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Predictive analytics for cardiovascular disease diagnosis using machine learning techniques 5th

Predictive analytics for cardiovascular disease diagnosis us...

引用

5th international conference on Advanced Machine Learning Technologies and Applications, AMLTA 2020

作者： Muniasamy, Anandhavalli Muniasamy, Vasanthi Bhatnagar, Roheet College of Computer Science King Khalid University Abha Saudi Arabia Department of CSE Manipal University Jaipur Jaipur India

ISBN: (纸本)9789811533822

Medical data can be mined for effective decision making in the presence of disease analysis. Globally, cardiovascular alias heart disease is one of the highly rated causes of death [1] disease which will lead to 76% of the deaths [2] by the year 2030. Currently, the techniques of machine learning and predictive analytics have proven importance in medical data analysis. In a nutshell, this paper aims to apply six classifiers namely artificial neural network, support vector machine, decision tree, nearest neighbor, linear discriminant analysis, random forest, and to predict the presence of heart diseases in the patient’s datasets. Moreover, the performance of these classifiers on three heart disease datasets is compared. The results reveal that RF, LDA, DT, and ANN have performed better than SVM and KNN in terms of accuracy, recall, F1-score, confusion matrix, and error rate. © Springer Nature Singapore Pte Ltd 2021.

关键词： Support vector machines

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Research on Escape Strategy Based on intelligent Firefighting Internet of Things Virtual Simulation System 1

引用

2nd international conference on Artificial Intelligence in China, ChinaAI 2020

作者： Wang, Hai Sun, Guiling Gao, Yi Li, Xiaochen Teaching Center for Experimental Electronic Information College of Electronic Information and Optical Engineering Nankai University Tianjin300350 China

ISBN: (数字)9789811585999

ISBN: (纸本)9789811585982

intelligent firefighting accomplishes the intellectualization of city fire protection by utilized the latest technologies such as the Internet of Things (IOT), artificial intelligence, virtual reality, and mobile Internet plus. Besides, it cooperates with the professional application of big data cloud computing platform, fire alarm intelligence judgment, and so on. intelligent fire control is not only the digital foundation of fire information service, but also an important part of smart perception, interconnection, and intelligent application architecture in smart city. In this paper, the virtual simulation technology is used to simulate the real fire scene. According to the specific scene, the appropriate network framework and communication protocol are selected. Different types of sensors are utilized to collect the real-time fire data. Through the simulation calculation and mathematical manipulation, the escape strategy and escape route are determined for the trapped people. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fires

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Improving Information Security in smart City 5

Improving Information Security in Smart City

引用

5th international conference on Communication and Information Systems, ICCIS 2021

作者： Zhang, Wei Palaoag, Thelma University of the Cordilleras College of Information Technology and Computer Science Baguio2600 Philippines

ISBN: (纸本)9781665422161

With the introduction of the concept of smart city and the continuous advancement of its construction process, it makes people more intelligent and convenient in urban travel, shopping, medical treatment and parking. However, in the process of smart city construction, the application of big data, IoT, artificial intelligence and other information technologies, it not only makes the city more convenient, but also brings new information security risks. In order to improve the security of information in the smart city environment, this paper starts with the physical perception layer, network communication layer, computing & storage layer, data & service support layer and application layer that constitute the smart city. This paper uses literature analysis method to make a statistical analysis of the attack cases of each layer of the basic architecture of smart city, and analyzes the information security risks of each layer, such as security risks at the physical perception layer, network communication layer, application layer, and cloud service layer. In the cloud service layer, starting from the security threats faced by the cloud system, through the study of network traffic analysis technology, network intrusion detection, vulnerability assessment methods, *** is proposed to improve the throughput rate of the cloud system by using four-stage fluidization PF_RING processing method when analyzing and evaluating the traffic in the cloud system. The neural network analysis is used to check the security of cloud system, and the best selection algorithm is used to evaluate the security of cloud system. Experiments show that the method proposed in this paper can handle real-Time network traffic capture and vulnerability detection in cloud system. Through calculation by the object of attack difficulty level to identify vulnerable object, according to the identity to enhance the level of protection, intrusion protection capacity up to 94.1% on average, to strengthen safety

关键词： Network security

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An Efficient Edge Analytical Model on Docker Containers for Automated Monitoring of Public Restrooms in India

An Efficient Edge Analytical Model on Docker Containers for ...

引用

IEEE international conference on Advanced Networks and Telecommunications Systems (IEEE ANTS)

作者： Gore, Rajasi Banerjea, Shashwati Tyagi, Neeraj Saurav, Sanu Acharya, Deepesh Verma, Vishesh Motilal Nehru Natl Inst Technol Allahabad Comp Sci & Engn Dept Prayagraj 211004 Uttar Pradesh India

ISBN: (纸本)9781728192901

The Government of India proposed "Clean India Mission" in 2014 that has led to the establishment of many public restrooms across the country. The purpose of this mission is to provide hygienic toilets to prevent open defecation and eradicate water-borne diseases. These restrooms are assigned human resources. However, the majority of them are in bad condition for usage. For increasing the availability of toilets, there is a requirement of a smart sanitation system for its automated monitoring. Moreover, rural and semi-urban restroom locations suffer from limited network connectivity. Thus, restroom state analysis needs to be performed near the site for seamless monitoring. This paper proposes an edge analytics framework based on the Internet of Things (IoT) and fog computing to analyze restroom data at the network edge and provide intelligent decisions. The machine learning model runs over Docker containers for analyzing data for the resource-constraint fog nodes. The choice of a machine learning model for the analysis depends on the model's performance in classification and on Docker containers over Raspberry Pi. Results show Adaptive Neuro-Fuzzy Inference System (ANFIS) is suitable over Docker containers for handling restroom data at the edge of the network.

关键词： Internet of Things Fog computing Edge analytics Raspberry Pi Docker Container

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An Enterprise Architecture based on Cloud, Fog and Edge computing for an Airfield Lighting Management System 24

An Enterprise Architecture based on Cloud, Fog and Edge Comp...

引用

24th IEEE international Enterprise Distributed Object computing conference (IEEE EDOC)

作者： Mijuskovic, Adriana Bemthuis, Rob Aldea, Adina Havinga, Paul Univ Twente Enschede Netherlands

ISBN: (数字)9781728164717

ISBN: (纸本)9781728164717

Followed by the introduction of IoT and new sustainable technologies, energy management, Quality of Service and decrease of communication costs become important and complex for enterprise systems at airports. The aviation authorities' reports reveal that the airport ICT investments are mainly focused on travel safety, mobile commerce, and new technologies. The main idea behind a smart airport is to deploy IoT network managed through a Cloud-Fog-Edge paradigm for a smart platform and optimize the airport's efficiency. An IoT cloud-based platform solution supports multiple types of data, advanced analytics, artificial intelligence, and machine learning techniques. However, cloud computing has certain limitations such as increased delay in data reporting, increased latency in accessing user network, limited customization, increased reliance on external network and data privacy. Fog-Cloud and Edge-Cloud paradigms can overcome the weaknesses of cloud computing architectures. Therefore, to understand the organizational impact of combining the usage of cloud, fog, and edge computing, we created an enterprise architecture that can be applied in a smart airport demonstration study. The enterprise architecture modelling was done by using ArchiMate and validated by means of an expert assessment and prototype implementation.

关键词： enterprise architecture smart airport solutions cloud computing fog computing edge computing

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Vehicle Refueling Behavior Model Based on Spatio-Temporal Big data Monitoring Platform

Vehicle Refueling Behavior Model Based on Spatio-Temporal Bi...

引用

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

作者： Wang, Wenbin China Automotive Technology and Research Center Co. Ltd Tianjin China

ISBN: (纸本)9783030514303

During the actual use of vehicles, a large number of irregularities such as refueling at illegal gas station or mobile gas refueling vehicles, caused the unqualified diesel to be refilled into the vehicle, affecting the normal operation of the engine aftertreatment system, the exhaust emission result not meeting the national emission standards, and causing vehicle speed limited, penalized by Ministry of Ecological Environment. Identifying the quality of the gas is a prerequisite to ensure the normal operation of the vehicle’s aftertreatment system. This paper introduces an spatio-temporal big data calculation platform based on improved data indexing algorithm, proposes two models, that is, analysis of gas position and gas station type matching, applies three analysis rules, that is, noise data removal, data frequency reduction, and category determination, performs three categories of gas stations to complete the identification and analysis of vehicle refueling behavior in real-time monitoring data. The application in the real Internet of Vehicles (IoV) monitoring platform shows that the results obtained are of great significance for determining the cause of the engine aftertreatment system problem, defining the responsibilities, and guiding the technical upgrade of the aftertreatment system. © 2021, Springer Nature Switzerland AG.

关键词： Vehicles

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Transactional data analytics for Inferring Behavioural Traits in Ethereum Blockchain Network 16

Transactional Data Analytics for Inferring Behavioural Trait...

引用

IEEE 16th international conference on intelligent Computer Communication and Processing (ICCP)

作者： Bhargavi, M. S. Katti, Sushmitha M. Shilpa, M. Kullcami, Vaishnavi P. Prasad, Supraja Bangalore Inst Technol Dept Comp Sci & Engn Bengaluru Karnataka India

ISBN: (纸本)9781728190808

Ethereum is a blockchain based development platform for users to build and deploy decentralized applications and smart contracts. Transactions substituting money over Ethereum space are carried out using Ethereum's cryptocurrency 'Ether'. Though the decentralization and public ledger recording of the transactions proves its limpidity, the anonymity of the users, hiding their true identity behind the addresses echoes the need for discerning the behavioural traits in transactions. The appalling nature of Ethereum transactions to have both, security and threat at a comparable level, demands analytics for inferring traits for better perspectives and insights. This research work focuses on characteristic analysis of Ethereum transaction space for inferring behavioural traits in supervised and unsupervised context. In an unsupervised environment, raw transaction data is extradited to a tabular transaction structure by selecting appropriate features. The data is further clustered and validated to form coherent groupings of similar patterns. The clusters are characteristically analyzed based on the features through Radar plots for inferring behavioural traits. In supervised context, labelled transactions are represented using histograms and feature-based characteristic analysis is performed to infer traits. Such analytics lay foundations for future deeper analysis that can be used to discover trends and patterns to understand the transaction network, enhancement of trading strategies, identification of but activities, anomaly detection and several others.

关键词： Ethereum Blockchain analytics Clustering Behaviour

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Visual Object Detection based LiDAR Point Cloud Classification

Visual Object Detection based LiDAR Point Cloud Classificati...

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IEEE international conference on Big data and smart computing (BigComp)

作者： Muhammad, Sualeh Gon-Woo, Kim Chungbuk Natl Univ Intelligent Robot Lab Control & Robot Engn Dept Cheongju South Korea

ISBN: (纸本)9781728160344

The environmental perception plays a pivotal role in autonomous driving tasks and demands robustness in cluttered dynamic environments such as complex urban scenarios. LiDAR being one of the popular perceptual sensor, suffers with large number of inaccurate object detections. This work is an extension of an ongoing research on multiple object detection and tracking. Where, Neural Network based approach is considered for visual detection to aid the LiDAR point cloud processing, and to address the inherent shortcoming of the sensor. It is inferred that the proposed framework would perform in real-time on an embedded platform. In addition, the separate processing of visual and LiDAR sensor data will enable switching to a light weight LiDAR only setup in runtime when required.

关键词： Object detection LiDAR visual-LiDAR calibration point cloud classification

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Expectation Differences Between Students and Staff of Using Learning analytics in Finnish Universities

Expectation Differences Between Students and Staff of Using ...

引用

international conference on Information Technology and Systems (ICITS)

作者： Okkonen, Jussi Helle, Tanja Lindsten, Hanna Tampere Univ Tampere 33014 Finland

ISBN: (纸本)9783030406905;9783030406899

The aim of this paper is to examine and discuss the dissonance between expectations and hopes towards utilising learning analytics in Finnish universities. The analysis is based on data collected among Finnish university students and staff in spring 2019. As a key result we present, that the university staff found it important that all data and information should and could be used for various planning, management and counselling purposes. At the same time student found it unnecessary or even harmful to allow university staff examine their personal data. We therefore propose that universities should develop and implement specific policy for using of analytical data.

关键词： Learning analytics Higher education User expectations Survey

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The Research on the Development and Utilization of Hospital Archive Information in the Big data Era

The Research on the Development and Utilization of Hospital ...

引用

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

作者： Yun, Dawei Zhou, Zhengjun She, Wei Hainan Vocational University of Science and Technology HaikouHainan China

ISBN: (纸本)9783030627423

With the continuous improvement of people’s health awareness, the intensity and working methods of hospital archives management have undergone great changes. What is certain is that if the hospital continues to adopt the traditional file information management model, it will inevitably cause certain obstacles to the hospital management level and development speed. To this end, this article analyzes the development and utilization of hospital archives information in the era of big data based on the impact of big data on hospital archive management, combined with the problems of hospital archive management, and aims to standardize hospitals. The usage of file information makes the hospital file management develop in the direction of digitization and informationization. © 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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