检索结果-内蒙古大学图书馆

Business Blockchain Suitability Determinants: Decision-Making through an Intuitionistic Fuzzy Method

computer Systems science & Engineering 2023年第11期47卷 1665-1690页

作者： Tomader Almeshal Jawad Berri Tarifa Almulhim Areej Alhogail Emam Ahmed Department of Information Systems College of Computer and Information SciencesKing Saud UniversityRiyadh11451Saudi Arabia Department of Quantitative Methods School of BusinessKing Faisal UniversityAl-Ahsa31982Saudi Arabia Faculty of Computer Science and Engineering King Salman International UniversitySouth SinaiEgypt

Blockchain is one of the innovative and disruptive technologies that has a wide range of applications in multiple industries beyond *** widespread adoption of blockchain technology in various industries has shown its potential to solve challenging business problems,as well as the possibility to create new business models which can increase a firm’s *** to the novelty of the technology,whereby many companies are still exploring potential use cases,and considering the complexity of blockchain technology,which may require huge changes to a company’s existing systems and processes,it is important for companies to carefully evaluate suitable use cases and determine if blockchain technology is the best solution for their specific *** research aims to provide an evaluation framework that determines the important dimensions of blockchain suitability assessment by identifying the key determinants of suitable use cases in a business *** this paper,a novel approach that utilizes both qualitative(Delphi method)and quantitative(fuzzy set theory)methods has been proposed to objectively account for the uncertainty associated with data collection and the vagueness of subjective *** work started by scanning available literature to identify major suitability dimensions and collected a range of criteria,indicators,and factors that had been previously identified for related *** opinions were then gathered using a questionnaire to rank the importance and relevance of these elements to suitability ***,the data were analyzed and we proceeded to integrate multi-criteria group decision-making(MCGDM)and intuitionistic fuzzy set(IFS)*** findings demonstrated a high level of agreement among experts,with the model being extremely sensitive to variances in expert ***,the results helped to refine and select the most relevant suitability determinants under three important dimensions:fu

关键词： Blockchain business blockchain use cases suitability assessment multi-criteria group decision-making fuzzy Delphi intuitionistic fuzzy set

来源：评论

学校读者我要写书评

暂无评论

A Consensus-Based Multi-Criteria Group Decision-Making Method Based on an Aggregated Operator Customised by Experts 9

A Consensus-Based Multi-Criteria Group Decision-Making Metho...

引用

9th International Conference on Control, Decision and Information Technologies, CoDIT 2023

作者： Trillo, José Ramón Cabrerizo, Francisco Javier Del Moral, María José Morente-Molinera, Juan Antonio Tapia, Juan Miguel Herrera-Viedma, Enrique University of Granada Department of Computer Science and Artificial Intelligence Granada18071 Spain University of Granada Granada18071 Spain University of Granada Department of Quantitative Methods for Business and Economics Granada18071 Spain

ISBN: (纸本)9798350311402

Group decision-making is a daily process where a group of experts has to choose from a set of alternatives. To help this group of experts, methods were developed that allowed them to recommend an alternative or a group of alternatives from the information generated by the experts, these methods were called Group Decision-Making methods. Nonetheless, some Group Decision-Making methods have some problems, such as evaluating alternatives in a general way. This problem leads to a loss of information because it is not possible to evaluate each alternative in detail and it may be the case that one alternative is better than another on one criterion but not on another. Another problem is that experts have priority for each criterion and for one expert one criterion may be more important than another and vice versa. To solve these two problems, in this novel method, we propose a consensual multi-criteria Group Decision-Making system, where experts can customise the order of the criteria. With the order of each expert, the method creates an aggregation operator for each criterion. Moreover, this method performs a consensus analysis for each criterion, so that there is a minimum consensus on each criterion. In this way, a solution is obtained that allows the set of alternatives to be evaluated in a detailed way and each criterion has the correct importance because the experts are the ones who create the order of importance. © 2023 IEEE.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Economic Analysis of the Situation Criminalization Production and Protection 15

Economic Analysis of the Situation Criminalization Productio...

引用

15th International Conference Management of Large-Scale System Development, MLSD 2022

作者： Troyanovskiy, V.M. Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences Department of Mathematical Methods of Regional Programming Moscow Russia

ISBN: (数字)9781665497015

ISBN: (纸本)9781665497015

The article analyzes criminal activity of an economic nature in case of penetration of crime into production and the system of protection against it. It is advisable to find out under what conditions it is unprofitable to steal, for which it is necessary to supplement legal studies with economic ones. The results of the analysis will help to find ways to rationally counteract crime. © 2022 IEEE.

关键词： Crime

来源：评论

学校读者我要写书评

暂无评论

Optimization on Cognitive Models 15

Optimization on Cognitive Models

引用

15th International Conference Management of Large-Scale System Development, MLSD 2022

作者： Solomatin, A.N. Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences Department of Mathematical Methods of Regional Programming Moscow Russia

The concept of acceptable systems with a limited level of systemic pathologies and dysfunctions is considered. The main provisions of cognitive modeling are given and the tasks of single- and multi-criteria optimizati... 详细信息

ISBN: (数字)9781665497015

ISBN: (纸本)9781665497015

关键词： Pathology

来源：评论

学校读者我要写书评

暂无评论

REES AAEE special issue on engineering education research capability development: introduction by guest editors

引用

Australasian Journal of Engineering Education 2023年第1期28卷 2-7页

作者： Dart, Sarah Seniuk Cicek, Jillian Sohoni, Sohum Learning and Teaching Unit & Faculty of Engineering Queensland University of Technology BrisbaneQLD Australia Centre for Engineering Professional Practice and Engineering Education University of Manitoba Winnipeg Canada Department of Electrical Engineering and Computer Science Milwaukee School of Engineering Milwaukee United States

Since the late 20th century, Engineering Education Research (EER) has been expanding globally as a field, although its identity varies across institutions and countries around the world. This diversity in how EER is experienced across contexts impacts how capability is developed, including identities, knowledge, practices, agendas, funding, and pathways. The theme of ‘Engineering Education Research Capability Development’ was explored in papers, presentations, and workshops throughout the jointly held 2021 Research in Engineering Education Symposium and Australasian Association for Engineering Education conference. This special issue presents a continuation of that theme. The papers collectively contribute to expanding global understanding of the field, with implications for future capacity building efforts in engineering education practice and research. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： Engineering education

来源：评论

学校读者我要写书评

暂无评论

Applied intelligence with deep learning assisted automated sarcasm recognition in twitter data

引用

Alexandria Engineering Journal 2025年 128卷 79-91页

作者： Alzaidi, Muhammad Swaileh A. Alsudais, Taghreed Ali Eltahir, Majdy M. Ebad, Shouki A. Alshuhail, Asma Alshahrani, Mohammed Alanazi, Sultan Department of English Language College of Language Sciences King Saud University P. O. Box 145111 Riyadh Saudi Arabia Department of Teaching and Learning College of Education and Human Development Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Department of Information Systems Applied College at Mahayil King Khalid University Saudi Arabia Center for Scientific Research and Entrepreneurship Northern Border University Arar73213 Saudi Arabia Department of Information Systems College of Computer Sciences & Information Technology King Faisal University Saudi Arabia Computer Department Applied College Najran University Najran66462 Saudi Arabia Department of Computer Science College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz University Al-Kharj16273 Saudi Arabia

Sarcasm is essential in human interaction, particularly on social networking, where individuals share their feelings through criticism, humour, and satire. Sarcasm detection is vital in understanding the context of communication and the sentiment on platforms such as Twitter. This presents sarcasm detection as a complex problem in natural language processing (NLP). The challenges and importance upsurge, particularly in languages such as Arabic and Urdu, where resources for NLP are inadequate. The classical rule-based techniques need to improve performance owing to sarcasm's context-based and subtle nature. On the other hand, the current developments in deep learning (DL) and NLP offer efficient solutions. Therefore, this study presents an Applied Intelligence with Deep Learning Assisted Automated Sarcasm Recognition Approach (AIDL-ASRA) on Twitter Data. The presented AIDL-ASRA technique concentrates on identifying sarcastic and non-sarcastic contexts in tweets. In the AIDL-ASRA technique, the initial pre-processing stage is executed with different subprocesses. Next, Global Vectors for Word Representation (GloVe)-based word embedding process occurs. The AIDL-ASRA technique utilizes the Discriminative Deep Belief Networks (DDBN) method for sarcasm recognition. The DBN model's effectiveness is improved using the cat swarm optimization (CSO) model. A set of experiments were involved in evaluating the performance of the AIDL-ASRA method under the Arabic sarcastic dataset comprising 10,000 tweets. The experimental validation of the AIDL-ASRA method attained a superior accuracy value of 91.25 % over existing techniques under distinct measures. © 2025 The Authors

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Enhancing Long-range Dependency with State Space Model and Kolmogorov-Arnold Networks for Aspect-based Sentiment Analysis 31

Enhancing Long-range Dependency with State Space Model and K...

引用

31st International Conference on Computational Linguistics, COLING 2025

作者： Lawan, Adamu Pu, Juhua Yunusa, Haruna Umar, Aliyu Lawan, Muhammad School of Computer Science and Technology Beihang University Beijing China National Research Institute for Teaching Materials in Information Science and Tech. China School of Automation Science and Electrical Engineering Beihang University Beijing China School of Computing University of Portsmouth Portsmouth United Kingdom Department of Information and Communication Technology Federal University Gusau Nigeria

ISBN: (纸本)9798891761964

Aspect-based Sentiment Analysis (ABSA) evaluates sentiments toward specific aspects of entities within the text. However, attention mechanisms and neural network models struggle with syntactic constraints. The quadratic complexity of attention mechanisms also limits their adoption for capturing long-range dependencies between aspect and opinion words in ABSA. This complexity can lead to the misinterpretation of irrelevant contextual words, restricting their effectiveness to short-range dependencies. To address the above problem, we present a novel approach to enhance long-range dependencies between aspect and opinion words in ABSA (MambaForGCN). This approach incorporates syntax-based Graph Convolutional Network (SynGCN) and MambaFormer (Mamba-Transformer) modules to encode input with dependency relations and semantic information. The Multihead Attention (MHA) and Selective State Space model (Mamba) blocks in the MambaFormer module serve as channels to enhance the model with short and long-range dependencies between aspect and opinion words. We also introduce the Kolmogorov-Arnold Networks (KANs) gated fusion, an adaptive feature representation system that integrates SynGCN and MambaFormer and captures non-linear, complex dependencies. Experimental results on three benchmark datasets demonstrate MambaForGCN's effectiveness, outperforming state-of-the-art (SOTA) baseline models. © 2025 Association for Computational Linguistics.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Machine Learning for Ischaemic Heart Disease Diagnostic Analysis 4

Machine Learning for Ischaemic Heart Disease Diagnostic Anal...

引用

4th IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability, ECBIOS 2022

作者： Xing, Ruiming Meng, James Loughborough University Department of Computer Science United Kingdom Lancashire Teaching Hospitals Nhs Foundation Trust United Kingdom

ISBN: (数字)9781728195797

ISBN: (纸本)9781728195797

Ischaemic Heart Disease (IHD) is a major cause of morbidity and mortality worldwide. Clinical diagnosis involves complex, costly and potentially invasive procedures. To reduce the cost and risk to patients, we present a functioning machine learning (ML) pipeline and developed ML predictive models for IHD diagnosis using a limited number of risk factors in a clinical dataset. We fine-tuned and compared a number of learning algorithms and feature selection methods. The effectiveness of proposed methods was evaluated with quantitative measures and clinician input. The best accuracy of 92.9% was achieved, demonstrating a promising tool for screening IHD patients. Practical issues and data bias when applying ML on medical data are discussed. © 2022 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Research on the Co-Creation Construction Model of Digital Education Resources in Internet+ Era 23

Research on the Co-Creation Construction Model of Digital Ed...

引用

7th International Conference on Education and Multimedia Technology, ICEMT 2023

作者： Chen, Ruxian Li, Xufeng Bian, Buxing Wang, Jie Cai, Ruiqi Zhang, Jing Department of Computer Science Software Engineering Institute of Guangzhou China Wushen Banner High School Nei Monggol China Leshan Normal University Teaching Departmen China Institute of Computing Science and Technology Guangzhou University China

ISBN: (纸本)9798400709142

With the development of Internet+, an open and innovative educational ecosystem is forming. The combination of Internet and education can greatly promote the integration and utilization of high-quality education resources. Firstly, we analyze the main problems in the construction of digital education resources. Secondly, we explore the co-creation construction model of high-quality mathematical resources among government, enterprises and schools, including the main elements of the model, the connection between the elements and the related mechanism support. Finally, it takes NetPad as an example to carry out practical research on the co-creation of digital education resource in the field of basic education, improving the construction and service level of high-quality digital education resources. © 2023 ACM.

关键词： E-learning

来源：评论

学校读者我要写书评

暂无评论

Quantum Particle Swarm Optimization with Deep Learning-Based Arabic Tweets Sentiment Analysis

引用

computers, Materials & Continua 2023年第5期75卷 2575-2591页

作者： Badriyya BAl-onazi Abdulkhaleq Q.A.Hassan Mohamed K.Nour Mesfer Al Duhayyim Abdullah Mohamed Amgad Atta Abdelmageed Ishfaq Yaseen Gouse Pasha Mohammed Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of English College of Science and Arts at MahayilKing Khalid UniversityAbha62217Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversityMakkah24231Saudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAl-Aflaj16828Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj16436Saudi Arabia

Sentiment Analysis(SA),a Machine Learning(ML)technique,is often applied in the *** SA technique is specifically applied to the data collected from social media *** research studies conducted earlier upon the SA of the tweets were mostly aimed at automating the feature extraction *** this background,the current study introduces a novel method called Quantum Particle Swarm Optimization with Deep Learning-Based Sentiment Analysis on Arabic Tweets(QPSODL-SAAT).The presented QPSODL-SAAT model determines and classifies the sentiments of the tweets written in ***,the data pre-processing is performed to convert the raw tweets into a useful ***,the word2vec model is applied to generate the feature *** Bidirectional Gated Recurrent Unit(BiGRU)classifier is utilized to identify and classify the ***,the QPSO algorithm is exploited for the optimal finetuning of the hyperparameters involved in the BiGRU *** proposed QPSODL-SAAT model was experimentally validated using the standard *** extensive comparative analysis was conducted,and the proposed model achieved a maximum accuracy of 98.35%.The outcomes confirmed the supremacy of the proposed QPSODL-SAAT model over the rest of the approaches,such as the Surface Features(SF),Generic Embeddings(GE),Arabic Sentiment Embeddings constructed using the Hybrid(ASEH)model and the Bidirectional Encoder Representations from Transformers(BERT)model.

关键词： Sentiment analysis Arabic tweets quantum particle swarm optimization deep learning word embedding

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：