检索结果-内蒙古大学图书馆

9th IEEE International Conference on Computational Intelligence and Applications, ICCIA 2024

作者： Xiao, Shuai Zhang, Yangyang Jiang, Liming Wang, Zhengxia School of Computer Science and Technology Hainan University China School of Information and Communication Engineering Hainan University China Software Co. Ltd. China

ISBN: (纸本)9798350352214

Medical Visual Language Pretraining (MVLP) utilizes textual reports for weak supervision to improve the learning of medical visual representations, showing promise in various medical image analysis tasks. While previous studies have focused on image and report correspondences within the same instances, they have overlooked high-level semantic associations, such as disease-level semantic correspondences, across different instances. To address this issue, we propose an Advanced Semantic Information Guided Multi-Scale Alignment Framework (ASIMSA) with two main modules: 1) Image-Report Alignment (IRA) module for learning shared representations between image and report of the same instance, and 2) Disease-Entity Alignment (DEA) module for learning disease entity correspondences across different instances. Extensive experiments on zero-shot classification, fine-tune classification, and semantic segmentation tasks validate the effectiveness of our proposed method, demonstrating its stable and superior performance. © 2024 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Conceptualizing Processes in Robotic Process Automation: A Basic Meta-Model 10

Conceptualizing Processes in Robotic Process Automation: A B...

引用

10th International Conference on Systems and Informatics, ICSAI 2024

作者： Zhang, Lingtong Yang, Jing Ouyang, Chun Yu, Yang Pan, Maolin School of Computer Science and Engineering Sun Yat-sen University GuangZhou China Queensland University of Technology Australia School of Software Engineering Sun Yat-sen University ZhuHai China

ISBN: (纸本)9798331510138

Robotic Process Automation (RPA) uses software to mimic human actions in performing repetitive, time-consuming tasks, enabling organizations to strategically reallocate their workforce towards more value-driven activities. RPA can be used to build new intelligent systems that combine business with Artificial Intelligence (AI). However, despite its widespread adoption, RPA lacks standardization and a theoretical foundation, giving rise to misconception. For example, it has caused confusion between RPA and the established field of Business Process Automation (BPA), which has prevented organizations from properly using RPA in new intelligent systems. In this paper, we address the gap by proposing a basic meta-model for conceptualizing processes in RPA. Our research involves identifying key characteristics of processes suitable for RPA, deriving fundamental concepts of processes in RPA, and articulating the interrelations between them. Built upon such a conceptual foundation, we conduct a comparative analysis between RPA and BPA, clarifying the differences between the two. We further demonstrate the practical applicability of our proposed basic meta-model by identifying an instantiation of the meta-model manifested in three mainstream RPA software products, respectively. Our research contributes to laying the conceptual foundations of RPA and facilitating its standardization. © 2024 IEEE.

关键词： Intelligent robots

来源：评论

学校读者我要写书评

暂无评论

Design of a Secured and Trusted E-Voting System Using Blockchain Technology

Design of a Secured and Trusted E-Voting System Using Blockc...

引用

2024 IEEE SmartBlock4Africa, SmartBlock4Africa 2024

作者： Elegba Jeremiah, O. Agbelusi, O. Olutayo Victor, A. Akintola Kolawole, G. School of Computing The Federal University of Technology Department of Software Engineering Akure Nigeria School of Computing The Federal University of Technology Department of Computer Science Akure Nigeria

ISBN: (纸本)9798350376838

The state of election in Nigeria is worrisome. Electoral malpractices have been a major challenge to the Nigerian government in recent times. Government has made frantic efforts to tackle these electoral challenges but the recent event in year 2023 presidential election is worrisome suggests that the solution is not near. Recently, the percentage of eligible voters who vote on election days is declining. Voters turnout went up from 52.3% in 1999 - the first general election since 1993 - to 69% in 2003. But, it has been on the decline nearly ever since - 57.5% in 2007, 53.7% in 2011, 43.7% in 2015 and 34.8% in 2019. In 2023, it is 28.63%. With the way things are going, if urgent action is not taken, this could signal the end of democracy in Nigeria. This research presents the design and implementation of a trusted and secured e-voting based on blockchain technology that will increase voters confidence and trust. The system utilizes *** for the frontend and Solidity on the Polygon blockchain for the backend, ensuring transparency, tamper-resistance, and heightened security. This innovative approach addresses trust and reliability concerns in traditional voting systems, offering a modernized and trustworthy electoral process. © 2024 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Dual-branch Complementary Multimodal Interaction Mechanism for Joint Video Moment Retrieval and Highlight Detection

Dual-branch Complementary Multimodal Interaction Mechanism f...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Liang, Xuehui Wang, Ruomei Lin, Ge Feng, Jiawei Luo, Yuanmao School of Computer Science and Engineering Sun Yat-sen University National Engineering Research Center of Digital Life Guangzhou China School of Software Engineering Sun Yat-sen University Zhuhai China

ISBN: (纸本)9781665410205

Joint video moment retrieval and highlight detection is a video understanding task that requires the model to construct multimodal interaction between heterogeneous features. Recent Transformer-based models mainly focus on promoting global interaction between features. However, local interaction and temporal asynchronism modeling are not deeply considered. To solve this problem, this paper proposes a dual-branch complementary multimodal interaction mechanism (DCMI), which consists of a global difference feature activation module (GDFA) and a local information dynamic aggregation module (LIDA). GDFA measures the difference between the target element and the global features, thus activating important information. LIDA designs a multimodal heterogeneous graph and constructs asynchronous interaction between heterogeneous features to dynamically aggregate local information. DCMI adaptively fuses the complementary dual branches to improve the model's cognitive and decision-making abilities of global and local information. Comprehensive comparisons with existing methods on public datasets verify the superiority of the proposed model. Extensive ablation experiments and qualitative analysis show the effectiveness and rationality of DCMI, which can promote the interaction between multimodal features. © 2024 IEEE.

关键词： Video analysis

来源：评论

学校读者我要写书评

暂无评论

Metamorphic Relation Patterns for Metamorphic Testing, Exploration and Robustness

Metamorphic Relation Patterns for Metamorphic Testing, Explo...

引用

作者： Ying, Zhihao Towey, Dave Bellotti, Anthony Chua, Caslon Quan Zhou, Zhi School of Computer Science University of Nottingham Ningbo China Zhejiang Ningbo China Department of Computer Science and Software Engineering Swinburne University of Technology HawthornVIC Australia School of Computing and Information Technology University of Wollongong WollongongNSW Australia

Metamorphic testing (MT) is an effective software quality assurance method;it uses metamorphic relations (MRs) to examine the inputs and outputs of multiple test cases. Metamorphic exploration (ME) and metamorphic robustness testing (MRT) are advanced additions to the MT literature: ME can enable better understanding, and thus testing, of systems;MRT can test software robustness without an oracle. Metamorphic relation patterns (MRPs) are abstractions or templates for multiple concrete MRs. The performance of MT/ME/MRT relies on the quality of MRs, but the identification of MRs is often a manual task requiring some knowledge of MRPs, creative thinking and a good understanding of the system. In other words, the effective identification of MRs remains a challenge and requires further study. In this paper, we propose formal definitions to describe the relationship between multiple MRPs in order to classify them. We also identify a series of new MRPs and propose a new MT framework that can guide the identification and application of MRPs. Based on our definitions, we present the notion of MRP family trees and further propose two trees by classifying previously published MRPs and our proposed MRPs, in order to make it easier for users to find their target MRPs for reuse, reference or inference. Finally, we report on case studies using the MRPs and our framework to guide the identification of MRs for MT/ME/MRT and successfully detect multiple violations. © 2025 John Wiley & Sons Ltd.

关键词： software testing

来源：评论

学校读者我要写书评

暂无评论

Constructing self-supporting surfaces with planar quadrilateral elements

引用

Computational Visual Media 2022年第4期8卷 571-583页

作者： Long Ma Sidan Yao Jianmin Zheng Yang Liu Yuanfeng Zhou Shi-Qing Xin Ying He School of Software Shandong UniversityJinan 250101China School of Computer Science and Engineering Nanyang Technological UniversitySingapore 639798Singapore Internet Graphics Group Microsoft Research AsiaBeijing 100080China School of Computer Science and Technology Shandong UniversityQingdao 266237China

We present a simple yet effective method for constructing 3D self-supporting surfaces with planar quadrilateral(PQ)*** with a triangular discretization of a self-supporting surface,we firstcompute the principal curvatures and directions of each triangular face using a new discrete differential geometryapproach,yielding more accurate results than existing ***,we smooth the principal direction field to reduce the number of ***,we partition all faces into two groups in terms of principalcurvature *** each face with small curvature difference,we compute a stretch matrix that turns the principal directions into a pair of conjugate *** the remaining triangular faces,we simply keep their smoothed principal ***,applying a mixed-integer programming solver to the mixed principal and conjugate direction field,we obtain a planar quadrilateral *** results show that our method is computationally efficient and can yield high-quality PQ meshes that well approximate the geometry of the input surfaces and maintain their self-supporting properties.

关键词： self-supporting surfaces planar quadri-lateral(PQ)meshes conjugate direction fields(CDFs)

来源：评论

学校读者我要写书评

暂无评论

Can end-user feedback in social media be trusted for software evolution: Exploring and analyzing fake reviews

Can end-user feedback in social media be trusted for softwar...

引用

作者： Khan, Javed Ali Ullah, Tahir Khan, Arif Ali Yasin, Affan Akbar, Muhammad Azeem Aurangzeb, Khursheed Department of Computer Science Faculty of Physics Engineering and Computer Science University of Hertfordshire Hatfield United Kingdom School of Computer & Technology Beijing Institute of Technology Beijing China M3S Empirical Software Engineering Research Unit University of Oulu Oulu Finland School of Software Northwestern Polytechnical University Shaanxi Xian China Software Engineering Department Lappeenranta-Lahti University of Technology Lappeenranta Finland Department of Computer Engineering College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia

End-user feedback in social media platforms, particularly in the app stores, is increasing exponentially with each passing day. software researchers and vendors started to mine end-user feedback by proposing text analytics methods and tools to extract useful information for software evolution and maintenance. In addition, research shows that positive feedback and high-star app ratings attract more users and increase downloads. However, it emerged in the fake review market, where software vendors started incorporating fake reviews against their corresponding applications to improve overall software ratings. For this purpose, we conducted an exploratory study to understand how end-users register and write fake reviews in the Google Play Store. We curated a research data set containing 68,000 end-user comments from the Google Play Store and a fake review generator, that is, the Testimonial generator (TG). Its purpose is to understand fake reviews on these platforms and identify the common patterns potential end-users and professionals use to report fake reviews by critically analyzing the end-user feedback. We conducted a detailed survey at the University of science and Technology Bannu, Pakistan, to identify the intelligence and accuracy of crowd-users in manually identifying fake reviews. In addition, we developed a ground truth to be compared with the results obtained from the automated machine and deep learning (M&DL) classifier experiment. In the survey, 512 end-users participated and recorded their responses in identifying fake reviews. Finally, various M&DL classifiers are employed to classify and identify end-user reviews into real and fake to automate the process. Unlike humans, the M&DL classifiers performed well in automatically classifying reviews into real and fake by obtaining much higher accuracy, precision, recall, and f-measures. The accuracy of manually identifying fake reviews by the crowd-users is 44.4%. In contrast, the M&DL classifiers obtained an

关键词： Application programs

来源：评论

学校读者我要写书评

暂无评论

Legal Text Retrieval with Contrastive Representation Learning and Evolutionary Data Augmentation 13

Legal Text Retrieval with Contrastive Representation Learnin...

引用

13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Zhou, Youhua Yan, Xueming Huang, Han Yan, Haowen Chen, Minghao School of Software Engineering South China University of Technology Guangzhou China School of Information Science and Technology Guangdong University of Foreign Studies Guangzhou China School of Computer Science & Engineering South China University of Technology Guangzhou China

ISBN: (纸本)9798350308365

Legal text retrieval holds significant importance in the audit field, posing a challenge as a semantic matching problem. Despite the success of text semantic matching methods, particularly with the advent of large language models, these approaches face challenges when applied to domain-specific tasks, like legal text retrieval. Specifically, issues arise due to the concentrated distribution of data within the specific domain and the insufficient number of training samples. To address these challenges, this paper introduces a text semantic matching model tailored for the task of legal text retrieval, leveraging contrastive learning and evolutionary algorithms. A contrastive learning-based embedding model, which learns semantic representations in a feature space, is used to minimize the distance between matched text pairs and maximize the distance between unmatched text pairs. Additionally, an evolutionary algorithm-based sample augmentation model is introduced to augment the sample set and enhance the representational capabilities of the samples. The efficacy of the proposed method is evaluated in the context of legal text retrieval in the auditing field, and the experimental results reveal promising outcomes, with the proposed method achieving a Hits@l accuracy of 53.09%, a 2.99% improvement over the best baseline model. The Hits@20 accuracy reaches 75.15%, representing a 2.69% enhancement compared to the state-of-the-art methods. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Periodic Attention Networks for Air Quality Index Prediction 4

Periodic Attention Networks for Air Quality Index Prediction

引用

4th International Conference on Machine Learning and computer Application, ICMLCA 2023

作者： Wu, Jiaqing Wu, Yinzhi Chen, Cheng Guangxi Normal University School of Computer Science and Engineering and School of Software Guilin China Yangtze Normal University School of Civil and Architectural Engineering Chongqing China

ISBN: (纸本)9798400709449

Air quality remains a pressing concern in urban regions globally, influencing public health, environmental sustainability, and residents' overall well-being. However, predicting the subsequent day's air quality index (AQI) using its history data is very challenging due to environmental complexities. To address this issue, a novel model named Periodic Attention Networks (PAN) is proposed in this paper, which exploits the hierarchical attention mechanism to capture the periodicity of AQI changes. PAN does a good job of stratifying the weekly periodicity of Beijing's AQI with its monthly periodicity, which enables the model to be constructed with a distinction between important and unimportant contents. The experimental results on the regression prediction task of Beijing's AQI from 2019-2021 show that the applied model surpasses the previous methods to a large extent. © 2023 ACM.

关键词： Air quality

来源：评论

学校读者我要写书评

暂无评论

Graph-Based Feature Learning for Cross-Project software Defect Prediction

引用

computers, Materials & Continua 2023年第10期77卷 161-180页

作者： Ahmed Abdu Zhengjun Zhai Hakim A.Abdo Redhwan Algabri Sungon Lee School of Software Northwestern Polytechnical UniversityXi’anChina School of Computer Science Northwestern Polytechnical UniversityXi’anChina Department of Computer Science Hodeidah UniversityPO Box 3114Al-HudaydahYemen Research Institute of Engineering and Technology Hanyang UniversityAnsanKorea Department of Robotics Hanyang UniversityAnsanKorea

Cross-project software defect prediction(CPDP)aims to enhance defect prediction in target projects with limited or no historical data by leveraging information from related source *** existing CPDP approaches rely on static metrics or dynamic syntactic features,which have shown limited effectiveness in CPDP due to their inability to capture higher-level system properties,such as complex design patterns,relationships between multiple functions,and dependencies in different software projects,that are important for *** paper introduces a novel approach,a graph-based feature learning model for CPDP(GB-CPDP),that utilizes NetworkX to extract features and learn representations of program entities from control flow graphs(CFGs)and data dependency graphs(DDGs).These graphs capture the structural and data dependencies within the source *** proposed approach employs Node2Vec to transform CFGs and DDGs into numerical vectors and leverages Long Short-Term Memory(LSTM)networks to learn predictive *** process involves graph construction,feature learning through graph embedding and LSTM,and defect *** evaluation using nine open-source Java projects from the PROMISE dataset demonstrates that GB-CPDP outperforms state-of-the-art CPDP methods in terms of F1-measure and Area Under the Curve(AUC).The results showcase the effectiveness of GB-CPDP in improving the performance of cross-project defect prediction.

关键词： Cross-project defect prediction graphs features deep learning graph embedding

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：