检索结果-内蒙古大学图书馆

25th IEEE International Conference on Autonomous Robot systems and Competitions, ICARSC 2025

作者： Rema, Catarina Sousa, Armando Sobreira, Heber Costa, Pedro Silva, Manuel F. University of Porto (FEUP) Faculty of Engineering Porto 4200-465 Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science CRIIS - Centre for Robotics in Industry and Intelligent Systems Porto 4200-465 Portugal ISEP Polytechnic of Porto rua Dr. António Bernardino de Almeida Porto 4249-015 Portugal

ISBN: (纸本)9798331538606

The rise of Industry 4.0 has revolutionized manufacturing by integrating real-time data analysis, artificial intelligence (AI), automation, and interconnected systems, enabling adaptive and resilient smart factories. Autonomous Mobile Robots (AMRs), with their advanced mobility and navigation capabilities, are a pillar of this transformation. However, their deployment in job shop environments adds complexity to the already challenging Job Shop Scheduling Problem (JSSP), expanding it to include task allocation, robot scheduling, and travel time optimization, creating a multi-faceted, non-deterministic polynomial-time hardness (NP-hard) problem. Traditional approaches such as heuristics, meta-heuristics, and mixed integer linear programming (MILP) are commonly used. Recent AI advancements, particularly large language models (LLM), have shown potential in addressing these scheduling challenges due to significant improvements in reasoning and decision-making from textual data. This paper examines the application of LLM to tackle scheduling complexities in smart job shops with mobile robots. Guided by tailored prompts inserted manually, LLM are employed to generate scheduling solutions, being these compared to an heuristic-based method. The results indicate that LLM currently have limitations in solving complex combinatorial problems, such as task scheduling with mobile robots. Due to issues with consistency and repeatability, they are not yet reliable enough for practical implementation in industrial environments. However, they offer a promising foundation for augmenting traditional approaches in the future. © 2025 IEEE.

关键词： Chatbots Large Language Model Mobile Robots Task Scheduling

来源：评论

学校读者我要写书评

暂无评论

Extracting Motion Patterns of Greeting Gestures Using GNG with Spiking Neuron Model

Extracting Motion Patterns of Greeting Gestures Using GNG wi...

引用

International Symposium on Soft Computing and Intelligent systems (SCIS)

作者： Takenori Obo Angga Wahyu Wibowo Eri Sato-Shimokawara Hiroki Shibata Yihsin Ho Ichiro Kobayashi Department of Mechanical Systems Engineering Tokyo Metropolitan University Tokyo Japan Department of Computer Science Tokyo Metropolitan University Tokyo Japan Department of Electronics and Computer Systems Takushoku University Tokyo Japan Faculty of Engineering Takushoku University Tokyo Japan

ISBN: (数字)9798350373332

ISBN: (纸本)9798350373349

This study focuses on behavior patterns, which are characteristic actions common to groups or communities, to promote intercultural understanding. Understanding greeting gestures is crucial for comprehending social relationships, but these vary across cultures and regions. Recent advancements in sensing technology and artificial intelligence, such as RGB-D cameras and markerless motion capture systems, have made it easier to capture motion data in diverse formats. Therefore, it is important to extract relevant motion patterns and apply appropriate structuring for effective long-term archiving. We propose a method for extracting motion patterns using a Growing Neural Gas (GNG) algorithm with a Spiking Neuron Model. Additionally, this paper presents an experimental example of extracting a gesture pattern in Indonesian style.

关键词： Neurons Cameras Motion capture Sensors Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Triple Band Antenna Using Superstate with Double Substrate for Wireless Applications 26

Triple Band Antenna Using Superstate with Double Substrate f...

引用

26th International Conference on computer and Information Technology, ICCIT 2023

作者： Uddin, Md. Kutub Hossen, Shawon Alam, Touhidul Islam, Mohammad Tariqul Alam, Mohammed Shamsul Hakim, Mohammad Lutful Institut Perubahan Iklim Selangor Bangi Malaysia International Islamic University Chittagong Department of Electronic and Telecommunication Engineering Chittagong4318 Bangladesh Universiti Kebangsaan Malaysia Faculty of Engineering and Built Environment Department of Electrical Electronic and Systems Engineering Selangor Bangi Malaysia International Islamic University Chittagong Department of Computer Science and Engineering Chittagong4318 Bangladesh

ISBN: (纸本)9798350359015

A multiband antenna is a good choice to keep the device as compact as possible. This study introduces a tripleband antenna that is well-suited for 5G New Radio applications, satellite communications, and WiMAX. The antenna design has a two-layer substrate, including a ring-slotted rectangular superstate. To meet the design requirements, a rectangular superstate was used to provide the antenna with its triple-band capabilities. The antenna's triband capabilities come from its rectangular superstate, constructed using a ring slot at every antenna's four patch corners. In addition, it is advised and used to employ two FR-4 substrates that are 1.5 millimeters each to improve the antenna's efficacy substantially. The three frequencies shown by the results of the antenna modeling cover the frequency range used by 5G NR service operations: 4.780 GHz, 5.50 GHz, and 10.75 GHz. In each operational range, the measured reflection coefficient has a value below -10 dB at the frequency center, while the peak gains surpass 7 dBi. Nevertheless, the antennas provided in this context exhibit a broad spectrum of applications within the realm of wireless communication. © 2023 IEEE.

关键词： 5G Double substrate Multiband superstate WiMAX

来源：评论

学校读者我要写书评

暂无评论

Advancing Precision Aquaculture Through Big Data Analytics and Machine Learning in Canadian Fish Farming

Advancing Precision Aquaculture Through Big Data Analytics a...

引用

OCEANS 2024 - Halifax, OCEANS 2024

作者： Bravo, Francisco Amorim, Joana Amirkandeh, Melika Besharati Bodorik, Peter Cerqueira, Vitor Gomes, Nuno R.C. Korus, Jennie Oliveira, Mariana Parent, Marianne Pimentel, João Reilly, Derek Sclodnick, Tyler Grant, Jon Filgueira, Ramón Whidden, Christopher Universidad Adolfo Ibañez Facultad de Ingenieria y Ciencias Santiago Chile Dalhousie University Faculty of Computer Science Halifax Canada University of Porto Faculty of Engineering Portugal Barcelona Spain Innovasea Marine Systems Bedford Canada Charlottetown Canada Dalhousie University Department of Oceanography Halifax Canada Marine Affairs Program Dalhousie University Halifax Canada

ISBN: (纸本)9798331540081

The aquaculture industry faces significant challenges related to sustainability, productivity, and fish welfare. Key issues include managing environmental conditions, disease, pests, and data integration from various sensors and monitoring systems. The BigFish project aims to address these challenges through advanced analytics and machine learning, focusing on three case studies in Atlantic salmon farms: predicting oxygen levels, reducing sea lice infestations, and improving data interaction and visualization. Predictive models for oxygen levels and sea lice infestation, as well as natural language interfaces for data visualization, demonstrate the potential for improved decision-making and management practices in aquaculture. Early results indicate the effectiveness of these approaches, highlighting the importance of data-driven solutions in enhancing industry sustainability and productivity. © 2024 IEEE.

关键词： Aquaculture

来源：评论

学校读者我要写书评

暂无评论

Supporting the Episodic Application of Clinical Guidelines over Significant Time Periods

Supporting the Episodic Application of Clinical Guidelines o...

引用

34th Medical Informatics Europe Conference, MIE 2024

作者： Ben Shahar, Bruria Shahar, Yuval Jaffe, Shai Cohen, Odeya Shalom, Erez Selivanova, Maya Rimon, Ephraim Goldstein, Ayelet Department of Software and Information Systems Engineering Ben-Gurion University Israel Department of Nursing Faculty of Health Sciences Ben-Gurion University Israel Nursing Informatics lab Faculty of Health Sciences Ben-Gurion University Israel Herzfeld Geriatric Rehabilitation Medical Center Clalit Health Services Israel Department of Computer Science Hadassah Academic College Jerusalem Israel

ISBN: (纸本)9781643685335

Medical errors contribute significantly to morbidity and mortality, emphasizing the critical role of Clinical Guidelines (GLs) in patient care. Automating GL application can enhance GL adherence, improve patient outcomes, and reduce costs. However, several barriers exist to GL implementation and real-time automated support. Challenges include creating a formalized, machine-comprehensible GL representation, and an episodic decision-support system for sporadic treatment advice. This system must accommodate the non-continuous nature of care delivery, including partial actions or partially met treatment goals. We describe the design and implementation of an episodic GL-based clinical decision support system and its retrospective technical evaluation using patient records from a geriatric center. Initial evaluation scores of the e-Picard system were promising, with a mean 94% correctness and 90% completeness based on 50 random pressure ulcer patients. Errors were mainly due to knowledge specification, algorithmic issues, and missing data. Post-corrections, scores improved to 100% correctness and a mean 97% completeness, with missing data still affecting completeness. The results validate the system's capability to assess guideline adherence and provide quality recommendations. Despite initial limitations, we have demonstrated the feasibility of providing, through the e-Picard episodic algorithm, realistic medical decision-making support for noncontinuous, intermittent consultations. © 2024 The Authors.

关键词： Random errors

来源：评论

学校读者我要写书评

暂无评论

Real-Time Deepfake Detection for AI-Generated Arabic Speech

Real-Time Deepfake Detection for AI-Generated Arabic Speech

引用

Novel Intelligent and Leading Emerging sciences Conference (NILES)

作者： Rewaa Awaad Abdelrahman Hedya Mariam Fadel Ahmed B. Zaky Department of Computer Science and Information Technology Egypt-Japan University of Science and Technology Alexandria Egypt Department of Computer Science and Information Systems Minia University Minya Egypt Faculty of Engineering at Shoubra Benha University Benha Egypt

ISBN: (数字)9798350378511

ISBN: (纸本)9798350378528

This study investigates the effectiveness of Retrieval-based Voice Conversion (RVC) in detecting AI-generated Arabic speech across diverse linguistic contexts. The primary research questions address whether the RVC model can accurately differentiate between real and synthetic speech samples in various languages and its generalization capability across different linguistic contexts. Experimental evaluations show that the model achieves accuracies of 92% using Ensemble Learning (XGBoost and LightGBM), 93% with Meta Learning, and 90% with Neural Networks. Assessments encompass scenarios with real Arabic and English speech not included in training datasets, as well as different speakers across languages. The study contributes insights into the robustness and practical application of RVC for speech authentication.

关键词： Training Metalearning Deepfakes Neural networks Speech recognition Linguistics Robustness Real-time systems Speech synthesis Ensemble learning

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Machine Learning Models in Online Payment Fraud Prediction 2

Comparative Analysis of Machine Learning Models in Online Pa...

引用

2nd International Conference of Intelligent Methods, systems and Applications, IMSA 2024

作者： Shdefat, Ahmed Younes Mohamed, Mennatallah Khaled, Shahd Hany, Farrah Fathi, Hanaa Abdelminaam, Diaa Salama College of Engineering and Technology American University of the Middle East Egaila54200 Kuwait Misr International University Faculty of Computer Science Cairo Egypt Applied Science Private University Applied Science Research Center Amman Jordan Jadara University Jadara Research Center Irbid21110 Jordan Benha University Faculty of Computers and Artificial Intelligence Information Systems department Benha Egypt MEU Research Unit Middle East University Amman11831 Jordan

ISBN: (纸本)9798350362633

With the substantial increase in Cybercrime, the pressing need for effective solutions in the light of the rising amount of corporate financial losses, is a concern f or many researchers. The widespread adoption of ecommerce and diverse online payment methods has contributed to the surge in a major form of cybercrime - online payment fraud. This further highlights the critical need to control and reduce the widespread danger of fraudulent behaviour on the internet. However, predicting online payment fraud is difficult as fraudsters are constantly changing their tactics, transactions happen quickly and in large volumes, transactions involve different regions and countries, stolen data is often used and other factors. Our goal is to improve the accuracy and usability of online payment fraud prediction through the use of machine learning. A well-established and widely recognized dataset specifically designed for studying online payment fraud was used. The six proposed algorithms trained and tested were (SVM), Decision Tree, Naïve Bayes, Random Forest, (KNN) and Logistic Regression. After rigorous testing, Decision Tree presented the highest accuracy in performance of 98.58%. However, as ten-fold cross validation was implemented on the dataset, Decision Tree suffered a loss while Random Forest had an increase in accuracy making it the best model with accuracy of 98.47%. As shown in this paper, machine learning has proven to be a reliable and ever-evolving approach for the prediction of Online Payment Fraud and results can be further improved in collaboration with financial and cybercrime specialists. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

A Compact Rhombus Shaped Antenna with Extended Stubs for Ultra-Wideband Applications

引用

computers, Materials & Continua 2022年第11期73卷 2637-2650页

作者： Syed Misbah un Noor Muhammad Amir Khan Shahid Khan NZ Jhanjhi Mamoona Humayun Hesham A.Alhumyan Department of Electrical Engineering IIC University of TechnologyPhnom PenhCambodia Department of Computer Science COMSATS University IslamabadAbbottabad Campus22060Pakistan Department of Electrical and Computer Engineering COMSATS University IslamabadAbbottabad Campus22060Pakistan School of Computer Science SCSTaylor’s UniversitySubang Jaya47500SelangorMalaysia 5Center for Smart Society 0 CSS5 Faculty of Innovation and TechnologyTaylor’s UniversitySubang Jaya47500Malaysia Department of Information Systems College of Computer and Information SciencesJouf UniversityAl-JoufKSA

Ultra-wideband(UWB)is highly preferred for short distance *** a result of this significance,this project targets the design of a compact UWB *** paper describes a printed UWB rhombusshaped antenna with a partial ground *** achieve wideband response,two stubs and a notch are incorporated at both sides of the rhombus design and ground plane *** excite the antenna,a simple microstrip feed line is *** suggested antenna is built on a 1.6 mm thick FR4 *** proposed design is very compact with overall electrical size of 0.18λ×0.25λ(14×18 mm2).The rhombus shaped antenna covers frequency ranging from 3.5 to 11 GHz with 7.5 GHz impedance *** proposed design simulated and measured bandwidths are 83.33%and 80%,*** pattern in terms of E-field and H-field are discussed at 4,5.5 and 10 GHz *** proposed design has 65%radiation efficiency and 1.5 dBi peak *** proposed design is simulated in CST(computer Simulation Technology)simulator and the simulated design is fabricated for the measured *** simulated and measured findings are in close *** obtained results confirm the application of the proposed design for the ultra-wide band applications.

关键词： Ultra-wideband impedance bandwidth radiation pattern CST electrical size

来源：评论

学校读者我要写书评

暂无评论

Using Formal Knowledge to Support Episodic Evidence-Based Nursing Care

Using Formal Knowledge to Support Episodic Evidence-Based Nu...

引用

34th Medical Informatics Europe Conference, MIE 2024

作者： Jaffe, Shai Ben Shahar, Bruria Shahar, Yuval Goldstein, Ayelet Shalom, Erez Selivanova, Maya Rimon, Ephraim Cohen, Odeya Department of Nursing Faculty of Health Sciences Ben-Gurion University of the Negev Israel Nursing Informatics lab Faculty of Health Sciences Ben-Gurion University of the Negev Israel Department of Software and Information Systems Engineering Ben-Gurion University of the Negev Israel Computer Science Department Hadassah Academic College Israel Herzfeld Geriatric Rehabilitation Medical Center Israel

ISBN: (纸本)9781643685335

Applying evidence-based medicine prevents medical errors highlighting the need for applying Clinical Guidelines (CGs) to improve patient care by nurses. However, nurses often face challenges in utilizing CGs due to patient-specific needs. Developing a Clinical Decision Support System (CDSS) can provide real-time context-sensitive CG-based recommendations. Therefore, there is a need to acquire and represent CGs in a machine-applicable manner. Also, there is a need to be able to provide recommendations episodically, only when requested, and not continuously, and to assess previous partial performance of evidence-based actions on a continuous scale. This study evaluated the feasibility of acquiring and representing major nursing CGs, in a machine-applicable manner for episodic use. Using data from an Israeli geriatric center, the results suggest that an episodic CDSS effectively supports the application of formalized nursing knowledge. © 2024 The Authors.

关键词： Nursing

来源：评论

学校读者我要写书评

暂无评论

MSConv: Multiplicative and Subtractive Convolution for Face Recognition

arXiv

引用

arXiv 2025年

作者： Zhou, Si Si, Yain-Whar Yuan, Xiaochen Li, Xiaofan Liu, Xiaoxiang Zhang, Xinyuan Lin, Cong Gong, Xueyuan School of Intelligent Systems Science and Engineering Jinan University Guangdong China Department of Computer and Information Science University of Macau China Faculty of Applied Sciences Macau Polytechnic University China

In Neural Networks, there are various methods of feature fusion. Different strategies can significantly affect the effectiveness of feature representation, consequently influencing the model’s ability to extract representative and discriminative features. In the field of face recognition, traditional feature fusion methods include feature concatenation and feature addition. Recently, various attention mechanism-based fusion strategies have emerged. However, we found that these methods primarily focus on the important features in the image, referred to as salient features in this paper, while neglecting another equally important set of features for image recognition tasks, which we term differential features. This may cause the model to overlook critical local differences when dealing with complex facial samples. Therefore, in this paper, we propose an efficient convolution module called MSConv (Multiplicative and Subtractive Convolution), designed to balance the model’s learning of salient and differential features. Specifically, we employ multi-scale mixed convolution to capture both local and broader contextual information from face images, and then utilize Multiplication Operation (MO) and Subtraction Operation (SO) to extract salient and differential features, respectively. Experimental results demonstrate that by integrating both salient and differential features, MSConv outperforms models that only focus on salient features. Copyright © 2025, The Authors. All rights reserved.

关键词： Convolution

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：