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Vocational Education and Electrical engineering, International Conference on

作者： Anak Agung Surya Pradhana Nobuo Funabiki I Nyoman Darma Kotama I Gusti Made Ngurah Desnanjaya Made Leo Radhitya Nyoman Sarasuartha Mahajaya Graduate School of Environmental Life Natural Science and Technology Okayama University Okayama Japan Department of Electrical and Communication Engineering Okayama University Okayama Japan Department of Computer System Engineering Institute of Business and Technology Indonesia Denpasar Indonesia Department of Informatic Technology Institute of Business and Technology Indonesia Denpasar Indonesia Departement of Magister Information Systems Institut Teknologi dan Bisnis STIKOM Denpasar Indonesia

ISBN: (数字)9798331505103

ISBN: (纸本)9798331505110

This study presents the development of an Internet of Things (IoT) system for a water heater model, focusing on enhancing reliability during sensor malfunctions that could disrupt operations. Using the SEMAR IoT platform, the system efficiently collects and analyzes data, while the integration of the Holt-Winter algorithm ensures accurate temperature estimates, even with unreliable or missing sensor data. The algorithm successfully auto-calibrates sensors, predicts temperature at specific time intervals based on real sensor behavior, and fills in missing data during sensor failures. Tests show strong correlations between estimated and actual temperatures, allowing uninterrupted operation. This solution offers a flexible, cost-effective alternative to traditional redundancy, ensuring system reliability during sensor failures. Future research will explore alternative predictive models and conduct real-world testing to validate the system’s resilience under complex conditions.

关键词： Temperature sensors Temperature measurement Temperature distribution Temperature dependence Water heating Prediction algorithms Internet of Things Monitoring Testing Resilience

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An Efficient Deep Network for Modulation Classification in Impaired MIMO-OFDM systems

An Efficient Deep Network for Modulation Classification in I...

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IEEE/SP Workshop on Statistical Signal Processing (SSP)

作者： Thien Huynh-The Quoc-Viet Pham Toan-Van Nguyen Daniel Benevides Da Costa Van-Phuc Hoang Department of Computer and Communication Engineering HCMC University of Technology and Education Vietnam Institute of System Integration Le Quy Don Technical University Vietnam School of Computer Science and Statistics Trinity College Dublin Ireland School of Computer Science and Engineering International University - VNU HCM City Vienam Technology Innovation Institute Masdar City Abu Dhabi United Arab Emirates

In this paper, an efficient automatic modulation classification for MIMO-OFDM signals is proposed for next generation wireless networks by exploiting cutting-edge deep learning techniques. Particularly, we design a deep network, namely OFDM modulation classification network (OMCNet), with asymmetric depthwise separable convolution, residual connection, and attention mechanism in a sophisticated design of processing blocks to reduce the overall complexity without sacrificing learning efficiency. Relying on the simulations, our deep network achieves over 92% for different delay spread models demonstrates the robustness of modulation classification under various channel impairments. Remarkably, compared with a baseline model, OMCNet reduces the network size by four times and computation cost by two times with the asymmetric depthwise separable while achieving a competitive accuracy thanks to residual connection and attention mechanism.

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Enhanced Condition Monitoring of Low Voltage Motors in Harsh Environments with Ladybug Beetle Optimization and Context-Aware Graph Convolutional Networks

Enhanced Condition Monitoring of Low Voltage Motors in Harsh...

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Sustainable Expert systems (ICSES), International Conference on

作者： P. Rajasekar Praveen Prakash Tiwari L. Sharmila Akriti Garg Rayudu Srinivas V V Satyanarayana Tallapragada Department of Data Science and Business System SRM Institute of Science and Technology Kattankulathur Tamil Nadu India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Electrical Engineering Mahatma Jyotiba Phule Rohilkhand University Bareilly Uttar Pradesh India Department of Electrical and Electronics Engineering Aditya College of Engineering & Technology Surampalem Andhra Pradesh India Department of Electronics and Communication Engineering School of Engineering Mohan Babu University Tirupati Andhra Pradesh India

ISBN: (数字)9798331540364

ISBN: (纸本)9798331540371

Low voltage motors are essential in many applications in contemporary industrial settings, as they power machines and guarantee efficient operations. However, these motors often operate in harsh environments where they are exposed to factors such as extreme temperatures, moisture, dust, and vibrations, which can lead to premature wear and failure. This paper proposes a hybrid method for low voltage motor condition monitoring in challenging industrial environments. The proposed method is the combined execution of Ladybug Beetle Optimization algorithm (LBOA) and Heterogeneous Context-Aware Graph Convolutional Network (HCAGCN). Hence it is named as LBOA-HCAGCN technique. Initially, the input data is collected from Triboelectric vibration sensors. Then, the collected data is fed into preprocessing utilizing Generalized Multi-kernel Maximum Correntropy Kalman Filter (GMKMCKF). This filter normalizes and cleans the data by effectively removing noise. Recursive Hilbert Transform (RHT) is used to extract time domain features such as mean, Root Mean Square (RMS), Peak-to-Peak Value, Skewness, and Kurtosis. Then the extracted features are given to HCAGCN for classify the motor health conditions such as normal, broken-bar, bowed-bar, bowed-rotor, faulty bearing, and voltage imbalance. In general, HCAGCN does not express adapting optimization strategies to determine optimal parameters to classify motor conditions. Hence, the LBOA is used to optimize the weight parameter of the HCAGCN which accurately classify motor conditions. The proposed LBOA-HCAGCN is implemented in MATLAB. Performance indicators such as Mean Absolute Error (MAE), Precision, and Accuracy were used to analyze the effectiveness of the proposed approach. Comparing the proposed LBOA-HCAGCN methodology to other existing techniques like Deep Residual Neural Network (DRNN), Convolutional Neural Network (CNN), and Recursive Neural Network (RNN), it achieves 25.8%, 26.4%, and 24.7% greater accuracy, 26.7%, 29.4%, and

关键词： Vibrations Condition monitoring Low voltage Accuracy Graph convolutional networks Transforms Motors Feature extraction Kalman filters Optimization

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A Compact Study of Recent Trends of Challenges and Opportunities in Integrating Internet of Things (IoT) and Cloud Computing

A Compact Study of Recent Trends of Challenges and Opportuni...

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2021 International Conference on Computing, Electronic and Electrical engineering, ICE Cube 2021

作者： Ishaq, Muhammad Afzal, Muhammad Hammad Tahir, Shehla Ullah, Kifayat National University of Computer and Emerging Sciences Department of Electrical Engineering Islamabad Pakistan COMSATS University Islamabad Wah campus Wah Cantt Department of Electrical Engineering Wah Cantt Pakistan Islamia University Bahawalpur Department of Information Security System and IoT Bahawalpur Pakistan Liaoning University of Technology School of Electronics and Communication Engineering Jinzhou China

ISBN: (纸本)9781665401548

The internet of things (IoT) has seen immense growth in a couple of decades. Many data centers are producing bulk data daily, which is needed to be handled properly. The extent of produced data is constantly growing. Storing data on local IoT devices is not recommended because of the availability of limited storage space, less security, and high energy consumption. The IoT integration with cloud computing requires service provision with other attributes like efficiency, high performance, scalability, reliability, and ubiquity. For accomplishing such attributions, research vision and business are anticipated to merge IoT and cloud computing concepts to enable everything as a service model to encompass new capabilities of cognitive IoT and functionalities. This manuscript describes IoT-cloud computing-based smart infrastructure and presents different techniques for preventing challenges for integrating cloud computing and IoT. © 2021 IEEE.

关键词： Internet of things

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Lightweight Task-Oriented Semantic communication Empowered by Large-Scale AI Models

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IEEE Transactions on Vehicular Technology 2025年

作者： Liu, Chuanhong Guo, Caili Yang, Yang Chen, Mingzhe Quek, Tony Q. S. Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing100876 China University of Miami Department of Electrical and Computer Engineering Institute for Data Science and Computing Coral GablesFL United States Singapore University of Technology and Design Dept. of Information Systems Technology and Design 487372 Singapore

Recent studies have focused on leveraging large-scale artificial intelligence (LAI) models to improve semantic representation and compression capabilities. However, the substantial computational demands of LAI models pose significant challenges for real-time communication scenarios. To address this, this paper proposes utilizing knowledge distillation (KD) techniques to extract and condense knowledge from LAI models, effectively reducing model complexity and computation latency. Nevertheless, the inherent complexity of LAI models leads to prolonged inference times during distillation, while their lack of channel awareness compromises the distillation performance. These limitations make standard KD methods unsuitable for task-oriented semantic communication scenarios. To address these issues, we propose a fast distillation method featuring a pre-stored compression mechanism that eliminates the need for repetitive inference, significantly improving efficiency. Furthermore, a channel adaptive module is incorporated to dynamically adjust the transmitted semantic information based on varying channel conditions, enhancing communication reliability and adaptability. In addition, an information bottleneck-based loss function is derived to guide the fast distillation process. Simulation results verify that the proposed scheme outperform baselines in term of task accuracy, model size, computation latency, and training data requirements. © 1967-2012 IEEE.

关键词： NP-hard

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Fully integrated hybrid microwave photonic receiver

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Photonics Research 2022年第6期10卷 1472-1483页

作者： JIACHEN LI SIGANG YANG HONGWEI CHEN XINGJUN WANG MINGHUA CHEN WEIWEN ZOU Beijing National Research Center for Information Science and Technology(BNRist) Department of Electronic EngineeringTsinghua UniversityBeijing 100084China State Key Laboratory of Advanced Optical Communications System and Networks Department of ElectronicsSchool of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center(imLic)Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghai 200240China

Microwave photonic receivers are a promising candidate in breaking the bandwidth limitation of traditional radio-frequency(RF)*** further balance the performance superiority with the requirements regarding size,weight,and power consumption(SWa P),the implementation of integrated microwave photonic microsystems has been considered an upgrade ***,up to now,to the best of our knowledge,chip-scale fully integrated microwave photonic receivers have not been reported due to the limitation of material *** this paper,we report a fully integrated hybrid microwave photonic receiver(FIH-MWPR)obtained by comprising the indium phosphide(In P)laser chip and the monolithic silicon-on-insulator(SOI)photonic circuit into the same substrate based on the low-coupling-loss micro-optics *** from the integration of all optoelectronic components,the packaged FIH-MWPR exhibits a compact volume of 6 cmand low power consumption of 1.2 *** FIH-MWPR supports a wide operation bandwidth from 2 to 18 ***,its RF-link performance to down-convert the RF signals to the intermediate frequency is experimentally characterized by measuring the link gain,the noise figure,and the spurious-free dynamic range metrics across the whole operation frequency ***,we have utilized it as a de-chirp receiver to process the broadband linear frequencymodulated(LFM)radar echo signals at different frequency bands(S-,C-,X-,and Ku-bands)and successfully demonstrated its high-resolution-ranging *** the best of our knowledge,this is the first realization of a chip-scale broadband fully integrated microwave photonic receiver,which is expected to be an important step in demonstrating the feasibility of all-integrated microwave photonic microsystems oriented to miniaturized application scenarios.

关键词： method microwave bands

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Energy Preservation in MANET Using Self-Adaptive CH Selection with Advanced Genetic Algorithm 1

Energy Preservation in MANET Using Self-Adaptive CH Selectio...

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1st International Conference on Advanced engineering and Technologies, ICONNIC 2023

作者： Indriyono, Bonifacius Vicky Pamungkas, Natalinda Abbas, Fatima Hashim Mintorini, Ery Almohamadi, Mohammed Mahmood, Sarmad Nozad Alani, Sameer Alkhayyat, Ahmed H. Rachmawanto, Eko Hari University of Dian Nuswantoro Information System Kediri Indonesia Al-Mustaqbal University College Medical Laboratories Techniques Department Hillah51001 Iraq University of Dian Nuswantoro Visual Communication Design Kediri Indonesia College of Information Technology Imam Ja'afar Al-Sadiq University Al-Muthanna66002 Iraq Computer Technology Engineering College of Engineering Technology Al-Kitab University Iraq University of Mashreq Research Center Medical Laboratories Techniques Baghdad Iraq College of Technical Engineering University of Mashreq the Islamic University Najaf Iraq University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia

ISBN: (纸本)9798350306484

Mobile Adhoc Networks (MANETs) is an emerging technology in both the industrial and academic research. The major drawback in MANETs is improving the battery capacity. MANETs are dynamic in nature therefore during communication it consumes more energy that reduces the overall energy efficiency of the network. Many past and present researches are concern about this problem. In this paper, Energy Preservation in MANETs using Self-Adaptive Cluster Head Selection with Advanced Genetic Algorithm (EPMSA-CHAG) approach is proposed where the CH selection is performed using two segments;they are initial parameter based on CH selection and Advanced Genetic Algorithm (AGA) based CH selection. At the initial stage the parameters which are considered for the CH selection are node degree, node stability, distance, residual energy, and speed and delivery rate. Using these parameters are the best fit for CH selection is chosen then in order to find the optimal best fit from the best fit calculation, Advanced Genetic Algorithm (AGA). The proposed EPMSA-CHAG approach is simulated using NS2 and the parameters which are considered for the performance analysis are packet delivery rate, energy efficiency, end to end delay, routing overhead and throughput. The methods that are taken for the comparative analysis are HLSPM-CHSR and HAMBO-CHLD. From the results calculated it is proven that the proposed EPMSA-CHAG approach achieved high packet delivery rate, energy efficiency and throughput as well as lower end to end delay and routing overhead when compared with the earlier methods HLSPM-CHSR and HAMBO-CHLD. © 2023 IEEE.

关键词： Energy efficiency

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Optimizing Information Freshness in Mobile Networks with Age-Threshold ALOHA

Optimizing Information Freshness in Mobile Networks with Age...

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IEEE International Symposium on Information Theory

作者： Fangming Zhao Nikolaos Pappas Chuan Ma Xinghua Sun Tony Q. S. Quek Howard H. Yang ZJU-UIUC Institute of Zhejiang University Haining China Department of Computer and Information Science Linköping University Linköping Sweden School of Computer Science Chongqing University Chongqing China School of Electronics and Communication Engineering Sun Yat-sen University Shenzhen China Information System and Technology Design Pillar Singapore University of Technology and Design Singapore

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

We optimize the Age of Information (AoI) in random access networks using the age-threshold slotted ALOHA (TSA) protocol. The network comprises multiple source-destination pairs, where each source sends a sequence of status update packets to its destination over a shared spectrum. The TSA protocol stipulates that a source node must remain silent until its AoI reaches a predefined threshold, after which the node accesses the radio channel with a certain probability. We derive analytical expressions for the transmission success probability and time-average AoI using stochastic geometry tools. Subsequently, we obtain closed-form expressions for the optimal update rate and age threshold that minimize the time-average AoI. In addition, we establish a scaling law for the time-average AoI in random access networks, revealing that the optimal time-average AoI increases linearly with the deployment density. Notably, the growth rate under TSA is half of that under conventional slotted ALOHA.

关键词： Geometry Protocols Closed-form solutions Information age Information theory

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Fusing Bluetooth with Pedestrian Dead Reckoning: A Floor Plan-Assisted Positioning Approach

arXiv

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arXiv 2025年

作者： Pan, Wenxuan Yang, Yang Chen, Mingzhe Wei, Dong Guo, Caili Mao, Shiwen Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Department of Electrical and Computer Engineering the Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Wireless Engineering Research and Education Center Auburn University AuburnAL36849 United States

Floor plans can provide valuable prior information that helps enhance the accuracy of indoor positioning systems. However, existing research typically faces challenges in efficiently leveraging floor plan information and applying it to complex indoor layouts. To fully exploit information from floor plans for positioning, we propose a floor plan-assisted fusion positioning algorithm (FP-BP) using Bluetooth low energy (BLE) and pedestrian dead reckoning (PDR). In the considered system, a user holding a smartphone walks through a positioning area with BLE beacons installed on the ceiling, and can locate himself in real time. In particular, FP-BP consists of two phases. In the offline phase, FP-BP programmatically extracts map features from a stylized floor plan based on their binary masks, and constructs a mapping function to identify the corresponding map feature of any given position on the map. In the online phase, FP-BP continuously computes BLE positions and PDR results from BLE signals and smartphone sensors, where a novel grid-based maximum likelihood estimation (GML) algorithm is introduced to enhance BLE positioning. Then, a particle filter is used to fuse them and obtain an initial estimate. Finally, FP-BP performs post-position correction to obtain the final position based on its specific map feature. Experimental results show that FP-BP can achieve a real-time mean positioning accuracy of 1.19 m, representing an improvement of over 28% compared to existing floor plan-fused baseline algorithms. Copyright © 2025, The Authors. All rights reserved.

关键词： Photomapping

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D2D Multi-hop Energy Efficiency Toward EMS in B5G

arXiv

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arXiv 2022年

作者： AL-Mansor, Asma Noordin, Nor Kamariah Saif, Abdu Alsamhi, Saeed Hamood Department of Computer and Communication System Engineering Universiti Putra Malaysia Serdang43400UPM Malaysia Department of Electrical Engineering Faculty of Engineering University Malaya Kuala Lumpur50603 Malaysia NUIG Galway Ireland Faculty of Engineering IBB University Ibb Yemen

Beyond fifth generation (B5G), communication has attracted much attention from academia, industry, and mobile network operators due to network densification, ultra-low latency communication, and enhanced energy and spectrum efficiency. However, a post-disaster emergency management system (EMS), which increasingly relies heavily on wireless communication infrastructure, is falling far behind in innovation and funding. Because the B5G concept represents a telecommunications industry revolution, EMS provisioning is intended to be dispersed, autonomous, and robust to network weaknesses caused by human and natural calamities. When the network is congested, partially functioning, or entirely isolated, we provide multi- device-to-device (D2D) communication to extend the communication coverage area with improved energy efficiency. Furthermore, we examine D2D multi-hop energy efficiency performance in the proposed network. The results demonstrate that the improved D2D multi-hop energy efficiency can improve the EMS effectively and efficiently in extending the coverage area and enhancing energy efficiency. Moreover, the proposed approach has been proven to increase energy efficiency, which acts as a suitable network design to recover from natural disasters and potentially save many lives. © 2022, CC BY.

关键词： Energy efficiency

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