IETI Transactions on Data Analysis and Forecasting (iTDAF)最新文献

The Way to Construct Innovative Methods for Solving Initial-Value Problem of the Volterra Integro-Differential Equation 构建解决 Volterra 积分微分方程初值问题创新方法的途径

IETI Transactions on Data Analysis and Forecasting (iTDAF) Pub Date : 2024-05-02 DOI: 10.3991/itdaf.v2i1.48883

Vagif Ibrahimov, Praveen Agarwal, Davron Aslonqulovic Juraev

{"title":"The Way to Construct Innovative Methods for Solving Initial-Value Problem of the Volterra Integro-Differential Equation","authors":"Vagif Ibrahimov, Praveen Agarwal, Davron Aslonqulovic Juraev","doi":"10.3991/itdaf.v2i1.48883","DOIUrl":"https://doi.org/10.3991/itdaf.v2i1.48883","url":null,"abstract":"Mathematical models for many problems in the natural sciences are often simplified to solving initial-value problems (IVPs) for the Volterra integro-differential equations (VIDE). Numerical methods of a multistep type are typically used to solve these problems. It is known that in some cases, the multi-step method (MSM) is applied to solving the IVPs of both ordinary differential equations (ODEs) and VIDE encountered in solving some problems in mathematical biology. Here, to solve such problems by combining different methods, some modifications of established methods were developed, and it was demonstrated that these methods outperform the existing ones. As is known, one of the main issues in solving the aforementioned problems is determining the reliability of calculating values using the known mathematicalstatistical models (MSMs). In this regard, some experts utilize the predictor-corrector method. Having highlighted the disadvantages of this method, the proposal is to develop an innovative approach and assess the errors that may arise when applying this method to solve various problems. Here, the IVPs for the VIDE of the first order are primarily investigated. To illustrate the benefits of the innovative methods proposed here, we discuss the use of simple numerical methods to solve some common examples.","PeriodicalId":509615,"journal":{"name":"IETI Transactions on Data Analysis and Forecasting (iTDAF)","volume":"44 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141019340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Knowledge Inference Combining Convolutional Feature Extraction and Path Semantics Integration 结合卷积特征提取和路径语义整合的知识推理

IETI Transactions on Data Analysis and Forecasting (iTDAF) Pub Date : 2024-05-02 DOI: 10.3991/itdaf.v2i1.40095

Xinyuan Chen, U. Comite

{"title":"Knowledge Inference Combining Convolutional Feature Extraction and Path Semantics Integration","authors":"Xinyuan Chen, U. Comite","doi":"10.3991/itdaf.v2i1.40095","DOIUrl":"https://doi.org/10.3991/itdaf.v2i1.40095","url":null,"abstract":"Many knowledge representation models extract local patterns or semantic features using fact embeddings but often overlook path semantics. There is room for improvement in pathbased approaches that rely solely on single paths. A customized convolutional neural network (CNN) architecture is proposed to encode multiple paths generated by random walks into vector sequences. For each path, the feature sequence is then merged into a single vector using bidirectional long short-term memory (LSTM) by concatenating both forward and backward hidden states. Semantic relevance between different paths and candidate relations is computed using the attention mechanism. The state vectors of the relations are calculated using weighted paths. These paths help determine the probabilities of the candidate relations, which are then used to assess the validity of the triples. Link prediction experiments on two benchmark datasets, NELL995 and FB15k-237, demonstrate the advantages of our solution. Our model shows a 7.19% improvement at Hits@3 on FB15k-237 compared to Att-Model + Type, another advanced model. The model is further applied to a large complex dataset, FC17, as well as a sparse dataset, NELL-One, for few-shot reasoning.","PeriodicalId":509615,"journal":{"name":"IETI Transactions on Data Analysis and Forecasting (iTDAF)","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141021889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on China’s Environmental Law and Low-carbon Emission Economy Trade Surplus under the Background of Carbon Neutrality 碳中性背景下中国环境法与低碳排放经济贸易顺差研究

IETI Transactions on Data Analysis and Forecasting (iTDAF) Pub Date : 2024-05-02 DOI: 10.3991/itdaf.v2i1.49197

Gaojing Gai, Yang Wang

引用次数: 0

Cybersecurity and Efficacity of Open Data Platforms 开放数据平台的网络安全和效率

IETI Transactions on Data Analysis and Forecasting (iTDAF) Pub Date : 2024-05-02 DOI: 10.3991/itdaf.v2i1.46779

Besart Hyseni, Lejla Abazi Bexheti

{"title":"Cybersecurity and Efficacity of Open Data Platforms","authors":"Besart Hyseni, Lejla Abazi Bexheti","doi":"10.3991/itdaf.v2i1.46779","DOIUrl":"https://doi.org/10.3991/itdaf.v2i1.46779","url":null,"abstract":"Cybersecurity is critical for protecting open data. Transparency and innovation are facilitated by open data platforms; however, concerns about cybersecurity and privacy persist. This study examines the role of cybersecurity in public institutions in the Republic of Kosovo to determine methods of safeguarding data integrity. The main aim of this study was to examine the role of cybersecurity in securing open data in public organizations in the Republic of Kosovo. The study aimed to identify optimal cybersecurity practices in the context of open data and provide a comprehensive overview of the implementation of cybersecurity measures. This study employed a structured and methodical approach to assess cybersecurity and the effectiveness of open data platforms in public organizations in the Republic of Kosovo. Results: The study provides an overview of the status of open data platforms in the Republic of Kosovo and highlights the importance of cybersecurity, data privacy, and data integrity. Despite the stated concerns, such as enhancing security measures and increasing user knowledge, it is evident that public institutions have made significant progress in securing and enhancing their open data platforms. It is suggested that institutions in the Republic of Kosovo continue to invest in cybersecurity, promote privacy protection measures, and focus on enhancing the quality of open data to develop in this sector. Furthermore, collaboration and coordination across institutions and government agencies are required to enhance the efficiency and effectiveness of these platforms.","PeriodicalId":509615,"journal":{"name":"IETI Transactions on Data Analysis and Forecasting (iTDAF)","volume":"7 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141020619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Study on the Willingness of Mobile Advertisement Users Based on TAM Model 基于 TAM 模型的移动广告用户意愿研究

IETI Transactions on Data Analysis and Forecasting (iTDAF) Pub Date : 2024-05-02 DOI: 10.3991/itdaf.v2i1.49105

Qiaoqin Su

引用次数: 0