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检索条件"任意字段=9th International Conference on Computer Aided Design and Computer Graphics"

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design and Fabrication of Bengali Braille Embosser Using Solenoid

Design and Fabrication of Bengali Braille Embosser Using Sol...

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international conference for Convergence of Technology (I2CT)

作者： Reshad Ibn Momin Ratan Kumar Das Sourav Raxit Umme Salma Muna Abdullah Al Miraj Dept. of Mechanical & Electrical Engineering University of Southern Denmark-SDU Sønderborg Denmark Dept. of Mechanical Engineering Chittagong University of Engineering & Technology Chattogram Bangladesh Department of Computer Science University of New Orleans United States Dept. of Computer Science & Engineering American International University Dhaka Bangladesh Dept. of Electrical & Electronic Engineering Chittagong University of Engineering & Technology Chattogram Bangladesh

ISBN: (数字)9798350394474

ISBN: (纸本)9798350394481

this paper presents the design and development of a low-cost and user-friendly Bengali braille embosser for the visually impaired population in Bangladesh. To produce braille text, the embosser employs a shifting mechanism and an Embosser head, both controlled by an Arduino microcontroller. A software has also been developed to allow users with basic printer knowledge to operate the embosser. Access to educational resources and reading materials is limited for people with disabilities in Bangladesh, and the availability of Bengali braille writing machines is scarce. the proposed solution aims to address these challenges and improve the learning and communication capabilities of visually impaired individuals.

关键词： Fabrication Braille Microcontrollers Sociology Motors Software Magnetic heads

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Accelerating Multi-Object Tracking in Edge Computing Environment with Time-Spatial Optimization 9

Accelerating Multi-Object Tracking in Edge Computing Environ...

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9th international conference on Advanced Cloud and Big Data, CBD 2021

作者： Liu, Mengyang Tang, Anran Wang, Huitian Shen, Lin Chang, Yunhan Cai, Guangxing Yin, Daheng Dong, Fang Zhao, Wei School of Computer Science and Engineering Southeast University Nanjing China School of Computer Science and Communication Engineering Jiangsu University Zhenjiang China Institute for Artificial Intelligence Comprehensive National Science Center Hefei China School of Computer Science and Technology Anhui University of Technology Ma'anshan China

ISBN: (纸本)9781665407458

Multi-Object Tracking (MOT) task is a key issue in computer vision. It has capacious application prospects in survelliance, self-driving, and augmented reality. Benefit from the continuous progress of Deep Neural Network (DNN), the accuracy of the MOT algorithm has been significantly improved. Nevertheless, limited to computing power, achieving real-time DNN-based MOT is difficult in embedded systems. In reality, there are many wasteful and unnecessary computations in traditional frame-by-frame full-size video analysis. therefore, in this paper, we propose a strategy that optimizing the execution of a traditional MOT pipeline in the dimension of time and space. In the temporal dimension, DNN only works in periodic keyframes while using a lightweight model for quickly generating results in the common frames. In the spatial dimension, we design an image density region discriminator to narrow down the input size of DNN. An edge device is introduced to perform end-edge collaborative computing to further accelerating the execution. Additionally, an end-edge parallel computing mechanism is designed that performing dynamic decisions based on the computing power and network environment between end and edge. Moreover, we rebuild the DNN model by TensorRT to optimize the model structure of DNN. By integrating the above approaches, the system can achieve 17.6 ~ 38.1 × speedup ratio, while with 3%~10.4% absolute tracking accuracy sacrifice and can be deployed in an unstable network environment. © 2022 IEEE.

关键词： Deep neural networks

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A new matrix method to innovation 9th

A new matrix method to innovation

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9th international conference on Information Technology and Quantitative Management, ITQM 2022

作者： Li, Hangzhou Ma, Minjin Zhao, Zhenzhu Ma, Yuzhan College of Nuclear Science and Technology Lanzhou University Lanzhou730000 China College of Atmospheric Sciences Lanzhou University Lanzhou730000 China Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia

A new method of constructing a two-dimensional demand matrix is proposed by design of products from perspectives of the products characteristics and requirements at the same time. Taking characteristics of the products as the matrix elements, the demand matrix is constructed for cross innovation in different demand fields. through analysis, variation, migration and reorganization of the characteristics points, the application of technical principles in the new field are realized to perform a new product innovation. the establishment and application of the demand matrix are demonstrated by a case of the dry powder extinguisher. Finally, the paper discusses differences between the demand matrix method and the cutting and function-oriented search in TRIZ, differences and relationships with the extension innovation, and points out the advantages of the application of the demand matrix method. © 2022 the Authors. Published by Elsevier B.V.

关键词： Product design

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Digital Nudge Evaluation on COVID-19 tracing Application 9

Digital Nudge Evaluation on COVID-19 tracing Application

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9th international conference on Information and Communication Technology, ICoICT 2021

作者： Sukmaningsih, Dyah Wahyu Abdurachman, Edi Purwandari, Betty Trisetyarso, Agung Bina Nusantara University BINUS Graduate Program-Computer Science Computer Science Department Jakarta Indonesia Faculty of Computer Science Universitas Indonesia Depok Indonesia

ISBN: (纸本)9781665404471

Nudge is considered as an intervention to change user behavior and influence decision-making. Mobile apps have become a part of our everyday life. In this pandemic era, governments use mobile apps' technology to control the spread of COVID-19 infection. Many governments implemented COVID-19 tracing apps, and citizens are forced to use the apps to record their contact tracing and alert them if they have contact with an infected person. the key to control the increasing spread of the virus also depends on citizens adhere to health protocol. Government has experience difficulty in enforcing the protocol without strict surveillance. therefore, building awareness of risk is essential-this study attempt to design nudge intervention into COVID-19 tracing apps. From the evaluation of the original apps, four nudge interventions can be applied in the application. © 2021 IEEE.

关键词： COVID-19

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Intelligent Scheduling of Serverless Computing in Computing Power Networks

Intelligent Scheduling of Serverless Computing in Computing ...

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international conference on computer and Communications (ICCC)

作者： Bowen Liu Xiaochen Liang Guiyu Zhang Jichun Ma Minkuan Li Anqi Zhou Qinqin Tang Kailai Peng Renchao Xie China Information Technology and Telecommunication Consulting Design Institute Beijing University of Post and Telecommunications Beijing PR. China State Key Lab. of Networking and Switching Technology Beijing University of Post and Telecommunications Beijing PR. China Purple Mountain Laboratories Nanjing China

In the rapidly evolving landscape of computing power networks, applications are becoming more complex and diverse. Consequently, this evolution has led to a growing need for sophisticated intelligent scheduling mechanisms to adeptly manage these networks. Utilizing intelligent algorithms has become pivotal in ensuring effective and reliable computational services for these intricate networks. this paper addresses the pressing issue of intelligent scheduling in serverless computing power networks. We explore a computing power network system model based on serveless computing, formulate the intelligent task scheduling problem as a multi-objective optimization problem, present a solution that designs task scheduling policies using the Deep Deterministic Policy Gradient (DDPG) algorithm from reinforcement learning. Additionally, we perform experiments to validate the practicality and effectiveness of our proposed approach.

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Research on Multi-Source Data Fusion Method under the Background of Unified Real Estate Registration 9

Research on Multi-Source Data Fusion Method under the Backgr...

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9th IEEE international conference on computer Science and Network Technology, ICCSNT 2021

作者： Cui, Jian Zhu, Mingshui Luan, Yongqiang Zheng, Wei Mi, Hongzhi School of Survey And Geo-Informatics Shandong Jianzhu University Jinan China Jinan Geotechnical Lnvestigation And Surveying Institute Jinan China Academy of Urban Planning And Design Tong Yuan Desing Group CO.LTD Jinan China

ISBN: (纸本)9781665443647

In-depth analysis and discussion of the integration methods in the implementation of the unified registration of real estate can better provide effective data protection for the real estate management department. Taking the land data and real estate data involved in real estate registration as an example, this paper discusses the process and method of standardized integration by analyzing the problems existing in data integration, and realizes the standardization and unification of multi-source data integration through the integration of land data and real estate data. At the same time, the data batch processing model constructed based on the Model-Builder provided by ArcGIS realizes the batch automatic processing of real estate data integration, improves the efficiency of data integration and storage, and lays a solid foundation for the unified registration data integration and storage of real estate. © 2021 IEEE.

关键词： Data integration

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9th international conference on HCI in Business, Government and Organizations, HCIBGO 2022 Held as Part of the 24th HCI international conference, HCII 2022

9th International Conference on HCI in Business, Government ...

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9th international conference on HCI in Business, Government and Organizations, HCIBGO 2022 Held as Part of the 24th HCI international conference, HCII 2022

ISBN: (纸本)9783031055430

the proceedings contain 39 papers presendted at a virtual meeting. the special focus in this conference is on HCI in Business, Government and Organizations. the topics include: COVID-19 AI Inspector;Online Shopping During COVID-19: A Comparison of USA and Canada;design and Implementation of a Collaborative Idea Evaluation System;electronic Performance Monitoring: Review of theories, Conceptual Framework, and Study Proposal;designing a Workplace Violence Reporting Tool for Healthcare Workers in Hospital Settings;evaluation of the Change in the Quality of Reports with the Application of Gamification in a Corporative Institution;developing Personas for designing Health Interventions;Attracting Future Students’ Attention by an UX-Optimized Website;holistic Approach to the Social Acceptance of Building Information Modelling Applications;factors that Influence Cookie Acceptance: Characteristics of Cookie Notices that Users Perceive to Affect their Decisions;a Survey-Based Study to Identify User Annoyances of German Voice Assistant Users;Easy Hand Gesture Control of a ROS-Car Using Google MediaPipe for Surveillance Use;user-Centered Assembly Knowledge Documentation: A Graph-Based Visualization Approach;China’s CO2 Emissions Interval Forecasting Based on an Improved Nonlinear Fractional-Order Grey Multivariable Model;building a "Corpus of 7 Types Emotion Co-occurrences Words" of Chinese Emotional Words with Big Data Corpus;predicting the Usefulness of Questions in Q&A Communities: A Comparison of Classical Machine Learning and Deep Learning Approaches;the Corpus of Emotional Valences for 33,669 Chinese Words Based on Big Data;the Economic theoretical Implications of Blockchain and Its Application in Marine Debris Removal;explore the Influence of Smart Contract on Online Lending;better Decision-Making through Collaborative Development of Proposals.

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Bridging the Gap: Knowledge Spaces and Storylines in Serious Games 9th

Bridging the Gap: Knowledge Spaces and Storylines in Seri...

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9th Joint international conference on Serious Games, JCSG 2023

作者： Brabänder, Wolfgang F. Göbel, Stefan Technical University of Darmstadt Darmstadt64289 Germany

ISBN: (纸本)9783031447501

In this paper, we propose a novel method for simplifying the design of adaptive educational games by integrating Knowledge Space theory (KST) with real- and/or build-time knowledge space alterations based on a story model and player progress. Our approach streamlines the design process by providing a more manageable learning experience for players, facilitating collaboration among game designers, educators, and narrative designers, and enhancing the overall effectiveness of serious games. By combining build-time and real-time adaptation techniques, our method enables dynamic learning experiences that maintain an engaging narrative structure while ensuring that the game remains focused on its learning objectives. We discuss the implications, potential benefits, and limitations of our approach, and provide an example of its application in the development of a vocational training serious game for teaching IT-security at the workplace. Future research directions include the evaluation of the adaptivity and learning engagement of players, as well as exploring more complex adaptations and additional educational fields. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Game design

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Graph Neural Networks for Drug Response Prediction

Graph Neural Networks for Drug Response Prediction

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international conference on Systems and Informatics (ICSAI)

作者： Jiehuang Zhu Xianfeng Liu Jin Zhang Sheng Wu College of Information and Computer Engineering Hunan Normal University Changsha China School of Computer and Communication Engineering Changsha University of Science and Technology Changsha China

Drug response prediction plays a crucial role in precision medicine, such as cancer analysis and treatment. Due to the uncertainty of drug efficacy and the heterogeneity of cancer, predicting drug response in vitro is expected to assist in guiding anticancer drug design and understanding cancer biology. Based on the Genomics of Drug Sensitivity in Cancer (GDSC) and the Cancer Cell Line Encyclopedia (CCLE), we propose a deep learning method for predicting drug sensitivity. Specifically, we first construct graphs of drugs and cell lines in the benchmark dataset. And we design a drug feature extraction module based on Graph Transformer and a cell line feature extraction module based on Graph Attention Networks (GAT) to capture the embeddings of drugs and cell lines. Finally, we feed the drug embeddings and cell line embeddings into the module for prediction. Experiment results show that our method outperforms several advanced models in drug response prediction, demonstrating the good performance and enormous application potential in precision medicine. In addition, the results of ablation experiments demonstrate the effectiveness of the modules in our model.

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Graph-aided Multivariate Signal Decomposition

Graph-Aided Multivariate Signal Decomposition

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international conference on Frontiers of Signal Processing (ICFSP)

作者： Mojtaba Nazari Anders Rosendal Korsh⊘j Naveed ur Rehman Electrical and Computer Engineering Aarhus University Aarhus Denmark Neurosurgery Aarhus University Hospital Clinical Medicine Aarhus University Aarhus Denmark

ISBN: (数字)9798350353235

ISBN: (纸本)9798350353242

this work addresses the challenge of decomposing time-varying graph signals into their constituent amplitude- and frequency-modulated components while inferring their dynamic functional connectivity structures, known as graph mode decomposition (GMD). the existing method within the graph signal processing (GSP) framework yields static connectivity structures, limiting its real-life applicability and relying heavily on the user-defined parameter of the total number of existing modes in the signal K. We present a novel method to overcome these limitations, offering dynamic multi-scale connectivity structures and amplitude-frequency components. the approach formulates a variational optimization problem, integrating a prior for time-varying edge weights, and employs a successive scheme for optimization, eliminating the need for a priori specification of the number of components K. the performance of the method is validated on both synthetic and real datasets.

关键词： Time-frequency analysis Limiting Optimization Signal resolution

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