检索结果-内蒙古大学图书馆

arXiv 2022年

作者： Hellings, Jelle Rahnama, Sajjad Gupta, Suyash Sadoghi, Mohammad Department of Computing and Software McMaster University HamiltonON Canada Exploratory Systems Lab Department of Computer Science University of California Davis DavisCA United States RISELab Department of Electrical Engineering and Computer Science University of California Berkeley BerkeleyCA United States

The introduction of Bitcoin fueled the development of blockchain-based resilient data management systems that are resilient against failures, enable federated data management, and can support data provenance. The key factor determining the performance of such resilient data management systems is the consensus protocol used by the system to replicate client transactions among all participants. Unfortunately, existing high-throughput consensus protocols are costly and impose significant latencies on transaction processing, which rules out their usage in responsive high-performance data management systems. In this work, we improve on this situation by introducing the Proof-of-Execution consensus protocol (PoE), a consensus protocol designed for high-performance low-latency resilient data management. PoE introduces speculative execution, which minimizes latencies by starting execution before consensus is reached, and PoE introduces proof-of-executions to guarantee successful execution to clients. Furthermore, PoE introduces a single-round check-commit protocol to reduce the overall communication costs of consensus. Hence, we believe that PoE is a promising step towards flexible general-purpose low-latency resilient data management systems. Copyright © 2022, The Authors. All rights reserved.

关键词： Information management

来源：评论

学校读者我要写书评

暂无评论

Proposing Model for Security of IoT Devices in Smart Logistics: A Review 3

Proposing Model for Security of IoT Devices in Smart Logisti...

引用

3rd International Conference on Computing, Mathematics and engineering Technologies, iCoMET 2020

作者： Abbas, Arbab Waseem Nawaz Khan Marwat, Safdar Ahmed, Salman Hafeez, Abdul Ullah, Khalil Khan, Ihsan Ullah University of Engineering Technology Department of Computer Systems Engg Peshawar Pakistan Department of Computer Science Pakistan University of Malakand Department of Software Engg Dir Lower Pakistan Islamabad Pakistan

ISBN: (纸本)9781728149707

The information technology's new revolution is Internet of Things (IoT), where physical world is connected to the internet. IoT applications are diversified such as smart health, smart industry, smart homes and most importantly smart logistics for perishable items conservation. Although IoT devices have revolutionized world but due to their constrained nature they are at the cost of a greater risk of personal data loss, security breaches and misuse. In this research, a review is presented for proposing two state of the art modules i.e. communication model of smart logistics and security of IoT devices in Smart Logistics. As the smart logistics have perishable items i.e. fruits, vegetables, meat, medicine, chemicals, and cosmetics etc. which are sensitive to temperature, humidity and pressure etc. If the sensors monitoring these items have been handled abnormally due to security attacks, it will give huge loss. Therefore, security of smart logistics is of paramount importance in this research. In order to expedite research in this emergent area of IoT, in this research paper a brief review on progress of IoT in smart logistics, and its security has been presented. © 2020 IEEE.

关键词： Cybersecurity

来源：评论

学校读者我要写书评

暂无评论

Research of the Particle Swarm Method for Generating Nonlinear Substitutions

Research of the Particle Swarm Method for Generating Nonline...

引用

2021 IEEE International Conference on Information and Telecommunication Technologies and Radio Electronics, UkrMiCo 2021

作者： Kuznetsov, Alexandr Myroshnychenko, Volodymyr Derevianko, Yaroslav Bulhakova, Olha Department of information systems and technologies security V. N. Karazin Kharkiv National University Kharkiv Ukraine Department of Economic and Information Security Dnipropetrovsk State University of Internal Affairs Dnipro Ukraine Department of Computer Science and Software Engineering University of Customs and Finance Dnipro Ukraine

ISBN: (纸本)9781665426527

Nonlinear substitutions (S-boxes) have an important role in ensuring security of symmetric cryptographical transformations. In this article, we consider a computational particle swarm optimization method (PSO) to generate S-boxes. We have implemented two algorithms for generating substitutions that reproduce a certain simulation of particle motion in the space of possible states to make experimental research. We perform a computational search and show the efficiency of these two implementations. Our proposed improved implementation allows us to confidently generate Sboxes with nonlinearity 104, delta uniformity 8, linear redundancy 0 and algebraic immunity 3. © 2021 UkrMiCo 2021 - 2021 IEEE International Conference on Information and Telecommunication Technologies and Radio Electronics, Proceedings. All rights reserved.

关键词： Particle swarm optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

F2A2: flexible fully-decentralized approximate actor-critic for cooperative multi-agent reinforcement learning

The Journal of Machine Learning Research

引用

The Journal of Machine Learning Research 2023年第1期24卷 8447-8521页

作者： Wenhao Li Bo Jin Xiangfeng Wang Junchi Yan Hongyuan Zha School of Data Science The Chinese University of Hong Kong Shenzhen Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China School of Software Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China School of Computer Science and Technology Key Laboratory of Mathematics and Engineering Applications Ministry of Education East China Normal University Shanghai China Department of Computer Science and Engineering Key Laboratory of Artificial Intelligence Ministry of Education Shanghai Jiao Tong University Shanghai China

Traditional centralized multi-agent reinforcement learning (MARL) algorithms are sometimes unpractical in complicated applications due to non-interactivity between agents, the curse of dimensionality, and computation complexity. Hence, several decentralized MARL algorithms are motivated. However, existing decentralized methods only handle the fully cooperative setting where massive information needs to be transmitted in training. The block coordinate gradient descent scheme they used for successive independent actor and critic steps can simplify the calculation, but it causes serious bias. This paper proposes a exible fully decentralized actor-critic MARL framework, which can combine most of the actor-critic methods and handle large-scale general cooperative multi-agent settings. A primal-dual hybrid gradient descent type algorithm framework is designed to learn individual agents separately for decentralization. From the perspective of each agent, policy improvement and value evaluation are jointly optimized, which can stabilize multi-agent policy learning. Furthermore, the proposed framework can achieve scalability and stability for the large-scale environment. This framework also reduces information transmission by the parameter sharing mechanism and novel modeling-other-agents methods based on theory-of-mind and online supervised learning. Sufficient experiments in cooperative Multi-agent Particle Environment and StarCraft II show that the proposed decentralized MARL instantiation algorithms perform competitively against conventional centralized and decentralized methods.

关键词： cooperative MARL decentralized actor-critic primal-dual method

来源：评论

学校读者我要写书评

暂无评论

An advanced algorithm for discrimination prevention in data mining

An advanced algorithm for discrimination prevention in data ...

引用

2022 IEEE Conference on Telecommunications, Optics and computer Science, TOCS 2022

作者： Wang, Shuoyu Ren, Jie Fang, Hao Pan, Jun Hu, Xin Zhao, Tingyun Tibet University College of Information Science and Technology Lhasa China Lyuliang University Department of Computer Science and Technology Lvliang China Liaoning University of Traditional Chinese Medicine College of Foreign Languages Shenyang China Beihang University School of Electronic and Information Engineering Beijing China Yangtze Normal University School of Mathematics and Statistics Chongqing China Changzhou College of Information Technology School of Software and Big Data Changzhou China

ISBN: (纸本)9781665470537

Data mining has been effectively utilized in huge expanded application areas. Associations overall go with significant business choices in light of mining of data. Discrimination in navigation and preservation of protection of data are a couple of significant difficulties in data mining. Discrimination is of two sorts, Direct Discrimination and Indirect Discrimination. Discrimination prevention includes two significant angles disclosure of direct and additionally roundabout discrimination and data transformation as alteration of separating rules without influencing data quality. Existing strategies for discrimination prevention utilize one of the three methodologies, in particular, the pre-process, in-process or post-process approach. Tests for the exhibition assessment of all calculations by fluctuating these info boundaries, each in turn to review and break down impact of these boundaries. © 2022 IEEE.

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

Agile Meets Quantum: A Novel Genetic Algorithm Model for Predicting the Success of Quantum software Development Project

arXiv

引用

arXiv 2024年

作者： Khan, Arif Ali Akbar, Muhammad Azeem Lahtinen, Valtteri Paavola, Marko Niazi, Mahmood Alatawi, Mohammed Naif Alotaibi, Shoayee Dlaim M3S Empirical Software Engineering Research Unit University of Oulu Oulu90014 Finland Software Engineering Department Lappeenranta-Lahti University of Technology Lappeenranta53851 Finland Quanscient Oy Tampere Finland VTT Technical Research Ctr of Finland Ltd Oulu Finland Department of Information and Computer Science King Fahd University of Petroleum and Minerals Saudi Arabia Interdisciplinary Research Centre for Intelligent Secure Systems King Fahd University of Petroleum and Minerals Saudi Arabia Information Technology Department Faculty of Computers and Information Technology University of Tabuk Saudi Arabia Department of Artificial Intelligence and Data Science College of Computer Science and Engineering University of Hail Hail Saudi Arabia

Context: Quantum software systems represent a new realm in software engineering, utilizing quantum bits (Qubits) and quantum gates (Qgates) to solve the complex problems more efficiently than classical counterparts. Agile software development approaches are considered to address many inherent challenges in quantum software development, but their effective integration remains unexplored. Objective: This study investigates key causes of challenges that could hinders the adoption of traditional agile approaches in quantum software projects and develop an Agile-Quantum software Project Success Prediction Model (AQSSPM). Methodology: Firstly, we identified 19 causes of challenging factors discussed in our previous study, which are potentially impacting agile-quantum project success. Secondly, a survey was conducted to collect expert opinions on these causes and applied Genetic Algorithm (GA) with Naive Bayes Classifier (NBC) and Logistic Regression (LR) to develop the AQSSPM. Results: Utilizing GA with NBC, project success probability improved from 53.17% to 99.68%, with cost reductions from 0.463% to 0.403%. Similarly, GA with LR increased success rates from 55.52% to 98.99%, and costs decreased from 0.496% to 0.409% after 100 iterations. Both methods result showed a strong positive correlation (rs=0.955) in causes ranking, with no significant difference between them (t=1.195, p=0.240>0.05). Conclusion: The AQSSPM highlights critical focus areas for efficiently and successfully implementing agile-quantum projects considering the cost factor of a particular project. © 2024, CC BY.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

A comparative analysis of machine learning algorithms to build a predictive model for detecting diabetes complications

引用

Informatica (Slovenia) 2021年第1期45卷

作者： Abaker, Ali A. Saeed, Fakhreldeen A. Department of Accounting Information Systems Faculty of Computer Science Al-Neelain University Khartoum Sudan Department of Software Engineering Faculty of Computer Science Al-Neelain University Khartoum Sudan

Diabetes complications have a significant impact on patients’ quality of life. The objective of this study was to predict which patients were more likely to be in a complicated health condition at the time of admission to allow for the early introduction of medical interventions. The data were 644 electronic health records from Alsukari Hospital collected from January 2018 to April 2019. We used the following machine learning methods: logistic regression, random forest, and k-nearest neighbor (KNN). The logistic regression algorithm performed better than the other algorithms achieving an accuracy of 81%, recall of 81%, and F1 score of 75%. Also, attributes such as infection years, swelling, diabetic ketoacidosis, and diabetic septic foot were significant in predicting diabetes complications. This model can be useful for the identification of patients requiring additional care to limit the complications and help practitioners in making decisions on whether the patient should be hospitalized or sent home. Furthermore, we used the sequential feature selection (SFS) algorithm which reduced the features to six, which is fewer than any model built before to predict diabetes complications. The primary goal of this study was achieved. The model had fewer attributes which means we have a simple and understandable model in addition to, it has a better performance. © 2021 Slovene Society Informatika. All rights reserved.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Enhancing Feedback Mechanisms in English Language Assessments Through Deep Learning Model

Enhancing Feedback Mechanisms in English Language Assessment...

引用

Artificial Intelligence and Quantum Computation-Based Sensor Application (ICAIQSA), International Conference on

作者： M.D Thamarai Selvi G Ahmed Zeeshan Omaia Al-Omari Amit Kumar Mishra Giftsy Dorcas E Fredrick Ruban Alphonse Department of Verbal and Life Skills Saveetha School of Engineering SIMATS Engineering Thandalam Chennai Department of ECE Global Institute of Engineering and Technology (Autonomous) Hyderabad India Information Systems Department College of Computer and Information Sciences Prince Sultan University Riyadh Saudi Arabia Department of CSE Graphic Era Hill University Dehradun Adjunct Professor Graphic Era Deemed to be University Dehradun Uttarakhand India Department of English Kristu Jayanti College (Autonomous) Bengaluru Karnataka Assistant Professor of English Department of Languages Institute of Finance and International Management Bengaluru India

ISBN: (数字)9798331517953

ISBN: (纸本)9798331517960

In the realm of English language assessments, optimizing feedback mechanisms is crucial for enhancing learning outcomes and learner engagement. This paper therefore presents a new approach of increasing feedback enhancement by incorporating a Double Integral Transformer (DIT) model within the assessment process. The DIT model is an improved version of the regular Transformer architecture which employs two, or rather dual integral attention modules, to handle both the local and global contextual semantics of the language use more efficiently. With help of this model, the feedback process can be more accurate, accurate and individual for each learner. The Double Integral Transformer evaluates linguistic data by employing double attention layer that combines data at the syntactic and semantic level to enhance the quality of feedback given accurately. It improves the recognition of learners' strengths and weaknesses concerning the language in question and provides customized feedback that is apparently more accurate. The enhanced feeback mechanism reduces problems that are associated current assessment practices: for example, general feedback and lack of context awareness. In this study, the author presents the empirical support for the effectiveness of the DIT model to enhance the quality of the feedback is a major contribution of this study as it results in better learner performance and satisfaction. In this respect, the study advances the area's knowledge by demonstrating how novel types of Transformers can be integrated into educational technology systems while providing insights for possible changes to language assessments procedures.

关键词： Deep learning Accuracy Quantum computing Semantics Educational technology Context awareness Syntactics Linguistics Transformers Context modeling

来源：评论

学校读者我要写书评

暂无评论

Managing Control software Variability in Cyber-Physical Production systems: The V4rdiac Approach

SSRN

引用

SSRN 2024年

作者： Fadhlillah, Hafiyyan Sayyid Meixner, Kristof Greiner, Sandra Fernández, Antonio Manuel Gutiérrez Rabiser, Rick Christian Doppler Laboratory VaSiCS Johannes Kepler University Linz Altenberger Straße 69 Linz4040 Austria LIT CPS Lab Johannes Kepler University Linz Altenberger Straße 69 Linz4040 Austria Christian Doppler Laboratory SQI TU Wien Favoritenstraße 9-11 Vienna1040 Austria Information Systems Engineering TU Wien Favoritenstraße 9-11 Vienna1040 Austria Software Engineering Group Institute of Computer Science University of Bern Neubrückstraße 10 Bern3012 Switzerland Department of Computer Languages and Systems Universidad de Sevilla Avenida Reina Mercedes s/n Sevilla41012 Spain

Cyber-Physical Production systems (CPPSs) are highly configurable and versatile production systems that utilize diverse hardware components through control software. Managing control software variants in CPPS development is challenging as variation points in the software stem from multiple engineering disciplines. Furthermore, there is a lack of mechanisms to explicitly describe control software variants as part of the software. In this paper, we present an extension of the Variability for 4diac (V4rdiac) approach and investigate its usefulness in managing control software variants based on multidisciplinary variability in CPPS development and delta modeling. We extend the approach by considering its application engineering activities to produce client-specific control software variants. We also present a novel mechanism to visualize deltas in control software to reduce the effort of implementing and maintaining deltas. We apply V4rdiac in two case studies and conduct an additional user study with four participants from industry to evaluate its usefulness. The evaluation results confirm that the engineers were able to successfully manage the control software variants. The results also show that V4rdiac can be easily learned and increases industrial practitioners’ productivity in managing control software. © 2024, The Authors. All rights reserved.

关键词： Application programs

来源：评论

学校读者我要写书评

暂无评论

Fast Symbolic Algorithms for Omega-Regular Games under Strong Transition Fairness

arXiv

引用

arXiv 2022年

作者： Banerjee, Tamajit Majumdar, Rupak Mallik, Kaushik Schmuck, Anne-Kathrin Soudjani, Sadegh Department of Computer Science and Engineering Indian Institute of Technology Delhi India Max Planck Institute for Software Systems Germany Institute of Science and Technology Austria Austria Newcastle University United Kingdom

We consider fixpoint algorithms for two-player games on graphs with ω-regular winning conditions, where the environment is constrained by a strong transition fairness assumption. Strong transition fairness is a widely occurring special case of strong fairness. It requires that any execution is strongly fair with respect to a specified set of live edges: whenever the source vertex of a live edge is visited infinitely often along a play, the edge itself is traversed infinitely often along the play as well. We show that, surprisingly, strong transition fairness retains the algorithmic characteristics of the fixpoint algorithms for ω-regular games-the new algorithms have the same alternation depth as the classical algorithms but invoke a new type of predecessor operator. For example, for Rabin games with k pairs under strong transition fairness, the complexity of the new algorithm is O(nk+2k!) symbolic steps, which is independent of the number of live edges in the strong transition fairness assumption. In contrast, strong fairness necessarily requires increasing the alternation depth depending on the number of fairness assumptions. We get symbolic algorithms for (generalized) Rabin, parity, and GR(1) objectives under strong transition fairness assumptions as well as a direct symbolic algorithm for qualitative winning in stochastic ω-regular games that runs in O(nk+2k!) symbolic steps, improving the state of the art. Previous approaches for handling fairness assumptions would either increase the alternation depth of the fixpoint algorithm or require an up-front automata-theoretic construction that would increase the state space, or both. We have implemented a BDD-based synthesis engine based on our algorithm. We show on a set of synthetic and real benchmarks that our algorithm is scalable, parallelizable, and outperforms previous algorithms by orders of magnitude. © 2022, CC BY.

关键词： Stochastic systems

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：