检索结果-内蒙古大学图书馆

IPT-ILR: Image Pyramid Transformer Coupled With Information Loss Regularization for All-in-One Image Restoration

IEEE Transactions on Circuits and Systems for Video Technology 2025年第5期35卷 4341-4356页

作者： Yang, Sai Hu, Bin Liu, Fan Wu, Xiaoxin Ding, Weiping Zhou, Jun Nantong University School of Electrical Engineering and Automation Nantong226019 China Nantong University School of Artificial Intelligence and Computer Science Nantong226019 China Hohai University College of Computer Science and Software Engineering Nanjing210098 China Griffith University School of Information and Communication Technology NathanQLD4111 Australia

All-in-one image restoration has recently developed to be a new research trend in the low-level computer vision field, aiming to tackle multiple image degradation types simultaneously in a unified model. As a typical multi-task learning, existing approaches focus on modeling either the specificity or commonality among different image restoration tasks. To exploit the unique strengths of both worlds, we propose a method of Image Pyramid Transformer coupled with Information Loss Regularization (IPT-ILR), in which the multi-scale architecture structure can excavate more information for multiple restoration tasks concurrently, while the learning strategy can identify the difference among multiple restoration tasks depending on the degree of information loss in each restoration task. Specifically, it first establishes a new Image Pyramid Transformer Network (IPT-Network) to accommodate multiple image restoration tasks. Given original degraded images, the IPT-Network exploits the image pyramid technique to establish a series of images with different scales, which are then restored by transformer-like auto-encoders. Moreover, the restored image on a low-level scale is referenced to assist restoring the degraded image on a high-level scale. Next, Information Loss Regularization (ILR) is presented to optimize the IPT-Network. ILR calculates the average distance between degraded images and their clean counterparts as the weights, which automatically implement different penalties for different image restoration tasks, thus avoiding the short-cut phenomenon for the easy task while encouraging the hard task. Extensive experiments have been conducted with 6 image restoration tasks in the all-in-one setting. The results show our method performs favorably against numerous state-of-the-art methods across most tasks, including image denoising, image deblurring, image dehazing, image deraining, image desnowing, as well as low-light enhancement. © 1991-2012 IEEE.

关键词： Restoration

来源：评论

学校读者我要写书评

暂无评论

Utilizing Evidential Reasoning (ER) Approach for software Components Selection

引用

SN computer Science 2025年第3期6卷 1-13页

作者： Ahmad, Nabot Al-Qerem, Ahmad Omar, Firas Jebreen, Issam Department of Software Engineering Al Zaytoonah University of Jordan Amman Jordan Computer Science Department Zarqa University Zarqa Jordan Business Intelligence Department Al Zaytoonah University of Jordan Amman Jordan Software Engineering Department Middle East University Amman Lebanon

software component selection is one of the most challenging problems for software developers to meet customer needs. Despite various methods researchers propose to aid in component selection, a gap exists in addressing the complexities of decision-making under uncertainty. This study utilizes the Evidential Reasoning (ER) approach, which effectively handles multi-criteria decision-making (MCDM) scenarios to evaluate software components for an online bookstore. The methodology involves assessing quality attributes using the ER approach incorporating evaluation grades, weights, and belief degrees to manage information uncertainty. The results demonstrate that the ER approach provides a robust framework for software component selection leading to informed decisions. This approach offers significant advantages in scenarios where traditional MCDM methods are insufficient, thereby enhancing the reliability of component selection in software engineering. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： Decision making Evidential reasoning Multi-criteria software component

来源：评论

学校读者我要写书评

暂无评论

Accelerating Blockchain Application Development: Integrating Blockchain as a Service Within Low-Code Platforms 7th

Accelerating Blockchain Application Development: Integrating...

引用

7th International Conference on Blockchain, ICBC 2024, Held as Part of the Services Conference Federation, SCF 2024

作者： He, Sheng Huang, Qinglin Jiao, Shaoshuai Lin, Zepeng Lin, Jinxuan Ren, Jun Xiong, Dengbin Zhang, Liang-Jie National Engineering Research Center for Supporting Software of Enterprise Internet Services Shenzhen518057 China Kingdee Research Kingdee International Software Group Co. Ltd. Shenzhen518057 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China

ISBN: (纸本)9783031770944

The integration of Blockchain as a Service (BaaS) within the Low-Code Development Platforms (LCDPs) is expected to revolutionize the speed and accessibility of blockchain application development. This paper explores the synergy between BaaS and the low-code or no-code development environments in Platform as a Service (PaaS) frameworks, examining opportunities, challenges, and implications for developers and organizations. LCDPs have gained popularity for simplifying application creation, empowering a broad spectrum of developers from citizen developers to experienced professionals. Concurrently, blockchain technology offers enhanced security and transparency but traditionally requires specialized skills for implementation. By embedding BaaS capabilities within LCDPs, developers can leverage blockchain benefits without extensive expertise, streamlining development processes and accelerating time-to-market for blockchain applications. Additionally, it addresses challenges related to security, scalability, and the complexity of managing blockchain operations within simplified development environments. By presenting best practices and identifying opportunities, this paper aims to contribute to the advancement of accessible and efficient blockchain application development. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Platform as a Service (PaaS)

来源：评论

学校读者我要写书评

暂无评论

Automatic Positioning of Intelligent Mobile Robot Based on Improved Front-End Scanning Matching

Journal of Network Intelligence

引用

Journal of Network Intelligence 2025年第1期10卷 559-572页

作者： Wang, Hong Wang, Yi-Gui Zhang, Jie Department of Computer and Software Engineering Shandong College of Electronic Technology Jinan250200 China School of Computer Science and Technology Shandong Jianzhu University Jinan250101 China College of Agricultural Science and Technology Yana Royal Polytechnic University Chiang Mai50000 Thailand

Traditional autonomous navigation methods for mobile robots mainly rely on geometric feature-based LiDAR scan-matching algorithms, but in complex environments, this method is often affected due to the presence of moving objects, occlusions, and other interfering factors, resulting in a decrease in positioning accuracy. With the growing demand for robotics applications in logistics, security, exploration and other fields, the need for robust autonomous navigation and high-precision mapping in highly dynamic and complex environments is becoming more and more urgent. To solve this problem, an improved front-end scan matching algorithm based on Frequency Modulated Continuous Wave (FMCW) LiDAR is proposed in this paper. Firstly, by using the target Doppler velocity information provided by the FMCW LiDAR, we design a novel point cloud segmentation algorithm based on velocity clustering, which is able to effectively distinguish between stationary and moving objects, and avoid the dynamic interference affecting the position estimation. Secondly, we introduce the Gaussian Mixture Model Sampling Consistency (GMMSC) algorithm, which is more robust to reject the mis-matched pairs in the scanning matching process and improve the alignment accuracy. Finally, based on the residual high-quality matched pairs, we combine the classical ICP algorithm with the robust kernel function to further enhance the stability of the position estimation in the case of occlusion and local mismatch. The experimental results show that the proposed improved algorithm significantly improves the mapping capability of mobile robots in complex environments compared with the existing techniques. The average relative error of the improved front-end scanning matching algorithm is reduced by 40.6 % compared with the pre-improved one. © 2025, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Mobile robots

来源：评论

学校读者我要写书评

暂无评论

Network-Wide Energy Efficiency Maximization in UAV-Aided IoT Networks: Quasi-Distributed Deep Reinforcement Learning Approach

引用

IEEE Internet of Things Journal 2025年第11期12卷 15404-15414页

作者： Lee, Seungmin Ban, Tae-Won Lee, Howon Newratek Inc Department of Wi-Fi MAC Standards and Software Engineering Seoul06175 Korea Republic of Gyeongsang National University Department of Intelligent Communication Engineering Jinju52828 Korea Republic of Ajou University Department of Electrical and Computer Engineering Gyeonggi Suwon16499 Korea Republic of

In unmanned aerial vehicle (UAV)-aided Internet of Things (IoT) networks, providing seamless and reliable wireless connectivity to ground devices (GDs) is difficult owing to the short battery lifetimes of UAVs. Hence, we consider a deep reinforcement learning (DRL)-based UAV base station (UAV-BS) control method to maximize the network-wide energy efficiency of UAV-aided IoT networks featuring continuously moving GDs. First, we introduce two centralized DRL approaches;round-robin deep Q-learning (RR-DQL) and selective-k deep Q-learning (SK-DQL), where all UAV-BSs are controlled by a ground control station that collects the status information of UAV-BSs and determines their actions. However, significant signaling overhead and undesired processing latency can occur in these centralized approaches. Hence, we herein propose a quasi-distributed DQL-based UAV-BS control (QD-DQL) method that determines the actions of each agent based on its local information. By performing intensive simulations, we verify the algorithmic robustness and performance excellence of the proposed QD-DQL method based on comparison with several benchmark methods (i.e., RR-DQL, SK-DQL, multi-agent Q-learning, and exhaustive search method) while considering the mobility of GDs and the increase in the number of UAV-BSs. © 2014 IEEE.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

An aspect-based sentiment analysis model for Arabic game reviews based on hybrid transformers models

引用

Neural Computing and Applications 2025年 1-23页

作者： Hammad, Mahmoud AbuEnnab, Noor Al-Refai, Mohammed IT Department Ajman University Ajman United Arab Emirates Software Engineering Department Jordan University of Science and Technology Irbid Jordan Computer Science Department Jordan University of Science and Technology Irbid Jordan

Aspect-based sentiment analysis (ABSA) is a natural language processing (NLP) technique to determine the various sentiments of a customer in a single comment regarding different aspects. The increasing online data content generated by interested customers and reviewers motivated researchers and data scientists to conduct ABSA. ABSA has become increasingly popular in recent years due to its versatility in e-commerce, social media, and customer feedback analysis. However, ABSA faces several significant challenges, including determining the aspects and their sentiment polarities (positive, negative, or neutral) in a given text. Moreover, ABSA faces particular challenges in non-English languages such as Arabic due to the lack of resources and mature models. Typically, ABSA tackles one or more of the ABSA research tasks: (T1) aspect term extraction, (T2) aspect term polarity, (T3) aspect category identification, and (T4) aspect category polarity. To identify the aspects and their corresponding sentiment polarities in a given text, accurate and efficient NLP techniques are required. Despite growing interest in Arabic ABSA, the lack of annotated datasets and pre-trained models has hindered its development. In this research, we have collected a dataset of Arabic game reviews and annotated them using three annotators, and then we trained an ABSA deep learning model based on the BERT pre-trained model combined with zero-shot learning (ZSL) to tackle all the four aforementioned tasks. Our best performing model achieved a high accuracy on all four tasks with an accuracy of 91.61% on T1, 90.99% on T2, 79.08% on T3, and 88.17% on T4. Finally, we compared our model’s accuracy with the state-of-the-art Arabic-based ABSA models on different datasets. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Sales

来源：评论

学校读者我要写书评

暂无评论

Heterogeneous signcryption scheme from CLC to IBC for IIoT

引用

Peer-to-Peer Networking and Applications 2025年第4期18卷 1-14页

作者： Jin, Chunhua Qin, Wenyu Chen, Zhiwei Li, Chenhao Chen, Xiaobing Chen, Guanhua Zhang, Hao Weng, Jian Faculty of Computer and Software Engineering Huaiyin Institute of Technology Huai’an 233003 China The College of Information Science and Technology Jinan University Zhuhuai 510632 China

The Industrial Internet of Things (IIoT) involves the real-time gathering of information from physical devices and technologies for improved perception and management. To ensure information transmission security, an efficient and secure cryptography scheme is needed, especially for devices under resource constraints. In this paper, a heterogeneous signcryption (HSC) scheme is designed to meet security requirements in the IIoT environment. This construction employs a heterogeneous system, with the sender using certificateless cryptography (CLC) to effectively solve the key escrow problem in identity-based cryptography (IBC) and the certificate management problem in public key infrastructure (PKI). The receiver, on the other hand, uses IBC to settle the certificate management issue in PKI. The scheme supports formal security proof in the random oracle model (ROM). Furthermore, the detailed performance analysis demonstrates that the scheme has advantages in terms of energy consumption and computation overhead, making it suitable for the IIoT environment. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Heterogeneous IIoT ROM Security Signcryption

来源：评论

学校读者我要写书评

暂无评论

Parkinson’s Disease Detection from Resting State EEG Using Multi-head Graph Structure Learning with Gradient Weighted Graph Attention Explanations 7th

Parkinson’s Disease Detection from Resting State EEG Using...

引用

7th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2024, Held in Conjunction with 27th International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2024

作者： Neves, Christopher Zeng, Yong Xiao, Yiming Department of Computer Science and Software Engineering Concordia University MontrealQC Canada Concordia Institute for Information Systems Engineering Concordia University MontrealQC Canada

ISBN: (纸本)9783031787607

Parkinson’s disease (PD) is a debilitating neurodegenerative disease that has severe impacts on an individual’s quality of life. Compared with structural and functional MRI-based biomarkers for the disease, electroencephalography (EEG) can provide more accessible alternatives for clinical insights. While deep learning (DL) techniques have provided excellent outcomes, many techniques fail to model spatial information and dynamic brain connectivity, and face challenges in robust feature learning, limited data sizes, and poor explainability. To address these issues, we proposed a novel graph neural network (GNN) technique for explainable PD detection using resting state EEG. Specifically, we employ structured global convolutions with contrastive learning to better model complex features with limited data, a novel multi-head graph structure learner to capture the non-Euclidean structure of EEG data, and a head-wise gradient-weighted graph attention explainer to offer neural connectivity insights. We developed and evaluated our method using the UC San Diego Parkinson’s disease EEG dataset, and achieved 69.40% detection accuracy in subject-wise leave-one-out cross-validation while generating intuitive explanations for the learnt graph topology. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

An empirical study of manual abstraction between class diagrams and code of open-source systems

引用

software and Systems Modeling 2025年 1-27页

作者： Zhang, Wenli Zhang, Weixing Strüber, Daniel Hebig, Regina Department of Computer Science and Engineering Chalmers University of Technology and University of Gothenburg Gothenburg Sweden Department of Software Science Radboud University Nijmegen Netherlands Institute of Computer Science University of Rostock Rostock Germany

Models play a crucial role in software design, analysis, and supporting new maintainers. However, over time, the benefits of models can diminish as system implementations evolve without corresponding updates to the original models. Reverse engineering methods and tools can help maintain alignment between models and implementation code. Yet, automatically reverse-engineered models often lack abstraction and contain extensive details that hinder comprehension. Recent advancements in AI-based content generation suggest that we may soon see reverse engineering tools capable of human-grade abstraction. To guide the design and validation of such tools, we need a principled understanding of manual abstraction—a topic that has received limited attention in existing literature. In pursuit of this goal, our paper presents a multiple-case study of model-to-code differences, examining nine substantial open-source software projects obtained through repository mining. We manually matched source code from projects comprising 4983 classes, 26k attributes, and 54k operations to 523 model elements (including classes, attributes, operations, and relationships). These mappings precisely capture discrepancies between provided class diagram designs and actual implementation code. By analyzing these differences in detail, we derive a taxonomy of difference types and provide a well-organized list of cases corresponding to identified differences. Our findings have the potential to contribute to improved reverse engineering methods and tools, propose new mapping rules for model-to-code consistency checks, and offer guidelines to avoid over-abstraction and over-specification during the design process. © The Author(s) 2025.

关键词： Abstraction Modeling software design

来源：评论

学校读者我要写书评

暂无评论

Invisible Warning Line: Efficient and Generic Regulation for Anonymous Cryptocurrencies

引用

IEEE Transactions on Dependable and Secure Computing 2025年第3期22卷 2022-2036页

作者： Gao, Rui Wan, Zhiguo Wang, Huaqun Luo, Shaoteng Nanjing University of Posts and Telecommunications College of Computer Jiangsu Cryptographic Technology Engineering Research Center Nanjing210023 China Zhejiang Lab Hangzhou310000 China UCAS School of Software Engineering Hangzhou Institute for Advanced Study Hangzhou310024 China

Decentralized finance based on blockchain has experienced rapid development. To safeguard the privacy of participants, decentralized anonymous payment (DAP) systems such as ZCash and Zether have emerged. These systems employ cryptographic techniques to conceal the trader addresses and payment amounts. However, this anonymity presents challenges in terms of regulation. To address this issue, we propose the Walsh-DAP (WDAP) scheme, an efficient and generic regulation scheme for decentralized anonymous payments that strikes a balance between regulation and privacy preservation. Our scheme introduces two regulation policies: first, users who have exceeded their spending limits within a certain period will be identified during the regulation process;second, the supervisor possesses the capability to trace any anonymous transaction. To implement regulation effectively, we have designed an innovative commitment scheme, Walsh commitment, which leverages the orthogonal properties of Walsh codes to achieve the features of aggregatability and extractability. The supervisor in WDAP only needs to deal with the aggregation result of the Walsh commitments instead of the huge amount of raw transactions information, which greatly increases the efficiency. In a DAP system with 256 users, 10 transactions per second and 30 days as a regulation period, we reduced the communication cost for regulation from 14 GB to 94.20 KB, and the computing cost from 1.6 × 105 s to 2.17s. Both improvement is of over five orders of magnitude. We formally discussed the security of the whole system, and verified its feasibility and practicability in the ZCash system. © 2004-2012 IEEE.

关键词： Decentralized finance

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：