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Cloud computing for Suitable data Management and Security within Organisations 4

Cloud Computing for Suitable Data Management and Security wi...

引用

4th international conference on Inventive Research in computing Applications, ICIRCA 2022

作者： Bhattacharyya, Lusaka Purohit, Supriya G Fatmawati, Endang Sunil, D.M. Toktakynovna, Zhanar Sriramakrishnan, G.V. Singhania University Science Information Security Domain India University Vtu Computer Science & Engineering Karnataka Belagavi India Universitas Diponegoro Indonesia Reva University Ece India Kobenkulova International Education Corporation Almaty Kazakhstan Sikkim Manipal Institute of Technology Sikkim Manipal University Computer Science and Engineering India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

Different contemporary organisations are using cloud computing application in business operation activities to gain competitive advantages over other competitors. It also helps in promoting flexibility of the business operation activities. Cloud computing involves delivery of different computer resources to data centres over the internet services. Different kinds of delivered computer resources include data storage, servers, database, analytics, software, networking, and other types of data applications etc. In this present era of data breaches, cloud computing ensures security protocols to protect different kinds of sensitive transaction data and confidential information. Use of cloud computing ensures that a third party individual does not tamper the data. Use of cloud computing also provides different kinds of competitive advantages to the organisations. Cloud computing also helps in providing efficiency and a platform for innovation for the contemporary organisations. theoretical frameworks are usedin the literature review section to determine the important roles of cloud computing in effective data and security management in the organisations. It is also justified in the research work that qualitative methodology is suitable for the researcher to meet the developed research objectives. A secondary data analysis approach has been considered by the researcher in this study to carry out the investigation and meet the developed objectives. From the findings, few challenges associated with the cloud computing system have been identified. Proper recommendations are suggested at the end of the study to help future researchers in overcoming the identified associated challenges. © 2022 IEEE.

关键词： Information management

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Research on Fatigue Life Intelligent Control System of Deepwater Jacket Platform based on Digital Twin 4

Research on Fatigue Life Intelligent Control System of Deepw...

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4th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2022

作者： Shi, Zhen Chen, Guoming Guan, Guochao Dong, He Shandong Qingdao266580 China Shandong Qingdao266580 China Shandong Qingdao266580 China Kunming University of Science and Technology School of Architectural Engineering in KUST Yunnan Kunming650031 China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

With the improvement of the design and manufacturing level of jacket platforms, there is a breakthrough in the design, manufacturing, and installation of the platform in China. there are many rods of deep-water jacket platforms. If the manual operation and maintenance mode is continued, the maintenance cost is very expensive, and the safety and reliability of the platform are difficult to guarantee. through the two-way data transmission between the physical layer and the model layer of the digital twin system, the virtual and real image comparison is realized to obtain the stress data results of dangerous nodes, realize the real-time stress state data analysis, early warning function, and fatigue life prediction of the platform, and use the three-dimensional data simulation visual effect expression to feedback the detection results to the on-site workers to ensure the safety of underwater facilities. © 2022 IEEE.

关键词： Fatigue of materials

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A Compact Literature Review on Stock Market Prediction 4

A Compact Literature Review on Stock Market Prediction

引用

4th international conference on Inventive Research in computing Applications, ICIRCA 2022

作者： Ayyappa, Yalanati Siva Kumar, A.P. Jawaharlal Nehru Technological University Department of Computer Science and Engineering A.P Anantapur India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

Stock market forecasting has been incredibly hard since it necessitates in-depth knowledge of news events, historical data analysis, as well as the influence of news on stock price movements. the situation is compounded much more difficult by the extreme movement of the stock price patterns. Nevertheless, there is indeed a scarcity of literature that provides a comprehensive review of a general background of stock forecasting. this report gives a complete literature review to fill up this research gap. data preprocessing strategies, feature extraction techniques, prediction techniques, and future prospects are all covered in length in this literature review. this research is noteworthy yet unique in that it develops a structured methodology for stock price prediction and identifies the advantages and flaws of previous techniques. It covers a wide range of outstanding challenges as well as research topics that the research community may find useful. © 2022 IEEE.

关键词： Forecasting

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Hybrid Classification Method for the Heart Disease Prediction 4

Hybrid Classification Method for the Heart Disease Predictio...

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4th international conference on Advances in computing, Communication Control and Networking, ICAC3N 2022

作者： Panigrahi, Satya Sourav Kaur, Navneet Chandigarh University Department of Computer Science and Engineering Punjab Mohali India

ISBN: (纸本)9781665474368

data mining is a method for separating crucial information from erratic data. In PA, future outcomes are predicted using current data. To evaluate heart failure, this study is being conducted. this strategy involves pre-processing the data, feature extraction, and classification to forecast cardiac disease. Over the years, several machine learning based strategies have been put forth. Heart disease detection cannot be done with great accuracy using current methods. this study suggests a hybrid model that combines RF and LR to evaluate heart failure with good accuracy. the disease is classified using LR after features are extracted using an RF classifier. In this study, many metrics are used to evaluate the effectiveness of the suggested approach. Using a hybrid strategy, heart failure can be predicted with 95% accuracy. © 2022 IEEE.

关键词： Feature extraction

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data Mining Framework of Public Sports Budget Performance Evaluation Index based on Smart data Transmission Algorithm 4

Data Mining Framework of Public Sports Budget Performance Ev...

引用

4th international conference on Inventive Research in computing Applications, ICIRCA 2022

作者： Pan, Hongling Physical Education Institute Changsha University of Science and Technology Changsha Hunan Changsha410114 China

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

Based on the design and monitoring framework of public sports performance management based on intelligent data transmission algorithm, the algorithm of fuzzy neural network is used, and the reason, method, plan, input, activity, etc. are used as the input of the neural network, and the goal, effect, impact and result of the project are, output is output. It also fully considers the mission value, operation capability and authorization environment that are closely related to the construction of public projects, which will help to maximize the public value of public projects, and will greatly improve the scientific nature of public project performance evaluation in my country. A set of exploratory local government performance evaluation index system based on massive data mining. this paper presents the process of mining the three-level index data of the public sports performance evaluation index system by taking public sports as an example. © 2022 IEEE.

关键词： Fuzzy neural networks

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Sensor based Smart Plant Monitoring using IOT and Deep Learning: A Systematic Approach 7

Sensor based Smart Plant Monitoring using IOT and Deep Learn...

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7th international conference on computing, Communication and Security, ICCCS 2022 and 2022 4th international conference on Big data and Computational Intelligence, ICBDCI 2022

作者： Kaur, Sukhdeep Joshi, Kapil Teja, Mudduluru Charan Singh, Ajay Khabeer, Amen A. Shukla, Sunil Uttaranchal Institute of Technology Uttaranchal University Department of CSE Dehradun India Ramaiah Institute of Technology Department of Information Science and Engineering Bangalore India Uttaranchal University School of Applied and Life Sciences Dehradun India University of Technology Biomedical Engineering Iraq University of Engineering and Technology Roorkee India

ISBN: (纸本)9798350309904

As we can see, only a select few gadgets, such as PCs and smartphones, are internet-connected in the modern world and since governments across the world instituted lockdowns to stop the spread of COVID-19, interest in home gardening has exploded. Internet of things (IoT) and the internet have completely taken over today's world. All humans utilize the internet to fulfill basic needs. the network of actual items is known as the Internet of things (IOT). Simply put, it refers to the process of keeping an eye on a physical machine or object. It can also refer to the interconnection of physical objects that have been implanted with electronics, sensors, software, and network connectivity. the foundation of our nation is agriculture. the main issue in agriculture is water scarcity. the water resource is not used in an effective manner, so the water is wasted. To overcome this problem, we proposed plant monitoring approach. © 2022 IEEE.

关键词： Internet of things

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A Combination Method of Resampling and Random Forest for Imbalanced data Classification 4

A Combination Method of Resampling and Random Forest for Imb...

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4th international conference on Advances in Computer Technology, Information science and Communications, CTISC 2022

作者： Zheng, Liu Han, Qiu Junhu, Zhu Information & Engineering University State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (数字)9781665458726

ISBN: (纸本)9781665458726

In the research of imbalanced data classification, the resampling effect of the existing resampling and random forest combination technology is greatly affected by the characteristic dimension of the training set, resulting in the unsatisfactory classification effect of the model. To solve this problem, a combination method of resampling and Random Forest for imbalanced data classification is proposed. the core idea is to resample the original data set multiple times by using the feature subset of each subtree in the random forest. By reducing the number of features used in a single resampling, the influence of feature dimension on resampling effect is reduced;Different feature subsets are used for resampling in different subtrees to improve the diversity of base classifiers. Based on SMOTE, B-SMOTE and ADASYN resampling techniques, three different optimization algorithms PSRF, PBSRF and PADRF are realized respectively. Taking the geometric mean and recall rate as evaluation indexes, the experimental results on 10 groups of KEEL data show that compared with the algorithm before optimization, the geometric mean values of the three algorithms are increased by 0.85%, 2.93% and 0.79% respectively, and the recall rates are increased by 1.44%, 3.26% and 1.07% respectively. © 2022 IEEE.

关键词： Machine learning

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A Comparative Study of Different Convolution Neural Network Architectures for Hyperspectral Image Classification 7

A Comparative Study of Different Convolution Neural Network ...

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7th international conference on computing, Communication and Security, ICCCS 2022 and 2022 4th international conference on Big data and Computational Intelligence, ICBDCI 2022

作者： Singh, Manoj Kumar Kumar, Brajesh MJP Rohilkhand University Department of Computer Science and Information Technology Uttar Pradesh Bareilly243006 India

ISBN: (纸本)9798350309904

In recent years, remote sensing and other applications have used hyperspectral image processing in a variety of ways. For more precise and in-depth information extraction, hyperspectral images offer a wealth of spectral information to recognize and discriminate spectrally identical materials. Numerous cutting-edge methods based on spectral and spatial data are available for hyperspectral image classification. Convolutional neural network (CNN), a subclass of artificial neural networks has gained popularity in a number of fields, including hyperspectral image classification. CNN is built to automatically and adaptively learn spatial hierarchies of data by backpropagation using a variety of building blocks, including convolution layers, pooling layers, and fully connected layers. In this paper, different CNN architectures such as IDCNN, 2D-CNN, 3D-CNN and 3D2D-CNN are evaluated to classify hyperspectral images. Experiments are performed on Indiana Pines and Pavia University images. Experimental results show that 3D2D-CNN gives highest classification accuracy. © 2022 IEEE.

关键词： Remote sensing

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CTISC 2022 - 2022 4th international conference on Advances in Computer Technology, Information science and Communications

CTISC 2022 - 2022 4th International Conference on Advances i...

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4th international conference on Advances in Computer Technology, Information science and Communications, CTISC 2022

ISBN: (纸本)9781665458726

the proceedings contain 128 papers. the topics discussed include: reduce redundant data packets forwarding strategy for named data mobile ad-hoc network (NDMANET);efficient load balance algorithm for network-on-chip mapping;realization of linear frequency modulated short range detection system based on software defined radio;a dynamic integrated network slicing strategy for future networks;sparse circular arrays with low sidelobe levels;parallel LDPC decoder based on low-complexity corrected min sum algorithm;a tampering detection algorithm based on multidirectional authentication;a soft terminal design and development based on sip protocol;composite reuse method based on graph database;deep reinforcement learning based UAVs trajectory optimization for maximum communication coverage of users;and an automated vulnerability detection method for the 5G RRC protocol based on fuzzing.

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Preserving data Management Security through Fog to Cloud computing 4

Preserving Data Management Security through Fog to Cloud Com...

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4th international conference on Inventive Research in computing Applications, ICIRCA 2022

作者： Pranav, M. Suresh, K. Amrita School of Arts and Sciences Amrita Vishwa Vidyapeetham Department of Compter Science Mysore India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

Organizations like Amazon, Netflix, eBay, and Gameloft are forced to use cloud computing due to a lack of storage space. Flexibility, scalability, multi-portability, and elasticity are all advantages of cloud computing. Despite the fact that attempts have been made to improve cloud security, it still contains flaws like security and data availability that prevent individuals from using it. the term 'fog computing' denotes to the extension of cloud computing with respect to network's edge. Fog computing expands storage in cloud computing, networking, and processing capabilities. data access security is improving day by day, despite the fact that data is kept remotely. the volume of data is likewise growing by the day. data secrecy is maintained by securing data utilizing multiple behaviour parameters. the technique of encrypting and modifying messages in order to build data securely and to protect from attacks is known as cryptology (secret writing). NIST recommends AES as a symmetric encryption standard. AES has been shown to be a very secure, quick, and powerful encryption method. AES is widely utilized due to its high level of competency and ease of use. this paper introduce a system that will provide capabilities such as automatic text encryption and decryption. For this, the AES-256 bit method is utilized. AES is used for encryption and decryption, in the proposed system it can encrypt both textual data and IoT sensor data collected from different sensors and decryption can be done with an secret key. © 2022 IEEE.

关键词： Cryptography

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