检索结果-内蒙古大学图书馆

11th International Conference on Analysis of Images, Social Networks and Texts , AIST 2023

作者： Gromov, Vasilii A. Zvorykina, Ekaterina I. Beschastnov, Yurii N. Sohrabi, Majid School of Data Analysis and Artificial Intelligence Faculty of Computer Science HSE University Moscow109028 Russia Laboratory for Models and Methods of Computational Pragmatics HSE University Moscow Russia

ISBN: (纸本)9783031670077

The paper explores mathematical methods that differentiate regular and chaotic time series, specifically for identifying pathological fistulas. It proposes a noise-resistant method for classifying responding rows of normally and pathologically functioning fistulas. This approach is grounded in the hypothesis that laminar blood flow signifies normal function, while turbulent flow indicates pathology. The study explores two distinct methods for distinguishing chaotic from regular time series. The first method involves mapping the time series onto the entropy-complexity plane and subsequently comparing it to established clusters. The second method, introduced by the authors, constructs a concepts-objects graph using formal concept analysis. Both of these methods exhibit high efficiency in determining the state of the fistula. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Entropy

来源：评论

学校读者我要写书评

暂无评论

A High-Capacity Image Steganography Based on LSB Inversion and Summing of Bit Pairs 6

A High-Capacity Image Steganography Based on LSB Inversion a...

引用

6th IEEE Novel Intelligent and Leading Emerging sciences Conference, NILES 2024

作者： Mamdouh, Loay Bekhet, Saddam South Valley University Faculty of Computers and Artificial Intelligence Department of Computer Science Hurghada Egypt South Valley University Faculty of Commerce Department of Quantitative Methods Qena Egypt

ISBN: (纸本)9798350378511

Nowadays, computer users face a challenge in maintaining the security of their information. There are many techniques for transferring information safely over networks. Image steganography, one of these techniques, is an effective way to conceal important information. The Least Significant Bit (LSB) technique is a famous method for data hiding. This technique exchanges the LSBs of the cover image pixel with the mystery message bits. However, it was always the challenging problem of increasing the number of bits utilized for embedding that led to a decreased quality of the stego image. Hence, this research targets optimizing the stego image quality by inverting the LSBs of image pixels to reduce the changes that occur in pixels. This paper proposes a new method based on summing the pairs and inverting the LSBs of the cover image pixels. The secret data are arranged in pairs, and then the sum of every two successive pairs is computed. After that, the secret bits are embedded by inverting the pixel bits depending on that sum. Finally, for more enhancement of the results, some of the inverted bits will be inverted again. Rigorous experiments using benchmark datasets confirm that the proposed scheme yields superior results compared to the substitution LSB scheme. Also, shows the effectiveness of the proposed approach in achieving a high payload with acceptable visual quality for stego image that cannot be noticed by human eyes when compared with state-of-the-art steganography techniques. © 2024 IEEE.

关键词： Image quality

来源：评论

学校读者我要写书评

暂无评论

Optical image recognition strategy for keyword extraction and page ranking for slide recommendation system

Optical image recognition strategy for keyword extraction an...

引用

2023 International Conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2023

作者： Obionwu, Chukwuka Victor Abbas, S. M Laique Padmanabhan, Visakh Tiwari, Taruna Broneske, David Saake, Gunter Otto-von-Guericke University Faculty of Computer Science Magdeburg Germany German Centre for Higher Education Research and Science Studies Research Infrastructure and Methods Lower Saxony Hannover Germany

ISBN: (纸本)9798350322972

One of the main advantages of the traditional instructor/student interaction is the possibility of receiving immediate instructional feedback within the defined lecture periods. However, the transition into full online, and hybrid pedagogy has gradually replaced instructional feedback with peer feedback. While essential for knowledge transfer among learners, peer feedback largely depends on prior knowledge from learning engagements that may not fully be related to the particular course in question. What we have observed in our learning management system is lots of unnecessarily repeated errors which could easily be averted with the right instruction. To this end, we employed optical image recognition to extract structured query language-based keywords from lecture slides and exercise sheets. Using these keywords, we automatically rank the degree to which a lecture slide suitable matches an exercise task, and thus provide an automatic recommendation to students encountering errors in respective tasks during exercise task engagements. Overall, we achieved a precision of 0.707 for German lecture slides and 0.72 for English lecture slides, which validates our strategy of assisting students with automatic lecture slide recommendations during their online exercise engagements. © 2023 IEEE.

关键词： Extraction

来源：评论

学校读者我要写书评

暂无评论

Deep Neural Network Architecture Search via Decomposition-Based Multi-Objective Stochastic Fractal Search

引用

Intelligent Automation & Soft Computing 2023年第11期38卷 185-202页

作者： Hongshang Xu Bei Dong Xiaochang Liu Xiaojun Wu School of Computer Science Shaanxi Normal UniversityXi’an710119China Key Laboratory of Modern Teaching Technology Ministry of EducationXi’an710062China

Deep neural networks often outperform classical machine learning algorithms in solving real-world ***,designing better networks usually requires domain expertise and consumes significant time and com-puting ***,when the task changes,the original network architecture becomes outdated and requires ***,Neural Architecture Search(NAS)has gained attention as an effective approach to automatically generate optimal network *** NAS methods mainly focus on achieving high performance while ignoring architectural complexity.A myriad of research has revealed that network performance and structural complexity are often positively ***,complex network structures will bring enormous computing *** cope with this,we formulate the neural architecture search task as a multi-objective optimization problem,where an optimal architecture is learned by minimizing the classification error rate and the number of network parameters *** then a decomposition-based multi-objective stochastic fractal search method is proposed to solve *** view of the discrete property of the NAS problem,we discretize the stochastic fractal search step size so that the network architecture can be optimized more ***,two distinct update methods are employed in step size update stage to enhance the global and local search abilities ***,an information exchange mechanism between architectures is raised to accelerate the convergence process and improve the efficiency of the *** studies show that the proposed algorithm has competitive performance comparable to many existing manual and automatic deep neural network generation approaches,which achieved a parameter-less and high-precision architecture with low-cost on each of the six benchmark datasets.

关键词： Deep neural network neural architecture search multi-objective optimization stochastic fractal search decomposition

来源：评论

学校读者我要写书评

暂无评论

A Strategy for Retrospective Evaluation of Students SQL Learning Engagements

A Strategy for Retrospective Evaluation of Students SQL Lear...

引用

2023 International Conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2023

作者： Obionwu, Chukwuka Victor Oji Kalu, Kalu Blockhaus, Paul Broneske, David Saake, Gunter Otto-von-Guericke University Faculty of Computer Science Magdeburg Germany German Centre for Higher Education Research and Science Studies Research Infrastructure and Methods Department Lower Saxony Hannover Germany

ISBN: (纸本)9798350322972

The adoption of e-learning pedagogy in educational institutions has become increasingly prevalent, and it has proffered solutions to notable deficiencies that existed in the traditional learning pedagogy. However, it has also opened up new sets of challenges. One such challenge is the management of the huge amounts of data generated by students in the course of their daily interaction with various e-learning subsystems. Furthermore, as these systems are mostly online assessment systems, In-depth evaluation of student's interaction is mostly coarse, and a strategy for retrospective evaluation of students' interaction data for improved knowledge acquisition is mostly lacking. In our own peculiar scenario, an understanding of the challenges experienced by students in their pursuit of Structured Query Language knowledge acquisition was necessary. A strategy we adopted to tackle the challenge of gaining retrospective insight into student's learning engagements is the use of error codes, and a real-time analytics. Thus, we are able to understand the extent to which our teaching strategy is effective against reducing stress resulting in exercise task engagement, and other learning challenges that may affect knowledge acquisition by individual students in the course of their learning interactions. We show that the error code strategy is an effective indicator for tracking, and intervening on student's Structured Query Language (SQL) based learning interactions. Our evaluation further showed that syntax errors are the most prevalent type of error encountered by students learning SQL. © 2023 IEEE.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

The Development and Testing of a Model for Converting American Sign Language (ASL) Sentences Using Natural Language Processing Techniques

The Development and Testing of a Model for Converting Americ...

引用

2024 IEEE International Conference on Cybernetics and Innovations, ICCI 2024

作者： Kaewprom, Alongkorn Suriyapattanapong, Aritat Sanmano, Smith Songmuang, Pokpong Malakul, Sivakorn Suksanareewittaya School Bangkok Thailand Streesmutprakan School Bangkok Thailand Chitrala School Bangkok Thailand Thammasat University Department Of Computer Science Pathum Thani Thailand The Institute For The Promotion Of Teaching Science And Technology Bangkok Thailand

ISBN: (纸本)9798350370096

This research addresses the global prevalence of people with hearing disabilities, recognizing the increasing numbers within this demographic. The communication challenges encountered by these individuals drive the development and evaluation of a language translation model. The primary goal is to design a model specifically tailored for translating sign language sentences into English, considering the unique word order in sign language. The study involves comparing eight models that utilize various techniques. Evaluation will be conducted through the bleu score, with 100 randomly selected sentences in each of the 10 rounds. Consistent inputs will be used across rounds to calculate the bleu score, offering a comprehensive assessment of model performance. © 2024 IEEE.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

An informed deep learning model of the Omicron wave and the impact of vaccination

引用

computers in Biology and Medicine 2025年 191卷 109968-109968页

作者： Shamsara, Elham König, Florian Pfeifer, Nico Methods in Medical Informatics Department of Computer Science University of Tübingen Tübingen72076 Germany

The Omicron (B.1.1.529) variant of SARS-CoV-2 emerged in November 2021 and has since evolved into multiple lineages. Understanding its transmission, vaccine efficacy, and potential for reinfection is crucial. This study examines the dynamics of Omicron in Germany, France, and Italy by employing Physics-Informed Neural Networks to estimate the temporal parameters influencing its spread. We validated the performance of our model using the Root Mean Squared Percent Error (RMSPE). Our analysis revealed significant correlations between specific viral mutations—S371F, T376A, D405N, and R408S—and increased transmission rates in all three countries. These mutations, prevalent in the Omicron BA.2 and BA.3 sublineages, are linked to immune evasion and heightened transmissibility. © 2025 The Author(s)

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Study on the Fundamentals of Electrical Engineering Based on Grey Correlation Analysis 18th

Study on the Fundamentals of Electrical Engineering Based on...

引用

18th International Conference on computer science and Education, ICCSE 2023

作者： Tang, Fei Xu, Jian Qi, Huamei Liao, Qingfen Qi, Junfeng School of Electrical Engineering and Automation Wuhan University Wuhan China School of Computer Science and Engineering Center for Teaching and learning development Central South University Changsha China

ISBN: (纸本)9789819707294

The fundamentals of electrical engineering is a compulsory course set up by the school of electrical and automation of Wuhan University for undergraduate junior students. As an important platform course of electrical engineering, it has high requirements for students to learn the pre sequence basic courses. Firstly, this paper uses grey correlation analysis to analyze the correlation between the courses of advanced mathematics, circuit theory and electrical engineering of undergraduate students in recent three years and this course. Then the correlation coefficient is obtained and normalized. Finally, it is used as the analysis of new students’ learning situation. In this way, we can effectively have a scientific and objective understanding of the basic knowledge of new students and the learning situation of preamble courses. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Heuristic Algorithm for Solving Travelling Salesman Problem: Adding the Endpoints of the Longest Edges 5

Heuristic Algorithm for Solving Travelling Salesman Problem:...

引用

5th International Conference on Problems of Cybernetics and Informatics, PCI 2023

作者： Nuriyeva, Fidan Dokuz Eylul University Department of Computer Science Izmir Turkey Institute of Control Systems Laboratory of Recognition Identification and Methods of Optimal Solutions Baku Azerbaijan

ISBN: (纸本)9798350319064

This study proposes, a new heuristic algorithm based on insertion heuristic to solve the symmetric Travelling Salesman Problem. In the proposed algorithm, firstly the two longest edges are selected and the starting tour passing through their endpoints is constructed, then the endpoints of the next longest edges are added to this tour and the solution passing through all the vertices is found. This problem is known to be NP-Hard. The proposed method was successfully tested on different-sized problems. The experimental results show that the proposed algorithm outperforms many existing methods. © 2023 IEEE.

关键词： Traveling salesman problem

来源：评论

学校读者我要写书评

暂无评论

Arabic Sign Language Gesture Classification Using Deer Hunting Optimization with Machine Learning Model

引用

computers, Materials & Continua 2023年第5期75卷 3413-3429页

作者： Badriyya B.Al-onazi Mohamed K.Nour Hussain Alshahran Mohamed Ahmed Elfaki Mrim M.Alnfiai Radwa Marzouk Mahmoud Othman Mahir M.Sharif Abdelwahed Motwakel Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi 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 EgyptNew Cairo11835Egypt Department of Computer Science Faculty of Computer Science and Information TechnologyOmdurman Islamic UniversityOmdurman14415Sudan Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Sign language includes the motion of the arms and hands to communicate with people with hearing *** models have been available in the literature for sign language detection and classification for enhanced *** the latest advancements in computer vision enable us to perform signs/gesture recognition using deep neural *** paper introduces an Arabic Sign Language Gesture Classification using Deer Hunting Optimization with Machine Learning(ASLGC-DHOML)*** presented ASLGC-DHOML technique mainly concentrates on recognising and classifying sign language *** presented ASLGC-DHOML model primarily pre-processes the input gesture images and generates feature vectors using the densely connected network(DenseNet169)*** gesture recognition and classification,a multilayer perceptron(MLP)classifier is exploited to recognize and classify the existence of sign language ***,the DHO algorithm is utilized for parameter optimization of the MLP *** experimental results of the ASLGC-DHOML model are tested and the outcomes are inspected under distinct *** comparison analysis highlighted that the ASLGC-DHOML method has resulted in enhanced gesture classification results than other techniques with maximum accuracy of 92.88%.

关键词： Machine learning sign language recognition multilayer perceptron deer hunting optimization densenet

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：