检索结果-内蒙古大学图书馆

11th International Conference on Mechatronics and Robotics engineering, ICMRE 2025

作者： Deif, Mohanad A. Hafez, Mohamed A. Attar, Hani Rezeka, S.F. Awad, T. Attia, E.M. Badawi, M.B. Research Institute of Sciences and Engineering University of Sharjah United Arab Emirates INTI-IU Universi Faculty of Engineering Feqs Nilai Malaysia Zarqua University Department of Energy Engineering Zarqa Jordan College of Engineering University of Business and Technology Jeddah21448 Saudi Arabia Alexandria University Faculty of Engineering Mechanical Engineering Department Alexandria Egypt Alexandria University Faculty of Engineering Mechanical Engineering Department El-Chatby Alexandria21544 Egypt Faculty of Computer Science and Engineering Department of Computer Science South Sinai Governorate El Tor Egypt

ISBN: (纸本)9798331509293

With the expanding capabilities of fighter aircraft in gauging their targets with great accuracy, comes the necessity that fighter pilots possess higher talents in making the correct decision. Because human error is frequently a barrier to making precise and timely decisions, a control mechanism is required to regulate the trajectory of aircraft during combat maneuvers. In this paper, a combat-maneuver fuzzy program is developed and applied to the inverse kinematics of the F-16 aircraft. The program produces a new path for the plane to achieve the maneuver such that the minimum distance between the resulting path and the object aircraft path is larger than a specified distance (critical distance). Also, spatial defensive maneuvers against spatial offensive maneuvers of bandits were realized, accordingly, this research emphasizes the importance of process innovation in the design of adaptive air combat control systems, enabling more effective response strategies. © 2025 IEEE.

关键词： Adaptive control systems

来源：评论

学校读者我要写书评

暂无评论

Dual-Channel MEMS Actuated Tunable Optical Filter Based on Polarization Insensitive Compound Ring Resonator for DWDM Networks 11th

Dual-Channel MEMS Actuated Tunable Optical Filter Based on P...

引用

11th EAI International Conference on Advancement of science and Technology, ICAST 2023

作者： Ayalew, Hailu Dessalegn Talabattula, Srinivas Annamalai, Pushparaghavan Electrical and Computer Engineering Faculty Bahir Dar University-Institute of Technology Bahir Dar Ethiopia Department of Electrical Communication Engineering Indian Institute of Science Bangalore India

ISBN: (纸本)9783031641503

One of the key components of wavelength division multiplexing (WDM) networks is tunable optical filters (TOFs). This paper focused on the theoretical analysis and design of a new dual-channel micro-electromechanical system (MEMS) actuated tunable optical filter based on polarization insensitive compound ring resonators (PICRRs) for dense wavelength division multiplexing (DWDM) optical networking applications. It is basically structured on an optimally designed capacitive type microcantilever beam, which is fixed at both ends, with built-in PICRRs, which are placed at both fixed ends of the beam to gain linearly varying longitudinal strain and stress on the resonators. Also, the dimensions of the rings are properly chosen to achieve a full width at half maximum (FWHM) of 0.4078 nm with a flat pass band at 1 dB of 0.3626 nm and a good shape factor for both channels. It also shows a free spectral range of about 20.05 nm for the first channel and 20.046 nm for the second channel, with a high extinction ratio that allows filtering of adjacent channels of 50 GHz DWDM systems. Thus, when the electrostatic attraction force (EAF) is applied, the beam will bend, which induces strain and stress in the rings, which brings a change in effective refractive index of the rings and also affects the perimeter and coupling coefficients of the rings that leads to a change in the output spectrum shift, providing the tunability as high as 4.779 nm/μN, and it is capable of tuning up to 355 GHz with negligible variations of FWHM and channel spacing within the tunability range of the two channels. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Dense wavelength division multiplexing

来源：评论

学校读者我要写书评

暂无评论

Smartphone Continuous Authentication via Deep Behavioral Features and Isolation Forest 24

Smartphone Continuous Authentication via Deep Behavioral Fea...

引用

3rd International Conference on Signal Processing, computer Networks and Communications, SPCNC 2024

作者： Ma, Hangyuan Li, Zhongrui Mou, Shiyu School of Computer Science and Artificial Intelligence Southwest Minzu University Sichuan Chengdu China Engineering Faculty Biomedical Engineering Department University of Malaya Petaling Jaya Malaysia

ISBN: (纸本)9798400710834

Smartphone authentication typically relies on user input of passwords or biometric features such as facial recognition, fingerprint scanning, or iris recognition. However, these methods only authenticate the user at specific points in time, meaning that once the password is compromised or the device is unlocked, unauthorized individuals can access all information on the device or perform unauthorized actions. To resolve this issue, continuous authentication has emerged, continuously verifying the user’s identity by covertly monitoring the ongoing interactions between the user and the device. This paper proposes a continuous authentication method that utilizes smartphone sensor data to extract users’ deep behavioral features through Siamese Convolutional Neural Networks (Siamese CNN). These features are then input into the Isolation Forest (iForest) algorithm for classification. Experimental results demonstrate that the proposed method can authenticate the user within one second, achieving an average accuracy of 93.79% and an average Equal Error Rate (EER) of 8.37%, significantly outperforming other comparative methods used in this study. © 2024 Copyright held by the owner/author(s).

关键词： Smartphones

来源：评论

学校读者我要写书评

暂无评论

Air Pollutant (CO) Forecasting: A Hybrid Approach Using Gooseneck Barnacle Optimization and Artificial Neural Networks 4

Air Pollutant (CO) Forecasting: A Hybrid Approach Using Goos...

引用

4th IEEE International Conference on Artificial Intelligence in Cybersecurity, ICAIC 2025

作者： Ahmed, Marzia Mohamad, Ahmad Johari Hassan, Md Maruf Bhuiyan, Touhid Department of Software Engineering Dhaka Bangladesh Faculty of Electrical & Electronics Engineering Technology Malaysia Southeast University Department of Computer Science and Engineering Dhaka Bangladesh School of IT VA United States

ISBN: (纸本)9798331518882

Air quality forecasting is critical for environmental monitoring and public health, and in this study, we propose a hybrid approach utilizing Gooseneck Barnacle Optimization (GBO) and Artificial Neural Networks (ANN) to enhance predictive accuracy. The air quality dataset, comprising pollutant concentrations (CO, NOx, benzene) and meteorological factors (temperature, humidity), is sourced from the UCI Machine Learning Repository. GBO is employed to fine-tune the ANN's hyperparameters (especially the weight and bias), as well as the number of layers, neurons, and activation functions, to improve regression-based forecasting. The GBOANN model achieves a Mean Squared Error (MSE) of 0.562 and a Root Mean Squared Percentage Error (RMSPE) of 5.63%, outperforming other metaheuristic methods like BMO, SSA, DA, MVO, and EMA. This study demonstrates the GBO-ANN model's potential for accurate real-time air quality forecasting, offering a robust, sustainable solution. © 2025 IEEE.

关键词： Air Quality GBO Metaheuristic Neural Network Time series forecasting

来源：评论

学校读者我要写书评

暂无评论

An Innovative Next Activity Prediction Approach Using Process Entropy and DAW-Transformer

arXiv

引用

arXiv 2025年

作者： Zare, Hadi Abbasi, Mostafa Ahang, Maryam Najjaran, Homayoun Department of Electrical and Computer Engineering Faculty of Engineering and Computer Science University of Victoria Victoria Canada Department of Mechanical Engineering Faculty of Engineering and Computer Science University of Victoria Victoria Canada

Purpose - In Business Process Management (BPM), accurate prediction of the next activities is vital for operational efficiency and decision-making. Current Artificial Intelligence (AI)/Machine Learning (ML) models struggle with the complexity and evolving nature of business process event logs, balancing accuracy and interpretability. This paper proposes an entropy-driven model selection approach and DAW-Transformer, which stands for Dynamic Attribute-Aware Transformer, to integrate all attributes with a dynamic window for better accuracy. Design/methodology/approach - This paper introduces a novel next-activity prediction approach that uses process entropy to assess the complexity of event logs and dynamically select the most suitable ML model. A new transformer-based architecture with multi-head attention and dynamic windowing mechanism, DAW-Transformer, is proposed to capture long-range dependencies and utilize all relevant event log attributes. Experiments were conducted on six public datasets, and the performance was evaluated with process entropy. Finding - The results demonstrate the effectiveness of the approach across these publicly available datasets. DAW-Transformer achieved superior performance, especially on high-entropy datasets such as Sepsis exceeding Limited window Multi-Transformers by 4.69% and a benchmark CNN-LSTM-SAtt model by 3.07%. For low-entropy datasets like Road Traffic Fine, simpler, more interpretable algorithms like Random Forest performed nearly as well as the more complex DAW-Transformer and offered better handling of imbalanced data and improved explainability. Originality/ value - This work’s novelty lies in the proposed DAW-Transformer, with a dynamic window and considering all relevant attributes. Also, entropy-driven selection methods offer a robust, accurate, and interpretable solution for next-activity prediction. © 2025, CC BY-NC-SA.

关键词： Administrative data processing

来源：评论

学校读者我要写书评

暂无评论

Document Summarizer: A Machine Learning approach to PDF summarization

引用

Procedia computer science 2025年 252卷 1025-1036页

作者： Rama Krishna Peddarapu Sudagoni Anogna M N S Sri Harshini J Sireesha K Guna Rathna Department of Computer Science and Engineering“ Faculty of Computer Sciences and Engineering VNR Vignana Jyothi Institute of Engineering and Technology Hyderabad Telangana India Department of Computer Science and Engineering VNR Vignana Jyothi Institute of Engineering and Technology Hyderabad Telangana India

To address the need for summarizing and extracting information efficiently, this paper highlights the growing challenge posed by the increasing number of PDF files. Reading lengthy documents is a tedious and time-consuming task. To save time and quickly comprehend the key points of a PDF, a PDF summarizer tool has been developed to tackle these issues. In today’s professional environments, gathering and managing data from documents is critical. This article introduces an innovative solution called DocSum, which automates the process of summarizing extracted data. Powered by *** Core, the DocSum system allows users to upload PDF documents for processing and receive concise summaries in return. The system features a user-friendly interface that encourages interaction and engagement, utilizing AI and machine learning techniques to streamline document handling. Users can request specific summaries, enabling efficient document management workflows. By empowering users to seamlessly interact with vast amounts of information, DocSum enhances productivity and explores new ways to optimize document management. This solution is ideal for professionals seeking to stay informed and manage data effectively, while also keeping track of advancements in document handling technologies across multiple industries. It is not only helpful for professionals but also helpful for students who need quick revision or examinations, teachers to gain brief knowledge on the concepts.

关键词： K Means Clustering Abstractive Extractive Sentence Transformer Embeddings

来源：评论

学校读者我要写书评

暂无评论

Different architectures of thin film bilayers based on TiO2 and CuO for green hydrogen generation

引用

International Journal of Hydrogen Energy 2025年 136卷 1073-1085页

作者： Banaś-Gac, Joanna Radecka, Marta Llobet, Eduard Partyka-Jankowska, Ewa Zakrzewska, Katarzyna Faculty of Computer Science Electronics and Telecommunications AGH University of Krakow Krakow Poland Faculty of Materials Science and Ceramics AGH University of Krakow Krakow Poland Department of Electronic Electrical and Automatic Engineering Rovira i Virgili University Tarragona Spain SOLARIS National Synchrotron Radiation Centre Jagiellonian University Krakow Poland

Green hydrogen becomes one of the most important of all other forms due to ecological issues, described in directives requiring the transformation to energy sources with the lowest possible carbon footprint. The application of the PhotoElectrochemical Cell where hydrogen is produced with the direct use of solar energy is the best solution. Bilayer and multilayered systems based on CuO, especially in combination with TiO2 seem to be the most frequently studied of all heterostructured nanomaterials when considering green hydrogen generation. The interface created between rough surface of CuO and smooth TiO2 surface ensures the highest photocurrent when the top layer is of about 150 nm. For CuO(top)/TiO2 heterojunction characterized by rough/rough interface, photoeletrochemical performance also improves with increasing thickness of the top layer up to 100 nm. The cathodic character of the photocurrent is observed for both TiO2(top)/CuO and CuO(top)/TiO2 bilayers. © 2025 The Authors

关键词： Solar energy

来源：评论

学校读者我要写书评

暂无评论

IoT Based Monitoring System for Health During Menstruation 4

IoT Based Monitoring System for Health During Menstruation

引用

4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Khadse, Chinmaya Hajare, Shital Sheikh, Nishad Dahule, Roshni Kate, Priya Datta Meghe Institute of Higher Education and Research Faculty of Engineering and Technology Department of Computer Science and Engineering Sawangi Maharashtra Wardha442001 India Datta Meghe Institute of Higher Education and Research Faculty of Engineering and Technology Department of Artificial Intelligence and Machine Learning Sawangi Maharashtra Wardha442001 India Datta Meghe Institute of Higher Education and Research Faculty of Engineering and Technology Department of Computer Science and Engineering Sawani Maharashtra Wardha442001 India

ISBN: (纸本)9798331523923

The integration of IoT and ML brought forth new prospective solutions in menstrual health management, pertaining to continuous monitoring of physiological signals and personalization of insights for women. This article discusses the usage of IoT, smartphones, and cloud-based systems for tracking vital signs, temperature, pulse rate, and flow of menstruation that will enable pro-active management of the cycle. The use of ML algorithms, including supervised models-like Random Forest and Logistic Regression-and complex techniques like RNNs and LSTM networks-offers added advantages for predicting menstrual cycles and ovulation. These technologies offer personalized health recommendations, early diagnosis of menstrual disorders, and help in communicating with healthcare providers in a very short span of time. While offering huge potential to improve women's health, concerns around data privacy, ethical considerations, and equitable access to these digital health solutions are highlighted. The existing systems showed improvements yet they encountered problems because of insufficient data diversity and health system integration as well as insufficient personalization and imprecise cycle predictions. Data privacy issues and security threats that stem from ML models along with constant bias concerns prevent broad acceptance of ML systems in general use. This research study analyzes IoT and ML applications in menstrual health today and introduces their advantages as well as the barriers that require resolution before mass acceptance can occur. The proposal introduces an approach to create menstrual tracking software through a combination of rule-based systems with ML algorithms that generates precise forecasts alongside tailored information for women who have PCOS or PCOD. © 2025 IEEE.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Enhancing structural health monitoring with AI-ML algorithms: a focus on crack detection and prediction

引用

Asian Journal of Civil engineering 2025年第5期26卷 1907-1918页

作者： Bader, Ahmad Shtayat, Amir Al-Mistarehi, Bara’ Communication and Computer Department Faculty of Engineering Jadara University Irbid Jordan Department of City Planning and Design Jordan University of Science and Technology Irbid 22110 Jordan Department of Civil Engineering Jordan University of Science and Technology Irbid Jordan

SHM is a very important process in terms of the safety and durability of infrastructure. Traditional SHM often faces problems detecting minor structural defects and handling large datasets. Therefore, certain more advanced approaches are called for. The paper discussed the applications of AI and ML algorithms, such as CatBoost and the African Vultures Optimization Algorithm, for such challenges. The research is based on a unique dataset of 8,541 rows and diverse features, developing a predictive framework that enhances crack detection and forecast capabilities. The approach mainly deals with heterogeneous data using the CatBoost algorithm, given its capability for high-accuracy predictions, while AVOA optimizes feature selection, reduces the computational cost, and guarantees no loss in model performance. This methodology has resulted in a significant enhancement of the prediction accuracy, which states the importance of AI-ML integration in SHM. The key results demonstrate the effectiveness of the model in detecting structural anomalies and crack propagation to enable proactive maintenance strategies. This study’s contributions have gone toward advancing SHM with scalable and efficient AI-ML frameworks, enabling real-time monitoring for better infrastructure management. Such development might have a transforming potential to cut down on maintenance costs and enhance operational safety, thus further encouraging sustainable infrastructure systems. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： African vultures optimization algorithm CatBoost Crack Detection Feature selection Machine learning Structural health monitoring

来源：评论

学校读者我要写书评

暂无评论

The Analysis of Device-to-Device (D2D) Communication System Operating in 5G Underlaying Cellular Networks on Multiple Bands over Nakagami-m Fading Channels

引用

SN computer science 2025年第5期6卷 1-15页

作者： Shatnawi, Razan A. Khodeir, Mahmoud A. Al-Mistarihi, Mamoun F. Darabkh, Khalid A. Al-Zuraiqi, Eyad T. Qasaymeh, Mahmoud M. Electrical Engineering Department Faculty of Engineering Jordan University of Science and Technology P.O. Box 3030 Irbid 22110 Jordan Computer Engineering Department School of Engineering The University of Jordan Amman 11942 Jordan Department of Telecommunications Engineering Hijjawi Faculty for Engineering Technology Yarmouk University P.O. Box 566 Irbid 21163 Jordan Computer Engineering and Communication Department Tafila Technical University Tafila 66110 Jordan

In contrast to traditional cellular connection, device-to-device (D2D) communication is a direct connection amidst adjacent mobile users that does not pass through the base station (BS) and does not rely on network infrastructure to meet low power requirements and high data rate. Cellular networks and D2D connections were combined in underlay mode to address power usage concerns. In underlay D2D communication, licensed frequency bands are utilized by both D2D and cellular connections;due to resource sharing, these bands may overlap, which lowers service quality but boosts spectral efficiency. Most existing research exclusively discuss energy efficiency (EE) in the context of single cells. This article has taken into account the entire cellular network with D2D connections on various bands, and stochastic geometric theory has been used in order to obtain closed form expressions for the probability of successful transmission (STP), the average sum rate (ASR), and EE for D2D connection underlaid cellular networks over Nakagami-m fading channels. Results of simulations are used to validate analytical conclusions. Simulation results demonstrate that higher STP, higher ASR, and lower EE all result in enhanced system performance. In addition, as the shape parameter’s value m (Nakagami-m order) increases, the EE, ASR, and STP of D2D users improve, which enhances system performance. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： Device-to-device communication Energy efficiency Nakagami-m fading channel Stochastic geometry

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：