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检索条件"任意字段=18th International Conference on Software Engineering and Knowledge Engineering"

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High performance waveguide integrated vertical Silicon-based Germanium avalanche photodetectors 18

High performance waveguide integrated vertical Silicon-based...

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18th National conference on Laser Technology and Optoelectronics 2023

作者： Yi, Linkai Liu, Daoqun Zhang, Peng Tang, Bo Li, Bin Yang, Yan Wang, Wenwu Li, Zhihua Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781510668379

To achieve efficient optical communication and optical interconnection, it is necessary to develop and prepare detectors with high gain, low noise, high bandwidth and strong anti-electromagnetic interference. Because III-V materials cannot be integrated with CMOS process line, therefore, avalanche photodiodes (APDs) based on germanium silicon substrates are considered as detectors with large scale integration. Waveguide integrated structure can solve the contradiction between response and bandwidth in surface illuminated structure. Moreover, with germanium as the absorption region, a SACM (separate absorption charge multiplication) structure with silicon as a multiplication region has become a widely used device structure. In this work, a new vertical structure waveguide integrated structure of silicon-based germanium APD is designed with the charge layer on both sides of the germanium absorption layer, and the influence of the thickness of the multiplication layer on the dark current is simulated and tested. It shows that when the width of the multiplication layer increases, the breakdown voltage of the device increases, indicating that the electric field level of the multiplication region is similar to that of different devices at the breakdown voltage, furthermore, the simulation and experimental results are basically consistent. Under the input power of -16.8 dBm for 1310 nm incident light, the bandwidth of the designed vertical structure SACM silicon-based germanium APD can reach 25.7 GHz at 15.7 V bias. the primary responsivity of the device is up to 0.68 A/W and the gain bandwidth product is up to 247 GHz, showing the great potential of the present Ge/Si APD for the application in future high-speed data transmission systems. © 2023 SPIE.

关键词： Germanium

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A Distributed Large-Scale Agile software Development for Multiple Products and Its Practical Evaluation 19

A Distributed Large-Scale Agile Software Development for Mul...

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IEEE/ACIS 19th international conference on software engineering Research, Management and Applications (SERA)

作者： Tanaka, Masayuki Aoyama, Mikio Nanzan Univ Nagoya Aichi Japan

ISBN: (纸本)9781728176772

In agile software development, there are several well-known frameworks by integrating rules and methods. Among them, Scrum-based agile frameworks for large organizations need much knowledge and experience to start it, although Scrum has fewer rules and is easy to start. Among other known frameworks, Scaled Agile Framework (SAFe), which has complicated rules, has lots of case studies than others. However, Large Scale Scrum (LeSS) and LeSS Huge are also known and have lots of case studies in Japan, so enhancing LeSS and LeSS Huge framework is one of the well-developed ways to solve the organization's issues quickly. this paper aims to propose a new method, named Multi-Products Agile Method, based on LeSS Huge for developing multiple products in parallel at a large organization. We applied the proposed method to three products based in Japan. We had been tracking the velocity that is a total number of about 10 teams for one year. Our results prove that the proposed method is an effective way to scale agile organizations for multiple products. the method also makes it possible to use the knowledge and experiences of LeSS or LeSS Huge. We conclude Multi-Products Agile Method is an extended framework of LeSS and LeSS Huge.

关键词： Enterprise Agile Large Scale Scrum LeSS Huge Scrum Distributed Agile Development

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Efficient Numerical Computation of Dispersion Diagrams for Glide-Symmetric Periodic Structures with a Hexagonal Lattice

Efficient Numerical Computation of Dispersion Diagrams for G...

引用

European conference on Antennas and Propagation, EuCAP

作者： M. Petek J. A. Tobon Vasquez G. Valerio F. Mesa O. Quevedo-Teruel F. Vipiana Dept. of Electronics and Telecommunications Politecnico di Torino Torino Italy Division of Electromagnetic Engineering KTH Royal Institute of Technology Stockholm Sweden Laboratoire de Génie Electrique et Electronique de Paris (GeePs) Sorbonne Université CNRS Paris France Université Paris-Saclay CentraleSupélec CNRS GeePs Gif-sur-Yvette France Dept. Física Aplicada 1 Universidad de Sevilla Seville Spain

In this work, we present a modeling methodology to solve the eigenvalue problem for periodic structures with a hexagonal lattice. the method is based on the previously proposed multi-modal transfer matrix method, which is a hybrid method that takes into account the coupling between the multiple modes of the ports surrounding the single unit cell. Commercial software can be used to obtain the generalized scattering parameters which are subsequently applied to set up and solve the eigenvalue problem of the periodic structure. this approach has the ability to obtain complex solutions and thus makes it possible to analyze the attenuation in the stopbands. Here, we extend the multimodal transfer matrix method to the efficient solution of the resulting eigenvalue problem for the case of a hexagonal lattice, detailing the selection of the appropriate supercells and the appropriate irreducible Brillouin zones. Two types of structures are analyzed: a mirror-symmetric structure and a glide-symmetric structure. Very good agreement is obtained with commercial software, limited to the real part of the dispersion diagrams.

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A software Bug Fixing Approach Based on knowledge-Enhanced Large Language Models

A Software Bug Fixing Approach Based on Knowledge-Enhanced L...

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IEEE international conference on software Quality, Reliability and Security (QRS)

作者： Lili Bo Yuting He Xiaobing Sun Wangjie Ji Xiaohan Wu Yangzhou University

ISBN: (数字)9798350365634

ISBN: (纸本)9798350365641

software Bug Fixing is a time-consuming task in software development and maintenance. Despite the success of Large Language Models (LLMs) using in Automatic Program Repair (APR), they still have the limitations of generating patches with low accuracy and explainability. In this paper, we propose a software bug-fixing approach based on knowledge-enhanced large language models. First, we collect bugs as well as their fix information from bug tracking systems, such as Github and Stack Overflow. then, we extract bug entities and inter-entity relationships using Named Entity Recognition (NER) to construct a Bug knowledge Graph (BKG). Finally, we utilize LLMs (e.g., GPT-4) which is enhanced by the knowledge of the similar historical bugs as well as fix information from BKG to generate patches for new bugs. the experimental results show that the our approach can fix 28.52% (85\298) bugs correctly, which is significantly better than the state-of-the-art approaches. Furthermore, the generated patches are explainable and more credible.

关键词： Codes Accuracy Large language models Computer bugs knowledge graphs Maintenance engineering software

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Impact of gateway placement and energy consumption for data processing on lifetime of IoT networks 18

Impact of gateway placement and energy consumption for data ...

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18th international conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2021

作者： Jinaporn, Nakrop Saengudomlert, Poompat Ubon Ratchathani University Department of Electrical and Electronic Engineering Ubon Ratchathani Thailand BU-CROCCS Bangkok University Pathum Thani Thailand

ISBN: (纸本)9780738111278

the network lifetime has been considered as one of the key parameters in IoT networks. Energy consumption of sensor nodes is a major concern in maximizing the network lifetime where not only data transmission but also data processing consume energy. In this article, maximum lifetime routing (MLR) in an IoT network is formulated as a linear optimization problem that, in addition to energy dissipation of data transmission, includes energy consumption for data processing. Optimization results reveal that the placement of the gateway has a significant impact on the network lifetime. Compared to placing the gateway at the geographical center, the network lifetime increases by almost 36% if the gateway is in the optimal location. Numerical results of the network lifetime also quantify the impact of energy consumption for data processing. Compared with the MLR problem without considering data processing, the network lifetime can decrease as much as 40% when energy consumption for data transmission and data processing units are equal (Eelec = Epro). this work could be applied to facilitate the field of wireless network planning. © 2021 IEEE.

关键词： Energy utilization

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A Transfer Learning Approach to the Development of an Automation System for Recognizing Guava Disease Using CNN Models for Feasible Fruit Production 22nd

A Transfer Learning Approach to the Development of an Automa...

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22nd international conference on Hybrid Intelligent Systems, HIS 2022 and the 18th international conference on Information Assurance and Security, IAS 2022

作者： Shakil, Rashiduzzaman Akter, Bonna Rajbongshi, Aditya Sara, Umme Barman, Mala Rani Dhali, Aditi Department of CSE Daffodil International University Dhaka Bangladesh Department of CSE National Institute of Textile Engineering and Research Dhaka Bangladesh Department of CSE Sheikh Hasina University Dhaka Bangladesh Department of CSE Jahangirnagar University Dhaka Bangladesh

ISBN: (纸本)9783031274084

Guava (Psidium guava) is one of the most popular fruits which plays a vital role in the world economy. To increase guava production and sustain economic development, early detection and diagnosis of guava disease is important. As traditional recognition systems are time-consuming, expensive, and sometimes their predictions are also inaccurate, farmers are facing a lot of losses because of not getting the proper diagnosis and appropriate cure in time. In this study, an automatic system based on Convolution Neural Networks (CNN) models for recognizing guava disease has been proposed. To make the dataset more efficient, image processing techniques have been employed to boost the dataset which is collected from the local Guava Garden. For training and testing the applied models named InceptionResNetV2, ResNet50, and Xception with transfer learning technique, a total of 2,580 images in five categories such as Phytophthora, Red Rust, Scab, Stylar end rot, and Fresh leaf are utilized. To estimate the performance of each applied classifier, the six-performance evaluation metrics have been calculated where the Xception model conducted the highest accuracy of 98.88% which is good enough compared to other recent relevant works. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Diagnosis

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Integrated knowledge and Skills with Multi-Material Learning for engineering Students during COVID-19 29

Integrated Knowledge and Skills with Multi-Material Learning...

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29th international conference on Computers in Education (ICCE)

作者： Howimanporn, Suppachai Tangtrongpairos, Ornanong Chookaew, Sasithorn King Mongkuts Univ Technol North Bangkok Fac Tech Educ Dept Teacher Training Mech Engn Bangkok Thailand Rajamangala Univ Technol Suvarnabhumi Fac Ind Educ Dept Elect & Telecommun Engn Nonthaburi Thailand

ISBN: (纸本)9789869721486

Teaching and learning in engineering courses need to emphasize practicality to acquire integrated knowledge and skills. It is necessary to learn processes controlled by mathematical equations in mechatronic engineering to apply scientific principles to use automation control systems technology to support Industry 4.0, such as automatic control with a Programmable Logic Controller (PLC) control device. In addition, they are applying the data of engineering process control to real-time applications with Supervisory Control and Data Acquisition (SCADA) software and PLC Network. Due to the outbreak of Coronavirus (COVID-19), lack of practice face-to-face interaction, so the effectiveness of online learning practice is significantly reduced. this study presents the combination of remote-control technology and multi-material learning to promote engineering students' conceptual and practical experiments during online learning. the finding shows that this multi-material learning can operate and motivate engineering students in the distance learning situation.

关键词： Automation engineering education PLC SCADA STEM

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Vision-based drones tracking using correlation filters and linear integrated multiple model 18

Vision-based drones tracking using correlation filters and l...

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18th international conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2021

作者： Sie, Niven Junliang Xuan Seah, Shao Chan, Jalvin Jiaxiang Yi, Jiahe Chew, Kim Hoe Hooi Chan, Teng Srigrarom, Sutthiphong Holzapfel, Florian Hesse, Henrik National University of Singapore Mechanical Engineering Singapore Singapore Technical University of Munich Institute of Flight Systems Germany University of Glasgow Aerospace Systems Singapore Singapore

ISBN: (纸本)9780738111278

this paper presents the use of Correlation Filters and Integrated Multiple Model (IMM) for filtering the position measurement of fast moving drones acquired by computer vision, with probability for model selection. the maneuvering movement of the drones are often non-linear making it hard to be estimated by a simple Kalman filter. Instead of using a non-linear filter which are more complex and non-universal, this paper attempt to integrate multiple filters to estimate the drone position using low computational cost. the IMM switches between the Constant Velocity (CV), Constant Acceleration (CA) and a Constant Turn (CT) model with a Markov Chain in different flight scenario depending on the drone movement. Other filters i.e. Kernelized Correlation Filter (KCF), Particle Filter (PF) and Discriminative Correlation Filter (DCF) models are also presented for direct comparison. © 2021 IEEE.

关键词： Drones

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Prognosis Prediction of Alzheimer's Disease Based on Multi-Modal Diffusion Model

Prognosis Prediction of Alzheimer's Disease Based on Multi-M...

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international conference on Ubiquitous Information Management and Communication (IMCOM)

作者： Siwon Hwang Jitae Shin Department of Electrical and Computer Engineering Sungkyunkwan University Suwon Republic of Korea

Alzheimer's Disease is a complex and currently one of the most prevalent illnesses. Due to these factors there is a growing emphasis on the early diagnosis of Alzheimer's Disease and our approach involves leveraging deep learning techniques to overcome this challenge. In this paper, we introduce a deep learning model designed to predict the progression of Alzheimer's Disease. Our model is based on the diffusion model and utilizes a multi-modal dataset that includes Magnetic Resonance Imaging data (image) and biospecimen data (clinical non-image) associated with Alzheimer's Disease. the proposed model operates through image-to-image translation based on a conditional diffusion process. Our findings validate that our model can generate images that faithfully capture the structural changes in the brains of Alzheimer's patients. Moreover, it outperforms other models according to various evaluation metrics such as PSNR, SSIM, and FID. Additionally, we demonstrate the superiority of a multi-modal dataset over a single modality dataset. We anticipate that the adoption of our proposed model will facilitate the early diagnosis of Alzheimer's Disease, thereby making a significant contribution to the medical field.

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Neural Network-based End-effector Force Estimation for Mobile Manipulator on Simulated Uneven Surfaces 30

Neural Network-based End-effector Force Estimation for Mobil...

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30th international conference on software, Telecommunications and Computer Networks, SoftCOM 2022

作者： Kruxic, Stanko Music, Josip Stancic, Ivo Papic, Vladan University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia

ISBN: (数字)9789532901177

ISBN: (纸本)9789532901177

Mobile robotic manipulators often interact with other robots, humans or the environment in indoor and outdoor scenarios. In many cases, end-effector forces need to be known to give feedback about task completion. the mobile base might be titled due to the uneven surface on which the mobile base is positioned. the paper presents the approach to estimating end-effector forces based on neural networks in such cases. the estimates are inferred based on the force sensor mounted under the robot's base and the knowledge of the tilt angle. the robot's dynamic model does not have to be known since it is learned from data during neural network training. the dataset for this research was obtained in simulation. the angle between the robot and the surface changed to simulate a change in surface slope that a mobile manipulator might encounter during the execution of real-world tasks. the trained neural network shows good performance no matter the angle between the base and the ground. It showed an RMSE of 0.302 N (on the test set). Furthermore, there was no significant difference when comparing RMSE across all test data with test data obtained on a per-angle basis, demonstrating the effectiveness of the proposed approach. © 2022 University of Split, FESB.

关键词： Neural networks

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