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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 the 7th international conference on computing for Sustainable Global Development, INDIACom 2020

Proceedings of the 7th International Conference on Computing...

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7th international conference on computing for Sustainable Global Development, INDIACom 2020

ISBN: (纸本)9789380544366

the proceedings contain 51 papers. the topics discussed include: sentiment analysis using machine learning and deep learning;pixel wise image fusion by using quantization table for data security;robust comparative analysis of zero-knowledge proofs using discrete logarithm problem;a curve fitting thresholding approach for forensic source identification of jpeg compressed images;study of cloud security in hyper-scalers;partial occlusion handling using quadrant-wise sparsity for face image recognition;exemplifying the effects of distance metrics on clustering techniques: F-measure, accuracy and efficiency;comparative analysis of Gaussian filter, median filter and denoise autoenocoder;and performance analysis of gradient descent methods for classification of oranges using deep neural network.

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Fast Clustering for Redundancy Removal in Audio Anomaly Detection 7

Fast Clustering for Redundancy Removal in Audio Anomaly Dete...

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7th international conference on Cloud computing and Big Data Analytics, ICCCBDA 2022

作者： Hong, Renhang Zhou, Yang Shi, Shenghe Zhang, Bo Nankai University College of Software Tianjin China Chongqing Datang International Pengshu Hydropower Development Co. Ltd Chongqing China

ISBN: (纸本)9781665487115

the objective of this work is to detect anomalies of a group of hydro-Turbines and electric generators of a power plant based on their audio signals when they are running. Autoencoders are utilized for this task. In this approach, neural networks learn the time-frequency distribution of normal audio signals, and they are then used to predict the normal components of testing signals. If spectral features are used, the residuals produced by subtracting the predictions from the inputs can be regarded as estimations of anomaly signals in the inputs, and their energies can be used as the basis to make the normal/abnormal decision. When the approach was used in our project, we encountered a problem of large but imbalance training data. the training data has quite large a size(about 12,890 hours) but is highly redundant(caused by the fact that at most time devices run in stationary states). To make the training feasible, we propose a new clustering algorithm which is specially designed to quickly remove redundant data in the large database. the algorithm is significantly faster than the conventional k-means algorithm or its improved variants. the redundant data of the training database was removed by the algorithm. Autoencoders trained on the shrinked database can detect all the real anomalies recorded in the past months. When tested on a database of simulated anomalies, the average precision for the ten devices is 96.9 percent, showing the effectiveness of the algorithm. © 2022 IEEE.

关键词： Training Time-frequency analysis Databases Redundancy Clustering algorithms Training data Detectors

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proceedings of 2020 7th IEEE international conference on Behavioural and Social computing, BESC 2020

Proceedings of 2020 7th IEEE International Conference on Beh...

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7th IEEE international conference on Behavioural and Social computing, BESC 2020

ISBN: (纸本)9781728186054

the proceedings contain 44 papers. the topics discussed include: effects of temporal factors on human mobility lifestyle through GPS information;characterization of temporal patterns in the occurrence of aggressive behaviors in BogotaÁ (Colombia);testing tailored weekly feedback messages for behavioral change of people living with diabetes using a mHealth application;are they likely to complain on phish or spam? a prediction model;social network analysis of hadith narrators from Sahih Bukhari;an emerging security framework for connected autonomous vehicles;contextualized cyber security awareness approach for online romance fraud;knowledge interaction enhanced knowledge tracing for learner performance prediction;and a joint model of entity recognition and predicate mapping for Chinese knowledge base question answering.

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7th EAI international conference on Industrial Networks and Intelligent systems, INISCOM 2021

7th EAI International Conference on Industrial Networks and ...

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7th EAI international conference on Industrial Networks and Intelligent systems, INISCOM 2021

ISBN: (纸本)9783030774233

the proceedings contain 39 papers. the special focus in this conference is on Industrial Networks and Intelligent systems. the topics include: Micro-motion Target Classification Based on FMCW Radar Using Extended Residual Neural Network;preface;T4PW: TSCH in WBAN for Real-Time Monitoring of Pregnant Women;left Hand and Right Hand Circularly Polarized Antenna for 5G Devices;examination of Investigation Method of Malware Spreading State;Improving Power Efficiency of AESA System with GaN Supply-Modulated Power Amplifier;smart Shoe Based on Battery-Free Bluetooth Low Energy Sensor;Highly Reliable PUFs for Embedded systems, Protected Against Tampering;On Use of Deep Learning for Side Channel Evaluation of Black Box Hardware AES Engine;A New Method for Enhancing Software Effort Estimation by Using ANFIS-Based Approach;a New Method to Improve Quality Predicting of Software Project Completion Level;An Embedded Digital Multi-channel Analyzer for Radiation Detection Based on FPGA;A Design of CMOS PUF Based on Ring Oscillator and Time-to-Digital Converter;Design of a Compact and High-Efficiency 5.8 GHz Microwave Power Amplifier for Wireless Communication systems;a Bufferless Non-exact Matching Hardware Accelerator for Processing Large Non-uniform Stream Data;a New User Recommendation Model Within the Context of the Covid-19 Pandemic;enhancing the Capacity of Detecting and Classifying Cavitation Noise Generated from Propeller Using the Convolution Neural Network;a Feature-Augmented Deep Learning Model for Extractive Summarization;proposing Chatbot Model for Managing Comments in Vietnam;social Hybrid Reciprocal Velocity Obstacle-Based Socially Aware Mobile Robot Navigation Framework;Proposing Gesture Recognition Algorithm Using HOG and SVM for Smart-Home Applications.

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7th KES international conference on Sustainable Design and Manufacturing, KES-SDM 2020

7th KES International Conference on Sustainable Design and M...

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7th KES international conference on Sustainable Design and Manufacturing, KES-SDM 2020

ISBN: (纸本)9789811581304

the proceedings contain 49 papers. the special focus in this conference is on Sustainable Design and Manufacturing. the topics include: Research on green design of valve products based on response surface method;integrated electronic systems for acquisition of customers for transport and logistics services;mechanical performance of polylactic acid from sustainable screw-based 3d printing;organization and implementation of intermodal transport of perishable goods: Contemporary problems of forwarders;analysis of electric power consumption by the heat pump used in the spray booth;test stand for metamaterials dynamic properties examination;an association rule-based approach for storing items in an as/rs;infrastructure sharing model as a support for sustainable manufacturing;a correlation study between weather conditions and the control strategy of a solar water heating system;industry 4.0—supporting industry in design solutions—all-in-one computer cover;preface;bringing success and value in sustainable product development: the eco-design guidelines;development of a robotic system with stand-alone monocular vision system for eco-friendly defect detection in oil transportation pipelines;analysis and assessment of bottom-up models developed in central europe for enhancing open innovation and technology transfer in advanced manufacturing;a simplified triz approach involving technology transfer for reducing product energy consumption;calculating domestic environmental impacts: Challenging and solutions for an interactive configurator;additive manufacturing of continuous carbon fiber-reinforced plastic components;scalability analysis in industry 4.0 manufacturing;an investigation of the porosity effects on the mechanical properties and the failure modes of ti–6al–4v schwarz primitive structures;including ergonomic principles in the design and management of reconfigurable manufacturing systems.

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Accelerating Sustainability through Leveraging Machine Learning to Analyze CSR Spending in the Indian Automobile Industry 7

Accelerating Sustainability through Leveraging Machine Learn...

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7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Yogi, Kottala Sri Dankan Gowda, V. Pati, Anwesha Srinivas, Ved Aghav, Santosh Abdullah, Ibrahim International University Symbiosis Institute of Business Management Hyderabad Symbiosis Department of Operations Pune India BMS Institute of Technology and Management Department of Electronics and Communication Engineering Karnataka Bangalore India Symbiosis Institute of Business Management Hyderabad India Thiagarajar School of Management Department of Human Resources Tamil Nadu Madurai India Symbiosis Law School Hyderabad Pune India Al-Turath University College Department of Computer Science Baghdad Iraq

ISBN: (纸本)9798350372816

this paper uses machine learning to assess Corporate Social Responsibility spending trends on the Indian automobile sector between 2016 and 2021. Simply put, the aim of the research is to recognize trends and patterns in sustainability expenditures. More specifically, the study examines how businesses allocate money across the three important aspects of the sustainability report: People, Planet, and Profit Purcell, 2020. the research is based on a largely industry-based database obtained from public companies' records. the use of advanced statistical techniques, such as machine learning and random forest modeling, enables one to examine the impact of financial allocations on sustainability achievements. Increments in CSR spending are related to enhanced company sustainability performance in terms of correlation outcomes. the paper also recognizes areas where cost cuts have the best returns, as well as shortfalls in the existing CSR approach, offering a strategy for possible development's. © 2024 IEEE.

关键词： CSR Impact Sustainability Analysis Indian Automobile Industry Learning Machine Social Responsibility Environmental Spending Sustainability Investments Corporate

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Hybrid Machine Learning Models: Combining Strengths of Supervised and Unsupervised Learning Approaches 7

Hybrid Machine Learning Models: Combining Strengths of Super...

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7th international conference on Contemporary computing and Informatics, IC3I 2024

作者： Agrawal, Shashwat Gupta, Gopal Kumar Gopalakrishna, Pandi Kirupa Balasubramaniam, Vanitha Sivasankaran Goel, Lagan Mahadik, Siddhey Mehrauli Uttar Pradesh Ghaziabad India Nagpur Campus Maharashtra Pune India Karnataka Bengaluru India PT Rajan Salai KK Nagar Chennai India Akg International Kandela Industrial Estate Uttar Pradesh Shamli India Independent Researcher Vashi Maharashtra Navi Mumbai India

ISBN: (纸本)9798350350067

this research uses NSL-KDD to test hybrid machine learning models for network intrusion detection. the NSL-KDD dataset, a better version of KDD-99, is selected for its data quality and minimized duplication. It contains 147,907 entries with 42 properties for Attacks such as R2L, U2R, DoS, Probe, and normal. the dataset's improvements fix bugs and improve testing. Data preparation removed duplicates, normalized values to 0-1, and addressed class imbalance. the research tests supervised learning approaches like Random Forest and SVM. the Random Forest model has 97% accuracy, precision, recall, and F1-scores, whereas the SVM model had 95%. the most accurate model was a hybrid CNN-LSTM model with 99% accuracy. Random Forest with K-Means clustering and SVM classification were used for unsupervised learning. the Hybrid model using Autoencoders and Clustering outperformed other models with 99.8% accuracy. this research demonstrates how hybrid machine learning techniques may categorize and handle diverse attack types while overcoming model constraints in network intrusion detection. © 2024 IEEE.

关键词： Adversarial machine learning

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8th international conference on Frontiers of Intelligent computing: theory and Applications, FICTA 2020

8th International Conference on Frontiers of Intelligent Com...

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8th international conference on Frontiers of Intelligent computing: theory and Applications, FICTA 2020

ISBN: (纸本)9789811557873

the proceedings contain 147 papers. the special focus in this conference is on Frontiers of Intelligent computing: theory and Applications. the topics include: Potential of robust face recognition from real-time cctv video stream for biometric attendance using convolutional neural network;modelling cpu execution time of aes encryption algorithm as employed over a mobile environment;gradient-based feature extraction for early termination and fast intra prediction mode decision in hevc;a variance model for risk assessment during software maintenance;cyber attack detection framework for cloud computing;benchmarking semantic, centroid, and graph-based approaches for multi-document summarization;water availability prediction in chennai city using machine learning;field extraction and logo recognition on indian bank cheques using convolution neural networks;a genetic algorithm based medical image watermarking for improving robustness and fidelity in wavelet domain;developing dialog manager in chatbots via hybrid deep learning architectures;experimental analysis of fuzzy clustering algorithms;atm theft investigation using convolutional neural network;a regularization-based feature scoring criterion on candidate genetic marker selection of sporadic motor neuron disease;a study for ann model for spam classification;automated synthesis of memristor crossbars using deep neural networks;training time reduction in transfer learning for a similar dataset using deep learning;a novel model object oriented approach to the software design;optimal energy distribution in smart grid;robust automation testing tool for gui applications in agile world—faster to market;storage optimization using file compression techniques for big data;statistical granular framework towards dealing inconsistent scenarios for parkinson’s disease classification big data;preface.

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8th international conference on Frontiers of Intelligent computing: theory and Applications, FICTA 2020

8th International Conference on Frontiers of Intelligent Com...

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8th international conference on Frontiers of Intelligent computing: theory and Applications, FICTA 2020

ISBN: (纸本)9789811556784

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7th international conference on Microelectronics, Circuits, and systems, Micro 2020

7th International Conference on Microelectronics, Circuits, ...

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7th international conference on Microelectronics, Circuits, and systems, Micro 2020

ISBN: (纸本)9789811615696

the proceedings contain 23 papers. the special focus in this conference is on Microelectronics, Circuits, and systems. the topics include: Reconfigurable Antennas for RFID/GPS/WiMAX/WLAN Applications Using RF MEMS Switches;Design, Analysis and Simulation of a Piezoresistive Microbridge and Microcantilever for MEMS Pressure Sensor in Continuous Glucose;Investigation of the Optoelectronic Properties of InSbNBi with 16-Band k Dot p Model;High-K Biomolecule Sensor Based on L-Shaped Tunnel FET;A Novel Trench FinFET as a Biosensor for Early Detection of Alzheimer’s Disease;Interface Trap Charge Analysis of Junctionless Triple Metal Gate High-k Gate All Around Nanowire FET-Based Biotin Biosensor for Detection of Cardiovascular Diseases;Fin Aspect Ratio Optimization of Novel Junctionless Gate Stack Gate All Around (GS-GAA) FinFET for Analog/RF Applications;Design and Analysis of Cyl GAA-TFET-Based Cross-Coupled Voltage Doubler Circuit;Impact of Channel Epilayer Induced Corner-Effect on the Sensing Performance of a Unique PTFET-Based Biosensor (Epi-PTFET-Biosensor);Performance Comparison of III–V and Silicon FinFETs for Ultra-Low Power VLSI Applications;High Switching Performance of Novel Heterogeneous Gate Dielectric—Hetero-Material Based Junctionless-TFET;radiation Tolerant Memory Cell for Aerospace Applications;A Highly Reliable and Radiation-Hardened Majority PFET-Based 10T SRAM Cell;Design and Analysis of Ultra-Low Power Memory Architecture with MTCMOS Asymmetrical Ground-Gated 7T SRAM Cell;Data-Aware Near Subthreshold 10 T SRAM Cell for Ultra-Low Power Application;Radiation Immune SRAM Cell for Deep Space Applications;Comparative Study of InAlN and InGaN Back Barrier Layer on p-Gate/AlGaN/GaN HEMT;unified Analytical Model for Charge Density and Plasmonic Waves in the Quaternary AlInGaN/AlN/GaN Heterostructures.

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