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

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Research on intelligent monitoring and quality control of BIM technology based on computer vision in the construction process of villages and towns 3

Research on intelligent monitoring and quality control of BI...

引用

3rd international conference on Algorithms, Network, and Communication technology, ICANCT 2024

作者： Cao, Zhifang Guangdong Innovative Technical College Guangdong Dongguan523960 China

ISBN: (数字)9781510688902

ISBN: (纸本)9781510688896

In the field of construction, the application of Building Information Modeling (BIM) technology combined with computer vision offers a promising avenue for enhancing the quality control and intelligent monitoring of village and township construction projects. This paper introduces a novel approach that integrates BIM with advanced computer vision algorithms to automatically detect construction anomalies and assess quality in real time. Through this integration, the research deploys an experimental system across various construction phases, employing it to monitor adherence to BIM models and identify deviations. The findings reveal a significant improvement in error detection accuracy, substantially reducing the reliance on manual inspections and associated costs. Moreover, the system effectively provides project managers with continuous feedback and insights, thereby streamlining decision-making processes and ensuring compliance with construction standards. Conclusively, this research demonstrates the potential of combining BIM and computer vision technologies to revolutionize construction management practices, marking a step forward in the pursuit of more efficient and high-quality construction processes. © 2025 SPIE.

关键词： Building Information Model

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Research on Decision Optimization Based on Big Data Analysis and Calculation

Research on Decision Optimization Based on Big Data Analysis...

引用

2024 international conference on Electrical Drives, Power Electronics and engineering, EDPEE 2024

作者： Qiu, Zhilin School Of Mathematics And Statistics Guangdong University Of Technology Guangzhou China

ISBN: (纸本)9798350395631

This paper uses big data analysis technology to analyze the existing data, reveal the patterns and laws behind the data, and extract valuable information from the data types. And based on historical data, a prediction algorithm is constructed, and the prediction results are calculated by computer to predict the future trend. Finally, make an optimal decision based on the results of big data analysis and prediction. © 2024 IEEE.

关键词： Big data

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To Enhance the Security System of Mobile Phones by Using GSM technology

To Enhance the Security System of Mobile Phones by Using GSM...

引用

2024 international conference on Advances in Computing Research on Science engineering and technology, ACROSET 2024

作者： Mangal, Mayank Tiwari, Gagan Malviya, Kanchan Sahu, Vivek Pathare, Kalpesh Vaidya, Kaustubh Computer Engineering Alamuri Ratnamala Institute of Engineering & Technology Mumbai India Alamuri Ratnamala Institute of Engineering & Technology Department of Computer Science & Engineering Mumbai India

ISBN: (纸本)9798350388800

Nowadays to interconnect with the world, smart phones become an important part of our life, smart phones help us in various ways like keeping lots of important application and data. Using this we can store contacts messages photos videos. But what if you forget your phone at home when you go to work? You might need to make an urgent call, but you don't have the number memorized. So, this model is an Offline mobile device security method based on SMS. Which help to overcome this problem. This paper offered a comprehensive suite of features accessible via text message commands. It empowered users to remotely control their devices, facilitating tasks such as retrieving contact information, locating the device, changing the sound profile, and even ring the phone, and all without the need for internet access. This proposed model aimed to bridge the gap in mobile security by providing a robust offline solution that surpassed traditional online methods. Through these innovations, the model aimed to safeguard users' mobile devices and mitigate the risks associated with loss or theft. © 2024 IEEE.

关键词： Smartphones

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Recurrent Neural Network-Based Dynamic Cooling Adjustment for Energy-Efficient Air Conditioning with IoT Sensors 1

Recurrent Neural Network-Based Dynamic Cooling Adjustment fo...

引用

1st international conference on Innovations in Communications, Electrical and computer engineering, ICICEC 2024

作者： Sujatha, V. Shanthi, S. Juliet, P. Sudha Muthumarilakshmi, S. Latha, N. Mohankumar, N. Shree Sathyam College of Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu Salem India Care College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Tiruchirappalli India Meenakshi College of Engineering Department of Electronics and Instrumentation Engineering Tamil Nadu Chennai India Chennai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamil Nadu Chennai India Symbiosis Institute of Technology Nagpur Campus Maharashtra Pune India

ISBN: (纸本)9798350376517

This research introduces a novel approach to the problem of air conditioning (AC) system energy efficiency. It presents a dynamic method for cooling control by combining recurrent neural networks (RNNs) with Internet of Things (IoT) sensors. The suggested approach uses real-time environmental data collected by IoT sensors, in contrast to traditional systems that stick to static cooling schedules. To predict the best cooling parameters, RNNs examine this data in conjunction with past trends. The AC system may adjust the amount of cooling it provides in response to the current weather. This adaptive technique reduces energy use while simultaneously increasing comfort. By comparing the suggested technique to more conventional ones, experimental validation shows that it is effective and results in significant energy savings. This technology has the potential to improve the efficiency and longevity of AC systems in a wide variety of settings, according to the results. This study makes a significant contribution to the continuous quest for energy-efficient Heating, Ventilation, and Air Conditioning (HVAC) system solutions by integrating advanced neural network modeling with novel IoT technologies. © 2024 IEEE.

关键词： Air conditioning

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High-efficiency feature representation based lightweight reconstruction neural network for image compressive sensing 3

High-efficiency feature representation based lightweight rec...

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3rd international conference on Electronic Information engineering, Big Data, and computer technology, EIBDCT 2024

作者： Liu, Qiuyan Yang, Chunling School of Electronic and Information Engineering South China University of Technology Guangzhou China

ISBN: (纸本)9781510680449

Compressive sensing reconstruction has a great significance for limited sampling resources. The reconstruction methods combining iterative optimization with deep learning gain favorable development. However, many existing methods are inefficient in the feature representation due to the equal computating resource distribution between reconstruction phases and have a problem of a large number of parameters. In this paper, we propose a new scheme of expanding the reconstruction phase's subnet width with the depth increasing and design a high-efficiency feature representation based lightweight reconstruction neural network (HEFRNet) for image compressive sensing. Firstly, we introduce an incremental feature map generation subnet with the processing of intrinsic feature maps in inter-phase. Secondly, We design a multidimensional optimization subnet in intra-phase to update and optimize the feature maps. The experiments indicate that HEFRNet has significant advantages in parameters and the effect of image reconstruction. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Compressed sensing

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Ship detection in optical remote sensing images based on YOLOv7 3

Ship detection in optical remote sensing images based on YOL...

引用

3rd international conference on Electronic Information engineering, Big Data, and computer technology, EIBDCT 2024

作者： Wang, Chuangling Li, Qiming College of Information Engineering Shanghai Maritime University Shanghai China

ISBN: (纸本)9781510680449

Target detection technology based on optical remote sensing images has been widely used in military and civil fields, but there is still a problem of low detection rate due to blurred targets that are too small. An improved algorithm based on YOLOv7 is proposed. First, the Efficient Decoupled Head with privacy learning mechanism is improved to improve the detection accuracy. Secondly, the Normalized Wasserstein Distance loss function is used to solve the problem of targets that are too small and difficult to detect. Finally, the PConv convolution in FasterNet is used to redesign the four ELEN modules in the BackBone structure. Experimental results show that the mAP (0.5) of the improved algorithm increased from 92.8% before improvement to 98.2%, an increase of 5.4%, and can be effectively used for the ship detection in optical remote sensing images. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Optical remote sensing

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Privacy-Preserving Techniques for IoT Data Sharing 9

Privacy-Preserving Techniques for IoT Data Sharing

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9th international conference on Science, technology, engineering and Mathematics, ICONSTEM 2024

作者： Karthikeyan, P. Teotia, Shashiraj Pawan, Toralkar Reena, B. Ardly Melba Vibhakar, Chirag Kalai Priya, V. Velammal College of Engineering And Technology Department of Electronics And Communication Engineering Tamil Nadu Madurai625009 India Swami Vivekanand Subharti University Department of Computer Application Meerut250005 India Madanapalle Institute of Technology & Science Department of Artificial Intelligence Andhra Pradesh Madanapalle517325 India Saveetha University Department of Computer Science And Engineering Tamil Nadu Chennai600124 India Gujarat Power Engineering &. Research Institute Mevad Mehsana Gujarat Technological University Department of Electrical Engineering Gujarat Ahmedabad382710 India Rmk College of Engineering And Technology Department of Computer Science And Engineering Tamil Nadu Puduvoyal601206 India

ISBN: (纸本)9798350365092

In aperiod dominated by the Internet of Effects (IoT), the sharing of data has become an integral aspect of technological advancements. still, the ubiquitous nature of IoT raises significant enterprises regarding stonerse questration. Thisexploration paper delves into innovatives equestration conservingwaysacclimatized for securing the sharing of IoT-generated data. The explores cryptographic protocols, anonymisation strategies, and decentralized fabrics toguard sensitive information while easing meaningful data exchange. Addressing the contradiction between datamileage and individuals equestration, the paper proposes new methodologies that intricately balance the need for dataparticipation with the imperative tocoverstoner confidentiality. By introducing a comprehensive analysis of sequestration-conserving mechanisms with in the IoT eco system, this exploration contribute sprecious perceptivity to the ongoingconverse on securing the digitalgeography. The findings offer a foundation for developing robustfabrics that harmonize the imperatives of dataparticipating with the consummatesignificance of securing stoner sequestration in the expanding realm of Io'Toperations. © 2024 IEEE.

关键词： Privacy-preserving techniques

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Extending Scratch Framework to Improve the Analytical Skills of Undergraduate Students 24

Extending Scratch Framework to Improve the Analytical Skills...

引用

10th international conference on computer technology Applications, ICCTA 2024

作者： Akbar, Ubaid Ul Akbar, Saeed Ali, Mumtaz Ullah, Rahmat Khan, Rizwan Lopes, Ivandro Ortet Department of Computer Science City University of Science and Information Technology Peshawar Pakistan School of Computer Science and Technology Zhejiang Normal University Jinhua321004 China School of Computer Science and Electronic Engineering University of Essex United Kingdom School of Cyber Science & Engineering Huazhong University of Science & Technology Wuhan China

ISBN: (纸本)9798400716386

Scratch is an innovative and the most popular block-based Visual Programming Language designed for beginners to learn programming effectively. However, it lacks the capacity to allow users to learn and solve larger real-world problems such as the Travelling Salesman Problem (TSP). Hence, there is a need for an accessible and effective tool to assist beginners and novice programmers in learning and tackling the TSP. This paper introduces ScratchTSP, an extension of the Scratch programming Framework, specifically designed for the TSP. It offers an opportunity for beginners and novice programmers to grasp the TSP and the various algorithms used to solve it. For evaluation, we conduct a survey among undergraduate students to assess the usability and usefulness of the proposed ScratchTSP extension. Survey findings indicate that ScratchTSP offers a user-friendly and effective tool for beginners or novice programmers, aiding them in learning the TSP while developing their critical thinking and problem-solving skills. © 2024 ACM.

关键词： Students

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Accurate Detection of COVID-19 and Pneumonia from Chest X-Rays and CT Images Using DNN 2

Accurate Detection of COVID-19 and Pneumonia from Chest X-Ra...

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2nd international conference on Distributed Computing and Optimization Techniques, ICDCOT 2024

作者： Sekar, K. Suganya Devi, K. Murali Baskaran, V. Dheepa, T. Rajalakshmi Engineering College Department of Artificial Intelligence and Machine Learning Chennai Thandalam India National Institute of Technology Silchar Department of Computer Science and Engineering Silchar India Rajalakshmi Engineering College Department of Computer Science and Engineering Chennai Thandalam India Kongunadu College of Engineering and Technology Department of Computer Science and Engineering Tiruchirappalli India

ISBN: (纸本)9798350382952

X-rays play a crucial role in computed tomography (CT) imaging, enabling the visualization of internal structures within the body. It is particularly valuable in assessing pulmonary injuries in COVID-19 patients. Global health is facing a serious crisis as a result of such disease. Most affected persons could be saved if COVID-19 is diagnosed in time. However, COVID-19 can sometimes be misdiagnosed as other lung diseases, potentially leading to severe consequences such as death or significant injury, especially if the virus spreads rapidly throughout the thoracic cells. This research proposes a multi-classification deep neural network(DNN) to identify COVID-19 and pneumonia using a combination of CX-R and CT scan image datasets. The combined dataset will improve classification performance. The proposed DNN model achieves significant results in detecting COVID-19 and pneumonia. The proposed model provides an accuracy of 98.75%, a recall value of 98.75%, a precision value of 98.45%, F1-score of 98.43%, and an AUC of 99.60% on the above datasets. © 2024 IEEE.

关键词： Coronavirus

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A Study of Factors Influencing Cross-border E-commerce Platform Service Quality 9

A Study of Factors Influencing Cross-border E-commerce Platf...

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Joint 9th international conference on Digital Arts, Media and technology with 7th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2024

作者： Zhang, Jianemi Suteeca, Raslapat Chiang Mai University College of Arts Media and Technology Chiang Mai Thailand

ISBN: (纸本)9798350318241

This study selected Thai university students with experience using cross-border platforms as research subjects. It used SPSS AMOS software to analyze 323 valid questionnaires using a structural equation model. The research sought to investigate the effects of the quality of cross-border platforms in the Thai market on Thai customers' purchase intention. The service of cross-border e-commerce platforms was divided into six dimensions: ease of use, appearance design, security, responsiveness, reliability, and caring. The results showed that each service quality dimension of cross-border e-commerce platforms positively affects purchase intentions. Of these, responsiveness has the most significant impact on purchase intention. © 2024 IEEE.

关键词： Electronic commerce

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