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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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Predictive Analysis of Alzheimer’s Disease Based on Wrapper Approach Using SVM and KNN 4th

Predictive Analysis of Alzheimer’s Disease Based on Wrapper...

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4th international conference on Information and Communication Technology for intelligent Systems, ICTIS 2020

作者： Devi, Bali Srivastava, Sumit Verma, Vivek Kumar School of Computing and IT Manipal University Jaipur JaipurRajasthan India

ISBN: (纸本)9789811570612

Alzheimer’s is a neurodegenerative disorder, and early prediction of Alzheimer’s disease is important for its treatment and detection. This paper proposes machine learning-based method for Alzheimer's patient detection using SVM and KNN. This proposed method uses the concept of wrapper method for feature selection to improve the accuracy of the model. This framework focuses on neurological brain disease with analytics and prediction over it. We are using machine learning with supervised classifiers for model training, testing, and evaluation. Many neurological diseases related to the brain, spine, and nerve are dementia, Alzheimer's, Parkinson’s, and brain tumors. We are focusing on the most popular neurological disease like Alzheimer’s and do all the prediction and execution over the machine learning platform. We have also evaluated the prediction level of the framework with many assessment and evaluation metrics for checking the accuracy and ability of our model. We have reported our model accuracy as 92% on average, which is higher within its dataset. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Forecasting

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5th international conference on computing in Engineering and Technology, ICCET 2020

5th International Conference on Computing in Engineering and...

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5th international conference on computing in Engineering and Technology, ICCET 2020

ISBN: (纸本)9789811548505

The proceedings contain 35 papers. The special focus in this conference is on computing in Engineering and Technology. The topics include: Dynamic virtual machine provisioning in cloud computing using knowledge-based reduction method;early detection of grape stem borer using IoT;Controlled Privacy-Aware (CPA) protocol for machine-to-machine communication in internet of things;Performance analysis of wireless sensor network (WSN);verification of 32-bit memory using layered testbench with optimum functional coverage and constrained randomization;stochastic model of a sensor node;prevention of replay attack for isolated smart grid;dangers of bias in data-intensive information systems;Performance of routing protocols using mobility models in VANET;Entity-Centric Combined Trust (ECT) algorithm to detect packet dropping attack in vehicular Ad Hoc Networks (VANETs);graph partitioning using heuristic kernighan-lin algorithm for parallel computing;experimenting with reordering model of phrase-based machine translation system for english to Hindi;investigation of imbalanced big data set classification: Clustering minority samples over sampling technique;Blended learning and analysis of factors affecting the Use of ICT in education;automation in hydroponics farming ecosystem;low power, low voltage, low drop-out on-chip voltage regulator;optimized low-energy adaptive clustering hierarchy in wireless sensor network;qoS in vertical handoff for wireless network using hungarian model and data parceling technique;Study of three-way solution for node movement in mobile Ad Hoc Networks (MANETS);ioT capable mechanism for crowd analysis;probability analysis of vehicular traffic at city intersection;automated malware identifier and analyzer;preface;UAV communication in FANETs with metaheuristic techniques;animal repellents from agricultural fields.

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A data Privacy Protection Scheme for Underwater Network

A Data Privacy Protection Scheme for Underwater Network

引用

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

作者： Chen, Dandan Sun, Shijie Huang, Xiangdang Yang, Qiuling School of Computer Science and Cyberspace Security Hainan University Haikou570228 China School of Information and Communication Engineering Hainan University Haikou570228 China

ISBN: (纸本)9783030627423

Underwater sensor network is deployed in unattended underwater environment, which can be used to collect sensitive information. It has problems such as low bandwidth, high energy consumption and difficulty in ensuring data security. In order to reduce energy consumption and ensure data security, this paper proposes a data privacy protection scheme for underwater network. This scheme makes an upload decision when the node collects data, and compresses the uploaded data in the ordinary node to reduce the data transmission volume and energy consumption;furthermore, the cluster head node aggregates the data after receiving the data packets sent by the node to reduce the data redundancy;finally, the data packets are segmented to ensure the data security. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Energy utilization

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A Blockchain-based Model Sharing and Calculation Method for Urban Rail intelligent Driving Systems 23

A Blockchain-based Model Sharing and Calculation Method for ...

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23rd IEEE international conference on intelligent Transportation Systems (ITSC)

作者： Liang, Hao Zhang, Yong Xiong, Han Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing 100044 Peoples R China

ISBN: (纸本)9781728141497

In urban rail transit systems, the intelligent driving system is gradually replacing manual driving for its high safety, punctuality, and stopping accuracy. With the development of big data analytics, the data-driven intelligent driving system becomes a research focus. Traditional data-driven intelligent driving systems suffer from inadequate data. Due to lacking effective incentives and trust, data from different urban rail operators cannot be shared directly. In this paper, we propose a framework that uses blockchain technology to realize sharing and collaborative training of intelligent driving models between operators. In this framework, we use blockchain-based distributed federated reinforcement learning methods to complete intelligent driving calculations. We use smart contracts to implement the management of the entire federal reinforcement learning. Operators use local historical data to participate in intelligent driving training based on Q-network by exchanging encrypted model parameters, and optimize the safety distance, energy consumption, and punctuality of urban rail transit systems. Simulation results show that our proposed distributed federated reinforcement learning method can significantly improve the intelligent driving system performance.

关键词： Blockchain

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Study of the Soybean Imitation Cheese Based on intelligent Systems and Big data analytics

Study of the Soybean Imitation Cheese Based on Intelligent S...

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international conference on Cyber Security Intelligence and analytics (CSIA)

作者： Zhang, Zhiguo Zeng, Qi Qilu Univ Technol Shandong Acad Sci Coll Food Sci & Engn Jinan 250353 Shandong Peoples R China

ISBN: (纸本)9783030152352;9783030152345

The imitation cheese is the product with the cheese characteristics which can meet the specific requirements by using the non-milk-derived protein and fat or the full substitution of the milk protein and the milk fat. This paper introduces the production principles, processes and key control points of the imitation cheese with the soybean as main raw material, summarizes the researches and development of the soybean imitation cheese in recent years, and forecasts the market prospect of the soybean imitation cheese in China.

关键词： Soybean imitation cheese Functional characteristics Key control points Prospects

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IoT system accomplishment using blockchain in validating and data security with cloud 4

IoT system accomplishment using blockchain in validating and...

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4th international conference on IoT in Social, Mobile, analytics and Cloud, ISMAC 2020

作者： Solomon Doss, J. Kingsleen Kamalakkannan, S. Department of Computer Science Chennai India

ISBN: (纸本)9781728154640

In a block channel IoT system, sensitive details can be leaked by means of the proof of work or address check, as data or application Validation data is applied on the blockchain. In this, the zero-knowledge evidence is applied to a smart metering system to show how to improve the anonymity of the blockchain for privacy safety without disclosing information as a public key. Within this article, a blockchain has been implemented to deter security risks such as data counterfeiting by utilizing intelligent meters. Zero-Knowledge Proof, an anonymity blockchain technology, has been implemented through block inquiry to prevent threats to security like personal information infringement. It was suggested that intelligent contracts would be used to avoid falsification of intelligent meter data and abuse of personal details. © 2020 IEEE.

关键词： Blockchain

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Fuzzy-Based Predictive analytics for Early Detection of Disease—A Machine Learning Approach 5th

Fuzzy-Based Predictive Analytics for Early Detection of Dise...

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5th international conference on ICT for Sustainable Development, ICT4SD 2020

作者： Kakulapati, V. Sai Sandeep, R. Kranthi kumar, V. Ramanjinailu, R. Sreenidhi Institute of Science and Technology Yamnampet Ghatkesar HyderabadTelangana501301 India

ISBN: (纸本)9789811582882

Influenza is significant promising and re-emerging contagious disease, causing high morbidity and mortality throughout the world. Influenza also called swine flu, hoard flu, pig flu. The primary task of healthcare providers is providing diagnostic product services at low costs and to diagnose patients accurately. The use of data analytics and machine learning is a breakthrough technology that can have a significant impact on the healthcare field. Machine learning methods can be used for disease identification because they mainly apply to data themselves and give priority to outcomes of specific tasks. In this work, a framework of classification and regression trees (CART) algorithm is to create the fuzzy rules to employ for improved disease prediction. Validate the proposed method by choosing public medical datasets. Results on swine flu data demonstrate that our method distinguished the enhancement of the disease prediction accuracy. The implementation results exhibit that the aggregation of two methods such as fuzzy rule-based CART algorithm with irrelevant data elimination methods that could be useful in predicting disease. The proposed system can be helpful for healthcare providers as a healthcare analytical technique. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fuzzy inference

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Application of Image data analytics for Immediate Disaster Response 20

Application of Image Data Analytics for Immediate Disaster R...

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21st international conference on Distributed computing and Networking (ICDCN)

作者： Chaudhuri, Neha Bose, Indranil Indian Inst Management Management Informat Syst Kolkata W Bengal India

ISBN: (纸本)9781450377515

This study identifies a novel source of data, i.e. images from smart urban infrastructures, that would be helpful in effective disaster management decision-making. For this purpose, we collected images from disaster-hit environments of Central Mexico (2017 earthquake). Also, this study utilizes deep learning convolutional neural network to analyze this novel dataset and evaluates the model effectiveness and technical viability during crisis scenarios. TensorFlow was utilized for the image classification task. The findings have important significance for effective disaster response.

关键词： Convolutional neural networks deep learning disaster management smart urban environments image classification

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A Privacy Preserving Framework for smart Cities utilising IoT, smart Buildings and Big data 22

A Privacy Preserving Framework for Smart Cities utilising Io...

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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： Inibhunu, Catherine Carolyn McGregor, A.M. Ontario Tech University OshawaON Canada

ISBN: (纸本)9781728176499

There are many possibilities for a smart city that is enabled with smart buildings and well provisioned and managed internet of things (IoT) frameworks. The benefits of such frameworks can be felt in multiple domains. On planning an integrated city, data captured from the infrastructures within a city can be analyzed and utilized for effective resource and services provisions within the city. In urban mobility, automated planning and demand responsive to public transportation integrated with self-driven vehicles. On safety, security and health of cities and their citizens, real-Time surveillance and analytics can lead to better provision of emergency services, weather planning, early warnings on floods, tornadoes, man-made disasters and pandemics. To facilitate such services requires frameworks that can be effective at acquisition, processing and analysis of large volumes of data from vast systems as well as citizens within a city while preserving the security and privacy of data *** this paper, (a) a brief overview on the current landscape on smart cities is provided, the architectures and frameworks proposed to support data management, (b) highlights research opportunities that are still open, (c) proposes a privacy preserving computation framework that can be explored for a robust smart city ecosystem (d) and outlines the benefits possible with such a proposed framework. © 2020 IEEE.

关键词： Internet of things

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The Film Industry Leaps into Artificial Intelligence: Scope and Challenges by the Filmmakers 1st

The Film Industry Leaps into Artificial Intelligence: Scope ...

引用

1st FICR international conference on Rising Threats in Expert Applications and Solutions, FICR-TEAS 2020

作者： Datta, Angana Goswami, Ruchi Jaipur India

ISBN: (纸本)9789811560132

Artificial Intelligence (AI) is usually associated with assisting humans with tasks that are either ordinary or can be done better with automation. Since then technology grew, representation of AI and Robotics also evolved in films, especially the robots, which has given surplus roles from the antagonist, protagonist, the romantic, to a deadly weapon capable of machine learning. With the advent of CGI in the 2000s, an AI flareup took place in the world of cinema and came up with worthy concepts of AI-based movies. Today, the AI system can robotically deliver advanced visual effects which makes it easier for performers to act their alternative characters and creatures. data analytics and AI technology have already made their debut in films and are going to play a bigger role in the filmmaking process. Till now, films were made on AI. In the future, AI will be writing films, robots will perform, and animation will be done by a deep learning algorithm process. The study aimed to observe the AI technologies used in the film industry. The methods adopted to achieve the goals of the study is the content analysis method. The study will conclude that technology is constantly improving, and AI can become an inescapable force that could renovate the films and take it to the next level. © 2021, Springer Nature Singapore Pte Ltd.

关键词： data analytics

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