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  Subjects -> STATISTICS (Total: 130 journals)
Showing 1 - 151 of 151 Journals sorted alphabetically
Advances in Complex Systems     Hybrid Journal   (Followers: 10)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 53)
Applied Categorical Structures     Hybrid Journal   (Followers: 5)
Argumentation et analyse du discours     Open Access   (Followers: 7)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 7)
AStA Advances in Statistical Analysis     Hybrid Journal   (Followers: 2)
Australian & New Zealand Journal of Statistics     Hybrid Journal   (Followers: 12)
Biometrical Journal     Hybrid Journal   (Followers: 6)
Biometrics     Hybrid Journal   (Followers: 51)
Building Simulation     Hybrid Journal   (Followers: 2)
CHANCE     Hybrid Journal   (Followers: 5)
Communications in Statistics - Simulation and Computation     Hybrid Journal   (Followers: 9)
Communications in Statistics - Theory and Methods     Hybrid Journal   (Followers: 10)
Computational Statistics     Hybrid Journal   (Followers: 17)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 39)
Current Research in Biostatistics     Open Access   (Followers: 9)
Decisions in Economics and Finance     Hybrid Journal   (Followers: 15)
Demographic Research     Open Access   (Followers: 15)
Engineering With Computers     Hybrid Journal   (Followers: 5)
Environmental and Ecological Statistics     Hybrid Journal   (Followers: 7)
ESAIM: Probability and Statistics     Open Access   (Followers: 4)
Extremes     Hybrid Journal   (Followers: 2)
Fuzzy Optimization and Decision Making     Hybrid Journal   (Followers: 9)
Geneva Papers on Risk and Insurance - Issues and Practice     Hybrid Journal   (Followers: 13)
Handbook of Numerical Analysis     Full-text available via subscription   (Followers: 3)
Handbook of Statistics     Full-text available via subscription   (Followers: 9)
IEA World Energy Statistics and Balances -     Full-text available via subscription   (Followers: 2)
International Journal of Computational Economics and Econometrics     Hybrid Journal   (Followers: 6)
International Statistical Review     Hybrid Journal   (Followers: 12)
Journal of Algebraic Combinatorics     Hybrid Journal   (Followers: 3)
Journal of Applied Statistics     Hybrid Journal   (Followers: 22)
Journal of Biopharmaceutical Statistics     Hybrid Journal   (Followers: 17)
Journal of Business & Economic Statistics     Full-text available via subscription   (Followers: 42, SJR: 3.664, CiteScore: 2)
Journal of Combinatorial Optimization     Hybrid Journal   (Followers: 7)
Journal of Computational & Graphical Statistics     Full-text available via subscription   (Followers: 21)
Journal of Econometrics     Hybrid Journal   (Followers: 85)
Journal of Educational and Behavioral Statistics     Hybrid Journal   (Followers: 8)
Journal of Forecasting     Hybrid Journal   (Followers: 21)
Journal of Global Optimization     Hybrid Journal   (Followers: 7)
Journal of Mathematics and Statistics     Open Access   (Followers: 6)
Journal of Nonparametric Statistics     Hybrid Journal   (Followers: 7)
Journal of Risk and Uncertainty     Hybrid Journal   (Followers: 35)
Journal of Statistical Physics     Hybrid Journal   (Followers: 12)
Journal of Statistical Planning and Inference     Hybrid Journal   (Followers: 8)
Journal of Statistical Software     Open Access   (Followers: 19, SJR: 13.802, CiteScore: 16)
Journal of the American Statistical Association     Full-text available via subscription   (Followers: 78, SJR: 3.746, CiteScore: 2)
Journal of the Korean Statistical Society     Hybrid Journal   (Followers: 1)
Journal of the Royal Statistical Society Series C (Applied Statistics)     Hybrid Journal   (Followers: 37)
Journal of the Royal Statistical Society, Series A (Statistics in Society)     Hybrid Journal   (Followers: 31)
Journal of the Royal Statistical Society, Series B (Statistical Methodology)     Hybrid Journal   (Followers: 43)
Journal of Theoretical Probability     Hybrid Journal   (Followers: 3)
Journal of Time Series Analysis     Hybrid Journal   (Followers: 18)
Journal of Urbanism: International Research on Placemaking and Urban Sustainability     Hybrid Journal   (Followers: 28)
Law, Probability and Risk     Hybrid Journal   (Followers: 8)
Lifetime Data Analysis     Hybrid Journal   (Followers: 5)
Mathematical Methods of Statistics     Hybrid Journal   (Followers: 4)
Measurement Interdisciplinary Research and Perspectives     Hybrid Journal   (Followers: 1)
Metrika     Hybrid Journal   (Followers: 4)
Monthly Statistics of International Trade - Statistiques mensuelles du commerce international     Full-text available via subscription   (Followers: 4)
Multivariate Behavioral Research     Hybrid Journal   (Followers: 9)
Optimization Letters     Hybrid Journal   (Followers: 2)
Optimization Methods and Software     Hybrid Journal   (Followers: 5)
Oxford Bulletin of Economics and Statistics     Hybrid Journal   (Followers: 35)
Pharmaceutical Statistics     Hybrid Journal   (Followers: 10)
Queueing Systems     Hybrid Journal   (Followers: 7)
Research Synthesis Methods     Hybrid Journal   (Followers: 8)
Review of Socionetwork Strategies     Hybrid Journal  
Risk Management     Hybrid Journal   (Followers: 16)
Sankhya A     Hybrid Journal   (Followers: 3)
Scandinavian Journal of Statistics     Hybrid Journal   (Followers: 9)
Sequential Analysis: Design Methods and Applications     Hybrid Journal   (Followers: 1)
Significance     Hybrid Journal   (Followers: 6)
Sociological Methods & Research     Hybrid Journal   (Followers: 49)
SourceOECD Measuring Globalisation Statistics - SourceOCDE Mesurer la mondialisation - Base de donnees statistiques     Full-text available via subscription  
Stata Journal     Full-text available via subscription   (Followers: 10)
Statistica Neerlandica     Hybrid Journal   (Followers: 1)
Statistical Inference for Stochastic Processes     Hybrid Journal   (Followers: 3)
Statistical Methods and Applications     Hybrid Journal   (Followers: 5)
Statistical Methods in Medical Research     Hybrid Journal   (Followers: 25)
Statistical Modelling     Hybrid Journal   (Followers: 19)
Statistical Papers     Hybrid Journal   (Followers: 4)
Statistics & Probability Letters     Hybrid Journal   (Followers: 13)
Statistics and Computing     Hybrid Journal   (Followers: 14)
Statistics and Economics     Open Access  
Statistics in Medicine     Hybrid Journal   (Followers: 149)
Statistics: A Journal of Theoretical and Applied Statistics     Hybrid Journal   (Followers: 12)
Stochastic Models     Hybrid Journal   (Followers: 2)
Stochastics An International Journal of Probability and Stochastic Processes: formerly Stochastics and Stochastics Reports     Hybrid Journal   (Followers: 2)
Structural and Multidisciplinary Optimization     Hybrid Journal   (Followers: 12)
Teaching Statistics     Hybrid Journal   (Followers: 8)
Technology Innovations in Statistics Education (TISE)     Open Access   (Followers: 2)
TEST     Hybrid Journal   (Followers: 3)
The American Statistician     Full-text available via subscription   (Followers: 27)
The Canadian Journal of Statistics / La Revue Canadienne de Statistique     Hybrid Journal   (Followers: 10)
Wiley Interdisciplinary Reviews - Computational Statistics     Hybrid Journal   (Followers: 1)

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Review of Socionetwork Strategies
Number of Followers: 0  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1867-3236
Published by Springer-Verlag Homepage  [2468 journals]
  • Event Identification for Supply Chain Risk Management Through News
           Analysis by Using Large Language Models

    • Free pre-print version: Loading...

      Abstract: Abstract Event identification is important in many areas of the business world. In the supply chain risk management domain, the timely identification of risk events is vital to ensure the success of supply chain operations. One of the important sources of real-time information from across the world is news sources. However, the analysis of large amounts of daily news cannot be done manually by humans. On the other hand, extracting related news depends on the query or the keyword used in the search engine and the news content. Recent advancements in artificial intelligence have opened up opportunities to leverage intelligent techniques to automate this analysis. This paper introduces the LUEI framework, a lightweight framework that, with only the event’s name as input, can autonomously learn all the related phrases associated with that event. It then employs these phrases to search for relevant news and presents the search engine results with a label indicating their relevance. Hence, by conducting this analysis, the LUEI framework is able to identify the occurrence of the event in the real world. The framework’s novel contribution lies in its ability to identify those events (termed as the Contributing Events (CEs)) that contribute to the occurrence of a risk event, offering a proactive approach to risk management in supply chains. Pinpointing CEs from vast news data gives supply chain managers actionable insights to mitigate risks before they escalate.
      PubDate: 2024-07-15
       
  • Application of Deep Learning in the Classification of Maritime Safety
           Information

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      Abstract: Abstract Maritime safety information (MSI) refers to urgent information concerning navigation warnings, weather warnings, weather forecasts, and other safety-related information for navigation. MSI is primarily disseminated through two systems: the international NAVTEX (Navigational Telex) system and the Enhanced Group Calling (EGC) system. NAVTEX receivers on ships can automatically receive MSI, enhancing safety of life and property at sea and reducing the workload for communication personnel. Due to the narrowband direct printing telegraphy (NBDP) technology used in the broadcast of MSI, the information must be concise, it makes the information difficult for navigators to interpret. To address this challenge, various machine learning solutions have been proposed. Among these, deep neural networks have shown superior performance in MSI classification. This study provides a more detailed analysis of deep neural networks applied to MSI classification. It utilizes collected MSI datasets, including thousands of navigation warnings, and compares the performances of different models based on accuracy, precision, recall, and F1-score.
      PubDate: 2024-07-04
       
  • The Integration of Artificial Intelligence and Video Production Skills in
           Workplace Development: A Study from the Perspective of Vocational Training
           

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      Abstract: Abstract This paper explores the potential impact of artificial intelligence (A.I.) and video production skills on workplace development, focusing on the perspective of vocational training. With the rapid growth of A.I. technology, it is essential to investigate how learners acquire video production skills under the guidance of A.I. and imagine the possibilities for their future career development. This study examines the process of learning video production skills in the A.I.-dominated era and explores learners’ perceptions and expectations of their career development trajectory. This study adopts a qualitative approach, primarily through focus group interviews and thematic analysis. The findings of this study indicate that video-making skills are crucial in online marketing. While artificial intelligence enhances efficiency, human creativity remains indispensable. Integrating A.I. into training can improve learning outcomes. Recommendations include emphasizing hands-on experience, personalized learning paths, and collaborative learning.
      PubDate: 2024-06-25
       
  • Evaluating the Network Performance of the Ensembled-Based Veracity
           Architecture for Fake News Detection in Infrastructureless Social Networks
           

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      Abstract: Abstract Infrastructureless social networks (ISNs) are created by the interconnection of spectral-constrained mobile devices. One such type of ISN are the mobile ad hoc networks (MANETs). One of the issues that consumers of content on ISNs face is the inability to detect fake news in messages sent through the network. To address the fake news detection issue in ISNs, the ensemble-based veracity architecture, an ensemble-based computational social system for fake news detection in infrastructureless social networks, has been proposed. Ensemble-based Veracity detects fake news using both the publisher’s credibility and the content of the news. To understand the effect that ensemble-based Veracity has on network performance, this work investigates the network performance of the ensemble-based Veracity architecture. Ensemble-based Veracity is fully evaluated using a MANET-based experimental design and simulation environment. The network performance results of the experiments on ensemble-based Veracity are thoroughly analysed, and all the observations are noted. According to the experimental results, the throughputs were 2,445,528 bps, 2,391,905 bps and 2,236,778 bps for 20, 50 and 100 nodes, respectively. The experimental results show that ensemble-based Veracity negligibly affects the throughput, queuing time, queue length and number of packets passed to the upper layers of the network and the network performance.
      PubDate: 2024-06-21
       
  • Developing a Feature Set from Scene and Texture Features for Detecting
           Neural Texture Videos Using Boosted Decision Trees

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      Abstract: Abstract The prevalence of manipulated videos presents a significant challenge in today's era dominated by social media. Various types of fake videos, including notable examples such as Neural Textures, exist. Identifying such deceptive videos is a complex task. This research aims to understand the unique characteristics associated with Neural Texture videos. In the pursuit of comprehending these videos, the study explores the distinguishing traits that define them. The research employs techniques for scene and texture detection to formulate a distinct set of nineteen data features. This feature set is crafted to determine whether a video exhibits Neural Texture characteristics. To validate this set, a standard dataset of video attributes is utilized. These attributes undergo analysis using a machine learning classification model. The results of these experiments are assessed through four distinct methodologies. The evaluation reveals favourable performance outcomes when the machine learning approach and the proposed feature set are used. Based on these findings, it can be concluded that employing the suggested feature set enables the prediction of whether a video displays Neural Texture characteristics. This confirms the hypothesis that a correlation exists between a video's attributes and its authenticity, specifically in determining whether the video qualifies as a Neural Texture.
      PubDate: 2024-06-19
       
  • Impact of Computer Usage on Organizational Memory and Learning from
           Failure: A Case Study of a Japanese Company

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      Abstract: Abstract Few organizations are good at learning from failure, and failures are sometimes repeated. One reason could be the inadequate functioning of organizational memory. According to previous research, IT is often assumed to complement organizational memory. However, studies have also reported that information technology weakens memory; hence, no definite conclusion has been drawn. This study aimed to identify the impact of information technology on organizational memory in the context of organizational learning from failure. We focus on a Japanese company that has successfully implemented the use of information technology for organizational learning from failure. A quantitative analysis was conducted using a questionnaire survey, which revealed the following: (1) if the matter is of high interest in the organization, it is recorded, and knowledge storage and sharing media that employ information technology are used; (2) recording activity is strengthened using knowledge storage and sharing media that employ information technology; (3) even if the matter is of high interest in the organization, it is not always possible to strengthen individual memory, but it is possible to enhance individual memory with knowledge storage/sharing media that utilize information technology; (4) knowledge storage/sharing media that utilize information technology do not directly strengthen organizational memory; and (5) knowledge storage and sharing media using information technology strengthen records and personal memory, which ultimately strengthens organizational memory.
      PubDate: 2024-06-14
       
  • All-to-All Data Exchange Method for MANET in Congestion Environment

    • Free pre-print version: Loading...

      Abstract: Abstract Mobile Ad-hoc Network (MANET) are expected to be a means of communication for disaster victim support systems and information distribution systems at event sites where it is challenging to use existing infrastructure owing to their feature of being able to build a network immediately among nodes that are present on the spot. An operating scenario of such a post-disaster application requires an all-to-all exchange of information that quickly and reliably exchanges a lot of information among a large number of nodes present at the scene to collect more decision-making materials. All-to-all communication places a lot of load on all nodes in the network as they exchange information about all nodes with each other. The MANET routing protocol is also heavily loaded due to route discovery by flooding, which, together with the all-to-all information exchange, is a double challenge to MANET. In this article, we propose an information exchange method that is robust to high-density nodes and high-traffic environments, assuming a situation where communication becomes difficult as a result of requests to send and receive large amounts of information between overcrowded nodes in crowded environments, such as evacuation centers, during a disaster and event sites. The proposed method overcomes the problems of conventional methods and achieves smooth information exchange by applying a delay tolerant network(DTN), a clustering method, and a gossip protocol method. Simulation experiments have shown that the proposed method is highly tolerant of network congestion and increase in the number of nodes due to all-to-all information exchange.
      PubDate: 2024-05-20
       
  • Hybrid Load Balancing Technique for Cloud Environment Using Swarm
           Optimization

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      Abstract: Abstract One of the most challenging aspects of cloud computing is task scheduling. User needs are changing rapidly in a dynamic environment, and the resources can fluctuate depending on demand because they are virtual. This study presents a hybrid task scheduling model that combines Particle Swarm Optimization and Whale Optimization techniques to address the challenges of task scheduling and achieve the best performance. The method is analyzed and scored based on its “makespan,” “resource utilization,” and “convergence.” Test results indicate that the proposed method reduces the makespan in all cases. Additionally, it increases resource utilization compared to the existing state-of-the-art methods. Furthermore, resource utilization increases across the board with the number of tasks performed.
      PubDate: 2024-04-02
      DOI: 10.1007/s12626-024-00160-8
       
  • Data Augmentation and Large Language Model for Legal Case Retrieval and
           Entailment

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      Abstract: Abstract The Competition on Legal Information Extraction and Entailment (COLIEE) is a well-known international competition organized each year with the goal of applying machine learning algorithms and techniques in the analysis and understanding of legal documents. Two main applications of using machine learning in this domain are entailment and information retrieval. In the realm of legal text analysis, the scarcity of annotated data poses a significant challenge for training robust models. To address this limitation, we employ data augmentation methods to artificially expand the training dataset, enhancing the model’s ability to generalize across diverse legal contexts. Additionally, our approach harnesses the power of a state-of-the-art language model, enabling the extraction of nuanced legal information and improving entailment predictions. We evaluate the performance of our methodology on datasets from the competition, showcasing its effectiveness in achieving competitive results.
      PubDate: 2024-03-26
      DOI: 10.1007/s12626-024-00158-2
       
  • Preface of Special Issue on 10th Competition on Legal Information of
           Extraction and Entailment (COLIEE 2023)

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      PubDate: 2024-03-18
      DOI: 10.1007/s12626-024-00159-1
       
  • Contribution Analysis of Large Language Models and Data Augmentations for
           Person Names in Solving Legal Bar Examination at COLIEE 2023

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      Abstract: Abstract This paper describes our system for COLIEE 2023 Task 4, which automatically answers Japanese legal bar exam problems. We propose an extension to our previous system in COLIEE 2022, which achieved the highest accuracy among all submissions using data augmentation. We focus on problems that include mentions of person names. In this paper, we present two main contributions. First, we incorporate LUKE as our deep learning component, which is a named entity recognition model trained on RoBERTa. Second, we fine-tune the pretrained LUKE model in multiple ways, comparing fine-tuning on training datasets that include alphabetical person names and ensembling different fine-tuning models. We confirmed that LUKE and its fine-tuned model on person type problems improve their accuracies. Our formal run results show that LUKE and our fine-tuning approach using alphabetical person names were effective, achieving an accuracy of 0.69 in the COLIEE 2023 Task 4 formal run.
      PubDate: 2024-03-08
      DOI: 10.1007/s12626-024-00155-5
       
  • Does Travel Spread Infection'—Effects of Social Stirring
           Simulated on SEIRS Circuit Grid

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      Abstract: Abstract Previous models of the spread of viral infection could not explain the potential risk of non-infectious travelers and exceptional events, such as the reduction in infected cases with an increase in travelers. In this study, we provide an explanation for improving the model by considering two factors. First, we consider the travel of susceptible (S), exposed (E), and recovered (R) individuals who may become infected and infect others in the destination region in the near future, as well as infectious (I). Second, people living in a region and those moving from other regions are treated as separate but interacting groups to consider the potential influence of movement before infection. We show the results of the simulation of infection spread in a country where individuals travel across regions and the government chooses regions to vaccinate with priority. As a result, vaccinating people in regions with larger populations better suppresses the spread of infection, which turns out to be a part of a general law that the same quantity of vaccines can work efficiently by maximizing the conditional entropy Hc of the distribution of vaccines to regions. This strategy outperformed vaccination in regions with a larger effective regeneration number. These results, understandable through the new concept of social stirring, correspond to the fact that travel activities across regional borders may even suppress the spread of vaccination if processed at a sufficiently high pace. This effect can be further reinforced if vaccines are equally distributed to local regions.
      PubDate: 2024-03-01
      DOI: 10.1007/s12626-024-00156-4
       
  • NOWJ at COLIEE 2023: Multi-task and Ensemble Approaches in Legal
           Information Processing

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      Abstract: Abstract This paper presents the NOWJ team’s approach to the COLIEE 2023 Competition, which focuses on advancing legal information processing techniques and applying them to real-world legal scenarios. Our team tackled the four tasks in the competition, which involved legal case retrieval, legal case entailment, statute law retrieval, and legal textual entailment. We employ state-of-the-art machine learning models and innovative approaches, such as BERT, Longformer, BM25-ranking algorithm, and multi-task learning models. Our participation in the COLIEE 2023 has provided useful insights including the importance of the pre-processing and feature engineering, effectiveness of the multi-task models in combining different legal tasks to improve model’s performance. Although our team did not achieve state-of-the-art results, our findings identify areas for further research and improvements in legal information processing.
      PubDate: 2024-02-22
      DOI: 10.1007/s12626-024-00157-3
       
  • Exploring Prompting Approaches in Legal Textual Entailment

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      Abstract: Abstract We report explorations into prompt engineering with large pre-trained language models that were not fine-tuned to solve the legal entailment task (Task 4) of the 2023 COLIEE competition. Our most successful strategy used simple text similarity measures to retrieve articles and queries from the training set. We report on our efforts to optimize performance with both OpenAI’s GPT-4 and FLaN-T5. We also used an ensemble approach to find the best combination of models and prompts. Finally, we analyze our results and suggest ideas for future improvements.
      PubDate: 2024-01-23
      DOI: 10.1007/s12626-023-00154-y
       
  • Overview and Discussion of the Competition on Legal Information,
           Extraction/Entailment (COLIEE) 2023

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      Abstract: Abstract We summarize the 10th Competition on Legal Information Extraction and Entailment. In this tenth edition, the competition included four tasks on case law and statute law. The case law component includes an information retrieval task (Task 1), and the confirmation of an entailment relation between an existing case and a selected unseen case (Task 2). The statute law component includes an information retrieval task (Task 3), and an entailment/question-answering task based on retrieved civil code statutes (Task 4). Participation was open to any group based on any approach. Ten different teams participated in the case law competition tasks, most of them in more than one task. We received results from 8 teams for Task 1 (22 runs) and seven teams for Task 2 (18 runs). On the statute law task, there were 9 different teams participating, most in more than one task. 6 teams submitted a total of 16 runs for Task 3, and 9 teams submitted a total of 26 runs for Task 4. We describe the variety of approaches, our official evaluation, and analysis of our data and submission results.
      PubDate: 2024-01-12
      DOI: 10.1007/s12626-023-00152-0
       
  • Legal Information Retrieval and Entailment Using Transformer-based
           Approaches

    • Free pre-print version: Loading...

      Abstract: Abstract The challenge of information overload in the legal domain increases every day. The COLIEE competition has created four challenge tasks that are intended to encourage the development of systems and methods to alleviate some of that pressure: a case law retrieval (Task 1) and entailment (Task 2), and a statute law retrieval (Task 3) and entailment (Task 4). Here we describe our methods for Task 1 and Task 4. In Task 1, we used a sentence-transformer model to create a numeric representation for each case paragraph. We then created a histogram of the similarities between a query case and a candidate case. The histogram is used to build a binary classifier that decides whether a candidate case should be noticed or not. In Task 4, our approach relies on fine-tuning a pre-trained DeBERTa large language model (LLM) trained on SNLI and MultiNLI datasets. Our method for Task 4 was ranked third among eight participating teams in the COLIEE 2023 competition. For Task 4, We also compared the performance of the DeBERTa model with those of a knowledge distillation model and ensemble methods including Random Forest and Voting.
      PubDate: 2024-01-11
      DOI: 10.1007/s12626-023-00153-z
       
  • Preface of Special Issue on International Workshop on AI compliance
           mechanism (WAICOM 2022)

    • Free pre-print version: Loading...

      PubDate: 2023-09-30
      DOI: 10.1007/s12626-023-00150-2
       
  • Role of Regulatory Sandboxes and MLOps for AI-Enabled Public Sector
           Services

    • Free pre-print version: Loading...

      Abstract: Abstract This paper discusses how innovations in public sector AI-based services must comply with the Artificial Intelligence Act (AI Act) regulatory frameworks while enabling experimentation and participation of diverse stakeholders throughout the Artificial Intelligence (AI) lifecycle. The paper examines the implications of the emerging regulation, AI regulatory sandboxes and Machine Learning Operations (MLOps) as tools that facilitate compliance while enabling co-learning and active participation of multiple stakeholders. We propose a framework that fosters experimentation with automation pipelines and continuous monitoring for the deployment of future public sector AI-based services in a regulatory-compliant and technically innovative manner. AI regulatory sandboxes can be beneficial as a space for contained experimentation that goes beyond regulatory considerations to specific experimentation with the implementation of ML frameworks. While the paper presents a framework based on emerging regulations, tools and practices pertaining to the responsible use of AI, this must be validated through pilot experimentation with public and private stakeholders and regulators in different areas of high-risk AI-based services.
      PubDate: 2023-08-18
      DOI: 10.1007/s12626-023-00146-y
       
  • The Impact of Changing Political Positions on Charitable Donations: A Case
           Study of a Political Scandal in South Korea

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      Abstract: Abstract This study examines whether political ideology switching by moderates mediates their charitable donations. Using the impeachment of Park Geun-hye, the former conservative president of South Korea, as a quasi-natural experiment, we find that the charitable donations of those who changed their political ideology from moderate to progressive after the corruption scandal increased by 16.8–17.9%. A battery of robustness tests supports the basic results. These findings imply that political scandals can affect moderates’ charitable behavior through the channel of political ideology switching.
      PubDate: 2023-07-06
      DOI: 10.1007/s12626-023-00141-3
       
  • Review and Comparison of US, EU, and UK Regulations on Cyber Risk/Security
           of the Current Blockchain Technologies: Viewpoint from 2023

    • Free pre-print version: Loading...

      Abstract: Abstract The first cryptocurrency was invented in 2008/09, but the Blockchain-Web3 concept is still in its infancy, and the cyber risk is constantly changing. Cybersecurity should also be adapting to these changes to ensure security of personal data and continuation of operations. This article starts with a comparison of existing cybersecurity standards and regulations from the National Institute of Standards and Technology (NIST) and the International Organisation for Standardisation (ISO)—ISO27001, followed by a discussion on more specific and recent standards and regulations, such as the Markets in Crypto-Assets Regulation (MiCA), Committee on Payments and Market Infrastructures and the International Organisation of Securities Commissions (CPMI-IOSCO), and more general cryptography (and post-quantum cryptography), in the context of cybersecurity. These topics are followed up by a review of recent technical reports on cyber risk/security and a discussion on cloud security questions. Comparison of Blockchain cyber risk is also performed on the recent EU standards on cyber security, including European Cybersecurity Certification Scheme (EUCS)—cloud, and US standards—The National Vulnerability Database (NVD) Common Vulnerability Scoring System (CVSS). The study includes a review of Blockchain endpoint security, and new technologies e.g., IoT. The research methodology applied is a review and case study analysing secondary data on cybersecurity. The research significance is the integration of knowledge from the United States (US), the European Union (EU), the United Kingdom (UK), and international standards and frameworks on cybersecurity that can be alighted to new Blockchain projects. The results show that cybersecurity standards are not designed in close cooperation between the two major western blocks: US and EU. In addition, while the US is still leading in this area, the security standards for cryptocurrencies, internet-of-things, and blockchain technologies have not evolved as fast as the technologies have. The key finding from this study is that although the crypto-market has grown into a multi-trillion industry, the crypto-market has also lost over 70% since its peak, causing significant financial loss for individuals and cooperation’s. Despite this significant impact to individuals and society, cybersecurity standards and financial governance regulations are still in their infancy, specifically in the UK.
      PubDate: 2023-05-03
      DOI: 10.1007/s12626-023-00139-x
       
 
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  Subjects -> STATISTICS (Total: 130 journals)
Showing 1 - 151 of 151 Journals sorted alphabetically
Advances in Complex Systems     Hybrid Journal   (Followers: 10)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 53)
Applied Categorical Structures     Hybrid Journal   (Followers: 5)
Argumentation et analyse du discours     Open Access   (Followers: 7)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 7)
AStA Advances in Statistical Analysis     Hybrid Journal   (Followers: 2)
Australian & New Zealand Journal of Statistics     Hybrid Journal   (Followers: 12)
Biometrical Journal     Hybrid Journal   (Followers: 6)
Biometrics     Hybrid Journal   (Followers: 51)
Building Simulation     Hybrid Journal   (Followers: 2)
CHANCE     Hybrid Journal   (Followers: 5)
Communications in Statistics - Simulation and Computation     Hybrid Journal   (Followers: 9)
Communications in Statistics - Theory and Methods     Hybrid Journal   (Followers: 10)
Computational Statistics     Hybrid Journal   (Followers: 17)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 39)
Current Research in Biostatistics     Open Access   (Followers: 9)
Decisions in Economics and Finance     Hybrid Journal   (Followers: 15)
Demographic Research     Open Access   (Followers: 15)
Engineering With Computers     Hybrid Journal   (Followers: 5)
Environmental and Ecological Statistics     Hybrid Journal   (Followers: 7)
ESAIM: Probability and Statistics     Open Access   (Followers: 4)
Extremes     Hybrid Journal   (Followers: 2)
Fuzzy Optimization and Decision Making     Hybrid Journal   (Followers: 9)
Geneva Papers on Risk and Insurance - Issues and Practice     Hybrid Journal   (Followers: 13)
Handbook of Numerical Analysis     Full-text available via subscription   (Followers: 3)
Handbook of Statistics     Full-text available via subscription   (Followers: 9)
IEA World Energy Statistics and Balances -     Full-text available via subscription   (Followers: 2)
International Journal of Computational Economics and Econometrics     Hybrid Journal   (Followers: 6)
International Statistical Review     Hybrid Journal   (Followers: 12)
Journal of Algebraic Combinatorics     Hybrid Journal   (Followers: 3)
Journal of Applied Statistics     Hybrid Journal   (Followers: 22)
Journal of Biopharmaceutical Statistics     Hybrid Journal   (Followers: 17)
Journal of Business & Economic Statistics     Full-text available via subscription   (Followers: 42, SJR: 3.664, CiteScore: 2)
Journal of Combinatorial Optimization     Hybrid Journal   (Followers: 7)
Journal of Computational & Graphical Statistics     Full-text available via subscription   (Followers: 21)
Journal of Econometrics     Hybrid Journal   (Followers: 85)
Journal of Educational and Behavioral Statistics     Hybrid Journal   (Followers: 8)
Journal of Forecasting     Hybrid Journal   (Followers: 21)
Journal of Global Optimization     Hybrid Journal   (Followers: 7)
Journal of Mathematics and Statistics     Open Access   (Followers: 6)
Journal of Nonparametric Statistics     Hybrid Journal   (Followers: 7)
Journal of Risk and Uncertainty     Hybrid Journal   (Followers: 35)
Journal of Statistical Physics     Hybrid Journal   (Followers: 12)
Journal of Statistical Planning and Inference     Hybrid Journal   (Followers: 8)
Journal of Statistical Software     Open Access   (Followers: 19, SJR: 13.802, CiteScore: 16)
Journal of the American Statistical Association     Full-text available via subscription   (Followers: 78, SJR: 3.746, CiteScore: 2)
Journal of the Korean Statistical Society     Hybrid Journal   (Followers: 1)
Journal of the Royal Statistical Society Series C (Applied Statistics)     Hybrid Journal   (Followers: 37)
Journal of the Royal Statistical Society, Series A (Statistics in Society)     Hybrid Journal   (Followers: 31)
Journal of the Royal Statistical Society, Series B (Statistical Methodology)     Hybrid Journal   (Followers: 43)
Journal of Theoretical Probability     Hybrid Journal   (Followers: 3)
Journal of Time Series Analysis     Hybrid Journal   (Followers: 18)
Journal of Urbanism: International Research on Placemaking and Urban Sustainability     Hybrid Journal   (Followers: 28)
Law, Probability and Risk     Hybrid Journal   (Followers: 8)
Lifetime Data Analysis     Hybrid Journal   (Followers: 5)
Mathematical Methods of Statistics     Hybrid Journal   (Followers: 4)
Measurement Interdisciplinary Research and Perspectives     Hybrid Journal   (Followers: 1)
Metrika     Hybrid Journal   (Followers: 4)
Monthly Statistics of International Trade - Statistiques mensuelles du commerce international     Full-text available via subscription   (Followers: 4)
Multivariate Behavioral Research     Hybrid Journal   (Followers: 9)
Optimization Letters     Hybrid Journal   (Followers: 2)
Optimization Methods and Software     Hybrid Journal   (Followers: 5)
Oxford Bulletin of Economics and Statistics     Hybrid Journal   (Followers: 35)
Pharmaceutical Statistics     Hybrid Journal   (Followers: 10)
Queueing Systems     Hybrid Journal   (Followers: 7)
Research Synthesis Methods     Hybrid Journal   (Followers: 8)
Review of Socionetwork Strategies     Hybrid Journal  
Risk Management     Hybrid Journal   (Followers: 16)
Sankhya A     Hybrid Journal   (Followers: 3)
Scandinavian Journal of Statistics     Hybrid Journal   (Followers: 9)
Sequential Analysis: Design Methods and Applications     Hybrid Journal   (Followers: 1)
Significance     Hybrid Journal   (Followers: 6)
Sociological Methods & Research     Hybrid Journal   (Followers: 49)
SourceOECD Measuring Globalisation Statistics - SourceOCDE Mesurer la mondialisation - Base de donnees statistiques     Full-text available via subscription  
Stata Journal     Full-text available via subscription   (Followers: 10)
Statistica Neerlandica     Hybrid Journal   (Followers: 1)
Statistical Inference for Stochastic Processes     Hybrid Journal   (Followers: 3)
Statistical Methods and Applications     Hybrid Journal   (Followers: 5)
Statistical Methods in Medical Research     Hybrid Journal   (Followers: 25)
Statistical Modelling     Hybrid Journal   (Followers: 19)
Statistical Papers     Hybrid Journal   (Followers: 4)
Statistics & Probability Letters     Hybrid Journal   (Followers: 13)
Statistics and Computing     Hybrid Journal   (Followers: 14)
Statistics and Economics     Open Access  
Statistics in Medicine     Hybrid Journal   (Followers: 149)
Statistics: A Journal of Theoretical and Applied Statistics     Hybrid Journal   (Followers: 12)
Stochastic Models     Hybrid Journal   (Followers: 2)
Stochastics An International Journal of Probability and Stochastic Processes: formerly Stochastics and Stochastics Reports     Hybrid Journal   (Followers: 2)
Structural and Multidisciplinary Optimization     Hybrid Journal   (Followers: 12)
Teaching Statistics     Hybrid Journal   (Followers: 8)
Technology Innovations in Statistics Education (TISE)     Open Access   (Followers: 2)
TEST     Hybrid Journal   (Followers: 3)
The American Statistician     Full-text available via subscription   (Followers: 27)
The Canadian Journal of Statistics / La Revue Canadienne de Statistique     Hybrid Journal   (Followers: 10)
Wiley Interdisciplinary Reviews - Computational Statistics     Hybrid Journal   (Followers: 1)

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