检索结果-内蒙古大学图书馆

32nd International Conference on Software, Telecommunications and computer Networks, SoftCOM 2024

作者： Remenyi, Armin Alsaleh, Saleh Tepljakov, Aleksei Tallinn University of Technology Dept. of Software Science Tallinn Estonia Tallinn University of Technology Dept. of Computer Systems Tallinn Estonia

ISBN: (纸本)9789532901382

This research paper delves into the evaluation of human-machine interactions within the realm of Extended Reality (XR) applications, focusing on the integration of Digital Twins (DT) for control systems. The research explores multiple XR interaction methods and assesses their efficacy in enhancing user experience and operational efficiency in industrial settings, specifically in control systems. The study employs advanced tools such as the Microsoft HoloLens 2 headset, Unreal Engine 5, and the Mixed Reality Toolkit (MRTK) to develop and test XR interaction methods. Data collection and analysis involves usability testing using the System Usability Scale (SUS) and the NASA Task Load Index (NASA-TLX) to measure cognitive, physical and temporal demands on users. The findings highlight the most effective XR interaction strategies, providing valuable insight for future research and practical implementations in intelligent manufacturing environments. © 2024 University of Split, FESB.

关键词： NASA

来源：评论

学校读者我要写书评

暂无评论

Small object detection in diverse application landscapes: a survey

引用

Multimedia Tools and Applications 2024年第41期83卷 88645-88680页

作者： Iqra Giri, Kaisar J. Javed, Mohammed Department of Computer Science Islamic University of Science & Technology Pulwama India Computer Vision & Biometrics Lab Dept. of IT Indian Institute of Information Technology Allahabad India

The importance of object detection within computer vision, especially in the context of detecting small objects, has notably increased. This thorough survey extensively examines small object detection across various applications, consolidating and outlining the available methodologies. Traditional papers on small object detection have focused on specific domains. However, this survey paper incorporates insights from a multitude of domains, providing a comprehensive understanding of the versatility and applicability of small object detection techniques. This paper sheds light on the key challenges faced and delves into potential solutions to address the challenges, offering insights into viable solutions to enhance small object detection performance, setting it apart from existing literature. The strategies identified in our survey encompass a spectrum of approaches, categorized as transformer-based, CNN, and traditional methods. Also, this paper collates prevalent datasets relevant to small object detection, simplifying access to these resources. Further, it provides a succinct overview of diverse evaluation metrics used for performance assessment in this field, enhancing understanding of the effectiveness and proficiency of these methods. This survey paper not only consolidates established knowledge but also highlights innovative viewpoints, providing a comprehensive and enlightening compilation that contributes to the advancement of small object detection in the field of computer vision. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Integration between Bioinformatics Algorithms and Neutrosophic Theory

引用

Neutrosophic Sets and systems 2024年 66卷 34-54页

作者： Farag, Romany M. Shams, Mahmoud Y. Aldawody, Dalia A. Khalid, Huda E. El-Bakry, Hazem M. Salama, Ahmed A. Dept. of Math and Computer Science Faculty of Science Port Said Univ. Egypt Dept. of Machine Learning Faculty of Artificial Intelligence Kafrelsheikh University Egypt Telafer University Telafer Iraq Dept. of Information Systems Faculty of Computer and Information Sciences Mansoura University Egypt Dept. of Math and Computer Science Faculty of Science Port Said University Egypt

This paper presents a neutrosophic inference model for bioinformatics. The model is used to develop a system for accurate comparisons of human nucleic acids, where the new nucleic acid is compared to a database of old nucleic acids. The comparisons are analyzed in terms of accuracy, certainty, uncertainty, neutrality, and bias. The proposed system achieves good results and provides a reliable standard for future comparisons. It highlights the potential of neutrosophic inference models in bioinformatics applications. Data mining and bioinformatics play a crucial role in computational biology, with applications in scientific research and industrial development. Biological analysts rely on specialized tools and algorithms to collect, store, categorize, and analyze large volumes of unstructured data. Data mining techniques are used to extract valuable information from this data, aiding in the development of new therapies and understanding genetic relationships between organisms. Recent advancements in bioinformatics include gene expression tools, Bio sequencing, and Bio databases, which facilitate the extraction and analysis of vital biological information. These technologies contribute to the analysis of big data, identification of key bioinformatics insights, and generation of new biological knowledge. Data collection, analysis, and interpretation in this field involves the use of modern technologies such as cloud computing, machine learning, and artificial intelligence, enabling more efficient and accurate results. Ultimately, data mining and bioinformatics enhance our understanding of genetic relationships, aid in developing new therapies, and improve healthcare outcomes. © (2024), (Neutrosophic Sets and systems). All rights reserved.

关键词： Bioinformatics

来源：评论

学校读者我要写书评

暂无评论

A Novel Identity Authentication Mechanism forUnmanned Maritime Vessels Communication Based on MITRE ATT&CK Framework

引用

Journal of Marine science and technology (Taiwan) 2024年第2期32卷 170-180页

作者： He, Jun-Xian Chang, Shih-Hao Dept. of Computer Science and Information Engineering Tamkang University New Taipei City Taiwan Dept. of Computer Science and Information Engineering National Taipei University of Technology Taipei City Taiwan

With the development of the smart shipping industry, unmanned vessel technology is rapidly evolving, accompanied by a demand for robust Internet of Things (IoT) communication security practices. Key communication technologies for the operation of unmanned vessels include external vessel communication. One crucial aspect is the verification of the identities of the parties involved in these communication systems, as this ensures secure and trusted interactions between unmanned vessels and port management authorities. Identity authentication plays a vital role in ensuring the secure communication of unmanned vessels. This paper aims to analyze potential risks related to identity authentication technology in unmanned vessel communication systems. To effectively address these risks, we propose leveraging digital certificates and blockchain technology to achieve device non-repudiation and substitution. Based on this technology, we organize and implement defense strategies using the MITRE ATT&CK framework. This framework provides a comprehensive and systematic approach to understanding potential threats and designing appropriate defense measures. By utilizing this framework, security teams can better comprehend vulnerabilities and formulate effective countermeasures. To validate the effectiveness of the proposed defense framework, we conducted simulation experiments. These experiments helped us evaluate the efficiency and reliability of the strategies in real-world scenarios. Through these experiments, we could ascertain whether the countermeasures effectively mitigated the identified risks and ensured the secure communication of unmanned vessels. © 2024 National Taiwan Ocean University

关键词： Risk assessment

来源：评论

学校读者我要写书评

暂无评论

A Novel Music Recommendation System Using Filtering Techniques

引用

Informatica (Slovenia) 2024年第4期48卷 595-610页

作者： Vashishtha, Srishti Varshney, Deepika Sarin, Eva Kaur, Simran Computer Science and Engineering Dept. Bharati Vidyapeeth’s College of Engineering GGSIPU New Delhi India Computer Science and Engineering Dept. Jaypee Institute of Information Technology Noida India

With the growth of the World Wide Web, a large amount of music data is available on the Internet. A large number of people listen to music online rather than downloading and listening offline. But only some sites provide personalized and accurately recommended songs while they listen to an auto-playing playlist. Hence the need for recommendation systems arises. Two approaches can be applied to the recommendation system: content based filtering and collaborative filtering. While in content-based filtering approach, analysis on the songs’ content which has been preferred by the user in history is done and the songs with relative similarity are recommended. While latter suggests songs that certain users of similar listening pattern have preferred. But collaborative filtering-based recommendation systems not only requires time to attain stability but also might recommend unsuitable music because it is not personalized to each user’s preference. Also, the latter requires the songs to be listened by a few users already to recommend it any other user. Hence for overall analysis, answers to few questions need to be implemented in recommendation systems: the very first one is how the properties should be analyzed, next one is how the analysis should be done and last is how the songs related to the user’s preference should be chosen. So, for suggesting the better system which solves these three questions as well as provides better and personalized recommendations, In this paper we build a collaborative filtering as well as content based filtering recommendation system, where various factors determine the essence of the songs, i.e. liveliness, keys used, loudness, pitch, valence, etc., are analyzed for comparison. From the experimental analysis in has been identified that content-based filtering technique performed best on KNN machine learning classifier with accuracy of 85%. © 2024 Slovene Society Informatika. All rights reserved.

关键词： Collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

ASPECTS REGARDING THE BEHAVIOR OF MOLD CHEESE AT PENETRATION WITH CONES AND NEEDLES, AT MATURATION

引用

UPB Scientific Bulletin, Series D: Mechanical Engineering 2024年第4期86卷 289-304页

作者： Pana, Gratiela-Florinela Voicu, Gheorghe Ipate, George Tudor, Paula Stefan, Elena-Madalina Begea, Mihaela Dept. of Biotechnical Systems National University of Science and Technology POLITEHNICA Bucharest Romania National University of Science and Technology POLITEHNICA Bucharest Romania

The purpose of this study is to conduct a detailed investigation into the characteristics of moldy cheeses, aiming for a deeper understanding of the maturation process, the evolution of texture, and their physical properties. The penetration behavior of the Roquefort, Gorgonzola, Brie and Camembert cheeses is studied using both cone and needle methods, determining the dept. of penetration at various points across the diameter of the circle circumscribed around samples of different geometrical shapes. The variation of shear tangential tension of these cheeses is determined in relation to the penetration dept., and the logarithmic-type variation law is verified for the relationship between these characteristic quantities. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Needles

来源：评论

学校读者我要写书评

暂无评论

A COMPARATIVE STUDY OF SUPPORT VECTOR MACHINE AND RISK DETERMINISTIC APPROACH ON A PHOTOVOLTAIC SYSTEM

UPB Scientific Bulletin, Series C: Electrical Engineering an...

引用

UPB Scientific Bulletin, Series C: Electrical Engineering and computer science 2024年第3期86卷 67-80页

作者： Colbu, Ștefania-Cristiana Băncilă, Daniel-Marian Petrescuniță, Alina Popescu, Dumitru Olteanu, Severus-Constantin Dept. of Automatic Control and Systems Engineering National University of Science and Technology POLITEHNICA Bucharest Romania Dept. of Mathematical Methods and Models National University of Science and Technology POLITEHNICA Bucharest Romania

The present paper introduces a comparative analysis of the management of a stochastic optimization problem using both a risk deterministic approach and a support vector machine strategy. This optimization problem is formulated in consideration of the influence produced by environmental factors, such as irradiance and temperature, on a photovoltaic panel. The problem will be solved by applying both methods to determine the Maximum Power Point (MPP), thereby to enhance the power generation efficiency. The primary objective is to conduct an analysis comparing the two approaches, with the aim of recommending the most suitable approach for Maximum Power Point Tracking (MPPT). © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： machine learning photovoltaics risk optimization support vector machine for regression

来源：评论

学校读者我要写书评

暂无评论

Analysis of Arabs Publications In the Field of computer Networks 14

Analysis of Arabs Publications In the Field of Computer Netw...

引用

14th International Conference on Information and Communication systems, ICICS 2023

作者： El-Bashabsheh, Emran Younes, Mutaz Shatnawi, Mohammed Jordan University of Science and Technology Dept. of Computer Information Systems Irbid Jordan Jordan University of Science and Technology Dept. of Computer Science Irbid Jordan

ISBN: (纸本)9798350307870

Increasing technology led to increasing collaboration between the countries in general, especially the Arabic world. In recent years, many impacts affect the growth of research work in different Arabic countries. In this research, we show the growth of research work and its quality between Arabs and the rest of the world. We collected over 2500 publications and used it to create a new table that contains the intersection between each Arab country and each co-author's continent to show the relationship between each Arabic country with the rest of the world. We divided the data into two periods, before and after 2015, then we used Hue to apply our analysis on the data. We focused on the number of publications and the number of citation for each Arabic country. We noticed the rapid growth in the last period in some Arabic countries such as Jordan, Qatar, United Arab Emirates, and Saudi Arabia. In contrast, the rest of the countries had slow or decreasing growth. © 2023 IEEE.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

A review on 3D image reconstruction on specific and generic objects

引用

Materials Today: Proceedings 2023年 80卷 2400-2405页

作者： Shalma, H. Selvaraj, P. Dept. of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur Chennai India Dept. of Information Technology SRM Institute of Science and Technology Kattankulathur Chennai India

With the emergence of various techniques involved in deep learning the researchers of computer vision tends to focus on the strategies such as object recognition and segmentation of image. This has inclined to accomplish the deep learning techniques in 3D reconstruction of both specific and generic objects. As the space for reconstruction of 3D images either in single or multi view has envisioned the researchers to concentrate on the available technologies used for reconstruction. With the available built in methods and technologies in deep learning, the performance of the proposed methods were reviewed and analyzed using several parameters. As the remaking of 2D images is still in the beginning stage, it is important to study the 3D shape representations, various network architecture, methodologies and approaches behind 3D reconstruction. In this work a review of deep learning methods for single or multiple RGB images of specific and generic object 3D reconstruction was done. Several methods and their importance were also discussed along with the challenges encountered and with further research directions. This paper critically analyzes the various 3D Shaped Representations, 3D Data Network Architectures, dept. Estimation methods, Multi View Representations and the Data Representation Techniques. © 2021

关键词： Object recognition

来源：评论

学校读者我要写书评

暂无评论

LightNN: An Optimized Deep Learning Framework for Enhanced Fruit Classification

LightNN: An Optimized Deep Learning Framework for Enhanced F...

引用

2024 IEEE International Conference on Computing, Applications and systems, COMPAS 2024

作者： Afroj, Maharin Jahan, Israt Islam, Md Polash Saifur Rahman, Md. Bangladesh University of Business and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh Stockholm University Dept. of Computer and Systems Sciences Stockholm Sweden

ISBN: (纸本)9798331529765

The crucial field of fruit classification in computer vision and deep learning brings about breakthroughs that have broad applications in the retail and agricultural industries. By automating the identification and sorting of various fruit types, these technologies enhance efficiency, accuracy, and scalability, benefiting processes from farm production to market distribution. The integration of sophisticated algorithms and neural networks not only improves the speed and reliability of fruit classification but also offers the potential for real-time quality control and inventory management, revolutionizing traditional methods and paving the way for more innovative, data-driven approaches in these sectors. This study introduces LightNN, a novel and effective paradigm with a lightweight architecture that tackles the complex problems related to computational efficiency. Combining a small classifier with a simplified feature extractor, LightNN achieves the ideal balance between simplicity and accuracy. The feature extractor is capable of extracting hierarchical features from RGB images by using convolutional layers with ReLU activations and max-pooling procedures. The flattened output is then processed by the classifier, which consists of fully connected layers with ReLU activations and dropout regularisation. Remarkably, LightNN, with just 298,835 parameters, manages to get a respectable 96.37% test accuracy in fruit categorization tasks. The results highlight LightNN's promise as an effective and efficient fruit classifying method, particularly in situations with constrained computational resources. © 2024 IEEE.

关键词： Fruits

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：