检索结果-内蒙古大学图书馆

32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Wasinski, Frank Bonath, Werner Ricklefs, Ubbo Borcsok, Josef Schwarz, Michael Hahn, Eike University of Applied Sciences THM Dept. of Electrical Engineering and Information Technology Giessen Germany Institute for Computer Architecture and System Programming University of Kassel ICAS Kassel Germany

ISBN: (纸本)9798350399714

Optical speed sensors based on the spatial frequency filter method are a proven technology that offer high measurement accuracy over a wide speed range. Newly developed variants also enable measurements at very low speeds and increase the robustness of the method [1]. This makes the sensor very suitable for use in the area of functional safety. A measurement chain up to safety integrity level 3 (SIL3) should be feasible via a combination with a safety system on a chip (SoC) for evaluating the measurement data and an extension of the sensor module to include safety-related elements [2], [3]. By integrating the sensor at IC level, a compact overall solution is to be made possible. After the first successful tests with the safety SoC, further examinations of the measuring method with regard to functional safety are now necessary. © 2023 IEEE.

关键词： System-on-chip

来源：评论

学校读者我要写书评

暂无评论

Exploring the Growth of Blockchain Literature: Insights from 2016 to 2024

Exploring the Growth of Blockchain Literature: Insights from...

引用

2024 International Conference on Smart Devices, ICSD 2024

作者： Kumar, Amit Sharma, Neha Chauhan, Rahul Joshi, Kireet Chythanya, Kanegonda Ravi Ismail Iqbal, Mohammed Chitkara University Institute of Engineering & Technology Chitkara University Punjab Rajpura India Graphic Era Hill University Computer Science & Engineering Dehradun India Graphic Era Deemed to be University Computer Science & Engineering Uttarakhand Dehradun248002 India SR University School of Computer Science & Artificial Intelligence Warangal India University of Technology and Applied Sciences Petroleum Engineering Department Nizwa Oman

ISBN: (纸本)9798350394412

This bibliographic analysis research addresses the evolving landscape of blockchain research from 2016 to 2024. The introduction identifies the problem of understanding the current state and trends of blockchain literature, given the technology's rapid growth and diverse applications. Research gaps are identified in terms of understanding productivity, collaboration patterns, and emerging topics within the field. To address these gaps, the study conducts a comprehensive analysis using bibliometric techniques on data extracted from the Scopus database. The analysis reveals that China, the USA, and India emerge as the top three contributors, collectively accounting for 68% of the total publications and demonstrating substantial productivity and collaboration within the research community. Moreover, the study highlights the increasing focus on topics such as smart contracts (15%), digital storage (12%), and consortium blockchains (14%), indicating emerging areas of interest and research priorities. Security-related concerns remain prevalent, as evidenced by the frequent co-occurrence of keywords related to network security and cryptography. Additionally, the analysis underscores the diverse range of applications and implications of blockchain technology, spanning industries such as finance, supply chain management, and healthcare. By synthesizing these findings, the study contributes to a deeper understanding of the evolving landscape of blockchain research and provides insights for future research directions and collaborations. © 2024 IEEE.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of CNN and SVM Machine Learning Techniques for Plant Disease Detection 4th

Comparative Analysis of CNN and SVM Machine Learning Techniq...

引用

4th International Conference on Data, Engineering, and Applications, IDEA 2022

作者： Adeniyi, Abidemi Emmanuel Madamidola, Olugbenga Ayomide Awotunde, Joseph Bamidele Misra, Sanjay Agrawal, Akshat Department of Computer Science College of Computing and Communication Studies Bowen University Iwo Nigeria Department of Information Technology Federal University of Technology Akure Nigeria Department of Computer Science Faculty of Communication and Information Sciences University of Ilorin Ilorin Nigeria Department of Applied Data Science Institute for Energy Technology Halden Norway Department of Computer Science & Engineering Amity University Haryana Gurugram122412 India

ISBN: (纸本)9789819700363

The growing advancement of different jobs, skills and businesses has stimulated the spread of diseases. Most of the time, these diseases can cross countries’ borders and spread at a very rapid rate. Avoiding and detecting these infections have proved to be a major problem for our public health and one that must be treated with great importance. Crop disease has haunted, farmers have been victimized for several decades, and a remedy must be offered to halt this damage. As a result, a system should be developed to detect plant disease. Untreated plant diseases ultimately result in a loss to the farmer. Traditional methods of detecting plant disease have become less efficient and inaccurate;thus there is need to improve on the techniques of plant disease detection, as a reliable detection of plant diseases will greatly improve the quality of food crops produced and decrease the threat plant diseases pose to food security. Therefore, this study is aimed at analyzing comparatively, two machine learning language techniques convolutional neural network (CNN) and support vector machine (SVM) in terms of their respective accuracy in detecting plant diseases through their leaves in which both algorithms are used for the automatic diagnosis of plant disease. From the experimental test conducted on various plants using CNN and SVM algorithms, CNN had an accuracy of 98%, while SVM had an accuracy of 62% on various plant leaves used. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Enhancing Compressive Strength Prediction in Fiber Reinforced Geopolymer Concrete Through Machine Learning Algorithms 6

Enhancing Compressive Strength Prediction in Fiber Reinforce...

引用

6th IEEE International Conference on Recent Advances in Intelligent Computational Systems, RAICS 2024

作者： Thakur, Gaurav Agarwal, Arun Kumar Singh, Ajay Yamsani, Nagendar Uttaranchal University Department of Civil Engineering Uttaranchal Institute of Technology Dehradun India School of Applied & Life Sciences Uttaranchal University Dehradun India School of Computer Science and Artificial Intelligence Sr University Warangal India

ISBN: (纸本)9798350381689

This research focuses on accurately predicting the compressive strength of Fiber Reinforced Geopolymer Concrete (FRGC) using machine learning techniques, considering the material's complexity and diverse factors influencing its strength. A machine learning model was developed to forecast the compressive strength of FRGC, leveraging data analysis and comparison of regression techniques. Linear Regression, Lasso Regression, and Ridge Regression were assessed for their predictive accuracy. Feature selection methods were employed to identify influential factors impacting compressive strength. The Random Forest Regressor emerged as the most effective model, exhibiting the lowest Root Mean Square Error (RMSE). The findings offer a valuable tool for engineers to optimize FRGC properties, enhancing its strength and sustainability for various applications. This study underscores the potential of machine learning in streamlining material design processes in civil engineering. © 2024 IEEE.

关键词： Geopolymer concrete

来源：评论

学校读者我要写书评

暂无评论

Towards a Better Data Collection of Crisis Situations Based on Ontologies

引用

SN computer Science 2022年第5期3卷 383页

作者： Maalel, Ahmed Higher Institute of Applied Sciences and Technology University of Sousse Sousse Tunisia RIADI Laboratory National School of Computer Science ENSI Manouba Tunisia

In our research work, we were confronted with many complex real problems such as the problem of risk analysis and natural disasters. Within the framework of these real problems, we encountered difficulties in the process of acquiring knowledge since, in effect, experts in the field find it difficult to make explicit the varied and implicit knowledge they hold, and also, the variety and the multiplicity of the actors involved and in particular the sources of data. The use of semantic Web technologies and ontologies has been recognized as a suitable solution to address these challenges. This article proposes an ontology-based representation of crisis situations providing a unified and sharable knowledge base between crisis response stakeholders: from a theoretical point of view, the generic dimensions of crisis response are defined while from a technical point of view, we describe a mobile app allowing the responders on the field to send status updates regarding what is currently happening on the field to the decision makers who use the dashboard to view the reports, send notifications and many more. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Crisis response Crisis situation Data collection Ontologies

来源：评论

学校读者我要写书评

暂无评论

Implementation of QKD BB84 Protocol in Qiskit 19

Implementation of QKD BB84 Protocol in Qiskit

引用

19th International Bhurban Conference on applied sciences and Technology, IBCAST 2022

作者： Saeed, Muhammad Haroon Sattar, Hassan Durad, Muhammad Hanif Haider, Zeshan Pakistan Institute of Engineering and Applied Science Nilore National Institute of Lasers and Optronics College Islamabad45650 Pakistan Pakistan Institute of Engineering and Applied Sciences Nilore Department of Computer & Information Sciences Islamabad45650 Pakistan

ISBN: (数字)9781665460514

ISBN: (纸本)9781665460514

Quantum cryptography is a practical method of secret communication that guarantees the foolproof secrecy. This paper presents the simulation for implementation of a Quantum Key Distribution (QKD) protocol BB84, the pioneering, and most basic and fundamental protocol. We use the quantum computing platform developed by IBM named as Qiskit for the simulation of the BB84 protocol, implementing it with and without an Eve eavesdropper for studying the relative outcomes. Recently, Qiskit is globally very popular for quantum simulations because it provide us the opportunity to simulate quantum logic circuit on classical computer as well as real quantum computers owned by IBM. As per our best knowledge, there is no any proposal published for quantum circuit by anyone for BB84 QKD. We performed experimentation on local as well as cloud simulators: 1) The "qasm-simulator"was used as local machine simulator, and 2) The "ibmqx2"simulator was used as IBM cloud quantum simulator. The outcome of local as well as IBM simulator with and without an eavesdropper, between the two parties involved in key exchange were recorded and presented in the results section. © 2022 IEEE.

关键词： Quantum cryptography

来源：评论

学校读者我要写书评

暂无评论

Supervised Machine Learning for Text Analysis in R

引用

Quarterly Publications of the American Statistical Association 2023年第543期118卷 2207-2209页

作者： Martin Holub Patrícia Martinková a Institute of Formal and Applied Linguistics Charles University b Institute of Computer Science Czech Academy of Sciences

来源：评论

学校读者我要写书评

暂无评论

Synthetic fields, real gains Enhancing smart agriculture through hybrid datasets 44

Synthetic fields, real gains Enhancing smart agriculture thr...

引用

Die 44. Jahrestagung der Gesellschaft fur Informatik in der Land-, Forst- und Ernahrungswirtschaft 2024 - 44th Annual Conference of the German Association for Informatics in Agriculture, Forestry, and the Food Sector 2024

作者： Wachter, Paul Kruse, Niklas Schöning, Julius Osnabrück University Institute of Cognitive Science Neuer Graben 29 49074 Germany Osnabrück University of Applied Sciences Faculty of Engineering and Computer Science Albrechtstr. 30 Osnabrück49076 Germany

ISBN: (纸本)9783885797388

Artificial intelligence (AI) promises transformative impacts on society, industry, and agriculture, while being heavily reliant on diverse, quality data. The resource-intensive "data problem" has initialized a shift to synthetic data. One downside of synthetic data is known as the "reality gap", a lack of realism. Hybrid data, combining synthetic and real data, addresses this. The paper examines terminological inconsistencies and proposes a unified taxonomy for real, synthetic, augmented, and hybrid data. It aims to enhance AI training datasets in smart agriculture, addressing the challenges in the agricultural data landscape. Utilizing hybrid data in AI models offers improved prediction performance and adaptability. © 2024 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Data assimilation

来源：评论

学校读者我要写书评

暂无评论

Compliance of agricultural AI systems - app-based legal verification throughout the development 44

Compliance of agricultural AI systems - app-based legal veri...

引用

作者： Kruse, Niklas Wachter, Paul Schöning, Julius Osnabrück University Institute of Cognitive Science Neuer Graben 29 49074 Germany Osnabrück University of Applied Sciences Faculty of Engineering and Computer Science Albrechtstr. 30 Osnabrück49076 Germany

ISBN: (纸本)9783885797388

Significant advances in artificial intelligence (AI) have been achieved;however, practical implementation in agriculture remains limited. Compliance with emerging regulations, such as the EU AI Act and GDPR, is now vital, even for non-critical AI systems. Developers need tools to assess legal compliance, which is complex, often requiring full legal advice. To address this issue, we are developing a support app that simplifies the legal aspects of AI system development, covering the entire lifecycle, from conception to distribution. The current app, which covers the key legal area of copyright and will soon include GDPR and the AI Act, aims to bridge the gap between AI research and agriculture. An evaluation of our app by experts from both the legal and the IT domains shows that the app assists the developers so that they make legally correct statements. Consequently, it promotes legal compliance and awareness among developers, contributing to the seamless integration of AI into agriculture. The need for compliant AI systems in various industries, including agriculture, will only increase as regulations evolve. © 2024 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： agriculture AI compliance decision support application ethical AI law

来源：评论

学校读者我要写书评

暂无评论

Ultra-Low Power Designs and Strategies for Next-Generation Sensor Networks 7

Ultra-Low Power Designs and Strategies for Next-Generation S...

引用

7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Gupta, Priyanka Revathi, V. Hameed, Ali Abduhussien Gupta, Manish Yadav, Suman Avdhesh Rao, Bolleddu Devananda Institute of Aeronautical Engineering Department of Computer Science and Engineering Telangana Hyderabad India New Horizon College of Engineering Department of Applied Sciences Bangalore India The Islamic University College of Medical Technology Radiology Techniques Department Najaf Iraq Lovely Professional University Phagwara India Iilm University Department of Computer Science & Engineering Uttar Pradesh Greater Noida India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India

ISBN: (纸本)9798350350067

Energy-efficient design and operation are essential for next-generation sensor networks to persist and require less maintenance. This paper describes a novel energy-efficient sensor network. It uses superior data routing and aggregation. Three novel algorithms-EARA, DFAA, and Adaptive Data Sampling-make this strategy practicable. EARA sends data with little energy, DFAA collects all data to eliminate duplicates, and ADSA adjusts sample rates based on relevance and variability. Each piece of software sends, manages, and changes sample rates with minimal energy. This innovative energy-saving strategy is tested against static-duty cycling, non-adaptive data aggregation, fixed-rate data sampling, high-energy data transmission, centralized data routing, and unoptimized sensor node location. The recommended solution outperforms network lifetime, energy usage, data accuracy, latency, scalability, and dependability. Energy savings, ease of use, affordability, adaptability, long-lastingness, and network lifespan are usually better with the proposed response. Scatter plots illustrate how much better the proposed method saves energy and works properly. The EARA, DFAA, and ADSA algorithm-based techniques offer great potential for energy-efficient sensor networks. This strategy stabilizes and prolongs sensor network configurations by optimizing data pathways, aggregating data, and adaptively sampling data. The results show that it works, making it a novel strategy for the future generation of sensor networks that demand higher performance and less energy. © 2024 IEEE.

关键词： Adaptive Data Sampling Data Aggregation Data Management Energy Consumption Energy Efficiency Energy-Aware Routing Network Lifetime Performance Evaluation Sensor Networks Sustainability

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：