检索结果-内蒙古大学图书馆

2025 Joint National Conference on Cybersecurity, ITASEC and SERICS 2025

作者： Baldo, Massimiliano Ion, Fabio I. Miculan, Marino Paier, Matteo Riccio, Vincenzo University of Udine Dept. of Mathematics Computer Science and Physics Italy Ca’ Foscari University of Venice Dept. of Environmental Sciences Informatics and Statistics Italy IMT Alti Studi Lucca Italy

Service mesh technologies have emerged as a powerful tool for managing communications in microservices-oriented architectures. However, enforcing complex access control policies often requires stateful mechanisms, which are not directly supported by policy languages like Rego. To address this limitation, we propose the OPA Wrapper State Manager (OWSM). OWSM maintains a separate state store that can be accessed during policy evaluation. This enables the specification and enforcement of stateful access control policies using Rego’s declarative syntax. We evaluate the performance and overhead of OWSM through experiments, demonstrating its effectiveness in enhancing the capabilities of service mesh environments. © 2025 Copyright for this paper by its authors.

关键词： Access control Microservices Policy languages Service mesh

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Approaches for Early Diagnosis of Breast Cancer: A Comparative Study of Performance Evaluation

Machine Learning Approaches for Early Diagnosis of Breast Ca...

引用

2023 IEEE International Conference on Electro Information Technology, eIT 2023

作者： Al Mamlook, Rabia Shresth, Sujeet Gharaibeh, Tasnim Almuflih, Ali Saeed Al-Mawee, Wassnaa Bzizi, Hanin University of Al-Zawiya Dept. Industrial Engineering Libya Trine University Indian United States Wayne Stata University Dept. Industrial Engineering MI United States Kalamazoo College Dept. of Computer Science Kalamazoo United States King Khalid University Dept. Industrial Engineering Saudi Arabia Western Michigan University Dept. of Computer Science Department of Computer Science KalamazooMI United States Western Michigan University Department of Biomedical Science KalamazooMI United States

ISBN: (纸本)9781665493765

Breast cancer is a leading cause of death among women worldwide. Early detection and diagnosis are crucial to improving the chances of survival. This paper presents a study on the diagnosis of breast cancer using various machine-learning approaches. The study includes the performance evaluation of nine different techniques using confusion matrix accuracy for Sensitivity, Specificity, Precision, PME, PPV, NPV, and Model Accuracy. AdaBoost is found to have the highest Sensitivity and PME, while Random Forest and MLP gave the best Specificity and Precision. Logistic Regression is found to be the best model for accuracy with 97.8%, followed by SVM with 96.49%, Random Forest with 95.61%, and KNN & Decision Forest with 94.73%. The proposed approach is found to have the highest accuracy of 97.80% compared to other approaches studied. Our results indicate that the proposed approach using discretization can significantly improve the signal-to-noise ratio in the diagnosis of breast cancer. This approach can accurately predict and diagnose breast cancer using a subset of features. © 2023 IEEE.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

A Bottom-Up Enumeration Algorithm of Minimal Generators without Support Counting for Compressing Negative Association Rules 12

A Bottom-Up Enumeration Algorithm of Minimal Generators with...

引用

12th International Congress on Advanced Applied informatics, IIAI-AAI 2022

作者： Yajima, Kento Iwanuma, Koji Yamamoto, Yoshitaka University of Yamanashi Dept. of Computer Science & Eng Kofu-shi Japan Shizuoka University Dept. of Informatics Hamamatsu-shi Japan

ISBN: (数字)9781665497558

ISBN: (纸本)9781665497558

Negative association rules are valuable and essential for expressing various latent properties which hide in big data. The set of valid negative association rules, however, always becomes so huge, thus an effective compression method of negative rules is quite important. Minimal generators are important concepts for compressing the set of valid negative rules. In this paper, we study a bottom-up efficient algorithms for enumerating minimal generators from given closed itemsets. So far, support calculations have always been a bottleneck in data mining calculations. Therefore, we here propose a novel enumeration algorithm which does not use any explicit support computation. We show experimental results for evaluating our bottom-up enumeration algorithm, where the algorithm performs well in terms of memory consumption compared to previous algorithms. © 2022 IEEE.

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

Optimization of Building Construction Control System Based on Nonlinear Image Enhancement

引用

computer-Aided Design and Applications 2023年 20卷 213-224页

作者： Liu, Congru Lin, Mingsen Ghafoor, Kayhan Zrar Al-Dabagh, Mustafa Zuhaer Nayef Karras, Dimitrios A. School of Urban Construction Wuhan University of Science and Technology Wuhan China Changjiang Polytechnic Wuhan China Department of Computer Science Knowledge University Erbil44001 Iraq Department of Software & Informatics Engineering Salahaddin University-Erbil Erbil44001 Iraq School of Science Dept. General Athens Greece

To reflect the nonlinear characteristics of the building structural adjustment system, an active vibration control strategy based on the nonlinear is proposed. In this method, the size of the structural control force is determined by comparing the allowable energy with the actual energy, and its direction is determined by taking the derivative of the energy. Because there is no need to solve the linear matrix inequality, the calculation is simple and the operation is convenient. Moreover, when multiple actuators with the same capacity limit are used, the control output force is consistent, thus avoiding the design of multiple control systems and simplifying the controller design. The simulation results show that the maximum controlled displacements of floor 6 to floor 8 are 1.16cm, 1.12cm, and 0.97cm, respectively. The proposed nonlinear energy control method has the advantages of simple control process and avoiding actuator saturation. © 2023 CAD Solutions, LLC.

关键词： Floors

来源：评论

学校读者我要写书评

暂无评论

Using the Tsetlin Machine to Discover Fatality-Based Transitions in Political Violence

Using the Tsetlin Machine to Discover Fatality-Based Transit...

引用

Tsetlin Machine (ISTM), International Symposium on the

作者： Hsu-Chiang Hsu Bree Bang-Jensen Michael P. Colaresi Panos K. Chrysanthis Vladimir I. Zadorozhny Dept. of Informatics & Network Systems University of Pittsburgh Dept. of Political Science University of Pittsburgh Dept. of Computer Science University of Pittsburgh

ISBN: (数字)9798331504984

ISBN: (纸本)9798331504991

There is considerable momentum across multiple continents to build and deploy systems that can usefully inform policy-makers and aid agencies about the timing, location, and scale of political violence. In this paper we introduce a framework that utilizes an architecture based on the Tsetlin Machine to detect notable transitions between lower and higher levels of political violence as measured by fatalities. We engineer input features based on the influential framework of horizontal inequalities (HI) and conflict history as they have been theorized to presage violence. However, we encounter the challenge that some classes are more or less distinguishable from others using TM-generated rules. We leverage the analytical structure of TMs and their weights to explain these clusters. To do so, we introduce the concept of a class spectrum and reduce the dimensions of these spectrums across classes and features with principal components analysis (PCA). This pipeline allows us to find transition (change) points between the fatality classes and cluster the classes into efficiently detectable groups. These tools provide both researchers and policy-makers a means of understanding similarities and differences in explanations across different conflict phases.

关键词： Pipelines Warehousing Africa Predictive models Data models Timing History Principal component analysis

来源：评论

学校读者我要写书评

暂无评论

Selecting Machine Learning Models for Student Performance Prediction Aligned with Pedagogical Objectives

Selecting Machine Learning Models for Student Performance Pr...

引用

2023 IEEE International Conference on Computing, ICOCO 2023

作者： Khan, Ijaz Zabil, Mohammed Hazli Mohamed Ahmad, Abdul Rahim Jabeur, Nafaa College of Computing and Informatics Univsiti Tenaga Nasional Department of Computing Kajang Malaysia Buraimi University College Information Technology Dept. Al-Buraimi Oman Deparment of Computing and Informatics' Kajang Malaysia German University of Technology Computer Science Dept. Muscat Oman

ISBN: (纸本)9798350302684

Machine learning classifiers emerge as productive tools to develop prediction models which forecast the final outcome of the students, in a course, and provide an opportunity to the instructor to take appropriate measures. A single prediction model may not be enough to achieve all the objectives of an instructor. The selection of appropriate prediction models is yet a challenging task. This paper proposes a novel framework that applies a set of machine learning classifiers over the training dataset of a course. Along with the training dataset, the instructor clarifies the prime of objective of the binary model whether it must focus over the identification of fail, pass, or both students. The framework recommends a convenient model to achieve the specific objectives of the instructor. This research concludes that models inclined to reduce misclassification of minority class are suitable if the primary objective of the institution is the correct identification of students who are struggling to achieve the minimum course requirements. Further, a model specialized solely in amplifying the correct classification of majority class instance is appropriate if the aim is to focus on the correct identification of excellent students. The empirical analysis in this research leads towards the fact that accuracy alone is not an adequate metric to assess the performance of a model and that systematic selection of evaluation metrics is required to develop constructive models. © 2023 IEEE.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Causal Structure Learning from Imperfect Longitudinal Data in Healthcare 11

Causal Structure Learning from Imperfect Longitudinal Data i...

引用

11th IEEE International Conference on Healthcare informatics, ICHI 2023

作者： Yang, Haoyu Tourani, Roshan Li, Jia Caraballo, Pedro Steinbach, Michael Kumar, Vipin Simon, Gyorgy University of Minnesota Dept. of Computer Science and Engineering Minneapolis United States University of Minnesota Institute for Health Informatics Minneapolis United States Mayo Clinic Dept. of Internal Medicine Rochester United States

ISBN: (纸本)9798350302639

Causal Structure Discovery (CSD) is the task of learning the set of underlying causal relationships from observational data. Due to their computational scalability and flexibility, a recently developed class of CSD methods, NOTEARS, based on a formulation allowing for continuous optimization, is gaining popularity. However, this formulation can lead to incorrect edge orientations when little/no likelihood advantage is conferred upon any edge orientation, e.g., a → b → c versus c → b → a. In longitudinal data, like electronic health records (EHRs), temporal relationships are observable among many pairs of variables. Such temporal relationship is imperfect but still suggest an orientation since causal effects cannot travel backwards in time. Following this idea, we propose methods to incorporate precedence constraints into continuous optimization-based CSD methods. Experiments on both a synthetic and two real-world datasets validate the effectiveness of the proposed precedence constraints. © 2023 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Nanotechnology as a Tool for Computational Thinking Skills using Open Hardware, Embedded Systems and Repository Platform, in Industry 4.0 Era

Nanotechnology as a Tool for Computational Thinking Skills u...

引用

South Eastern European Design Automation, computer Engineering, computer Networks and Social Media Conference (SEEDA-CECNSM)

作者： Konstantinos Kalovrektis Ioannis Dimos Apostolos Xanakis Athanasios Kakarountas Dept. of Digital Systems University of Thessaly Larisa Greece Dept. of Computer Science and Biomedical Informatics University of Thessaly Lamia Greece

The advancement in Microelectromechanical System (MEMS) technology resulted in accurate and high-performance miniature device systems. These devices are so tiny that they are not noticeable by the human eye and exhibit excellent feasibility in miniaturization sensors due to their small dimensions, low power consumption, and superior performance. The area of sci-ence and engineering where MEMS are developed (dimensions in the manometer scale) is called Nanotechnology. Nanotechnology is one of the fastest growing scientific research related to Industry 4.0. Nanotechnology may introduce industrial skills deficits as well as opportunities for new teaching practices in several subjects and educational frameworks. In the present work, we investigate the attitude of STEM (i.e. technology/engineering) and non STEM - related instructors, regarding the integration of Nanotechnology applications in Higher education curricula. Their opinions, concerning the applied teaching method, the learning content material and expected student skills, should always be taken in to account, as they may boost any reformations proposed. Moreover, we propose a repository platform, with which instructors may interact with 3D designs and MEMs mate-rial to built their didactic plans. This work's findings is critical for the design and innovative training material and computational thinking (CT) activities, which will prepare student with skills related to Industry 4.0 demand.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Towards the Selection of Distance Metrics for k-NN Classifier in Students' Performance Prediction Modeling

Towards the Selection of Distance Metrics for k-NN Classifie...

引用

2023 IEEE International Conference on Computing, ICOCO 2023

作者： Khan, Ijaz Mohamed Zabil, Mohammed Hazli Ahmad, Abdul Rahim Jabeur, Nafaa College of Computing and Informatics' Univsiti Tenaga Nasional Department of Computing Kajang Malaysia Buraimi University College Information Technology Dept. Al-Buraimi Oman Deparmtne of Computing and Informatics' Kajang Malaysia German University of Technology Computer Science Dept. Muscat Oman

ISBN: (纸本)9798350302684

This paper investigates the impact of changing distance metrics on the performance of the k-NN classifier. The study investigates the variation in models performance with changing distance metric and value of k in the context of students' performance prediction models. The research utilizes datasets specifically designed for students' performance prediction modeling. Starting with a I-NN model, the experiments increment the value of k by 2 until the size of the dataset is reached. The experiments are repeated with different distance metrics derived from Minkowski derivation, including Euclidean, Manhattan, and Chebyshev. The findings indicate that there is no unanimously dominant distance metric for every dataset. However, the Euclidean and Manhattan distance metrics emerge effective, while Chebyshev exhibits lower performance. The research concludes Euclidean and Manhattan distance metrics as appropriate metrics for students' performance prediction modeling using the k-NN classifier. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Eye Tracking System Using Convolutional Neural Network 5

Eye Tracking System Using Convolutional Neural Network

引用

5th International Conference on computer and Applications, ICCA 2023

作者： Iskandar, Shatha Jaara, Zahraa Ali, Mohamad Abou Sbeity, Fatima Kasem, Abdallah Hamawy, Lara Lebanese International University Department of Biomedical Engineering Lebanon University of the Basque Country Dept.of Computer Science & Artificial Intelligence Spain Lebanese University Dept. of Physics & Electronics Lebanon Notre Dame University Dept. of Electrical & Computer Engineering Lebanon

ISBN: (纸本)9798350303254

Several diseases and disabilities, including cerebral palsy (CP), cause patients to lose their ability to communicate easily with the outside world. In this paper we aim to detect the movement of the iris that can be used to move a wheelchair for CP patients, write sentences by simply looking at an interactive screen, or even by moving an artificial arm. Thus, the two-dimensional CNN model and the coding method, we proposed, tracks the eye movement, specifically the movement of the iris, using VGG image annotator software and a dataset of several people's eyes images A dataset of 500 images from several patients, where only the eyes were cropped and studied, was taken to train the model about eye movement and detection. The proposed model achieved a mean squared error drop of about 49,720 from the original we started with, which was 50,000. © 2023 IEEE.

关键词： Neural network models

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：