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Financial Distress Prediction of Small and Medium- Sized Enterprises Based on Artificial Intelligence technology 1

Financial Distress Prediction of Small and Medium- Sized Ent...

引用

1st IEEE international conference on applied Intelligence and Sustainable computing, ICAISC 2023

作者： Tang, Yun Xie, Mingzhu Anhui Institute of International Business Hefei231131 China Anhui Xinhua University Hefei230088 China

ISBN: (纸本)9798350323795

In order to further improve the financial management quality of small and medium-sized enterprises, provide scientific and efficient financial information support for enterprise operation decisions and minimize the probability of enterprises falling into financial difficulties and crises caused by factors such as increased economic uncertainty, a financial distress and crisis management method based on machine learning algorithm is proposed with artificial intelligence technology supported. Empirical research was conducted on smes financial distress, with the help of random forest and other four machine learning models to manage financial distress and crisis. The experimental results show that the prediction accuracy of LR model is improved to 0.9061, SVC model to 0.9049, NB model to 0.8720. The result finding that the financial distress and crisis management method proposed in this article based on machine learning algorithms is effective, the accuracy of financial management and forecast can be effectively improved by controlling the variables of macro factors. © 2023 IEEE.

关键词： Machine learning

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computing services oriented evolutionary architecture and key technologies of electric power communication network 24

Computing services oriented evolutionary architecture and ke...

引用

24th IEEE international conference on Communication technology, ICCT 2024

作者： Zhang, Xiangyi Zhao, Xing Gao, Xiaofang Zhao, Hanyu Tang, Jia Guo, Xiaoxi Chen, Yanyu Zhao, Junfeng State Grid Information & Communication Beijing China Beijing China

ISBN: (纸本)9798350363760

With the deepening of the digital transformation of power systems, new service scenarios such as computing power access and interconnection are continuously developing. The electric power communication network urgently needs to evolve to comprehensively carry the existing services and new computing services. This paper analyzes the typical service scenarios and performance characteristics of new power systems against the development of computing services, summarizes the evolution demands faced by the electric power communication network. In response to the demand for comprehensive carrying of multiple services, the paper proposes a computing application oriented overall evolutionary architecture for the power communication network, and proposes key technologies such as all-optical interconnection based on OTN/OSU, multi-dimensional perception of computing and network, deterministic bearing, and intelligent collaborative operation and maintenance of computing and network. This paper can provide solid strategic suggestions for the future design and technological evolution of the electric power communication network oriented to computing services. © 2024 IEEE.

关键词： computing power

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Educators' Attitudes Towards Using Virtual Laboratories in Programming Courses in Higher Education in Saudi Arabia 21

Educators' Attitudes Towards Using Virtual Laboratories in P...

引用

21st international conference on information technology Based Higher Education and Training, ITHET 2024

作者： Alasmari, Ohud Abdullah College of Computing and Informatics Saudi Electronic University Saudi Arabia

ISBN: (纸本)9798331516635

This study explored the attitudes of educators in Saudi universities towards using virtual labs in programming courses. A descriptive analytical approach was used to analyse questionnaires to obtain data. 50 educators participated from five Saudi universities: the Saudi Electronic University, King Saudi University, Prince Sultan University, Princess Nourah Bint Abdul Rahman University, and King Khalid University. An online questionnaire form was distributed to them via two official academic WhatsApp groups. The results show that the attitudes of the educators in Saudi universities towards using virtual labs in programming courses are positive. According to the educators, using virtual labs in programming courses improves students critical thinking, problem-solving, and creative thinking skills. It improves students' searching, observation, and exploration skills. This paper recommends adding virtual lab-related activities to the curricula of programming courses in Saudi universities. © 2024 IEEE.

关键词： Students

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The Evolution of Zero Trust Architecture (ZTA) from Concept to Implementation 29

The Evolution of Zero Trust Architecture (ZTA) from Concept ...

引用

29th international conference on information technology, IT 2025

作者： Nasiruzzaman, Md Ali, Maaruf Salam, Iftekhar Miraz, Mahdi H. Xiamen University Malaysia School of Computing and Data Science Malaysia Universiteti Metropolitan Tirana Faculty of Computer Science and IT Albania The Doctoral College United Kingdom Xiamen University Malaysia Mahdi H. Miraz Is with the School of Computing and Data Science Malaysia Wrexham University School of Computing Faculty of Arts Science and Technology United Kingdom University of South Wales Faculty of Computing Engineering and Science United Kingdom

ISBN: (纸本)9798331517649

Zero Trust Architecture (ZTA) is one of the paradigm changes in cybersecurity, from the traditional perimeter-based model to perimeterless. This article studies the core concepts of ZTA, its beginning, a few use cases and future trends. Emphasising the always-verify and least privilege access, some key tenets of ZTA have grown to be integration technologies like Identity Management, Multi-Factor Authentication (MFA) and real-time analytics. ZTA is expected to strengthen cloud environments, education, work environments (including from home) while controlling other risks like lateral movement and insider threats. Despite ZTA's benefits, it comes with challenges in the form of complexity, performance overhead and vulnerabilities in the control plane. These require phased implementation and continuous refinement to keep up with evolving organisational needs and threat landscapes. Emerging technologies, such as Artificial Intelligence (AI) and Machine Learning (ML) will further automate policy enforcement and threat detection in keeping up with dynamic cyber threats. © 2025 IEEE.

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Bayesian Optimization of SVM for Efficient Detection of Cloud computing Failures 24

Bayesian Optimization of SVM for Efficient Detection of Clou...

引用

8th international conference on Electronic information technology and Computer Engineering, EITCE 2024

作者： Yuan, Yarui Li, Zhanhui Chengyi College Jimei University Fujian Xiamen China Tencent CSIG Zhejiang Hangzhou China

ISBN: (纸本)9798400710094

As cloud computing has become a fundamental technology underpinning a wide array of online services, ensuring its stability and reliability has emerged as a critical concern. Fault detection plays a pivotal role in maintaining service continuity and performance. However, the dynamic nature and inherent complexity of cloud computing environments pose significant challenges to effective fault detection. Despite the contributions of existing fault detection methods, they are often hampered by limitations in efficiency and accuracy. This paper proposes an online fault detection model based on Bayesian Optimization (BO) that adjusts the parameters of the Support Vector Machine (SVM) model to improve the efficiency and accuracy of fault detection. Pearson correlation and Principal Component Analysis (PCA) methods are employed to select appropriate attributes from cloud system operational data, thereby optimizing the model and improving detection performance. The experimental results prove that the BO-SVM has achieved an accuracy rate of 93% on the training set. The method we proposed demonstrates higher Accuracy, Precision, Recall, and F-score compared to several representative existing fault detection methods. This paper not only demonstrates the practicality of Bayesian Optimization (BO) in adjusting SVM model hyperparameters but also provides an effective solution for cloud computing fault detection. © 2024 Copyright held by the owner/author(s).

关键词： Support vector machines

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Minimum Volume Constraint with Perturbation for Non-negative Matrix Factorization

Minimum Volume Constraint with Perturbation for Non-negative...

引用

2023 international conference on applied Mathematics and Digital Simulation, AMDS 2023

作者： Sun, Li Yang, Song Yu, Ruilin Zhang, Xinyuan Department of Applied Mathematics School of Information Science and Technology Shandong Agricultural University Tai'an271018 China

Nonnegative matrix factorization (NMF) has been applied in hyperspectral unmixing. The nonconvexity of the NMF's cost function leads to solutions that are only locally optimal. Adding regularized terms to the NMF helps improve the solutions. In this study, we proposed a regularized NMF model, the regularized tern is the minimum volume constraint with perturbation. The NMF model is solved with multiplicative updated rules. Numerical results verified that adding a disturbance term to the minimum volume constraint effectively improves the spectral curve's local accuracy while maintaining the original model's advantages. © Published under licence by IOP Publishing Ltd.

关键词： Non-negative matrix factorization

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Enhancing AI Strategy in Checkers through Minimax and Alpha-Beta Pruning Techniques 1

Enhancing AI Strategy in Checkers through Minimax and Alpha-...

引用

1st international conference on Sustainable Energy Technologies and Computational Intelligence, SETCOM 2025

作者： Raut, Roshani Chaudhari, Mayur Raipalli, Shreya Banginwar, Sankalp Pimpri Chinchwad College of Engineering Department of Information Technology Pune India

ISBN: (纸本)9798331520540

This paper focuses on artificial intelligence in the game of Checkers and thus looks to further advance strategic decision-making within AI game agents. This is a problem arising in developing computationally efficient AI to scan complex board states so that optimum moves may be selected. Alpha-Beta Pruning applied with the Minimax algorithm reduces the amount of computing that needs to be done when assessing any move, thus enabling its speed and strategic playing capabilities to be increased. Results will come out of experiments regarding the proficiency of AI in competitive environments with the benefits of more efficient play, strategic placement, and adaptability. In summing this up, this way leads toward the improvement in advanced algorithms to enhance the strategic capabilities of AI as in games, thus toward generating responsive high-performance game agents. © 2025 IEEE.

关键词： Heuristic algorithms

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Kernel Fashion Context Recommender System (KFCR): A Kernel Mapping Fashion Recommender System Algorithm Using Contextual information 21

Kernel Fashion Context Recommender System (KFCR): A Kernel M...

引用

21st international Bhurban conference on applied Sciences and technology, IBCAST 2024

作者： Abbas, Waseem Rasheed, Uzair Khalid, Sadia Ghazanfar, Mustansar Hassan, Ali College of EME NUST Dept of Computer and Software Engineering Islamabad Pakistan University of East London Department of Engineering and Computing London United Kingdom

ISBN: (纸本)9798331516680

In Fashion, Recommender System represents a growing trend. They enable to offer the customer online fully personalized shopping experience. Many known names on the Fashion market such as Asos (***) or Zalando (***), have already bet on this technology to retain customers, boosting profits. Multiple filtering approaches exist, developed to cope with all the inherent challenges driven by the lack of information and the ephemeral nature of fashion items. However, even if the methods adopted are very varied, the main motive remains the same: reducing the margin of error at all costs to produce the nearest reality prediction. Accuracy, scalability, flexibility, and performance have become the keywords when creating a fully skilled Recommender System. To achieve these objectives, it appears that including in the model user's context information, such as time, location, mood, occasion, weather, or people's influence can be the answer. Not including contextual information is eluding a fundamental element in the decision-making process for the purchase of a particular piece of clothing. In this paper, we decided to apply to the Fashion domain issues the scalable context-aware algorithm to target the customer's tastes better, producing predictions as close to his preferences as possible. This new algorithm named KFCR uses the kernel mapping framework developed by (KMR) to complement context information. We evaluated and compared this new system to the Basic KMR, as well as to other widely used context-aware approaches like preand post-filtering techniques. Once evaluated, the KFCR was more accurate than both non-context-aware and context-aware approaches. © 2024 IEEE.

关键词： Sales

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An Effective Analysis of Proficient Two Level Security Contraptions for Loading Data in Cloud 1

An Effective Analysis of Proficient Two Level Security Contr...

引用

1st IEEE international conference on Innovations in High Speed Communication and Signal Processing, IHCSP 2023

作者： Arulkumaran, G. Jayagopalan, Santhosh Thanga Mariappan, L. Balamurugan, P. School of Computing and Information Technology REVA University Bengaluru India British Applied College Department of Computing Umm Al Quwain United Arab Emirates School of Information Technology and Engineering Vellore Institute of Technology Vellore Department of Smart Computing Vellore Dist Tamil Nadu India School of Computing SRM Institute of Science and Technology Department of Networking and Communications Chengalpattu Dist Tamil Nadu Kattankulathur India

ISBN: (纸本)9798350345957

One of the cornerstones of the future generation of computing is cloud computing, a form of internet-based computing. It allows for the instantaneous allocation of Internet-accessible resources whenever they are needed. Services such as software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS) are made available to people and businesses through cloud computing. By giving customers a low-cost, scalable, and financially-independent place to store their data, cloud storage services have seen rapid revenue growth in recent years. An interoperable cloud computing system is built on open architectures and interfaces that support both private and public cloud services. Many businesses today are making the switch to the cloud because of the numerous advantages it offers in terms of data storage, retrieval, management, and availability. While cloud computing is receiving a lot of attention, it is imperative that security problems be addressed first. This study proposes a crypto-stegno mechanism in the cloud as a solution to cloud security problems. This study proposes a practical method for ensuring data privacy and security in cloud storage. In order to obtain their own public and private key, users must first register their information in the cloud and come up with a unique username and password. Cryptography, a means of concealing information and sending information in an unreadable format, is employed in the next level of security. Secure data transmission and storage on the web, electronic commerce, digital media privacy, and ATM transfer are all dependent on cryptography to some degree. Repudiation, integrity, authenticity, and confidentiality are all possible using today's cryptographic methods. Signcryption is a lightweight cryptographic system that combines encryption and signatures in a logical way to achieve higher security with less computing time. © 2023 IEEE.

关键词： Cryptography

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Exploring Opinionated Sentiments through Web Scraping and Attribute-based Analysis 3

Exploring Opinionated Sentiments through Web Scraping and At...

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3rd international conference on applied Artificial Intelligence and computing, ICAAIC 2024

作者： Patil, Manjiri Patil, Palak Deshpande, Vedashree Karankale, Isha More, Shraddha St. John College of Engineering and Management Department of Information Technology Palghar India

ISBN: (纸本)9798350375190

The majority of customers consult online reviews before choosing which e-commerce services or products to buy. The new aspect of the suggested strategy is the use of opinion mining on customer reviews to assist businesses and organizations in continuously improving their marketing strategies and acquiring a thorough analysis of consumer impressions of their goods and brands. This study employed deep learning convolutional neural networks coupled with convolutional neural networks and long short-term memory (CNN-LSTM) to analyze the sentiment of reviews inside the ecommerce business. The algorithm's performance on previous iterations of the website was assessed using a web archive to predict how well the algorithm might function in the future. When the words around the pertinent data are categorized under the presumption that the website's future HTML would seem similar to the current HTML, robust scraping is possible. The algorithm generates a variety of outcomes based on a wide range of factors that can be discovered both in the website's internal code and in prior versions of the websites. The confusion matrix indicates how well the classification algorithm is executed. In simple terms, we obtained an accuracy of 80.12%. The model performed good job prediction for both classes with high precision and recall scores. © 2024 IEEE.

关键词： Long short-term memory

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