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2022 IEEE SmartWorld, 19th IEEE International Conference on Ubiquitous Intelligence and Computing, 2022 IEEE International Conference on Autonomous and Trusted Vehicles Conference, 22nd IEEE International Conference on Scalable Computing and Communications, 2022 IEEE International Conference on Digital Twin, 8th IEEE International Conference on Privacy Computing and 2022 IEEE International Conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Zhang, Siyuan Ouyang, Yuanxin Liu, Zhuang Rong, Wenge Xiong, Zhang Beihang University State Key Laboratory of Software Development Environment Beijing China Beihang University Engineering Research Center of Advanced Computer Application Technology Ministry of Education Beijing China

ISBN: (纸本)9798350346558

Introducing knowledge graphs (KGs) into the recommender systems not only improves their performance but also enhances the interpretability. However, most KG-based recommendation methods have the problem of inefficiency and ex-post explanation, which reinforcement learning (RL) methods can solve properly. Most existing RL-based methods for explainable recommendations only consider positive rewards when designing the reward part of the RL environment, which is defective and misleads the policy of the RL agent. To address this problem, we propose Reinforced Knowledge Graph Reasoning with Reinforced Negative Sampling (RKGR-RNS) by introducing a negative sampling method into RL-based recommendation, which refines the reward mechanism to help optimize the agent's policy. And a judge module is proposed to improve the performance of the recommender system further. Experiments on three real datasets demonstrate that our method is better than the state-of-the-art baseline. © 2022 IEEE.

关键词： Reinforcement learning

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A Pattern Language of Multi-Organizational Collaboration in Public Sector in Developing Countries 22

A Pattern Language of Multi-Organizational Collaboration in ...

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Proceedings of the 29th Conference on Pattern Languages of Programs

作者： Haji Gul Wahaj Valentino Vranić Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava

ISBN: (纸本)9781941652183

Researchers have extensively discussed the importance of collaborative efforts between public organizations, especially in developing countries. For outsourcing projects to be delivered successfully, collaboration is seen as a vital business trait. Due to low economy in often developing countries, several public organizations may not have access to the required resources. Therefore, sharing the resources, expertise, and lessons learned could be a good practice for governments, particularly in developing nations. Several public organizations are assigned individual tasks and responsibilities in different sectors. Collaboration with other public organizations might be facilitated by sharing infrastructure, public data, consultations, computer networks, lessons learned, and building capacity of stakeholders. Despite lack of resources, public organizations distributed across the country faced other obstacles such as inadequate infrastructure for collaboration. This study discusses a comprehensive collaboration between public organizations to share existing resources with other public organizations. During this study, we attempt to document some newly observed organizational patterns. We interlink them into a language that can assist both researchers and practitioners in understanding how to convince public organizations to collaborate.

关键词： collaboration developing countries organizational patterns patterns public sector software development software engineering

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CADEC: A Combinatorial Auction for Dynamic Distributed DNN Inference Scheduling in Edge-Cloud Networks

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IEEE Transactions on Mobile Computing 2025年

作者： Xu, Xiaolong Hu, Yuhao Cui, Guangming Qi, Lianyong Dou, Wanchun Nanjing University of Information Science and Technology School of Software Nanjing210044 China Nanjing University of Information Science and Technology Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services School of Software China Nanjing University State Key Laboratory for Novel Software Technology China College of Computer science and technology Qingdao China Georgia State University Department of Computer Science United States

Deep Neural Network (DNN) Inference, as a key enabler of intelligent applications, is often computation-intensive and latency-sensitive. Combining the advantages of cloud computing (abundant computing resources) and edge computing (fast transmission), edge-cloud collaborative DNN inference is a powerful solution to these problems. However, in edge-cloud networks with heterogeneous resources, how to obtain reasonable decisions on server selection, model partition and resource allocation for efficient distributed DNN inference is a hard challenge. Furthermore, it is non-trivial to design suitable resource prices to maximize the social welfare. These challenges even escalate in dynamic edge-cloud networks where decisions should be generated as soon as each user arrives without future information. Therefore, we design a combinatorial auction for dynamic distributed DNN inference scheduling, named CADEC. CADEC first constructs a bid set for each user based on convex optimization theory for optimal solution searching. Next, prices of resources in the edge-cloud network are adjusted according to changes in supply-demand relationship, and whether to admit the request of each user is decided. Finally, the dynamic distributed inference scheduling decisions are generated through the primal-dual algorithm to maximize the social welfare. Theoretical analysis shows the good competitive ratio and polynomial time complexity of CADEC. Results of simulation experiments present that CADEC improves social welfare by up to 46% compared with state-of-the-art distributed DNN inference schemes. © 2002-2012 IEEE.

关键词： Convex optimization

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Complementary Learning System Based Intrinsic Reward in Reinforcement Learning

Complementary Learning System Based Intrinsic Reward in Rein...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zijian Gao Kele Xu Hongda Jia Tianjiao Wan Bo Ding Dawei Feng Xinjun Mao Huaimin Wang National University of Defense Technology Changsha China Key Laboratory of Software Engineering for Complex Systems Changsha China

Deep reinforcement learning has achieved encouraging performance in many realms. However, one of its primary challenges is the sparsity of extrinsic rewards, which is still far from solved. Complementary learning system theory suggests that effective human learning relies on two complementary learning systems utilizing short-term and long-term memories. Inspired by the fact that humans evaluate curiosity by comparing current observations with historical information, we propose a novel intrinsic reward, namely CLS-IR, which aims to address the problems caused by sparse extrinsic rewards. Specifically, we train a self-supervised predictive model with short-term and long-term memories via exponential moving averages. We employ the information gain between the two memories as the intrinsic reward, which does not incur additional training costs but leads to better exploration. To investigate the effectiveness of CLS-IR, we conduct extensive experimental evaluations; the results demonstrate that CLS-IR can achieve state-of-the-art performance on Atari games and DeepMind Control Suite.

关键词： Learning systems Training Deep learning Costs Reinforcement learning Games Signal processing

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An innovative Galerkin scheme based on anisotropic trilinear immersed finite elements for the magnetized plasma diffusion problem with plasma sheath interface

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Computers and Mathematics with Applications 2025年 192卷 155-171页

作者： Wang, Ziping Xia, Guangqing Han, Yajie Lu, Chang Zhang, Lin Xu, Gang State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment Dalian University of Technology Dalian 116024 China Key Laboratory of Advanced Technology for Aerospace Vehicles of Liaoning Province Dalian University of Technology Dalian116024 China Collaborative Innovation Center of Micro & Nano Satellites of Hebei Province North China Institute of Aerospace Engineering Langfang065000 China Suzhou Industry CFD Development Central China Co. Ltd. &CISC Suzhou215100 China School of Mathematical Sciences Mathematical Institute Nanjing Normal University Nanjing210023 China

Via introducing the Robin flux jump into the Galerkin scheme, this paper develops a new anisotropic trilinear immersed finite element (IFE) method for solving the magnetized plasma diffusion problem with plasma sheath interface condition under Cartesian meshes. The three-dimensional (3D) diffusion process of magnetized plasma is anisotropic and highly sensitive to magnetic fields, making it difficult to efficiently solve by commonly used body fitted mesh methods when the simulation domain has complex boundary conditions. Even worse, the plasma sheath boundary will further exacerbates its solving difficulty. The presented method first utilizes the anisotropic trilinear IFE basis functions describing the diffusion of magnetized plasma in interface elements. Then the trilinear IFE basis functions are used to handle the plasma sheath interface conditions, i.e. the Robin flux jump conditions. As for the other non interface elements, the traditional trilinear basis functions are used. On this basis, a new Galerkin scheme is derived and applied to efficiently solving the plasma anisotropic diffusion problem with the Robin flux jump interfaces in Cartesian meshes. The proposed method can also solve other types of elliptical interface problems via controlling the coefficients. Moreover, the orthogonal meshes makes it convenient to couple other Cartesian mesh based methods, such as the particle-in-cell method, which provides an advanced tool for solving plasma transport problems. Numerical experiments are provided to demonstrate the proposed method and show the applicability in the simulations of actual engineering issues. © 2025 Elsevier Ltd

关键词： Plasma sheaths

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Denoising Diffusion Model-Based Channel Estimation in IRS-Assisted ISAC systems 16

Denoising Diffusion Model-Based Channel Estimation in IRS-As...

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16th International Conference on Wireless Communications and Signal Processing, WCSP 2024

作者： Yi, Lan Miao, Jiansong Zhang, Tao Yuan, Zhenhui Kang, Jiawen Niyato, Dusit Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks Beijing China School of Software Engineering Beijing Jiaotong University Beijing China School of Engineering University of Warwick CV4 7AL United Kingdom School of Automation Guangdong University of Technology Guangzhou China School of Computer Science and Engineering Nanyang Technological University Singapore Singapore

ISBN: (纸本)9798350390643

In Integrated Sensing and Communications (ISAC) systems assisted by Intelligent Reflecting Surfaces (IRS), precise channel estimation is crucial for optimal system performance and maximizing the potential benefits. The estimation problem, however, becomes intricate due to complex channel coupling and specific environmental conditions. This paper addresses these challenges by formulating channel estimation as a denoising problem and proposing a novel diffusion-based framework. This approach mitigates the impact of ill-posedness, which is typically problematic for general neural network (NN)-based techniques. By modeling the joint distribution and sampling from the learned posterior distribution, we accurately recover the channel coefficients from noisy pilot-based observations. Simulation results demonstrate significant performance improvements of the proposed method compared to both least-squares and NN-based benchmarks. Moreover, thanks to the carefully designed architecture and residual prediction strategy, the number of sampling steps in the diffusion reverse process is greatly reduced, enabling real-time CSI acquisition. © 2024 IEEE.

关键词： Least squares approximations

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GUIDE: LLM-Driven GUI Generation Decomposition for Automated Prototyping

GUIDE: LLM-Driven GUI Generation Decomposition for Automated...

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International Conference on software engineering - Companion, ICSE, Companion

作者： Kristian Kolthoff Felix Kretzer Christian Bartelt Alexander Maedche Simone Paolo Ponzetto Institute for Software and Systems Engineering Clausthal University of Technology Clausthal Germany Human-Centered Systems Lab Karlsruhe Institute of Technology Karlsruhe Germany Data and Web Science Group University of Mannheim Mannheim Germany

ISBN: (数字)9798331536831

ISBN: (纸本)9798331536848

Graphical user interface (GUI) prototyping serves as one of the most valuable techniques for enhancing the elicitation of requirements, facilitating the visualization and refinement of customer needs and closely integrating the customer into the development activities. While GUI prototyping has a positive impact on the software development process, it simultaneously demands significant effort and resources. The emergence of Large Language Models (LLMs) with their impressive code generation capabilities offers a promising approach for automating GUI prototyping. Despite their potential, there is a gap between current LLM-based prototyping solutions and traditional user-based GUI prototyping approaches which provide visual representations of the GUI prototypes and direct editing functionality. In contrast, LLMs and related generative approaches merely produce text sequences or non-editable image output, which lacks both mentioned aspects and therefore impede supporting GUI prototyping. Moreover, minor changes requested by the user typically lead to an inefficient regeneration of the entire GUI prototype when using LLMs directly. In this work, we propose GUIDE, a novel LLM-driven GUI generation decomposition approach seamlessly integrated into the popular prototyping framework Figma. Our approach initially decomposes high-level GUI descriptions into fine-granular GUI requirements, which are subsequently translated into Material Design GUI prototypes, enabling higher controllability and more efficient adaption of changes. To efficiently conduct prompting-based generation of Material Design GUI prototypes, we propose a retrieval-augmented generation (RAG) approach to integrate the component library. Our preliminary evaluation demonstrates the effectiveness of GUIDE in bridging the gap between LLM generation capabilities and traditional GUI prototyping workflows, offering a more effective and controlled user-based approach to LLM-driven GUI prototyping. Video presentation

关键词： Visualization Translation Large language models Retrieval augmented generation Prototypes Controllability Libraries Graphical user interfaces software engineering software development management

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Recurring Structures of Subcontract Management in System Outsourcing 22

Recurring Structures of Subcontract Management in System Out...

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Proceedings of the 29th Conference on Pattern Languages of Programs

ISBN: (纸本)9781941652183

Despite numerous efforts to address system outsourcing problems in the subcontract management system, the existing available solutions do not appear to be sufficient. They are fragmented into individual patterns, neither composing legible pattern languages to address the subcontract management systems nor being integrated into comprehensive pattern languages for managing system outsourcing in general. Communication among stakeholders is another issue that takes a long time because of their naturally hierarchical or multi-layered structure. And usually, false information reaches the sub-contractor at the bottom of the chain, which affects a project, and causes delays in deliverables. We attempt to overcome these problems by providing a set of four organizational patterns for the subcontract management system. Using them in combination with other available patterns and practices, we demonstrate a pattern language for better communication among different involved organizations. This paper focuses on better relationships between stakeholders. The relationships contain an inter-organizational communication and coordination among the stakeholders. A pattern story of a real case illustrates the overall use of this pattern language.

关键词： multi-sourcing organizational patterns patterns software engineering subcontract management system outsourcing

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Building Customer Capacity Through Organizational Patterns Improves the Development Team's Understanding 22

Building Customer Capacity Through Organizational Patterns I...

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Proceedings of the 29th Conference on Pattern Languages of Programs

作者： Mohammad Ismail Khattab Valentino Vranić Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava

ISBN: (纸本)9781941652183

The development team needs to work together with a customer who has a basic understanding of information technology. Customers need to be aware of the business processes and the importance of technology. A customer and the development team need to communicate and understand each other in the software project's development. software projects can be successfully built when the customer has sufficient capacity. The process of building an organization's strength and sustainability is called capacity-building. software projects are more effective and quality when capacity development takes place at the organizational level. Capacity directly affects work performance and business outcomes. Due to low customer capacity, we have found in practice and in the literature that False Requirements, No Basic technology Knowledge, No Domain Knowledge, Mismanaged Timeline, No Trust in software Project, and Unproductive Discussion are the main customer capacity challenges to the software project development team. We documented our experiences and five newly discovered patterns in government organizations to solve the mentioned challenges. We present this documented experience in the form of patterns in this paper to improve the customer capacity Before work begins on a software project or during the software development process. Some organizational patterns that reduce the mentioned challenges are also used along with newly discovered patterns. We have illustrated the sequences of the patterns and explained how we could make a pattern language from these patterns.

关键词： customer customer capacity building development team organizational patterns patterns software projects

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Task-Specific Alignment and Multiple-Level Transformer for Few-Shot Action Recognition

SSRN

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SSRN 2023年

作者： Guo, Fei Zhu, Li Wang, YiKang Sun, Jing School of Software Engineering Xi’an Jiaotong University China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China

In the research field of few-shot learning, the main difference between image-based and video-based is the additional temporal dimension. In recent years, some works have used the Transformer to deal with frames, then get the attention feature and the enhanced prototype, and the results are competitive. However, some video frames may relate little to the action, and only using single frame-level or segment-level features may not mine enough information. We address these problems sequentially through an end-to-end method named "Task-Specific Alignment and Multiple-level Transformer Network (TSA-MLT)". The first module (TSA) aims at filtering the action-irrelevant frames for action duration alignment. Affine Transformation for frame sequence in the time dimension is used for linear sampling. The second module (MLT) focuses on the Multiple-level feature of the support prototype and query sample to mine more information for the alignment, which operations on different level features. We adopt a fusion loss according to a fusion distance that fuses the L2 sequence distance, which focuses on temporal order alignment, and the Optimal Transport distance, which focuses on measuring the gap between the appearance and semantics of the videos. Extensive experiments show our method achieves state-of-the-art results on the HMDB51 and UCF101 datasets and a competitive result on the benchmark of Kinetics and something-2-something V2 datasets. Our code will be available at the URL: https://***/cofly2014/***. © 2023, The Authors. All rights reserved.

关键词： Alignment

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