检索结果-内蒙古大学图书馆

4th International Conference on Informatics, Multimedia, Cyber and Information System, ICIMCIS 2022

作者： Maulana, Fairuz Iqbal Lestari, Dian Widartha, Vandha Pradwiyasma Haidar, Nirwana Dirgantara, Wahyu School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Airlangga University Faculty of Medicine Surabaya60132 Indonesia Telkom University Information System of Industrial Engineering Faculty Bandung Indonesia University of Madura Informatics Engineering Study Program Pamekasan Indonesia University of Merdeka Malang Department of Electrical Engineering Malang Indonesia

ISBN: (纸本)9781665473279

This study examines the mapping of research data on digital technology in the field of health education using bibliometric analysis method. Data was collected by identifying keywords in the Scopus database and sorting them out to sort the studies from the last 10 years (2012-2021). Through this step, a total of 1482 documents were obtained (articles, journals, proceedings, books, and others). The data is then processed using the VOSViewer instrument to obtain a visualization of the mapping analysis. This study also analyzes the network types of authors and co-authors through the VOSViewer instrument. The result of this study indicates that the most document types published within ten years are Articles (66.5%), Review (22.9%), Conference Paper (4.2%), and others. The most studied subjects are Medicine (55.7%), Nursing (9.0%), Health Professions (8.2%), Social Sciences (7.8%), engineering (3.9%), computer Science (2.6%), Environmental Science (2.6%), Biochemistry-Genetics and Molecular Biology (2.2%), Psychology (1.6%), and Dentistry (1.3%). This study offers a written communication process and the nature and direction of developing descriptive means of counting and analyzing the various phases of communication as well as recognizing the authorship and direction of its symptoms in documents on the subject of digital technology in the health sector. © 2022 IEEE.

关键词： Mapping

来源：评论

学校读者我要写书评

暂无评论

Knowledge Graph-Enabled Text-Based Automatic Personality Prediction

arXiv

引用

arXiv 2022年

作者： Ramezani, Majid Feizi-Derakhshi, Mohammad-Reza Balafar, Mohammad-Ali Computerized Intelligence Systems Laboratory Department of Computer Engineering Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran Department of Computer Engineering Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran

How people think, feel, and behave primarily is a representation of their personality characteristics. By being conscious of the personality characteristics of individuals whom we are dealing with or deciding to deal with, one can competently ameliorate the relationship, regardless of its type. With the rise of Internet-based communication infrastructures (social networks, forums, etc.), a considerable amount of human communications take place there. The most prominent tool in such communications is the language in written and spoken form that adroitly encodes all those essential personality characteristics of individuals. Text-based Automatic Personality Prediction (APP) is the automated forecasting of the personality of individuals based on the generated/exchanged text contents. This paper presents a novel knowledge graph-enabled approach to text-based APP that relies on the Big Five personality traits. To this end, given a text, a knowledge graph which is a set of interlinked descriptions of concepts was built by matching the input text's concepts with DBpedia knowledge base entries. Then, due to achieving a more powerful representation, the graph was enriched with the DBpedia ontology, NRC Emotion Intensity Lexicon, and MRC psycholinguistic database information. Afterwards, the knowledge graph which is now a knowledgeable alternative for the input text was embedded to yield an embedding matrix. Finally, to perform personality predictions the resulting embedding matrix was fed to four suggested deep learning models independently, which are based on convolutional neural network (CNN), simple recurrent neural network (RNN), long short term memory (LSTM), and bidirectional long short term memory (BiLSTM). The results indicated considerable improvements in prediction accuracies in all of the suggested classifiers. Copyright © 2022, The Authors. All rights reserved.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

Projection-Free Methods for Stochastic Simple Bilevel Optimization with Convex Lower-level Problem

arXiv

引用

arXiv 2023年

作者： Cao, Jincheng Jiang, Ruichen Abolfazli, Nazanin Hamedani, Erfan Yazdandoost Mokhtari, Aryan Department of Electrical and Computer Engineering The University of Texas AustinTX United States Department of Systems and Industrial Engineering The University of Arizona TucsonAZ United States

In this paper, we study a class of stochastic bilevel optimization problems, also known as stochastic simple bilevel optimization, where we minimize a smooth stochastic objective function over the optimal solution set of another stochastic convex optimization problem. We introduce novel stochastic bilevel optimization methods that locally approximate the solution set of the lower-level problem via a stochastic cutting plane, and then run a conditional gradient update with variance reduction techniques to control the error induced by using stochastic gradients. For the case that the upper-level function is convex, our method requires Õ(max{1/Ε2f, 1/Ε2g}) stochastic oracle queries to obtain a solution that is Εf-optimal for the upper-level and Εgoptimal for the lower-level. This guarantee improves the previous best-known complexity of O(max{1/Ε4f, 1/Ε4g}). Moreover, for the case that the upper-level function is non-convex, our method requires at most Õ(max{1/Ε3f, 1/Ε3g}) stochastic oracle queries to find an (Εf, Εg)stationary point. In the finite-sum setting, we show that the number of stochastic oracle calls required by our method are Õ(√n/Ε) and Õ(√n/Ε2) for the convex and non-convex settings, respectively, where Ε = min{Εf, Εg}. Copyright © 2023, 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

Rapid remote access system for heterogeneous laboratory resources 38

Rapid remote access system for heterogeneous laboratory reso...

引用

38th Information systems Education Conference, ISECON 2022

作者： Bolanowski, Marek Krogulski, Piotr Department of Complex Systems The Faculty of Electrical and Computer Engineering Rzeszow University of Technology Al. Powstańców Warszawy 12 Rzeszów35-959 Poland

The work is dedicated to the possibility of implementing remote access to the laboratory for students, which will enable them to use physical laboratory stations to carry out exercises. Unlike the available solutions, the work assumes the maximum reduction of the cost and time of implementing the system of remote access to resources, the maximum flexibility of the used solutions and a large variety of supported laboratory equipment. The paper presents a diagram of the architecture and its components. The system has been implemented in a real laboratory and its operation tested by remotely executing sample laboratory instructions. The results of the research work can be used to make specialized laboratory resources more widely available and also during pandemic restrictions. © ISECON 2022. All Rights Reserved.

关键词： Laboratories

来源：评论

学校读者我要写书评

暂无评论

Exploring Contextual Representation and Multi-modality for End-to-end Autonomous Driving

引用

engineering Applications of Artificial Intelligence 2024年 135卷

作者： Azam, Shoaib Munir, Farzeen Kyrki, Ville Kucner, Tomasz Piotr Jeon, Moongu Pedrycz, Witold Department of Electrical Engineering and Automation Aalto University Espoo Finland Finnish Center for Artificial Intelligence Finland School of Electrical Engineering and Computer Science Gwangju Institute of Science and Technology Gwangju61005 Korea Republic of Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia Systems Research Institute Polish Academy of Sciences Warsaw01-447 Poland

Learning contextual and spatial environmental representations enhances autonomous vehicle's hazard anticipation and decision-making in complex scenarios. Recent perception systems enhance spatial understanding with sensor fusion but often lack global environmental context. Humans, when driving, naturally employ neural maps that integrate various factors such as historical data, situational subtleties, and behavioral predictions of other road users to form a rich contextual understanding of their surroundings. This neural map-based comprehension is integral to making informed decisions on the road. In contrast, even with their significant advancements, autonomous systems have yet to fully harness this depth of human-like contextual understanding. Motivated by this, our work draws inspiration from human driving patterns and seeks to formalize the sensor fusion approach within an end-to-end autonomous driving framework. We introduce a framework that integrates three cameras (left, right, and center) to emulate the human field of view, coupled with top-down bird-eye-view semantic data to enhance contextual representation. The sensor data is fused and encoded using a self-attention mechanism, leading to an auto-regressive waypoint prediction module. We treat feature representation as a sequential problem, employing a vision transformer to distill the contextual interplay between sensor modalities. The efficacy of the proposed method is experimentally evaluated in both open and closed-loop settings. Our method achieves displacement error by 0.67m in open-loop settings, surpassing current methods by 6.9% on the nuScenes dataset. In closed-loop evaluations on CARLA's Town05 Long and Longest6 benchmarks, the proposed method enhances driving performance, route completion, and reduces infractions. © 2024 The Authors

关键词： Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

Hybrid Schrödinger-Ginzburg-Landau (Sch-GL) approach in study of superconducting integrated structures

arXiv

引用

arXiv 2023年

作者： Stojewski, Bartosz Pomorski, Krzysztof Cracow University of Technology Faculty of Electrical and Computer Engineering Poland Cracow University of Technology Faculty of Computer Science and Telecommunications Poland Quantum Hardware Systems

Various superconducting lattices were simulated and can be treated as lattices of superconducting atoms with preimposed symmetry in 1, 2 and 3 dimensions. Hybrid Schrödinger-Ginzburg-Landau approach is based on the fact of the mathematical similarity of Ginzburg-Landau (GL) and Schrödinger formalisms. Starting from Schrödinger approach by change of term V (x) - E with term α(x) + β(x)|ψ(x)|2we arrived at the Ginzburg-Landau equation. In the presented relaxation algorithm we use one and two dimensional ground energy solutions of Schrödinger equation and placed them as starting trial solution for GL relaxation method. In consecutive steps we increase the nonlinear term in the GL equation which results in achieving a stable approach of solution of GL equation. The obtained numerical results and used methodology form simulation platform bases for study of superconducting integrated structures that can model various superconducting devices. In general, one can model time-dependent geometry of superconducting structures. © 2023, CC0.

关键词： Simulation platform

来源：评论

学校读者我要写书评

暂无评论

ELA: Exploited Level Augmentation for Offline Learning in Zero-Sum Games

arXiv

引用

arXiv 2024年

作者： Lei, Shiqi Lee, Kanghoon Li, Linjing Park, Jinkyoo Li, Jiachen Institute of Automation Chinese Academy of Sciences Beijing China Department of Industrial & Systems Engineering KAIST Daejeon Korea Republic of Department of Electrical and Computer Engineering University of California RiversideCA United States

Offline learning has become widely used due to its ability to derive effective policies from offline datasets gathered by expert demonstrators without interacting with the environment directly. Recent research has explored various ways to enhance offline learning efficiency by considering the characteristics (e.g., expertise level or multiple demonstrators) of the dataset. However, a different approach is necessary in the context of zero-sum games, where outcomes vary significantly based on the strategy of the opponent. In this study, we introduce a novel approach that uses unsupervised learning techniques to estimate the exploited level of each trajectory from the offline dataset of zero-sum games made by diverse demonstrators. Subsequently, we incorporate the estimated exploited level into the offline learning to maximize the influence of the dominant strategy. Our method enables interpretable exploited level estimation in multiple zero-sum games and effectively identifies dominant strategy data. Also, our exploited level augmented offline learning significantly enhances the original offline learning algorithms including imitation learning and offline reinforcement learning for zero-sum games. Copyright © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Text-Based Automatic Personality Prediction Using KGrAt-Net: A Knowledge Graph Attention Network Classifier

arXiv

引用

arXiv 2022年

Nowadays, a tremendous amount of human communications occur on Internet-based communication infrastructures, like social networks, email, forums, organizational communication platforms, etc. Indeed, the automatic prediction or assessment of individuals’ personalities through their written or exchanged text would be advantageous to ameliorate their relationships. To this end, this paper aims to propose KGrAt-Net, which is a Knowledge Graph Attention Network text classifier. For the first time, it applies the knowledge graph attention network to perform Automatic Personality Prediction (APP), according to the Big Five personality traits. After performing some preprocessing activities, it first tries to acquire a knowing-full representation of the knowledge behind the concepts in the input text by building its equivalent knowledge graph. A knowledge graph collects interlinked descriptions of concepts, entities, and relationships in a machine-readable form. Practically, it provides a machine-readable cognitive understanding of concepts and semantic relationships among them. Then, applying the attention mechanism, it attempts to pay attention to the most relevant parts of the graph to predict the personality traits of the input text. We used 2,467 essays from the Essays Dataset. The results demonstrated that KGrAt-Net considerably improved personality prediction accuracies (up to 70.26% on average). Furthermore, KGrAt-Net also uses knowledge graph embedding to enrich the classification, which makes it even more accurate (on average, 72.41%) in APP. Copyright © 2022, The Authors. All rights reserved.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

Design of ANN Based Non-Linear Network Using Interconnection of Parallel Processor

引用

computer systems Science & engineering 2023年第9期46卷 3491-3508页

作者： Anjani Kumar Singha Swaleha Zubair Areej Malibari Nitish Pathak Shabana Urooj Neelam Sharma Department of Computer Science Aligarh Muslim UniversityAligarh202002India Department of Industrial and Systems Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Technology Bhagwan Parshuram Institute of Technology(BPIT)GGSIPUNew Delhi110078India Department of Electrical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Artificial Intelligence&Machine Learning Maharaja Agrasen Institute of Technology(MAIT)GGSIPUNew Delhi110086India

Suspicious mass traffic constantly evolves,making network behaviour tracing and structure more *** networks yield promising results by considering a sufficient number of processing elements with strong interconnections between *** offer efficient computational Hopfield neural networks models and optimization constraints used by undergoing a good amount of parallelism to yield optimal *** neural network(ANN)offers optimal solutions in classifying and clustering the various reels of data,and the results obtained purely depend on identifying a *** this research work,the design of optimized applications is presented in an organized *** addition,this research work examines theoretical approaches to achieving optimized results using *** mainly focuses on designing *** optimizing design approach of neural networks analyzes the internal process of the neural *** in developing the network are based on the interconnections among the hidden nodes and their learning *** methodology is proven best for nonlinear resource allocation problems with a suitable design and complex *** ANN proposed here considers more or less 46k nodes hidden inside 49 million connections employed on full-fledged parallel *** proposed ANN offered optimal results in real-world application problems,and the results were obtained using MATLAB.

关键词： Artificial neural network(ANN) multiprocessor hidden node nonlinear optimization parallel processing

来源：评论

学校读者我要写书评

暂无评论

An Inexact Conditional Gradient Method for Constrained Bilevel Optimization

arXiv

引用

arXiv 2023年

作者： Abolfazli, Nazanin Jiang, Ruichen Mokhtari, Aryan Hamedani, Erfan Yazdandoost Department of Systems and Industrial Engineering The University of Arizona TucsonAZ United States Department of Electrical and Computer Engineering The University of Texas AustinTX United States

Bilevel optimization is an important class of optimization problems where one optimization problem is nested within another. While various methods have emerged to address unconstrained general bilevel optimization problems, there has been a noticeable gap in research when it comes to methods tailored for the constrained scenario. The few methods that do accommodate constrained problems, often exhibit slow convergence rates or demand a high computational cost per iteration. To tackle this issue, our paper introduces a novel single-loop projection-free method employing a nested approximation technique. This innovative approach not only boasts an improved per-iteration complexity compared to existing methods but also achieves optimal convergence rate guarantees that match the best-known complexity of projection-free algorithms for solving convex constrained single-level optimization problems. In particular, when the hyper-objective function corresponding to the bilevel problem is convex, our method requires Õ(ϵ−1) iterations to find an ϵ-optimal solution. Moreover, when the hyper-objective function is non-convex, our method’s complexity for finding an ϵ-stationary point is O(ϵ−2). To showcase the effectiveness of our approach, we present a series of numerical experiments that highlight its superior performance relative to state-of-the-art methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Gradient methods

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：