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检索条件"任意字段=International Conference on Computer Engineering and Technology"

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Digital Conscience: Investigating the State of Ethics in CS Curricula in India 24

Digital Conscience: Investigating the State of Ethics in CS ...

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20th Annual ACM conference on international Computing Education Research, ICER 2024

作者： Parthasarathy, P.D. Lakshmi, T.G. Indra, R. Spruha, Satavlekar Joshi, Swaroop BITS Pilani KK Birla Goa Campus Goa India Shikha Institute of Education Mumbai India B.M.S. College of Engineering Bengaluru India Indian Institute of Technology Bombay India

ISBN: (纸本)9798400704758

Contemporary computer science graduates enter a world where numerous profound ethical dilemmas confronting society revolve around computing. Navigating the complexities of today's technological landscape requires a profound consideration of ethical questions. Deliberations on the kinds of data to be gathered or avoided, the ethical dimensions of algorithmic decision-making, and the role of digital platforms in safeguarding democratic principles are at the forefront of discussions. Additionally, addressing biases in large language models (LLMs), ensuring responsible AI practices, and evaluating the technology industry's contributions to climate change are pivotal aspects. © 2024 Owner/Author.

关键词： Ethical technology

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Research on the Application of computer Digital Media and Virtual Reality technology 13th

Research on the Application of Computer Digital Media and Vi...

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13th international conference on Frontier Computing, FC 2023

作者： Yang, Min Zhang, Jiajie Shandong Communication and Media College Shandong Jinan250200 China Shandong Technician Institute Shandong Jinan250200 China

ISBN: (纸本)9789819992980

The research will focus on the application of computer digital media and virtual reality technology to support, enhance, improve and promote the learningprocess in various fields. The project is expected to provide a new way for students to learn through the use of computer digital media and virtual reality technology. In addition, it will contribute to the development of Malaysia's education system through its potential as an effective teaching tool. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Digital storage

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Smart City Problem Analysis by Using Design Thinking 8

Smart City Problem Analysis by Using Design Thinking

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Joint 8th international conference on Digital Arts, Media and technology and 6th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2023

作者： Sureephong, Pradorn Kummalue, Komalaporn Chernbumroong, Suepphong Khiawcha-Um, Orathai College of Arts Media and Technology Chiang Mai University ChiangMai Thailand

ISBN: (纸本)9798350396546

The training Course under project 'City Data Planner (CDP)' aimed to facilitate the change of sustainable smart city development. The local governance organization over 70 municipalities around Thailand were involved in the project. Knowledge and comprehension of city data is required to construct smart cities in multiple aspects. The utilization of information and technology to drive local government organizations has the potential to create a viable smart city. The aim of this paper is to survey the requirement of local government organization in order to adopt smart city technology in their workplace. © 2023 IEEE.

关键词： Big data

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Evaluation of jet energy determination in heavy-ion collisions using Machine Learning 2

Evaluation of jet energy determination in heavy-ion collisio...

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2nd international conference on Big Data, Computational Intelligence, and Applications, BDCIA 2024

作者： Zhao, Yangguang Wang, Yuhui Zhou, Yujie Bao, Qihan College of Computer Science and Technology Qingdao University Qingdao266071 China College of Food Science Sichuan Agriculture University Chengdu610000 China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China College of Computer and Information Science Southwest University Chongqing400715 China

ISBN: (纸本)9781510689053

In high-energy physics experiments, the precise reconstruction of the transverse momentum of jets is challenging. The primary obstacle is the interference caused by background noise particles overlapping with the jet and the limitations of the sensors currently being used. A traditional noise reduction method is area-based subtraction, which calculates the mean value of certain events. In previous studies, some noise reduction methods utilizing machine learning techniques have been proposed. In this study, we evaluate the performance of various machine learning models in reconstructing the jet transverse momentum in simulated heavy-ion events, based on Pythia events embedded in a thermal background distribution. The performance of the models at the particle level is compared to that using pseudo-towers of various resolutions in eta, phi to evaluate the impact of the sensor performance limitations. The results demonstrate that as the resolution decreases, the performance of the machine learning models also degrades, but still performs better than the traditional method. This provides a reference for the application of machine learning methods. © 2025 SPIE.

关键词： Heavy ions

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Design and realization of an autonomous dock for unmanned ships 3

Design and realization of an autonomous dock for unmanned sh...

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3rd international conference on Intelligent Mechanical and Human-computer Interaction technology, IHCIT 2024

作者： Liu, Xin Sun, YuHan Zhang, TengWen Shen, ZhengHao Shandong Jiaotong University ShanDong Weihai264200 China Weihai Marine Information Science and Technology Research Institute ShanDong Weihai264400 China

ISBN: (纸本)9781510683105

Addressing the shortcomings in automatic deployment and retrieval as well as long-endurance capability of unmanned surface vessels (USVs) for inland waterways, this study focuses on the small-scale USV "Dolphin" as the research subject. A prototype of a docking station equipped with autonomous deployment/retrieval technology and wireless charging capabilities has been designed and implemented. Finite element analysis and dynamic simulation were employed to verify its feasibility. The results of practical application tests indicate that this prototype can further enhance the application capability and continuous operation time of USVs in complex environments, broadening their application prospects in fields such as marine scientific research, offshore patrols, and maritime rescue. © 2024 SPIE.

关键词： Unmanned surface vehicles

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Logistics Sorting and Transportation System based on McNamum Wheel - Intelligent Manufacturing Professional Training Research 7

Logistics Sorting and Transportation System based on McNamum...

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7th international conference on computer Information Science and Application technology, CISAT 2024

作者： Ning, Lingling Liu, Ranran Shandong University of Engineering and Vocational Technology No.6196 Jingshidong Road Jinan250200 China

ISBN: (纸本)9798350375107

With the arrival of Industry 4.0, under the influence of the international financial crisis, the state proposed to revitalize the equipment manufacturing industry to achieve the transformation of the national economic growth mode. In this paper, an innovative logistics automatic sorting system is developed to improve the degree of automation and efficiency of logistics sorting. The system adopts machine vision technology and McNamum wheel conveyor belt structure to realize high-precision cargo identification and flexible space adaptability. The omnidirectional wheel and OpenMV technology are expected to further enhance the level of logistics automation, expand application scenarios, and achieve a comprehensive upgrade and transformation of the logistics industry through industrial cooperation and technological innovation. This paper analyzes and compares the growth process of students and technicians, constructs the 'three with three integration and three stages' professional group talent training model, and provides a reference training model for related majors and professional groups of equipment manufacturing. © 2024 IEEE.

关键词： Students

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Recognition and Identification of COVID-19 from Chest X-Rays for Earlier Diagnosis 4

Recognition and Identification of COVID-19 from Chest X-Rays...

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4th international conference on Expert Clouds and Applications, ICOECA 2024

作者： Kavitha, P. Sharma, Manish Pradeep Kumar, G.M. Barve, Amit Patil, Harshal Maranan, Ramya CMR Institute of Technology Department of Computer Science and Engineering Karnataka Bengaluru560037 India Graphic Era Deemed to be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India BMS Institute of Technology and Management Department of AI & ML Karnataka Bangalore560064 India Parul Institute of Technology Parul University Faculty of Engineering and Technology Department of Computer Science and Engineering P.O. Limda Gujarat 391760 India Computer Science and Engineering Maharashtra Pune412115 India Saveetha School of Engineering SIMATS Department of Research and Innovation Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350385793

Early detection is critical for controlling the spread and death of the COVID-19 worldwide pandemic, which affects global health care and lifestyle. The gold standard diagnosis, Reverse Transcription Polymerase Chain Reaction (RT-PCR) is both costly and has a lengthy process time. So more readily available and fast diagnostic methods are necessary. Many researchers proved that COVID-19 data can be effectively detected by Chest X-rays (CXR). However, diagnosing chest X-ray images for COVID-19 is difficult and error-prone. The only way to improve the COVID-19 diagnosis is to use DL algorithms. In this research, a novel deep learning model Convolutional Neural Network and Autoencoder (CNN-AE) tuned by Bat Optimization Algorithm (BOA) is proposed. The proposed approach would identify whether the CXR images were positive or negative for COVID. We received the CXR images from Kaggle. The pre-processing phases in the proposed technique assist with providing relevant information and reducing biased outputs. This is followed by the classification model. We were able to evaluate the performance of our proposed model by using Kaggle datasets. Our proposed model is evaluated using Kaggle datasets and achieved an average accuracy, True Positive Rate (TPR), True Negative Rate (TNR), precision, F1-score, False Positive Rate (FPR), and False Negative Rate (FNR) of 99.28%, 99.42%, 99.14%, 99.42%, 99.28%, 0.85%, and 0.57% respectively. The outcome of the proposed method is compared with the existing and similar research. A comparative study shows that our proposed method outperforms the state-of-art methods. © 2024 IEEE.

关键词： COVID-19

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Advancing Virtual Reality Interaction through Real-Time Hand Gesture Recognition for Immersive Experiences 3

Advancing Virtual Reality Interaction through Real-Time Hand...

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3rd international conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Singh, Vinayak Kumar Kalinathan, Lekshmi Marimuthu, Marimuthu Vadivel, Sengazhani Murugesan Palani, Saravanan Vellore Institute of Technology School of Computer Science and Engineering Chennai India VIT Business School Vellore Institute of Technology Chennai India

ISBN: (纸本)9798350372120

Virtual Reality technology offers immersive experiences, but reliance on handheld controllers can limit immersion. This study explores real-time hand gesture recognition to enhance natural interaction in VR environments. Motivated by VR's diverse applications in gaming, education, and training, it seeks to improve engagement and realism. The study provides an overview of current hand gesture recognition techniques, including computer vision and deep learning methods. Understanding the state of real-time gesture recognition informs future research and development in VR interaction. It enables researchers, developers, and practitioners to make informed decisions about integrating and enhancing gesture recognition technologies in various VR applications © 2024 IEEE.

关键词： Virtual reality

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STANet: Spatio-Temporal Attention-Enhanced WaveNet for Crime Hotspot Prediction 15

STANet: Spatio-Temporal Attention-Enhanced WaveNet for Crime...

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15th international conference on Information and Knowledge technology, IKT 2024

作者： Roshankar, Rojan Keyvanpour, Mohammad Reza Data Mining Laboratory Department of Computer Engineering Faculty of Engineering Alzahra University Tehran Iran Department of Computer Engineering Faculty of Engineering Alzahra University Tehran Iran

ISBN: (纸本)9798331522254

An accurate prediction of crime hotspots is critical for optimizing law enforcement strategies and urban planning. In this paper, we introduce STANet, a Spatio-Temporal Attention-Enhanced WaveNet model developed to predict crime hotspots using spatial and temporal crime data. K-Means clustering and advanced data preprocessing techniques are combined in STANet to analyze five years of crime incidents reported in Chicago. In the model, spatial-temporal dependencies are incorporated through WaveNet architecture and enhanced through attention mechanisms in order to capture complex crime patterns more effectively. As a result of our experiments, we are able to demonstrate that STANet outperforms traditional models, such as XGBoost, DNN, and decision trees, with The model achieved an accuracy of 86%, along with precision and recall values that demonstrate a balanced performance in predicting crime hotspots. As a result of this mechanism, the model can identify and focus on the most relevant time steps dynamically, improving its accuracy in predicting the future. STANet can be used to predict hotspots for crime, offering actionable insights for resource allocation and crime prevention. To enhance the predictive capability of the model, further exploration will involve expanding the dataset and incorporating additional features. © 2024 IEEE.

关键词： Resource allocation

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Global Context-Aware Single Object Tracking Algorithm Based on Enhanced Swin-T 7

Global Context-Aware Single Object Tracking Algorithm Based ...

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7th IEEE international conference on computer and Communication engineering technology, CCET 2024

作者： Li, Yang Ren, Pengyu Wang, Yanping Lin, Yun Shen, Wenjie Jiang, Wen Bai, Zechao School of Information Science and Technology North China University of Technology Beijing China

ISBN: (纸本)9798350355673

Single-object tracking based on computer vision facilitates the collection, analysis, and utilization of target information. Currently, the latest single-object tracking algorithms solely rely on the Transformer for feature fusion and matching between the template frame and the search area frame. However, all of the Transformer-based algorithms fail to fully leverage the dynamic encoding capabilities of the Transformer for feature extraction, neglecting the inherent abilities of the Vision Transformer in feature extraction and decoding prediction. To address these issues, we propose a global context-based single-object tracking method with an enhanced tiny Swin Transformer encoder (Swin-T). By leveraging the Swin-T as our backbone network, we are able to extract both local and global information through the use of shifting windows. This approach allows for a more precise representation of the object state, consequently enhancing the accuracy of a single-object tracking system. Through comparative experiments on multiple challenging datasets, our algorithm demonstrates an increase in success rates of 1.9% and 2.8% on the Lasot and UAV123 datasets, respectively, and an improvement of 0.5% in the F-score on the VOT2020LT dataset compared to the benchmark algorithm. © 2024 IEEE.

关键词： Object tracking

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