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4th international conference on machine Intelligence and Signal Processing, MISP 2022

4th International Conference on Machine Intelligence and Sig...

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4th international conference on machine Intelligence and Signal Processing, MISP 2022

ISBN: (纸本)9789819900848

the proceedings contain 74 papers. the special focus in this conference is on machine Intelligence and Signal Processing. the topics include: A Hybrid Approach for Missing Data Imputation in Gene Expression Dataset Using Extra Tree Regressor and a Genetic Algorithm;A Clustering and TOPSIS-Based Developer Ranking Model for Decision-Making in Software Bug Triaging;GujAGra: An Acyclic Graph to Unify Semantic Knowledge, Antonyms, and Gujarati–English Translation of Input Text;attribute-Based Encryption Techniques: A Review Study on Secure Access to Cloud System;Fall Detection and Elderly Monitoring System Using the CNN;precise Stratification of Gastritis Associated Risk Factors by Handling Outliers with Feature Selection in Multilayer Perceptron Model;portfolio Selection Using Golden Eagle Optimizer in Bombay Stock Exchange;hybrid Moth Search and Dragonfly Algorithm for Energy-Efficient 5G Networks;identifying the Impact of Crime in Indian Jail Prison Strength with Statical Measures;automatic Cataract Detection Using Ensemble Model;Nepali Voice-Based Gender Classification Using MFCC and GMM;analysis of Convolutional Neural Network Architectures for the Classification of Lung and Colon Cancer;wireless String: machine learning-Based Estimation of Distance Between Two Bluetooth Devices;function Characterization of Unknown Protein Sequences Using One Hot Encoding and Convolutional Neural Network Based Model;prediction of Dementia Using Whale Optimization Algorithm Based Convolutional Neural Network;goodput Improvement with Low–Latency in Data Center Network;empirical Study of Image Captioning Models Using Various Deep learning Encoders;SMOTE Variants for Data Balancing in Intrusion Detection System Using machine learning;grey Wolf Based Portfolio Optimization Model Optimizing Sharpe Ratio in Bombay Stock Exchange.

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FNDSD- A machine learning based approach for Fake News Detection and Severity Determination 4

FNDSD- A Machine learning based approach for Fake News Detec...

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4th international conference on Distributed Sensing and Intelligent Systems, ICDSIS 2023

作者： Reddy, Edula Sri Ranga Srihith Kumar, S.K.V.S. Praveen Srujan, Chinta Das, Pranesh Department of Computer Science and Engineering National Institute of Technology Calicut Kattangal Kerala Kozhikode673601 India

ISBN: (纸本)9781839539954

In our day-to-day lives, social media is becoming a pervasive platform that is misleading society with fake information. In addition to the rise in utilization of social media sites like Facebook and Twitter, news is quickly circulated among the millions of users of Twitter and Facebook within a relatively short period of time. the aim is to provide the user with the ability to classify the news as fake or real and also check the authenticity of the website providing the news. Fake news may lead to very serious conflicts within the nation and disrupt communal harmony. In this study, a machine learning based approach for Fake News Detection and Severity Determination(FNDSD) is proposed for the same. In the proposed FNDSD model, the severity of the impact caused by the fake news is determined by proposing two methods: (i) A clustering based method named as Severity Determination using Clustering(SDC) and (ii) Severity Determination by Finding Category(SDFC). A degree of severity on a scale of 0 to 1 is taken as a measure, and fake news is assigned low, medium, or high severity accordingly. In the proposed SDC method, fake news is said to have more severity if its degree of severity is greater than 0.5, and in the category-based severity method, fake news degree of severity is determined using its category. Better fake news classification results are observed in case of ISOT dataset when compared to Liar and FA-KES datasets. © the Institution of Engineering & Technology 2023.

关键词： Fake detection

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Cryptocurrency Trading Strategies and Profitability Based on Deep learning Algorithms 4

Cryptocurrency Trading Strategies and Profitability Based on...

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4th international conference on Applied machine learning, ICAML 2022

作者： Qing, Yinghe Kong, Ying Sun, Jifeng Lin, Jianwu Tsinghua-Berkeley Shenzhen Institute Shenzhen China Tsinghua Shenzhen International Graduate School Guangdong Shenzhen China

ISBN: (纸本)9781665462655

Quantitative trading replaces the traditional subjective judgment mode based on modern digital model, so as to avoid irrational investment decisions under extreme conditions. this processing method has important research and application value in many fields such as stock and foreign exchange. Especially in the context of increasingly strong research on deep learning algorithms, judgment analysis on Cryptocurrency trading strategies and profitability has also received attention from all walks of life. therefore, on the basis of understanding the current development of the stock market and the overall state of China's economy, this paper combines the stock prediction model with deep learning as the core, and constructs corresponding trading strategies on the basis of understanding the prediction results to improve the actual profitability. © 2022 IEEE.

关键词： Profitability

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Zero Cost Online Food Delivery System with machine learning Prediction 7

Zero Cost Online Food Delivery System with Machine Learning ...

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7th international conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Reddy, Yaparla Adithya Kumar Swaroop, Chebrolu Satya Terence, Sebastian Reddy, Kummetha Sai Manoj Santhosh, Korrapati Karunya Institute of Technology and Sciences Dept. of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350397253

the growth of Food Delivery application (FDA), helps customers to get variety of food items in their door steps. this helps restaurant to serve their customers with different food items, and to increase their business. FDA also provides jobs to millions of food delivery persons. But the major drawback of FDA is high commission charges for food orders. this article presents zero cost online food delivery system with ML prediction models. Zero cost online food delivery system provides user friendly interface to restaurant, home makers, customers and delivery persons. In this system, the restaurant or home makers can showcase their food items. the customers would be able to place the order. Delivery person can show interest towards delivery of the order. the customers have an option to select the delivery person for delivery and pay the delivery charges. All the payments are done through UPI payment. Advantage of the system is, it will not collect commission from home makers (or) restaurant owners and customers for the orders and also machine learning models is used to suggest food items based on different factors. Random Forest, Decision Tree Regression, K-Nearest Neighbor, and Extra Tree Classifier models are used to suggest food items to the customer. © 2023 IEEE.

关键词： Decision trees

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QuMoS: A Framework for Preserving Security of Quantum machine learning Model 4

QuMoS: A Framework for Preserving Security of Quantum Machin...

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4th IEEE international conference on Quantum Computing and Engineering, QCE 2023

作者： Wang, Zhepeng Li, Jinyang Hu, Zhirui Gage, Blake Iwasawa, Elizabeth Jiang, Weiwen George Mason University Department of Electrical and Computer Engineering VA United States George Mason University Quantum Science and Engineering Center VA United States Leidos VA United States

ISBN: (纸本)9798350343236

Security has always been a critical issue in machine learning (ML) applications. Due to the high cost of model training - such as collecting relevant samples, labeling data, and consuming computing power - model-stealing attack is one of the most fundamental but vitally important issues. When it comes to quantum computing, such a quantum machine learning (QML) model-stealing attack also exists and is even more severe because the traditional encryption method, such as homomorphic encryption can hardly be directly applied to quantum computation. On the other hand, due to the limited quantum computing resources, the monetary cost of training QML model can be even higher than classical ones in the near term. therefore, a well-tuned QML model developed by a third-party company can be delegated to a quantum cloud provider as a service to be used by ordinary users. In this case, the QML model is likely to be leaked if the cloud provider is under attack. To address such a problem, we propose a novel framework, namely QuMoS, to preserve model security. Instead of applying encryption algorithms, we propose to divide the complete QML model into multiple parts and distribute them to multiple physically isolated quantum cloud providers for execution. As such, even if the adversary in a single provider can obtain a partial model, it does not have sufficient information to retrieve the complete model. Although promising, we observed that an arbitrary model design under distributed settings cannot provide model security. We further developed a reinforcement learning-based security engine, which can automatically optimize the model design under the distributed setting, such that a good trade-off between model performance and security can be made. Experimental results on four datasets show that the model design proposed by QuMoS can achieve a close accuracy to the model designed with neural architecture search under centralized settings while providing the highest security than the b

关键词： Quantum computers

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4th international conference on Advances in Information Communication Technology and Computing, AICTC 2022

4th International Conference on Advances in Information Comm...

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4th international conference on Advances in Information Communication Technology and Computing, AICTC 2022

ISBN: (纸本)9789811998874

the proceedings contain 51 papers. the special focus in this conference is on Advances in Information Communication Technology and Computing. the topics include: Internet of things and Retail Performance in an Emerging Market: A Qualitative Analysis;the Impact of Social Media on Consumer Purchase Behaviour;the Contribution of the Internet of things to Enhance the Brands of Small and Medium-Sized Enterprises in Iraq;trust Chain for Managing Trust in Blockchain-Associated IoT-Enabled Supply-Chains;supply Chain Management Using Blockchain Security Enhancement;a Novel Image Encryption Algorithm Using Logistic and Henon Map;an Analysis of Data Sparsity Resolution Algorithms Used in Recommender Systems;recent Trends for Practicing machine learning in Brain Tumors: A Survey;voice-Based Intelligent Virtual Assistant;the Impact of IT Capabilities on Competitive Advantage;Identification of Autism Spectrum Disorder from Functional MRI Using Deep learning;conversion of Sign Language to Text and Audio Using Deep learning Techniques;security Attacks and Key Challenges in Blockchain Technology: A Survey;advancing from Manual to Automatic Telecast of News for Deaf;study of Nutrition-Based Recommender System for Diabetes and Cardiovascular Patients Based on Various machine learning Techniques: A Systematic Review;comparing Fish Finding Techniques using Satellite and Indigenous Data based on Different machine learning Algorithms;implementation of E-Governance Framework for Rural Areas of India;opinion Summarization from Online Mobile Phone Reviews Using Feature Based Association Rule Mining;unconventional to Automated Attendance Marking Using Image Processing;synthetic Animations Based Dictionary for Indian Sign Language;start of Telemedicine in Uzbekistan. Technological Availability;review of Feature Extraction Techniques for Fake News Detection.

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Intelligent thermostatic cold storage design strategies based on Monte Carlo and graph neural networks 4

Intelligent thermostatic cold storage design strategies base...

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4th international conference on computer Vision, Image and Deep learning, CVIDL 2023

作者： Ouyang, Kaichen Liu, Chang Qiu, Minyu Wang, Zixin Xu, Tianxiang University of Science and Technology China School of Mathematical Science Anhui Hefei China Chinese Hlth. Med. Information and Big Data Association-Information and Application Security Agency Beijing China China Jiliang University Information Engineering College Zhejiang Hangzhou China Beijing Normal University HoncKong Baptist University Unitednternational College Guangdong Zhuhai China University of Jinan School of Information Science and Engineering Shandong Jinan China

ISBN: (纸本)9798350326444

We first introduce four annular lattice systems with periodic boundaries as the basic model of a cold storage cooler. the four annular lattice systems represent the four subsystems of the refrigeration system and are located at the four corners of the cold storage. We introduce the energon as a self-driven particle in the system. the energy generated by the energon leaping through the subsystems ultimately serves as the source of cooling power for each subsystem, and the energon can be adsorbed into each subsystem from an external particle source, detached from each subsystem to an external particle source, moved from one subsystem to another by leapfrogging, or leapfrogged within a subsystem. At the same time, we introduce slow movers, which obey a Poisson distribution and enter each lattice point of the ystem with equal probability with parameter. When there are slow movers in the front lattice of the energetics, the leap rate of the energetics will be slowed down, thus preventing the system from being overpowered and fine-tuning the power of the system. We use Monte Carlo simulation to simulate the jumping process of energetons in the system and calculate the cooling power of the system with different parameters. By adjusting the particle adsorption rate, desorption rate, and the entry rate of slow movers, the temperature can drop to the target temperature quickly and temperature. Finally, we use CNN convolutional neural network to perform supervised learning image classification of the spatio-temporal evolution diagrams of closed system, evanescent system and absorbing system, which are three kinds of systems. © 2023 IEEE.

关键词： Cold storage

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4th international conference on machine Intelligence and Signal Processing, MISP 2022

4th International Conference on Machine Intelligence and Sig...

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4th international conference on machine Intelligence and Signal Processing, MISP 2022

ISBN: (纸本)9789819900466

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Design and implementation of financial risk control system based on machine learning algorithm and big data technology 4

Design and implementation of financial risk control system b...

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4th international conference on Advanced Algorithms and Signal Image Processing, AASIP 2024

作者： Gao, Yanqun School of Finance & Economics Guangdong University of Science and Technology Dongguan523083 China

ISBN: (数字)9781510682818

ISBN: (纸本)9781510682801

this study aims to design and implement a financial risk control system based on machine learning algorithms and big data technologies to improve the risk management capability of financial institutions. the system is designed using key steps such as data collection and collation, feature engineering, model selection and training, risk assessment and prediction, risk reporting and monitoring, and automated decision making and *** the data collection and collation phase, the system collects a large amount of financial market data, transaction data and customer data, and ensures the accuracy and consistency of the data through data cleansing and collation. Next, the system performs feature engineering, using machine learning algorithms to extract and transform features from the data to better express the characteristics and relationships of the data. this includes statistical features, time series features, technical indicators, etc. the system then selects machine learning models suitable for financial risk control, such as decision trees, random forests, support vector machines, etc., and uses historical data to train and optimise the models. the trained models are used to perform risk assessment and prediction on current data, such as assessing the risk of investment varieties such as stocks and bonds, predicting market volatility, and detecting abnormal transactions. the system also generates detailed risk reports and monitoring indicators to help financial institutions identify and respond to potential risk events in a timely manner. this includes the calculation of risk indicators and the generation of risk alerts, etc. Finally, the system can automatically trigger risk management strategies and trading decisions based on risk assessment results to reduce risk and improve investment returns. the design and implementation can effectively improve the risk management capability of financial institutions and promote the stable development of the financial mar

关键词： Support vector machines

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13th international conference on Frontier Computing, FC 2023

13th International Conference on Frontier Computing, FC 2023

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13th international conference on Frontier Computing, FC 2023

ISBN: (纸本)9789819993413

the proceedings contain 180 papers. the special focus in this conference is on Frontier Computing. the topics include: Optimization of English machine Translation Model Based on Neural Network;exploration on Text Detection Optimization Algorithm Based on Neural Network Technology;CO2 Emission Prediction of Vehicle Fuel Consumption Based on EMD-LSTM;application of Data Fusion Algorithms in the Data Processing of Intelligent Greenhouses;intelligent Film and Television Communication Optical Technology Based on Network New Media;design of Heterogeneous Database Encryption and Decryption System Based on Data Mining;research and Implementation of Music Recommendation System Based on Particle Swarm Algorithm;design of High-Speed Multi-channel Data Transmission System Based on Single-Chip Microcomputer;application of Distributed Database System in Financial Management;Research on the Development of Japanese MOOC System Based on BP Neural Algorithm;research on Default Risk Prediction of Listed Companies’ Green Credit Based on Deep learning Algorithm;improvement of Cloud Platform Utilization Based on Evaluation and Optimization of Computing Resource Runtime Surplus Capacity;design and Implementation of Operation and Maintenance Monitoring Platform Based on Data Mining Algorithm;civil Aviation Logistics Transportation Route Optimization Algorithm Based on A+ Algorithm;design of Interactive Japanese Translation System Based on Feature Extraction Algorithm;a Preliminary Study on Low-Carbon City Planning Methods Supported by the Cluster Optimization Algorithm;object Detection Algorithms in Embedded Systems and their applications;application of computer VR Technology in Digital Media System Design;discuss the Technical application of Cloud Data Center and Cloud Management Platform;Design of ARM-Based Program Automatic Shelling Data Acquisition System.

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