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5th International conference on Deep Learning, Artificial Intelligence and Robotics, ICDLAIR 2023

ISBN: (纸本)9783031609343

The proceedings contain 70 papers. The special focus in this conference is on Deep Learning, Artificial Intelligence and Robotics. The topics include: A Short Survey on Comparative Study of Modern Cryptography Approach;advances in Computer-Aided Detection and Diagnosis of Retinal Diseases: A Comprehensive Survey of Fundal Image Analysis;driver Safety and Drowsiness Detection in Internet of Vehicles with Federated Learning;privacy Preserving Fingerprint Classification Using Federated Learning;comparative Study of Ensemble Learning Models for Smart Meter Load;social-Media Video Summarization Using Convolutional Neural Network and Kohnen’s Self Organizing Map;machine Learning and Deep Leaning in Predicting Coronary Heart Disease;Augmented Super Resolution GAN (ASRGAN) for Image Enhancement Through Reinforced Discriminator;Convolutional Block Attention Assisted Dense Stacked Bi-LSTM for the Generation of RDF Statements;real-Time Permanent Change Proposals for Abandoned Object Detection;an Excursion to Ontology-Based Non-functional Requirements Specification;a Review of Traditional and Neural Network Methods for Protecting Privacy in Big Data Analytics;a Long Short-Term Memory Learning Based Malicious Node Detection for Clustering in Wireless sensor Networks;experimental Analysis for sensor Reduction to Depict Real-Time applications Through Regression Techniques;multi-resolution Neural Network for Road Scene Segmentation;A CNN-Based Road Accident Detection and Comparison of Classification Techniques;football Match Result Prediction Using Twitter Statistical/Historical Data;safeguarding Ecosystems and Efficiency in Peer-to-Peer File Sharing systems: An IoT-Inspired Approach to Pollution Mitigation;a Heuristic for Minimizing Resource Requirement for Quantum Graph Neural Networks;Light-Gated Recurrent Unit Based Acoustic Modeling for Improved Hindi ASR;Detecting Phishing URLs Using Machine Learning: A Review;comparative Analysis of Pneumonia Detection from Chest x-ray Using

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NiCuZn Ferrites with Iron Deficiency for High-Power Low-Loss Microwave applications 12th

NiCuZn Ferrites with Iron Deficiency for High-Power Low-Loss...

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12th International conference on advanced Materials and Engineering Materials, ICAMEM 2023

作者： Zhang, Hanyu Jiang, xiaona Wu, Chuanjian Li, Qifan Sun, Ke Lan, Zhongwen Yu, Zhong School of Materials and Energy University of Electronic Science and Technology of China Chengdu610054 China

ISBN: (纸本)9789819735297

Nickel-based spinel ferrites can be applied in the Ka-band with high resistivity ρ, high saturation magnetization 4πMs, and low ferromagnetic resonance (FMR) linewidth ΔH and are widely applied in satellite communications, missile guidance systems, and on-board or airborne imaging radars. In this study, NiCuZn ferrites (NCZF) with the composition of Ni0.505Cu0.1Zn0.4Co0.015Ho0.01Fe1.97-xO4-δ (x = 0.00 ~ 0.04) were synthesized by solid-phase reaction. The crystalline phase formation, microstructure, magnetic and microwave properties of NCZF with iron deficiency are reported. The results demonstrated that NCZF with x = 0.01 sintered at 1050 ℃ possessed high 4πMs (5.062 kGs), low ΔH (113 Oe), and high spin-wave linewidth ΔHk (25.6 Oe). © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Saturation magnetization

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Haptic In-sensor Computing Device Based on CNT/PDMS Nanocomposite Physical Reservoir

ADVANCED INTELLIGENT SYSTEMS

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advanced INTELLIGENT systems 2025年第3期7卷

作者： Kimizuka, Kouki Azhari, Saman Tokuno, Shoshi Karacali, Ahmet Usami, Yuki Ikemoto, Shuhei Tamukoh, Hakaru Tanaka, Hirofumi Kyushu Inst Technol Grad Sch Life Sci & Syst Engn 2-4 Hibikino Aizu Wakamatsu Kitakyushu 8080196 Japan Waseda Univ Grad Sch Informat Prod & Syst IPS 2-7 Hibikino Aizu Wakamatsu Kitakyushu 8080135 Japan Kyushu Inst Technol Res Ctr Neuromorph AI Hardware 2-4 Hibikino Aizu Wakamatsu Kitakyushu 8080196 Japan

The importance of haptic in-sensor computing devices has been increasing. Herein, a haptic sensor with a hierarchical structure is successfully fabricated via the sacrificial template method, using carbon nanotube-polydimethylsiloxane (CNT-PDMS) nanocomposites for in-sensor computing applications. The CNT-PDMS nanocomposite sensors, with different sensitivities, are obtained by varying the amount of CNTs. The input stimuli are transformed into higher-dimensional information, enabling a new path for the CNT-PDMS nanocomposite application, which is implemented on a robotic hand as an in-sensor computing device by applying a reservoir computing paradigm. The nonlinear output data obtained from the sensors are trained using linear regression and used to classify nine different objects used in everyday life with an object recognition accuracy of >80% for each object. This approach can enable tactile sensation in robots while reducing the computational cost.

关键词： haptic sensors in-sensor computing nanomaterials reservoir computing soft robotics

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A Single-Wire Soft sensor for Seamless Multimodal Tactile Sensing

A Single-Wire Soft Sensor for Seamless Multimodal Tactile Se...

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IEEE International conference on Soft Robotics (RoboSoft)

作者： Matteo Meneghetti Francesco Visentin Department of Engineering for Innovation Medicine Section Engineering University of Verona Italy

ISBN: (数字)9798331520205

ISBN: (纸本)9798331520212

Integrating sensing in a soft robot is still crucial to enable feedback response to environmental stimuli. This paper presents a single-wire soft sensor for multimodal tactile sensing designed to address the limitations of current technologies. The sensor integrates a stimulus-responsive hydrogel with a unique design that enables spatial and force sensing by leveraging changes in electromagnetic resonance properties. With a simplified structure, the sensor is fabricated with minimal wiring, maintaining flexibility and adaptability for various robotic applications. Experimental results demonstrate high accuracy in detecting contact points (up to 98%) and applied forces (96%) and a combined detection accuracy of 87%. This approach allows for distributed sensing within the robot or using the whole body as a sensing element, enhancing the system’s responsiveness to environmental stimuli and supporting advanced applications in physical intelligence.

关键词： Wiring Accuracy Soft sensors Hydrogels Force Soft robotics Robot sensing systems Resonance Electromagnetics

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sensor based posture detection system

Sensor based posture detection system

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International conference on Integration of advanced Technologies for Industry 4.0 (ICIATI) - Materials Science

作者： Devi, K. Nirmala Anand, Jose Kothai, R. Krishna, J. M. Ajai Muthurampandian, R. KCG Coll Technol Chennai Tamil Nadu India

Posture identification system has been extensively useful in areas such as physical activities, ecological awareness events, man machine interfacing applications, control room panel monitoring systems and in autonomous old people caring systems. This paper describes a sensor based posture detection and guidance system while doing yoga exercise. In our day-to-day life, doing yoga exercise has become a well-known discipline, which helps people to be physically fit and have good mental health. Practicing yoga exercise is a recognized system for the human beings to improve their physical and mental activities. This practice helps in regulatory activities in an individual's mind, body and soul. As a result of this, flexibility, muscle power and body image will increase. The existing method has shown the recognition of posture analysis through virtual reality and exergame. We proposed a suit that is designed and implemented through a virtual master. The suit is integrated with various types of accelerometer sensors which are fixed on the flexible bands, that are light in weight and are used indirectly to measure the orientation of the limbs. Also the sensor integrated suit is very helpful to measure the direction of the tilt moment. Predefined calibrated values are loaded on to the microcontroller, which are compared with the measured values and when there is a match the information is sent to a mobile application. The mobile app identifies whether the user is doing the posture correctly or not based on the information given to practice the yoga exercise. (C) 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International conference on Integration of advanced Technologies for Industry 4.0 : Materials Science

关键词： Mobile app Posture detection sensors Suit Yoga

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Deep Learning-based Predictive Maintenance for Industrial IoT applications 7

Deep Learning-based Predictive Maintenance for Industrial Io...

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7th International conference on Inventive Computation Technologies, ICICT 2024

作者： Jeba Emilyn, J. Vinod Kumar, D. David Samuel Azariya, S. Prakash, M. Sam Thamburaj, A. Sona College of Technology Information Technology Tamil Nadu Salem India Biomedical Engineering Vinayaka Mission's Kirupananda Variyar Engineering College Tamil Nadu Salem India Computer Science Vinayaka Mission's Kirupananda Variyar Arts And Science College Tamil Nadu Salem India Vinayaka Mission's College of Physiotherapy Tamil Nadu Salem India

ISBN: (数字)9798350359299

ISBN: (纸本)9798350359299

Integrating Deep Learning-based Predictive Maintenance (DL-PM) in Industrial Internet of Things (IoT) applications optimizes operational efficiency and reduces downtime. This reaserch work explores the synergy between deep learning and predictive maintenance within the Industrial IoT context. The study traces the evolution from traditional maintenance to modern deep learning methods facilitated by IoT's real-time data acquisition. Methodologically, it details data preprocessing, model selection, and design for DL-PM. Convolutional Neural Networks (CNNs) analyze sensor data, Recurrent Neural Networks (RNNs) predict time-series patterns and hybrid models incorporate transfer *** reaserch work demonstrates DL-PM's application across industries through diverse case studies, evaluating its performance and comparing it to conventional approaches. It highlights challenges like data quality, model interpretability, scalability, ethical concerns, and biases. Future directions encompass advanced deep learning techniques, edge-cloud integration, collaborative learning, and strategies to overcome challenges. DL-PM's potential to revolutionize industrial processes in the IoT era is *** reaserch work underscores the transformative impact of Deep Learning-based Predictive Maintenance in Industrial IoT. It provides insights into implementation, challenges, and prospects, guiding industries towards efficient, downtime-minimized operations through DL-PM integration. © 2024 IEEE.

关键词： Internet of things

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Numerical Analysis on Slinky 3 dB Power Divider for High Speed RF sensor System

Numerical Analysis on Slinky 3 dB Power Divider for High Spe...

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2022 IEEE International conference on Electronics, Computing and Communication Technologies, CONECCT 2022

作者： Gurulakshmi, A.B. Rajesh, G. Sharma, Sanjeev New Horizon College of Engineering Department of Electronics & Communication Engineering Bangalore India

ISBN: (数字)9781665497817

ISBN: (纸本)9781665497817

The aim of the presented article is to design a high frequency 3db slinky power divider for RF sensor applications which operates at 6 GHz frequency. The material used for the design of proposed structure is FR4 material commonly used for PCB design. This material is identified to have medium refractive index in the order of 4.6 which ensures minimizes structure and compatible with the exciting systems. The purpose of the proposed power divider is to handle the power in RF sensor network to ensure optimal functioning at high frequency RF systems. The size and frequency handling ability of the power divider is confined to FR4 material due to the advantage of the compatibility of the available RF systems. The entire structure is mathematically analysed followed by numerical solving and fabrication. The design of novel 3db slinky power divider for RF sensor applications at high frequency which provides higher bandwidth that can be appreciated and recommended for real time wireless sensing networks. This work starts with the understanding of Electromagnetic fundamentals for RF system design and its parametric properties like Insertion Loss, Return Loss, current distribution, Near Field Crosstalk (NFC), Far Field Crosstalk (FEC), radiation pattern and Voltage Standing Wave Ratio (VSWR). Literature survey on various power divider for real time applications are studied. The need for the power divider circuits in RF sensors are identified and proposed a 3dB slinky power divider. Numerical solving of the proposed structure is done using the simulator and the validation of obtained results with the previous finding are done. Proper material selection is done based on the industry used products. advanced Design System (ADS) is used for simulation and parametric study of the power divider. The insertion loss with frequency plot with resonant frequency of 8.912 GHz is presented along with the return loss verses frequency plot. The proposed power divider is covering the frequency

关键词： Crosstalk

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Relevance Meets Diversity: A User-Centric Framework for Knowledge Exploration Through Recommendations 24

Relevance Meets Diversity: A User-Centric Framework for Know...

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30th ACM SIGKDD conference on Knowledge Discovery and Data Mining

作者： Coppolillo, Erica Manco, Giuseppe Gionis, Aristides Univ Calabria Dept Comp Sci Arcavacata Di Rende Italy ICAR CNR Arcavacata Di Rende Italy KTH Royal Inst Technol Div Theoret Comp Sci Stockholm Sweden

ISBN: (纸本)9798400704901

Providing recommendations that are both relevant and diverse is a key consideration of modern recommender systems. Optimizing both of these measures presents a fundamental trade-off, as higher diversity typically comes at the cost of relevance, resulting in lower user engagement. Existing recommendation algorithms try to resolve this trade-off by combining the two measures, relevance and diversity, into one aim and then seeking recommendations that optimize the combined objective, for a given number of items. Traditional approaches, however, do not consider the user interaction with the suggested items. In this paper, we put the user at the central stage, and build on the interplay between relevance, diversity, and user behavior. In contrast to applications where the goal is solely to maximize engagement, we focus on scenarios aiming at maximizing the total amount of knowledge encountered by the user. We use diversity as a surrogate for the amount of knowledge obtained by the user while interacting with the system, and we seek to maximize diversity. We propose a probabilistic user-behavior model in which users keep interacting with the recommender system as long as they receive relevant suggestions, but they may stop if the relevance of the recommended items drops. Thus, for a recommender system to achieve a high-diversity measure, it will need to produce recommendations that are both relevant and diverse. Finally, we propose a novel recommendation strategy that combines relevance and diversity by a copula function. We conduct an extensive evaluation of the proposed methodology over multiple datasets, and we show that our strategy outperforms several state-of-the-art competitors. Our implementation is publicly available(1).

关键词： User Modeling Diversity Recommender systems

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advanced Piezoelectric PVDF Fiber Films with Te Nanowires for Sustainable Energy Harvesting

Advanced Piezoelectric PVDF Fiber Films with Te Nanowires fo...

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IEEE International conference on Power and Energy systems (ICPES)

作者： Yuanyuan Li Pengfei Fang Yumin Wang Siwei Pan School of Physics and Technology Wuhan University Wuhan China Electric Power Research Institute of Guangdong Power Grid Co. Ltd. Guangzhou China

ISBN: (数字)9798350391329

ISBN: (纸本)9798350391336

Piezoelectric polymers are valued for their ease of fabrication and integration into devices, making them highly promising for self-powered systems and sensor applications that rely on converting mechanical energy into electrical energy. However, their relatively low piezoelectric performance compared to piezoelectric ceramics has limited their practical use. In this study, we present Te-doped PVDF piezoelectric nanofiber mats fabricated through electrospinning, demonstrating enhanced piezoelectric properties. Flexible piezoelectric nanogenerators (PENGs) incorporating 8 wt% Te in PVDF show a notable increase in output voltage, from 1.2 V to approximately 4.2 V, under a 5 N pressure at 3 Hz. This improvement allows the fiber mats to effectively convert mechanical energy into electrical energy, generating an instantaneous output power density of around $45.7 \mu \mathrm{W} / \text{cm}^applications$ , making them suitable for self-powered sensing and energy harvesting applications.

关键词： Optical fiber sensors Power system measurements Nanogenerators Nanocomposites Voltage sensor systems Nanowires Mechanical energy sensors Wearable devices

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H Shaped Broad Band Dielectric Antenna With Low Profile and Trapezoidal Feed for advanced Wireless applications

H Shaped Broad Band Dielectric Antenna With Low Profile and ...

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2022 International conference on Electronics and Renewable systems, ICEARS 2022

作者： Prabha K., Venkata Ratna Raja A., Ravi Anusha, T Krishna Reddy, A. Rama Perusomula, Haneesha Naidu, Praveen V. V R Siddhartha Engineering College Vijayawada520007 India

ISBN: (纸本)9781665484251

In this article, a novel H-shaped dielectric resonator antenna (DRA) placed on top of a cube DRA excited with a trapezoidal feed was analyzed for broadband applications. A ceramic material with a dielectric constant of 9.8 was used in the DRA structure design and placed on a NeltecNY9260 (IM) (tm) substrate measuring 55 x 55 x 0.715 mm3 to analyze the proposed antenna. From 4.0 to 8.1 GHz, the proposed antenna structure has a large impedance bandwidth of 67.7% with | S11 | -10 *** simulated antenna offers a maximum gain of 6.68 dB in the operating band. This antenna is useful for C-band, Wi-Max (3.3-3.7 GHz) and WLAN (4.6-5.8 GHz) applications. © 2022 IEEE.

关键词： Microwave antennas

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