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检索条件"任意字段=Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application"

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A Simple User-friendly Android application for Oxygen and Blood Pressure Measurement 4

A Simple User-friendly Android Application for Oxygen and Bl...

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4th international conference on Cybernetics, Cognition and machine learning applications, ICCCMLA 2022

作者： Cheemakurthi, Srujan Chakka, Jahnavi Parida, Sagar Mousam Praneeth, V.N. Siva Kinjal Debasis, Kumar VIT-AP University School of Computer Science and Engineering Amaravati India VIT-AP University School of Electronics Engineering Amaravati India

ISBN: (数字)9781665462464

ISBN: (纸本)9781665462464

In the current generation, health is a major concern for people regardless of age. People were so drastically affected by the pandemic that they couldn't muster up the courage to visit a hospital for a general checkup. Monitoring one's health condition is vital, especially for senior citizens. Photo-plethysmography is an optical measurement method used to compute the arterial blood volumetric variations of blood circulation with the help of a pulse oximeter. A pulse oximeter uses a bright LED at one end and a detector on the other end to measure the pulse rate and oxygen saturation. Hypoxemia is one of the common issues faced in recent times which is caused by the dropping of oxygen levels. It causes frequent headaches, dysfunction of the brain, heart, etc. Hence, there exists a necessity for a device that can monitor a person's oxygen levels and provide a rough estimate. this paper proposes an android application that can provide an estimate of a person's oxygen levels with over 90% accuracy. the application also predicts the rough value of blood pressure. © 2022 IEEE.

关键词： Blood pressure

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Deep learning for speech emotion recognition: A technical tutorial on the state of the art 8

Deep learning for speech emotion recognition: A technical tu...

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8th international conference on Information Systems Engineering, ICISE 2023

作者： Liu, Hai Li, Jiawen Zhao, Li Si, Junya Li, Weixin Shen, Dazhen Li, Zixin Liu, Tingting Wuhan Donghu University School of Computer Science Wuhan430212 China

ISBN: (纸本)9798350307009

Speech is the simplest, most natural and most direct way of communication between people, and the rise of smart devices makes speech emotion recognition (SER) technology the most important part of human-computer interaction (HCI). this paper will start from the concept of language emotion recognition, and research the systematic research on speech emotion recognition in five aspects. First, we review the classification of some phonetic emotional features. Secondly, we introduce some of the latest technologies for speech emotion recognition based on traditional and machine learning. Furthermore, we summarize the classification of some common datasets. Finally, we discuss the practical application and future research direction of speech emotion recognition. © 2023 IEEE.

关键词： Classification (of information)

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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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Multi-Objective and Multiple Information Source Optimization for Fair & Green machine learning 4th

Multi-Objective and Multiple Information Source Optimizatio...

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4th international conference on Numerical Computations: theory and Algorithms, NUMTA 2023

作者： Candelieri, Antonio Ponti, Andrea Archetti, Francesco University of Milano-Bicocca Milan20126 Italy

ISBN: (纸本)9783031812408

Democratizing machine learning (ML) requires endowing ML algorithms with fairness and low environmental impact. Training ML models on real-life data might lead to inherently biased predictions, a critical issue when the bias translates into discrimination of certain social groups. this unfairness is exacerbated by searching for the best predictive model only depending on accuracy. FairML was initially addressed as a constrained optimization problem, but recently multi-objective methods proved to be more effective. the second issue, considered here, is the carbon footprint of ML: the massive usage of computational resources for training ML models, and searching for the best one, implies a significant environment impact, leading to Green AutoML methods. Recent approaches estimate the carbon footprint as a proxy of the energy consumption and reduce it by using multiple information sources (i.e., small portions of the data), each with a different fidelity and cost. We propose a method combining multi-objective and multiple information source into a single Bayesian optimization framework. It was evaluated on four fairness datasets and three ML algorithms, and compared those from state-of-the-art methods. Results empirically prove that our method outperforms the others in terms of accuracy, fairness, and "greenness". © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Zero-carbon

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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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Improved Gastric Cancer Diagnosis with machine learning Technique: Addressing Imbalanced Data Distribution 1

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4th international conference on Smart Systems: Innovations in Computing, SSIC 2023

作者： Jamil, Danish Bagchi, Susama Debnath, Sanjoy Kumar Malik, Swati Kaur, Gaganpreet Sethi, Monika Khan, Muhammad Numan Ali School of Science and Engineering Malaysia University of Science and Technology Petaling Jaya Malaysia Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India Shinas Oman

ISBN: (数字)9789819736904

ISBN: (纸本)9789819736898

the use of computer-aided detection (CAD) system utilizing machine learning (ML) techniques can reduce the mortality rate of gastric cancer (GC) patients. Nevertheless, the presence of class imbalance within datasets has the potential to introduce bias into the predictions made by these systems which can lead to the misdiagnosis for a higher risk individual. this study addressed this problem by dividing the acquired 145,787 screening records from the NHS Liverpool hospital into imbalanced and balanced datasets by implementing the stratified sampling method. Four frequently utilized ML techniques, namely Support Vector machine (SVM), Multilayer Perceptron (MLP), Naive Bayes (NB), and logistic regression (LR), were trained and evaluated on these two datasets across five distinct test circumstances. the obtained findings indicate that the utilization of a balanced dataset has the potential to enhance the accuracy of stomach cancer diagnosis. the dataset that was not balanced had a higher sensitivity for Class 0, indicating a lower number of missing negative cases. Conversely, the balanced dataset demonstrated better sensitivity and positive predictive value (PPV) values for Class 1, showing a lower number of missed diagnosed gastric cancer patients and fewer erroneous predictions. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Contrastive learning

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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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FoodSavior: Distributing Surplus Food to NGOs or Manure Producers Using Internet of things and machine learning 5

FoodSavior: Distributing Surplus Food to NGOs or Manure Prod...

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5th international conference on Sustainable Communication Networks and application, ICSCNA 2024

作者： Uke, Shailaja Jadhav, Prithviraj Kakarwal, Urmila Kolawale, Sanika Nikam, Vivek Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798331530013

By evaluating the quality of leftover food and enabling its best possible redistribution, this research presents a novel approach to addressing food waste in the restaurant sector. the system uses a Flutter an Dart-based application to control the food distribution process and hardware sensors like MQ4 to identify gasses that indicate spoiling. While spoiled food is sent to manure producers for use in agriculture, non-spoiled food is sent to NGOs to feed people in need. In order to minimize waste, the system analyzes sensor data and uses machine learning algorithms, such as Decision Trees, to forecast spoiling patterns and suggest preparation techniques. Restaurants can quickly enter food data into the app, which NGOs and manure producers may use to collaborate in real time. this data is processed by the Django-developed backend server, and Arduino C++ is used to control hardware activities. this solution promotes sustainability, social responsibility, and community welfare by facilitating a smooth collaboration between farmers, restaurants, and non-governmental organizations. the method helps create a more sustainable and just food environment by decreasing food waste and improving resource efficiency. this version emphasizes the objectives, innovation, and societal impact of the work while maintaining technical details. © 2024 IEEE.

关键词： C++ (programming language)

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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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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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