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检索条件"任意字段=11th International Conference on Computer-Aided Design and Computer Graphics"

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Magnetic Characteristics-based Selective Driving Algorithm of IPT EV Systems with DDQ Power Pad for High-Efficiency Operation and Wide Misalignment Tolerance

Magnetic Characteristics-based Selective Driving Algorithm o...

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international conference on Power Electronics (ICPE)

作者： Hyeonu Jo Ju-A Lee Dong Hyeon Sim Won-Jin Son Byoung Kuk Lee Department of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea

this paper proposes a selective driving algorithm for a high-efficiency operation of an inductive power transfer (IPT) system in which the double-D quadrature pad (DDQP) is applied. Initially, the IPT pads are manufactured, and the coupling coefficients are measured according to the pad misalignment. Subsequently, the driving algorithm and compensation network of the IPT converter are designed according to the measurement results. After that, the loss analysis is conducted through the simulation to evaluate the designed IPT converter, and the efficiency before and after applying the proposed driving algorithm to the IPT converter is compared to demonstrate the feasibility of the algorithm. Finally, the experimental waveforms are suggested to validate the design of the DDQP - CP IPT system.

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Deep Learning Technique for Real-Time Forest Fire Detection from Video Streams

Deep Learning Technique for Real-Time Forest Fire Detection ...

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Intelligent Systems and Embedded design (ISED), international conference on

作者： Nidhi Gupta Sujata Chakravarty Satyabrata Dash Dept. of Computer Science & Engineering Centurion University of Technology & Management Odisha India Dep. of Computer Science and Engineering Gandhi Institute of Technology & Management (GITAM Deemed to be University) Andhra Pradesh India

Forest fires are currently the most common issue that we are dealing with. the resources that have been lost are irreplaceable. Forest fires are uncontrollable fires that occur in nature as a result of human involvement or any other natural event. Forest fires can be so large that putting them out takes a long time. Contrasting with previous years, there has been a striking surge in the frequency of forest fires. Changes in climatic conditions are the key factor affecting the scope of forest fires. Long dry spells in the spring and summer make the woodlands particularly vulnerable. the extent of forest fires is mostly determined by weather conditions such as precipitation and wind, as well as the terrain's architecture. Long dry spells in the spring and summer make the woodlands particularly vulnerable. the extent of forest fires is mostly determined by weather conditions such as precipitation and wind, as well as the terrain's architecture. the incorporation of a Video Fire Detection model significantly enhances the efficiency of fire detection systems, particularly in large spaces. Establishing a video fire detection system involves focusing on spatial, spectral, and temporal indicators, as well as flame picture segmentation, recognition, tracking, and prediction. Analytical techniques, specifically utilizing ResNet50 and VGG16 models, can be applied to identify pool fire images through these segmentation processes, contributing to more robust fire detection capabilities.

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Magnetics design Optimization for LLC Converter employing Machine Learning

Magnetics Design Optimization for LLC Converter employing Ma...

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international conference on Power Electronics (ICPE)

作者： Nguyen Tan Tung Man-Hay Pong Huang-Jen Chiu Department of Electronics and Computer Engineering National Taiwan University of Science and Technology Taiwan

this paper proposes an intelligent and machine-learning based optimization method that targets to optimal windings layer setup for LLC converter transformer with small number of optimizing iterations. the research utilizes Bayesian optimization (BO) to guide designers toward winding layers setup that achieves the maximum efficiency at nominal operating point of LLC converters. Furthermore, a new multiphysics simulation platform is proposed for feeding efficiencies to optimizing iterations. this simulation platform is able to provide entire losses estimation, high simulation accuracy is verified by measurement. An LLC converter prototype with 33V input and 400V/250W output is implemented to demonstrate effectiveness of proposed optimization method.

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A Class of "Basic Media design" Based on 3D-CAD for Beginners of Digital Processing 19th

A Class of "Basic Media Design" Based on 3D-CAD for Beginner...

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19th international conference on Geometry and graphics, ICGG 2020

作者： Yamashima, Kazuhiro Hori, Seiji Tsukuba Gakuin University Tsukuba Japan

ISBN: (纸本)9783030634025

A basic subject of computer graphics (CG) based on three-dimensional (3D) computer-aided design (CAD) was provided in a class of "Basic Media design" for undergraduate students in their first years. the 3D-CAD used here was the web browser-based 3D modeling tool Autodesk Tinkercad®. During a three-hour class, students are introduced to the following tasks: in the first hour they learn basic functions and skills about 3D design through basic functions of Tinkercad®;in the next hour, they operate the 3D design just by executing the procedures;in the remaining, they create their own 3D model. At the end of the class, they show their 3D models in augmented reality (AR). AR is a technology that allow the visualization of 3D models in the real world adding new information that can also be available on a smartphone. In this way, the students made remarks for what were displayed. © 2021, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Augmented reality

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Surveying the Extent of Demographic Reporting of Animal Participants in ACI Research 24

Surveying The Extent of Demographic Reporting of Animal Part...

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11th international conference on Animal computer Interaction

作者： Ashooh, Lena Hirskyj-Douglas, Ilyena Kleinberger, Rebecca Harvard Univ Cambridge MA 02138 USA Univ Glasgow Sch Comp Sci Glasgow Lanark Scotland Northeastern Univ INTERACT Anim Lab Boston MA USA MIT Media Lab Cambridge MA 02139 USA

ISBN: (纸本)9798400711756

We present a review of demographic information collected and reported about animal research participants in Animal-computer Interaction (ACI) research. Starting from the complete ACI proceedings of 161 publications from the conference beginnings in 2016 until 2023, we established a corpus of 79 publications involving live animal participants. Our aim was to paint a picture of who these animals are, what demographic data was collected about them, and how this data varied across different research contexts. Our analysis revealed 841 live animals represented in ACI research, encompassing 23 different types of animals across 10 research contexts. We observed differences in the demographic information correlating with the animals' types and contexts. We argue that these differences might reflect biases about animals and could impact the interdisciplinary exchange of research findings. In particular, descriptors such as breed, species, and context-specific details were frequently reported, while aspects like personalities, life experiences, and social relationships were less consistently documented, and only in some specific contexts. We discuss the implications of these findings for research validity, reproducibility, and ethical considerations within ACI, proposing recommendations for more consistent and comprehensive reporting practices. this work aims to enhance our understanding of animal participants in ACI research and advance efforts towards equitable and ethical interspecies relationships through technology.

关键词： demographics ethics context animal subjects Animal-computer Interaction animal-centered design multi-species interaction design animal behavior research methods reporting practices

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Integrated Prediction Model for Software Effort of Diversifying Projects Using Machine Learning

Integrated Prediction Model for Software Effort of Diversify...

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Intelligent Systems and Embedded design (ISED), international conference on

作者： Amrita Sharma Neha Chaudhary Bhavna Hotchandani Department of Computer Science Indus University Ahmedabad India Department of Computer Science & Engineering Manipal University Jaipur Jaipur India

Among the most significant responsibilities for those involved in software project management is software effort estimation. the fact that software development is constantly evolving makes it very hard to forecast effort. In the past, academics have estimated effort and duration for one type of methodology for software development. Various size matrices are used for software project estimation. To estimate the lines of code, use cases, objects, and story point for various development methodologies, algorithmic models are used. this work develops a hybrid software-estimating model for projects that are both object-oriented and traditional. there is the primary input is the size of the software, expressed as the lines of code and use case points. the combined Software Effort Prediction Model is created using linear regression analysis. this model is developed using the size of the project and the selected parameters identified with the correlation coefficient. the proposed work has been analyzed using the average magnitude of relative error. this study is further evaluated using existing methods for estimating software costs, and it is discovered that these methods—case-based reasoning, linear regression, radial basis function neural networks, ensemble modeling, and fuzzy analytic hierarchy process — the combined models have the least amount of inaccuracy. Linear regression is used to forecast the effort for procedural and object-oriented projects, and the findings are compared to those from other models to ensure the work is valid. the work obtains the highest accuracy for accurately estimating software projects.

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Combining Context-Awareness and Data Analytics in Support of Drone Technology 1

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11th international conference on Telecommunications and Remote Sensing, ICTRS 2022

作者： Shishkov, Boris Ivanova, Krassimira Verbraeck, Alexander van Sinderen, Marten Institute of Mathematics and Informatics Bulgarian Academy of Sciences Sofia Bulgaria Faculty of Information Sciences University of Library Studies and Information Technologies Sofia Bulgaria Institute IICREST Sofia Bulgaria Faculty of Technology Policy and Management Delft University of Technology Delft Netherlands Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede Netherlands

ISBN: (数字)9783031232268

ISBN: (纸本)9783031232251

Drones performing an autonomous mission need to adapt to frequent changes in their environment. In other words, they have to be context-aware. Most current context-aware systems are designed to distinguish between situations that have been pre-defined in terms of anticipated situation types and corresponding desired behavior types. this only partially benefits drone technology because many types of drone missions can be characterized by situations that are hard to predict at design time. We suggest combining context-awareness and data analytics for a better situation coverage. this could be achieved by using performance data (generated at real-time) as training data for supervised machine learning – it would allow relating situations to appropriate behaviors that a drone could follow. the conceptual ideas are presented in this position paper while validation is left for future work. © 2022, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Data Analytics

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design and Implementation of a High-Gain Ku-Band Low Noise Amplifier

Design and Implementation of a High-Gain Ku-Band Low Noise A...

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IEEE UP Section conference on Electrical computer and Electronics (UPCON)

作者： Kirti Shivam Verma Somak Bhattacharyya Department of Electronics Engineering Indian Institute of Technology (BHU) Varanasi U.P. India

ISBN: (数字)9798350378726

ISBN: (纸本)9798350378733

this paper presents a robust Ku-band low-noise amplifier (LNA) developed using GaN high-electron-mobility transistor (HEMT). the LNA employs a small signal equiva lent circuit model that exhibits significant small-signal and noise characteristics, as well as impressive linearity. the LNA is designed using $0.15~\mu\mathrm{m}$ AlGaN/GaN process on the SiC sub starte. the design incorporates a careful selection of HEMT configurations and the use of simultaneous matching tech niques that maximizes the gains and minimizing noise figure (NF), input, output, and isolation losses simultaneously. the proposed LNA based on GaN HEMT design offers gain of 35 dB and 36 dB, respectively, at 12 GHz and 18 GHz, with ex tremely low noise figures of 1.1 dB and 1.26 dB. the return losses for both input and output over the complete band of operation are better than 15 dB. the proposed LNA can find potential applications in a space receiver.

关键词： Noise figure Low-noise amplifiers Noise Receivers HEMTs Aerospace electronics Ku-band Reflection coefficient Gain Wideband

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design Safety Training Using Extended Reality Tracking Tools in Semiconductor Fabrication Laboratory Furnace 11th

Design Safety Training Using Extended Reality Tracking Tools...

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11th international conference on Robotics, Vision, Signal Processing and Power Applications, RoViSP 2021

作者： Alnagrat, Ahmed Jamah Ahmed Ismail, Rizalafande Che Idrus, Syed Zulkarnain Syed Faculty of Applied and Human Sciences Universiti Malaysia Perlis Perlis Arau Malaysia Department of Computer Science and Information Technology Higher Institute of Science and Technology Wadi al-Shati Fezzan Libya School of Computing and Informatics Albukhary International University Kedah Alor Setar Malaysia

ISBN: (纸本)9789811681288

Due to the possibilities provided by such technologies to provide people with live immersive virtual worlds, Extended Reality (XR) technologies such as virtual (VR), augmented (AR), and mixed reality (MR) have grown. the role of XR has a highly effective and efficient technology in virtual laboratories (VL) as experiments can be performed almost anywhere. During the laboratory activities, students are facing the issue of dealing with dangerous equipment such as Semiconductor fabrication furnace, which has a high temperature. In recent years, modern sensors such as Leap Motion Controller can track human movements and analyses the accuracy. this work presents a novelty approach of design training that can tracks body movements. Moreover, it provides warring alerts to trainer when it comes closer to dangerous places. While she/he is making wrong hand/body movement. When user do the experiment a semiconductor furnace training is operation in a VL. To illustrate more, this training enables the trainee to prevent his/her burning during the experiment according to safety and social distancing standards as well. thus, Unity 3D has the capability to measure the following: accuracy, quality and efficiency of the system. XR training is significantly considering as safe technology to avoid user’s accidents. To conclude, in the field of Human-computer interaction (HCI), the analysis has been improved the training movement in terms of accuracy and interactivity respectively. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Human computer interaction

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Review Paper Real-Time Phishing Website With Machine Learning

Review Paper Real-Time Phishing Website With Machine Learnin...

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Intelligent Systems and Embedded design (ISED), international conference on

作者： Khushal Sharma Pratik Rai Jyoti Chandel Department of Computer Science & Engineering Chandigarh University Mohali India

Phishing is a cybercrime in which an attacker sends a false email designed to mislead the receiver into exposing personal information, such as passwords, credit card numbers, or other sensitive data. Phishing websites are one of the most frequent ways attackers carry out phishing attacks. these websites are made to look like actual websites, such as banking websites or online businesses, to fool the victim into entering their personal information. Machine learning is a form of artificial intelligence that can detect phishing websites. Machine learning algorithms can be educated on enormous datasets of phishing websites and legal websites to identify the properties that discriminate between the two. Once taught, these algorithms can be used to classify new websites as phishing or authentic in real time. this paper addresses the state-of-the-art in machine learning-based phishing website identification. the paper explains the many machine-learning approaches that have been deployed for this work, as well as the features that have been utilized to train these algorithms. the article also explores the limitations of real-time phishing website identification and the prospects of this research.

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