检索结果-内蒙古大学图书馆

International Conference on Electronics, Computers and Artificial Intelligence (ECAI)

作者： Shaidah Jusoh Hejab Al Fawareh School of Electrical Engineering and Artificial Intelligence Xiamen University Malaysia Sepang Selangor Malaysia School of Computing and Data Science) Xiamen University Malaysia Sepang Selangor Malaysia

AI games are one of the growing fields along with the advancement of computing technologies. Many computer games have been deployed as AI games. To the best of our knowledge, there is no clear category of algorithms used for AI games. The aim of this paper is to survey and classify AI games according to their algorithms. In this paper, AI games are classified into two categories: AI games that have been developed using traditional AI methods and AI games that have used machine learning (ML) approaches. The classifications highlight genres, techniques, and approaches used in game development. Researchers and developers in the field of AI games can use this paper as a quick reference to further explore the use of AI and ML algorithms in games.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An ADRC-Incorporated Stochastic Gradient Descent Algorithm for Latent Factor Analysis

arXiv

引用

arXiv 2024年

作者： Li, Jinli Yuan, Ye The School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing400065 China The Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Engineering Research Center of Big Data Application for Smart Cities Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing400714 China The College of Computer and Information Science Southwest University Chongqing400715 China

High-dimensional and incomplete (HDI) matrix contains many complex interactions between numerous nodes. A stochastic gradient descent (SGD)-based latent factor analysis (LFA) model is remarkably effective in extracting valuable information from an HDI matrix. However, such a model commonly encounters the problem of slow convergence because a standard SGD algorithm only considers the current learning error to compute the stochastic gradient without considering the historical and future state of the learning error. To address this critical issue, this paper innovatively proposes an ADRC-incorporated SGD (ADS) algorithm by refining the instance learning error by considering the historical and future state by following the principle of an ADRC controller. With it, an ADS-based LFA model is further achieved for fast and accurate latent factor analysis on an HDI matrix. Empirical studies on two HDI datasets demonstrate that the proposed model outperforms the state-of-the-art LFA models in terms of computational efficiency and accuracy for predicting the missing data of an HDI matrix. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

Boosting Meaningful Dependency Mining with Clustering and Covariance Analysis

Boosting Meaningful Dependency Mining with Clustering and Co...

引用

International Conference on data Engineering

作者： Xi Wang Ruochun Jin Wanrong Huang Yuhua Tang Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha China Department of Intelligent Data Science College of Computer Science and Technology National University of Defense Technology Changsha China

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

Functional dependencies (FDs) form a valuable ingredient for various data management tasks. However, existing methods can hardly discover practical and interpretable FDs, especially in large noisy real-life datasets. This paper studies the problem of discovering meaningful functional dependencies (FDms) that utilize support and error parameters to capture interesting dependencies in such datasets and proposes an efficient discovery algorithm called FDMε. In order to scale with large datasets, FDM ε employs an efficient sampling method with accuracy guarantees to capture the differences between tuple pairs and to quantify the connection between support/error of dependencies on samples and those on the entire dataset. Moreover, it adopts a clustering-based correlated attributes extraction to divide the exponentially large search space into multiple small sub-spaces and proposes an easy-first traversal strategy with covariance-based guidance that quickly detects candidate dependencies and validates them. Additionally, we prove a covariance lower bound as an additional pruning criterion to reduce the search space. Extensive experiments on real-life and synthetic datasets demonstrate that FDM ε is 14 times faster than existing discovery algorithms on average, up to 31 times, and scales to larger datasets with the least memory cost.

关键词： Accuracy Costs Clustering algorithms Search problems data engineering Noise measurement Frequency division multiplexing

来源：评论

学校读者我要写书评

暂无评论

Intelligent New Energy Vehicle Battery Swap Scheme based on Blockchain Technology 23

Intelligent New Energy Vehicle Battery Swap Scheme based on ...

引用

Proceedings of the 2023 5th International Conference on Blockchain Technology

作者： Ya Han Jianbo Gao Zhi Guan Zhong Chen Lifeng Ren School of Computer Science Peking University China and Peking University Chongqing Research Institute of Big Data China National Engineering Research Center for Software Engineering Peking University China Peking University Chongqing Research Institute of Big Data China

ISBN: (纸本)9798400708930

With the development of electric vehicle technology, electric vehicles surpass fuel vehicles in terms of power performance and intelligence, and the cruising range has also increased to more than 400km with the increase of battery energy density and power consumption. However, the overall is still facing the problem of energy refueling anxiety, and the fuel vehicle refueling time is 5 minutes, and the current fast charge takes at least 60 minutes. The waiting time for charging during peak hours has also been further lengthened. Increasing the speed of energy replenishment has become an urgent need for new energy vehicle owners. The way electric vehicles are supplied with energy is fundamentally different from that of traditional cars. The battery swap mode naturally separates the vehicle and electricity, providing the possibility for novel business models (vehicle electricity separation, battery sharing). Let the battery return to its "energy carrier" use attribute, realize the sharing of batteries, create conditions for battery financialization, carry out full life cycle value management of batteries, implement battery gradient utilization, and provide a feasible path for future energy storage business. However, in battery swap mode, there are many divisions of responsibilities. For example, if the battery burns the car, should I find the main engine factory or the power exchange company/high-voltage electrical failure after the power exchange, especially when the responsibility is not clear, who will check and repair. This paper proposes a new energy vehicle monitoring platform based on blockchain technology, which can manage the whole process life cycle of new energy batteries through blockchain traceability technology. At the same time, according to the current responsibility division system, the transparent division of responsibilities is realized in combination with blockchain smart contracts.

关键词： Battery swap mode Blockchain New energy Responsibility division

来源：评论

学校读者我要写书评

暂无评论

Quantum-Inspired Distributed Memetic Algorithm

引用

Complex System Modeling and Simulation 2022年第4期2卷 334-353页

作者： Guanghui Zhang Wenjing Ma Keyi Xing Lining Xing Kesheng Wang the School of Information Science and Technology and the Hebei Key Laboratory of Agricultural Big Data Hebei Agricultural UniversityBaoding 071001China the School of Information Science and Technology Hebei Agricultural UniversityBaoding 071001China. the State Key Laboratory for Manufacturing System Engineering and the Systems Engineering Institute Xi’an Jiaotong UniversityXi’an 710049China the School of Electronic Xidian UniversityXi’an 710071China the Department of Production and Quality Engineering Norwegian University of Science and TechnologyTrondheim 7491Norway

This paper proposed a novel distributed memetic evolutionary model,where four modules distributed exploration,intensified exploitation,knowledge transfer,and evolutionary restart are coevolved to maximize their strengths and achieve superior global *** exploration evolves three independent populations by heterogenous *** exploitation evolves an external elite archive in parallel with exploration to balance global and local *** transfer is based on a point-ring communication topology to share successful experiences among distinct search *** restart adopts an adaptive perturbation strategy to control search diversity *** computation is a newly emerging technique,which has powerful computing power and parallelized ***,this paper further fuses quantum mechanisms into the proposed evolutionary model to build a new evolutionary algorithm,referred to as quantum-inspired distributed memetic algorithm(QDMA).In QDMA,individuals are represented by the quantum characteristics and evolved by the quantum-inspired evolutionary optimizers in the quantum *** QDMA integrates the superiorities of distributed,memetic,and quantum *** experiments are carried out to evaluate the superior performance of *** results demonstrate the effectiveness of special designs and show that QDMA has greater superiority compared to the compared state-of-the-art algorithms based on Wilcoxon’s rank-sum *** superiority is attributed not only to good cooperative coevolution of distributed memetic evolutionary model,but also to superior designs of each special component.

关键词： distributed evolutionary algorithm memetic algorithm quantum-inspired evolutionary algorithm quantum distributed memetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Hybrid Visual Verification

Hybrid Visual Verification

引用

International Conference on Confluence The Next Generation Information Technology Summit (Confluence)

作者： S.Nikkath Bushra A. Syed Ismail P. Sasigresa Edwin Singh C Department of Computing Technologies SRM Institute of Scienece and Technology KattankulathurChengalpattu India Department of Data Science and Business Systems SRM Institute of Scienece and Technology KattankulathurChengalpattu India Department: Computer Science and Engineering Veltech University Department: Computer Science and Engineering Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology

data security is becoming increasingly important as cloud computing advances. data security is the fundamental problem of all distributed computing systems. Cloud computing enables access to distributed applications and services belonging to various organizations spread across different locations. Cloud computing raises security concerns, because it shares data with distributed users via network in an open terrain. In this system, some of the most important security services like image-based security are handled by the cloud computing system. The proposed scheme takes care of several attacks like botnets, malware and guessing attacks. This scheme is contrasted withseveral established schemesand a new form of authentication is used for the purpose of storing files in a secure manner.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Wait, wasn’t that code here before? Detecting Outdated Software Documentation

Wait, wasn’t that code here before? Detecting Outdated Soft...

引用

International Conference on Software Maintenance (ICSM)

作者： Wen Siang Tan Markus Wagner Christoph Treude School of Computer Science University of Adelaide Adelaide SA Australia Department of Data Science & AI Monash University Melbourne VIC Australia School of Computing and Information Systems The University of Melbourne Melbourne VIC Australia

Encountering outdated documentation is not a rare occurrence for developers and users in the software engineering community. To ensure that software documentation is up-to-date, developers often have to manually check whether the documentation needs to be updated whenever changes are made to the source code. In our previous work, we proposed an approach to automatically detect outdated code element references in software repositories and found that more than a quarter of the 1000 most popular projects on GitHub contained at least one outdated reference. In this paper, we present a GitHub Actions tool that builds on our previous work’s approach that GitHub developers can configure to automatically scan for outdated code element references in their GitHub project’s documentation whenever a pull request is submitted.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A data-Centric Accelerator for High-Performance Hypergraph Processing 22

A Data-Centric Accelerator for High-Performance Hypergraph P...

引用

Proceedings of the 55th Annual IEEE/ACM International Symposium on Microarchitecture

作者： Qinggang Wang Long Zheng Ao Hu Yu Huang Pengcheng Yao Chuangyi Gui Xiaofei Liao Hai Jin Jingling Xue National Engineering Research Center for Big Data Technology and System/Services Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China and Zhejiang Lab Hangzhou China National Engineering Research Center for Big Data Technology and System/Services Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China School of Computer Science and Engineering University of New South Wales Sydney NSW Australia

ISBN: (纸本)9781665462723

Hypergraph processing has emerged as a powerful approach for analyzing complex multilateral relationships among multiple entities. Past research on building hypergraph systems suggests that changing the scheduling order of bipartite edge tasks can improve the overlap-induced data locality in hypergraph processing. However, due to the complex intertwined connections between vertices and hyperedges, it is almost impossible to find a locality-optimal scheduling order. Thus, these task-centric hypergraph systems often suffer from substantial off-chip *** this paper, we first propose a novel data-centric Load-Trigger-Reduce (LTR) execution model to exploit fully the locality in hypergraph processing. Unlike a task-centric model that loads the required data along with a task, our LTR model invokes tasks as per the data used. Specifically, once the hypergraph data is loaded into the on-chip memory, all of its relevant computation tasks will be triggered simultaneously to output intermediate results, which are finally reduced to update the final results. Our LTR model enables all hypergraph data to be accessed once in each iteration. To fully exploit the LTR performance potential, we further architect an LTR-driven hypergraph accelerator, XuLin, which features with an adaptive data loading mechanism to minimize the loading cost via chunk merging at runtime. XuLin is also equipped with a priority-based differential data reduction scheme to reduce the impact of conflicting updates on performance. We have implemented XuLin both on a Xilinx Alveo U250 FPGA card and using a cycle-accurate simulator. The results show that XuLin outperforms the state-of-the-art hypergraph processing solutions Hygra and ChGraph by 20.47× and 8.77× on average, respectively.

关键词： hypergraph data-centric accelerator

来源：评论

学校读者我要写书评

暂无评论

DPSA: A Framework for dataflow Aware Precision Scalable DNN Accelerator Design

DPSA: A Framework for Dataflow Aware Precision Scalable DNN ...

引用

Frontiers Technology of Information and Computer (ICFTIC), IEEE International Conference on

作者： Hanyuan Gao Zheyuan Zou Wenbin Teng Teng Wang School of Data Science University of Science and Technology of China Hefei China Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou China School of Computer Science and Technology University of Science and Technology of China Hefei China

Many hardware architectures have been proposed to support such computation that bit width or precision is low and scalable, especially quantized deep neural networks (DNN). However, these works lack the consideration of dataflow, which means how the batches of data of deep neural network transfer and compute on the hardware efficiently. Besides, research focusing on dataflow lacks the consideration of the precision scalable situation. Meanwhile, these architectures and their dataflow are designed manually and will take much effort to update given that the DNNs evolve rapidly. To solve these shortcomings, we propose a framework to provide efficient precision-scalable DNN accelerators design parameters and dataflows on them automatically. We model the hardware structures and dataflows by intermediate representations. Then, we perform a design space exploration with the modeling and search for optimum hardware and dataflow design. Experimental results show that our designs are competitive to manually designed structures and hand-optimized programs. In some cases, our results exceed a state-of-the-art hardware accelerator in performance by an average of 1.19x.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Detecting JVM JIT Compiler Bugs via Exploring Two-Dimensional Input Spaces

Detecting JVM JIT Compiler Bugs via Exploring Two-Dimensiona...

引用

International Conference on Software Engineering (ICSE)

作者： Haoxiang Jia Ming Wen Zifan Xie Xiaochen Guo Rongxin Wu Maolin Sun Kang Chen Hai Jin School of Cyber Science and Engineering Huazhong University of Science and Technology China Hubei Key Laboratory of Distributed System Security Services Computing Technology and System Lab Cluster and Grid Computing Lab. Hubei Engineering Research Center on Big Data Security National Engineering Research Center for Big Data Technology and System School of Informatics Xiamen University China School of Computer Science and Technology Huazhong University of Science and Technology China

Java Virtual Machine (JVM) is the fundamental software system that supports the interpretation and execution of Java bytecode. To support the surging performance demands for the increasingly complex and large-scale Java programs, Just-In-Time (JIT) compiler was proposed to perform sophisticated runtime optimization. However, this inevitably induces various bugs, which are becoming more pervasive over the decades and can often cause significant consequences. To facilitate the design of effective and efficient testing techniques to detect JIT compiler bugs. This study first performs a preliminary study aiming to understand the characteristics of JIT compiler bugs and the corresponding triggering test cases. Inspired by the empirical findings, we propose JOpFuzzer, a new JVM testing approach with a specific focus on JIT compiler bugs. The main novelty of JOpFuzzer is embodied in three aspects. First, besides generating new seeds, JOpFuzzer also searches for diverse configurations along the new dimension of optimization options. Second, JOpFuzzer learns the correlations between various code features and different optimization options to guide the process of seed mutation and option exploration. Third, it leverages the profile data, which can reveal the program execution information, to guide the fuzzing process. Such nov-elties enable JOpFuzzer to effectively and efficiently explore the two-dimensional input spaces. Extensive evaluation shows that JOpFuzzer outperforms the state-of-the-art approaches in terms of the achieved code coverages. More importantly, it has detected 41 bugs in OpenJDK, and 25 of them have already been confirmed or fixed by the corresponding developers.

关键词：

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：