检索结果-内蒙古大学图书馆

Federated Conference on computer science and Information Systems (FedCSIS)

作者： Chris Cornelis Henri Bollaert Department of Applied Mathematics Computational Web Intelligence Computer Science and Statistics Ghent University Belgium

Noting the highly complementary characteristics of fuzzy sets and rough sets, Dubois and Prade [7] proposed the first working definition of a fuzzy rough set, and thus paved the way for a flourishing hybrid theory wit...

关键词：

来源：评论

学校读者我要写书评

暂无评论

Extracting Key Information from Shopping Receipts by Using Bayesian Deep Learning via Multi-modal Features 3rd

Extracting Key Information from Shopping Receipts by Using...

引用

3rd International Conference on Neural Computing for Advanced Applications, NCAA 2022

作者： Chen, Jiaqi Shao, Lujiao Zhou, Haibin Ma, Jianghong Meng, Weizhi Wang, Zenghui Zhang, Haijun Departmant of Computer Science Harbin Institudte of Technology Shenzhen China Department of Applied Mathematics and Computer Science Technical University of Denmark Kongens Lyngby Denmark Department of Electrical and Mining Engineering University of South Africa Florida1710 South Africa

ISBN: (纸本)9789811961410

This research presents a new key information extraction algorithm from shopping receipts. Specifically, we train semantic, visual and structural features through three deep learning methods, respectively, and formulate rule features according to the characteristics of shopping receipts. Then we propose a multi-class text classification algorithm based on multi-modal features using Bayesian deep learning. After post-processing the output of the classification algorithm, the key information we seek for can be obtained. Our algorithm was trained on a self-labeled Chinese shopping receipt dataset and compared with several baseline methods. Extensive experimental results demonstrate that the proposed method achieves optimal results on our Chinese receipt dataset. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Seeking optimal Human/Machine collaborative practice in antisemitic terminology detection

Seeking optimal Human/Machine collaborative practice in anti...

引用

2024 IEEE Digital Platforms and Societal Harms, DPSH 2024

作者： Melillo, Wendy Emami, Jessica Guarinos, Solene Kikkisetti, Dhanush Klein, Melanie Liubovich, Lisa Mustafa, Raza Ul Japkowicz, Nathalie American University Journalism Division School of Communication United States American University College of Arts and Science Department of Sociology United States American University College of Arts and Science Department of Mathematics United States American University Justice Law and Criminology School of Public Affairs United States American University Data Science for Applied Public Affairs School of Public Affairs United States American University College of Arts and Science Department of Computer Science United States

ISBN: (纸本)9798350351309

This study is concerned with the use of antisemitic language on loosely moderated extremist alt-right social media. It compares, contrasts, and combines human-and machinebased approaches for discovering antisemitic coded or noncoded terminology in such media. Coded terminology refers to the language used in closed-knit communities to communicate beliefs and attitudes without expressing them explicitly. In noncoded discourse, the views of the writer are expressed more explicitly. The detection and analysis of antisemitic terminology in social media is an important problem that can help uncover and monitor the evolution of societal attitudes towards the Jews, and eventually, towards other minority groups once we expand our study. Given the growing prevalence of antisemitic rhetoric in online public spaces, there is a greater need for academic studies to determine its presence and identify strategies to curb its influence. Scholars have noted how intolerant expressions can threaten democratic values. Antisemitic content, like other forms of hate speech, has the potential to radicalize people who may commit violence based on their prejudicial viewpoints. The purpose of this paper is to discuss three different approaches for discovering antisemitic terminology on social media. In particular, it describes an experiment in which three groups-human, software, and mixed-"competed' on the task of retrieving antisemitic terminology over a two-month period (January-February, 2024). The results were manually evaluated for relevance and frequency of occurrence in the next month period (March 2024). The study shows that each group discovered valuable terminology and that neither the human nor the machine group could replace the other. Instead, we advocate that both groups work together using their respective knowledge to optimize the discovery of new terminology on social media. © 2024 IEEE.

关键词： Terminology

来源：评论

学校读者我要写书评

暂无评论

Optimization of Cognitive Radio System Using Enhanced Firefly Algorithm

引用

Intelligent Automation & Soft Computing 2023年第9期37卷 3159-3177页

作者： Nitin Mittal Rohit Salgotra Abhishek Sharma Sandeep Kaur SSAskar Mohamed Abouhawwash University Center for Research and Development Chandigarh UniversityMohaliPunjab140413India Faculty of Physics and Applied Computer Science AGH University of Science&TechnologyKrakowPoland Faculty of Information Technology Middle East UniversityAmman11813Jordan Department of Computer Engineering and Applications GLA UniversityMathura281406India Department of Computer Engineering&Technology Guru Nanak Dev UniversityAmritsarPunjab143005India Department of Statistics and Operations Research College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia Department of Computational Mathematics Science and EngineeringCollege of EngineeringMichigan State UniversityEast LansingMI48824USA Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt

The optimization of cognitive radio(CR)system using an enhanced firefly algorithm(EFA)is presented in this *** Firefly algorithm(FA)is a nature-inspired algorithm based on the unique light-flashing behavior of *** has already proved its competence in various optimization prob-lems,but it suffers from slow convergence *** improve the convergence performance of FA,a new variant named EFA is *** effectiveness of EFA as a good optimizer is demonstrated by optimizing benchmark functions,and simulation results show its superior performance compared to biogeography-based optimization(BBO),bat algorithm,artificial bee colony,and *** an application of this algorithm to real-world problems,EFA is also applied to optimize the CR *** is a revolutionary technique that uses a dynamic spectrum allocation strategy to solve the spectrum scarcity ***,it requires optimization to meet specific performance *** results obtained by EFA in CR system optimization are compared with results in the literature of BBO,simulated annealing,and genetic *** results further prove that the proposed algorithm is highly efficient and provides superior results.

关键词： Firefly algorithm cognitive radio bit error rate genetic algorithm simulated annealing biogeography-based optimization

来源：评论

学校读者我要写书评

暂无评论

Aggregating Structural Features for Computational Analysis of Mutations in BRCT Domains of BRCA1 Protein

Aggregating Structural Features for Computational Analysis o...

引用

2023 International Conference on Informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Hidayat, Alam Ahmad Nirwantono, Rudi Isnan, Mahmud Trinugroho, Joko Pebrianto Pardamean, Bens Bina Nusantara University School of Computer Science Bioinformatics and Data Science Research Center Mathematics Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Bioinformatics and Data Science Research Center Biotechnology Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Binus Graduate Program Bioinformatics and Data Science Research Center Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350307306

Understanding the mechanistic interpretability of mutation effects in a protein can help predict the clinical implications of the genetic variants. Hence, computational variant effect predictions that involve protein structural features of the protein mutations might be suitable in this case. In this work, we focus on BRCT domains of BRCA1 gene that is widely studied in breast cancer studies. We retrieved 88 selected missense variants found in BRCT domains annotated in both ClinVar and gnomAD databases. To computationally characterize the pathogenic property of the mutations we used two types of features extracted from protein structures: a change in free Gibbs energy and a set of features derived from molecular dynamics simulations of each mutant. Using a dimensional reduction and Gaussian mixture model (GMM)-based clustering we demonstrate that the variants are segregated into two regions that may correspond to their pathogenic status. This method can be a potential computational pipeline for providing the preliminary mechanistic interpretation of mutation effects in terms of their thermodynamic and structural features. © 2023 IEEE.

关键词： Proteins

来源：评论

学校读者我要写书评

暂无评论

AI-Based Detection of Droplets and Bubbles in Digital Microfluidic Biochips

AI-Based Detection of Droplets and Bubbles in Digital Microf...

引用

Design, Automation and Test in Europe Conference and Exhibition

作者： Jianan Xu Wenjie Fan Jan Madsen Georgi Plamenov Tanev Luca Pezzarossa Department of Applied Mathematics and Computer Science Technical University of Denmark Kgs. Lyngby Denmark

Digital microfluidic biochips exploit the electrowet-ting on dielectric effect to move and manipulate microliter-sized liquid droplets on a planar surface. This technology has the potential to automate and miniaturize biochemical processes, but reliability is often an issue. The droplets may get temporarily stuck or gas bubbles may impede their movement leading to a disruption of the process being executed. However, if the position and size of the droplets and bubbles are known at run-time, these undesired effects can be easily mitigated by the biochip control system. This paper presents an AI-based computer vision solution for real-time detection of droplets and bubbles in DMF biochips and its implementation that supports cloud-based deployment. The detection is based on the YOLOv5 framework in combination with custom pre and post-processing techniques. The YOLOv5 neural network is trained using our own data set consisting of 5115 images. The solution is able to detect droplets and bubbles with real-time speed and high accuracy and to differentiate between them even in the extreme case where bubbles coexist with transparent droplets.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Thermal-Aware Channel Capacity

Thermal-Aware Channel Capacity

引用

2023 IEEE International Symposium on Information Theory, ISIT 2023

作者： Meng Chee, Yeow Etzion, Tuvi Schouhamer Immink, Kees A. Thanh Nguyen, Tuan Khu Vu, Van Weber, Jos H. Yaakobi, Eitan National University of Singapore Department of Industrial Systems Engineering and Management Singapore Technion - Israel Institute of Technology Department of Computer Science Haifa3200003 Israel Turing Machines Inc. Rotterdam3016 DK Netherlands Singapore University of Technology and Design Science Mathematics and Technology Cluster Singapore Delft University of Technology Department of Applied Mathematics Delft2628 CD Netherlands

ISBN: (纸本)9781665475549

High temperatures in electronic devices have a negative effect on their performance. Various techniques have been proposed and studied to address and combat this thermal challenge. To guarantee that the peak temperature of the devices will be bounded by some maximum temperature, the transmitted signal has to satisfy some *** this motivation, we study the constrained channel that only accepts sequences that satisfy prescribed thermal constraints. The main goal in this paper is to compute the capacity of this channel. We provide the exact capacity of the channel with some certain parameters and we also present some bounds on the capacity in various ***, we consider the model that multiple wires are available to use and find out the smallest number of wires required to satisfy the thermal constraints. © 2023 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Improved PIR Schemes using Matching Vectors and Derivatives

arXiv

引用

arXiv 2024年

作者： Ghasemi, Fatemeh Kopparty, Swastik Sudan, Madhu Department of Mathematics University of Toronto Canada Department of Mathematics Department of Computer Science University of Toronto Canada School of Engineering and Applied Sciences Harvard University CambridgeMA United States

In this paper, we construct new t-server Private Information Retrieval (PIR) schemes with communication complexity subpolynomial in the previously best known, for all but finitely many t. Our results are based on combining derivatives (in the spirit of Woodruff-Yekhanin [WY05]) with the Matching Vector based PIRs of Yekhanin [Yek08] and Efremenko [Efr09]. Previously such a combination was achieved in an ingenious way by Dvir and Gopi [DG15], using polynomials and derivatives over certain exotic rings, en route to their fundamental result giving the first 2-server PIR with subpolynomial communication. Our improved PIRs are based on two ingredients: • We develop a new and direct approach to combine derivatives with Matching Vector based PIRs. This approach is much simpler than that of Dvir-Gopi: it works over the same field as the original PIRs, and only uses elementary properties of polynomials and derivatives. • A key subproblem that arises in the above approach is a higher-order polynomial interpolation problem. We show how "sparse S-decoding polynomials", a powerful tool from the original constructions of Matching Vector PIRs, can be used to solve this higher-order polynomial interpolation problem using surprisingly few higer-order evaluations. Using the known sparse S-decoding polynomials from [Efr09, IS08, CFL+13] in combination with our ideas leads to our improved PIRs. Notably, we get a 3-server PIR scheme with communication (formula presented), improving upon the previously best known communication of 2Õ(√log n) due to Efremenko [Efr09]. Copyright © 2024, The Authors. All rights reserved.

关键词： Vectors

来源：评论

学校读者我要写书评

暂无评论

GastroFuse-Net: an ensemble deep learning framework designed for gastrointestinal abnormality detection in endoscopic images

引用

Mathematical Biosciences and Engineering 2024年第8期21卷 6847-6869页

作者： Aggarwal, Sonam Gupta, Isha Kumar, Ashok Kautish, Sandeep Almazyad, Abdulaziz S. Mohamed, Ali Wagdy Werner, Frank Shokouhifar, Mohammad Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Model Institute of Engineering and Technology J&K Jammu India Chandigarh University Punjab Mohali140413 India Department of Computer Engineering College of Computer and Information Sciences King Saud University P.O. Box 51178 Riyadh11543 Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical Research Cairo University Giza12613 Egypt Applied Science Research Center Applied Science Private University Amman11931 Jordan Faculty of Mathematics Otto-von-Guericke University Magdeburg39016 Germany Institute of Research and Development Duy Tan University Da Nang550000 Viet Nam

Convolutional Neural Networks (CNNs) have received substantial attention as a highly effective tool for analyzing medical images, notably in interpreting endoscopic images, due to their capacity to provide results equivalent to or exceeding those of medical specialists. This capability is particularly crucial in the realm of gastrointestinal disorders, where even experienced gastroenterologists find the automatic diagnosis of such conditions using endoscopic pictures to be a challenging endeavor. Currently, gastrointestinal findings in medical diagnosis are primarily determined by manual inspection by competent gastrointestinal endoscopists. This evaluation procedure is labor-intensive, time-consuming, and frequently results in high variability between laboratories. To address these challenges, we introduced a specialized CNN-based architecture called GastroFuse-Net, designed to recognize human gastrointestinal diseases from endoscopic images. GastroFuse-Net was developed by combining features extracted from two different CNN models with different numbers of layers, integrating shallow and deep representations to capture diverse aspects of the abnormalities. The Kvasir dataset was used to thoroughly test the proposed deep learning model. This dataset contained images that were classified according to structures (cecum, z-line, pylorus), diseases (ulcerative colitis, esophagitis, polyps), or surgical operations (dyed resection margins, dyed lifted polyps). The proposed model was evaluated using various measures, including specificity, recall, precision, F1-score, Mathew’s Correlation Coefficient (MCC), and accuracy. The proposed model GastroFuse-Net exhibited exceptional performance, achieving a precision of 0.985, recall of 0.985, specificity of 0.984, F1-score of 0.997, MCC of 0.982, and an accuracy of 98.5%. ©2024 the Author(s), licensee AIMS Press.

关键词： Endoscopy

来源：评论

学校读者我要写书评

暂无评论

Guest Editorial to the Special Issue Public Transport Optimization: From Theory to Practice

引用

Operations Research Forum 2024年第3期5卷 73页

作者： Cacchiani, Valentina Müller-Hannemann, Matthias Rojas-Marcos, Federico Perea Department of Electrical Electronic and Information Engineering “Guglielmo Marconi” University of Bologna Viale Risorgimento 2 Bologna 40136 Italy Institute for Computer Science Martin Luther University Halle-Wittenberg Von-Seckendorff-Platz 1 Halle D 06120 Germany Department of Applied Mathematics II and Institute of Mathematics (IMUS) University of Seville Avda. Reina Mercedes s/n Seville 41012 Spain

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：