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检索条件"任意字段=Proceedings of the 7th International Conference on Algorithms, Computing and Systems"

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proceedings of MLHPC 2021: Workshop on Machine Learning in High Performance computing Environments, Held in conjunction with SC 2021: the international conference for High Performance computing, Networking, Storage and Analysis

Proceedings of MLHPC 2021: Workshop on Machine Learning in H...

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7th IEEE/ACM Workshop on Machine Learning in High Performance computing Environments, MLHPC 2021

ISBN: (纸本)9781665411240

the proceedings contain 9 papers. the topics discussed include: semantic-aware lossless data compression for deep learning recommendation model (DLRM);Colmena: scalable machine-learning-based steering of ensemble simulations for high performance computing;production deployment of machine-learned rotorcraft surrogate models on HPC;high-performance deep learning toolbox for genome-scale prediction of protein structure and function;HPCFAIR: enabling FAIR AI for HPC applications;HPC ontology: towards a unified ontology for managing training datasets and AI models for high-performance computing;HYPPO: a surrogate-based multi-level parallelism tool for hyperparameter optimization;and is disaggregation possible for hpc cognitive simulation?.

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7th international conference on Technologies and Innovation, CITI 2021

7th International Conference on Technologies and Innovation,...

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7th international conference on Technologies and Innovation, CITI 2021

ISBN: (纸本)9783030882617

the proceedings contain 14 papers. the special focus in this conference is on Technologies and Innovation. the topics include: Preface;approach Based on Text Processing and Ontology Applied to the Health Domain of Palliative Care in Panama;relationships of Compression Ratio and Error in Trajectory Simplification algorithms;sensor Network Prototypes for Environmental Noise Monitoring Based on Free Software;agrotechnology: Analysis of the Services Offered by Mobile Applications for the Agronomic Control of Orchards;automation of Poultry Production Monitoring through Web Services;A Brief Systematic Review of the Latest Advances in IOT Platforms in Agriculture;data Governance, a Knowledge Model through Ontologies;on Intelligent Fingerprinting of Antique Buildings from Clay Composition;emotional Corpus, Feature Extraction and Emotion Classification Using the Parameterized Voice Signal;importance of international R&D Collaboration Between Companies: the CollaborativeHealth Use Case;evaluating Extractive Automatic Text Summarization Techniques in Spanish.

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14th international conference on Applications and Techniques in Information Security, ATIS 2024

14th International Conference on Applications and Techniques...

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14th international conference on Applications and Techniques in Information Security, ATIS 2024

ISBN: (纸本)9789819797424

the proceedings contain 24 papers. the special focus in this conference is on Applications and Techniques in Information Security. the topics include: Optical Neural Networks – A Strategy for Secure Quantum computing;guarding Against Quantum threats: A Survey of Post-Quantum Cryptography Standardization, Techniques, and Current Implementations;cryptographic Distinguishers through Deep Learning for Lightweight Block Ciphers;detection and Mitigation of Email Phishing;securing Digital Forensic Data Using Neural Networks, Elephant Herd Optimization and Complex Sequence Techniques;Design of Image Encryption Technique Using MSE Approach;Low Latency Binary Edward Curve Crypto Processor for FPGA Platforms;Augmenting Security in Edge Devices: FPGA-Based Enhanced LEA Algorithm with S-Box and Chaotic Functions;machine Learning Approach for Malware Detection Using Malware Memory Analysis Data;DDOS Attack Detection in Virtual Machine Using Machine Learning algorithms;an Unsupervised Method for Intrusion Detection Using Novel Percentage Split Clustering;HATT-MLPNN: A Hybrid Approach for Cyber-Attack Detection in Industrial Control systems Using MLPNN and Attention Mechanisms;silent threats: Monitoring Insider Risks in Healthcare Sector;Enhanced Deep Learning for IIoT threat Intelligence: Revealing Advanced Persistent threat Attack Patterns;Adaptive Data-Driven LSTM Model for Sensor Drift Detection in Water Utilities;Enhancing FGSM Attacks with Genetic algorithms for Robust Adversarial Examples in Remote Sensing Image Classification systems;GAN-Enhanced Multiclass Malware Classification with Deep Convolutional Networks;IOT Based Locker Access System with MFA & Remote Authentication;a Secure Authentication Scheme between Edge Devices Using Hypergraph Hashing Technique in Iot Environment;enhancing Access Control and Information Sharing in Cloud IoT with an Effective Blockchain-Based Authority System.

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ICT4AWE 2021 - proceedings of the 7th international conference on Information and Communication Technologies for Ageing Well and e-Health

ICT4AWE 2021 - Proceedings of the 7th International Conferen...

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7th international conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2021

ISBN: (纸本)9789897585067

the proceedings contain 27 papers. the topics discussed include: designing interventions to support ageing well through telerehabilitation;technology and aging: supporting our current and future selves;robotics to characterize, retrain, and restore human movements;exploring different user interfaces for velocity based training using smart gym machines: pilot study;from age to age: key ‘gerontographics’’ contributions to technology adoption by older adults;satisfaction, self-management and usability: assessment of two novel IT solutions for type 2 diabetes patients’ empowerment;design approach of medical devices for regulation compatibility: a robotic rehabilitation case study;and de-identification of medical information for forming multimodal datasets to train neural networks.

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Predicting Round Result in Counter-Strike: Global Offensive Using Machine Learning 7

Predicting Round Result in Counter-Strike: Global Offensive ...

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7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Xu Huang, Weison Wang, Jincheng Xu, Yizhi Cincinnati Country Day School CincinnatiOH United States Ap Center Hangzhou 14th High School Hangzhou China Olive Tree International Academy Bfsu Hangzhou China

ISBN: (纸本)9781665478571

this paper first analyzes the research of Xenopoulos et al. and Makarov et al. about using machine learning to predict the result of CS: GO matches. We then carry out our experiment to compare the performance of different machine learning algorithms in predicting. Inspired by the previous research, TrueSkill value was introduced to 5 algorithms: Decision Tree, Gradient Boosted Decision Tree, XGBoost, Logistic Regression, and Neural Network. After comparing each algorithm and implementation of each algorithm with TrueSkill values, the result shows that XGBoost and Neural Network perform better than others, and the difference between these two algorithms is not significant. Our experimental result also reflects that TrueSkill values can slightly improve the accuracy of each algorithm by increasing the size of the data set. © 2022 IEEE.

关键词： Forecasting

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Efficient Quantum algorithms for Nonlinear Stochastic Dynamical systems 4

Efficient Quantum Algorithms for Nonlinear Stochastic Dynami...

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

作者： Gnanasekaran, Abeynaya Surana, Amit Sahai, Tuhin Raytheon Technologies Research Center BerkeleyCA United States Raytheon Technologies Research Center East HartfordCT United States Sri International Menlo ParkCA United States

ISBN: (纸本)9798350343236

In this paper, we propose efficient quantum algorithms for solving nonlinear stochastic differential equations (SDE) via the associated Fokker-Planck equation (FPE). We discretize the FPE in space and time using two well-known numerical schemes, namely Chang-Cooper and implicit finite difference. We then compute the solution of the resulting system of linear equations using the quantum linear systems algorithm. We present detailed error and complexity analyses for both these schemes and demonstrate that our proposed algorithms, under certain conditions, provably compute the solution to the FPE within prescribed ϵ error bounds with polynomial dependence on state dimension d. Classical numerical methods scale exponentially with dimension, thus, our approach, under the aforementioned conditions, provides an exponential speed-up over traditional approaches. © 2023 IEEE.

关键词： Linear systems

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R2 Score Estimation with Various Time Series Models Incorporating 1000 Epochs for Optimization of Accuracy of Renewable Energy Future Trends 4

R2 Score Estimation with Various Time Series Models Incorpor...

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4th international conference on Ubiquitous computing and Intelligent Information systems, ICUIS 2024

作者： Chowdhury, Suman Saha, Apurba Kumar Das, Dilip Kumar International University of Business Agriculture and Technology Department of Electrical and Electronic Engineering Dhaka1230 Bangladesh Khulna University of Engineering and Technology Department of Electrical and Electronic Engineering Khulna Bangladesh International University of Business Agriculture and Technology Department of Mathematics Dhaka1230 Bangladesh

the 176;C rise in global temperature since the pre-industrial era is mainly attributed to the use of fossil fuels and human activities. To mitigate this temperature increase, it is crucial to reduce greenhouse gas ... 详细信息

ISBN: (纸本)9798331529635

the 1°C rise in global temperature since the pre-industrial era is mainly attributed to the use of fossil fuels and human activities. To mitigate this temperature increase, it is crucial to reduce greenhouse gas emissions. In recent years, renewable energy has gained popularity due to its economic and environmental benefits. this study projects 450 days of renewable energy consumption based on a dataset spanning 5.5 years. three machine learning algorithms - Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Hist Gradient Boosting (HGBoost) - were utilized to predict renewable energy production and consumption. Based on the margin of error, it can be inferred that producing 2000MW to 5000MW of electricity is a viable option for Romania. the obtained r2 score for Random Forest Regressor is 0.95, whereas it is 0.83 for XGBoost and 0.84 for HGBoost Regressor as a performance parameter for the time series analysis. © 2024 IEEE.

关键词： Clean energy

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6th international conference on Computational Intelligence in Pattern Recognition, CIPR 2024

6th International Conference on Computational Intelligence i...

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6th international conference on Computational Intelligence in Pattern Recognition, CIPR 2024

ISBN: (纸本)9789819780921

the proceedings contain 45 papers. the special focus in this conference is on Computational Intelligence in Pattern Recognition. the topics include: Vietnamese Text Summarization Using Transformer Approach;DQN Trader: Reinforcement Learning for Automated Trading;indirect Feature Extraction for Efficient Fingerprint Recognition;A Novel and Intelligent Neuroimage Analysis for Tumor Classification with thermo-Color Segmentation Using VGG-16;a Deep Feature Ensemble Methodology for 2D Biomedical Image Classification;detection of Hardware Trojan in Nanocrossbar-Based Cryptographic Circuit;convolutional Neural Network Segmentation for Satellite Imagery Data to Identify Landforms Using U-Net Architecture;performance Comparison of Different Machine Learning Classifiers for Diabetes Prediction;Intelligent Anti-tamper systems: Safeguarding Critical Infrastructure in the Era of Proliferating Interconnected Devices and IoBT;contrasting Various Cryptographic algorithms for Storage and Cloud computing Services;A New Technique of Cellular-Automata-Based PUF Design in Nanoscale Crossbar Circuits;CrimeScene2Graph: Generating Scene Graphs from Crime Scene Descriptions Using BERT NER;a Squeeze and Excitation Framework Utilizing ResNet-152 for Alzheimer’s Disease Dementia Classification;Identification of Real or Fake Currency Using Semi-supervised Generative Adversarial Networks (SSGANs);efficient Detection of Fake Twitter Profiles on Social Media through Hybrid Deep Learning Model;religious Sentiment Analysis and Detection on Social Media;Visualizing NASDAQ Composite Index Historical Data Using Tableau;typeface Identification for English Using Convolutional Neural Networks;Adaptive Ensemble of ML Regressors and LSTM for Stock Price Prediction;PolyNMT: Neural Machine Translation Model with Seq2Seq Encoder-Decoder System;a Rectangular Slotted Sierpinski Fractal Bowtie Antenna for Multiband Wireless Communications;enhancing Cardiac Health: Machine Learning in Coronary Artery Disease Predi

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A Multidimensional Scoliosis Assessment Algorithm Based on Back Images 7

A Multidimensional Scoliosis Assessment Algorithm Based on B...

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7th international conference on Biological Information and Biomedical Engineering, BIBE 2024

作者： Peng, Xiangwei Sun, Jingwei Xie, Ruimou Pan, Yu Ni, Xueyi Luo, Zhendong International Graduate School Tsinghua University Shenzhen China Department of Rehabilitation Medicine Beijing Tsinghua Changgung Hospital Beijing China Department of Radiology The University of Hong Kong Shenzhen Hospital Shenzhen China

ISBN: (纸本)9783800762910

Scoliosis refers to the deviation of the spine from the centerline of the torso on one or both sides, forming a "C" or "S" shaped curvature. the rehabilitation period for scoliosis is long and requires regular follow-up. If the patient is frequently exposed to X-rays, it can cause irreversible damage to the blood and reproductive systems. the main research work of this article is as follows:1. Research on monocular ranging algorithm: In response to the problem that the scoliosis assessment module need to measure the distance between the camera and the human body, a technology using a common camera combined with an object detection algorithm is proposed, which can achieve monocular ranging without the need for a depth camera. the relative ranging error is less than 10%, providing quality control function for input images for subsequent scoliosis assessment task. 2. Research on Multidimensional Assessment algorithms for Scoliosis: In response to the problem of previous studies only focusing on AI assessment of the coronal plane of the spine, this study designed and implemented: (1) an angle of trunk rotation measurement algorithm for assessment the degree of spinal deviation in the sagittal plane, with a relative measurement error of 6.2%;(2) the spinal curvature type discrimination algorithm used to determine whether the spine is in a "C", "S", or multi curvature shape has a discrimination accuracy of 0.887;(3) the spinal coronal scoliosis grading algorithm, which combines doctor's assessment experience and is used to evaluate the severity of the spine on the coronal plane, has a grading accuracy of 0.793, higher than existing methods. this algorithm solves the problem of patients having difficulty performing spinal dynamic assessment at home. © VDE VERLAG GMBH.

关键词： Patient rehabilitation

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Developing a Smart Drip Infusion System to Elevate Precision in Healthcare 4

Developing a Smart Drip Infusion System to Elevate Precision...

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4th international conference on Ubiquitous computing and Intelligent Information systems, ICUIS 2024

作者： Molefinyane, Sefemo Yahya, Abid Hamsadhwani, V. Rohini, R. Samikannu, Ravi Begam, K.Maruliya Botswana International University of Science and Technology Department of Electrical and Communications Systems Engineering Palapye Botswana Periyar Maniammai Institute of Science and Technology Department of Electrical and Electronics Engineering Thanjavur India Vivekanandha College of Engineering for Women Department of Computer Science and Engineering Tiruchengode India Saveetha School of Engineering Saveetha Institute of Medical and Technology Science Department of Computer Science and Communications Engineering Tiruchengode India

ISBN: (纸本)9798331529635

Intravenous (IV) therapy is a critical component of modern healthcare, yet traditional IV systems are prone to human errors, manual adjustments, and limited monitoring capabilities, which can jeopardize patient safety and hinder healthcare efficiency. this paper presents the development of the Smartdrip IV Infusion System, a sophisticated and automated solution that integrates advanced sensors, control algorithms, and intuitive user interfaces to address these limitations. the Smartdrip system minimizes human intervention, provides real-time monitoring, and automates fluid administration with enhanced precision and safety features. the system demonstrates high reliability through simulation and prototype testing in detecting anomalies, issuing alerts, and ensuring accurate infusion rates, thereby improving patient outcomes and reducing healthcare provider workload. the results validate the Smartdrip system as a transformative approach to optimizing IV therapy in diverse clinical settings. © 2024 IEEE.

关键词： Automated Infusion System Drip Rate Monitoring Healthcare Automation Intravenous therapy Patient

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