检索结果-内蒙古大学图书馆

2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Nandhakumar, R.G. Devi, K. Nirmala Krishnamoorthy, N. Shanthi, S. Pranesh, V.R. Nikhalyaa, S. Kongu Enginering College Perundurai Department of Computer Science and Engineering Tamilnadu Erode India Vellore Institutte of Technology School of Information and Engineering Department of Software Systems and Engineering Vellore India

ISBN: (纸本)9798350348217

Road safety is of prime importance as road accidents are among the biggest causes of deaths in the country. Road Accidents are majorly due to violators and lawbreakers of road safety rules like not wearing helmets, triple riding etc. Even though there are many smart systems to monitor these violations, it is complicated to keep a track of the data and view it efficiently anywhere. Also monitoring the permit details of other state vehicles is hard. A method was proposed to address this issue. based on Deep learning and Optical Character Recognition (OCR). Here we detect the riders not wearing helmet and triple riders using object detection by comparing YOLOv2 and YOLOv3. This simplifies the task of traffic police who can't continuously and efficiently monitor all the violators. We gathered our data from three different sources. Kaggle was used to collect the data set. A number of items can be recognized by the real-time object recognition system YOLO in a single frame. It recognizes object more precisely and faster than other recognition systems. It can predict up to 9000 classes and even unseen classes. It divides the image into m∗m matrix and each grid detects objects within itself. The trained model is tested using a test dataset set after training in order to measure the performance. For Number plate detection we use OCR based character recognition. The recognized license plate images of violators are captured and stored in a database which is then sent to the concerned department. The stored data can be easily accessed using the developed mobile app. Metrics considered for evaluation is Accuracy. The average is utilized to assess object detection models like R-CNN and YOLO. The average calculates a score by comparing the detected box to the ground-truth bounding box. The better the score, the more precise the model's detections are. When compared to YOLOv2, YOLOv3 exhibits strong performance in terms of accuracy with 95.5%. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Enhancing Intrusion Detection systems Using RNN, LSTM, and Hybrid RNN-LSTM Models 2

Enhancing Intrusion Detection Systems Using RNN, LSTM, and H...

引用

2nd International Conference on Machine Learning and Autonomous systems, ICMLAS 2025

作者： Ebadinezhad, Sahar Nia, Nooshin Nooraei Shirzad, Nasratullah Osemeha, Nwabueze Kenneth Near East University Department of Computer Information Systems Nicosia99138 Cyprus Artificial Intelligence Near East University Nicosia Cyprus Near East University Software Engineering Department Nicosia Cyprus

ISBN: (纸本)9798331505745

Due to The lack of comparison studies and practical applications of RNN, LSTM, and hybrid RNN-LSTM models for intrusion detection systems, especially when managing class imbalances in complex network datasets, represents a gap in the literature. This study investigates the application of deep learning techniques to improve the detection capabilities of IDS. For this study, we applied and assessed Recurrent Neural Network, Long Short-Term Memory, and Hybrid RNN-LSTM models on a UNSW-NB15 dataset, and to redress class imbalance we trained and validated our models using synthetic minority over-sampling. The RNN-LSTM model was shown to perform the best with a 9 4. 0 0 % accuracy in comparison to other models. These experimental results signify the possibility of enhancing IDS performance and a dependable method of detecting various network intrusions with the use of hybrid models comprised of RNN & LSTM. © 2025 IEEE.

关键词： Recurrent neural networks

来源：评论

学校读者我要写书评

暂无评论

A Systematic Review of Approaches for Reviewing Security-Related Aspects in Agile Requirements Specification of Web Applications

A Systematic Review of Approaches for Reviewing Security-Rel...

引用

2023 Congress in computer Science, computer engineering, and Applied Computing, CSCE 2023

作者： Munir, Aqsa Assiri, Mohammed Alam, Saba Naveed Khan, Muzna Butt, Wasi Haider Humayun, Mamoona Department of Computer and Software Engineering Islamabad Pakistan College of Sciences and Humanities Aflaj Prince Sattam Bin Abdulaziz University Department of Computer Science Saudi Arabia College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Department of Software Engineering Saudi Arabia College of Computer and Information Sciences Jouf University Department of Information Systems Al-Jouf Saudi Arabia

ISBN: (纸本)9798350327595

Imperfections in requirement specification can cause serious issues during software development life cycle. It might bring about inferior quality products due to missing attributes, for example, security. Specifically, Web Applications are considered as obvious target for getting significant information. Security aspects have gotten hard to manage in web applications because security requirements are not regularly seen appropriately and often details are missing which lead into ill-characterized security-related aspects. With the help of systemic literature review (SLR), we have identified 32 major research works which were published in period of year 2010 to 2020. We identified 38 security-related aspects of web applications and also 13 techniques and tools for security related aspects in agile requirement specification. We have also analyzed 22 challenges in reviewing security related aspects in agile development life cycle. © 2023 IEEE.

关键词： Agile software development Quality requirements Requirement engineering Security specification Web applications

来源：评论

学校读者我要写书评

暂无评论

FedIERF: Federated Incremental Extremely Random Forest for Wearable Health Monitoring

引用

Journal of computer Science & Technology 2023年第5期38卷 970-984页

作者：胡春雨忽丽莎袁林陆佃杰吕蕾陈益强 Key Laboratory of Computing Power Network and Information Security Ministry of EducationShandong Computer Science Center(National Supercomputer Center in Jinan)Qilu University of Technology(Shandong Academy of Sciences)Jinan 250353China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer ScienceJinan 250000China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan 25000China Institute of Information Technology Hebei University of Economics and BusinessShijiazhuang 050061China School of Information Science and Engineering Shandong Normal UniversityJinan 250358China Institute of Computing Technology Chinese Academy of SciencesBeijing 100190China

Wearable health monitoring is a crucial technical tool that offers early warning for chronic diseases due to its superior portability and low power ***,most wearable health data is distributed across dfferent organizations,such as hospitals,research institutes,and companies,and can only be accessed by the owners of the data in compliance with data privacy *** first challenge addressed in this paper is communicating in a privacy-preserving manner among different *** second technical challenge is handling the dynamic expansion of the federation without model *** address the first challenge,we propose a horizontal federated learning method called Federated Extremely Random Forest(FedERF).Its contribution-based splitting score computing mechanism significantly mitigates the impact of privacy protection constraints on model *** on FedERF,we present a federated incremental learning method called Federated Incremental Extremely Random Forest(FedIERF)to address the second technical *** introduces a hardness-driven weighting mechanism and an importance-based updating scheme to update the existing federated model *** experiments show that FedERF achieves comparable performance with non-federated methods,and FedIERF effectively addresses the dynamic expansion of the *** opens up opportunities for cooperation between different organizations in wearable health monitoring.

关键词： federated learning incremental learning random forest wearable health monitoring

来源：评论

学校读者我要写书评

暂无评论

Formal Verification Based Synthesis for Behavior Trees 9th

Formal Verification Based Synthesis for Behavior Trees

引用

9th International Symposium on Dependable software engineering: Theories, Tools and Applications, SETTA 2023

作者： Hong, Weijiang Chen, Zhenbang Li, Minglong Li, Yuhan Huang, Peishan Wang, Ji College of Computer National University of Defense Technology Changsha China Key Laboratory of Software Engineering for Complex Systems National University of Defense Technology Changsha China Institute for Quantum Information & State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China

ISBN: (纸本)9789819986637

Behavior trees (BTs) have been extensively applied in the area of both computer games and robotics, as the control architectures. However, the construction of BTs is labor-expensive, time-consuming, and even impossible as the complexity of task increases. In this work, we propose a formal verification based synthesis method to automatically construct BTs whose behaviors satisfy the given Linear Temporal Logic (LTL) specifications. Our method first explores candidate BTs by a grammar-based Monte Carlo Tree Search (MCTS), then the explored BTs are transformed into Communicating Sequential Processes (CSP) models. After that, we invoke the verifier to check the models’ correctness w.r.t. specifications, and provide feedback based on the verification result for guiding the search process. The application of our method on several representative robotic missions indicates its promising. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Behavior Trees CSP MCTS Synthesis

来源：评论

学校读者我要写书评

暂无评论

A Deep Learning Method for Statistical Downscaling of CLDAS Relative Humidity with Different Sources of Data:Sensitivity Analysis

引用

Journal of Meteorological Research 2023年第6期37卷 878-895页

作者： Bin BAI Chunxiang SHI Ling YANG Lingling GE Luhui YUE Guangyu LIU College of Electronic Engineering Chengdu University of Information TechnologyChengdu610225China Key Laboratory of Atmospheric Sounding of China Meteorological Administration Chengdu610225China National Meteorological Information Centre China Meteorological AdministrationBeijing100081China School of Computer and Software Nanjing University of Information Science&TechnologyNanjing210044China

High-resolution relative humidity(RH)data are essential in studies of climate change and in numerical meteorological ***,because high-resolution meteorological grid data require a large number of stations,the sparse distribution of ground meteorological stations in China before 2008 has limited the development of long-term and high-resolution RH products in the China Meteorological Administration’s Land Assimilation System(CLDAS)*** retrieve high-quality and high-resolution RH data before 2008,we propose a statistical downscaling model(SDM)based on a generative adversarial network(GAN)to transform the original RH data from a resolution of0.05°to 0.01°.The GAN-based SDM(GSDM)is trained with the RH of the CLDAS(0.05°)dataset after 2008 as its input,and the RH of the high-resolution CLDAS(HRCLDAS,0.01°)dataset after 2008 as its target for ***2-m air temperature data from the HRCLDAS dataset are also included in the input,and the station observations of RH are incorporated in the target for *** select the optimum data combination for the model,we compared three methods:(1)incorporating without auxiliary data(GSDM),(2)incorporating air temperature as an additional input(GSDM_T),and(3)incorporating air temperature as an additional input and the RH data at stations as an additional target for training(GSDM_TO).Taking the Beijing–Tianjin–Hebei region as an example,we trained the GSDM by using data from 2018 and tested the model performance in *** experimental results showed that the GSDM_TO algorithm achieved the lowest root-mean-square error(3.85%),followed by the GSDM_T(4.01%)and GSDM(4.95%)*** proposed models showed a competitive performance and captured more local details of the RH fields than other deep learning models and traditional bilinear *** general,the GSDM_TO algorithm using a combination of different sources of data(air temperature and observed RH)achieved the best results among the various d

关键词： relative humidity statistical downscaling generative adversarial network(GAN) temperature

来源：评论

学校读者我要写书评

暂无评论

Audio2AB:Audio-driven collaborative generation of virtual character animation

引用

虚拟现实与智能硬件（中英文） 2024年第1期6卷 56-70页

作者： Lichao NIU Wenjun XIE Dong WANG Zhongrui CAO Xiaoping LIU School of Computer Science and Information Engineering Hefei University of TechnologyHeifei 230009China School of Software Hefei University of TechnologyHeifei 230009China Anhui Province Key Laboratory of Industry Safety and Emergency Technology Hefei University of TechnologyHefei 230601China

Background Considerable research has been conducted in the areas of audio-driven virtual character gestures and facial animation with some degree of ***,few methods exist for generating full-body animations,and the portability of virtual character gestures and facial animations has not received sufficient *** Therefore,we propose a deep-learning-based audio-to-animation-and-blendshape(Audio2AB)network that generates gesture animations and ARK it's 52 facial expression parameter blendshape weights based on audio,audio-corresponding text,emotion labels,and semantic relevance labels to generate parametric data for full-body *** parameterization method can be used to drive full-body animations of virtual characters and improve their *** the experiment,we first downsampled the gesture and facial data to achieve the same temporal resolution for the input,output,and facial *** Audio2AB network then encoded the audio,audio-corresponding text,emotion labels,and semantic relevance labels,and then fused the text,emotion labels,and semantic relevance labels into the audio to obtain better audio ***,we established links between the body,gestures,and facial decoders and generated the corresponding animation sequences through our proposed GAN-GF loss *** By using audio,audio-corresponding text,and emotional and semantic relevance labels as input,the trained Audio2AB network could generate gesture animation data containing blendshape ***,different 3D virtual character animations could be created through *** The experimental results showed that the proposed method could generate significant gestures and facial animations.

关键词： Audio-driven Virtual character Full-body animation Audio2AB Blendshape GAN-GF

来源：评论

学校读者我要写书评

暂无评论

Cooperative Selection and Communications in 6G Ultra-mMTC IoV Networks 4

Cooperative Selection and Communications in 6G Ultra-mMTC Io...

引用

4th International Symposium on Electrical, Electronics and information engineering, ISEEIE 2024

作者： Huang, He Huang, Wei College of Communication Technology Chengdu China School of Computer Science and Information Engineering Hefei China Intelligent Interconnected Systems Laboratory of Anhui Province Hefei China

ISBN: (纸本)9798350355772

Although Cooperative Communications (CC) already exists in 4G/5G, performance improvement is just not enough. As 5G standard has gradually established recently, CC has been one of most critical communication technologies which plays a founding role in 6G IoV networks. Therefore, it is important to apply collaborative technology to achieve Internet of Everything (IoV) and improve communication quality significantly in 6G IoV ultra-mMTC networks. In this study, we review that collaborative ideology has been regarded as foundation theory which widely exists in future multiple hybrid scenarios, such as, Cognitive Internet of Things (C-IoT) networks, UAVs (Unmanned Aerial Vehicles) communications, air-space-ground integrated networks, underwater acoustic communication and so on. Besides, we discuss key communication technologies that are closely combined with unique communication scenes, and elaborate critical problems that shall be solved in 6G ultra-mMTC IoV networks. Furthermore, we discuss extreme low complexity and fast ultra-massive relays selection algorithm in all sorts of future 6G scenarios. At last, it is concluded that for arbitrary two communication points (source/destination devices, sensors, relays, IoT nodes and so on), ideology of nodes selection of collaborative communication is theory of foundation to realize IoV and optimize communication transmission performance in future networks. © 2024 IEEE.

关键词： Cooperative communication

来源：评论

学校读者我要写书评

暂无评论

Business Scenario Driven Reinforcement Learning Testing Method 26

Business Scenario Driven Reinforcement Learning Testing Meth...

引用

26th ACIS International Winter Conference on software engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD-Winter 2023

作者： Cai, Lizhi Wang, Jin School of Information Science and Engineering East China University of Science and Technology Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai China

ISBN: (纸本)9798350345865

Reinforcement learning has been successfully applied in software testing, but the existing testing methods cannot perform effective testing according to the characteristics of applications, and using outdated interactive experience during training, resulting in inefficient testing. In this paper, we propose BSDRTesting. Firstly, the demonstration experience of human users is collected according to the functional scenarios and business logic of each application, and combining reinforcement learning and imitation learning to maximize rewards while imitating user behavior, experience replay aims to sample experiences from the agent's self-exploration and expert demonstrations to improve sampling efficiency. At the same time, according to the input rules, the black-box testing method is used to fully test the input events, and finally an experience filtering mechanism is proposed, and the reward value and TD-Error are used as the basis for priority sampling. The experimental results on 10 open source applications show BSDRTesting has achieved significant improvements in code coverage and branch coverage compared with existing methods. © 2023 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Fusion of speech and handwritten signatures biometrics for person identification

引用

International Journal of Speech Technology 2023年第4期26卷 833-850页

作者： Abushariah, Ahmad A. M. Abushariah, Mohammad A. M. Gunawan, Teddy Surya Chebil, J. Alqudah, Assal A. M. Ting, Hua-Nong Mustafa, Mumtaz Begum Peer Faculty of Engineering University of Malaya Kuala Lumpur50603 Malaysia Department of Computer Information Systems King Abdullah II School of Information Technology The University of Jordan Amman Jordan ECE Department Faculty of Engineering International Islamic University Malaysia Kuala Lumpur53100 Malaysia Department of Computer Science Faculty of Science and Information Technology Al-Zaytoonah University of Jordan Amman Jordan Department of Biomedical Engineering Faculty of Engineering University of Malaya Kuala Lumpur50603 Malaysia Department of Software Engineering Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia

Automatic person identification (API) using human biometrics is essential and highly demanded compared to traditional API methods, where a person is automatically identified using his/her distinct characteristics including speech, fingerprint, iris, handwritten signatures, and others. The fusion of more than one human biometric produces bimodal and multimodal API systems that normally outperform single modality systems. This paper presents our work towards fusing speech and handwritten signatures for developing a bimodal API system, where fusion was conducted at the decision level due to the differences in the type and format of the features extracted. A data set is created that contains recordings of usernames and handwritten signatures of 100 persons (50 males and 50 females), where each person recorded his/her username 30 times and provided his/her handwritten signature 30 times. Consequently, a total of 3000 utterances and 3000 handwritten signatures were collected. The speech API used Mel-Frequency Cepstral Coefficients (MFCC) technique for features extraction and Vector Quantization (VQ) for features training and classification. On the other hand, the handwritten signatures API used global features for reflecting the structure of the hand signature image such as image area, pure height, pure width and signature height and the Multi-Layer Perceptron (MLP) architecture of Artificial Neural Network for features training and classification. Once the best matches for both the speech and the handwritten signatures API are produced, the fusion process takes place at decision level. It computes the difference between the two best matches for each modality and selects the modality of the maximum difference. Based on our experimental results, the bimodal API obtained an average recognition rate of 96.40%, whereas the speech API and the handwritten signatures API obtained average recognition rates of 92.60% and 75.20%, respectively. Therefore, the bimodal API system is a

关键词： Biometrics

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：