检索结果-内蒙古大学图书馆

4th International Conference on Smart Grid Metrology, SMAGRIMET 2023

作者： Knol, Kristian Bensic, Tin Barukcic, Marinko Osijek Josip Juraj Strossmayer University of Osijek Faculty of Electrical Engineering Computer Science and Information Technology Department of Electromechanical Engineering Osijek Croatia

ISBN: (纸本)9798350323597

During the development of control strategies for permanent magnet synchronous machines (PMSM) used in wind turbines, usage of wide range of simulation allows for more detailed, more safe and less expensive development. This paper presents type of HIL simulation, where instead of using real controller and real-Time simulator, two real-Time simulators are used and form a co-simulation environment where vector control of PMSM is conducted. The whole process of designing and simulating is a part of model-based design (MBD). The PMSM is described and controller for vector control is derived. Created co-simulation environment with its advantages and problems is described. An experiment with different scenarios is conducted to test created co-simulation. © 2023 IEEE.

关键词： Vectors

来源：评论

学校读者我要写书评

暂无评论

Computational Microarray Gene Selection Model Using Metaheuristic Optimization Algorithm for Imbalanced Microarrays Based on Bagging and Boosting Techniques 11th

Computational Microarray Gene Selection Model Using Metaheur...

引用

11th International Conference on Model and Data engineering, MEDI 2022

作者： Elden, Rana Hossam Ghoneim, Vidan Fathi Hadhoud, Marwa M. A. Al-Atabany, Walid Biomedical Engineering Department Faculty of Engineering Helwan University Cairo Egypt Information Technology and Computer Science School Nile University Giza Egypt

ISBN: (纸本)9783031215940

Genomic microarray databases encompass complex high dimensional gene expression samples. Imbalanced microarray datasets refer to uneven distribution of genomic samples among different contributed classes which can negatively affect the classification performance. Therefore, gene selection from imbalanced microarray dataset can give rise to misleading, and inconsistent nominated genes that would alter the classification performance. Such unsatisfactory classification performance is due to the skewed distribution of the samples across the microarrays toward the majority class. In this paper, we propose a modified version of Emperor Penguin Optimization (EPO) algorithm combined with Random Forest (RF) of Bagging and Boosting Classification named by EPO-RF to select the most informative genes based on classification accuracy using imbalanced microarray datasets. The modified version of EPO was built to be based on decision trees that takes in consideration the criterion of tree splitting weights to handle the imbalanced microarray datasets. Average gene expression binary values are used as a preliminary step for exploring disease trajectories with the aid of metaheuristic optimization feature selection algorithms. Results show that the proposed model revealed its superiority compared to well-known established metaheuristic optimization algorithms, e.g., Harris Hawks Optimization (HHO), Grey Wolf Optimization (GWO), Salp Swarm Optimization (SSO), Particle Swarm Optimization (PSO), and Genetic Algorithms (GA’s) using several pediatric sepsis microarray datasets for patients who admitted to the Intensive Care Unit (ICU) for the first 24 h. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Gene expression

来源：评论

学校读者我要写书评

暂无评论

Ontology-Based News Linking for Semantic Temporal Queries

引用

computers, Materials & Continua 2023年第2期74卷 3913-3929页

作者： Muhammad Islam Satti Jawad Ahmed Hafiz Syed Muhammad Muslim Akber Abid Gardezi Shafiq Ahmad Abdelaty Edrees Sayed Salman Naseer Muhammad Shafiq Faculty of Computing Riphah International UniversityI-14 CampusIslamabad44000Pakistan Department of Computer Science Zabsolutions SZABISTIslamabadPakistan Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Information Technology University of the Punjab Gujranwala CampusGujranwala52250Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Daily newspapers publish a tremendous amount of information disseminated through the *** available and easily accessible large online repositories are not indexed and are in an un-processable *** major hindrance in developing and evaluating existing/new monolingual text in an image is that it is not linked and *** is no method to reuse the online news images because of the unavailability of standardized benchmark corpora,especially for South Asian *** corpus is a vital resource for developing and evaluating text in an image to reuse local news systems in general and specifically for the Urdu *** of indexing,primarily semantic indexing of the daily news items,makes news items impracticable for any ***,the most straightforward search facility does not support these unindexed news *** study addresses this gap by associating and marking the newspaper images with one of the widely spoken but under-resourced languages,i.e.,*** present work proposed a method to build a benchmark corpus of news in image form by introducing a web *** corpus is then semantically linked and annotated with daily news *** techniques are proposed for image annotation,free annotation and fixed cross examination *** second technique got higher *** news ontology in protégéusing OntologyWeb Language(OWL)language and indexed the annotations under *** application is also built and linked with protégéso that the readers and journalists have an interface to query the news items ***,news items linked together will provide complete coverage and bring together different opinions at a single location for readers to do the analysis themselves.

关键词： Annotations corpus information retrieval semantic ontology

来源：评论

学校读者我要写书评

暂无评论

Exploring the Potential of Secure Shell (SSH) as a Wireless Network Security Tool 15

Exploring the Potential of Secure Shell (SSH) as a Wireless ...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Mishra, Abhinav Sahoo, Girija Shankar Sekaran, Ramesh Umamaheswari, B. Futane, Pravin R. Choudhary, Sanjay Chitkara University Institute of Engineering and technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Maharishi University of Information Technology Maharishi School of Engineering and Technology UttarPradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Ramnagar District562112 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai127 India Vishwakarma Institute of Technology Department of Information Technology Pune India Vivekananda Global University Department of Mechanical Engineering Jaipur India

ISBN: (纸本)9798350370249

Comfy Shell is an open-source protocol used for many years to comfy community logins and communication over the net. It is primarily based on public key cryptography and is well known for being one of the maximum cozy strategies of authentication and communication. It is now being explored as a Wi-Fi network security device for defensive information transmitted over WiFi networks, including those typically determined in cafes, airports, and other public locations. Its safety capabilities, which include robust authentication and encryption, make it an excellent desire to securely access assets, shift information, and connect to far-off structures. Moreover, it can be used as a digital private network (VPN) to safely establish connections between two or extra computers in a public community. At the same time as SSH is properly-appropriate for relaxed far-off connections, it can be configured to provide additional ranges of authentication and encryption to ensure the WiFi network's safety from malicious assaults. This paper will explore the capability of SSH as a Wi-Fi network safety tool, discuss diverse implementations, and focus on the particular components of using SSH as a security device for WiFi networks. © 2024 IEEE.

关键词： Wi-Fi

来源：评论

学校读者我要写书评

暂无评论

An Attention-Based Deep Network for Plant Disease Classification

引用

Machine Graphics and Vision 2024年第1期33卷 47-67页

作者： Bera, Asish Bhattacharjee, Debotosh Krejcar, Ondrej Department of Computer Science and Information Systems Birla Institute of Technology and Science Rajasthan Pilani India Department of Computer Science and Engineering Jadavpur University West Bengal Kolkata India Center for Basic and Applied Science Faculty of Informatics and Management University of Hradec Králové Czech Republic Škoda Auto University Mladá Boleslav Czech Republic Universiti Teknologi Malaysia Kuala Lumpur Malaysia

Plant disease classification using machine learning in a real agricultural field environment is a difficult task. Often, an automated plant disease diagnosis method might fail to capture and interpret discriminatory information due to small variations among leaf sub-categories. Yet, modern Convolutional Neural Networks (CNNs) have achieved decent success in discriminating various plant diseases using leave images. A few existing methods have applied additional pre-processing modules or sub-networks to tackle this challenge. Sometimes, the feature maps ignore partial information for holistic description by part-mining. A deep CNN that emphasizes integration of partial descriptiveness of leaf regions is proposed in this work. The efficacious attention mechanism is integrated with high-level feature map of a base CNN for enhancing feature representation. The proposed method focuses on important diseased areas in leaves, and employs an attention weighting scheme for utilizing useful neighborhood information. The proposed Attention-based network for Plant Disease Classification (APDC) method has achieved state-of-the-art performances on four public plant datasets containing visual/thermal images. The best top-1 accuracies attained by the proposed APDC are: PlantPathology 97.74%, PaddyCrop 99.62%, PaddyDoctor 99.65%, and PlantVillage 99.97%. These results justify the suitability of proposed method. © 2024 Institute of information technology, Warsaw University of Life sciences - SGGW. All rights reserved.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Sand Cat Swarm Optimization with Deep Transfer Learning for Skin Cancer Classification

引用

computer Systems science & engineering 2023年第11期47卷 2079-2095页

作者： C.S.S.Anupama Saud Yonbawi G.Jose Moses E.Laxmi Lydia Seifedine Kadry Jungeun Kim Department of Electronics and Instrumentation Engineering V.R.Siddhartha Engineering CollegeVijayawada520007India Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of Computer Science and Engineering University Institute of Engineering and Technology(UIET)Guru Nanak UniversityHyderabadIndia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Software Kongju National UniversityCheonan31080Korea

Skin cancer is one of the most dangerous *** of the high melanoma death rate,skin cancer is divided into non-melanoma and *** dermatologist finds it difficult to identify skin cancer from dermoscopy images of skin ***,pathology and biopsy examinations are required for cancer *** studies have formulated computer-based systems for detecting skin cancer from skin lesion *** recent advancements in hardware and software technologies,deep learning(DL)has developed as a potential technique for feature ***,this study develops a new sand cat swarm optimization with a deep transfer learning method for skin cancer detection and classification(SCSODTL-SCC)*** major intention of the SCSODTL-SCC model lies in the recognition and classification of different types of skin cancer on dermoscopic ***,Dull razor approach-related hair removal and median filtering-based noise elimination are ***,the U2Net segmentation approach is employed for detecting infected lesion regions in dermoscopic ***,the NASNetLarge-based feature extractor with a hybrid deep belief network(DBN)model is used for ***,the classification performance can be improved by the SCSO algorithm for the hyperparameter tuning process,showing the novelty of the *** simulation values of the SCSODTL-SCC model are scrutinized on the benchmark skin lesion *** comparative results assured that the SCSODTL-SCC model had shown maximum skin cancer classification performance in different measures.

关键词： Deep learning skin cancer dermoscopic images sand cat swarm optimization machine learning

来源：评论

学校读者我要写书评

暂无评论

An Assessment of the Security Benefits of Secure Shell (SSH) in Wireless Networks 3

An Assessment of the Security Benefits of Secure Shell (SSH)...

引用

3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Preetha, M. Dhabliya, Dharmesh Lone, Zeeshan Ahmad Pandey, Sakshi Acharjya, Kalyan Gowrishankar, J. Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Information Technology Maharashtra Pune India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science Engineering Faculty of Engineering and Technology Karnataka Ramnagar India

ISBN: (纸本)9798350319125

Comfortable Shell (SSH) is a community protocol that provides relaxed communique over an unsecured community, such as the internet. This protocol is generally used for far flung login, file switch, and remote command execution, making it a vital device for managing and securing networks. Wi-Fi networks, which rely upon radio frequency indicators for verbal exchange, are prone to various safety threats such as eavesdropping, spoofing, and man-in-themiddle assaults. This makes using relaxed protocols like SSH critical for protective sensitive statistics and keeping the integrity of Wi-Fi networks. This technical assessment evaluates the safety advantages of utilizing SSH in wireless networks. First of all, SSH makes use of strong encryption algorithms consisting of AES and RSA to encrypt the whole communique session, ensuring that records is transmitted securely between devices. This prevents attackers from intercepting and reading touchy records exchanged among gadgets. Secondly, SSH makes use of a public-key infrastructure for authentication, that's more at ease than conventional password-based totally authentication. This is because the private key, which is used for authentication, is not transmitted all through the login system, making it greater tough for attackers to advantage get entry to the network. © 2023 IEEE.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

Applications of Artificial Intelligence in the Economy, Including Applications in Stock Trading, Market Analysis, and Risk Management

引用

IEEE Access 2023年 11卷 80769-80793页

作者： Rahmani, Amir Masoud Rezazadeh, Bahareh Haghparast, Majid Chang, Wei-Che Ting, Shen Guan National Yunlin University of Science and Technology Future Technology Research Center Yunlin Douliou64002 Taiwan Islamic Azad University Science and Research Branch Department of Computer Engineering Tehran*** Iran University of Jyväskylä Faculty of Information Technology Jyväskylä40014 Finland

In an increasingly automated world, Artificial Intelligence (AI) promises to revolutionize how people work, consume, and develop their societies. science and technology advancement has led humans to seek solutions to problems;however, AI-based technology is not novel and has a wide range of economic applications. This paper examines AI applications in economics, including stock trading, market analysis, and risk assessment. A comprehensive taxonomy is proposed to investigate AI applications in various scopes of the proposed categories. Furthermore, we will discuss this area's most significant AI-based techniques and evaluation criteria. As a final step, we will identify challenges, open issues, and future work suggestions. © 2013 IEEE.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Hybrid of Distributed Cumulative Histograms and Classification Model for Attack Detection

引用

computer Systems science & engineering 2023年第5期45卷 2235-2247页

作者： Mostafa Nassar Anas M.Ali Walid El-Shafai Adel Saleeb Fathi E.Abd El-Samie Naglaa F.Soliman Hussah Nasser AlEisa Hossam Eldin H.Ahmed Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt Department of Computer Science Security Engineering LaboratoryPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Traditional security systems are exposed to many various attacks,which represents a major challenge for the spread of the Internet in the *** techniques have been suggested for detecting attacks using machine learning and deep *** significant advantage of deep learning is that it is highly efficient,but it needs a large training time with a lot of ***,in this paper,we present a new feature reduction strategy based on Distributed Cumulative Histograms(DCH)to distinguish between dataset features to locate the most effective *** histograms assess the dataset instance patterns of the applied features to identify the most effective attributes that can significantly impact the classification *** different models for detecting attacks using Convolutional Neural Network(CNN)and Long Short-Term Memory Network(LSTM)are also *** accuracy test of attack detection using the hybrid model was 98.96%on the UNSW-NP15 *** proposed model is compared with wrapper-based and filter-based Feature Selection(FS)*** proposed model reduced classification time and increased detection accuracy.

关键词： Feature selection DCH LSTM CNN security systems

来源：评论

学校读者我要写书评

暂无评论

Process Discovery Automation: Benefits and Limitations 1

Process Discovery Automation: Benefits and Limitations

引用

1st International Conference of Intelligent Methods, Systems and Applications, IMSA 2023

作者： Montasser, Reem Kadry Helal, Iman M. A. October University for Modern Sciences and Arts Faculty of Computer Science Software Engineering Department Giza Egypt Cairo University Faculty of Computers and Artificial Intelligence Information Systems Department Giza Egypt

ISBN: (纸本)9798350335569

Process discovery algorithms incorporating domain knowledge can have varying levels of user involvement. It ranges from fully automated algorithms to interactive approaches where the user makes critical decisions about the process model. Designing domain knowledge using process discovery techniques faces various challenges. These challenges could cause some issues with existing approaches. Acquiring domain knowledge with domain experts, integrating domain knowledge with process data, scalability to handle large complex data sets, and ensuring data quality are examples of these challenges. In this survey, we assess recent work with varying levels of automation in process discovery to enhance the analysis and understanding of business processes within an organization. Current work can be classified into two categories: fully automated or semi-automated process discovery. We conclude that semi-automated process discovery gives a better opportunity for involving users. Also, the use of deep learning algorithms in automation gives better performance than machine learning algorithms. © 2023 IEEE.

关键词： Domain Knowledge

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：