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

共 8485 条记录，以下是1111-1120 订阅

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Experimental Evaluation of Multiple Multipath Schedulers over Various Urban Mobile Environments 22

Experimental Evaluation of Multiple Multipath Schedulers ove...

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11th international Symposium on Information and Communication Technology, SoICT 2022

作者： Diakhate, Papa Bara Chu, Tran-Tuan Labiod, Mohamed Aymen Augustin, Brice Tran, Hai-Anh Mellouk, Abdelhamid Universite Paris Est Creteil Vitry-sur-SeineF-94400 France Soict Hanoi University of Science and Technology Hanoi Viet Nam

ISBN: (纸本)9781450397254

the use of multiple interfaces and multipath protocols for end-To-end devices, especially in a mobile environment, has recently gained much attention. At the heart of any multipath protocol lies a scheduler, whose ability to select the best path dictates the system's overall performance. While a plethora of schedulers has been proposed so far, their evaluation was only conducted in simulated, static environments. A question remains on their behavior in real-world, dynamic, and mobile conditions. In this paper, we design a framework and conduct various experiments to assess the performance of four state-of-the-Art schedulers for the cutting-edge MPQUIC multipath protocol. Our setup involves mobile situations within an urban area around Paris, France. We first design and implement an MPQUIC-based modular scheduler assessment framework to compare the schedulers. We then take advantage of this framework to measure their performance in real-world scenarios involving multiple transportation modes (train and car). the collected datasets allow us to perform an in-depth analysis to find insights as well as quantify the schedulers' performances. Our experimental results confirm the dominance of the state-of-the-Art learning-based multipath scheduler. © 2022 ACM.

关键词： computer networks

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AttDenseUnet : Segmentation of Polyps from Colonoscopic Images Based on Attention-DenseNet-Unet Architecture

AttDenseUnet : Segmentation of Polyps from Colonoscopic Imag...

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international conference on Wireless Networks and Mobile Communications (WINCOM)

作者： Samira Lafraxo Mohamed El Ansari Lahcen Koutti Zakaria Kerkaou Meryem Souaidi Department of Computer Science LabSIV Faculty of Science Ibnou Zohr University Agadir Morocco Department of Computer Science Informatics and Applications Laboratory Faculty of Sciences Moulay Ismail University Meknès Morocco

ISBN: (数字)9798350377866

ISBN: (纸本)9798350377873

Globally, colorectal cancer is the primary cause of cancer-related death. Colonoscopy is currently one of the most common ways to identify precancerous gastrointestinal disorders. thus, early and precise polyp segmentation is of therapeutic importance in reducing the risk of developing cancer. the manual examination is a tedious and time-consuming procedure for physicians. Many computer algorithms have been created by scientists to automatically identify problems from colonoscopic images. In order to further increase polyp segmentation performance, we provide in this study an attDenseU-Net design that concurrently includes the attention mechanism and U-Net. AttDenseU-Net reduces the amount of background in an input image while emphasizing key components by inserting a sequence of attention units in between relevant downs amp ling and upsampling operations. Integrating DenseNet blocks into U-Net architecture helps to more effective and efficient feature learning, and improved gradient flow. A publicly available dataset called K vasir-SEG was utilized in this study to evaluate and confirm the proposed approach. Our model's accuracy rate is 86.31 %, its Dice coefficient is 91.48%, and its Jaccard index is 84.30 %. the experiment findings show that the proposed AttDenseU-Net outperforms its baselines and provide s performance on par with existing polyp segmentation methods.

关键词： Representation learning Image segmentation Wireless networks Semantics computer architecture Medical services Manuals

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11th international conference on Cross-Cultural design, CCD 2019, held as part of the 21st international conference on Human-computer Interaction, HCI international 2019

11th International Conference on Cross-Cultural Design, CCD ...

引用

11th international conference on Cross-Cultural design, CCD 2019, held as part of the 21st international conference on Human-computer Interaction, HCI international 2019

ISBN: (纸本)9783030225797

the proceedings contain 80 papers. the special focus in this conference is on Cross-Cultural design. the topics include: User Experience in Older Adults Using Tablets for Neuropsicological Tests in Mexico City;parallel Orientation Assistant, a Vehicle System Based on Voice Interaction and Multi-screen Interaction;Can Virtual Reality Satisfy Entertainment Needs of the Elderly? the Application of a VR Headset in Elderly Care;cross-Cultural Recycling and design Methodology;to Prove the Effectiveness of the three-Stage design Method of Cross-Cultural Recycling "Why-What-How";mobility-as-a-Service: A Critical Review and the Generalized Multi-modal Transport Experience;design for Urban Resilience: A Case of Community-led Placemaking Approach in Shanghai China;"We Are Actively Reaching Out to Different Organizations and Folks to Come in": Collective design of the Vancouver Tool Library Project;urban Interaction design Supports Modular design Practice for Urban Public Space;city Change Maker: A design Innovation Workshop on Social Impact;museum and Cultural Products Co-creation Brand Value: Taking the Innovative Cultural Products of Ningbo Port Museum as an Example;a Comparison of Critical Time Interval Between Young and Old Subjects;qianLi: A Modular System for Connecting Distant Family Members through Tacit Interaction;the Vibrotactile Experience of the HOME Button on Smartphones;a Study of Japan’s Welfare Beauty Service from Cultural Creative’s Perspective;what Do Users like About Smart Bottle? Insights for designers;business Practice of Service design in New Retail Era in China;attempts to Leverage Interaction design to Mimic Emotional Care and Empathy-Based Feedback on Smart Speakers;luxury Industry’s Chinese User Experience design.

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A Comprehensive Review of Image Segmentation Architectures

A Comprehensive Review of Image Segmentation Architectures

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international conference on Electrical Engineering, computer Science and Informatics (EECSI)

作者： Chandana Mohan G.M. Arundhati R Caren Laurette Adithi Sabu Jerrin thomas Panachakel S. P. Anusha Dept. of Elect. and Comm. Engg. College of Engineering Trivandrum India Dept. of Civil Engg. College of Engineering Trivandrum India

ISBN: (数字)9798350355314

ISBN: (纸本)9798350355321

Semantic segmentation, the task of assigning class labels to each pixel in an image, is fundamental to numerous computer vision applications. this review paper critically analyzes six prominent segmentation architectures: Fully Convolutional Networks (FCN), U-Net, DeepLab, YOLO, SegNet, and Mask R-CNN, with evaluations primarily based on mean Intersection over Union (IoU) scores on the COCO dataset. FCN initiated the development of end - to-end trainable models for pixel-wise classification. U-Net's symmetric encoder-decoder architecture with skip connections has proven highly effective in biomedical image segmentation. DeepLab variants utilize atrous convolutions to enhance dense prediction tasks. YOLO, primarily recognized for real-time object detection, also supports segmentation with a balance of speed and accuracy. SegNet's straight-forward design and computational efficiency make it ideal for resource-constrained environments. Mask R-CNN extends Faster R-CNN by integrating instance seg-mentation with object detection. Performance evaluations reveal mean IoU scores as follows: FCN (0.35-0.55), U-Net (0.50-0.70), DeepLab (0.60-0.80), YOLO (0.55-0.65), SegNet (0.40-0.60), and Mask R-CNN (0.60-0.80). this review provides insights into the strengths, limitations, and application domains of these architectures, assisting researchers and practitioners in selecting appropriate models for specific segmentation tasks.

关键词： YOLO Performance evaluation Electrical engineering computer vision Accuracy Reviews Semantic segmentation computer architecture Real-time systems Informatics

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Retrainable Hand Gesture Recognition Model Driven by Edge AI

Retrainable Hand Gesture Recognition Model Driven by Edge AI

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international conference on Dependable Systems and their Applications (DSA)

作者： Tse-Chuan Hsu Dong-Meau Chang Department of Computer Science & Information Management Soochow University Taipei Taiwan School of Computer Science and Intelligence Education Lingnan Normal University China

ISBN: (数字)9798331532390

ISBN: (纸本)9798331532406

Based on computer vision and machine learning, accurate hand behavior and gesture recognition are crucial, especially for missing or incomplete hand models. Finger joint point prediction technology is of great value for applications such as virtual reality and human posture recognition. However, hand joint point prediction models, such as Google’s MediaPipe, perform well in full-finger models but are ineffective in missing-finger situations. Missing fingers are familiar in clinical medicine, rehabilitation facilities, and unique scenarios such as hand injuries or congenital hand deformities. Accurate prediction of hand joints is critical for hand rehabilitation, prosthetic design, and human motion analysis and inspires the development of related technologies. Since traditional prediction models rely on complete hand data, and missing fingers can make the hand structure irregular, the complexity of prediction increases. this study proposes an improved prediction model focusing on hand joint point prediction in the case of missing fingers, hoping to improve prediction accuracy and provide valuable reference for future applications and research. Among the research results, we successfully integrated the new training image model with MediaPipe, significantly improving missing fingers’ prediction accuracy.

关键词： Hands Training Solid modeling Adaptation models Accuracy Computational modeling Gesture recognition Virtual reality Predictive models Data models

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We're too busy singing: acoustic analysis with apes 24

We're too busy singing: acoustic analysis with apes

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11th international conference on Animal computer Interaction

作者： French, Fiona Good, Stephen Makaddem, Karim Frost, Naomi Finch, Katherine London Metropolitan Univ Sch Comp & Digital Media London England London Metropolitan Univ London England Twycross Zoo Leicester Leics England

ISBN: (纸本)9798400711756

this project focuses on novel methods for investigating auditory perception and associated environmental enrichment of great apes in managed scenarios. Research outputs can inform animal husbandry and the design of human and animal infrastructures in both managed and wild environments. this is a report from the start of the project, explaining the motivation for the research and demonstrating the utility of soundscape analysis for identifying anthropogenic noise that potentially impacts great ape welfare, natural behaviours and communication strategies. At this early stage, technology is being used to passively monitor acoustic signals in the environment and subsequently support the analysis of recordings, using visualisation techniques to reveal patterns and identify sound sources. Initial findings demonstrate that the fundamental frequency of gorilla low growls fall in the range of 150 to 200 Hz, with subharmonics as low as 30 Hz, just on the edge of human hearing. Ultimately, we are planning a deeper investigation of auditory perception, by developing interactive devices that offer agency to non-humans and enable us to find out more about the hearing capabilities of different species.

关键词： environmental acoustics acoustic monitoring great ape gorilla perception environmental enrichment animal-computer interaction

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Analysis and design Optimization of Surface Permanent Magnet Motor to Improve Torque Density and Ripple

Analysis and Design Optimization of Surface Permanent Magnet...

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international conference on Power Electronics (ICPE)

作者： Yussuf Shakhin Kulash Talapiden Nguyen Gia Minh thao Mehdi Bagheri Ton Duc Do Department of Robotics and Mechatronics School of Engineering and Digital Sciences (SEDS) Nazarbayev University Astana Kazakhstan Graduate School of Engineering Toyota Technological Institute Japan Department of Electrical and Computer Engineering School of Engineering and Digital Sciences (SEDS) Nazarbayev University Astana Kazakhstan

Small-scale permanent magnet motor to reach high torque density and low torque ripple is discussed in this research. To increase the torque density, meanwhile making the motor size smaller and lighter, the motor axial length within a constrained diameter is optimized in view of various pole-slot configurations. Different slot-poles are selected and various combinations are studied, and the stator windings are optimized. To compare the torque density and ripple of new designs, precise models are created and simulated through ANSYS Maxwell 2D FEA under constant operational conditions, such as rated speed, torque, and power. Over the new designs, the influence of loss and temperature distribution variations in motor elements are analyzed. the simulation results show that the proposed 20-pole 18-slot motor design will obtain superior torque density and lower torque ripple compared to the baseline design. the final design provides a 30.7 % improvement of the torque density within the same rated torque condition.

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IoT based on Membrane Computing Models 11

IoT based on Membrane Computing Models

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11th international conference on Electromechanical and Energy Systems, SIELMEN 2021

作者： Victor, Ababii Viorica, Sudacevschi Silvia, Munteanu Olesea, Borozan Ana, Nistiriuc Victor, Lasco Technical University of Moldova Computer Sciences and Systems Engineering Dep. Chisinau Moldova

ISBN: (纸本)9781665400787

In the given paper it is approached a method of the application of the Membrane Computing models in the design of IoT systems with Collective Intelligence properties. the topology of the IoT system is presented as a Mesh network that ensures a total interconnection of its devices. the Collective Intelligence definition model presents a Hopfield Neural Network based on the set of knowledge consisting of data and their processing models. the following were elaborated: cell structure, cell interaction diagram and the manner of formation of hierarchical structures and of Collective Intelligence. the synthesis process of an IoT system on the basis of Membrane Computing models with Collective Intelligence properties is presented by the sequence of operations that begins with the definition of the mathematical model and ends with the development of the structure of the IoT system on the basis of the programmable devices ESP8266. © 2021 IEEE.

关键词： Hopfield neural networks

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Towards a Metamorphic Testing Architecture for Software-Defined Drone Systems

Towards a Metamorphic Testing Architecture for Software-Defi...

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international conference on Software Defined Systems (SDS)

作者： Erik M. Fredericks Mallory Jacobs Byron DeVries College of Computing Grand Valley State University Allendale MI USA

ISBN: (数字)9798331518325

ISBN: (纸本)9798331518332

Safety-critical systems, such as drones, are vulnerable to effects of uncertainty, where uncertainty can manifest as adverse weather conditions, unexpected human interactions, and misconfigured system settings. Moreover, it is humanly infeasible to test for all possible combinations of conditions that a system may experience through its lifetime during design. Additionally, drones are difficult to exhaustively test prior to deployment as real-world validation is costly in terms of time and equipment. Search-based testing is an approach for discovering new situations that a system may experience, however such tests can suffer from automatically inferring incorrect expected values/outcomes without domain knowledge (i.e., the oracle problem). As such, we propose a metamorphic testing framework for software-defined drone systems that uses exploratory search and aims to minimize the oracle problem at both design time and run time. We demonstrate our framework through a motivating example that illustrates each step of the process.

关键词： Uncertainty computer architecture Search problems Software Drones Testing Meteorology

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design and Implementation of RDMS Platform Intelligent Inspection System in Changqing Oilfield 11th

Design and Implementation of RDMS Platform Intelligent Inspe...

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11th international Field Exploration and Development conference, IFEDC 2021

作者： Jiao, Yang Li, Liang Yao, Weihua Yang, Zhuo Research Institute of Exploration and Development Changqing Oilfield Company Shaanxi Xian710021 China

ISBN: (纸本)9789811921483

In the process of producing 60 million tons in Changqing Oilfield, the platform of reservoir decision-making system (RDMS) plays an important supporting role. In order to ensure the normal operation of the platform, several administrators regularly test and inspect the functions of the platform every day, which takes about 2 h. there are some outstanding problems, such as heavy workload of operation and maintenance and poor pertinence of inspection. In this paper, an intelligent inspection system is designed to replace manual operation. Based on data mining, process automation and computer vision technology, an accurate inspection system is constructed, which focuses on hot function analysis, simulated manual operation and running state inspection. the operation results show that the system can quickly and effectively identify the operation status of the platform function, and has good application value in the operation and maintenance management of similar scientific research information platform. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Data mining

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