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arXiv 2020年

作者： Mu, Zihao Castro, Francisco M. Marín-Jiménez, Manuel J. Guil, Nicolás Li, Yan-Ran Yu, Shiqi College of Computer Science and Software Engineering Shenzhen University China Department of Computer Architecture University of Málaga Spain Department of Computing and Numerical Analysis University of Córdoba Spain China Department of Computer Science and Engineering Southern University of Science and Technology China

Gait is a popular biometric pattern used for identifying people based on their way of walking. Traditionally, gait recognition approaches based on deep learning are trained using the whole training dataset. In fact, if new data (classes, view-points, walking conditions, etc.) need to be included, it is necessary to re-train again the model with old and new data samples. In this paper, we propose iLGaCo, the first incremental learning approach of covariate factors for gait recognition, where the deep model can be updated with new information without re-training it from scratch by using the whole dataset. Instead, our approach performs a shorter training process with the new data and a small subset of previous samples. This way, our model learns new information while retaining previous knowledge. We evaluate iLGaCo on CASIA-B dataset in two incremental ways: adding new view-points and adding new walking conditions. In both cases, our results are close to the classical ‘training-from-scratch’ approach, obtaining a marginal drop in accuracy ranging from 0.2% to 1.2%, what shows the efficacy of our approach. In addition, the comparison of iLGaCo with other incremental learning methods, such as LwF and iCarl, shows a significant improvement in accuracy, between 6% and 15% depending on the experiment. Copyright © 2020, The Authors. All rights reserved.

关键词： Gait analysis

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Innovative Approaches in Network architecture: Enhancing Connectivity and Performance in the Era of 5G and Beyond

Innovative Approaches in Network Architecture: Enhancing Con...

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Sustainable Communication Networks and Application (ICSCNA), International Conference on

作者： Sunita Pachar Satti Sudha Mohan Reddy Lakshmi Narasimhan Srinivasagopalan Balla Mounica B Srinivasa Rao Sivakoteswararao Katta IBM Department GLA University Department of ECE SRKR Engineering College India Software Development Enterprise Architecture Plano TX USA Computer Science and Engineering (AI&ML) Vignan Institute of Technology and Science Hyderabad Ace Engineering College Hyderabad Department of Mechanical KIETW Kakinada

ISBN: (数字)9798331530013

ISBN: (纸本)9798331530020

This research study examines the evolving ecosystem of network applications for enhancing connectivity and performance in 5G and beyond (B5G) networks. The objective is to streamline large-scale deployment of vertical applications through a middleware layer, facilitating interactions among network operators and third parties based on varying trust levels. The proposed model addresses the complexity and computational demands of enabling adaptable, secure, and scalable applications for diverse 5G platforms. In particular, this study highlights the 5G-EPICENTRE project, which enables traffic management and dynamic control, especially for missioncritical Public Protection and Disaster Relief (PPDR) applications. By optimizing resource allocation, the model reduces computational costs while meeting the unique demands of PPDR services, such as high-quality video and data for emergency operations. The model's effectiveness will be evaluated through experiments leveraging 5G Core (5GC) control-plane capabilities, with a focus on quality of service (QoS) and latency. Practical limitations, including the integration challenges of multi-network APIs, are discussed in the conclusion.

关键词： Adaptation models 5G mobile communication Computational modeling Scalability Ecosystems Quality of service Telecommunications Complexity theory Resource management Protection

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Large Language Model-Based Optimization for System-Level Test Program Generation

Large Language Model-Based Optimization for System-Level Tes...

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IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems

作者： Denis Schwachhofer Peter Domanski Steffen Becker Stefan Wagner Matthias Sauer Dirk Pflüger Ilia Polian Institute of Computer Engineering and Computer Architecture University of Stuttgart Stuttgart Germany Institute of Software Engineering University of Stuttgart Stuttgart Germany Institute for Parallel and Distributed Systems University of Stuttgart Stuttgart Germany Technical University of Munich Heilbronn Germany Advantest Europe Boeblingen Germany

ISBN: (数字)9798350366884

ISBN: (纸本)9798350366891

System-Level Test (SLT) is essential for testing integrated circuits, focusing on functional and non-functional properties of the Device under Test (DUT). Traditionally, test engineers manually create tests with commercial software to simulate the DUT's end-user environment. This process is both time-consuming and offers limited control over non-functional properties. This paper proposes Large Language Models (LLMs) enhanced by Structural Chain of Thought (SCoT) prompting, a temperature schedule, and a pool of previously generated snippets to generate high-quality code snippets for SLT. We repeatedly query the LLM for a better snippet using previously generated snippets as examples, thus creating an iterative optimization loop. This approach can automatically generate snippets for SLT that target specific non-functional properties, reducing time and effort. Our findings show that this approach improves the quality of the generated snippets compared to unstructured prompts containing only a task description.

关键词： Measurement Schedules Codes Temperature Process control Very large scale integration software Optimization Nanotechnology Testing

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Hardware/software co-design for high performance computing: Challenges and opportunities

Hardware/software co-design for high performance computing: ...

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作者： Hu, X. Sharon Murphy, Richard C. Dosanjh, Sudip Olukotun, Kunle Poole, Stephen Department of Computer Science and Engineering University of Notre Dame Notre Dame IN United States Scalable Computer Architecture Department Sandia National Laboratories Albuquerque NM United States Computer and Software Systems Department Sandia National Laboratories Albuquerque NM United States Department of Electrical Engineering Stanford University Stanford CA United States Computational Sciences Division Oak Ridge National Lab. Oak Ridge TN United States

ISBN: (纸本)9781605589053

This special session aims to introduce to the hardware/software codesign community challenges and opportunities in designing high performance computing (HPC) systems. Though embedded system design and HPC system design have traditionally been considered as two separate areas of research, they in fact share quite some common features, especially as CMOS devices continue along their scaling trends and the HPC community hits hard power and energy limits. Understanding the similarities and differences between the design practices adopted in the two areas will help bridge the two communities and lead to design tool developments benefiting both communities. © 2010 ACM.

关键词： Hardware-software codesign

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Large Language Models to Generate System-Level Test Programs Targeting Non-functional Properties

arXiv

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arXiv 2024年

作者： Schwachhofer, Denis Domanski, Peter Becker, Steffen Wagner, Stefan Sauer, Matthias Pflüger, Dirk Polian, Ilia Institute of Software Engineering University of Stuttgart Stuttgart Germany Institute for Parallel and Distributed Systems University of Stuttgart Stuttgart Germany Advantest Europe Boeblingen Germany Institute of Computer Engineering and Computer Architecture University of Stuttgart Stuttgart Germany Technical University of Munich Heilbronn Germany

System-Level Test (SLT) has been a part of the test flow for integrated circuits for over a decade and still gains importance. However, no systematic approaches exist for test program generation, especially targeting non-functional properties of the Device under Test (DUT). Currently, test engineers manually compose test suites from off-the-shelf software, approximating the end-user environment of the DUT. This challenging and tedious task does not guarantee sufficient control over non-functional properties. This paper proposes Large Language Models (LLMs) to generate test programs. We take a first glance at how pre-trained LLMs perform in test program generation to optimize nonfunctional properties of the DUT. Therefore, we write a prompt to generate C code snippets that maximize the instructions per cycle of a super-scalar, out-of-order architecture in simulation. Additionally, we apply prompt and hyperparameter optimization to achieve the best possible results without further training. © 2024, CC BY.

关键词： software testing

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Temperature-aware software-based self-testing for delay faults 15

Temperature-aware software-based self-testing for delay faul...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Ying Zhang Zebo Peng Jianhui Jiang Huawei Li Masamro Fujita School of Software Engineering Tongji University China Embedded Systems Lab Linköping University Sweden State Key Laboratory of Computer Architecture Chinese Academy of Sciences China VLSI Design and Education Center University of Tokyo Japan

ISBN: (纸本)9783981537048

Delay defects under high temperature have been one of the most critical factors to affect the reliability of computer systems, and the current test methods don't address this problem properly. In this paper, a temperature-aware software-based self-testing (SBST) technique is proposed to self-heat the processors within a high temperature range and effectively test delay faults under high temperature. First, it automatically generates high-quality test programs through automatic test instruction generation (ATIG), and avoids over-testing caused by nonfunctional patterns. Second, it exploits two effective powerintensive program transformations to self-heat up the processors internally. Third, it applies a greedy algorithm to search the optimized schedule of the test templates in order to generate the test program while making sure that the temperature of the processor under test is within the specified range. Experimental results show that the generated program is successful to guarantee delay test within the given temperature range, and achieves high test performance with functional patterns.

关键词： Delays Program processors Temperature distribution Power dissipation Circuit faults Schedules

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Exploring the Potential of 3d Printing Technology for Sustainable Plastic Roads: A Preliminary Investigation

SSRN

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SSRN 2023年

作者： Al-Atroush, Mohamed Ezzat Almushcab, Jumana Alhudaif, Duha Meskinyar, Yosra Civil and Environmental Engineering Program College of Engineering Prince Sultan University Riyadh11543 Saudi Arabia Software Engineering College of Computer and Information Systems Prince Sultan University Riyadh11543 Saudi Arabia Architectural Engineering Department College of Architecture and Design Prince Sultan University Riyadh11543 Saudi Arabia

The urgency of climate change has highlighted the need for sustainable road construction materials, replacing the conventional asphalt that significantly contributes to global warming and the urban heat island effect. With that in mind, the construction of the world's first 30-meter plastic road in Zwolle, Netherlands, in 2018 opened the door for novel plastic applications as paving materials. However, the current application is still limited to sidewalks and light-loaded cycling lanes. This preliminary study investigated the feasibility of using 3D printing technology to provide the required structural design flexibility for manufacturing plastic pavement modules able to sustain heavy traffic and extreme weather conditions. The suitability of six plastic materials for 3D printing was evaluated. Polylactic Acid (PLA), and Polyethylene Terephthalate Glycol (PETG) were identified as the most suitable materials for this study. Three small-scale structural systems, namely hollow modular with plastic columns, hollow modular with solid plastic cones, and hollow modular with X-bracing, were designed and successfully printed using the adopted materials and a 3D printer. The developed systems were then tested under compression to evaluate their structural performance under heavy traffic loads and prove the concept. The results showed that the PLA conic structural system was effective and exhibited the highest compression strength, while PETG conic system exhibited ductile behavior with superior thermal stability. The study suggested that the hybrid system of PLA and PETG materials may improve overall performance, combine flexibility and strength, and potentially improve resistance to extreme weather and heavy traffic. These findings proved that 3D printing technology has the potential to revolutionize the road construction industry and provide more sustainable solutions for infrastructure development. © 2023, The Authors. All rights reserved.

关键词： Plastic bottles

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Analytical Model of Customer Churn Based on Bayesian Network

Analytical Model of Customer Churn Based on Bayesian Network

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International Conference on Computational Intelligence and Security

作者： Peng Sun Xin Guo Yunpeng Zhang Ziyan Wu College of Computer Science Northwestern Polytechnical University Xi'an Shaanxi Province China Civil Engineering Institute Xi'an University of Architecture and Technology Xi'an Shaanxi Province China School of Software and Microelectronics Northwestern Polytechnical University Xi'an Shaanxi Province China School of Mechanics Civil Engineering & Architecture Northwestern Polytechnical University Xi'an Shaanxi Province China

A customer churn analytical model based Bayesian network is built for prediction of customer churn. We propose Bayesian Network approaches to predict churn motivation, mining the result in churn characters in order to help decision-making manager formulate corresponding detainment strategy. Experimental results show that classification performance of both methods is resultful.

关键词： Mathematical model Bayes methods Educational institutions Predictive models Analytical models Broadband communication Companies

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Dynamic Resource Allocation Based on User experience in Virtualized Servers

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Procedia engineering 2011年 15卷 3780-3784页

作者： Wei Zhang Jiajun Liu Ying Song Mingfa Zhu Limin Xiao Yuzhong Sun Li Ruan State Key Laboratory of Software Development Environment Beijing 100191 China School of Computer Science and Engineering Beihang University Beijing 100191 China Key Laboratory of Computer System and Architecture Chinese Academy of SciencesBeijing Institute of Computing Technology Chinese Academy of Sciences Beijing China

Web workloads are known to vary dynamically with time which poses a challenge to resource allocation among the applications. In this paper, we argue that the existing dynamic resource allocation based on resource utilization has some drawbacks in virtualized servers. Dynamic resource allocation directly based on real-time user experience is more reasonable and also has practical significance. To address the problem, we propose a system architecture that combines real time measurements and analysis of user experience for resource allocation. We evaluate our proposal using Webbench. The experiment results show that these techniques can judiciously allocate system resources.

关键词： resource allocation virtualized servers user experience

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A Broadly Applicable Coarse Alignment Framework for the Point Cloud of Hull Blocks

SSRN

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SSRN 2023年

作者： Huo, Shilin Liu, Yujun Wang, Ji Li, Rui Liu, Xiao School of Naval Architecture and Ocean Engineering Dalian University of Technology Dalian China Collaborative Innovation Center for Advanced Ship and Deep-sea Exploration China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment China

The Terrestrial Laser Scanning (TLS) technology, which has been widely used in recent years, provides a new approach to control the construction quality of hull blocks in shipyards. As the cloud-model registration problem plays the most significant role in the data processing stage of utilizing the TLS devices, this paper concentrates on developing a broadly applicable coarse alignment framework for the point cloud of hull blocks. This framework involves two steps: the recognition of the connection regions of the point clouds, and the coarse registration method according to the classification results. To detect the connection regions automatically, a hand-crafted simple model of the connection regions of hull blocks is built and its supporting detection method is proposed, besides, consider the recent overwhelming success of deep learning methods, a deep learning network suitable for large hull block data sets is constructed according to the Point-Net and convolutional neural networks paradigms. Then, the coarse alignment method based on the detected connection regions is proposed. Experimental results illustrate the good performance of the proposed framework. © 2023, The Authors. All rights reserved.

关键词： Deep learning

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