检索结果-内蒙古大学图书馆

Competing with autonomous model vehicles:a software stack for driving in smart city environments

Autonomous Intelligent Systems 2024年第1期4卷 166-178页

作者： Julius Bächle Jakob Häringer Noah Köhler Kadir-KaanÖzer Markus Enzweiler Reiner Marchthaler Institute for Intelligent Systems Faculty of Computer Science and EngineeringEsslingen University of Applied SciencesFlandernstraße 101Esslingen am Neckar73732Germany

This article introduces an open-source software stack designed for autonomous 1:10 scale model *** developed for the Bosch Future Mobility Challenge(BFMC)student competition,this versatile software stack is applicable to a variety of autonomous driving *** stack comprises perception,planning,and control modules,each essential for precise and reliable scene understanding in complex environments such as a miniature smart city in the context of *** the limited computing power of model vehicles and the necessity for low-latency real-time applications,the stack is implemented in C++,employs YOLO Version 5 s for environmental perception,and leverages the state-of-the-art Robot Operating System(ROS)for inter-process *** believe that this article and the accompanying open-source software will be a valuable resource for future teams participating in autonomous driving student *** work can serve as a foundational tool for novice teams and a reference for more experienced *** code and data are publicly available on GitHub.

关键词： Autonomous model vehicle Software architecture Embedded real-time systems Bosch Future Mobility Challenge Autonomous driving

来源：评论

学校读者我要写书评

暂无评论

An electron-transfer-tuning strategy at the graphene/metal interface for improving acidic water electrolysis in proton exchange membrane electrolyzers

引用

Journal of Energy Chemistry 2025年第4期103卷 344-352页

作者： Yue Xu Shuaidong Li Yingjian He Fumiya Shiokawa Samuel Jeong Aimi Asilah Haji Tajuddin Zeyu Xi Yoshikazu Ito Jingzi Zhang Zeyun Cai Xi Lin Kailong Hu School of Materials Science and Engineering and Institute of Materials Genome&Big DataHarbin Institute of TechnologyShenzhen 518055GuangdongChina Institute of Special Environments Physical Sciences Harbin Institute of TechnologyShenzhen 518055GuangdongChina School of Computer Science and Technology Harbin Institute of TechnologyShenzhen 518055GuangdongChina Institute of Applied Physics Graduate School of Pure and Applied SciencesUniversity of TsukubaTsukuba 305-8573Japan

Graphene encapsulation has been shown to be an effective technique for improving the corrosion resistance of non-noble metal catalysts for the acidic water *** key challenge lies in enhancing the electrocatalytic activity of graphene-encapsulated metals while maintaining their durability in acidic ***,an electron-transfer-tuning strategy is investigated at the graphene/NiMo interface,aiming to improve the hydrogen evolution reaction(HER)performance of graphene-encapsulated NiMo *** doping of Ti,a low electronegativity element,into NiMo substrate was confirmed to increase electron transfer from the metal core toward the *** electron-rich state on graphene facilitates the adsorption of positively charged protons on graphene,thereby enabling a Pt/C-comparable performance in 0.5 M H_(2)SO_(4),with only a 3.8%degradation in performance over a 120-h continuous *** proton exchange membrane(PEM)water electrolyzer assembled by the N-doped grapheneencapsulated Ti-doped NiMo exhibits a smaller cell voltage to achieve a current density of 2.0 A cm^(-2),in comparison to the Pt/C based *** study proposes a novel electron-transfer-tuning strategy to improve the HER activity of graphene-encapsulated non-noble metal catalysts without sacrificing durability in acidic electrolytes.

关键词： Hydrogen evolution Acidic media Graphene encapsulation Interface Proton exchange membrane

来源：评论

学校读者我要写书评

暂无评论

Using Autoencoder as Feature Extractor for Malware Detection

Using Autoencoder as Feature Extractor for Malware Detection

引用

2024 International Conference on IT and Industrial Technologies, ICIT 2024

作者： Tayyab, Umm-E-Hani Khan, Faiza Babar Durad, Muhammad Hanif Hussain, Mureed Department of Computer Information Sciences Pakistan Institute of Engineering and Applied Sciences Islamabad Pakistan CESAT Islamabad Pakistan

ISBN: (纸本)9798331504465

Malware detecting approaches suffer many limitations, and all anti-malware solutions have failed to be reliable enough for detecting zero day malware. Signature based solutions depend upon the signatures generated only when malware surfaces at least once in the cyber world. Another approach that works by detecting the anomalies caused in the environment can easily be defeated by diligently and intelligently written malware. Solutions trained to observe the behavior for detecting malicious files have failed to cater to the malware capable of detecting the sandboxed or protected environment. Machine learning and deep learning based approaches greatly suffer in training their models with either an imbalanced dataset or an inadequate number of samples. AI based anti-malware solutions that have been trained with enough samples targeted a selected feature vector thus ignoring the input of leftover features in the maliciousness of malware just to cope with the lack of underlying hardware’s processing power. Our research focuses on producing an anti-malware solution for detecting malicious PE files by circumventing the earlier mentioned shortcomings. Our proposed framework, which is based upon automated feature engineering through autoencoders, trains the model over a fairly large dataset. It focuses on the visual patterns of malware samples to automatically extract the meaningful part of the visual pattern. Our experiment has successfully produced a state-of-the-art accuracy of 99.54. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

DIGILOG: Towards a Monitoring Platform for Digital Transformation of European Communities

DIGILOG: Towards a Monitoring Platform for Digital Transform...

引用

2024 Joint International Conferecence on Research Challenges in Information Science Workshops and Research Projects Track, RCIS-WS and RP 2024

作者： Gerber, Jonathan Saxer, Jasmin S. Kreiner, Bruno B. Weiler, Andreas Institute of Computer Science Zurich University of Applied Sciences Technikumstrasse 9 Winterthur8401 Switzerland

DIGILOG is an interdisciplinary research project between computer and Political Science. The goal of the research project is to monitor and evaluate the digital transformation of the local governments of Europe. The project will generate coherent data for a systematic comparison using methodological triangulation, i.e., quantitative and qualitative methods. It will take the form of a regular and automated quantitative survey of all local authorities in 47 European countries (members of the Council of Europe), based on web crawling and machine learning techniques - this is a novel approach in the context of the social sciences - and qualitative research, namely case studies in selected European countries. Renowned scholars from the University of Potsdam, ZHAW, and the Vienna University of Economics and Business, with extensive experience in local government and comparative research, form the consortium of this project. Key project deliverables will be an openly accessible monitoring platform of digital transformation at the local tier of government, journal articles, an edited volume, and publications for practitioners. The real-time platform "Monitoring Digital Transformation in European Local Governments" will be accessible to researchers and practitioners worldwide and contribute to a better understanding of long-term developments. The duration of the project submitted to the SNSF/DFG is three years;however, by automating the process, the real-time platform will continue to exist and be updated regularly beyond this time frame. The research project will yield policy-relevant knowledge concerning local digitization measures from a European perspective, which can then be utilized to improve policymaking for future public sector modernization. © 2024 Copyright for this paper by its authors.

关键词： Web crawler

来源：评论

学校读者我要写书评

暂无评论

An Enhancement of Object Detection Using YOLO V8 and Mobile Net in Challenging Conditions

引用

SN computer Science 2025年第4期6卷 1-20页

作者： Pasupuleti, Shailaja Ramalakshmi, K. Gunasekaran, Hemalatha Arokiaraj, Rex Macedo Debnath, Saswati Jebaseeli, T. Jemima Department of Computer Science and Engineering Alliance University Karnataka Anekal Bangalore India AU-Centre of Excellence Department of Computer Vision Alliance University Karnataka Anekal Bangalore India College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman Department of Information Technology College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman Department of Computer Science and Engineering Alliance University Karnataka Bangalore India Division of Artificial Intelligence and Machine Learning Karunya Institute of Technology and Sciences Coimbatore India

Autonomous drones and deep learning neural networks are becoming popular tools to revolutionize aircraft operations by partially automating visual inspection processes in aircraft maintenance. The research aims to provide a trustworthy method for locating and classifying surface flaws on aircraft, such as dents, fractures, corrosion, and a few other anomalies. To assess the model performance with and without a lightweight network integration, the implementation merges YOLOv8 and Mobile Net architectures, using dropout regularization and data augmentation approaches. To guarantee the model's performance in low-light situations, the dataset has been carefully selected to contain images replicating such settings. Annotation, environment setup, model training, and online dataset scraping are all covered by the thorough technique. A web-scraped dataset is used to train and validate two popular semantic segmentation algorithms, YOLOv8 and Mobile Net, which show enough performance for segmenting and grading aircraft surface problems in practical settings. The results show that precision and recall values are improved using a hybrid technique that ensembles trained Mobile Net and YOLOv8 models. Using COCO metrics, in the proposed approach an assessment of Ensemble WBF, Mobile Net-YOLO, and YOLOv8 outcomes on test and validation sets, guaranteed reliable object recognition and classification abilities. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： Aircraft Classification Mobile-Net Object detection Weighted Box Fusion YOLOv8

来源：评论

学校读者我要写书评

暂无评论

Benchmarking a ROS 2-Based Indirect SLAM on Edge Devices 4

Benchmarking a ROS 2-Based Indirect SLAM on Edge Devices

引用

4th International Conference on Robotics, Automation, and Artificial Intelligence, RAAI 2024

作者： Behret, Valentino Kushtanova, Regina Palme, Frank Munich University of Applied Sciences Laboratory for 3D Measuring Systems and Computer Vision Department of Mechanical Automotive and Aeronautical Engineering Munich Germany

ISBN: (纸本)9798331520038

This study provides insights into SLAM performance on embedded systems and introduces an unsupervised parameter tuning approach for enhanced localisation accuracy. Our paper benchmarks a ROS 2-based indirect Simultaneous Localisation and Mapping (SLAM) system across six NVIDIA Jetson devices: Orin Nano 4 GB, Orin Nano 8 GB, Orin NX 8 GB, Orin NX 16 GB, AGX Orin 32 GB Auvidea, and AGX Orin 32 GB Devkit, using sequences from the KITTI dataset. The edge devices differ significantly in GPU computing power, number of CPU cores, CPU clock frequency as well as memory. SLAM evaluations are conducted within Docker containers to ensure consistency, with feature detection parameters optimised using an unsupervised tuning approach for each device. In addition to localisation accuracy, hardware utilisation is analysed, revealing that less than a half of CPU capabilities and approximately 5- 10 % of GPU power are utilised. The results indicate that in the default configuration devices with lower computing power demonstrate higher fluctuation in SLAM localisation accuracy. However, optimising feature parameters improves accuracy stability, especially for less powerful edge devices, indicating that even lower-powered but more energy-saving devices can achieve similar performance when an optimised balance between feature quantity and runtime constraints is achieved. © 2024 IEEE.

关键词： Graphics processing unit

来源：评论

学校读者我要写书评

暂无评论

Data driven Approaches for Demand Forecasting in Supply Chain for Business Decisions 5

Data driven Approaches for Demand Forecasting in Supply Chai...

引用

5th International Conference on Advancements in Computational sciences, ICACS 2024

作者： Javed, Salman Akhtar, Rizwan Pak-Austria Fachhochschule Institute of Applied Sciences and Technology Dept. It and Computer Science Haripur Pakistan

ISBN: (纸本)9798350394764

Demand forecasting is viewed as a complex challenge for industries as it relies heavily on various factors. The Supply Chain Management (SCM) integrates processes vital for corporate environments across industries. This paper presents a comprehensive data-driven framework for sales demand forecasting in SCM aiming to enhance accuracy of forecasts. Using Rossmann Stores data case study the sales are predicted up to 6 weeks ahead with a comparative analysis conducted for long-term predictions. Multi-dimensional data complexity is addressed by identifying relevant features and selecting appropriate algorithms. The proposed framework utilizes four data-driven machine learning algorithms: Extreme Learning Machine (ELM), Decision Tree (DT), Random Forests (RF), and Extreme Gradient Boosting (XGBoost) aiming to construct a high-precision sales demand forecasting model. The experimental validation using Rossmann Stores data demonstrates the effectiveness of the proposed framework, highlighting its significance in improving the accuracy of forecasts in SCM and enhancing decision-making processes. © 2024 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Sentiment Analysis of Low-Resource Language Literature Using Data Processing and Deep Learning

引用

computers, Materials & Continua 2024年第4期79卷 713-733页

作者： Aizaz Ali Maqbool Khan Khalil Khan Rehan Ullah Khan Abdulrahman Aloraini Department of IT and Computer Science Pak-Austria Fachhochschule:Institute of Applied Sciences and TechnologyHaripur22620Pakistan Software Competence Center Hagenberg Softwarepark 32aHagenberg4232Austria Department of Computer Science School of Engineering and Digital SciencesNazarbayev UniversityAstana010000Kazakhstan Department of Information Technology College of ComputerQassim UniversityP.O.Box 1162BuraydahSaudi Arabia

Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse *** numerous scholars conduct sentiment analysisin widely spoken languages such as English, Chinese, Arabic, Roman Arabic, and more, we come to grapplingwith resource-poor languages like Urdu literature which becomes a challenge. Urdu is a uniquely crafted language,characterized by a script that amalgamates elements from diverse languages, including Arabic, Parsi, Pashtu,Turkish, Punjabi, Saraiki, and more. As Urdu literature, characterized by distinct character sets and linguisticfeatures, presents an additional hurdle due to the lack of accessible datasets, rendering sentiment analysis aformidable undertaking. The limited availability of resources has fueled increased interest among researchers,prompting a deeper exploration into Urdu sentiment analysis. This research is dedicated to Urdu languagesentiment analysis, employing sophisticated deep learning models on an extensive dataset categorized into fivelabels: Positive, Negative, Neutral, Mixed, and Ambiguous. The primary objective is to discern sentiments andemotions within the Urdu language, despite the absence of well-curated datasets. To tackle this challenge, theinitial step involves the creation of a comprehensive Urdu dataset by aggregating data from various sources such asnewspapers, articles, and socialmedia comments. Subsequent to this data collection, a thorough process of cleaningand preprocessing is implemented to ensure the quality of the data. The study leverages two well-known deeplearningmodels, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for bothtraining and evaluating sentiment analysis performance. Additionally, the study explores hyperparameter tuning tooptimize the models’ efficacy. Evaluation metrics such as precision, recall, and the F1-score are employed to assessthe effectiv

关键词： Urdu sentiment analysis convolutional neural networks recurrent neural network deep learning natural language processing neural networks

来源：评论

学校读者我要写书评

暂无评论

Advances and Adaptation in Artificial General Intelligence Based on Novel Q∗ Framework 27

Advances and Adaptation in Artificial General Intelligence B...

引用

27th International Symposium on Wireless Personal Multimedia Communications, WPMC 2024

作者： Upreti, Meenakshi Bhatnagar, Abhinav Birla Institute of Applied Sciences Dept. of Master of Computer Applications Bhimtal India Birla Institute of Applied Sciences Dept. of Electronics and Communication Engineering Bhimtal India

ISBN: (纸本)9798350392319

A priority in the researches on artificial intelligence is the creation of Artificial General Intelligence. Even though the regular artificial intelligence was making some progress in certain areas, there were challenges and untried domains. This study introduces a novel Q∗ framework which is intended for improving AGI. Understanding, obtaining and using machine-generated knowledge across multiple domains are some of the aspects of AGI. It integrates concepts form cognitive psychology and reinforcement learning to produces a cohesive approach that includes learning as well as introspection and flexibility. By leveraging the advantages of Q-learning and refining existing methods, achieving AGI through Q∗ is feasible. Q* prioritizes metalearning and hierarchical representations over traditional AI systems that perform well within narrow contexts yet fail when asked to generalize more broadly. This makes it possible to be adaptable and learn well in unfamiliar settings. The paper gives a detailed explanation of the theoretical underpinnings and possible applications of AGI, emphasizing Q∗′ 's commitmentto advancing its pursuit. We discuss the conceptual framework proposed by Q∗ and speculate on its implications for future AI research. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Psychological Outcomes and Effectiveness of a Collaborative Video-Based Learning Tool for Synchronous Discussions 4th

Psychological Outcomes and Effectiveness of a Collaborati...

引用

4th International Conference on Higher Education Learning Methodologies and Technologies Online, HELMeTO 2022

作者： Straßmann, Carolin Helgert, André Lingnau, Andreas Computer Science Institute University of Applied Sciences Ruhr West Bottrop Germany

ISBN: (纸本)9783031297991

In the context of digitization and the COVID-19 pandemic, online teaching comes more and more into focus of higher education. Various online learning methodologies such as using videos as a teaching method are promising, but can also create problems in the area of social relations or learning habits. The concept of collaborative learning, especially in an online environment, could counteract these problems. This paper presents a collaborative online learning tool that allows students to get together in learning groups to watch educational videos together. Various functions, such as a chat, help students to communicate with each other. A psychological evaluation was conducted to investigate the effects on students. The evaluation demonstrated positive effects of the tool, since it enhances important psychological processes (like flow and cognitive load) within the learning process. Moreover, its usability was rated as good and participants showed a high usage intention for the tool. Nevertheless, further investigations in long-term learning courses are needed to finally confirm the tool’s effectiveness. © 2023, The Author(s).

关键词： Students

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：