检索结果-内蒙古大学图书馆

3rd International Conference on Creative Communication and Innovative technology, ICCIT 2024

作者： Siswanto, Joko Hendry Rahardja, Untung Sembiring, Irwan Lisangan, Erick Alfons Hakim, Muhammad Iman Nur Wibowo, Feri Polytechnic of Road Transportation Safety Road Transportation System Engineering Tegal Indonesia Satya Wacana Christian University Faculty of Information Technology Indonesia University of Raharja Faculty of Science and Technology Tangerang Indonesia Satya Wacana Christian University Faculty of Computer Science Indonesia The University of Western Australia Computer Science and Software Engineering Perth Australia Polytechnic of Road Transportation Safety Automotive Engineering Technology Tegal Indonesia Muhammadiyah University Purwokerto Faculty of Engineering and Science Banyumas Indonesia

ISBN: (纸本)9798350367492

A crucial role in the BRT transportation system's planning, development, and operation is the prediction of passenger numbers. Using time-series data, it is necessary to develop careful prediction models, appropriate techniques, and an indepth understanding of the number of BRT Transjakarta passengers. A prediction model is sought based on comparing combined LSTM and BiLSTM experiments using three evaluation matrices and time. Historical data used from daily passenger data for 13 BRT Transjakarta corridors (1/01/2021-31/12/2023). The best prediction model was obtained from the BiLSTM-CNN combination with the lowest MSLE (0.0425), MAPE (0.1598), and SMAPE (15.9387) evaluation matrix values. However, it required a longer time (00:02:14). Predictions of passenger numbers on the 13 Transjakarta BRT corridors for the next 12 months can be made simultaneously by predicting fluctuations occurring simultaneously. The strongest positive correlation is in corridor 9-6, while the strongest negative correlation is in corridor 12-5. The prediction results must be understood by stakeholders, managers, and technopreneurs to develop and support appropriate strategies to increase the number of BRT passengers. © 2024 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

Learning to Cluster Person in the Video via Graph Convolution Network 13

Learning to Cluster Person in the Video via Graph Convolutio...

引用

13th International Conference on information technology in Medicine and Education, ITME 2023

作者： Li, Wei Liang, Sixin Bian, Ang Du, Guodong College of Computer Science Sichuan University Chengdu China School of Information Science and Engineering Yanshan University The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China

ISBN: (纸本)9798350319156

Video person re-identification is receiving academic interest. However, the practical application of the algorithm is hardly supported because of prohibitive annotated data. Hence, the study for unlabeled data will lead to an attractive alternative. This work explores an innovative strategy, namely, learning to cluster unlabeled person in the video through graph convolutional networks. In this paper, we find that the possibility of inter-frame linkage can be inferred from context. Therefore, a pose-guided topology linkage clustering framework is proposed. Our framework consists of three modules: (i) a pose-guided representation module;(ii) a pose-guided embedding module;(iii) a link prediction module. Firstly, the representation coding alone is performed at the level of relational induction bias, embedding the implicit pose structure information in image features. Then, based on the consideration of the topology relationship between adjacent and cross-frame, graph convolutional network is introduced to infer the likelihood of linkage between frame nodes. Experiments show that the method demonstrates excellent scalability in addition to being an effective response to person clustering in case of changes, and does not need the number of clusters as a prior. © 2023 IEEE.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Range-angle Imaging Based on the Prior of Target Scattering Characteristics in Distributed Arrays 2

Range-angle Imaging Based on the Prior of Target Scattering ...

引用

2nd IEEE International Conference on Signal, information and Data Processing, ICSIDP 2024

作者： Mei, Yongjie Zhang, Guangbin Huang, Tianyao Wang, Yan Beijng Institute of Technology School of Information and Electronics Beijing China Yangtze Delta Region Academy Beijing Institute of Technology Radar System and Intelligent Signal Processing Jiaxing China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China

ISBN: (纸本)9798331515669

We consider the problem of target range-angle imaging using distributed arrays. High resolution imaging requires a large array aperture. However, due to the limited number of array elements, the subarrays are usually sparsely located, which results in severe under-sampling and ambiguity problem, degrading the imaging performance. To this end, we propose a range-angle imaging method based on the prior of target scattering characteristic to resolve the ambiguity. The main idea is to use the information increment of priors to reduce the dependence on the measurements. Particularly, we first statistically extract the prior distribution of target scattering intensity by data analysis on the target images. Then we use these priors to design weighting parameters and achieve the ambiguity-free images by solving a weighted sparse recovery problem. Finally, numerical simulation results verify the feasibility of the proposed method. © 2024 IEEE.

关键词： ambiguity distributed array Range-angle imaging the prior of target scattering characteristics weight

来源：评论

学校读者我要写书评

暂无评论

Effect of Pectoral Muscles on CNN based Mammographic Cancer Detection 18

Effect of Pectoral Muscles on CNN based Mammographic Cancer ...

引用

18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Dhimann, Santoresh Kumari Sawhney, Tinny Yadav, Rakesh Kumar Maharishi University of Information Technology Department of Computer Science and Engineering Lucknow India University of Jammu Digital Signal Processing Lab Department of Electronics Jammu India

ISBN: (纸本)9789380544519

Cancer is attributed to abnormal growth of tissue cells in any part of the living body. The number of cancer patients is increasing worldwide. The reason of the development of abnormal cells within the body is still unknown to the researchers. The most common is breast cancer and it is affective affecting one out of every ten women. The reason of breast lesions formation may be calcification or mass deposit and digital mammography is generally used for verifying it. It is a cheap, non-toxic, and user-friendly test, but needs expert opinion for ascertaining the presence of cancer. The accuracy of mammographic detection varies between 80% and 90%. Recently, Convolutional neural networks (CNNs) have shown their application in automatic detection of the cancer, but inclusion of pectoral muscle in the mammogram reduces the efficiency of the CNN system as the texture of the muscle resembles with cancerous tissues. Further, CNN based detection requires high resolution images which in turn requires state of art technology-based machines, generally, not available in rural area-based clinics. The focus of the proposed research is to investigate effect of low-quality blurred input mammograms on the detection of pectoral muscle boundary, so that the pectoral muscle removed mammograms can be applied to CNN system for automatic prediction of cancerous images. The investigations carried out have shown that low quality blurred images can also be employed for detecting cancerous tissues provided the pectoral muscle is removed from the mammograms before using CNN based classifier. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： cancer detection CNN Hough lines mammogram pectoral muscle

来源：评论

学校读者我要写书评

暂无评论

Multifunction integration within magnetic CNT-bridged MXene/CoNi based phase change materials

引用

escience 2024年第6期4卷 108-117页

作者： Yan Gao Xiao Chen Xu Jin Chenjun Zhang Xi Zhang Xiaodan Liu Yinhui Li Yang Li Jinjie Lin Hongyi Gao Ge Wang Beijing Advanced Innovation Center for Materials Genome Engineering Beijing Key Laboratory of Function Materials for Molecule&Structure ConstructionSchool of Materials Science and EngineeringUniversity of Science and Technology BeijingBeijing 100083China School of Physics and Astronomy Beijing Normal UniversityBeijing 100875China Research Institute of Petroleum Exploration&Development PetroChinaBeijing 100083China Micro-Nano System Research Center College of Information and Optical EngineeringTaiyuan University of TechnologyTaiyuanShanxi 030024China Shunde Graduate School University of Science and Technology BeijingShunde 528399China

Developing advanced nanocomposite phase change materials(PCMs)integrating zero-energy thermal management,microwave absorption,photothermal therapy and electrical signal detection can promote the leapfrog development of flexible wearable electronic *** this goal,we propose a multidimensional collaborative strategy combining two-dimensional(2D)MXene nanosheets with metal-organic framework-derived onedimensional(1D)carbon nanotubes(CNTs)and zero-dimensional(0D)metal *** encapsulating paraffin wax(PW)in three-dimensional(3D)networked multidimensional MXene/CoNi-C,the resulting composite PCMs exhibit excellent thermal energy storage capacity and long-term thermally reliable *** from the synergistically enhanced photothermal effects of CNTs,Co/Ni nanoparticles and MXene,PW@MXene/CoNi-C can capture photons efficiently and transfer phonons quickly,yielding an ultrahigh photothermal conversion and storage efficiency of 97.5%.Additionally,PW@MXene/CoNi-C composite PCMs exhibit high microwave absorption with a minimum reflection loss of -49.3 dB at 8.03 GHz in heat-related electronic application *** attractively,the corresponding flexible phase change film can simultaneously achieve thermal management and electromagnetic shielding of electronic devices,as well as photothermal therapy and electrical signal detection for *** functional integration design provides an important reference for developing advanced flexible multifunctional wearable materials and devices.

关键词： Phase change materials Metal-organic frameworks Two-dimensional MXene Photothermal conversion Thermal energy storage Microwave absorption

来源：评论

学校读者我要写书评

暂无评论

Zero Watermarking Algorithm for Medical Image Based on Resnet50-DCT

引用

Computers, Materials & Continua 2023年第4期75卷 293-309页

作者： Mingshuai Sheng Jingbing Li Uzair Aslam Bhatti Jing Liu Mengxing Huang Yen-Wei Chen School of Information and Communication Engineering Hainan UniversityHaikou570228China State Key Laboratory of Marine Resource Utilization in the South China Sea Hainan UniversityHaikou570228China School of Computer Science and Technology Hainan UniversityHaikou570228China Research Center for Healthcare Data Science Zhejiang LabHangzhou311121China Graduate School of Information Science and Engineering Ritsumeikan UniversityKyoto5258577Japan

Medical images are used as a diagnostic tool, so protecting theirconfidentiality has long been a topic of study. From this, we propose aResnet50-DCT-based zero watermarking algorithm for use with medicalimages. To begin, we use Resnet50, a pre-training network, to draw out thedeep features of medical images. Then the deep features are transformedby DCT transform and the perceptual hash function is used to generatethe feature vector. The original watermark is chaotic scrambled to get theencrypted watermark, and the watermark information is embedded into theoriginal medical image by XOR operation, and the logical key vector isobtained and saved at the same time. Similarly, the same feature extractionmethod is used to extract the deep features of the medical image to be testedand generate the feature vector. Later, the XOR operation is carried outbetween the feature vector and the logical key vector, and the encryptedwatermark is extracted and decrypted to get the restored watermark;thenormalized correlation coefficient (NC) of the original watermark and therestored watermark is calculated to determine the ownership and watermarkinformation of the medical image to be tested. After calculation, most ofthe NC values are greater than 0.50. The experimental results demonstratethe algorithm’s robustness, invisibility, and security, as well as its ability toaccurately extract watermark information. The algorithm also shows goodresistance to conventional attacks and geometric attacks.

关键词： Medical images deep residual network resnet50-DCT privacy protection robustness security

来源：评论

学校读者我要写书评

暂无评论

Hyper-Relational Knowledge Representation Learning with Multi-Hypergraph Disentanglement 25

Hyper-Relational Knowledge Representation Learning with Mult...

引用

34th ACM Web Conference, WWW 2025

作者： Li, Jiecheng Luo, Xudong Lu, Guangquan Zhang, Shichao School of Computer Science and Engineering Key Lab of Education Blockchain and Intelligent Technology of the Ministry of Education Guangxi Key Lab of Multi-source Information Mining & Security Guangxi Normal University Guilin China

ISBN: (纸本)9798400712746

Hyper-relational knowledge graphs (HKGs) extend the traditional triplet-based knowledge graph by adding qualifiers to the relationships, making HKGs particularly useful for tasks that require more profound understanding and inference from relationships between entities. However, existing hyper-relational knowledge representation learning methods (HKRL) focus on direct neighbourhood information of entities only by neglecting the relational similarity of the main triple in hyper-relational facts and the attribute details in the qualifiers. In addition, few works extract common and private information across multiple views to minimize noise and interference. This paper proposes a multi-hypergraph disentanglement method for HKRL to address the above issues. Specifically, we first construct four hypergraphs to mine and utilise the inherent structure information of HKGs, and then propose to extract common representations among hypergraphs and private representations within individual hypergraphs to mine the semantic information and the task-relevant information, respectively. Experiment results on four real datasets demonstrate the effectiveness of the proposed method compared to SOTA methods in link prediction tasks on HKGs. © 2025 Copyright held by the owner/author(s).

关键词： hyper-relational knowledge graph

来源：评论

学校读者我要写书评

暂无评论

AI-Based Child Care Parental Control system 4

AI-Based Child Care Parental Control System

引用

4th International Conference on Advancements in Computing, ICAC 2022

作者： Jayasekara, Udara Maniyangama, Hansindu Vithana, Kalhan Weerasinghe, Tharana Wijekoon, Janaka Panchendrarajan, Rrubaa Department of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Sri Lanka Department of Computer System Engineering Sri Lanka Institute of Information Technology Sri Lanka

ISBN: (纸本)9798350398090

Due to the prevalence of the COVID-19 epidemic around the globe, children were compelled to engage in remote learning through online platforms, hence mobile phone has become one of their predominant devices. Mobile device with Internet access offers a major outlet for education, entertainment, and social connection, but this combination can lead to several significant bad sequences such as online exploitation, harmful addictions, and other negative impacts of online social networking. To address harmful effects, parental controls are becoming more crucial, yet Sri Lankan parents are less aware of this. Consequently, this study proposes a parental control system to monitor their child's activities. Android, Microsoft Azure, Java, Python, OpenCV, MySQL, and FastAPI are among the most prominent technologies utilized in the proposed application's development. The suggested approach focuses primarily on the Sri Lankan context and aims to enhance parental digital literacy while safeguarding children from cyber threats. Yielded results showed the proposed mobile application for the identification of toxic words, drugs & alcohol content, game character images, and Instagram Sinhala comments severity as 94%, 95%, 97%, and 55% respectively in controlled experiments. © 2022 IEEE.

关键词： Control systems

来源：评论

学校读者我要写书评

暂无评论

Interior Scene Intelligent Generated for Smart Homes Based on GAN-ID Algorithms

Journal of Network Intelligence

引用

Journal of Network Intelligence 2024年第2期9卷 1046-1055页

作者： Zhang, Fu-Quan Ma, Lin-Juan Zhou, Jun-Xian Wang, Run-Hong Zhang, Guang-Zhen College of Computer and Control Engineering Minjiang University Fuzhou China Digital Media Art Key Laboratory of Sichuan Province Sichuan Conservatory of Music Chengdu China Fuzhou Technology Innovation Center of Intelligent Manufacturing Information System Minjiang University Fuzhou China Fujian Province University Fuzhou China School of Computer Science and Technology Beijing Institute of Technology Beijing China Minjiang University Fuzhou China Information Media School of Tianjin Technician Institute of Mechanical & Electrical Technology Tianjin China

The purpose of this paper is to present a new GAN-ID algorithm to gener-ate interior scene intelligently based on Artificial Intelligence of Things (AIoT). Although great progress has been made when GAN algorithm applied in smart homes and smart cities, the issue of the trade-off between the accuracy and the efficiency in interior scene has been overlooked. A number of experiments were performed to check the performance and it is indicated that the results of the proposed GAN-ID has great advantages in model sample generation than other common methods when generating interior scene intelligently, which is similar to state-of-the-art. It is meaningful when it can be applied in smart cities and smart homes filed based on AIoT in the future. © 2024, J. Network Intell. All rights reserved.

关键词： Automation

来源：评论

学校读者我要写书评

暂无评论

Cloud-Based IoT Solutions for Smart Grids: Advancing Smart Technologies in Energy Management 3

Cloud-Based IoT Solutions for Smart Grids: Advancing Smart T...

引用

3rd IEEE International Conference on Electrical Power and Energy systems, ICEPES 2024

作者： Antonius Alijoyo, Franciskus Vidhate, Deepak A. Kaur, Chamandeep Nivedan, V. Rani, V. Kanpur Balakumar, A. School of Business and Information Technology STMIK LIKMI Bandung Indonesia Dr. Vithalrao Vikhe Patil College of Engineering Department of Information Technology Maharashtra Ahmednagar India Jazan University Department of Computer Science Jazan Saudi Arabia Sri Ramakrishna College of Arts & Science Department of Electronics and Communication System Coimbatore India Hindustan Institute of Technology and Science Chennai India K.Ramakrishnan College of Engineering Department of ECE Trichy India

ISBN: (纸本)9798350390728

The incorporation of Internet of Things (IoT) cloud computing solutions with smart grids signifies a significant advancement in energy management. Traditional methods, though beneficial, often lack scalability and real-time capabilities, limiting their effectiveness in managing the complexity of modern energy systems. In this paper, a novel approach cloud-based IoT technologies to address these shortcomings and enhance smart grid functionalities. Existing energy management methods heavily rely on localized monitoring and control systems, constraining scalability and real-time responsiveness. Additionally, these methods struggle to handle the immense data generated by IoT devices dispersed throughout the grid. The proposed approach tackles these challenges by utilizing cloud computing to store, process, and analyze IoT sensor data in real-time. The novelty of this method lies in seamlessly integrating cloud-based platforms with IoT devices across the smart grid. Through utilising cloud resources, the limitations of traditional approaches are overcome, enabling scalable, real-time oversight and management of grid assets. The methodology involves deploying IoT sensors across the grid to compile information about energy usage, generation, and distribution, which is then transmitted to cloud servers for analysis and decision-making. Through simulations and real-world experiments, the effectiveness of this approach in optimizing grid performance, improving reliability, and facilitating demand-response programs is demonstrated. The results exhibit significant enhancements in grid efficiency and resilience, showcasing the potential of cloud-based IoT solutions to transform energy management in smart grids. Overall, this proposed method presents a promising pathway towards establishing more efficient, sustainable, and resilient energy infrastructure for the future. © 2024 IEEE.

关键词： Cloud platforms

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：