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检索条件"任意字段=2024 International Conference on Smart Computing, IoT and Machine Learning, SIML 2024"

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23rd international conference on Next Generation Wired/Wireless Networking, NEW2AN 2023, and 16th conference on Internet of Things and smart Spaces, rusmart 2023

23rd International Conference on Next Generation Wired/Wirel...

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23rd international conference on Next Generation Wired/Wireless Networking, NEW2AN 2023, and 16th conference on Internet of Things and smart Spaces, rusmart 2023

ISBN: (纸本)9783031609961

The proceedings contain 67 papers. The special focus in this conference is on Next Generation Wired/Wireless Networking. The topics include: Detecting PII Leakage Using DPI and machine learning in an Enterprise Environment;deep learning for Preventing Botnet Attacks on iot;Design of Multi-polarisation MIMO Antenna for Heterogeneous smartphone Applications;potential Possibilities of Voice Pattern Recognition by a Distributed Fiber Optic Sensor;Enhancing Wireless Connectivity Through Bayesian-Optimized UAV-BS Positioning and Charging;comparison of Centralized and Federated machine learning Techniques for Beamtracking in 5G/6G Systems;exploring the Efficiencies and Vulnerabilities of smart Door Control Systems: A Systematic Review;System-Level Model for SINR and HPBW Evaluation in 5G mmWave UDN with Location-Aware Beamforming;reinforcement learning Based Power Allocation for 6G Heterogenous Networks;The Impact of Capacity Averaging in Packet-Level Modeling of 5G NR with Blockage and Micromobility;Interference Mitigation for Reconfigurable Intelligent Surface (RIS)-Aided Non-terrestrial Base Station (NTBS) in NOMA Downlink HetNets;modeling a Digital Avatar of a Car Drivers Based on the Quantification of the Information Environment;A New Blockage Detection Approach for 6G THz Systems;real-Time Anomaly Detection in Network Traffic Using Graph Neural Networks and Random Forest;addressing Security and Privacy Issues in a smart Environment by Using Blockchain as a Preemptive Technique;the Role of Cryptocurrencies in the Development of Countries and the Fight Against Financial Problems;Designing the UzBCS Lending Platform Network Based on Blockchain Technology and Ensure Transaction Security;decentralized Blockchain Networks and Economic Security: Balancing Scalability and Security Tradeoffs;study of machine learning Models for iot Based Efficient Classroom Usage;transforming Higher Education: A Comprehensive Analysis of Blockchain Technologies and Digitalization.

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4th international conference on smart Systems: Innovations in computing, SSIC 2023

4th International Conference on Smart Systems: Innovations i...

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4th international conference on smart Systems: Innovations in computing, SSIC 2023

ISBN: (纸本)9789819736898

The proceedings contain 60 papers. The special focus in this conference is on smart Systems: Innovations in computing. The topics include: An Algorithmic Framework for Clustering Cab Pickup Geo-points for Cab Recommender System (CRS);simulation and Analysis of Routing Protocols Using Real-Time Data in Vehicular Ad Hoc Networks;research Trends and Key Themes in the Intersection of Renewable Energy and smart Homes;smart Attendance System Using Face Recognition;Data Augmentation to Improve Fake Account Detection Using ANN;end-to-End Portfolio Optimization Using Transformer Encoder Model for Long Positions Strategy;phonetic Redundancy Avoidance Technique;towards Sustainable Power: A Quantitative Analysis of Environmental Factors and Energy Demand in Different Indian States;customer Segmentation Using K-means Clustering;web Miner: Automated Web Crawling and Database System with Puppeteer and ***;machine learning-Based Cardiovascular Disease Prediction;Efficient Identification of Waste in Water Bodies with YOLO V7-Object Detection;bumbleBee: The Multi-purpose Voice Assistant;efficientNet Deep learning Model for Computer-Aided Polyps Classification from Colonoscopy Images;improved Gastric Cancer Diagnosis with machine learning Technique: Addressing Imbalanced Data Distribution;an Effective and Secure Privacy Diagnosis Made Online System for the E-Healthcare Ecosystem Based on Federated learning;efficientViT: An Efficient Vision Transformer for Fire and Smoke Image Classification;Tomato Disease Classification Using CNN;artificial Intelligence Application for Electronic Governance to Achieve Sustainability: A Case of Selected Segments of Indian Economy;analyzing Sentiments of Global Workforce Towards Hybrid Work Culture in the New Normal;deep learning Techniques for Real-Time Object Detection and Classification;Task Scheduling Cost Evaluation over Cloud with Using GA, ACO, PSO.

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international conference on Intelligent Systems and smart Technologies, I2ST 2023

International Conference on Intelligent Systems and Smart Te...

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international conference on Intelligent Systems and smart Technologies, I2ST 2023

ISBN: (纸本)9783031476716

The proceedings contain 35 papers. The special focus in this conference is on Intelligent Systems and smart Technologies. The topics include: DoS and DDoS Cyberthreats Detection in Drone Networks;artificial Intelligence in Supply Chain 4.0: Using machine learning in Demand Forecasting;COVID-19 Prediction Applying machine learning and Ontological Language;EEG-Based Drivers Drowsiness Prediction Using Personalized Features Extraction and Classification Methods Under Python;a Systematic Review on Blind and Visually Impaired Navigation Systems;Comparison of Deep learning-Based Channel Estimator and Classical Estimators in VANET;decision Support Systems Based on Artificial Intelligence for Supply Chain Management: A Literature Review;a New Design of 5G Planar Antenna with Enhancement of the Gain Using Array Antenna;Minimization of Task Offloading Latency for COVID-19 iot Devices;machine learning, Deep learning, and Computer Vision for Age and Gender Detection;grape and Apple Plant Diseases Detection Using Enhance DenseNet121 Based Convolutional Neural Network;operational Code Based on the Lattice Boltzmann Method for Coastal Flows: Application to Oualidia Lagoon;the Use of Chatbots as Supportive Agents in Air Transportation Systems;the Conception of a Controlled Trigonometric Phase Locked Loop Working Under Grid Anomalies Conditions;a Deep learning Model for Intrusion Detection with Imbalanced Dataset;towards Complex Systems Behavioral Prediction: A Survey of Artificial Intelligence Applications;chaotic Image Encryption Scheme Based on Double Substitution and Diffusion Process;temperature Forecast Using machine learning;Improved YOLOv7 Models with Attention Mechanism for Inspection of Broken Glass Insulator on Power Line UAV Images;Physics-Informed Neural Network with PDE Soft Constraint Regularization Invariance.

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1st international conference on Artificial Intelligence Towards smart Sustainable Society, AISSS 2023

1st International Conference on Artificial Intelligence Towa...

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1st international conference on Artificial Intelligence Towards smart Sustainable Society, AISSS 2023

ISBN: (纸本)9789819775910

The proceedings contain 19 papers. The special focus in this conference is on Artificial Intelligence Towards smart Sustainable Society. The topics include: Devanagari Character Classification Using Heuristic Approach;Stacked Autoencoder-Based Deep Unsupervised learning Approach for SQL Injection Attack Detection;implementation of Chat Bot Using Sequence to Sequence Model;optimizing Greenhouse Lighting Systems Using Genetic Algorithms;Extensive Analysis of Deep CNN-Based Multispectral Palmprint Verification System on All Fusion Levels;leaf Disease Detection in Paddy Using Inception-V3;an Aspect-Based Sentiment Analysis Model to Classify the Sentiment of Twitter Data Using Long-Short Term Memory Classifier;machine learning-Based Cardiovascular Heart Disease Detection: A Review with Future Scope;capacity Estimation in Automotive Battery Management Systems with Intelligent Techniques;An Attention Module Integrated Deep learning Architecture with BERT to Detect SQL Injection Attacks;Quora Question Duplication Detection: An ML Approach for Identifying Semantically Equivalent Questions;detection of Wildlife Animals Based on Transfer learning Using ResNet Algorithm;Identification of Structural Damage in Single Bay Steel Frame Using ANFIS Software;revolutionizing Osteosarcoma Diagnosis: A Comparative Analysis of Deep learning Models for Precise Bone Cancer Detection Using Multi-Modal Medical Imaging;object Detection Using TensorFlow for Road Navigation: Enhancing Safety for the Visually Impaired;machine learning and iot Driven Precision Agriculture for Indian Crop Selection;adapting Single-Speaker Models for Multi-Speaker Environments.

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9th EAI international conference on smart Objects and Technologies for Social Goods, GOODTECHS 2023

9th EAI International Conference on Smart Objects and Techno...

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9th EAI international conference on smart Objects and Technologies for Social Goods, GOODTECHS 2023

ISBN: (纸本)9783031525230

The proceedings contain 13 papers. The special focus in this conference is on smart Objects and Technologies for Social Goods. The topics include: Enhancing Student Well-Being: The Impact of a Mindfulness-Based Program (Mind7 +) on Stress, Anxiety, Sleep Quality, and Social Interactions in a Sample of Portuguese University Students;Algorithm for Diagnosis of Metabolic Syndrome and Heart Failure Using CPET Biosignals via SVM and Wavelet Transforms;meal Suggestions for Caregivers and Indecisive Individuals Without a Set Food Plan;the Impact of the Evolution of Operating Systems on Older Web Applications;Method for Evaluating the Performance of Web-Based APIs;application of Traditional and Deep learning Algorithms in Sentiment Analysis of Global Warming Tweets;3D Simulation and Comparative Analysis of Immune System Cell Micro-Level Responses in Virtual Reality and Mixed Reality Environments;developing a 3D Laparoscopy Training Application to Assess the Efficacy in Virtual Reality Environments;collaborating with Agents in Architectural Design and Decision-Making Process: Top-Down and Bottom-Up Case Studies Using Reinforcement learning;5G and iot for Intelligent Healthcare: AI and machine learning Approaches—A Review;experience of Visually-Impaired Children in the Enjoyment of Cartoons.

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6th international conference on smart computing and Informatics, SCI 2024

6th International Conference on Smart Computing and Informat...

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6th international conference on smart computing and Informatics, SCI 2024

ISBN: (纸本)9789819619801

The proceedings contain 46 papers. The special focus in this conference is on smart computing and Informatics. The topics include: Resilient Domain Authentication Framework for Enhancing Digital Identity Security;traffic Sign Detection with Pattern Recognition Techniques Using Image Processing;exploring Advanced Techniques in Natural Language Processing and machine learning for In-depth Analysis of Insurance Claims;Network Intrusion Detection with SMOTE-ENN and Deep learning Techniques;leveraging Transfer learning to Enhance Location Accuracy in Mapping Services: A Case Study of Google Maps;assessment of Enhanced Email Spam Detection System Through machine learning Algorithms;machine learning Methods for Predicting Traffic Congestion Forecasting;hybridization of Computational Intelligence Algorithm for Scheduling of Tasks and Balancing of Load in Cloud Network;MDSV: Mobs Detection by Enhanced Fused Feature Base Deep Neural Network from Surveillance Camera;iot-Based Solution for Enhanced Tracking of Individuals Living with Dementia;a Novel Task Scheduling Algorithm in Heterogeneous Multi-cloud Environment;Evaluating the Integration and Usage of AI in Higher Education;evaluating the Connectional Benefits of Artificial Intelligence in the Digital Classroom;Influence of AI as an Aspect of Modern Education Era in Present World;Hilbert–Huang Transform Framework-Based Email and SMS Spam Detection;the Advancement and Utilization of Artificial Intelligence and machine learning in the Financial Industry and Its Impact on Macro and Microeconomics;analysis on the Cutting-Edge Approach to Assess Artificial Intelligence’s Educational Consequences in Contemporary Studies;data Analytics in Sales and Marketing: A Comprehensive Methodology for Business Analysts;Wireless Energy Transfer for UAV (Drone) Using machine learning.

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smart Caregiving Support Cloud Integration Systems

Smart Caregiving Support Cloud Integration Systems

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2024 international conference on smart computing, iot and machine learning, siml 2024

作者： Hapsari, Diajeng Tyas Purwa Nataliani, Yessica Sembiring, Irwan Wahyono, Teguh Satya Wacana Christian University Faculty of Information Technology Salatiga Indonesia

ISBN: (纸本)9798350364101

The effective interpretation and response to infant crying signals are imperative for ensuring infant well-being. Manual interpretation of these signals can be challenging, leading to delayed or suboptimal caregiving responses. This study aims to address this challenge by proposing a novel approach to infant cry analysis, leveraging the ESP8266 WiFi module for real-time analysis and smart caregiving support. The research objectives include integrating acoustic feature extraction, machine learning, and iot connectivity to empower caregivers with actionable insights derived from cry signal analysis. The study also aims to evaluate the performance of machine learning models and cloud computing infrastructure in achieving these objectives. Results indicate promising accuracy rates of 92% and 90% for convolutional neural network (CNN) and recurrent neural network (RNN) models, respectively, alongside efficient utilization of cloud server resources. These findings underscore the potential of the proposed approach to significantly enhance infant care practices and contribute to advancements in healthcare technology. © 2024 IEEE.

关键词： Recurrent neural networks

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An Advanced smart Bathtub System with Automated Temperature and Water Level Control

An Advanced Smart Bathtub System with Automated Temperature ...

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2024 international conference on smart computing, iot and machine learning, siml 2024

作者： Erlina, Tati Faren, Satria Diaz Ferdian, Rian Aisuwarya, Ratna Universitas Andalas Computer Engineering Padang Indonesia

ISBN: (纸本)9798350364101

With the advent of the Internet of Things (iot), a revolutionary era in smart home technology has commenced, reshaping how individuals interact with and perceive their living spaces. This study introduces an Intelligent Bathtub Filling System (IBFS) prototype poised to transform the bathing experience within smart homes, enabling users to interact with the system remotely. The research methodology involved the design and implementation of the IBFS, incorporating sensors, actuators, and smartphone integration to regulate the bathtub's water level and temperature. Experimental testing was conducted to evaluate the system's performance, with accuracy calculated by comparing the actual water level and temperature achieved by the system against user input preferences. Results indicate that the IBFS achieves an impressive 94.62% accuracy in maintaining the appropriate water level and an outstanding 99.06% success rate in reaching the desired temperature. These findings underscore the remarkable efficacy of the system development, providing users with a seamless and convenient bathing experience in smart home environments. © 2024 IEEE.

关键词： Water levels

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NearCount for Model Compression on Edge computing-Based smart Lighting with Product-of-Sum Function

NearCount for Model Compression on Edge Computing-Based Smar...

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2024 international conference on smart computing, iot and machine learning, siml 2024

作者： Putrada, Aji Gautama Abdurohman, Maman Perdana, Doan Nuha, Hilal Hudan Telkom University School of Computing Bandung Indonesia Telkom University School of Electrical Engineering Bandung Indonesia

ISBN: (纸本)9798350364101

Edge computing is an emerging concept in the Internet of Things (iot), where some processing, such as artificial intelligence (AI), is carried out on the end device, not in the cloud. However, running AI on end devices has challenges because iot end devices usually have limited resources. Our research aim is to utilize NearCount sampling to reduce samples in the AI models we use in edge computing-based smart lighting (EdgeSL). We added a product-of-sum (PoS) function and named our novel method NearCount-PoS. After developing the novel method, we applied NearCount-PoS on the Make_Moons synthetic dataset (MMSD) to analyze its performance in reducing training data and its influence on k-nearest neighbor (KNN) prediction performance. Then, we implemented it and measured its performance on our smart lighting control dataset. Finally, we benchmarked the NearCount-PoS method with the shuffle-split edited nearest neighbor (SSENN) method. The test results show that, on the MMSD with 900 samples, NearCount with K=6 provides 31% samples without reducing the accuracy of KNN in making predictions. The NearCount-PoS test results on the smart lighting dataset show that NearCount with K=159 provides samples of 42% with a KNN prediction accuracy reduced by 0.0001 from the accuracy of KNN predictions on the original sample with a value of 0.9998. Benchmarks with SSENN show that NearCount-PoS provides higher KNN prediction accuracy at sample numbers above 9,000. © 2024 IEEE.

关键词： Edge computing

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Time Series Forecasting Using LSTM to Predict Stock Market Price in the First Quarter of 2024

Time Series Forecasting Using LSTM to Predict Stock Market P...

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2024 international conference on smart computing, iot and machine learning, siml 2024

作者： Maharani, Farrah A Ivana, Sharen Fithriyah, Belva Zakiyyah, Alfi Yusrotis Sihotang, Erna Fransisca Angela Bina Nusantara University School of Computer Science Mathematics Department Jakarta Indonesia Bina Nusantara University Jakarta School of Computer Science Statistics Department Indonesia

ISBN: (纸本)9798350364101

Predictions on the stock market are critical because they significantly influence the world economy. The value of share prices usually experiences continuous fluctuations. Therefore, predicting share price growth is very important. Notable stocks dominating global markets include Amazon, Apple, Microsoft, and Google. The paper discusses predictions for developing these four shares for the next two months. The research uses the Long Short-Term Memory (LSTM) Network method to predict stock prices for the next two months using an input sequence of previous stock values. LSTM methods demonstrate the capacity to retain long-term memory while reducing the influx of irrelevant information and superior efficiency in data processing, prediction, and classification. After analysis, the results show that the close price value from Microsoft shows the highest results, reaching 374.736. © 2024 IEEE.

关键词： Long short-term memory

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