检索结果-内蒙古大学图书馆

International IEEE Conference on Intelligent Systems, IS

作者： George Kandilogiannakis Paris Mastorocostas Costas Hilas Dept. of Informatics and Computer Engineering University of West Attica Athens Greece Dept. of Computer Informatics & Telecommunications Engineering International Hellenic University Serres Greece

ISBN: (数字)9781728154565

ISBN: (纸本)9781728154572

A dynamic fuzzy neural system is proposed, for time series anomaly detection. The model is entitled BFuzzTiD (Block-diagonal Fuzzy Time-series Detector) and consists of fuzzy rules whose consequent parts are three-layer small recurrent neural networks. The hidden layer of each network has blocks of neurons that feed back to each other. BFuzzTid is trained by the Dynamic Resilient Propagation algorithm. The model learns the dynamics of the time series such that it can classify them by detecting the anomaly points. A comparative analysis is conducted with a series of time series anomaly detection models, in order to investigate the capabilities of the proposed detector.

关键词： Time series analysis Anomaly detection Neurons Computational modeling Detectors Recurrent neural networks Training

来源：评论

学校读者我要写书评

暂无评论

The state-of-the-art review on resource allocation problem using artificial intelligence methods on various computing paradigms

arXiv

引用

arXiv 2022年

作者： Joloudari, Javad Hassannataj Mojrian, Sanaz Saadatfar, Hamid Nodehi, Issa Fazl, Fatemeh Shirkharkolaie, Sahar Khanjani Alizadehsani, Roohallah Dipu Kabir, H.M. Tan, Ru-San Rajendra Acharya, U. Department of Computer Engineering Faculty of Engineering University of Birjand Birjand*** Iran Department of Information Technology Mazandaran University of Science and Technology Babol Iran Department of Computer Engineering Qom University of Technology Qom Iran Department of Electronic Engineering Faculty of Electrical and Computer Engineering University of Birjand Birjand Iran Institute for Intelligent Systems Research and Innovation Deakin University GeelongVIC3216 Australia School of Science and Technology Singapore University of Social Sciences Singapore Ngee Ann Polytechnic Singapore599489 Singapore Dept. of Biomedical Informatics and Medical Engineering Asia University Taichung Taiwan

With the increasing growth of information through smart devices, increasing the quality level of human life requires various computational paradigms presentation including the Internet of Things, fog, and cloud. Between these three paradigms, the cloud computing paradigm as an emerging technology adds cloud layer services to the edge of the network so that resource allocation operations occur close to the end-user to reduce resource processing time and network traffic overhead. Hence, the resource allocation problem for its providers in terms of presenting a suitable platform, by using computational paradigms is considered a challenge. In general, resource allocation approaches are divided into two methods, including auction-based methods (goal, increase profits for service providers-increase user satisfaction and usability) and optimization-based methods (energy, cost, network exploitation, Runtime, reduction of time delay). In this paper, according to the latest scientific achievements, a comprehensive literature study (CLS) on artificial intelligence methods based on resource allocation optimization without considering auction-based methods in various computing environments are provided such as cloud computing, Vehicular Fog Computing, wireless, IoT, vehicular networks, 5G networks, vehicular cloud architecture, machine-to-machine communication (M2M), Train-to-Train(T2T) communication network, Peer-to-Peer (P2P) network. Since deep learning methods based on artificial intelligence are used as the most important methods in resource allocation problems;Therefore, in this paper, resource allocation approaches based on deep learning are also used in the mentioned computational environments such as deep reinforcement learning, Q-learning technique, reinforcement learning, online learning, and also Classical learning methods such as Bayesian learning, Cummins clustering, Markov decision process. © 2022, CC BY-SA.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

The Role of Extraversion in Phishing Victimisation: A Systematic Literature Review

The Role of Extraversion in Phishing Victimisation: A System...

引用

eCrime Researchers Summit

作者： Pablo López-Aguilar Constantinos Patsakis Agusti Solanas Dept. of Research and Innovation Anti-Phishing Working Group - Europe Barcelona Catalonia Spain Dept. of Informatics University of Piraeus Piraeus Greece Athena Research Center Marousi Athens Greece Dept. of Computer Engineering and Mathematics Universitat Rovira i Virgili Tarragona Catalonia Spain

Over the last decade, phishing attacks have become preeminent and increasingly successful. Anti-phishing strategies focus on raising awareness and training users to identify risks. However, those strategies do not fully consider the psychological profile of each individual. We sustain that maximising potential victims’ resilience requires additional protection strategies to focus on individual personality *** this article, we concentrate on extraversion as a personality trait for which there is no consensus about its effect on susceptibility to phishing attacks. We implement a robust bibliographic analysis methodology and identify potentially relevant articles, which we screen and filter against inclusion and exclusion criteria. We report and analyse the findings of the 39 articles that fulfil all criteria and are deemed relevant to this research. Our analysis shows that, despite the positive correlation between extraversion and phishing susceptibility found in many studies, there is no consensus supported by a well-established psychological theory. Moreover, we identify a number of reasons justifying this lack of consensus, namely the use of non-representative samples, the non consideration of contextual factors, and the use of self-reported personality tests, which lead to limited reproducibility and data inconsistencies.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Knowledge discovery of patients reviews on breast cancer drugs: Segmentation of side effects using machine learning techniques

引用

Heliyon 2024年第19期10卷 e38563页

作者： Nilashi, Mehrbakhsh Ahmadi, Hossein Abumalloh, Rabab Ali Alrizq, Mesfer Alghamdi, Abdullah Alyami, Sultan UCSI Graduate Business School UCSI University Cheras Kuala Lumpur 56000 Malaysia Centre for Health Technology Faculty of Health University of Plymouth Plymouth PL4 8AA United Kingdom Department of Computer Science and Engineering Qatar University Doha 2713 Qatar Information Systems Dept. College of Computer Science and Information Systems Najran University Najran Saudi Arabia Computer Science Dept. College of Computer Science and Information Systems Najran University Najran Saudi Arabia AI Lab Scientific and Engineering Research Center (SERC) Najran University Najran Saudi Arabia Centre for Business Informatics and Industrial Management UCSI Graduate Business School UCSI University Malaysia

Breast cancer stands as the most frequently diagnosed life-threatening cancer among women worldwide. Understanding patients' drug experiences is essential to improving treatment strategies and outcomes. In this research, we conduct knowledge discovery on breast cancer drugs using patients' reviews. A new machine learning approach is developed by employing clustering, text mining and regression techniques. We first use Latent Dirichlet Allocation (LDA) technique to discover the main aspects of patients' experiences from the patients' reviews on breast cancer drugs. We also use Expectation-Maximization (EM) algorithm to segment the data based on patients' overall satisfaction. We then use the Forward Entry Regression technique to find the relationship between aspects of patients' experiences and drug's effectiveness in each segment. The textual reviews analysis on breast cancer drugs found 8 main side effects: Musculoskeletal Effects, Menopausal Effects, Dermatological Effects, Metabolic Effects, Gastrointestinal Effects, Neurological and Cognitive Effects, Respiratory Effects and Cardiovascular. The results are provided and discussed. The findings of this study are expected to offer valuable insights and practical guidance for prospective patients, aiding them in making informed decisions regarding breast cancer drug consumption. © 2024 The Authors

关键词： Breast cancer Drugs Knowledge discovery Machine learning Online reviews Public health Text mining

来源：评论

学校读者我要写书评

暂无评论

A Web and Mobile Application to Identify the Availability of Drinking Water Information During a Water Crisis

A Web and Mobile Application to Identify the Availability of...

引用

Intelligent Computing and Control for engineering and Business Systems (ICCEBS)

作者： Suhail Razeeth Fathima Shihara Kasuni Pavithra Maran Kaliyamoorthy Samsudeen Sabraz Nawaz Rkar Kariyapper Dept. of Information and Communication Technology South Eastern University of Sri Lanka Sri Lanka Dept. of Computer Science and Informatics Uva Wellassa University of Sri Lanka Sri Lanka Sri Sai Ram Institute of Management Studies Sri Sai Ram Engineering College India Department of Management and Information Technology South Eastern University of Sri Lanka Sri Lanka

Sri Lanka faces drinking water related issues often due to many reasons like weather changes, floods, droughts, and tsunamis, affecting the drinking water availability. In such instances, people find difficult to gather information regarding consumable drinking water availability. In order to facilitate the meeting of commercial water sellers and customers and to engage the general public and social services in addressing the drinking water problem, this study is focused on building both web and mobile applications. The web application was implemented with a selected set of functionalities such as social login, social sharing, geocoding, reverse geocoding, viewing, and filtering posts using Angular 6, *** web framework, and Leaflet. The mobile application was developed to direct the customers to the water availability location with a shortest path using the Dijkstra's algorithm. Case evaluation was conducted with the Rotaract Club members in Badulla and thinking aloud method was used to pick up the user's ideas while interacting with the system. It can be concluded that the created web and mobile applications would offer the public a clever way to draw attention to an issue with water availability, and the commercial water service providers are given a venue to market their services and locate potential customers.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Coherent VCSEL Network Computing 27

Coherent VCSEL Network Computing

引用

27th OptoElectronics and Communications Conference/International Conference on Photonics in Switching and Computing, OECC/PSC 2022

作者： Chen, Zaijun Sludds, Alexander Davis, Ronald Christen, Ian Ateshian, Lamia Bernstein, Liane Heuser, Tobias Heermeier, Niels Lott, James Reitzenstein, Stephan Hamerly, Ryan Englund, Dirk Massachusetts Institute of Technology 77 Massachusetts Ave. CambridgeMA02139 United States Ming Hsieh Dept. of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States Fakultät Ii Institut für Festkörperphysik Sekretariat Technische Universität Berlin Berlin10623 Germany Ntt Research Inc. Physics & Informatics Laboratories SunnyvaleCA94085 United States

ISBN: (数字)9784885523366

ISBN: (纸本)9784885523366

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Approach to Parallel Pattern Discovery in C++ 28

A Hybrid Approach to Parallel Pattern Discovery in C++

引用

28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2020

作者： Brown, C. Janjic, V. Barwell, A. Thomson, J. Castaneda Lozano, R. Cole, M. Franke, B. Garcia-Sanchez, J.D. Del Rio Astorga, D. MacKenzie, K. University of St Andrews School of Computer Science StAndrews United Kingdom University of Edinburgh School of Informatics Edinburgh United Kingdom Universidad Carlos III de Madrid Computer Science and Engineering Dept. Madrid Spain IOHK

ISBN: (纸本)9781728165820

Parallel pattern libraries offer a strong combination of abstraction and performance. However, discovering places in sequential code where parallel patterns should be introduced is still highly non-trivial, often requiring expert manual analysis and profiling. We present a hybrid discovery technique to detect instances of parallel patterns in sequential code. This employs both static and dynamic trace-based analysis, together with hotspot detection. We evaluate our pattern discovery mechanism on a number of representative benchmarks. We evaluate the performance of the resulting parallelised benchmarks on a 24core parallel machine. © 2020 IEEE.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

Stabilization with Zero Location Constraints for Delay-Based Non-collocated Vibration Suppression ⁎

引用

IFAC-PapersOnLine 2021年第18期54卷 121-126页

作者： Haik Silm Wim Michiels Tomáš Vyhlídal Departement of Computer Science KU Leuven Celestijnenlaan 200A 3001 Leuven Belgium Dept. Instrumentation and Control Engineering Faculty of Mechanical Engineering and Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 6 Czechia

A generally applicable design of non-collocated vibration absorption by a delayed resonator is proposed. It is grounded in the direct assignment of imaginary axis zeros of the transfer function between the periodic disturbance force and the target. We show that these transmission zeros are characterized as eigenvalues of a delay differential-algebraic system. Furthermore, a stabilizing local controller is added to the setup in order to widen the range of admissible vibration frequencies. These design requirements are translated into an optimization problem of the spectral abscissa function subjected to zero location constraints. The presented approach and algorithm are validated by a simulation on a three body lumped mass-spring system.

关键词： Vibration control Delayed resonator Transmission zeros Stability Spectral method

来源：评论

学校读者我要写书评

暂无评论

Estimating leverage scores via rank revealing methods and randomization

arXiv

引用

arXiv 2021年

作者： Sobczyk, Aleksandros Gallopoulos, Efstratios IBM Research Zurich Saümerstrasse 4 Rüschlikon Switzerland HPCLab Computer Engineering & Informatics Dept. University of Patras Patras26504 Greece

We study algorithms for estimating the statistical leverage scores of rectangular dense or sparse matrices of arbitrary rank. Our approach is based on combining rank revealing methods with compositions of dense and sparse randomized dimensionality reduction transforms. We first develop a set of fast novel algorithms for rank estimation, column subset selection and least squares preconditioning. We then describe the design and implementation of leverage score estimators based on these primitives. These estimators are also effective for rank deficient input, which is frequently the case in data analytics applications. We provide detailed complexity analyses for all algorithms as well as meaningful approximation bounds and comparisons with the state-of-the-art. We conduct extensive numerical experiments to evaluate our algorithms and to illustrate their properties and performance using synthetic and real world data sets. © 2021, CC BY-NC-ND.

关键词： Data Analytics

来源：评论

学校读者我要写书评

暂无评论

Acoustic measurement framework for audio systems based on structured periodic test signals

Acoustic measurement framework for audio systems based on st...

引用

IEEE Global Conference on Consumer Electronics (GCCE)

作者： Hideki Kawahara Kohei Yatabe Ken-Ichi Sakakibara Mitsunori Mizumachi Tatsuya Kitamura Cntr. Innovative Research and Liaison Wakayama University Wakayama Japan Dept. Electrical Engineering and Computer Science Tokyo University of Agriculture and Technology Tokyo Japan Dept. Speech-Language-Hearing Therapy Health Sciences University of Hokkaido Hokkaido Japan Dept. Electrical and Electronic Eng. Kyushu Institute of Technology Kita-Kyushu Japan Dept. Intelligence and Informatics Konan University Kita-Kyushu Japan

We introduce a framework for acoustic measurement that allows everyday sounds into acoustic measurement test signals and standard test signals such as swept-sine and MLS (Maximum Length Sequence). The framework extends our extended Time-Stretched-Pulse generation method and safeguarding method for any signals to make them appropriate for acoustic measurement. The extension uses the periodic nature of discrete Fourier transform combined with orthogonalization based on the Walsh-Hadamerd matrix. This framework enables simultaneous measurement of acoustic attributes such as linear time-invariant response, signal-dependent non-linear and time-invariant components, and random time-varying components. We also discuss and demonstrate practical scenarios in classes and laboratory lessons using tools developed based on the proposed framework.

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：