiority of the metric with respect to the Shannon's Entropy is also illustrated. The approach demostrated in this paper is extendable to the measurement of LULC dynamics and hotspot identification in a Big data environment as well. © 2020 IEEE.

关键词： Dynamics

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Energy- And Time-Efficient Tasks Offloading and Dynamic Resource Allocation in smart City 13

Energy- And Time-Efficient Tasks Offloading and Dynamic Reso...

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2020 IEEE Congress on Cybermatics: 13th IEEE international conferences on Internet of Things, iThings 2020, 16th IEEE international conference on Green computing and Communications, GreenCom 2020, 13th IEEE international conference on Cyber, Physical and Social computing, CPSCom 2020 and 6th IEEE international conference on smart data, smartdata 2020

作者： Zhao, Bohai Peng, Kai Zhang, Haoqi Xu, Xiaolong School of Engineering Huaqiao University Quanzhou China The Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information Nanjing University of Science and Technology Ministry of Education Nanjing China

ISBN: (纸本)9781728176475

With the rapid development of information society, people urgently need to develop the traditional city model into a highly information and intelligent city model to meet the needs of users and the development of sociality. Therefore, people put forward a new concept called smart city. Correspondingly, as a concept of multiple intelligence, smart city has also got an excellent opportunity for development in terms of service performance with the emergence of mobile cloud computing, mobile edge computing and some new technologies. Specifically, based on the concept of mobile edge computing, there are many edge servers are installed close to users in smart city, and users can offload tasks to these edge servers to obtain better services by computation offloading. However, in the further development process of this new concept, smart city still need to face some problems in terms of energy consumption, latency, resource utilization and even in privacy security. These issues will affect the service quality of smart city seriously. In view of this, the optimization problem of smart city is studied in this paper. Considering the diversity and large number of users, the tasks generated are defined as a series of complex tasks composed of time-constrained workflows and concurrent constrained workflows, and an energy- and time-efficient method with privacy preservation is proposed, which can optimize the energy consumption, time consumption and the resource of the system jointly. Experimental results have shown that the proposed method can reduce the energy consumption and improve resource utilization for the system effectively. © 2020 IEEE.

关键词： smart city

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Application of association rules algorithm in teaching reform under the background of internet plus era – taking the teaching reform of international trade as an example

Application of association rules algorithm in teaching refor...

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

作者： Zhong, Feiyan Guangzhou City Construction College Guangzhou510925 China

ISBN: (纸本)9789811525674

Under the background of internet plus era, the teaching reform of international trade major is imperative, but the reform is very difficult. Therefore, an algorithm based on association rules was established to calculate and analyze the related issues of teaching reform. In this way, the difficulty of artificial reform can be simplified, and the goal of reform can be achieved. Through the test and experiment of algorithm, it is proved that our algorithm has great advantages. It not only has short time and high accuracy, but also is an algorithm that has been utilized well, which is suitable for our teaching reform. © Springer Nature Singapore Pte Ltd. 2020.

关键词： international trade

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Effects of the Use of smart Glasses on Eyesight 2nd

Effects of the Use of Smart Glasses on Eyesight

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2nd international conference on Human Systems Engineering and Design (IHSED) - Future Trends and Applications

作者： Herzog, Natasa Vujica Beharic, Amer Univ Maribor Fac Mech Engn Maribor Slovenia Healthcare Ctr Dr Adolfa Drolca Maribor Maribor Slovenia

ISBN: (纸本)9783030279288;9783030279271

smart glasses, also named as data glasses, are an example of Head Mounted Display (HMD) with a great potential in different manufacturing environments. They collect data from a wireless network and project information directly into the user's eye. It is evidenced from the literature that HMD can cause headaches, pressure in the eyes, problems with focusing and difficulties with text reading. Therefore, we tried to research whether use of smart glasses could be harmful for the human eye or not. To study the addressed problems, a research was performed in testing warehouse environment at the Faculty of Mechanical Engineering. Users comfort was tested through questionnaire and several eyes investigations before and after use of smart glasses in Healthcare Center Maribor. The results of the performed ophthalmologic tests show that there are some statistically significant differences between tests results performed before and after use of smart glasses that cannot be overlooked.

关键词： Human-systems integration smart glasses Industry 4.0 Warehouse

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intelligent Correction Algorithm for Energy Metering data for Lean Management

Intelligent Correction Algorithm for Energy Metering Data fo...

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international conference on Cyber Security Intelligence and analytics, CSIA 2020

作者： Ye, Bin Department of Mechanical and Electrical Engineering Shandong Vocational College of Light Industry Zibo255300 China

ISBN: (纸本)9783030433086

The traditional method multiplies the synthetic error and the data reading of the energy metering system, and selects the corrected measured value. The result cannot meet the accuracy requirement of the energy metering data. To this end, an intelligent correction algorithm for energy metering data for lean management is proposed. By determining the data correction value, the intelligent correction of the data error of the energy metering system is completed, and the simulation experiment is performed on the result. The experimental results show that the data of the energy metering system is accurate after the error correction is completed by the proposed method. © Springer Nature Switzerland AG 2020.

关键词： Error correction

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3rd international conference on Computer Science, Engineering and Education Applications, ICCSEEA 2020

3rd International Conference on Computer Science, Engineerin...

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3rd international conference on Computer Science, Engineering and Education Applications, ICCSEEA 2020

ISBN: (纸本)9783030555054

The proceedings contain 59 papers. The special focus in this conference is on Computer Science, Engineering and Education Applications. The topics include: Construction of Individual Learning Scenarios;technology-Enhanced Financial Education and Sustainability Goals;health Status Recognition System for Communication Equipment Based on data Mining;use of Sustainable Innovation in Information System: Integrate Individual’s Spirit and Team Climate;relations of the Genetic Code with Algebraic Codes and Hypercomplex Double Numbers;research on Logistics Center Location-Allocation Problem Based on Two-Stage K-Means Algorithms;operational Intelligence Software Concepts for Continuous Healthcare Monitoring and Consolidated data Storage Ecosystem;method of Recognition and Indexing of People’s Faces in Videos Using Model of Machine Learning;deduplication Method for Ukrainian Last Names, Medicinal Names, and Toponyms Based on Metaphone Phonetic Algorithm;two-Layer Perceptron for Voice Recognition of Speaker’s Identity;significant Parameters of the Keystroke for the Formation of the Input Field of a Convolutional Neural Network;detection of Ventricular Late Potentials in Electrocardiograms Using Machine Learning;smart Prothesis: Sensorization, Humane Vibration and Processor Control;optimization of Stock Basing on Improved Grey Prediction Model: A Case Study on Garment Supply Chain;improved Post-quantum Merkle Algorithm Based on Threads;improvement of Merkle Signature Scheme by Means of Optical Quantum Random Number Generators;integrated Water Management and Environmental Rehabilitation of River Basins Using a System of Non-linear Criteria;distribution of Resources Between Composite Applications in a Hyperconverged System;the Possibilistic Gustafson-Kessel Fuzzy Clustering Procedure for Online data Processing;information System Penetration Testing Using Web Attack Automated Simulation.

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Log analytics in HPC: A data-driven Reinforcement Learning Framework

Log Analytics in HPC: A Data-driven Reinforcement Learning F...

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39th IEEE international conference on Computer Communications (IEEE INFOCOM)

作者： Luo, Zhengping Hou, Tao Nguyen, Tung Thanh Zeng, Hui Lu, Zhuo Univ S Florida Tampa FL 33620 USA Intelligent Automat Inc Rockville MD USA

ISBN: (纸本)9781728186955

High Performance computing (HPC) has been employed in many fields such as aerospace, weather forecast, numerical simulation, scientific research etc. Security of HPC, especially anomaly/intrusion detection, has attracted many attentions in recent years. Given the heavily instrumented property of HPC systems, logs become an effective and direct data source that can be utilized to evaluate the system status, further, to detect anomalies or malicious users. In this paper, we offer a novel perspective, treating the anomaly detection in HPC as a sequential decision process, and further applying reinforcement learning techniques to learn the state transition process, based on which we build a framework named as ReLog to detect anomalies or malicious users. Besides, a common challenge of employing machine learning techniques is lacking sufficient data, we provide a generative adversarial network (GAN)-based solution to generate sufficient training data in HPC. The experimental validations are conducted based on real-world collected MPI logs, and our results demonstrate a 93% of detection accuracy on the collected dataset.

关键词： High performance computing security reinforcement learning defenses and attacks log analytics

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Optimizing Hospital Resources using Big data analytics with Standardized e-Clinical Pathways 18

Optimizing Hospital Resources using Big Data Analytics with ...

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18th IEEE international conference on Pervasive intelligent and computing (PICom)

作者： Alahmar, Ayman Benlamri, Rachid Lakehead Univ Dept Software Engn Thunder Bay ON Canada

ISBN: (纸本)9781728166094

In today's overloaded and costly healthcare systems, more research focusing on hospital resource optimization is needed. Resource optimization can reduce costs and improve healthcare outcomes. Optimization can even save the lives of patients when resulting, for example, in more efficient time management in hospitals. Optimized time utilization frees caregivers for treating more patients and frees hospital testing rooms/beds for the high volumes of patients. Without caregivers and rooms, some patients may die while waiting for their turns. In this research, we show the importance of automated and fully digitized electronic Clinical Pathways (e-CPs) in the field of hospital resource optimization. This is because the full digitization of CPs provides the rich data needed for optimization and enables physicians and healthcare administrators to have control over the "micro" CP data that is missing in other health information systems. After addressing our novel CP automation framework, we illustrate our contribution to optimizing hospital resources through three scenarios. In the first scenario, we show how communicating the best CP practices can improve the efficiency of CPs and patient treatment, resulting in faster, lower-cost, and optimized healthcare provision for patients. Next, we address the issue of unnecessary blood tests ordered in hospitals and show how blood test cost/count analytics enables healthcare providers to reduce costs and optimize resources. The third scenario is related to time management. We illustrate how CP intervention time analytics can pinpoint sources of inefficient time management in hospitals. Optimizing hospital resources is an important research topic that has great effects on the cost and efficiency of our healthcare systems, as well as the safety and well-being of the whole society.

关键词： hospital resource optimization clinical pathway ontology engineering SNOMED CT HL7 data analytics

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data Security Risk and Preventive Measures of Virtual Cloud Server Based on Cloud computing

Data Security Risk and Preventive Measures of Virtual Cloud ...

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international conference on Cyber Security Intelligence and analytics, CSIA 2020

作者： Xia, Ping Guangzhou College of Technology and Business Guangdong China

ISBN: (纸本)9783030433055

Cloud computing is another technological revolution of the Internet. It is the product of the development of the information age, which has changed the way people use data and applications. The core idea of cloud computing is to virtualize server entities into logical servers, forming a large cloud resource pool, and providing services such as common computing, parallel processing, and shared resources. However, with the continuous development of cloud computing technology, the large amount of user and application data processed on the virtual cloud server is vulnerable to various security threats. This paper mainly analyzes the data security risks of the virtual cloud server from three aspects of data transmission, data storage, and data application, and proposes corresponding data security precautions to ensure the data security of the virtual cloud server and build a good cloud service network security environment. © Springer Nature Switzerland AG 2020.

关键词： Risk assessment

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E-Health Parkinson Disease Diagnosis in smart Home Based on Hybrid Intelligence Optimization Model 5th

E-Health Parkinson Disease Diagnosis in Smart Home Based on ...

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5th international conference on Advanced intelligent Systems and Informatics (AISI)

作者： Anter, Ahmed M. Zhang, Zhiguo Shenzhen Univ Hlth Sci Ctr Sch Biomed Engn Shenzhen 518060 Peoples R China Beni Suef Univ Fac Comp & Artificial Intelligence Benisuef 62511 Egypt

ISBN: (纸本)9783030311292;9783030311285

The use of internet of things (IoT) in smart home with medical devices within a connected health environment promotes the quick flow of information, the patient's vital parameters are transmitted by medical devices onto secure cloud based platforms where they are stored, aggregated and analyzed. IoT helps to store data for millions of patients and perform analysis and diagnosis in real-time, promoting an evidence-based medicine system. Different intelligence optimization models can be integrated with IoT to improve the patient healthcare. In this paper, an intelligent optimization model is proposed for monitoring patients with Parkinson's disease (PD) based on UPDRS assessment (Unified Parkinson's Disease Rating Scale) from voice records in smart home. Ant lion optimization algorithm (ALO) and adaptive extreme learning machine (ELM) based on differential evaluation (DE) algorithm is proposed;namely (ALO-DEELM), for PD diagnosis. Using this model, home residents will get feedback and keep track on their PD situation. ALO-DEELM model is compared with different machine learning (ML) prediction algorithms and showed the superiority based on different measures. Moreover, the experimental results showed that the proposed model is effective and can significantly reduce the prediction computational time of UPDRS scores. The proposed ALO-DEELM has the potential to be implemented as an intelligent system for PD prediction in healthcare.

关键词： Regression Internet of things (IoT) Parkinson's disease (PD) Differential evaluation (DE) ALO-DEELM UPDRS

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