Informatics最新文献

{"title":"Artificial Intelligence Chatbots in Chemical Information Seeking: Narrative Educational Insights via a SWOT Analysis","authors":"Johannes Pernaa, Topias Ikävalko, Aleksi Takala, Emmi Vuorio, Reija Pesonen, Outi Haatainen","doi":"10.3390/informatics11020020","DOIUrl":"https://doi.org/10.3390/informatics11020020","url":null,"abstract":"Artificial intelligence (AI) chatbots are next-word predictors built on large language models (LLMs). There is great interest within the educational field for this new technology because AI chatbots can be used to generate information. In this theoretical article, we provide educational insights into the possibilities and challenges of using AI chatbots. These insights were produced by designing chemical information-seeking activities for chemistry teacher education which were analyzed via the SWOT approach. The analysis revealed several internal and external possibilities and challenges. The key insight is that AI chatbots will change the way learners interact with information. For example, they enable the building of personal learning environments with ubiquitous access to information and AI tutors. Their ability to support chemistry learning is impressive. However, the processing of chemical information reveals the limitations of current AI chatbots not being able to process multimodal chemical information. There are also ethical issues to address. Despite the benefits, wider educational adoption will take time. The diffusion can be supported by integrating LLMs into curricula, relying on open-source solutions, and training teachers with modern information literacy skills. This research presents theory-grounded examples of how to support the development of modern information literacy skills in the context of chemistry teacher education.","PeriodicalId":37100,"journal":{"name":"Informatics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140686951","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}

{"title":"A Machine Learning as a Service (MLaaS) Approach to Improve Marketing Success","authors":"Ivo Pereira, Ana Madureira, Nuno Bettencourt, Duarte Coelho, M. Â. Rebelo, Carolina Araújo, Daniel Alves de Oliveira","doi":"10.3390/informatics11020019","DOIUrl":"https://doi.org/10.3390/informatics11020019","url":null,"abstract":"The exponential growth of data in the digital age has led to a significant demand for innovative approaches to assess data in a manner that is both effective and efficient. Machine Learning as a Service (MLaaS) is a category of services that offers considerable potential for organisations to extract valuable insights from their data while reducing the requirement for heavy technical expertise. This article explores the use of MLaaS within the realm of marketing applications. In this study, we provide a comprehensive analysis of MLaaS implementations and their benefits within the domain of marketing. Furthermore, we present a platform that possesses the capability to be customised and expanded to address marketing’s unique requirements. Three modules are introduced: Churn Prediction, One-2-One Product Recommendation, and Send Frequency Prediction. When applied to marketing, the proposed MLaaS system exhibits considerable promise for use in applications such as automated detection of client churn prior to its occurrence, individualised product recommendations, and send time optimisation. Our study revealed that AI-driven campaigns can improve both the Open Rate and Click Rate. This approach has the potential to enhance customer engagement and retention for businesses while enabling well-informed decisions by leveraging insights derived from consumer data. This work contributes to the existing body of research on MLaaS in marketing and offers practical insights for businesses seeking to utilise this approach to enhance their competitive edge in the contemporary data-oriented marketplace.","PeriodicalId":37100,"journal":{"name":"Informatics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140699488","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}

{"title":"Variations in Pattern of Social Media Engagement between Individuals with Chronic Conditions and Mental Health Conditions","authors":"Elizabeth Ayangunna, Gulzar Shah, Kingsley Kalu, Padmini Shankar, Bushra Shah","doi":"10.3390/informatics11020018","DOIUrl":"https://doi.org/10.3390/informatics11020018","url":null,"abstract":"The use of the internet and supported apps is at historically unprecedented levels for the exchange of health information. The increasing use of the internet and social media platforms can affect patients’ health behavior. This study aims to assess the variations in patterns of social media engagement between individuals diagnosed with either chronic diseases or mental health conditions. Data from four iterations of the Health Information National Trends Survey Cycle 4 from 2017 to 2020 were used for this study with a sample size (N) = 16,092. To analyze the association between the independent variables, reflecting the presence of chronic conditions or mental health conditions, and various levels of social media engagement, descriptive statistics and logistic regression were conducted. Respondents who had at least one chronic condition were more likely to join an internet-based support group (Adjusted Odds Ratio or AOR = 1.5; Confidence Interval, CI = 1.11–1.93) and watch a health-related video on YouTube (AOR = 1.2; CI = 1.01–1.36); respondents with a mental condition were less likely to visit and share health information on social media, join an internet-based support group, and watch a health-related video on YouTube. Race, age, and educational level also influence the choice to watch a health-related video on YouTube. Understanding the pattern of engagement with health-related content on social media and how their online behavior differs based on the patient’s medical conditions can lead to the development of more effective and tailored public health interventions that leverage social media platforms.","PeriodicalId":37100,"journal":{"name":"Informatics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140706342","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}

{"title":"Governors in the Digital Era: Analyzing and Predicting Social Media Engagement Using Machine Learning during the COVID-19 Pandemic in Japan","authors":"Salama Shady, Vera Paola Shoda, Takashi Kamihigashi","doi":"10.3390/informatics11020017","DOIUrl":"https://doi.org/10.3390/informatics11020017","url":null,"abstract":"This paper presents a comprehensive analysis of the social media posts of prefectural governors in Japan during the COVID-19 pandemic. It investigates the correlation between social media activity levels, governors’ characteristics, and engagement metrics. To predict citizen engagement of a specific tweet, machine learning models (MLMs) are trained using three feature sets. The first set includes variables representing profile- and tweet-related features. The second set incorporates word embeddings from three popular models, while the third set combines the first set with one of the embeddings. Additionally, seven classifiers are employed. The best-performing model utilizes the first feature set with FastText embedding and the XGBoost classifier. This study aims to collect governors’ COVID-19-related tweets, analyze engagement metrics, investigate correlations with governors’ characteristics, examine tweet-related features, and train MLMs for prediction. This paper’s main contributions are twofold. Firstly, it offers an analysis of social media engagement by prefectural governors during the COVID-19 pandemic, shedding light on their communication strategies and citizen engagement outcomes. Secondly, it explores the effectiveness of MLMs and word embeddings in predicting tweet engagement, providing practical implications for policymakers in crisis communication. The findings emphasize the importance of social media engagement for effective governance and provide insights into factors influencing citizen engagement.","PeriodicalId":37100,"journal":{"name":"Informatics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140733767","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}

{"title":"Detecting Structured Query Language Injections in Web Microservices Using Machine Learning","authors":"Edwin Peralta-Garcia, Juan Quevedo-Monsalbe, Victor Tuesta-Monteza, Juan Arcila-Diaz","doi":"10.3390/informatics11020015","DOIUrl":"https://doi.org/10.3390/informatics11020015","url":null,"abstract":"Structured Query Language (SQL) injections pose a constant threat to web services, highlighting the need for efficient detection to address this vulnerability. This study compares machine learning algorithms for detecting SQL injections in web microservices trained using a public dataset of 22,764 records. Additionally, a software architecture based on the microservices approach was implemented, in which trained models and the web application were deployed to validate requests and detect attacks. A literature review was conducted to identify types of SQL injections and machine learning algorithms. The results of random forest, decision tree, and support vector machine were compared for detecting SQL injections. The findings show that random forest outperforms with a precision and accuracy of 99%, a recall of 97%, and an F1 score of 98%. In contrast, decision tree achieved a precision of 92%, a recall of 86%, and an F1 score of 97%. Support Vector Machine (SVM) presented an accuracy, precision, and F1 score of 98%, with a recall of 97%.","PeriodicalId":37100,"journal":{"name":"Informatics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140755323","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}

{"title":"Loan classification using a feed-forward neural network","authors":"U. I. Behunkou","doi":"10.37661/1816-0301-2024-21-1-83-104","DOIUrl":"https://doi.org/10.37661/1816-0301-2024-21-1-83-104","url":null,"abstract":"Objectives. The purpose of the study is to construct and study the use of a feed-forward neural network to solve the problem of loan classification, as well as to conduct a comparative analysis of the neural networkbased approach with the existing approach based on logistic regression.Methods. Based on a feed-forward neural network using historical data on loans issued, the following metrics are calculated: cost function, Accuracy, Precision, Recall, and measure, calculated on Precision and Recall values. Polynomial parameters and the principal component method are used to determine the optimal set of input data for the studied neural network.Results. The impact of data normalization on the final result was analyzed, the influence of the number of units in the hidden layer on the outcome was evaluated using a two-stage method and the Monte Carlo method, the effect of balanced data use was determined, the optimal threshold value for output layer of the neural network under investigation was calculated, the optimal activation function for the hidden layer units was found, the effect of increasing input indicators through missing values imputation and the use of polynomials of varying degrees was studied and the redundancy in the existing set of input indicators was analyzed.Conclusion. Based on the results of the research, we can conclude that the use of a direct distribution network to solve problems of loan classification is appropriate. Compared to logistic regression, implementing a solution using a feed-forward neural network requires more time and computing resources. However, the obtained most important values of Accuracy and measure are higher than those calculated using logistic regression [1].","PeriodicalId":37100,"journal":{"name":"Informatics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140368194","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}

{"title":"System of complex data analysis of thematic sites ISCAD IS","authors":"I. I. Piletski, M. P. Batura, N. A. Volоrоva, P. A. Zorko, A. O. Kulevich","doi":"10.37661/1816-0301-2024-21-1-105-120","DOIUrl":"https://doi.org/10.37661/1816-0301-2024-21-1-105-120","url":null,"abstract":"Objectives. Currently, the main source of information is the Internet. The huge amount of information available on the Internet makes it urgent to comprehensively analyze data from open Internet sources.The goal of this work is to create a multi-purpose, modifiable cluster for in-depth analysis of data from Internet sources, the main objectives of which are to identify the most important publications in a certain subject area, thematic analysis of these publications, identifying the leader of a scientific direction and determining trends in the development of areas and interaction of groups of people.Methods. To solve this problem, a methodology was developed for constructing a multi-purpose cluster using technologies for quickly constructing a thematic graph database, a knowledge graph, methods and models of machine learning for in-depth analysis of data.Results. A system for comprehensive analysis of data from thematic sites ISKAD IS has been developed, a methodology for quickly constructing a thematic graph database and a comprehensive technology for in-depth analysis of data from Internet sources and analysis of data from the most important well-known world sites have been tested.Conclusion. An IT environment has been created for the rapid construction of thematic graph databases. The results of using the technology for quickly constructing graph databases are shown using examples of the work of ISKAD IS.","PeriodicalId":37100,"journal":{"name":"Informatics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140368149","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}

{"title":"Prediction and decision-making based on nonlinear risks model in stomach cancer treatment","authors":"O. Krasko, M. Reutovich, A. Ivanov","doi":"10.37661/1816-0301-2024-21-1-65-82","DOIUrl":"https://doi.org/10.37661/1816-0301-2024-21-1-65-82","url":null,"abstract":"Objectives. The goals are to develop a nonlinear risk model and examine its prediction applicability for clinical use.Methods. Methods of survival analysis and regression statistical models were used.Results. A practical approach to assessing nonlinear risks of adverse events using the example of gastric cancer treatment is proposed. A model for predicting the metachronous peritoneal dissemination in patients undergoing radical surgery for gastric cancer was proposed and studied. Assessment of risks for various periods of observation was performed, and the clinical suitability of developed approach was assessed.Conclusion. In clinical oncological practice, not only timely treatment plays an important role, but also the prevention of adverse outcomes after treatment. Individualization of patient monitoring after treatment reduces the risks of fatal outcomes and the costs of additional research and treatment in the event of cancer progression. Based on the results of this study, we propose solutions that should lead to more effective and high-quality treatment tactics and follow-up after treatment for gastric cancer, also to the selection of optimal approaches and to obtaining clinically favorable outcomes of the disease. The proposed risk prediction method will ultimately lead to individualized patient management based on the results of personal data.","PeriodicalId":37100,"journal":{"name":"Informatics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140365401","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}

{"title":"Symmetric physically unclonable functions of the arbiter type","authors":"V. N. Yarmolik, A. A. Ivaniuk","doi":"10.37661/1816-0301-2024-21-1-9-27","DOIUrl":"https://doi.org/10.37661/1816-0301-2024-21-1-9-27","url":null,"abstract":"Objectives. The problem of constructing a new class of physically unclonable functions of the arbiter type (APUF) that combines the advantages of both classical and balanced APUF is solved. The relevance of such a study is associated with the active development of physical cryptography. The following goals are pursued in the work: research and analysis of classical APUF, construction of a new mathematical model of APUF and development of a new basic element of APUF.Methods. The methods of synthesis and analysis of digital devices are used, including those based on programmable logic integrated circuits, the basics of Boolean algebra and circuitry.Results. It has been established that classical APUF uses a standard basic element that performs three functions, namely, the function of generating two random variables Generate, the function of choosing a pair of paths Select and the function of switching paths Switch, which are specified by one bit of the challenge. It is shown that the joint use of these functions, on the one hand, makes it possible to achieve high characteristics of the APUF, and on the other hand, leads to the formation of an asymmetric behavior of the APUF. In order to analyze the main characteristics of APUF and their ideal behavior, a new mathematical model of APUF was considered, similar to the model of random coin toss. To implement APUF functioning according to the proposed model, a new basic element was developed. It is shown that the use of the proposed basic element allows to build symmetrical physically unclonable functions (C_APUF), which differ from the classical APUF in that the Generate, Select and Switch functions of the basic element are performed by their independent components and are specified by different bits of challenge.Conclusion. The proposed approach to the construction of symmetrical physically unclonable functions, based on the implementation of the Generate, Select and Switch functions by various components of the base element, has shown its efficiency and promise. The effect of improving the characteristics of similar C_APUF has been experimentally confirmed, and, first of all, a noticeable improvement in their probabilistic properties expressed in equal probability of responses. It seems promising to further develop the ideas of building C_APUF, experimental study of their characteristics, as well as analysis of resistance to various types of attacks, including using machine learning.","PeriodicalId":37100,"journal":{"name":"Informatics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140368346","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}

{"title":"Algorithm for estimating the absolute total electron content of the ionosphere from dual-frequency phase and range satellite measurements","authors":"A. S. Shapkin","doi":"10.37661/1816-0301-2024-21-1-48-64","DOIUrl":"https://doi.org/10.37661/1816-0301-2024-21-1-48-64","url":null,"abstract":"Objectives. The problem of developing an algorithm for estimating the absolute total electron content of the ionosphere from dual-frequency phase and range satellite measurements for a single receiving station of global navigation satellite systems is being solved.Methods. To obtain an estimate the phase measurement data are corrected using digital signal processing methods, well known total electron content formulas for phase and range measurements are applied and combined, and also the differential code bias of the receiving station is estimated using the least squares method.Results. It is shown that the total electron content calculated from phase measurements provides high accuracy, but up to an unknown constant, but the content calculated from range measurements allows one to obtain the absolute value, but with a large noise component and differential code bias of a satellite and receiver equipment. An algorithm for estimating the absolute total electron content of the ionosphere has been developed, its description and diagram are given. The algorithm was used to estimate the total electronic content within six months of observations, and the average error of the resulting estimate was calculated.Conclusion. The developed algorithm can be used to estimate the absolute total electron content of the ionosphere for a single receiving station of global navigation satellite systems. In contrast to theoretically known formulas for phase and range measurements, this article contains information about adjusting phase measurements and estimating the differential code delay of receiving station. Further research may be related to the adaptive selection of parameters and testing of the algorithm for working with nanosatellites of the CubeSat format.","PeriodicalId":37100,"journal":{"name":"Informatics","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140367316","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}