检索结果-内蒙古大学图书馆

3rd International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2021

作者： Kumar, Sushil Sharma, Meera Singh, V. B Muttoo, S. K University of Delhi Shyam Lal College Department of Computer Science India University of Delhi Swami Shraddhan and College Department of Computer Science India Jawaharlal Nehru University School of Computer and System Science Delhi India University of Delhi Department of Computer Science India

ISBN: (纸本)9781665438117

Software systems are being used in many businesses for performing critical operations such as financial operations. A bug in these systems can lead to financial losses. By identifying the type of such bugs, developers can easily take an action to fix a bug. Orthogonal defect classification model is a popular model for classifying bug reports in various attributes. In this paper, we proposed a bug report classification method that classify into their type as defined by ODC based on long short term memory, a RNN which is used in many classification task. The proposed method outperforms the classical approach such as bag of words and TF-IDF based classification models. © 2021 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Microservice-Based Fog Testbed for 6G Applications 26

Microservice-Based Fog Testbed for 6G Applications

引用

26th International Conference on Advanced Communications Technology, ICACT 2024

作者： Kuzmina, Ekaterina Tefikova, Meriem Volkov, Artem Muthanna, Ammar Ateya, Abdelhamied A. Koucheryavy, Andrey Saint-Petersburg State University of Telecommunications Department of Telecommunication Networks and Data Transmission Saint Petersburg Russia Zagazig University Department of Electronics and Communications Engineering Zagazig44519 Egypt College of Computer and Information Sciences Prince Sultan University Eias Data Science Lab Riyadh11586 Saudi Arabia

ISBN: (纸本)9791188428120

This paper provides a real-time fog computing model based on a microservice architecture that enables testing and modeling of eventual implementations of ultra-reliable low-latency communications (uRLLC) services. The work provides fog-based architecture for sixth-generation cellular (6G) applications, including telepresence and uRLLC. A testbed of a robot swarm was developed to prototype the proposed network architecture. Computing tasks are offloaded and handled based on a proposed microservice scheme introduced to meet the 6G requirements. Furthermore, we developed a novel migration scheme for the proposed architecture to support the mobility of end devices. The optimum server for migrating computing tasks is allocated by solving a proposed optimization problem using particle swarm optimization (PSO). All proposed algorithms were implemented in the developed prototype. The proposed work is introduced to provide an architectural foundation for testing fog-based 6G applications and services and to implement and test novel network methods in the future. © 2024 Global IT Research Institute - GIRI.

关键词： Fog

来源：评论

学校读者我要写书评

暂无评论

Interoperability and Standardization in the Internet of Things

Interoperability and Standardization in the Internet of Thin...

引用

International Conference on science Technology Engineering and Management (ICONSTEM)

作者： Ravi Kumar Saidala Haseeb V V G. Padmapriya Jayabalan S V. Kalai Priya Anwar Ahamed Shaikh Department of Computer Science Engineering Alliance University Bangalore Karnataka India Department of Computer Science NAM College Kallikkandy Kerala Tamil Nadu India Department of Computing Technologies School of Computing SRM Institute of Science and Technology Chennai Tamil Nadu India Department of Computer Science and Business System Panimalar Engineering College Chennai Tamil Nadu India Department of Computer Science and Engineering RMK college of Engineering and Technology Puduvoyal India Department of Computer Science and Engineering KoneruLakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

This research highlights the importance of standards and interoperability in the IoT. An essential component of IoT ecosystems is interoperability, which refers to the ability for various systems and devices to converse and share data. Formats for data, methods of communication, and safeguards are all outlined by standards. Widespread adoption and scalability are made possible through interoperability and standards, which allow devices from many manufacturers to communicate with one another. This research investigates the alliances, regulatory authorities, and commercial associations that cooperate in the creation and advancement of open standards that can be embraced by other entities. The main objective of the research is to showcase the construction of an Internet of Things device capable of communicating with various embedded peripheral protocols utilizing Plug and Play (PnP) technology. Moreover, the research examines the impact of regulatory frameworks on the IoT ecosystem and their role in fostering interoperability. An IoT ecosystem necessitates a standardized and open environment to provide optimal performance in terms of connectivity, data exchange, and innovation. This research contributes to the progress of harmonizing and achieving interoperability among World Wide Web Things.

关键词： Technological innovation Protocols Scalability Ecosystems Internet of Things Web sites Interoperability

来源：评论

学校读者我要写书评

暂无评论

Machine learning based Collaborative Intelligent Closing Gap between Graduates and Labour Market Framework

Machine learning based Collaborative Intelligent Closing Gap...

引用

2021 International Conference on Artificial Intelligence and Smart systems, ICAIS 2021

作者： Yafooz, Wael M.S. Hezzam, Essa Abdullah Emara, Abdel-Hamid Mohamed Taibah University College of Computer Science and Engineering Department of Computer Science Medinah Saudi Arabia Al-Azhar Uiversity Department of Computer and System Engineering Medinah Saudi Arabia

ISBN: (纸本)9781728195377

Unemployment of college graduates is a major issue in many countries throughout the world. Nevertheless, rapid economic growth in many fields requires graduates with specialized skills, particularly in the Gulf region and especially in the Kingdom of Saudi Arabia, which has two main projects, Saudi Vision 2030 and NEOM. Such projects need graduates equipped with skills and experience to cope with economic growth, digital transformation, technological advancements, and future needs. Therefore, Saudi Vision is focusing on the second pillar of Saudi Vision 2030: creating a thriving economy to increase employment and reduce the unemployment rate from 11.6% to 7%. Some studies have sought to highlight or to solve graduate unemployment problems using traditional methods. Even though many of them are time-consuming and endeavouring, the outcome received is exceedingly faint. Hence, this study utilizes information technology to build a framework called Collaborative Intelligent computer study Graduates and Labour Market Framework (CICCLM). CICCLM uses a machine learning approach and data science methods to identify the weaknesses to close the gap between university computing graduates and employer expectations through an analysis of the labour market requirements aligning them to the graduates 'capabilities. Furthermore, CICCLM provides recommendations and visualization platform about the mismatch between academic education and industry requirements. Additionally, CICCLM provides recommendations to update the curriculum and course plan, while providing training courses for old graduate students. © 2021 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Feature Selection with Stacked Autoencoder Based Intrusion Detection in Drones Environment

引用

computers, Materials & Continua 2022年第12期73卷 5441-5458页

作者： Heba G.Mohamed Saud S.Alotaibi Majdy M.Eltahir Heba Mohsen Manar Ahmed Hamza Abu Sarwar Zamani Ishfaq Yaseen Abdelwahed Motwakel Department of Electrical Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia

The Internet of Drones(IoD)offers synchronized access to organized airspace for Unmanned Aerial Vehicles(known as drones).The availability of inexpensive sensors,processors,and wireless communication makes it possible in real time *** several applications comprise IoD in real time environment,significant interest has been received by research *** IoD operates in wireless environment,it is needed to design effective intrusion detection system(IDS)to resolve security issues in the IoD *** article introduces ametaheuristics feature selection with optimal stacked autoencoder based intrusion detection(MFSOSAEID)in the IoD *** major intention of the MFSOSAE-ID technique is to identify the occurrence of intrusions in the IoD *** do so,the proposed MFSOSAE-ID technique firstly pre-processes the input data into a compatible *** addition,the presented MFSOSAEID technique designs a moth flame optimization based feature selection(MFOFS)technique to elect appropriate ***,firefly algorithm(FFA)with stacked autoencoder(SAE)model is employed for the recognition and classification of intrusions in which the SAE parameters are optimally tuned with utilize of *** performance validation of the MFSOSAE-ID model was tested utilizing benchmark dataset and the outcomes implied the promising performance of the MFSOSAE-ID model over other techniques with maximum accuracy of 99.72%.

关键词： Internet of drones unmanned aerial vehicles security intrusion detection machine learning

来源：评论

学校读者我要写书评

暂无评论

Ensemble Learning for Fetal Health Classification

引用

computer systems science & Engineering 2023年第10期47卷 823-842页

作者： Mesfer Al Duhayyim Sidra Abbas Abdullah Al Hejaili Natalia Kryvinska Ahmad Almadhor Huma Mughal Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz University Al-Kharj16273Saudi Arabia Department of Computer Science COMSATS UniversityIslamabad53000Pakistan Faculty of Computers&Information Technology Computer Science DepartmentUniversity of TabukTabuk71491Saudi Arabia Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySakaka72388Saudi Arabia Information Systems Department Faculty of Management Comenius University in BratislavaOdbojárov 1082005 Bratislava 25Slovakia Department of Computer Science Kinnaird College for WomenLahore54000Pakistan

Cardiotocography(CTG)represents the fetus’s health inside the womb during ***,assessment of its readings can be a highly subjective process depending on the expertise of the *** signals from fetal monitors acquire parameters(i.e.,fetal heart rate,contractions,acceleration).Objective:This paper aims to classify the CTG readings containing imbalanced healthy,suspected,and pathological fetus ***:We perform two sets of ***,we employ five classifiers:Random Forest(RF),Adaptive Boosting(AdaBoost),Categorical Boosting(CatBoost),Extreme Gradient Boosting(XGBoost),and Light Gradient Boosting Machine(LGBM)without over-sampling to classify CTG readings into three categories:healthy,suspected,and ***,we employ an ensemble of the above-described classifiers with the *** use a random over-sampling technique to balance CTG records to train the ensemble *** use 3602 CTG readings to train the ensemble classifiers and 1201 records to evaluate *** outcomes of these classifiers are then fed into the soft voting classifier to obtain the most accurate ***:Each classifier evaluates accuracy,Precision,Recall,F1-scores,and Area Under the Receiver Operating Curve(AUROC)*** reveal that the XGBoost,LGBM,and CatBoost classifiers yielded 99%***:Using ensemble classifiers over a balanced CTG dataset improves the detection accuracy compared to the previous studies and our first experiment.A soft voting classifier then eliminates the weakness of one individual classifier to yield superior performance of the overall model.

关键词： Fetal health cardiotocography(CTG) ensemble learning adaptive boosting(AdaBoost) voting classifier

来源：评论

学校读者我要写书评

暂无评论

Hybrid Power Generation Forecasting Using an Intellectual Evolutionary Energy-Preserve Rate Clustering Technique 1

引用

10th International Conference on Innovations in computer science and Engineering, ICICSE 2022

作者： Webber, Julian L. Jayagopal, Vellingiri Mehbodniya, Abolfazl Sengan, Sudhakar Velayutham, Priya Rangasamy, Rajasekar Stalin David, D. Doha Kuwait Department of Software & System Engineering School of Information Technology & Engineering Vellore Institute of Technology Tamil Nadu Vellore632014 India Department of Computer Science and Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli627152 India Department of Computer Science and Engineering Paavai Engineering College Tamil Nadu Namakkal637018 India Department of Computer Science and Engineering GITAM School of Technology GITAM University Karnataka Bengaluru561203 India Department of Information Technology Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College Tamil Nadu Chennai600072 India

ISBN: (数字)9789811974557

ISBN: (纸本)9789811974540

The significant growth of Wind Power (WP) has significant challenges due to the inconsistency and uncertainty of Wind Power Generation (WPG) to ensure the power system. Solar energy and WP calculation are great ways to overcome the problem. Mainly voltage and frequency fluctuations and harmonics have a high impact on the power generation and distribution system;in any high case, the power quality of grid systems is reduced. This can be primarily solved with proper design, advanced rapid response control facilities and optimization of power systems. A new type of Multi-term Wind Energy (WE) with an IEEE 30 bus forecasting system based on digital weather forecasting and error modification methods is presented. From the Evolutionary Energy- Preserve Rate Clustering (EEPRC) Technique-based technique for the evaluates the probability ratio in Solar and wind error energy prediction, the error assessment model is proposed, which has the advantage of estimating from real wind farms and statistical Weather Forecast (WF) data and has proven to be a nominal method for improving the predictive accuracy of Multi-term WPG. The primary step of the Energy-Preserve Rate Clustering (EPRC) method is to calculate the uncertainty of real-time data with the predicted value. The computed values are helpful for the increases in Solar WPG production. The proposed wind forecasting system is utilized in the Coastal area-based energy generation. Also, it has been demonstrated that wind speed and WPG with its probability ratio have been evaluated with the EEPRC-based forecasting method, especially for its powerful predictive capability for the complex properties of the controller function. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Solar energy

来源：评论

学校读者我要写书评

暂无评论

Diverse Approaches Have Been Presented To Mitigate SQL Injection Attack, But It Is Still Alive: A Review 4

Diverse Approaches Have Been Presented To Mitigate SQL Injec...

引用

4th International Conference on computer and Applications, ICCA 2022

作者： Qbea'h, Mohammad Alrabaee, Saed Alshraideh, Mohammad Sabri, Khair Eddin College of It United Arab Emirates University Department of Information System and Security Al Ain United Arab Emirates The University of Jordan Computer Science Department Amman Jordan

ISBN: (纸本)9781665452946

A huge amount of stored and transferred data is expanding rapidly. Therefore, managing and securing the big volume of diverse applications should have a high priority. However, Structured Query Language Injection Attack (SQLIA) is one of the most common dangerous threats in the world. Therefore, a large number of approaches and models have been presented to mitigate, detect or prevent SQL injection attack but it is still alive. Most of old and current models are created based on static, dynamic, hybrid or machine learning techniques. However, SQL injection attack still represents the highest risk in the trend of web application security risks based on several recent studies in 2021. In this paper, we present a review of the latest research dealing with SQL injection attack and its types, and demonstrating several types of most recent and current techniques, models and approaches which are used in mitigating, detecting or preventing this type of dangerous attack. Then, we explain the weaknesses and highlight the critical points missing in these techniques. As a result, we still need more efforts to make a real, novel and comprehensive solution to be able to cover all kinds of malicious SQL commands. At the end, we provide significant guidelines to follow in order to mitigate such kind of attack, and we strongly believe that these tips will help developers, decision makers, researchers and even governments to innovate solutions in the future research to stop SQLIA. © 2022 IEEE.

关键词： Cybersecurity

来源：评论

学校读者我要写书评

暂无评论

Machine Learning-Enabled Power Scheduling in IoT-Based Smart Cities

引用

computers, Materials & Continua 2021年第5期67卷 2449-2462页

作者： Nabeela Awan Salman Khan Mohammad Khalid Imam Rahmani Muhammad Tahir Nur Alam MD Ryan Alturki Ihsan Ullah Department of Computer Science Government Girls Degree College MardanKPK23200Pakistan Department of Electrical Energy System UETPeshawar25000Pakistan Department of Computer Science College of Computing and InformaticsSaudi Electronic UniversityKSA Department of Smart Computing Kyungdong UniversityGlobal CampusGosung24764South Korea Department of Information Sciences College of Computer and Information SystemsUmm Al-Qura UniversityMakkahSaudi Arabia Robotics Engineering Daegu Gyeongbuk Institute of Science and TechnologySouth Korea

Recent advancements in hardware and communication technologies have enabled worldwide interconnection using the internet of things(IoT).The IoT is the backbone of smart city applications such as smart grids and green energy *** smart cities,the IoT devices are used for linking power,price,energy,and demand information for smart homes and home energy management(HEM)in the smart *** complex smart gridconnected systems,power scheduling and secure dispatch of information are the main research *** challenges can be resolved through various machine learning techniques and data *** this paper,we have proposed a particle swarm optimization based machine learning algorithm known as a collaborative execute-before-after dependency-based requirement,for the smart *** proposed collaborative execute-before-after dependencybased requirement algorithm works in two phases,analysis and assessment of the requirements of end-users and power distribution *** the rst phases,a xed load is adjusted over a period of 24 h,and in the second phase,a randomly produced population load for 90 days is evaluated using particle swarm *** simulation results demonstrate that the proposed algorithm performed better in terms of percentage cost reduction,peak to average ratio,and power variance mean ratio than particle swarm optimization and inclined block rate.

关键词： PSO IBR machine learning IoT smart cities CDBR

来源：评论

学校读者我要写书评

暂无评论

The impact of Routing Protocols and topologies on IOT Based systems 2

The impact of Routing Protocols and topologies on IOT Based ...

引用

2nd International Conference of Modern Applications on Information and Communication Technology, ICMAICT 2020

作者： Hameed, Saif Saad Saleh, Hadeel Mohammed University of Anbar College of Computer Science and Information Technology Department of Computer Networking System Iraq University of Anbar College of Pharmacy Iraq

Routing protocols is a mechanism of detecting best route path from single node to multiple nodes or signal node in order to transfer data between network and it specify how routing techniques in routers communicate between routers to accomplish communication tasks. A simulation was done to compare some protocols such as ""RIP"", ""OSPF""and "EIGRB' to determine the best routing protocol at a specific given network topology for IoT applications. The main problem there is a different routing protocols was developed each has its performance among different IoT applications. As well a simulation was required to detect the perfect routing protocol required for IoT applications. In this project a simulation of "IoT"network that serve the "IoT"applications using different routing protocols such as ""RIP"", ""OSPF"' and "EIGRB"and an evaluation to the performance of each routing technique was to decide which is the best routing for "IoT"applications. Opnet modular was used to implement the simulation and it is found that the ""IGRP""has the fastest router convergence among the three protocols we are testing. © Published under licence by IOP Publishing Ltd.

关键词： Routing protocols

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：