检索结果-内蒙古大学图书馆

22nd IEEE/ACIS International Conference on software engineering Research, Management and Applications, SERA 2024

作者： Ghosh, Partha Charit, Arnab Banerjee, Hindol Bandhu, Debanwesa Ghosh, Agniv Pal, Ankita Goto, Takaaki Sen, Soumya Academy of Technology Department of Computer Science and Engineering Adisaptagram India Toyo University Faculty of Information Sciences and Arts Saitama Japan A.K.Choudhury School of Information Technology University of Calcutta Kolkata India

ISBN: (纸本)9798350391343

Addressing the persistent challenge of student dropout, particularly prevalent in developing countries like India, Bangladesh, etc. are of paramount importance. Factors such as poverty, natural calamities, and early marriages exacerbate this issue. High student dropout rates can negatively impact a country by diminishing its economic productivity, increasing social inequalities, and perpetuating a cycle of poverty. Addressing dropout issues requires comprehensive strategies to ensure a skilled and educated workforce, fostering societal well-being and global competitiveness. This research focuses on analysing comprehensive data on students who have dropped out. Thereafter, a machine learning based methodology is used to discern the underlying causes of student attrition in various schools. Furthermore, it allows for efficient monitoring of the state's educational landscape, with the ability to drill down to granular levels when necessary to identify specific regional challenges. The effectiveness of this approach is validated through the utilization of real-world datasets. © 2024 IEEE.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Primary User-Awareness-Based Energy-Efficient Duty-Cycle Scheme in Cognitive Radio Networks

引用

computers, Materials & Continua 2022年第3期70卷 5991-6005页

作者： Zilong Jin Chengbo Zhang Kan Yao Dun Cao Seokhoon Kim Yuanfeng Jin School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)Nanjing University of Information Science and Technology Nanjing210044China Jiangsu Institute of Economic and Information Technology Nanjing210003China School of Computer and Communications Engineering Changsha University of Science and TechnologyChangsha410114China Department of Computer Software Engineering Soonchunhyang UniversityAsan31538Rep.of Korea Department of Mathematics Yanbian UniversityYanji133002China

Cognitive radio devices can utilize the licensed channels in an opportunistic manner to solve the spectrum scarcity issue occurring in the unlicensed ***,these cognitive radio devices(secondary users)are greatly affected by the original users(primary users)of licensed *** users have to adjust operation parameters frequently to adapt to the dynamic network environment,which causes extra energy *** consumption can be reduced by predicting the future activity of primary ***,the traditional prediction-based algorithms require large historical data to achieve a satisfying precision accuracy which will consume a lot of time and memory ***,many of these schemes lack methods to deal with the very busy network *** this paper,one semi-supervised learning algorithm,i.e.,tri-training,has been employed to investigate the prediction of primary *** on the prediction results of tri-training,a duty-cycle mechanism and an intermediate node selection approach are proposed to improve the energy *** results show the effectiveness of the proposed algorithm.

关键词： Cognitive radio tri-training duty-cycle intermediate node energy efficiency

来源：评论

学校读者我要写书评

暂无评论

Deep Forest-Based Fall Detection in Internet of Medical Things Environment

引用

computer Systems science & engineering 2023年第6期45卷 2377-2389页

作者： Mohamed Esmail Karar Omar Reyad Hazem Ibrahim Shehata College of Computing and Information Technology Shaqra UniversityP.O.Box 33Shaqra11961Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Computer Science Department Faculty of Computers and Artificial IntelligenceSohag UniversitySohag82524Egypt Department of Computer and Systems Engineering Faculty of EngineeringZagazig UniversityZagazig44519Egypt

This article introduces a new medical internet of things(IoT)framework for intelligent fall detection system of senior people based on our proposed deep forest *** cascade multi-layer structure of deep forest classifier allows to generate new features at each level with minimal hyperparameters compared to deep neural ***,the optimal number of the deep forest layers is automatically estimated based on the early stopping criteria of validation accuracy value at each generated *** suggested forest classifier was successfully tested and evaluated using a public SmartFall dataset,which is acquired from three-axis accelerometer in a *** includes 92781 training samples and 91025 testing samples with two labeled classes,namely non-fall and *** results of our deep forest classifier demonstrated a superior performance with the best accuracy score of 98.0%compared to three machine learning models,i.e.,K-nearest neighbors,decision trees and traditional random forest,and two deep learning models,which are dense neural networks and convolutional neural *** considering security and privacy aspects in the future work,our proposed medical IoT framework for fall detection of old people is valid for real-time healthcare application deployment.

关键词： Elderly population fall detection wireless sensor networks internet of medical things deep forest

来源：评论

学校读者我要写书评

暂无评论

Designing an Attribute-Based Encryption Scheme with an Enhanced Anonymity Model for Privacy Protection in E-Health

引用

SN computer science 2024年第2期5卷 203页

作者： Zala, Kirtirajsinh Thakkar, Hiren Kumar Dholakia, Neel Shukla, Madhu Thumar, Deep Department of Information Technology Marwadi University Gujarat Rajkot 360006 India Department of Computer Science and Engineering School of Technology Pandit Deendayal Energy University Gujarat Gandhinagar 382007 India Department of Computer Engineering Marwadi University Gujarat Rajkot 360006 India Faculty of Engineering Marwadi Education Foundations Gujarat Rajkot 360006 India

The medical field and the health care industry generate large volumes of data that are ultimately beneficial to society. Yet, the exposure of sensitive aspects might jeopardize this data generation. Exposure to Healthcare information made available via the internet with the intention of benefiting healthcare professionals presents a challenge for researchers in terms of privacy and security concerns. This access is intended to benefit the medical community. With growing technology, medical data on the cloud are subject to unanticipated dangers, and the threat landscape appears resilient with sensitive qualities. Organizations fail to keep their reputations and are unable to maintain public trust in our modern day. The severity of advanced security threats compromises patient data privacy and healthcare unit security. Many studies and practitioners’ fruitful approaches gave up healing resolutions, but the requirement for a perfect solution remains unsatisfactory. In this research, we provide a solution for dealing with security challenges in healthcare administration. We present a hybrid system that combines sensitive attribute access primitives with enhanced attribute-based encryption and anonymity methods. The proposed approach electronic health records design model is closely linked with the proposed approach and system scenario, forming a comprehensive blueprint for our healthcare technology solution. In terms of completion time when user instance is upto 500, the practical flexible ABE instances method outperforms the other approaches such as real-time operational data base extraction–transformation–loading, and long short-term memory to recurrent neural network by a significant margin. This method offers the quick encryption (7.5 s), decryption (5.4 s), and reduced memory usage (5361 s). A cloud sim simulator is used to evaluate the proposed mechanism’s performance, encryption, decryption, and memory usage. The latest model with better hardware and software opt

关键词： Anonymity Attribute-based encryption (ABE) Cloud computing E-health Privacy Secure hash algorithm (SHA-1)

来源：评论

学校读者我要写书评

暂无评论

Weak and Extremely Low Frequency Magnetic Fields Alter the Growth Rates of HT-1080 Fibrosarcoma

Weak and Extremely Low Frequency Magnetic Fields Alter the G...

引用

2025 United States National Committee of URSI National Radio science Meeting, USNC-URSI NRSM 2025

作者： Dang, Nhat Keller, Jason Bajtos, Marek Gurhan, Hakki Barnes, Frank Department of Electrical Computer and Energy Engineering College of Engineering and Applied Science University of Colorado Boulder BoulderCO United States Department of Electromagnetics and Biomedical Engineering Faculty of Electrical Engineering and Information Technology University of Zilina Zilina Slovakia

ISBN: (纸本)9781946815200

This study presents experimental results showing that weak, extremely low frequency electromagnetic (EM) fields influence the growth rates of HT-1080 fibrosarcoma cells in vitro and offers a theoretical explanation for these effects. The results demonstrate that weak magnetic fields both increase and decrease the growth rates of fibrosarcoma cells by altering the mitochondrial superoxide (O2-) and calcium ions (Ca2+) concentrations in living cells. Over a 4-day exposure period, fibrosarcoma growth rates were modulated in the presence of low-level alternating current (AC) magnetic fields at a 10 μT amplitude at 13.5 Hz to 30 Hz frequency, superimposed on a 45 μT static background field. Effects due to changes in amplitude from 10 to 30 μT at selected frequencies are also investigated with the same superimposed static field. © 2025 USNC-URSI.

关键词： Electromagnetic field effects

来源：评论

学校读者我要写书评

暂无评论

Intelligent Systems for Medical Diagnostics with the Detection of Diabetic Retinopathy at Reduced Entropy

Intelligent Systems for Medical Diagnostics with the Detecti...

引用

2023 IEEE International Conference on Network, Multimedia and information technology, NMITCON 2023

作者： Sindhu Madhuri, G. Somashekhara Reddy, D. Mahesh, T.R. Rajan, T. Vanitha, K. Shashikala, H.K. Manipal Institute of Technology Manipal Academy of Higher Education Department of Information Technology Karnataka Bengaluru India Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India School of Computer Science and Engineering Presidency University Bangalore India Karpagam Academy of Higher Education Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350300826

Diabetes Mellitus (DM) is primarily defined by hyperglycemia, polyuria, and polyphagia and as a result of a complex interaction of hereditary and environmental variables, it has developed into a severechronic metabolic condition. Numerous diabetes problems might arise from uncontrolled high blood sugar. Long-term diabetes causes severe complications, some of which are fatal. Everywhere in the world, the prevalence of diabetes in patients is increasing at epidemic rates. Every year, diabetes and related disorders consume a sizable percentage of the national health budget. Several risk factors influence the etiopathogenesis of the disease and the emergence of the epidemic. The untreatable condition of diabetes may be managed by maintaining self-care in daily life, providing appropriate education about diabetes, and making significant advancements in knowledge, attitudes, skills, and management. Diabetes should be diagnosed as soon as possible because it can lead to several illnesses, including kidney failure, stroke, blindness, heart attacks, and lower limb amputation. This study aims to use relevant variables, create a prediction algorithm using machine learning, and choose the best classifier to produce results that are as close to clinical outcomes as possible with reduced entropy. The proposed approach is on selecting the characteristics that ail in the early detection of Diabetes Miletus utilizing Predictive analysis. The computational techniques K-Nearest Neighbour (KNN) and Decision Tree (DT) have been employed to detect DM at an early stage. The KNN outperforms with the best performance when evaluated against different performance metrics. © 2023 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Expert System for Kubernetes Cluster Autoscaling and Resource Management 4

Expert System for Kubernetes Cluster Autoscaling and Resourc...

引用

4th International Conference on Advancements in Computing, ICAC 2022

作者： Hettiarachchi, Lasal Sandeepa Jayadeva, Senura Vihan Bandara, Rusiru Abhisheak Vikum Palliyaguruge, Dilmi Samaratunge Arachchillage, Udara Srimath S. Kasthurirathna, Dharshana Department of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Sri Lanka

ISBN: (纸本)9798350398090

The importance of orchestration tools such as Kubernetes has become paramount with the popularity of software architectural styles such as microservices. Furthermore, advancements in containerization technologies such as Docker has also played a vital role when it comes to advancements in the field of DevOps, enabling developers and system engineers to deploy are manage applications much more effectively. However, infrastructure configuration and management of resources are still challenging due to the disjointed nature of the infrastructure and resource management tools' failure to comprehend the deployed applications and create a holistic view of the services. This is partly due to the extensive knowledge required to operate these tools or due to the inability to perform specific tasks. As a result, multiple tools and platforms need to configure together to automate the deployment, monitoring and management processes to provide the optimal deployment strategy for the applications. In response to this issue, this research proposes an expert system that creates a centralized approach to cluster autoscaling and resource management, which also provides an automated low-latency container management system and resiliency evaluation for dynamic systems. Furthermore, the time series load prediction is done using a BiLSTM and periodically creates an optimized autoscaling policy for cluster performance, thus creating a seamless pipeline from deployment, monitoring scaling, and troubleshooting of distributed applications based on Kubernetes. © 2022 IEEE.

关键词： Expert systems

来源：评论

学校读者我要写书评

暂无评论

Real Estate Management via a Decentralized Blockchain Platform

引用

computers, Materials & Continua 2021年第2期66卷 1813-1822页

作者： Iftikhar Ahmad Mohammed AAlqarni Abdulwahab Ali Almazroi Laiba Alam Department of Computer Science and Information Technology University of Engineering and TechnologyPeshawarPakistan Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of Information Technology College of Computing and Information Technology at KhulaisUniversity of JeddahJeddahSaudi Arabia

Blockchain technology is one of the key technological breakthroughs of the last *** has the ability to revolutionize numerous aspects of society,including financial systems,healthcare,e-government and many *** such area that is able to reap the benefits of blockchain technology is the real estate *** many other industries,real estate faces major administrative problems such as high transaction fees,a lack of transparency,fraud and the effects of a middleman including undue influence and *** enables supporting technologies to overcome the obstacles inherent within the real estate investment *** technologies include smart contracts,immutable record management and time-stamped *** utilize these key properties of blockchain technology in our work by proposing a system that has the ability to record real estate transactions in a private blockchain,using smart *** immutability of the blockchain ledger and transactions can provide a safe space for the real estate *** technology can also assist the authentication process by hastening background *** digital keys are provided to parties that are involved in a contract,thus minimizing the risk of *** also discuss the rationale behind the advantages of using a blockchain in this manner,and how we selected the consensus mechanism for our proposed system.

关键词： Blockchain real estate smart contracts

来源：评论

学校读者我要写书评

暂无评论

Early Prediction and Diagnosis Cardiovascular Disease Using Deep Learning Models

Early Prediction and Diagnosis Cardiovascular Disease Using ...

引用

2024 IEEE International Conference on Emerging Technologies in computer science for Interdisciplinary Applications, ICETCS 2024

作者： Rani, Rudra Yamini Prasad, Mudarakola Lakshmi Reddy, Induru Sunnihith Tayubi, Iftikhar Aslam Sultan, Ghazala Reddy, Pundru Chandra Shaker VNR Vignana Jyothi Institute of Engineering and Technology Department of Information Technology Telangana Hyderabad India Computer Science and Engineering Institute of Aeronautical Engineering Telangana Dundigal India Computer Science and Business Systems RMK Engineering College Tamilnadu Tiruvallur India King Abdulaziz University Faculty of Computing and Information Technology Rabigh Jeddah Saudi Arabia Aligarh Muslim University Department of Computer Science Uttar Pradesh Aligarh India SR University School of Computer Science and Artificial Intelligence Telangana Warangal506371 India

ISBN: (纸本)9798350372502

Cardiovascular disease (CVD) risk assessment and prognosis in otherwise healthy people is an important part of disease management. Early detection and diagnosis of CVD, supported by the extensive health data on the condition already stored in hospital systems, has the ability to greatly improve disease outcomes. Clinical practice for the management of Cardiovascular Diseases (CVDs) stands to benefit greatly from the use of machine learning approaches. Patients and the healthcare system can save money thanks to these methods, which can be used to create evidence-based clinical guidelines and management algorithms. This will cut down on expensive and time-consuming clinical and laboratory examinations. This study suggests creating new deep learning algorithms that can automatically identify important variables and detect early-stage heart disease;these algorithms should be resilient, effective, efficient, and unique in order to improve early anticipation and interference for CVDs. An F1-score of around 89% is produced by the suggested Catboost model. Hence, it outperformed numerous other state-of-the-art methods by maximizing classification efficiency with better correctness and precision. © 2024 IEEE.

关键词： Hospitals

来源：评论

学校读者我要写书评

暂无评论

Secure Audio Transmission Over Wireless Uncorrelated Rayleigh Fading Channel

引用

computers, Materials & Continua 2022年第1期70卷 1603-1615页

作者： Osama S.Faragallah M.Farouk Hala S.El-sayed Mohsen A.M.El-bendary Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Computer Science and Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electrical Engineering Faculty of EngineeringMenoufia UniversityShebin El-Kom32511Egypt Department of Electronics Technology Faculty of Technology and EducationHelwan UniversityCairoEgypt

Audio communications and computer networking play essential roles in our daily lives,including many domains with different *** in these technologies are *** consequence,there is a dire need to secure these technologies up to *** paper presents an efficient model for secure audio signal transmission over the wireless noisy uncorrelated Rayleigh fading ***,the performance of the utilized multiple secret keys-based audio cryptosystem is analyzed in different transformation *** discrete cosine transform(DCT),the discrete sine transform(DST),and the discrete wavelet transform(DWT)are investigated in the utilizedmultiple secret key-based audio *** results show consistent results with the wireless noisy *** performance of the proposed multiple secret keys-based audio cryptosystem can be ranked concerning the employed domain as DWT,DCT,and DST transform *** simulation experiments proved that the presented multiple secret keysbased audio cryptosystemfor audio signals transmitted over the wireless noisy uncorrelatedRayleigh fading channel achieves reliable and secure wireless link utilizing combined multi security layers.

关键词： Audio communications encryption uncorrelated Rayleigh fading channel

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：