检索结果-内蒙古大学图书馆

Cultivating Expertise: Unravelling Type 2 Diabetes Associations through Incremental Knowledge-Based System Development: Ripple Down Rules or Machine Learning 44

Cultivating Expertise: Unravelling Type 2 Diabetes Associati...

引用

44th International Conference on Information Systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023

作者： Omar, Adel Beydoun, Ghassan Win, Khin Shukla, Nagesh Jelinek, Herbert F. Elias, Hector School of Systems Management and Leadership University of Technology Sydney Sydney Australia School of Computing and Information Technology Wollongong University Wollongong Australia Department of Business Strategy Innovation Griffith University Griffith Australia Department of Biomedical Engineering Khalifa University of Science and Technology Abu Dhabi United Arab Emirates Wollongong University College Wollongong University Wollongong Australia

ISBN: (纸本)9781713893622

Type 2 diabetes is a chronic disease that is caused by a combination of genetic and environmental factors, with social determinants playing a significant role. These social determinants include but not limited to factors such as education level, occupation, family history, ethnicity and place of residence etc. The prevalence of Type 2 diabetes (T2D) necessitates inventive management strategies. This study explores the potential of utilizing Ripple Down Rules (RDR) in comparison with Machine Learning (ML) approaches for the incremental development of a Knowledge-Based System (KBS). The aim is to create a robust Decision Support System (DSS) for effective T2D management, focusing on the dynamic influence of evolving social determinants. The research outcomes substantiate the viability of this approach. The KBS, fortified by RDRs, demonstrated notable performance metrics. Specifically, the system achieved an impressive accuracy rate of 90.2%, accompanied by a specificity of 96.9%. The sensitivity, crucial for identifying potential T2D cases, reached 73.6%, indicating the system's proficiency in recognizing diverse instances. Copyright © 2023 Omar, Beydoun, Win, Shukla, Jelinek and Elias.

关键词： Decision support systems

来源：评论

学校读者我要写书评

暂无评论

A Study of Cryptographic Primitives in the context of Blockchain's Data Integrity and Privacy 11

A Study of Cryptographic Primitives in the context of Blockc...

引用

11th International Conference on System Modeling and Advancement in Research Trends, SMART 2022

作者： Singh, Ramveer Pooja Agarwal, Ambuj Kumar Naaz, Rohaila Kumar, Raj Vijay, Richa Greater Noida Institute of Professional Studies Greater Noida India School of Engineering and Technology Ct University Ludhiana India School of Engineering and Technology Sharda University Department of Computer Science and Engineering Greater Noida India Teerthanker Mahaveer University Faculty of Engineering and Computing Sciences Moradabad India Department of Computer Applications Faridabad India

ISBN: (纸本)9781665487320

In Today's World, Blockchain is a promising technology in all areas;things have also been drastically changed after COVID-19;challenges surfaced for implementing blockchain technology in the context of its computational complexity and security. After invention of it in 2008, cryptocurrency applications, i.e., Bitcoin it also getting introduced in Different applications. One of the Major Building blocks of Blockchain is Cryptography techniques. This paper discusses Cryptographic primitives used in different phases of Blockchain implementation and the challenges of implementing these cryptographic primitives. Bitcoin uses Cryptographic primitives to generate public-private key pairs and mining, while Ethereum uses Elliptic curve cryptography to create public-private keys and digital signatures. This paper divided uses of cryptographic primitives into three categories used in Blockchains, i.e., key generation Hashes, signature generation hashes, and proof hashes. © 2022 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Multi-Layer Perceptron Regression Model for Material Characterization in the Microwave Frequency Range with Cross-Dataset Validation 7

Multi-Layer Perceptron Regression Model for Material Charact...

引用

7th International Youth Conference on Radio Electronics, Electrical and Power engineering, REEPE 2025

作者： Hanima Kannan, C.H. Gupta, Deepa Mathur, Parul Kurup, Dhanesh G. Chaudhari, Tilesh Sanjay Mathur, Priyanka Amrita School of Engineering Amrita Vishwa Vidyapeetham Rf and Wireless Systems Laboratory Department of Electronics and Communication Engineering Bengaluru India Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India Indian Institute of Technology Creative and Advanced Research Based on Nanomaterials Laboratory Department of Chemical Engineering Hyderabad India School of Engineering and Applied Science Bennett University U.P. Greater Noida India

ISBN: (纸本)9798331531836

This paper presents a Multi-Layer Perceptron (MLP) based regression model for characterizing materials at micrwave frequency range. A mathematical model and experimental setup of the Open-Ended Coaxial Probe (OECP) sensor interacting with the material under test (MUT) generate a cross-dataset to validate the MLP regression model, utilizing the frequency-dependent complex dielectric constant for material characterization. This paper utilizes the frequency-dependent response of the OECP sensor (scattering parameters) as input features for the MLP model, while the complex dielectric constant of the MUT serves as the output feature. The optimized MLP model has an R2 of 99.991% and MSE of 6.65 × 10-5, with predictions closely aligning with literature values for standard loads such as distilled water, acetone, and ethanol, obtained using a commercially available dielectric assessment software kit. This cost-effective model enables precise dielectric property estimation, with future work extending to unknown materials, mixtures, and electrolyte solutions. © 2025 IEEE.

关键词： Linear regression

来源：评论

学校读者我要写书评

暂无评论

Improve the Network Security during the Implementation of IoT Application Using Data Encryption and Trustworthy Network

Improve the Network Security during the Implementation of Io...

引用

2023 IEEE World Conference on Communication and computing, WCONF 2023

作者： Tripathi, Neha Mishra, Amit Kumar Vaqur, Musheer Sharma, Sugandha Pandey, Neeraj Kumar Department of Computer Science & Engineering Uttarakhand Dehradun India Graphic Era Hill University Department of Computer Science & Engineering Uttarakhand Dehradun India Uttaranchal Institute of Technology Uttaranchal University Department of Computer Science & Engineering Uttarakhand Dehradun India UPES Bidholi School of Computer Science Uttarakhand Dehradun India DIT University School of Computing Uttarakhand Dehradun India

ISBN: (纸本)9798350311204

Internet of Things (IoT) has been explored in terms of its purpose, breadth, and actual use. As a result of this effort, the whole network is now safer. Many studies have looked at the security of the Internet of Things;however, the security measures used in those studies have had a negative impact on the network performance. That is why prior studies only looked at certain types of data. Previous research has been hindered by obstacles such as high error rates, sluggish speeds, and a large proportion of packets lost. The need for approaches that protect both text and visual content while using minimal system resources cannot be overstated. IoT solutions might tremendously benefit from this research. In today's Internet of Things (IoT) technologies, data compression and security are routinely necessary. When using this hybrid strategy, transmission is more reliable and error-free. This sort of research might benefit IoT-based systems, such as healthcare and the commercial sector. Research on IoT and network security via encryption is essential. Investigate the security implementation issues of the IoT network such as the speed, accuracy, and latency of the Internet of Things more deeply. Such research should concentrate on merging compression and encryption approaches to offer high-performance and trustworthy network security for IoTs by solving security problems in the IoT network. This new approach of network security should be safer and more efficient than the current one. Data is protected from hackers by a unique security technique. © 2023 IEEE.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

Thermally Evaporated ZnSe for Efficient and Stable Regular/Inverted Perovskite Solar Cells by Enhanced Electron Extraction

引用

Energy & Environmental Materials 2023年第5期6卷 440-448页

作者： Xin Li Guibin Shen Xin Ren Ng Zhiyong Liu Yun Meng Yongwei Zhang Cheng Mu Zhi Gen Yu Fen Lin Solar Energy Research Institute of Singapore(SERIS) National University of SingaporeSingapore 117574Singapore Key Laboratory of Advanced Light Conversion Materials and Biophotonics Department of ChemistryRenmin University of ChinaBeijing 100872China State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China School of Materials Science and Engineering Nanyang Technological UniversitySingapore 639798Singapore Shandong Provincial Engineering and Technical Center of Light Manipulation and Shandong Provincial Key Laboratory of Optics and Photonic Devices School of Physics and ElectronicsShandong Normal UniversityJinan 250014China Institute of High Performance Computing A^(*)STARSingapore 138632Singapore

Electron transport layers(ETLs)are crucial for achieving efficient and stable planar perovskite solar cells(PSCs).Reports on versatile inorganic ETLs using a simple film fabrication method and applicability for both low-cost planar regular and inverted PSCs with excellent efficiencies(>22%)and high stability are very ***,we employ a novel inorganic ZnSe as ETL for both regular and inverted PSCs to improve the efficiency and stability using a simple thermal evaporation *** TiO_(2)-ZnSe-FAPbl_(3)heterojunction could be formed,resulting in an improved charge collection and a decreased carrier recombination further proved through theoretical *** optimized regular PSCs based on TiO_(2)/ZnSe have achieved 23.25%efficiency with negligible *** addition,the ZnSe ETL can also effectively replace the unstable bathocuproine(BCP)in inverted ***,the ZnSe-based inverted device realizes a champion efficiency of 22.54%.Moreover,the regular device comprising the TiO_(2)/ZnSe layers retains 92%of its initial PCE after 10:00 h under 1 Sun continuous illumination and the inverted device comprising the C_(60)/ZnSe layers maintains over 85%of its initial PCE at 85℃for 10:00 *** highlights one of the best results among universal ETLs in both regular and inverted perovskite photovoltaics.

关键词： high efficiency long-term stability planar regular/inverted perovskite solar cells thermal evaporation ZnSe electron transport layer

来源：评论

学校读者我要写书评

暂无评论

Business Intelligence System for Human Resource Management System

Business Intelligence System for Human Resource Management S...

引用

2022 International Conference on Emerging Trends in computing and engineering Applications, ETCEA 2022

作者： Fraihat, Salam Innab, Haneen Makhadmeh, Sharif Naser Al-Betar, Mohammed Azmi College of Engineering and Information Technology Ajman University Artificial Intelligence Research Center United Arab Emirates Princess Sumaya University for Technology King Hussein School of Computing Sciences Amman Jordan

ISBN: (纸本)9781665477093

Human Resources management system (HRMS) plays a crucial role in achieving an organization's financial and social objectives by supporting decision-making. Implementing new technologies for business data analysis becomes a top priority to assess and improve performance continuously. This paper proposes a complete Business Intelligence solution that targets workforce and absence management to fulfill customer needs by extracting data from multiple systems, transforming it into an appropriate format, and loading it into a data warehouse. Finally, a concise and interactive dashboard to help executives, HR analysts, and line managers to monitor everything at a glance is designed. © 2022 IEEE.

关键词： Data warehouses

来源：评论

学校读者我要写书评

暂无评论

Sentiment Analysis Model using Text and Emoticons for Pharmaceutical & Healthcare Industries 2

Sentiment Analysis Model using Text and Emoticons for Pharma...

引用

2nd International Conference on Innovative Sustainable Computational Technologies, CISCT 2022

作者： Bhaskaran, S. Veeramanickam, M.R.M. Hariharan, S. Bharathiraja, N. Pradeepa, K. Marappan, Raja Sastra Deemed University School of Computing Thanjavur India Chitkara University Chitkara University Institute of Engineering and Technology Punjab India Vardhaman College of Engineering Department of Computer Science and Engineering Hyderabad India St. Michael College of Engineering and Technology Department of Computer Science and Engineering India

ISBN: (纸本)9781665474160

Background: Nowadays, pharmaceutical and healthcare industries apply sentiment analysis (SA) to analyze customers' feedback on pharmaceutical products. SA uses natural language processing (NLP) to recognize, assess and analyze the pharmaceutical data to extract valuable insights about the sentiment it conveys. Over the past two decades, in addition to text, emoticons have become a conventional way of expressing one's sentiments. The researchers utilizing textual data for SA have largely ignored emoticons due to their complexity and insufficient resources. Aim of the study: Necessary to include emoticons in SA to capture the emotion expressed by pharmaceutical data. However, this research develops an algorithm that performs SA on text and emoticons. Methods: To highlight the significance of emoticons, the analysis has been conducted on text-only and text-and-emoticon data, using deep learning (DL) and machine learning (ML) methods on multiple datasets. The features - term frequency-inverse document frequency (TF-IDF), emoticon lexicons, and a bag of words (BoW) are taken for simulation. Results: Simulation of text features using BiLSTM provides better accuracy, between 85% and 90%, compared to other methods. The precision lies between 70% and 90%. The recall is lowered to 64%. The sentiment the emoticon conveys outweighs that of the text associated with it. In addition, the DL algorithms outperform the ML methods. The overall results indicate that considering emoticons along with text positively impacts ***, it is noted that the DL model marginally outperforms all of the ML algorithms used. Conclusions: This research analyzed the augmentations to the implementation, including multiple enhancements during the pre-processing stage, the inclusion of emojis, and the usage of a bi-long short-term memory network (BiLSTM) in the DL model. The experimental results conclude that better measures are obtained using the DL method. © 2022 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Netflix Stock Price Prediction Using LSTM Based RNN 1st

Netflix Stock Price Prediction Using LSTM Based RNN

引用

1st International Conference on Intelligent computing, Smart Communication, and Network Technologies, ICICSCNT 2023

作者： Mohamed Usman Ali, A. Madhi Perkin, T. Department of Computer Science Engineering Hindustan Institute of Technology and Science Chennai India School of Computing Sciences Department of Computer Science Engineering Hindustan Institute of Technology and Science Chennai India

ISBN: (纸本)9783031759567

Stock market forecast is a complex process on account of the clamorous, individual, complex and changeable character of the stock price occasion succession. Due to the growing number of consumers and new rules achieved apiece Netflix Corporation to stop giving passwords, the stock price of Netflix has existed unsteady currently. This project uses a Long Short-Term Memory (LSTM) model to think the stock price of Netflix. The LSTM model is a type of repeating interconnected system (RNN) that can efficiently capture worldly dependencies later succession dossier. Historical stock price data for Netflix is composed and pre-treated expected used as input for the LSTM model. The LSTM model is therefore prepared on the ancient dossier and proven on a grasped-beginning of dossier to judge allure predicting depiction. The results show that the LSTM model can efficiently envision the stock price of Netflix accompanying a large size of accuracy. This project explains the potential for utilizing LSTM models to forecast stock prices and supplies valuable observations for financiers curious in Netflix’s stock. Using LSTM located RNN, the model has the thought of the earlier dossier and can efficiently deceive new data to envision correct results for the active data. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Costs

来源：评论

学校读者我要写书评

暂无评论

CVchain: A Cross-Voting-Based Low Latency Parallel Chain System

CVchain: A Cross-Voting-Based Low Latency Parallel Chain Sys...

引用

IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Jianrong Wang Yacong Ren Dengcheng Hu Qi Li Sen Li Xuewei Li Xiulong Liu College of Intelligence and Computing Tianjin University China School of Electrical and Information Engineering Tianjin University China School of Future Technology Tianjin University China

ISBN: (数字)9798331506209

ISBN: (纸本)9798331506216

Despite existing parallel chain systems improving blockchain throughput by allowing concurrent blocks to be appended, challenges such as the excessive number of waiting blocks before confirmation and the inconsistency between block generation order and global confirmation sequence still persist. To address these challenges, we propose CVchain, a parallel chain system with a cross-voting mechanism. Blocks from other subchains are incorporated into the consistency determination of the main chain, reducing the probability of confirmation errors. Our global sorting mechanism leverages both real-time height information and the implicit temporal order contained in voting to improve the accuracy of block ordering. Furthermore, our voting mechanism randomly splits the mining power of the system, preventing targeted attacks on the specific subchain and defending against liveness attacks. We prove the safety and liveness properties of CVchain. We demonstrated its performance with a prototype implementation and large-scale experiments involving 200 nodes across 10 cloud servers in a distributed network environment. The results indicate that CVchain achieves a latency reduction of approximately 32.3% at a confirmation error probability of 0.01 while maintaining throughput levels comparable to OHIE. Additionally, it provides enhanced transaction ordering services.

关键词： Accuracy Scalability Prototypes Throughput Real-time systems Safety Servers Security Low latency communication Sorting

来源：评论

学校读者我要写书评

暂无评论

Internet of Things Assisted Blockchain based Secured Cloud Data Maintenance Scheme

Internet of Things Assisted Blockchain based Secured Cloud D...

引用

2022 IEEE International Conference on Advances in computing, Communication and Applied Informatics, ACCAI 2022

作者： Ali, Ahmed Mudassar Bapu, B R Tapas Partheeban, N. Nagaraju, V. Kumar, N. Jagadish S.A. Engineering College Department of Information Technology Chennai India S.A. Engineering College Department of ECE Chennai India School of Computing Science and Engineering Galgotias University Greater Noida Delhi India Saveetha School of Engineering SIMATS Department of CSE Chennai India Velammal Institute of Technology Department of IT Chennai India

ISBN: (纸本)9781665495295

The term 'Internet-of-Things (IoT)' has received a loT of interest nowadays. Blockchain has previously been employed in IoT as a reliable, robust and decentralized way. Furthermore, the present blockchain technology has a number of shortcomings that preclude it from serving as a general IoT infrastructure. The networks in the Internet of Things are severely resource constrained, particularly in terms of processing and communication capabilities. Regrettably, they are required by the Blockchain in order to achieve research objectives and disseminate blocks. We present a novel mining and cloud handling methodologies in this study to address the aforementioned challenge in the Blockchain assisted IoT, which is called as 'Deep Precise Networking Model (DPNM)'. To be more precise, miners function as data mining drivers for IoT terminals, outsource processing duties to deliver effective cloud enabled servers and flexibly allocate networking connections. Additionally, in addition to improve efficiency, the access control determination challenge, computational resource allocation algorithm and communication resource allocation issue are combined into a single optimization method. We next offer a competing back-propagation learning technique for resolving this issue and the subsequent section thoroughly justifies the efficacy of our proposed technique DPNM. © 2022 IEEE.

关键词： Internet of things

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：