检索结果-内蒙古大学图书馆

Algorithm for Solving Inverse Problems of Geoelectrical Prospecting for Vertical Electrical Sounding by the Indirect Near-Boundary Element Method 19

Algorithm for Solving Inverse Problems of Geoelectrical Pros...

引用

19th IEEE International Conference on computer science and Information Technologies, CSIT 2024

作者： Zhuravchak, Liubov Zabrodska, Nataliya Lviv Polytechnic National University Software Department Institute of Computer Science and Information Technologies Bandery street 12 Lviv Ukraine National Academy of Sciences Department of Geoelectromagnetic Methods Carpathian Branch of S.I. Subbotin Institute of Geophysics Naukova street 3-b Lviv Ukraine

ISBN: (纸本)9798331542627

using the indirect near-boundary element method, an algorithm for recognizing the physical and geometric parameters of the inclusion in a piecewise homogeneous half-plane, whose components are in ideal contact, based on the potential field data measured at its boundary, is constructed. The direct and inverse two-dimensional problems of the potential theory in relation to electrical prospecting, in particular, the method of vertical electrical soundings, have been solved. A computational experiment was conducted in which initial approximations for the electrical conductivity of the inclusion, its center of mass, orientation, and dimensions were determined by the nature of the change in apparent resistivity. The inverse problem is solved using excess boundary conditions by a number of iterations while minimizing the functional. © 2024 IEEE.

关键词： Inverse problems

来源：评论

学校读者我要写书评

暂无评论

Practical Study of Selected Multi-Criteria methods Comparison 26

Practical Study of Selected Multi-Criteria Methods Compariso...

引用

26th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2022

作者： Wieckowski, Jakub Szyjewski, Zdzislaw Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology Szczecin ul. Zolnierska 49 Szczecin71-210 Poland Institute of Management University of Szczecin ul. Cukrowa 8 Szczecin71-004 Poland

Multi-Criteria Decision Analysis (MCDA) methods enable a comprehensive analysis of decision options to identify the most preferred values. However, the abundance of these techniques, using different transformations in the calculations, can cause a divergence of results. However, the resulting rankings should be as consistent and reliable as possible. In this paper, we used the TOPSIS, COPRAS, SPOTIS, and COMET methods to examine the consistency of their results in the practical problem of laptop evaluation. The rankings were then compared with the reference ranking. The research showed that among the methods listed, the COPRAS method's results differed the most from the others. In turn, this technique ensured a ranking in line with the reference ranking. Based on the results, it can be established that the methods used are characterized by high consistency of results. © 2022 The Authors. Published by Elsevier B.V.

关键词： Preferred numbers

来源：评论

学校读者我要写书评

暂无评论

Rl-Gcn: Trafffc Flow Prediction Based on Graph Convolution and Reinforcement Learning for Smart Cities

SSRN

引用

SSRN 2023年

作者： Xing, Hang Chen, An Zhang, Xuan College of Engineering South China Agricultural University Guangdong Guangzhou510642 China Department of Experiment Teaching Guangdong University of Technology Guangzhou510006 China Department of computer science University of Pennsylvania 19104-6106 United States

The trafffc ffow problem has become essential in urban planning and management in today’s increasingly urbanized world. Traditional trafffc ffow prediction models cannot fully consider urban trafffc networks’ complex and dynamic characteristics. To this end, this paper proposes a trafffc ffow prediction method for smart cities (RL-GCN) based on graph convolution, LSTM network and reinforcement learning, aiming to solve the problem of urban trafffc ffow prediction . Firstly, we use the graph convolutional neural network to process the urban trafffc network data features, then use the LSTM network model to learn the temporal information, and then combine the reinforcement learning algorithm to develop the optimal trafffc control strategy based on which the future trafffc ffow is predicted. Our experiments on several datasets show that the model developed in this paper has outstanding performance for urban trafffc ffow prediction . Compared with the traditional trafffc ffow prediction methods, the method in this paper has signiffcantly improved prediction accuracy . Our research can provide valuable references and inspiration in urban planning and trafffc management. © 2023, The Authors. All rights reserved.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

The Implementation of Artificial Intelligence Tools In Retail Sector Among Consumers - A New Evolution Traditional to Morden

The Implementation of Artificial Intelligence Tools In Retai...

引用

Electronic Systems and Intelligent Computing (ICESIC), International Conference on

作者： Leena Jenefa Ashok Kumar S Bibiana Lim Chiu Yiong M. Jayakumar Lenin Lokesh B M. Sakthivel School of Management Hindustan Institute of Technology and Science Chennai India Learning and Teaching Unit Swinburne University of Technology Sarawak Campus Malaysia Department of Management Studies Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India Department of Computer Science and Engineering Vel Tech High Tech Dr. Rangarajan Dr.Sakunthala Engineering College Chennai India

ISBN: (数字)9798331522988

ISBN: (纸本)9798331522995

AI technologies may serve numerous functions in entire retail sector in value chain, and employ the employees for the job done by using to implement AI operations in the value chain. Because of the increasing degree of competition in the retail industry, merchants must now provide higher-quality services and prioritize their clients more than ever before. Retailers have increasingly adopted AI-based solutions to study new potential in the retail industry. The focus of the research is to know the people mind set to use the digital sectors. Performance expectation refers to consumers' belief that technology would improve productivity and effectiveness in reaching goals. The Indian retail sector has emerged as one of the most rapidly increasing industries. The findings show the influence are favorably connected to performance expectation, but not correlated with anthropomorphism. Retailers are always seeking to unleash the industry's true potential by using cutting-edge technologies such as artificial intelligence-based data analytics, CRM systems.

关键词： Industries Productivity Performance evaluation Data analysis Customer satisfaction Object recognition Artificial intelligence Anthropomorphism Consumer electronics

来源：评论

学校读者我要写书评

暂无评论

Cheating Detection in Browser-based Online Exams through Eye Gaze Tracking 6

Cheating Detection in Browser-based Online Exams through Eye...

引用

6th International Conference on Information Technology Research, ICITR 2021

作者： Dilini, Nimesha Senaratne, Asara Yasarathna, Tharindu Warnajith, Nalin Seneviratne, Leelanga Software Engineering Teaching Unit University of Kelaniya Kelaniya Sri Lanka College of Engineering and Computer Science Australian National University Canberra Australia Faculty of Information Technology University of Moratuwa Moratuwa Sri Lanka

ISBN: (纸本)9781665420006

Eye-tracking can detect and examine human visual attention, emotional conditions, latent cognitive processes such as efforts to recall a concept or the fear of running out of time, and so on. Hence, we can use eye-tracking to identify deviant behavior patterns in learning and problem-solving. At present, given the existence of a global pandemic, online exams are widely used by educational institutions to evaluate students' performance. However, identifying cheating is challenging due to the absence of a human (invigilator) monitoring students' behavior as done in exams held in a physical location. In an online environment, students' behavior, and attempts to cheat, can only be captured via a computer, thus requiring a mechanism for online proctoring with capabilities for cheating detection. In this research paper, we present a browser based cheating detection approach in online examinations through eye gaze tracking. We developed a browser plugin to track the eye gaze movements through the in-built web camera. Using the plugin, we generate an eye gaze dataset while a student faces an online examination. We then process and analyze this dataset to detect any misbehavior during an online examination. The underlying research work of this paper identifies different eye gaze patterns during online examinations and present a cheating detection mechanism. For anomaly detection in the eye gaze data, we use a One-Class Support Vector Machine (OCSVM). We then use these identified anomalies to predict cheating behaviors of the test takers. The given approach can be used for any web-based quiz examination such as academic institutions' exams, company recruitment exams, and overseas testing exams to detect any anomalous behaviors of the test takers during the examination period. The given eye tracking approach can also be applied to other research domains such as online gaming, and web usability studies to capture information related to user behaviors. © 2021 IEEE.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Autonomous Emergency Triage Support System

Autonomous Emergency Triage Support System

引用

International Conference on Computational science and Computational Intelligence (CSCI)

作者： Ol'Tunde Ashaolu William Lyons Ioannis Stefanakos Radu Calinescu Ibrahim Habli Victoria Hodge Chiara Picardi Katherine Plant Beverley Townsend York and Scarborough Teaching Hospitals NHS Foundation Trust / Hull-York Medical School York UK Department of Computer Science University of York York UK Faculty of Engineering and Physical Sciences University of Southampton Southampton UK

ISBN: (数字)9798350361513

ISBN: (纸本)9798350372304

Medical staff shortages and growing healthcare demands due to an ageing population mean that many patients face delays in receiving critical care in the emergency departments (EDs) of hospitals worldwide. As such, the use of autonomous, robotics and AI technologies to help streamline the triage of ED patients is of utmost importance. In this paper, we present our ongoing work to develop an autonomous emergency triage support system intended to alleviate the current pressures faced by hospital emergency departments. By employing a combination of robotic and AI techniques, our solution aims to speed up the initial stages of ED triage. Its preliminary evaluation using synthetic patient datasets generated with ED medic input suggests that our solution has the potential to improve the ED triage process, supporting the timely and accurate delivery of patient care in emeraency settings.

关键词： Hospitals Scientific computing Sociology Aging Delays Artificial intelligence Statistics

来源：评论

学校读者我要写书评

暂无评论

A case review of ductal carcinoma in situ in a bitch: histomorphological and immunohistochemical evaluations

引用

Comparative Clinical Pathology 2024年第5期33卷 677-681页

作者： Ubah, Simon Azubuike Abalaka, Samson Eneojo Okafor, Richard Oluchukwu Sunday Onah, Jonas Anayo Zaifada, Aishatu Ummi Zachariya, Esther Okere, Nkechi Chikwem Omoike, Philomina Monday Egedigwe, Ugochukwu John Tenuche, Oremeyi Zaynab Adah, Bridget Mary Jesicca Uba, Charles Amaechi Department of Theriogenology Faculty of Veterinary Medicine University of Abuja Abuja Nigeria Department of Veterinary Pathology Faculty of Veterinary Medicine University of Abuja Abuja Nigeria Department of Veterinary Surgery Faculty of Veterinary Medicine University of Abuja Abuja Nigeria University of Abuja Veterinary Teaching Hospital Abuja Nigeria Department of Computer Science Health Informatics Metropolitan College Boston University Boston MA United States Clinical Chemistry Unit Laboratory Services Department University of Abuja Teaching Hospital Abuja Nigeria Laboratory Services Department Haematology Unit University of Abuja Teaching Hospital Abuja Nigeria Department of Veterinary Microbiology Faculty of Veterinary Medicine University of Abuja Abuja Nigeria Department of Animal Health and Production Technology School of Agriculture and Related Disciplines Anambra State Polytechnic Anambra State Mgbakwu Awka North Nigeria

Mammary tumours are the second most diagnosed tumours after skin tumours in bitches;however, the aetiology is still unknown and this calls for continuous investigations. The present study aimed to surgically excise and evaluate a solitary mass on the right first axillary mammary gland of a 9-year-old Caucasian bitch presented for clinical attention. The surgical intervention was according to standard procedure under general anaesthetic protocols. Histopathological and immunohistochemical evaluation of the tumour followed standard procedures after fixing in 10% neutral buffered formalin. The immunohistochemical evaluation of the samples followed the Avidin-Biotin-Peroxidase Complex Method as described by [8]. The lobulated mass (1.6 kg) had greenish-brown fluid-filled cysts on cut surface and presented multiple multi-layered epithelial intratubular papillary growths supported by fibrovascular connective tissue stroma with ductal ectasis containing homogenous eosinophilic materials and inter-tubular fibrosis. The mass also stained positively to vimentin and α-Smooth muscle actin but negatively to oestrogen receptor, progesterone receptor, and E-cadherin antibodies. The definitive diagnosis is a ductal carcinoma in situ with mixed carcinoma features showing the tendency to metastasize. Prompt diagnosis and appropriate management of the present case shall prevent future occurrence and the continuous investigations may serve as models for the understanding and management of human breast tumours. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Benign mixed carcinoma Canine Histopathology Immunohistochemistry Mammary tumour Morphology

来源：评论

学校读者我要写书评

暂无评论

MODELING OF ENHANCED FRACTAL CHEETAH OPTIMIZER WITH DEEP LEARNING FOR INTEGRATED ARABIC DIALECT IDENTIFICATION

引用

Fractals 2025年第2期33卷

作者： Alahmari, Saad Al-Shathry, Najla I. Eltahir, Majdy M. Alruwais, Nuha Sayed, Ahmed Abdelbagi, Sitelbanat Department of Computer Science Applied College Northern Border University Arar91431 Saudi Arabia Department of Language Preparation Arabic Language Teaching Institute Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Department of Information Systems Applied College Mahayil King Khalid University Abha Saudi Arabia Department of Computer Science and Engineering College of Applied Studies and Community Services King Saud University Saudi Arabia P.O. Box 22459 Riyadh11495 Saudi Arabia Research Center Future University in Egypt New Cairo11835 Egypt Department of Computer and Self Development Preparatory Year Deanship Prince Sattam bin Abdulaziz University AlKharj Saudi Arabia

The Arabic language has different variants that can roughly be classified into three major types, namely Modern Standard Arabic (MSA), Dialectal Arabic (DA), and Classical Arabic (CA). There are slight variations between CA and MSA regarding pronunciation, syntax, and terminology. On the other hand, DA is quite different from MSA and CA in that it reflects the country of origin, or at least the geographic location of the speaker if the mobility factor is considered. Deep learning demonstrated its effectiveness in DA detection tasks, leveraging neural network models such as transformer models, Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs). Researchers have established models that automatically discriminate between Arabic dialects by processing contextual information, linguistic features, and phonetic patterns embedded in large datasets. Using Deep Learning (DL) in Arabic dialect detection contributes in various complex systems to the development of natural language processing. It assists in addressing the problems related to a wide variety of Arabic dialects, which facilitate applications including machine translation, speech recognition, and sentimental analysis tailored to regional linguistic variation. This study suggests an Enhanced Fractal Cheetah Optimization Algorithm with Deep Learning for Integrated Arabic Dialect Identification (ECOADL-IADI) technique. The ECOADL-IADI technique mainly intends to classify the variations of the Arabic language into multiple classes. At the preliminary level, the ECOADL-IADI technique performs preprocessing of Arabic text. Next, the BERT word embedding process is carried out. The ECOADL-IADI technique applies a Bidirectional Recurrent Neural Network (BiRNN) model for Arabic dialect identification. Lastly, the ECOA-based hyperparameter selection process improves the classifier outcomes of the BiRNN model. A wide range of experiments were conducted to examine the detection results of the ECODL-IADI t

关键词： Recurrent neural networks

来源：评论

学校读者我要写书评

暂无评论

Chaotic Elephant Herd Optimization with Machine Learning for Arabic Hate Speech Detection

引用

Intelligent Automation & Soft Computing 2024年第3期39卷 567-583页

作者： Badriyya B.Al-onazi Jaber S.Alzahrani Najm Alotaibi Hussain Alshahrani Mohamed Ahmed Elfaki Radwa Marzouk Heba Mohsen Abdelwahed Motwakel Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMecca24382Saudi Arabia Prince Saud AlFaisal Institute for Diplomatic Studies Riyadh12735Saudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqra11911Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in Egypt New CairoNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipAl-Kharj16278Saudi Arabia

In recent years,the usage of social networking sites has considerably increased in the Arab *** has empowered individuals to express their opinions,especially in ***,various organizations that operate in the Arab countries have embraced social media in their day-to-day business activities at different *** is attributed to business owners’understanding of social media’s importance for business ***,the Arabic morphology is too complicated to understand due to the availability of nearly 10,000 roots and more than 900 patterns that act as the basis for verbs and *** speech over online social networking sites turns out to be a worldwide issue that reduces the cohesion of civil *** this background,the current study develops a Chaotic Elephant Herd Optimization with Machine Learning for Hate Speech Detection(CEHOML-HSD)model in the context of the Arabic *** presented CEHOML-HSD model majorly concentrates on identifying and categorising the Arabic text into hate speech and *** attain this,the CEHOML-HSD model follows different sub-processes as discussed *** the initial stage,the CEHOML-HSD model undergoes data pre-processing with the help of the TF-IDF ***,the Support Vector Machine(SVM)model is utilized to detect and classify the hate speech texts made in the Arabic ***,the CEHO approach is employed for fine-tuning the parameters involved in *** CEHO approach is developed by combining the chaotic functions with the classical EHO *** design of the CEHO algorithm for parameter tuning shows the novelty of the work.A widespread experimental analysis was executed to validate the enhanced performance of the proposed CEHOML-HSD *** comparative study outcomes established the supremacy of the proposed CEHOML-HSD model over other approaches.

关键词： Arabic language machine learning elephant herd optimization TF-IDF vectorizer hate speech detection

来源：评论

学校读者我要写书评

暂无评论

Trends and Challenges of Sustainable Agriculture in the Iraqi Environment

Trends and Challenges of Sustainable Agriculture in the Iraq...

引用

2022 IEEE International Conference on Blockchain, Smart Healthcare and Emerging Technologies, SmartBlock4Health 2022

作者： Al-Asadi, Hanan Hussein Goga, Maria Ali, Haider Abdullah Popa, Ramona Cristina Oludele, Awodele University POLITEHNICA of Bucharest Faculty of Automatic Control and Computers Bucharest Romania University of Technology-Iraq Baghdad Iraq Technical University of Civil Engineering of Bucharest UTCB Department for Training of Teaching Personnel Bucharest Romania Madenat Alelem University College Baghdad Iraq Babcock University Computer Science Department Ogun State Nigeria

ISBN: (纸本)9781665460149

The use of Agriculture Intelligent Systems (AISs) in Iraq has become popular among farmers. The greenhouse is a solution for plant growth, which uses an effective microclimate to simulate seasons and to use alternative energy sources like solar, thermal, and photovoltaic systems for microclimate control. Greenhouses are considered a successful solution with developments and achievements in the technology of this field. However, problems like high costs, difficulties in installation and maintenance, or the need for some procedures should be considered. Because Iraq is close to the equator (3669 km), it receives sufficient solar power. It also has large areas available for the building of solar greenhouse systems. The farmers need an affordable and functional smart greenhouse to enable and encourage them to use the environment efficiently. We intend to develop low-cost, accurate, and easy-to-use greenhouse systems controlled by artificial intelligence algorithms. Farmers will be able to control the greenhouse by using simple commands. Machine learning algorithms provide real-time and effective analysis that could support farmers in decision-making and provide relevant data for researchers and policymakers. AISs algorithms can lead to a sustainable and productive agriculture system. The system can be used in Iraq with sufficient government support and subsidy. © 2022 IEEE.

关键词： Intelligent systems

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：