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4th international conference on Innovative Manufacturing, Mechatronics and Materials Forum, iM3F2023

4th International conference on Innovative Manufacturing, Me...

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4th international conference on Innovative Manufacturing, Mechatronics and Materials Forum, iM3F2023

ISBN: (纸本)9789819988181

The proceedings contain 50 papers. The special focus in this conference is on Innovative Manufacturing, Mechatronics and Materials Forum. The topics include: Effect of Crack Length, Depth, and Location on Natural Frequencies of Railway Track;imputation Analysis of Time-Series Data Using a Random Forest Algorithm;harnessing Machine Learning, Blockchain, and Digital Twin technology for Advanced Robotics in Manufacturing: Challenges and Future Directions;humanizing Humanoids: An Extensive Review on the Potential of Prosthetic Robotic Arm with Integrated Monitoring System for Disabled People;intelligent Machining systems for Robotic End-Effectors: State-of-the-Art and Toward Future Directions;artificial Neural Network Analysis in Road Crash Data: A Review on Its Potential Application in Autonomous Vehicles;the Role and Impact of Robotics Integration in Precision Machining and Manufacturing: A Comprehensive Review;nanomaterial in Robotics: Bridging the Gap Between Current Applications and Future Possibilities;Optimized-ELM based on Geometric Mean Optimizer for Bearing Fault Diagnosis;detection of Fault Features in Remanufacturing of Automotive Components Using image Processing and Computer Vision Techniques;the Significance of the Thoracic Spinal Multiple Segments During Different Pick-Object Approaches;Vibration Suppression of the Flexible Beam Structure Using PID Controller Tuned by Advanced Firefly Algorithm;Bearing Fault Diagnosis based on Prominence Peak-Picking IMFs Selection and PSO-SSAE;investigation of Wheel Robot Grouser Width Parameter Effect on Robot Mobility in Soft Sand Terrain Using Sand Test Bed;automated Harmonic signal Removal-based image Feature Extraction Technique: A Comparative Study Using Online Databases;Human Mental Stage Interpretation based on the Analysis of Electroencephalogram (EEG) signals.

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1st international conference on Microelectronics, Communication systems, Machine Learning, and internet of Things, MCMI 2020

1st International Conference on Microelectronics, Communicat...

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1st international conference on Microelectronics, Communication systems, Machine Learning, and internet of Things, MCMI 2020

ISBN: (纸本)9789811919053

The proceedings contain 59 papers. The special focus in this conference is on Microelectronics, Communication systems, Machine Learning, and internet of Things. The topics include: Analysis on image Compression for Multimedia Communication Using Hybrid of DWT and DCT;face Detection Using Convolutional Neural Network;utilization of Smartphone-based Wireless Sensors in Agricultural Science: A State of Art;development of Smart Village for Better Lifestyle of Farmers by Crop and Health Monitoring System;a Novel Approach for Sink Route in Wireless Sensor Network;automated Cheque Processing Through Data Verification and Siamese Networks;Degradation of Optical Communication System Performance Due to SPM;real-Time Measurement and Analysis of Power Quality Issues in Distribution System;Design of Low-Power 10T Full Adder Circuit using DG—MOSFET at 180 nm technology;study the Effect of Pt–Ga Sensitization on Sol–Gel-Grown Nano-ZnO Thin-Film H2 Sensor;preface;design, Implementation, and Study of an IoT-based Battery Life Cycle Tester and State of Charge Indicator;effect of Electromagnetic Radiations on Children;Experimental Investigation of Solar PV Panel Using Phase Change Material Cooling by Capric Acid (C10H20O2);Performance Enhancement of PV Panel by Cooling Front Surface of PV Panel with the Use of Water as a Cooling Medium;drinking Water Quality of Different Industrial Sources: (Environmental Science and Engineering, Urban Planning);Design of Low-Power High-Efficient Single-Tail Comparator Using 180 nm CMOS technology;design of Protection Circuit for Biomedical signals Using 180 nm technology;analyzing Performance of IoT Applications—A Software Metric Approach;study and Comparison of Various Protection Configurations in Optical Networks;Design of CMOS Low Noise Amplifier.

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Photonics-Assisted Complex-Valued Discrete Fourier Transform Processor based on Temporal Computing

Photonics-Assisted Complex-Valued Discrete Fourier Transform...

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2023 Asia Communications and Photonics conference/2023 international Photonics and Optoelectronics Meetings, ACP/POEM 2023

作者： Yu, Weizhen Wang, Bin Zhang, Weifeng School of Information and Electronics Beijing Institute of Technology Beijing Institute of Technology Ministry of Education Radar Research Lab Key Laboratory of Electronic and Information Technology in Satellite Navigation Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing Key Laboratory of Novel Civilian Radar Chongqing China

ISBN: (纸本)9798350312614

In this paper, we propose and experimentally demonstrate a photonics-assisted complex-valued discrete Fourier transform (DFT) processor based on temporal computing. In the proposed DFT processor, the complex-valued input data and the orthogonal basis are encoded in sequence on an optical carrier via two high-speed dual-drive Mach-Zehnder modulators (DD-MZMs). By precisely controlling the synchronization time of the input data and orthogonal basis loading, the complex-valued multiplication operation is performed in the time domain. An optical hybrid is used to implement coherent detection, and two low-speed photodetectors are used to perform the complex-valued accumulation operation. As a demonstration, 32-points complex-valued DFT is performed, and the normalized root mean square error (NRMSE) is as small as 0.0133. In addition, a 16\times 32 pixels image is employed to implement 2D DFT, which achieves an NRMSE as small as 0.0065. The proposed DFT processor holds unique advantages including high throughput and low latency, which is potential to be widely used in artificial intelligence computing and radar signal processing systems. © 2023 IEEE.

关键词： complex-valued computing Optical discrete Fourier transform optical signal/image processing temporal computing

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AI and Ml based systemic analysis on Highly Advanced Life Threatening Cybernetics for Future Wireless Network 7

AI and Ml based systemic analysis on Highly Advanced Life Th...

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7th international conference on image Information Processing, ICIIP 2023

作者： Pandian, Anita Priyadarshini Durai Aarhus University Department of Business Development And Technology Herning Denmark

ISBN: (纸本)9798350371406

Over the past decades, the telecommunication industry has developed many folds due to industrial revolution, by which helping human race with vast number of possibilities, exploring in-numerous fields such as medicine, defense, education, research, world economy, etc. Now, the places which never even know the human touch were accessible through radio signal communication starting from deep water to Mars which continue into other galaxies, mean while Mobile phones become a necessity reaching every nook and corner of the world. The feasibility of 5G technology allows connecting every instrument, machine, devise and even living being through internet of Things (IoT), Unmanned Aerial Vehicle (UAV), Artificial Intelligence (AI), Machine Learning (ML), medical body implantation etc. to bring end to end or peer to peer connection between Machine to Machine (M2M), Vehicle to Vehicle (V2V), Device to Device (D2D) or in hybrid communication mode. As important as the sophistication grows, the possibility to suffocation threatens. Due to the vital nature and need for such technological advancement, it is inevitable to imagine life without it. This research is focused on high level threats which next generation Future Wireless Networks (FWN) are about to face and current scenarios to deliberate the protocols and standardization to such vulnerabilities and protection of big data resources from the cyber-attacks forming Highly Advanced Life-threatening Cybernetics (HALC). The significance of the green technology for safeguarding environmental resources by creating tailor made technological Green Business Models (GBM) were introduced for the future generation's social wellbeing. © 2023 IEEE.

关键词： 5G mobile communication systems

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Infrared Small Object Detection using Hybrid Augmented Intensity and Density based Clustering 1

Infrared Small Object Detection using Hybrid Augmented Inten...

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1st IEEE international conference on Cognitive Robotics and Intelligent systems, ICC - ROBINS 2024

作者： Sri Sutharsan, V.M. Kishore Kumar, C. Karthik Kallapiran, T. Rajagopal, S. National Engineering College B. Tech Information Technology Tamil Nadu Kovilpatti628503 India National Engineering College Dept. of Information Technology Tamil Nadu Kovilpatti628503 India

ISBN: (数字)9798350372748

ISBN: (纸本)9798350372748

Small object detection is the process of identifying tiny physical entity or features present within an image. Detecting small objects in infrared images presents unique challenges due to limited visible features and signal quality. The existing study introduces an established method for spotting small targets in single-frame IR images. The existing method detects the infrared images and the drawback is that the method only detects the images and does not label it. In order to overcome the above drawbacks, the proposed method concentrates on two key elements: improving infrared intensity maps using careful analysis of variation and applying clustering techniques to recognize object shapes and central points. These steps ensure precise detection, even for very small targets. The proposed integration of the YOLOv5 algorithm improves both speed and accuracy, enabling real-time detection in complex infrared scenes. The proposed method detects accurately up to 95%, which is higher when compared to the existing method along with the labeling of objects. This approach offers quick and precise small object detection in infrared images with potential benefits in surveillance. © 2024 IEEE.

关键词： Object detection

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Neural Network-based Techniques for Enhancing Raman Spectroscopy in Near-Field Applications 13

Neural Network-Based Techniques for Enhancing Raman Spectros...

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13th IEEE international conference on Communication systems and Network Technologies, CSNT 2024

作者： Anuradha, R. Rai, Avinash Kumar Swathi, B. Nagpal, Amandeep Habelalmateen, Mohammed I. Kalra, Ravi Institute of Aeronautical Engineering Hyderabad India Ies College of Technology Department of Electrical & Electronics Engineering M. P. Bhopal India New Horizon College of Engineering Department of Information Science Engineering Bangalore India Lovely Professional University Phagwara India The Islamic University Najaf Iraq Lloyd Institute of Engineering & Technology Uttar PradeshKnowledge Park II Greater Noida201306 India

ISBN: (纸本)9798350305463

The Deep Raman Enhance method uses deep neural networks to improve near-field Raman spectroscopy. This allows for higher quality signals, lower noise levels, and the potential for super-resolution Raman imaging. The Deep Raman Enhance research group came up with this technique. This state-of-the-art method employs three fundamental algorithms, each of which is grounded in mathematical equations, to achieve the goals. The Raman spectrum data is enhanced using signal Enhancement, which makes use of convolutional and densely connected layers. The second iteration of the Noise Reduction Algorithm employs a deep denoising autoencoder to reduce the amount of noise in Raman spectra. Using convolutional neural networks SuperResolution Raman Imaging boosts the image's spatial resolution. © 2024 IEEE.

关键词： Raman scattering

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Machine Condition Monitoring System based on IoT Platform for Intelligent Maintenance

Machine Condition Monitoring System Based on IoT Platform fo...

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2023 international conference on Artificial Intelligence Robotics, signal and image Processing, AIRoSIP 2023

作者： Mastang Wilarso Pahmi, Muhamad Ali Mugisidi, Dan Arsad, Norhana Sekolah Tinggi Teknologi Muhammadiyah Cileungsi Department of Industrial Engineering Jakarta Indonesia Sekolah Tinggi Teknologi Muhammadiyah Cileungsi Department of Mechanical Engineering Jakarta Indonesia Universitas Muhammadiyah Prof. Dr. Hamka Department of Mechanical Engineering Jakarta Indonesia National University of Malaysia Department of Electrical Electronic and System Selangor Malaysia

ISBN: (纸本)9798350327472

The internet of Things (IoT) in an industrial automation system is a new strategy for keeping machines operational during production. Conventional approaches to machinery condition monitoring are labor-intensive, time-consuming, and disrupt production processes that will affect productivity. It is very important to have an IoT solution set up for remote machine monitoring. Productivity can be achieved by continuous monitoring of machine performance in real time. For condition monitoring, real-time machine data were gathered from the many external sensors and PLC systems networked to the gateway through the data acquisition board. The control panel of the IoT system was connected to the different devices. An IoT platform created by Python was evaluated and made sense of the acquired data. Linear Regression was used as an algorithm to detect the machine abnormality in normal operating conditions. The implemented algorithm for predicting machine failure extends the machine's remaining usable life, enhances safety, minimizes production time lost to maintenance, and lowers the cost of auxiliary components and items. Real-time data visualization inspired the development of an augmented reality virtual environment based on picture targets that allow the manufacturer to track the system's health and locate malfunctioning components. The overall equipment efficiency (OEE) and theoretical tool life are shown in real time from a distant location to enable intelligent maintenance. © 2023 IEEE.

关键词： Gateways (computer networks)

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A Proficient and Economical Approach for IoT-based Smart Doorbell System 1

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international conference on Advances in Data-driven Computing and Intelligent systems, ADCIS 2022

作者： Thakkar, Abhi K. Ukani, Vijay Institute of Technology Nirma University Gujarat Ahmedabad382421 India

ISBN: (数字)9789819932504

ISBN: (纸本)9789819932498

The internet of Things has expanded and is now being used in electronic devices of daily use because of the developments in technology and connectivity. The concept is to employ a computing device to automatically or remotely monitor the essential functions and properties of these things. The primary concern of a homeowner is that he/she remains safe from intruders or strangers;therefore, smart doorbells may be a solution to alleviate this issue. Depending on the system design, smart doorbells provide a variety of security measures such as biometric authentication, remote access and more. This paper discusses an effective design approach to IoT-based smart doorbell systems by using a framework that employs well-established algorithms for face detection, liveness detection and face recognition as well as some minor aspects of enhancing security. Another aspect is to have low-cost, readily available components so that individuals can build their own smart doorbell security devices by following a similar approach. The smart doorbell system is able to recognise the face, differentiate between a live person and a fake image and classify the person as either an owner or a visitor. Depending on the classification, the door is unlocked for the owner and, in the presence of a visitor, the owner is notified on the mobile application. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： internet of things

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A novel heating load forecasting method based on information entropy attention mechanism 3

A novel heating load forecasting method based on information...

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3rd international conference on Advanced Algorithms and signal image Processing, AASIP 2023

作者： Yin, Jianhua Zhang, Guobin Huo, Hongyan Zhang, Qian Inner Mongolia Electric Power Science and Research Institute Huhhot010020 China

ISBN: (纸本)9781510668522

Due to the high delay and large inertia characteristics, there are issues with inefficient regulation and energy waste in district heating systems. Improving the predictive ability of regional heating load can help improve the accuracy of thermal network control. In order to improve the accuracy of heating load prediction, this paper proposes a new heating load prediction algorithm, STL-IEA-LSTM, which combines LSTM model with information entropy attention mechanism to separately model the data modeling of heating load after STL algorithm decomposition, so as to enhance the prediction ability of heating load. The experimental evaluation conducted on the operating data of a heating station in Shijiazhuang during the heating season demonstrated that the STL-IEA-LSTM combination model constructed in this study achieved a MAPE of 0.7031%, indicating its superior performance in predicting heating load. Comparative analysis with other models, including STL-LSTM, entropy-based LSTM, classic LSTM, XGBoost, and MLP, further confirmed the effectiveness of the proposed method in achieving high prediction accuracy. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Forecasting

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3rd international Workshop on New Approaches for Multidimensional signal Processing, NAMSP 2022

3rd International Workshop on New Approaches for Multidimens...

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3rd international Workshop on New Approaches for Multidimensional signal Processing, NAMSP 2022

ISBN: (纸本)9789811978418

The proceedings contain 23 papers. The special focus in this conference is on New Approaches for Multidimensional signal Processing. The topics include: Development of IoT Indoor Monitoring System for Independent Elderly;improving the Process of Evaluating User Stories Using the Paraconsistent Annotated Evidential Logic Eτ;neural Network Algorithm Applied in Electrical Engineering Automation;Truss Structure Optimization Design based on FE-PSO-SQP Algorithm;practice System of Ant Colony Optimization Algorithm in Business Administration;literature Review of Smart Contracts Using Blockchain technology;a Comprehensive Study of 5th Generation Scheduling Algorithms;a Comparative Analysis of Homogeneous and Heterogeneous Protocols to Maximize the Lifetime of Wireless Sensor Network for Precision Agriculture;the Integration Development and Upgrading Path of Industry 4.0 Architecture Industrial Engineering Network Driven by Big Data;video Tracing of Moving Objects by Fusing Three-Term Decompositions;SAAS Application Prospect Analysis in Hrm and Methods to Upgrade the Contemporary System;All Digital Phase Locked Loop (ADPLL) and Its Blocks—A Comprehensive Knowledge;on Realization of Smart Logistic Warehouse Management with internet of Things;development and Design of Intelligent Traction System for Bulk Cargo Terminal;deep Learning Approaches for Classroom Audio Classification Using Mel Spectrograms;Tensor Spectral Pyramid for Color Video Sequences Representation, based on 3D FO-AHKLT;electromyography signal Acquisition, Processing, Optimization and Its Applications;research on the Radar signal Classification Method based on the Deep Faith Network Model;measuring Machine Intelligence Using Black-Box-based Universal Intelligence Metrics;COVID Detection Using ECG image Reports: A Survey;disease Detection Techniques in Plants: Transition from Manual to Automation.

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