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Vehicle Head and Tail Recognition Algorithm for Lightweight DCDSNet

Computers, Materials & Continua 2024年第9期80卷 4451-4473页

作者： Chao Wang Kaijie Zhang Xiaoyong Yu Dejun Li Wei Xie Xinqiao Wang School of Informatics and Engineering Suzhou UniversitySuzhou234000China School of Informatics and Engineering Suzhou Vocational College of Civil AviationSuzhou234122China Institute of Machine Learning and Systems Biology School of Electronics and Information EngineeringTongji UniversityShanghai201804China

In the model of the vehicle recognition algorithm implemented by the convolutional neural network,the model needs to compute and store a lot of *** many parameters occupy a lot of computational resources making it difficult to run on computers with poor ***,obtaining more efficient feature information of target image or video with better accuracy on computers with limited arithmetic power becomes the main goal of this *** this paper,a lightweight densely connected,and deeply separable convolutional network(DCDSNet)algorithmis proposed to achieve this *** Geometry Group(VGG)model is improved by utilizing the convolution instead of the fully connected module,the deeply separable convolution module,and the densely connected network module,with the first two modules reducing the parameters and the third module allowing the algorithm to have more features in a limited number of *** algorithm achieves better results in the mine vehicle recognition *** show that the recognition accuracy is improved by 4.41% compared to VGG19 and the amount of parameters is reduced by 71% compared to VGG19.

关键词： VGGNet vehicle head and tail recognition densely connected depthwise separable convolutional

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Molecules with a TEMPO-based head group as high-performance organic friction modifiers

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Friction 2023年第2期11卷 316-332页

作者： Jinchi HOU Masaki TSUKAMOTO Seanghai HOR Xingyu CHEN Juntao YANG Hedong ZHANG Nobuaki KOGA Koji YASUDA Kenji FUKUZAWA Shintaro ITOH Naoki AZUMA Department of Complex Systems Science Graduate School of InformaticsNagoya UniversityNagoya 464-8601Japan Institute of Materials and Systems for Sustainability Nagoya UniversityNagoya 464-8601Japan Department of Micro-Nano Systems Engineering Graduate School of EngineeringNagoya UniversityNagoya 464-8603Japan

High-performance organic friction modifiers(OFMs)added to lubricating oils are crucial for reducing energy loss and carbon *** establish a new class of OFMs,we measured the friction and wear properties of N-(2,2,6,6-tetramethyl-1-oxyl-4-piperidinyl)dodecaneamide referred to as *** effect of its head group chemistry,which is characterized by a rigid six-membered ring sandwiched by an amide group and a terminal free oxygen radical,was also investigated with both experiments and quantum mechanical(QM)*** measurement results show that C12Amide-TEMPO outperforms the conventional OFMs of glyceryl monooleate(GMO)and stearic acid,particularly for load-carrying capacity,wear reduction,and stability of friction over *** friction and wear reduction effect of C12Amide-TEMPO is also greatly superior to those of C12Ester-TEMPO and C12Amino-TEMPO,in which ester and amino groups replace the amide group,highlighting the critical role of the amide *** QM calculation results suggest that,in contrast to C12Ester-TEMPO,C12Amino-TEMPO,and the conventional OFMs of GMO and stearic acid,C12Amide-TEMPO can form effective boundary films on iron oxide surfaces with a unique double-layer structure:a strong surface adsorption layer owing to the chemical interactions of the amide oxygen and free radical with iron oxide surfaces,and an upper layer owing to the interlayer hydrogen-bonding between the amide hydrogen and free radical or between the amide hydrogen and ***,the intralayer hydrogen-bonding in each of the two layers is also *** suggest that in addition to strong surface adsorption,the interlayer and intralayer hydrogen-bonding also increases the strength of the boundary films by enhancing the cohesion strength,thereby resulting in the high tribological performance of *** findings in this study are expected to provide new hints for the optimal molecular design of OFMs.

关键词： organic friction modifiers(OFMs) TEMPO friction and wear surface adsorption molecular reactivity boundary lubrication

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INTEGRATING UNMANNED AERIAL systems INTO THE INTELLIGENT systems engineering CURRICULUM 34th

INTEGRATING UNMANNED AERIAL SYSTEMS INTO THE INTELLIGENT SYS...

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34th Congress of the International Council of the Aeronautical Sciences, ICAS 2024

作者： Dantsker, Or D. Department of Intelligent Systems Engineering Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN United States

This paper presents two hands-on, project-based courses on unmanned aerial systems recently offered by the Intelligent systems engineering program at Indiana University. In Fall 2023, ENGR-E399/599 Autonomous Sports was redeveloped to focus on integrated vehicle design and development of lighter-than-air vehicles in a capstone-like, project-based course format. And in Spring 2024, ENGR-E399/599 Unmanned Aerial systems was developed to introduce students to UAS in a lecture-lab-project format where students learned about underlying aircraft concepts, developed a micro-controller-based autopilot, ultimately integrated it into a small fixed-wing unmanned aircraft that was test flown. These courses, geared towards advanced undergraduate and graduate students, allow them to apply their prerequisite knowledge to these hardware-lab heavy courses, enabling experiential learning, i.e. "learn-by-doing". © 2024, International Council of the Aeronautical Sciences. All rights reserved.

关键词： Students

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Real-Time Tracking of Diagnostic Discrepancies in Electronic Health Records for Improved Predictive Modeling

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IEEE Access 2025年 13卷 101841-101851页

作者： Trader, Elizabeth A. Gurupur, Varadraj P. University of Central Florida Department of Electrical and Computer Engineering FL United States University of Central Florida Center for Decision Support Systems and Informatics FL United States University of Central Florida School of Global Health Management and Informatics FL United States

Diagnostic discrepancies, a persistent threat in healthcare, compromise patient outcomes and hinder effective treatment. Despite their prevalence, addressing diagnostic discrepancies remains a complex challenge due to the limitations of traditional methods and fragmented and inaccessible data. The emergence of machine learning (ML) offers a promising solution by analyzing vast medical datasets to detect subtle disease signatures and improve treatment personalization with unparalleled precision. However, data quality and availability remain significant barriers, as incompleteness, inconsistencies, and biases can distort ML models, leading to potentially harmful misinterpretations. This paper highlights the critical role of diagnostic discrepancy statistics in overcoming these challenges and proposes a standardized data schema that ensures interoperable, real-time, and historical data without compromising patient privacy. By addressing the current lack of accessible diagnostic discrepancy data, the schema lays a foundation for more effective analysis, better patient outcomes, and improved use of machine learning in healthcare. The key contribution of this paper is the framework that allows for increased data transparency and improved data quality. © 2013 IEEE.

关键词： Electronic health record

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Design and Development of Smart Farming System for Monitoring and Bird Pest Control Based on Raspberry Pi 4 with Implementation of YOLOv5 Algorithm 5

Design and Development of Smart Farming System for Monitorin...

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5th International Conference on Advancement in Data Science, E-Learning and Information systems, ICADEIS 2023

作者： Antariksa, Muhammad Deagama Surya Husodo, Ario Yudo Huwae, Raphael Bianco Nugraha, Ryan Adhitya University of Mataram Informatics Engineering Mataram Indonesia Telkom University School of Industrial and Systems Engineering Indonesia

ISBN: (纸本)9798350303414

This research proposes a novel solution to address the issue of bird pests in agricultural fields by utilizing a Raspberry Pi 4 Model B, a webcam, and a connected speaker. Leveraging the capabilities of the Internet of Things and computer vision technologies, the webcam employs the YOLOv5 algorithm and OpenCV for real-time bird detection. The system incorporates a Telegram chatbot for instant notifications and allows for photo capture when birds cross predefined boundaries. Extensive testing showcases the webcam's ability to detect birds under various conditions. In open spaces, the detection range spans approximately 80-400 cm, while in environments resembling rice fields, the range is around 80-200 cm, although false positives may occur at a distance of 200 cm. The Raspberry Pi 4 Model B demonstrates a processing speed of 0.78-0.8 frames per second. During a 1-hour temperature test, the temperature of the Raspberry Pi 4 Model B ranged from 58.4 to 61.8 °C. Furthermore, the implementation of a speaker emitting loud noises effectively repels birds within the covered area, although some birds may still return to that area. © 2023 IEEE.

关键词： Birds

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Nano-Width Zigzag Flexure Structures for Highly Tunable Grating Pitch 22

Nano-Width Zigzag Flexure Structures for Highly Tunable Grat...

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22nd International Conference on Solid-State Sensors, Actuators and Microsystems, Transducers 2023

作者： Atsuya, Kiryu Furusawa, Gaku Masaaki, Oshita Kan, Tetsuo The University Of Electro-Communications Graduate School Of Informatics And Engineering Department Of Mechanical Engineering And Intelligent Systems Japan

ISBN: (纸本)9784886864352

We propose a diffraction grating structure with a tunable grating pitch using a nano-width zigzag flexure structure. By introducing a high-aspect flexure structure between the gratings, which is thin in an external force direction and thick in an orthogonal direction, the grating pitch could be changed largely without distorting the grating. We designed a flexure structure to increase the grating pitch change and fabricated a pitch-tunable grating with a high-aspect flexure structure on a silicon-on-insulator wafer. © 2023 IEEJ.

关键词： MEMS Pitch tuning Tunable diffraction grating

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Generation of Routes Using Genetic Algorithms to Optimize the Domestic Solid Waste Collection 8th

Generation of Routes Using Genetic Algorithms to Optimize th...

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8th International Conference on Intelligent Technologies, ICIT 2023

作者： Vega-Huerta, Hugo Marcos, Jordy Mayhuay Acosta, Marx Campos Monrroy, Xavier Villanueva Maquen-Niño, Gisella Luisa Elena Puelles-Bulnes, María Gil-Calvo, Rubén School of Systems Engineering Universidad Nacional Mayor de San Marcos Lima Peru School of Computing and Informatics Engineering Universidad Nacional Pedro Ruiz Gallo Lambayeque Peru

ISBN: (纸本)9789819738588

The district of San Juan de Lurigancho (SJL) in Lima—Peru, is one of the districts crowed in the capital and has one of the highest amounts solid domestic wastes. To fix this problem, a model was developed to map the distance and calculate the best route to collect the domes-tic solid waste in the whole San Carlos neighborhood in SJL district. Our model was developed using genetic algorithms in JavaScript with Node JS to calculate the shortest path. For the data visualization was used the React JS for the frontend and Google Maps API for the display of an interactive map. The results obtained allowed were able to find an optimal route that joins two opposite points within the map of the San Carlos neighborhood, which is made up of 5 nodes and measures 514 m away. The model developed could generate populations of 10 to 100 individuals with the map nodes through selection, crossing and mutation processes, obtaining an optimal route that facilitates the domestic waste collection processes with the shortest distance. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Collection Genetic algorithm Minimum route Pathfinding Solid waste

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A Classification Method for 'Kawaii' Images Using Semantic Interpretation

A Classification Method for 'Kawaii' Images Using Semantic I...

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2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Komiya, Daiki Akiyoshi, Masanori Graduate School of Engineering Kanagawa University Japan Kanagawa University Faculty of Informatics Department of Applied Mathematics Systems Japan

ISBN: (纸本)9781665410205

This paper proposes a classification method for five types of images represented by the word 'kawaii.' 'kawaii images' do not have fixed concept or object, which makes it to classify them simply using conventional methods such as Convolutional Neural Network or Support Vector Machine. Our previous study extracted color and shape features from such images, then achieving a classification accuracy of 70.2 %. However, this approach did not handle the semantic content of the images. In this study, a classification method based on the constituent elements of 'kawaii images' is used, resulting in a classification accuracy of 71.4 %. Additionally, the experiment seems to providing possibilities to reflect similarities with human recognition to some extent. © 2024 IEEE.

关键词： Image classification

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SUPPORTING FARMING SMART DOCUMENTATION SYSTEM by MODULAR BLOCKCHAIN SOLUTIONS

Decision Making: Applications in Management and Engineering

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Decision Making: Applications in Management and engineering 2022年第1期5卷 1-26页

作者： Arsyad, Andi Arniaty Widayat, Irawan Widi Köppen, Mario Departement of Computer Science and Systems Engineering Graduate School of Creative Informatics Kyushu Institute of Technology Japan

For more than a decade, various farm-specific models have been developed by collaborating and integrating sensing technologies as a step toward successful data-farm documentation and effective decision-making. However, the stored and gathered data continues to rely on cloud infrastructure or centralized platform control, which is particularly vulnerable to threats such as data tampering, data distortion, confidentiality, and manipulation, which caused the farm product data difficult to trace to its provenance. The objective study in this paper proposes a farm transaction model by demonstrating a flow of farm transaction simulation implicated by Modular Block Chain(MBC) sensing instrument with an array of sensors, controllers, networking hardware, computing equipment, and internal memory functions to enhance data integrity and security farm object. Based on the proposed model, a proof-of-concept experimental system called Encapsulating Block Mesh (EBM) integrates blockchain technology with the specific application case of cocoa production has been implemented. Results have shown that farm objects represented by MBC take turn recording information on the process of generating, transacting, and consuming a farm product and encrypting it into a block was validated and linked in the EBM with the hash of transaction data that connected to each cocoa farm object in a simulation environment. The findings from this study are twofold: the approach has been shown to be feasible and effective, but also capable to be expanded to other stages of the food supply chain, such as manufacturing, supermarkets, food consumption (consumers), and recycling in real-world environments. © 2018 by the authors.

关键词： Food supply

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Disrupting Higher Education: A Comparative Study of Synchronous Lecturing and Self-Paced Learning in Higher Education 2

Disrupting Higher Education: A Comparative Study of Synchron...

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2nd International Conference on Software engineering and Information Technology, ICoSEIT 2024

作者： Putri, Nuril Kusumawardani Soeprapto Yuhana, Umi Laili Siahaan, Daniel Oranova Alfian, Muhammad Bina Nusantara Universiy School of Information Systems Information Systems Department Jakarta11480 Indonesia Institut Teknologi Sepuluh Nopember Department of Informatics Engineering Surabaya Indonesia

ISBN: (纸本)9798350317503

During the two-year period of the COVID-19 pandemic, educators worldwide had to adapt to various teaching methods, including synchronous instruction via platforms like Zoom and asynchronous teaching methods utilizing technology to deliver course content. Even after the pandemic subsided, it became evident that asynchronous learning continued to play a significant role in higher education. The pandemic accelerated the use of technology and disrupted various sectors, including e-commerce and others. In the area of education, the question arose as to whether technology could also disrupt higher education. This study aims to investigate the potential disruptive impact of technology in higher education. The research delves into the transformative possibilities of online education by comparing the effectiveness of two distinct methods: synchronous lecturing and self-paced learning (asynchronous learning) with interactive digital content. Undergraduate students were engaged in pre-test and post-test evaluations after each learning process, focusing on a subject matter that was new to them. The study's findings reveal that both self-paced learning with interactive digital content and synchronous lecturing lead to significant improvements in students' scores. This suggests that online learning, when thoughtfully designed, can effectively facilitate learning in higher education, potentially reshaping traditional educational paradigms. © 2024 IEEE.

关键词： COVID-19

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