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Drug-Target Interactions Prediction Based on Signed Heterogeneous Graph Neural Networks

Chinese Journal of Electronics 2024年第1期33卷 231-244页

作者： Ming CHEN Yajian JIANG Xiujuan LEI Yi PAN Chunyan JI Wei JIANG College of Information Science and Engineering Hunan Normal University School of Computer Science Shaanxi Normal University Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences Computer Science Department BNU-HKBU United International College

Drug-target interactions(DTIs) prediction plays an important role in the process of drug *** computational methods treat it as a binary prediction problem, determining whether there are connections between drugs and targets while ignoring relational types information. Considering the positive or negative effects of DTIs will facilitate the study on comprehensive mechanisms of multiple drugs on a common target, in this work, we model DTIs on signed heterogeneous networks, through categorizing interaction patterns of DTIs and additionally extracting interactions within drug pairs and target protein pairs. We propose signed heterogeneous graph neural networks(SHGNNs), further put forward an end-to-end framework for signed DTIs prediction, called SHGNN-DTI,which not only adapts to signed bipartite networks, but also could naturally incorporate auxiliary information from drug-drug interactions(DDIs) and protein-protein interactions(PPIs). For the framework, we solve the message passing and aggregation problem on signed DTI networks, and consider different training modes on the whole networks consisting of DTIs, DDIs and PPIs. Experiments are conducted on two datasets extracted from Drug Bank and related databases, under different settings of initial inputs, embedding dimensions and training modes. The prediction results show excellent performance in terms of metric indicators, and the feasibility is further verified by the case study with two drugs on breast cancer.

关键词： Drug-target interactions Signed heterogeneous network Link sign prediction Graph neural networks

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VGWO: Variant Grey Wolf Optimizer with High Accuracy and Low Time Complexity

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computers, Materials & Continua 2023年第11期77卷 1617-1644页

作者： Junqiang Jiang Zhifang Sun Xiong Jiang Shengjie Jin Yinli Jiang Bo Fan School of Information Science and Engineering Hunan Institute of Science and TechnologyYueyang414006China Department of Computer and Information Science Linköping UniversityLinköping58183Sweden Department of Safety and Quality Hunan Construction Investment GroupChangsha410004China

The grey wolf optimizer(GWO)is a swarm-based intelligence optimization algorithm by simulating the steps of searching,encircling,and attacking prey in the process of wolf *** with its advantages of simple principle and few parameters setting,GWO bears drawbacks such as low solution accuracy and slow convergence speed.A few recent advanced GWOs are proposed to try to overcome these ***,they are either difficult to apply to large-scale problems due to high time complexity or easily lead to early *** solve the abovementioned issues,a high-accuracy variable grey wolf optimizer(VGWO)with low time complexity is proposed in this *** first uses the symmetrical wolf strategy to generate an initial population of individuals to lay the foundation for the global seek of the algorithm,and then inspired by the simulated annealing algorithm and the differential evolution algorithm,a mutation operation for generating a new mutant individual is performed on three wolves which are randomly selected in the current wolf individuals while after each iteration.A vectorized Manhattan distance calculation method is specifically designed to evaluate the probability of selecting the mutant individual based on its status in the current wolf population for the purpose of dynamically balancing global search and fast convergence capability of VGWO.A series of experiments are conducted on 19 benchmark functions from CEC2014 and CEC2020 and three real-world engineering *** 19 benchmark functions,VGWO’s optimization results place first in 80%of comparisons to the state-of-art GWOs and the CEC2020 competition winner.A further evaluation based on the Friedman test,VGWO also outperforms all other algorithms statistically in terms of robustness with a better average ranking value.

关键词： Intelligence optimization algorithm grey wolf optimizer(GWO) manhattan distance symmetric coordinates

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A Real-time Execution System of Multimodal Transformer through PIM-GPU Collaboration 24

A Real-time Execution System of Multimodal Transformer throu...

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61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Ji, Shengyi Liu, Chubo Ding, Yan Liao, Qing Tang, Zhuo College of Information Science and Engineering Hunan University Changsha China Department of Computer Science and Technology Harbin Institute of Technology Shenzhen China

ISBN: (纸本)9798400706011

Multimodal transformer excels in various applications, but faces great challenges such as high memory consumption and limited data reuse that hinder real-time performance. To address these issues, we propose a processing-in-memory (PIM)-GPU collaboration oriented compiler to accelerate the multimodal transformers. The PIM-GPU collaboration adapts well to multimodal transformers and significantly accelerates model inference. In addition, we introduce a tailored PIM allocation algorithm for variable-length inputs to further improve computation efficiency. Experimental results show that our scheme can achieve an average 15x end-to-end speedup. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Graphics processing unit

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Enhancing data sovereignty to improve intelligent mobility services in smart cities

Urban Governance

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Urban Governance 2025年第1期5卷 20-31页

作者： Anthony, Bokolo Sarshar, Sizarta Department of Applied Data Science Institute for Energy Technology Halden 1777 Norway Department of Computer Science and Communication Østfold University College Halden Norway Department of Risk and Safety Institute for Energy Technology Halden 1777 Norway

Smart cities aim to provide more digitalized, equitable, sustainable, and liveable cities. In smart cities data evolves as an important asset and citizens data in particular is being used to provide data-driven mobility services. Likewise, in smart cities data is produced and used by individuals having no ownership or control over these data thus affecting their security and privacy. Also, actors such as mobility service providers, companies, third parties, etc. often leverage individuals’ data without regarding users’ autonomy. Accordingly, data sovereignty which entails the possibility to govern and keep control over owned data is gaining widespread attention. As a result, stakeholders in the mobility sector need to share data whilst keeping control to manage data access and usage. Although, existing initiatives are promoting sovereign participation using a federated infrastructure. However, achieving an effective governance usage control and access mechanisms can be challenging especially in the transportation sector. It is thus imperative for individuals to have control, ownership, and custody over their data. This has necessitated the notions of data sovereignty. Therefore, this article employs a systematic review to examine how data sovereignty can be achieved for individuals when they use urban mobility services in smart cities by enabling the secure sharing of data by giving control of data over to individuals. Additionally, this article designs a data control scheme that can be applied to realize data sovereign mobility services. Evidence from this study provides technical and non-technical requirements needed in realizing data sovereignty in smart cities. © 2025 The Author(s)

关键词： Data access mechanisms Data governance, Data usage control Data sovereignty Data-driven mobility services Intelligent mobility services Smart cities

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Visual Transformer for Image Splicing Localization 4

Visual Transformer for Image Splicing Localization

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4th International Conference on Big Data and Artificial Intelligence and Software Engineering, ICBASE 2023

作者： Li, Jie Wang, Zuling Hangzhou Normal University Department of Computer Science Hangzhou China Chongqing Vocational Institute of Safety & Technology Department of Network and Information Security Chongqing China

ISBN: (纸本)9798350329490

Image splicing, a prevalent form of image tampering with potential security implications, has prompted the need for reliable models to detect and locate manipulated regions. While convolutional neural network (CNN) based algorithms have shown promise, they often lack global modeling capabilities. In this paper, we propose an end-to-end image splicing and localization network based on a visual Transformer to address the uneven modeling of long-range dependencies between image pixels in existing algorithms. The model incorporates an encoder-decoder architecture that captures pixel relationships and local continuity, leveraging both shallow and deep features through skip connections. Multi-scale features are combined to enhance the accuracy of tampered area localization. The loss function utilizes weighted cross-entropy to locate splicing areas of various sizes and shapes. Evaluation on four public datasets demonstrates significant performance improvements over existing methods, with F1 scores increasing by 33.3%, 21.1%, 9.5%, and 5.4% on the IMD2020, CASIA2.0, Columbia, and NIST16 datasets, respectively. Furthermore, the model exhibits robustness to various post-processing operations. These findings highlight the efficacy of the proposed approach in addressing the challenges associated with image splicing localization. The developed model holds promise for enhancing security measures in image forensics and related applications. © 2023 IEEE.

关键词： Image enhancement

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Implementation of Secure and Verifiable Access Control Procedures using the NTRU Cryptosystem to Store Big Data in the Cloud Environment

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Recent Patents on Engineering 2025年第2期19卷 57-70页

作者： Babu B, Ravindra Saxena, Swati Widjaja, Gunawan Vinodha D, Vedha Omarov, Batyrkhan Ramaiah, Gurumurthy B. Vats, Prashant Adama Ethiopia Department of Computer Science KCG College of Technology Chennai India Universitas Krisnadwipayana Jawa Barat 13077 Indonesia Department of Electronics and Communication Engineering JCT College Of Engineering and Technology Pichanur Coimbatore India International University of Tourism and Hospitality Turkistan Kazakhstan Technical and Vocational Training Institute Addis Ababa Ethiopia Department of Computer Science and Engineering Faculty of Engineering and Technology SGT University Haryana Gurugram India

Background: Due to their complexity and size, deploying ciphertexts for clouds is considered the most useful approach to accessing large data stores. Methods: However, access to a user's access legitimacy and improving a decrypted text on the cloud depending on an improved access policy (AP) specified by the data owner are the key challenges for making large data storage realistic and effective in clouds. The traditional ways either totally remove the problem of AP development or offer renewal to arbiter power, but in real-time, enhancing the AP is essential to maximising security and handling agility. Results: In this patent paper, a safe and verifiable access control program characterised by the NTRU cryptographic system for large storage of data in the clouds is proposed. Primarily, an improved NTRU decryption protocol to deal with the decryption failures of the prime NTRU is established, and in addition, the program is analysed for its security strength and computational performance. When a new AP is specified by the data owner, the cloud server allows the program to improve ciphertext and allows the owner to verify the upgrade to oppose the cloud's fraudulent behaviour. Conclusion: It enables (i) checking the user's legitimacy to access the data owner and qualified users, and (ii) allowing the user to verify the data provided by other users for the recovery of the right user. Strong analysis can prevent and block delinquency from various attacks, namely the collusion attack that could potentially target fraud users. © 2025 Bentham science Publishers.

关键词： Cloud security

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Unveiling the safety Aspects of DevSecOps: Evolution, Gaps and Trends

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Recent Advances in computer science and Communications 2023年第3期16卷 61-69页

作者： Ramaj, Xhesika Sánchez-Gordón, Mary Chockalingam, Sabarathinam Colomo-Palacios, Ricardo Department of Computer Science and Communication Faculty of Computer Sciences Engineering and Economics Østfold University College Halden Norway Department of Risk Safety and Security Institute for Energy Technology Halden Norway

Background: The popularity of DevSecOps is on the rise because it promises to integrate a greater degree of security into software delivery pipelines. However, there is also an unacceptable risk related to safety that cannot be overlooked, given the importance of this aspect in many industries. Objective: The objective of this study is to provide an overview of the safety aspects reported in the literature on DevSecOps. This study also characterizes such aspects and identifies the gaps that may lead to future research work. Methods: A systematic literature review was conducted using five well-known academic databases. The search was executed in September 2021 and March 2022 to identify relevant studies. Results: The search returned 114 academic studies. After the screening process, five primary studies published between 2019 and 2021 were selected. These studies were analyzed thoroughly to identify the safety aspects. Then, we categorized them into three main groups: (i) risk-related safety aspects, (ii) human-related aspects, and (iii) management aspects. Conclusion: safety is an important characteristic that is becoming more critical as the number of critical systems grows. This review reveals that only a scarce number of studies are focusing on safety in DevSecOps. However, those studies gave us some insights into this topic. Therefore, our main observation is that this topic has not yet been completely explored in the academic literature. This review can encourage reflection and discussion between the safety and security communities. © 2023 Bentham science Publishers.

关键词： Accident prevention

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Reflecting on Integrating Team-Based Learning into Project-Based Practical Courses to Enhance Social-Emotional Learning 13th

Reflecting on Integrating Team-Based Learning into Project-B...

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13th International Conference on Frontier Computing, FC 2023

作者： Lin, Ching-Yao Lin, Chih-Che Graduate Institute of Technology and Vocational Education National Taipei University of Technology Taipei Taiwan Department of Computer Science Taipei Municipal Sung-Shan Vocational Industrial-Agricultural Senior High School Taipei Taiwan

ISBN: (纸本)9789819994151

Taiwan’s new 12-year basic education curriculum has been in place for four years. The development of the curriculum is based on the spirit of whole-person education, with "spontaneity, interaction, and mutual benefit" as its philosophy. The spirit of the new curriculum is echoed. Team-Based Learning (TBL) can be described as a unique and powerful form of small-group learning through which teachers can also develop the highest assessable performance of their students, prompting them to show all that they have learned and allowing them to demonstrate their learning. Social-Emotional Learning (SEL) has attracted attention and discussion in the field of K12 education, and in recent years, it has been gradually developed in higher education and adult vocational education and training. In this study, 15 students were divided into 5 groups to promote team-based learning method into the project-based practical course and to participate in project-based competition activities. At the end of the course, 15 students were interviewed qualitatively to observe the development of their SEL. From the qualitative interviews conducted after the activity, it was observed that the students grew in the process of accepting and embracing different ideas, and became more active learners and problem solvers, and the cultivation of cross-disciplinary talents could help develop students’ core competencies. On the other hand, students’ confidence in self-decision making is enhanced through effective interpersonal interactions in TBL. During the process, students explore themselves, increase self-discipline, demonstrate their self-worth, and use interpersonal skills in groups to foster and effectively enhance SEL. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Students

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Provable Data Possession with Outsourced Tag Generation for AI-Driven E-Commerce

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computers, Materials & Continua 2025年第5期83卷 2719-2734页

作者： Yi Li Wenying Zheng Yu-Sheng Su Meiqin Tang School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China School of Computer Science and Technology(School of Artificial Intelligence) Zhejiang Sci-Tech UniversityHangzhou310018China Department of Computer Science and Information Engineering National Chung Cheng UniversityChiayi621301TaiwanChina Advanced Institute of Manufacturing with High-tech Innovations National Chung Cheng UniversityChiayi621301TaiwanChina Department of Computer Science and Engineering National Taiwan Ocean UniversityKeelung202301TaiwanChina School of Integrated Circuits Wuxi Vocational College of Science and TechnologyWuxi214028China

AI applications have become ubiquitous,bringing significant convenience to various *** e-commerce,AI can enhance product recommendations for individuals and provide businesses with more accurate predictions for market strategy ***,if the data used for AI applications is damaged or lost,it will inevitably affect the effectiveness of these AI ***,it is essential to verify the integrity of e-commerce *** existing Provable Data Possession(PDP)protocols can verify the integrity of cloud data,they are not suitable for e-commerce scenarios due to the limited computational capabilities of edge servers,which cannot handle the high computational overhead of generating homomorphic verification tags in *** address this issue,we propose PDP with Outsourced Tag Generation for AI-driven e-commerce,which outsources the computation of homomorphic verification tags to cloud servers while introducing a lightweight verification method to ensure that the tags match the uploaded ***,the proposed scheme supports dynamic operations such as adding,deleting,and modifying data,enhancing its ***,experiments show that the additional computational overhead introduced by outsourcing homomorphic verification tags is acceptable compared to the original PDP.

关键词： Provable data possession data auditing cloud computing e-commerce bloom filter

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Dis-NDVW: Distributed Network Asset Detection and Vulnerability Warning Platform

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computers, Materials & Continua 2023年第7期76卷 771-791页

作者： Leilei Li Yansong Wang Dongjie Zhu Xiaofang Li Haiwen Du Yixuan Lu Rongning Qu Russell Higgs Artificial Intelligence Academy Wuxi Vocational College of Science and TechnologyWuxi214068China School of Computer Science and Technology Harbin Institute of TechnologyWeihai264209China Department of Mathematics Harbin Institute of TechnologyWeihai264209China School of Astronautics Harbin Institute of TechnologyHarbin150001China School of Mathematics and Statistics University College DublinDublinDO4 V1W8Ireland

With the rapid development of Internet technology,the issues of network asset detection and vulnerability warning have become hot topics of concern in the ***,most existing detection tools operate in a single-node mode and cannot parallelly process large-scale tasks,which cannot meet the current needs of the *** address the above issues,this paper proposes a distributed network asset detection and vulnerability warning platform(Dis-NDVW)based on distributed systems and multiple detection ***,this paper proposes a distributed message sub-scription and publication system based on Zookeeper and Kafka,which endows Dis-NDVW with the ability to parallelly process large-scale ***,Dis-NDVW combines the RangeAssignor,RoundRobinAssignor,and StickyAssignor algorithms to achieve load balancing of task nodes in a distributed detection *** terms of a large-scale task processing strategy,this paper proposes a task partitioning method based on First-In-First-Out(FIFO)*** method realizes the parallel operation of task producers and task consumers by dividing pending tasks into different queues according to task *** ensure the data reliability of the task cluster,Dis-NDVW provides a redundant storage strategy for master-slave partition *** terms of distributed storage,Dis-NDVW utilizes a distributed elastic storage service based on ElasticSearch to achieve distributed storage and efficient retrieval of big *** verification shows that Dis-NDVW can better meet the basic requirements of ultra-large-scale detection tasks.

关键词： Distributed network security network asset detection vulnerability warning

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