检索结果-内蒙古大学图书馆

Joint of the 5th International Workshop on Experience with SQuaRE Series and its Future Direction and the 11th International Workshop on Quantitative Approaches to software Quality, IWESQ-QuASoQ 2023

作者： Lichter, Horst Sunetnanta, Thanwadee Anwar, Toni Research Group Software Construction RWTH Aachen University Aachen Germany Computer Science Academic Group Faculty of Information And Communication Technology Mahidol University Bangkok Thailand Faculty of Science and Information Technology Computer & Information Systems Universiti Teknologi Petronas Bandar Seri Iskandar Perak Malaysia

来源：评论

学校读者我要写书评

暂无评论

Comparative Study between KNN and CNN's Techniques for Kidney Stone Detection

Comparative Study between KNN and CNN's Techniques for Kidne...

引用

2023 International Conference on Smart Computing and Application, ICSCA 2023

作者： Al-Tbenawey, Fahdah M. Alotaibi, Shoayee Salem, Marwa Mir, Shamaila Mir, Zahida Computer Science and Engineering College University of Ha'il Department of Computer Science and Information Hail Saudi Arabia Faculty of Engineering Department of Electrical Communication and Electronics Systems Engineering Cairo Egypt

ISBN: (纸本)9798350347050

This paper aims to determine the better technique for kidney stone detection between K-Nearest Neighbor (KNN) and Convolutional Neural Networks (CNNs). As well known, the presence of kidney stones is an important topic that deserves discussion regarding expected medical outcomes. Most of the detection measures comprise CT scans, ultrasounds, and abdominal X-rays. These measures have varying effectiveness levels, hence used in the detection to prepare patients for specific treatment options. Patients' treatment options comprise percutaneous nephrolithotomy (PCNL), extracorporeal shockwave lithotripsy (ESWL), and ureteroscopy. The different detection techniques carried out for the patients are essential to test whether the patient has small or large kidney stones. One essential technique is using conventional neural networks (CNNs) technology. In this paper kidney, stone detection will be carried out using both of K-Nearest Neighbor (KNN) and CNN's techniques. A comparison between both techniques will be carried out to figure out the better. All of the simulations are carried out using MATLAB. © 2023 IEEE.

关键词： MATLAB

来源：评论

学校读者我要写书评

暂无评论

A Code-Switched Arabic-English Sentiment Analysis Approach Based on Deep-Learning 3

A Code-Switched Arabic-English Sentiment Analysis Approach B...

引用

3rd International Mobile, Intelligent, and Ubiquitous Computing Conference, MIUCC 2023

作者： Almasah, Tasneem S. Ebrahim, Gamal A. Abdelaal, Marwa A. The British University in Egypt Faculty of Engineering Electrical Engineering Department Cairo Egypt Ain Shams University Faculty of Engineering Computer and Systems Engineering Department Cairo Egypt Sadat Academy for Management Sciences Faculty of Computers and Information Computer Science Department Cairo Egypt

ISBN: (纸本)9798350306231

Sentiment analysis within Online Social Networks (OSNs) becomes a major challenge. Mainly, because of the large amount of data on social networks and the mix of different languages that can be used in these environments. Due to the lack of existing research and datasets on code-switched Arabic-English sentiment analysis, this study creates a new dataset collected from various online social networks. The data is subjected to several preprocessing steps before being analyzed using various deep learning architectures. Moreover, a thorough evaluation of the preprocessing techniques and the performance of the deep learning models have been conducted. This is achieved using comprehensive Twitter datasets in Arabic and English. The study reveals that individual deep learning architectures, specifically, Convolutional Neural Networks (CNNs), Bidirectional Long Short Term Memory (Bi-LSTM), and LSTM demonstrated superior results compared to their hybrid counterparts. Notably, CNN emerged as the most accurate model with an accuracy of 83%, followed closely by Bi-LSTM at 82.3%. Additionally, the paper presents the deployment of an automated machine learning tool, which is Auto-Keras. Furthermore, it designs an optimized sentiment analysis model that aims to enhance accuracy. This approach leads to an increase in the model accuracy to 86%. © 2023 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Organizational Patterns for Improving the Understanding between a Customer and the Development Team 27

Organizational Patterns for Improving the Understanding betw...

引用

2022 27th European Conference on Pattern Languages of Programs, EuroPLoP 2022

作者： Khattab, Mohammad Ismail Vranic, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Slovakia

ISBN: (纸本)9781450395946

During a software development process, a customer and the development team need to communicate and understand each other. Poor communication between a customer and the development team is one of the most common challenges in the software development process, which leads to software failures and further increases the budget. In our practical experience and from the literature, we found that lack of customer involvement, no common communication language, complex business processes, end-user resistance toward system development, lack of trust, lack of leadership, and and end-user capacity are the main challenges toward the development team understanding. We bring six newly discovered patterns that address these problems and improve the understanding between a customer and the development team during the software development process. We also bring some of the known organizational patterns that also mitigate these problems into relation to the newly discovered patterns. To create a pattern language from these patterns, we illustrated the sequences of the patterns so that the development team and customer could understand each other. © 2022 ACM.

关键词： software design

来源：评论

学校读者我要写书评

暂无评论

Identifying and Involving the Real End User in software Development: Towards a Pattern Language 27

Identifying and Involving the Real End User in Software Deve...

引用

2022 27th European Conference on Pattern Languages of Programs, EuroPLoP 2022

作者： Daud Haiderzai, Mohammad Vranic, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Slovakia

ISBN: (纸本)9781450395946

software development demand and identification of end users involvement have been increasing rapidly, but identifying the real end user and involving them in software development is challenging for software developers reported in the literature. One of the problems is the difficulty of designing the business domain. It takes longer to find the actual business domain when different and inexpert domain end users are engaged with developers. Another problem is the difficulty of incorporating all types of end users needs in software development. Several expectations and different information make the development process more complex and overload the project scope. software development also takes more time, and the project goal is challenging. The above problems are the leading causes that create a complex process and difficulty in software development. To overcome these problems, we established a pattern language composed of eight organizational patterns observed and documented during in practical work on many projects. These patterns and other known organizational patterns relation are described in a patterns story of a real company. © 2022 ACM.

关键词： software design

来源：评论

学校读者我要写书评

暂无评论

Comparison of Visual Occupancy Detection Approaches for Parking Lots and Dedicated Containerized REST-API Server Application 9

Comparison of Visual Occupancy Detection Approaches for Park...

引用

9th Workshop on software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2022

作者： Petričko, Andrej Dakić, Pavle Vranić, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology Bratislava Slovakia

With the development of new technology, the urban infrastructure, which is necessary to meet the social, economic, and physical needs of the population, is also gradually improving. Therefore, cities face significant urban planning challenges. With the increasing population and number of cars on the road parking space occupancy detection techniques are of great importance for efficient parking space management. Knowing the availability of parking spaces within a city in real-time and informing residents can be of great help in reducing the number of car park councils, reducing traffic congestion in cities, or improving the scalability of car parks and the time needed to find empty parking space. In many car parks, ground sensors are used to determine occupancy status. However, this requires the installation and maintenance of these sensors in every parking space. This can be expensive, especially in car parks with a large number of available spaces. With increasing computing power, new approaches to parking space occupancy detection using computer vision are emerging. However, these approaches are tailored to the site of application. In this work, we propose a comparison of two general approaches: classification and object detection. The reliability, precision, and scalability of these approaches are compared using a REST-API server application implemented in Python. In order to get as close as possible to general use, we use docker, which enables us easier develop and deploy this application independently of the hardware. © 2022 Copyright for this paper by its authors.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Toward Organizational Pattern Ontology 27

Toward Organizational Pattern Ontology

引用

2022 27th European Conference on Pattern Languages of Programs, EuroPLoP 2022

作者： Waseeb, Shakirullah Vranic, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Slovakia

ISBN: (纸本)9781450395946

Organizational patterns of agile software development are proven practices for dealing organizational principles. Finding and selecting the right pattern is difficult. One way to select a pattern is to follow the sequence and compositions given in a pattern language. However, in general, pattern languages do not always reveal every reliable connection. Patterns are described in informal and unstructured text, making it difficult to understand their connections. This work attempts to provide a conceptual ontology model for organizational patterns-describing the collection of concepts (terms) and their relations. This contribution can be an attempt to express, expose, and share semantic knowledge between patterns using ontology. The resulting ontology can be used on top of the organizational patterns repositories to help retrieve patterns based on their logical connections. © 2022 ACM.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Opinion Formation and Social Impact in Networks with Natural and Artificial Intelligence systems 16

Opinion Formation and Social Impact in Networks with Natural...

引用

16th International Conference Management of Large-Scale System Development, MLSD 2023

作者： Tsarev, Dmitriy Avdyushina, Anna Alodjants, Alexander Itmo University Institute of Advanced Data Transfer Systems St. Petersburg Russia Itmo University Faculty of Software Engineering and Computer Systems St. Petersburg Russia

ISBN: (纸本)9798350337907

We suggest a new quantum-like approach to study distributed intelligence systems (DIS) consisting of natural (owners) and artificial (avatars) intelligence agents organized in a scale-free network. We demonstrate the complex features of social impact in DIS that imply the hierarchical formation of opinion leaders in the network and their topological protection. We elucidated the effect of significant narrowing of the spread of opinions within the network when most owners chose their position as limiting (extreme). © 2023 IEEE.

关键词： Multi agent systems

来源：评论

学校读者我要写书评

暂无评论

Adaptive Dynamic Dipper Throated Optimization for Feature Selection in Medical Data

引用

computers, Materials & Continua 2023年第4期75卷 1883-1900页

作者： Ghada Atteia El-Sayed M.El-kenawy Nagwan Abdel Samee Mona M.Jamjoom Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Ahmad Taher Azar Nima Khodadadi Reham A.Ghanem Mahmoud Y.Shams Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Faculty of Computers and Artificial Intelligence Benha UniversityBenha13518Egypt College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Civil Engineering University of Science and TechnologyMiami33101USA Department of Civil and Environmental Engineering Florida International UniversityMiamiUSA Oral Biology Department Faculty of Oral and Dental MedicineDelta University for Science and TechnologyGamasaEgypt Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt

The rapid population growth results in a crucial problem in the early detection of diseases inmedical *** all the cancers unveiled,breast cancer is considered the second most severe ***,an exponential rising in death cases incurred by breast cancer is expected due to the rapid population growth and the lack of resources required for performing medical *** recent advances in machine learning could help medical staff in diagnosing diseases as they offer effective,reliable,and rapid responses,which could help in decreasing the death *** this paper,we propose a new algorithm for feature selection based on a hybrid between powerful and recently emerged optimizers,namely,guided whale and dipper throated *** proposed algorithm is evaluated using four publicly available breast cancer *** evaluation results show the effectiveness of the proposed approach from the accuracy and speed *** prove the superiority of the proposed algorithm,a set of competing feature selection algorithms were incorporated into the conducted *** addition,a group of statistical analysis experiments was conducted to emphasize the superiority and stability of the proposed *** best-achieved breast cancer prediction average accuracy based on the proposed algorithm is 99.453%.This result is achieved in an average time of 3.6725 s,the best result among all the competing approaches utilized in the experiments.

关键词： Medical dataset breast cancer guided whale optimizer dipper throated optimizer feature selection meta-heuristics

来源：评论

学校读者我要写书评

暂无评论

Hybrid Malware Variant Detection Model with Extreme Gradient Boosting and Artificial Neural Network Classifiers

引用

computers, Materials & Continua 2023年第9期76卷 3483-3498页

作者： Asma A.Alhashmi Abdulbasit A.Darem Sultan M.Alanazi Abdullah M.Alashjaee Bader Aldughayfiq Fuad A.Ghaleb Shouki A.Ebad Majed A.Alanazi Department of Computer Science Northern Border UniversityArar9280Saudi Arabia Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Information Systems College of Computer Science and InformationJouf UniversitySakakaAljoufSaudi Arabia School of Computing University Teknologi Malaysia81310 UTM Johor BahruJohor81310Malaysia Department of Computer and Electronic Engineering Sana’a Community CollegeSana’a5695Yemen

In an era marked by escalating cybersecurity threats,our study addresses the challenge of malware variant detection,a significant concern for amultitude of sectors including petroleum and mining *** paper presents an innovative Application Programmable Interface(API)-based hybrid model designed to enhance the detection performance of malware *** model integrates eXtreme Gradient Boosting(XGBoost)and an Artificial Neural Network(ANN)classifier,offering a potent response to the sophisticated evasion and obfuscation techniques frequently deployed by malware *** model’s design capitalizes on the benefits of both static and dynamic analysis to extract API-based features,providing a holistic and comprehensive view of malware *** these features,we construct two XGBoost predictors,each of which contributes a valuable perspective on the malicious activities under *** outputs of these predictors,interpreted as malicious scores,are then fed into an ANN-based classifier,which processes this data to derive a final *** strength of the proposed model lies in its capacity to leverage behavioral and signature-based features,and most importantly,in its ability to extract and analyze the hidden relations between these two types of *** efficacy of our proposed APIbased hybrid model is evident in its performance *** outperformed other models in our tests,achieving an impressive accuracy of 95%and an F-measure of 93%.This significantly improved the detection performance of malware variants,underscoring the value and potential of our approach in the challenging field of cybersecurity.

关键词： API-based hybrid malware detection model static and dynamic analysis malware detection

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：