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26th International Conference on Industrial Technology, ICIT 2025

作者： Fujimoto, Ren Siang Leow, Chee Yajima, Hideaki Makino, Koji Mao, Xiaoyang Nishiizaki, Hiromitsu University of Yamanashi Dept. of Mechatoronics Kofu Japan University of Yamanashi Dept. of Computer Science and Engineering Kofu Japan

ISBN: (纸本)9798331521950

This paper presents a novel autonomous navigation system for grapevine cultivation robots operating in overhead trellis vineyards, a challenging environment characterized by irregular grape cluster distribution and complex 3D structures. The system integrates two complementary navigation approaches: high-precision positioning under target grape bunches using YOLOv8-based object detection of QR codes, and large-scale vineyard navigation using global navigation satellite system (GNSS). Each QR code uniquely identifies a grape bunch and provides access to its associated cultivation data. Experimental evaluations in a simulated vineyard environment demonstrated an 83.3% success rate for object detection-based positioning beneath grape bunches and 90% accuracy for GNSS-based navigation within a 1.0 m radius of the target locations. These results validate the system's effectiveness in automating navigation tasks within overhead trellis vineyards, offering a promising solution to address labor shortages and improve the efficiency of grape cultivation practices. © 2025 IEEE.

关键词： Precision agriculture

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Navigating the Landscape of Intelligent Systems, Smart Technologies, and User-Centric Evolution

Navigating the Landscape of Intelligent Systems, Smart Techn...

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), International Conference on

作者： Sanjay Reddy Komatireddy Y. Krishna Bhargavi Dept. of Computer Science and Engineering Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad India

Human-computer Interaction (HCI) is a dynamic field pi votal in shaping human-technology relationships. HCI is a multidisciplinary field, essential in understanding and enhancing the interaction between humans and technology. Challenges within HCI encompass design, usability, accessibility, and emotional resonance. The aim of this research study is to highlight the multifaceted nature of HCI, offering insights into its transformative and complementing potential and its continuous influence on the digital landscape. By delving into the challenges faced and the current technologies (Multimodal Affect Recognition, Artificial Intelligence, etc.), this review serves as a foundation for further research and development in this vital domain, offering valuable insights into the dynamic HCI landscape.

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Advancements in User Security: Enhancing Usability with Graphical Password Authentication

Advancements in User Security: Enhancing Usability with Grap...

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), International Conference on

作者： Harisha Sandhya Ramesh Naik Shettigar Sarvani Vasudeva K Shrilakshmi Vaishnavi Kothwal Dept. of Computer Science & Engineering Sahyadri College of Engineering & Management Mangalore Karnataka India

Text-based password authentication is a common method used to verify the identity of users who are trying to access a secure system or service. In order to use this authentication method, the user must input a password or other secret phrase that is then compared to a server-side copy of the same password. Access is given if the password typed matches the one saved. Graphical password authentication is a type of user authentication that involves using images or visual elements instead of alphanumeric characters to verify the identity of the user. Unlike traditional text-based passwords, graphical passwords offer an intuitive and user-friendly way of authentication, as they rely on the user's ability to remember pictures, shapes, and patterns. This technology has been developed to address the limitations of traditional text-based passwords, such as the difficulty of creating and remembering complex passwords, and the vulnerability to brute-force attacks. Compared to conventional text-based passwords, graphical password authentication has a number of benefits, including better usability and higher security.

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Predictive Maintenance of a Metro's Air Compressor 5

Predictive Maintenance of a Metro's Air Compressor

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5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Barpute, Jyotsna Vilas Suryawanshi, Shubhangi Kshirsagar, Vanita Bhosale, Digvijay Patil, Pramod Patil, Atharv Dr. D. Y. Patil Institute of Technology Dept. of Artificial Intelligence and Science Pune Pimpri India Dr. D. Y. Patil Institute of Technology Dept. of Mechanical Engineering Pune Pimpri India Dr. D. Y. Patil Institute of Technology Dept. of Computer Engineering Pune Pimpri India

ISBN: (纸本)9798350379945

A Metro air compressor turns power into potential energy by compressing and storing air in a tank. When the pressure reaches its limit, the compressor shuts down, storing the compressed air until it is needed for various uses. Early prediction enables proactive decision-making, which helps to avoid unfavourable outcomes before they occur. It also optimizes resource allocation to ensure efficiency and effectiveness across several processes. The proposed method is a machine learning-based strategy for predictive maintenance of a metro train's air compressor. The MetroPT -3 dataset was used, which includes parameters for pressure, temperature, motor current, air intake valves, and so on. Seven analogue and eight digital signals. The technique entails data preprocessing, anomaly identification using an exclusion forest classifier, training multiple machine learning models, and integrating the chosen model with the rest of the system. Gradient-boosting models outperformed linear models in terms of accuracy, but they were slower to compute. They conclude that predictive maintenance benefits metro compressors and has the potential to revolutionize equipment maintenance in general. © 2024 IEEE.

关键词： Predictive maintenance

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Modulo-(22n + 1) Arithmetic via Two Parallel n-bit Residue Channels

arXiv

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arXiv 2024年

作者： Jaberipur, Ghassem Nadimi, Bardia Lee, Jeong-A Dept. of Computer Engineering Chosun University Gwangju Korea Republic of Dept. of Computer Science and Engineering University of South Florida TampaFL United States

Augmenting the balanced residue number system moduli-set {m1 = 2n, m2 = 2n − 1, m3 = 2n + 1}, with the co-prime modulo m4 = 22n + 1, increases the dynamic range (DR) by around 70%. The Mersenne form of product m2m3m4 = 24n − 1, in the moduli-set {m1, m2, m3, m4}, leads to a very efficient reverse converter, based on the New Chinese remainder theorem. However, the double bit-width of the m4 residue channel is counter-productive and jeopardizes the speed balance in {m1, m2, m3}. Therefore, we decompose m4 to two complex-number n−bit moduli 2n ± √−1, which preserves the DR and the co-primality across the augmented moduli set. The required forward modulo-(22n + 1) to moduli-(2n ± √−1) conversion, and the reverse are immediate and cost-free. The proposed unified moduli-(2n ± √−1) adder and multiplier, are tested and synthesized using Spartan 7S100 FPGA. The 6−bit look-up tables (LUT), therein, promote the LUT realizations of adders and multipliers, for n = 5, where the DR equals 225 −25. However, the undertaken experiments show that to cover all the 32-bit numbers, the power-of-two channel m1 can be as wide as 12 bits with no harm to the speed balance across_ the five moduli. The results also show that the moduli-(25 ± √−1) add and multiply operations are advantageous vs. moduli-(25 ± 1) in speed, cost, and energy measures and collectively better than those of modulo-(210 + 1). Copyright © 2024, The Authors. All rights reserved.

关键词： Table lookup

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Field Demonstration of Blockchain-based Security for a Solar Farm

Field Demonstration of Blockchain-based Security for a Solar...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： BoHyun Ahn Kalyan Nakka Nathanial R. Handke Trevor J. Reyna Taesic Kim Dept. of Electrical Engineering and Computer Science Texas A&M University-Kingsville Kingsville TX USA Dept. of Computer Science and Engineering Texas A&M University College Station TX USA Dept. of Electrical Engineering and Computer Science University of Missouri-Columbia Columbia MO USA

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

This paper introduces a Blockchain (BC)-based security model for a solar farm, providing security functions such as firmware patching management, role-based access control, public key infrastructure, and man-in-the-middle attacks detection (MITM), malware file detection. In particular, this paper provides detailed field-testing methods at a solar fam to demonstrate the feasibility and effectiveness of cyber-attack detection methods. Practical cyberattacks targeting solar farms are designed and conducted. It is demonstrated that the proposed BC-based system proactively detects MITM attacks, firmware modification attack, and malware attack, while ensuring the continuous operation of the solar farm during attack events.

关键词： Solar farms Solar energy Network security Malware Vectors Blockchains Security Testing Payloads Microprogramming

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An Extended Reality Platform Powered by Large Language Models: A Case Study on Teaching Dance Costumes

An Extended Reality Platform Powered by Large Language Model...

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IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)

作者： Silvia Garzarella Giacomo Vallasciani Pasquale Cascarano Shirin Hajahmadi Elena Cervellati Gustavo Marfia Dept. of the Arts University of Bologna Bologna Italy Dept. of Computer Science and Engineering University of Bologna Bologna Italy

ISBN: (数字)9798331521578

ISBN: (纸本)9798331521585

In this paper, we present an Extended Reality (XR) platform powered by Large Language Models (LLMs), designed to support education in dance history and cultural heritage. The platform here applied to a case study on a dance costume, allows users to interact with 3D models, annotate them, and explore their historical and cultural contexts collaboratively. Using features like image-to-LLM queries, users can gain insights into costume details and performance history, and the annotation tools enable uploading multimedia resources, thereby simulating an archival research environment. By integrating LLMs, the platform provides tailored information and context on demand, enriching the user experience with detailed explanations about objects, such as costume construction, usage, and cultural significance.

关键词： Solid modeling Three-dimensional displays Extended reality Annotations Large language models User experience Cultural differences History Context modeling

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Online Signature Recognition using Transformer Networks: An Overview 6

Online Signature Recognition using Transformer Networks: An ...

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6th IEEE International Conference on Advances in science and Technology, ICAST 2023

作者： Bharadi, Vinayak Hamdule, Zohaib Kambli, Sujan Salvi, Raj Chavan, Raj Nimbalkar, Vrishali Finolex Academy of Management and Technology Department of Information Technology Ratnagiri India Finolex Academy of Management and Technology Dept. of Computer Science and Engineering Ratnagiri India

ISBN: (纸本)9798350359817

Online signature verification remains a pivotal component in digital security, ensuring the authenticity of digital transactions and documents. This paper offers a comprehensive overview of prevailing online signature verification techniques, with a particular emphasis on methods employing Deep Learning. RNNs, with their inherent capability to process sequential data, have been instrumental in improving the accuracy and efficiency of signature verification systems. However, as the digital forgery landscape becomes increasingly sophisticated, there is a pressing need to explore advanced neural architectures. In this context, the paper introduces a transformer-based approach for signature verification. Unlike traditional models, transformers, with their self-attention mechanisms, have the potential to capture intricate signature patterns and nuances, offering a promising avenue for future research and application. © 2023 IEEE.

关键词： Recurrent neural networks

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A Comprehensive Study of Solar Energy Harvesting System in Wireless Sensor Networks 9

A Comprehensive Study of Solar Energy Harvesting System in W...

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9th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and computer engineering, UPCON 2022

作者： Sah, Dipak Kumar Mazumdar, Nabajyoti Pal, Pankaj Amgoth, Tarachand Dept. of Computer Science & Engineering Dhanbad826004 India Indian Institute of Information Technology Dept. of Information Technology Allahabad211015 India

ISBN: (数字)9798350332506

ISBN: (纸本)9798350332506

Wireless Sensor Networks (WSNs) incorporate sensor nodes with minimal power consumption. Sensor devices are in high demand in many areas, including smart cities, environmental monitoring, the Internet of Things (IoT), health monitoring, and the like. As nodes are frequently located in remote places, and an ordinary node battery life is too short, energy depletion is a significant problem for the sensor network. But it's not practical to change or regularly maintain the sensor node's battery. This could cause the network to disconnect. Consequently, a recharging sensor node battery has been identified using energy harvesting (EH). It has several environmental forms, including solar, wind, mechanical, etc. The solar system provides unlimited energy resources to nodes. This paper examines a comprehensive case study of solar harvesting systems and their most recent applications. In solar harvesting nodes, the following primary components are utilised: solar panels, energy storage classes, a DC-DC converter, maximum power point tracking (MPPT), an energy predictor, and a sensing module. Furthermore, we have discussed some recent applications and future work of sensor networks, for example, green street lights, agriculture 4.0, outdoor environment-based monitoring, IIoT, hybrid storage class and new communication technologies. © 2022 IEEE.

关键词： Sensor nodes

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Non-Invasive Oral Cancer Detection Using Hyperspectral Imaging and Advanced Spectral Unmixing Models

Non-Invasive Oral Cancer Detection Using Hyperspectral Imagi...

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Intelligent Computing and Emerging Communication Technologies (ICEC), International Conference on

作者： Valluri Ayyapa Kesava Sriram Kothamasu Priyusha Killaru Saadhivik Muddana Suresh Aala Vamsi Gutha Mukkara Prasana Kumar Sunil Chinnadurai Dept.of Electronics and Communication Engineering SRM University AP India Dept. of Computer Science and Engineering SRM University AP India Dept. of Computer Science SRM University AP India

ISBN: (数字)9798331508432

ISBN: (纸本)9798331508449

Oral cancer is a significant global health concern, often leading to high mortality rates due to late-stage diagnosis and the lack of effective early detection methods. Despite advances in medical science, the absence of reliable early diagnostic tools remains a critical challenge. Hyperspectral imaging (HSI) has emerged as a powerful noninvasive technology, capturing detailed spectral information across a wide range of wavelengths. This allows for accurate differentiation between cancerous and healthy tissues, improving early detection and enhancing treatment outcomes. In this study, we propose the use of HSI for early oral cancer diagnosis. To address the scarcity of labeled data, we developed a synthetic hyperspectral dataset that includes spectral signatures of both normal and cancerous tissues. The dataset was generated using a bilinear mixing model, with key spectral features extracted through Vertex Component Analysis (VCA) and abundances computed using Non-Negative Least Squares (NNLS). The model's performance was evaluated using Spectral angle distance (SAD) and Root mean square error (RMSE) metrics. Our findings demonstrate that HSI significantly improves the accuracy of early oral cancer detection, outperforming traditional methods. This work highlights the potential of advanced imaging technologies in revolutionizing cancer diagnosis, offering a robust framework for non-invasive detection and showcasing the effectiveness of synthetic datasets in medical imaging research.

关键词： Measurement Accuracy Computational modeling Mortality Feature extraction Reliability Root mean square Cancer Hyperspectral imaging Synthetic data

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