Intelligent Program Research Articles

Real-time detection of acromegaly from facial images with artificial intelligence.

Despite improvements in diagnostic methods, acromegaly is still a late-diagnosed disease. In this study, it was aimed to automatically recognize acromegaly disease from facial images by using deep learning methods and to facilitate the detection of the disease. Cross-sectional, single-centre study. The study included 77 acromegaly (52.56 ± 11.74, 34 males/43 females) patients and 71 healthy controls (48.47 ± 8.91, 39 males/32 females), considering gender and age compatibility. At the time of the photography, 56/77 (73%) of the acromegaly patients were in remission. Normalized images were obtained by scaling, aligning, and cropping video frames. Three architectures named ResNet50, DenseNet121, and InceptionV3 were used for the transfer learning-based convolutional neural network (CNN) model developed to classify face images as "Healthy" or "Acromegaly". Additionally, we trained and integrated these CNN machine learning methods to create an Ensemble Method (EM) for facial detection of acromegaly. The positive predictive values obtained for acromegaly with the ResNet50, DenseNet121, InceptionV3, and EM were calculated as 0.958, 0.965, 0.962, and 0.997, respectively. The average sensitivity, specificity, precision, and correlation coefficient values calculated for each of the ResNet50, DenseNet121, and InceptionV3 models are quite close. On the other hand, EM outperformed these three CNN architectures and provided the best overall performance in terms of sensitivity, specificity, accuracy, and precision as 0.997, 0.997, 0.997, and 0.998, respectively. The present study provided evidence that the proposed AcroEnsemble Model might detect acromegaly from facial images with high performance. This highlights that artificial intelligence programs are promising methods for detecting acromegaly in the future.

A cognitive design assistant for context-aware computer-aided design

Computer-Aided Design (CAD) plays a crucial role throughout a product's life cycle, especially regarding detecting design errors early on. To date, for complex engineered systems, the detection of design errors in a digital mock-up. It is a reactive and laborious activity that requires a complete CAD design before searching for applicable design rules in a set of large and unstructured design guidelines containing hundreds or thousands of design rules and making sure that the design complies with the applicable rules. This paper will illustrate how a context-aware cognitive design assistant, a seamless, ubiquitous and intelligent computer program, can sense relevant data of a CAD context to provide, without explicit user intervention, proactive and on-the-fly recommendations of relevant design rules, where relevancy depends on the designer's task. To illustrate the feasibility of the proposal, the cognitive design assistant will be integrated with the 3DExperience CAD software. The functional demonstrator shows that this proactive approach will not only reduce design iterations usually due to a-posteriori checks but also deal with any kind of design rules rather than a specific set of geometry and topology constraints verified by design checkers based on IF-ELSE instructions.

Research solutions for IoT applications in the construction of intelligent logic programming devices for measurement and control systems

This article is aimed at researching IoT technology and specific applications. On that basis, build an intelligent logic programming device capable of performing automation, measurement, and control problems in today's technology trend. From there, giving simple instructions and helping users easily realize their control measurement problems in a completely new, intuitive, and effective way.

Determining the reliability of diagnosis and treatment using artificial intelligence software with panoramic radiographs.

The objective of this study was to evaluate the accuracy and effectiveness of an artificial intelligence (AI) program in identifying dental conditions using panoramic radiographs (PRs), as well as to assess the appropriateness of its treatment recommendations. PRs from 100 patients (representing 4497 teeth) with known clinical examination findings were randomly selected from a university database. Three dentomaxillofacial radiologists and the Diagnocat AI software evaluated these PRs. The evaluations were focused on various dental conditions and treatments, including canal filling, caries, cast post and core, dental calculus, fillings, furcation lesions, implants, lack of interproximal tooth contact, open margins, overhangs, periapical lesions, periodontal bone loss, short fillings, voids in root fillings, overfillings, pontics, root fragments, impacted teeth, artificial crowns, missing teeth, and healthy teeth. The AI demonstrated almost perfect agreement (exceeding 0.81) in most of the assessments when compared to the ground truth. The sensitivity was very high (above 0.8) for the evaluation of healthy teeth, artificial crowns, dental calculus, missing teeth, fillings, lack of interproximal contact, periodontal bone loss, and implants. However, the sensitivity was low for the assessment of caries, periapical lesions, pontic voids in the root canal, and overhangs. Despite the limitations of this study, the synthesized data suggest that AI-based decision support systems can serve as a valuable tool in detecting dental conditions, when used with PR for clinical dental applications.

Land Use and Urban Sprawl in the Case of the City of Rabat in Morocco: An Integrated Approach Using Remote Sensing, Geospatial Modeling, and Machine Learning

This document is produced as part of a project of mapping, monitoring and prediction of urban sprawl in the city of Rabat, using algorithms of machine Learning, remote sensing and geographic information system. It therefore aims to determine and monitor the urban sprawl of the city of Rabat, using new Geo-spatial technologies, this socio-economic mechanism is theoretically based on the increase in the horizontal area of the city, and a decrease in population density. On the contrary, the city of Rabat is characterized by a negative growth rate between the years 2004-2014 at about -0.79% different from 1.2% at the national level, and defined by a higher population density of 255 inhabitants per km2, these statistics were directed to a hypothesis that indicates a horizontal confinement of the city of Rabat and reverse immigration to per-urban territories. In addition, this project is mainly aimed at the implementation of a computerized simulation model for the characterization and prediction of the urban expansion of the city of Rabat for 40 years (1990, 2000, 2010, 2020, 2030). To conclude, the city of Rabat has experienced a very slow urban sprawl, thanks to the green belt put in 1971, and the modernization strategy that has been adapted in recent years to eliminate informal housing, in addition to the development of roads and the new TGV railway line, and also to the lack of land use, of which many large villas of several hectares were built. Although this mechanism is moving very slowly, the city of Rabat has had negative consequences on the territory and the environment. So, local authorities need a creative, innovative and intelligent urban planning programme to both eliminate the effects of this mechanism, and build the pillars of the functional city (smart city).

КОНЦЕПТУАЛЬНІ ЗАСАДИ «ОСОБЛИВИХ ВІДНОСИН» США ТА ВЕЛИКОЇ БРИТАНІЇ

The aim of this article is to shed light on the phenomenon of «special relations» between the United States of America and Great Britain. Despite the fact that the topic gained considerable attention in the academic literature and the term «special relations» is applied to different states and regions, it is necessary to understand its origins. The purpose of the article is to investigate the phenomenon of American-British relations, to analyze the historical and political view of the problem, and to formulate the characteristics of the relations between the United States and the United Kingdom. Chronological limits are determined by the first mention of the term in 1946 and the presidential term of D.Trump, who managed the office in 2017–2021. Methodology of the article. Hypotheses were tested through historiographical analysis and the historical-comparative method were used to analyze published studies on the history of «special relations». The scientific novelty of the study consists in determining the peculiarities of relations between the United States and Great Britain during the tenure of Donald Trump. Therefore, the «special relationship» is a unique historically formed complex of interaction between the USA and Great Britain, which is manifested in various spheres of public life: political (to have an opportunity for better implementation of their own foreign policy), military (the USA and the United Kingdom have an unprecedented level of mutual trust and cooperation in the field of intelligence and nuclear programs), cultural (the historical memory of both nations makes American and British society sensitive to the problems of their «English-speaking neighbours»). We consider it necessary to highlight the following features of American-British relations:the long-term historical interaction that brought the two nations closer together and laid the foundation for relations between the United States and Great Britain; the common ideology of liberalism; cooperation provides an opportunity to better implement one’s own foreign policy; close relations between political figures of states; relations are characterized by periodic «approaching and distancing», which create new challenges for the allies. Each of these features is traced in the relations between the USA and Great Britain and during the administration of Donald Trump. Both states faced a number of challenges in international politics, due to the crisis state of the modern system of international relations. The governments of the United States and the United Kingdom have demonstrated the ability to compromise in critical situations, that proves the uniqueness of such an alliance.

American Intelligence and Belarusian Emigration against Soviet Byelorussia during the Cold War

By the end of the Second World War, about 200 thousand Belarusians ended up as refugees in Western Europe. A significant part of them were repatriated to the Soviet Union, more than one thousand moved to the USA, another fifteen hundred — to other non-European countries. In 1951, the number of Belarusians remaining in Europe was sixty thousand people. Belarusian emigration, as well as the emigration from other Soviet Republics, immediately came to the attention of the US Central Intelligence Agency within the framework of a document developed in 1948 by the State Department entitled “Utilization of Refugees from the Soviet Union in U. S. National Interests”, which was supposed to “fill in the niches in our current intelligence, in public information, and in our politico-psychological operations”. The Central Intelligence Agency was supposed to develop and quite generously finance the intelligence and propaganda projects and programs important for the agency. The leadership of the Rada of the Belarusian People’s Republic (in exile) headed by its chairman Nikolai Abramchik was to be responsible for staffing the necessary number of agents from among the emigrant Belarusian youth to infiltrate into Belarus and for distributing information among the national European emigration. However, this did not cause any expected “resistance movement” within the Byelorussian Soviet Socialist Republic contrary to the intended actions of the Central Intelligence Agency and the Rada. By the end of 1961, the projects of the Central Intelligence Agency in Belarus conducted since 1951, including the most famous AEQUOR, which involved infiltrating agents into the territory of the republic, were closed.

БАЗА ЗНАНЬ ІНТЕЛЕКТУАЛЬНОЇ ІНФОРМАЦІЙНОЇ СИСТЕМИ ПРОГНОЗУВАННЯ ФАЗОВОЇ СТАБІЛЬНОСТІ ТВЕРДИХ РОЗЧИНІВ

This research work is devoted to the development of a knowledge base for solving the current problem of forecasting the phase stability of solid solutions. Knowledge bases mean a set of facts and inference rules that allow logical conclusion and purposeful processing of information. The most important property of information stored in knowledge bases is the reliability of specific and generalized information in the database and the relevance of the original information obtained using the rules of inference embedded in the knowledge base. The best knowledge bases include the most relevant, reliable and fresh information, have perfect information search systems, a carefully thought-out structure and format of knowledge. The expert system embodies the methodology of adapting the algorithm of successful solutions from one sphere of scientific and practical activity to another. With the spread of computer technologies, it is an identical intelligent computer program that contains the knowledge and analytical abilities of one or more experts in some field of application and is able to draw logical conclusions based on this knowledge, thereby providing a solution to specific tasks. An intelligent information system (IIS) is one of the types of automated information systems, which is a complex of software, linguistic and logical-mathematical tools for the implementation of the main task, which usually consists of data interpretation and forecasting. Data interpretation is one of the traditional tasks for expert systems. Interpretation means the process of determining the content of data, the results of which must be agreed and correct. A multivariate analysis of the data is usually assumed, and the findings from this model form the basis for probabilistic estimates. Forecasting allows you to predict the consequences of some events or phenomena based on the analysis of available data. A parametric dynamic model is usually used in the forecasting system, in which parameter values are set for a given situation. As a result of the development, a knowledge base model was built for predicting the phase stability of solid solutions using a set of production rules, predicates, functions and operators.

Bone Age Estimation and Prediction of Final Adult Height Using Deep Learning.

The appropriate evaluation of height and accurate estimation of bone age are crucial for proper assessment of the growth status of a child. We developed a bone age estimation program using a deep learning algorithm and established a model to predict the final adult height of Korean children. A total of 1678 radiographs from 866 children, for which the interpretation results were consistent between two pediatric endocrinologists, were used to train and validate the deep learning model. The bone age estimation algorithm was based on the convolutional neural network of the deep learning system. The test set simulation was performed by a deep learning program and two raters using 150 radiographs and final height data for 100 adults. There was a statistically significant correlation between bone age interpreted by the artificial intelligence (AI) program and the reference bone age in the test set simulation (r=0.99, p<0.001). In the test set simulation, the AI program showed a mean absolute error (MAE) of 0.59 years and a root mean squared error (RMSE) of 0.55 years, compared with reference bone age, and showed similar accuracy to that of an experienced pediatric endocrinologist (rater 1). Prediction of final adult height by the AI program showed an MAE of 4.62 cm, compared with the actual final adult height. We developed a bone age estimation program based on a deep learning algorithm. The AI-derived program demonstrated high accuracy in estimating bone age and predicting the final adult height of Korean children and adolescents.

Artificial intelligence and psychiatry: questions from psychiatrists to ChatGPT

Psychiatrists and psychotherapists specialising in the fields of addiction, personality disorders, ADHD and suicidal crisis, we questioned the ChatGPT artificial intelligence program in order to form an opinion on the quality of its answers to questions on these subjects. Our aim is to satisfy our curiosity about these emerging tools. On the other hand, we want to assess the relevance of the answers in order to know whether relatives and patients can use them safely. In this article, we comment on the question-and-answer dialogue with the artificial intelligence program in the light of the literature.

Exploring the Use of Artificial Intelligence for Qualitative Data Analysis: The Case of ChatGPT

The potential use of artificial intelligence programs such as a ChatGPT to analyze qualitative data raises any number of questions, most notably whether it is possible to produce similar results without the demanding process of manual coding. In addition, there are questions about both the simplicity of using ChatGPT for qualitative data analysis and the potential time savings that it might provide This article addresses these questions by using ChatGPT to reinvestigate two qualitative datasets that were previously analyzed by more traditional methods. In particular, it examines the extent to which the responses from ChatGPT can recreate the themes that were originally chosen to summarize the two previous analyses. The results show that ChatGPT performed reasonably well, but in both cases it was less successful at locating subtle, interpretive themes, and more successful at reproducing concrete, descriptive themes. In doing so, the program was quite easy to use and required very little effort in comparison to approaches that rely on manual coding. It is important to recognize, however, that both coding and approaches based on artificial intelligence are simply tools that must be applied within a larger analytic process. Overall, this exploration suggests that artificial intelligence may well have the power to disrupt the coding of data segments as a dominant paradigm for qualitative data analysis.

ТЕНДЕНЦІЇ РОЗВИТКУ ВІТЧИЗНЯНОЇ МЕДІАІНДУСТРІЇ

The media industry is an important element of the information society and an integral part of the national economic system, which provides the public need for communication services and, in particular, such a resource as current information. As a component of the business environment, it ensures the production and distribution of media products and advertising. The media industry is characterized by the rapid pace of transformation of its structural components and the uneven dynamics of this process. The article considers the factors that will influence the development of both the global and domestic media industry. The main ones are: changes in the structure of consumption towards an increase in the share of digital media products, the appearance on the global market of new producers of media products, the development of media corporations, an increase in the advertising budgets of the share of Internet sources and online commerce, Internet security and legal regulation of relations with digital platforms, changing the speed of content creation due to the rapid development of technologies and artificial intelligence programs. The article notes that the adoption of the Law of Ukraine "On Media", in which the regulation of this sphere is coordinated with the relevant EU directives, should streamline organizational and legal relations in the media sphere and will contribute to updating its structure. The changes that took place in certain segments of the media market are highlighted. The television market of Ukraine was characterized by the concentration of TV channels in media holdings, and its structural and technical changes are related to the transition of television to digital broadcasting, the coding of satellite signals of TV channels, and the banning of a number of TV channels. The radio market saw a decline in the popularity of over-the-air radio and an increase in online consumption, with three quarters of the market divided between four radio groups. The publishing market is characterized by a reduction in the range of printed publications and their circulations, and the segment of periodicals is characterized by an accelerated transition to their electronic versions. The study of the changes that have taken place in the media sphere since the full-scale military invasion revealed their main factors, including: changes in infrastructure and reduction in coverage of the territory of Ukraine, reduction of the audience, changes in consumer preferences of target audiences, deterioration of the financial situation, etc. The further transformation of the media industry will be its reaction to the appearance of new challenges in the external environment.

S-47-3: APPLICATION OF AI FOR SCREENING CARDIOVASCULAR DISEASE

Recent advancements in information technologies and computer science brought dramatic changes not only in the field of business but also in the field of medicine. By analyzing big data using artificial intelligence techniques, especially deep learning, computers now have similar or even better diagnostic performance than trained physicians in medical image interpretation. In addition to their speed, reproducibility, and tirelessness, these artificial intelligence programs are starting to reveal their possibility to find hidden information from medical images. For example, studies have shown that not only present arrhythmias but also the presence of myocardial dysfunction and latent arrhythmias can be found in a body-surface ECG. Given the extremely high prevalence of hypertension worldwide, screening the cardiovascular risk in all patients with hypertension has not been realistic so far. However, such artificial intelligence may become a wider and more ubiquitous tool for the general screening of cardiovascular risk. Furthermore, big data generated from digital tools surrounding our daily life, such as laptops, smartphones, and smartwatches may provide further information regarding healthy or risky lifestyles, with which the risk stratification can be personalized. Thus, the current achievement in the application of artificial intelligence technologies in medicine and future perspective in regard to cardiovascular risk screening in patients with hypertension will be summarized in the talk.

Implementation of the General Data Protection Regulation in Romania: problems, perspectives, solutions

In the context of the accelerated development of new technologies and the evolution of artificial intelligence programs, in the context of more and more discussions related to the digitization of public services, interoperability, cross-border data transfer, Big Data, fake news, deep fake, hybrid warfare and cyberattacks we must admit that it is necessary to find quickly solutions to give to all data subjects the right to have control over their personal data. Legislative solutions are not enough. Can a state, through a correct, coherent, constant information of citizens and their institutionalized training in the field of privacy protection to reach through prevention, to ensure effective protection of personal data? Using comparative analysis as a research method, we have identified good practices of implementing GDPR in several European countries. The results obtained through the analysis of the data collected by the open-ended questionnaire and the interview research methods revealed to us the real needs of the Romanian citizens. Having good practices models for implementing GDPR in several European countries and the real needs of the population regarding the data protection field, we aim to provide solutions to improve the implementation of the GDPR in Romania.

ИСКУССТВЕННЫЙ ИНТЕЛЛЕКТ В КОНТРОЛЕ И УПРАВЛЕНИИ ФИНАНСАМИ КОРПОРАЦИИ

A technique has been developed for obtaining data on the financial and economic state of enterprises of a given corporation, conducting their analysis and establishing corporate financial management strategies using mathematical models, numerical methods, and artificial intelligence programs. The technique has been tested on the example of management strategies selection for enterprises of the Abrau-Durso Group, using the recommender program of the IGLA decision support system.

We asked Chat GPT to describe brain fog in chronic pain: What did we learn?

Chat GPT is a modern artificial intelligence program: its recent introduction has created controversy in the academic world. This commentary discusses the utility of Chat GPT to explore healthcare issues such as chronic pain and associated conditions. To illustrate the potential application of brain fog, this commentary presents an example of Chat GPT using brain fog. Brain fog is a phenomenon which has been increasingly discussed in both academic and social media discourses. Further, the potential advantages and dangers of Chat GPT are described. Noted advantages include search facilitation, drafting patient information, identifying opportunities for future research, and highlighting areas with a lack of consensus. Dangers of Chat GPT include the possibility for misinformation and the reproduction of social stereotypes and assumptions. Lastly, this commentary concludes with recommendations for healthcare professionals considering use of Chat GPT. Artificial intelligence-driven technologies like Chat GPT become increasingly available and trusted in our society, so does the importance of our awareness for both benefit and potential for harm when artificial intelligence is used for non-critical information seeking and self-education.

ПРАВОВЫЕ ВОПРОСЫ ВНЕДРЕНИЯ СОВРЕМЕННЫХ ИНФОРМАЦИОННЫХ СИСТЕМ В ОБРАЗОВАТЕЛЬНЫЙ ПРОЦЕСС (на примере творческих вузов)

2023 has become a significant year in the development of the IT industry in the Russian Federation. Within the Federal project “Digital Public Administration” of the national programme “Digital Economy of the Russian Federation”, activities are being carried out to digitally transform state and municipal services. First of all, the Superservice programme was launched. The Superservice University Admission system has certain advantages. It is one of a whole list of proposed implementation programmes in various areas of the economy and public administration, developed by domestic companies. At the same time, programmes positioning themselves as artificial intelligence programmes are being actively introduced into the environment. Especially it concerns the Chat GPT and the Midjourney programme. Various research methods are used in the study of neural network data, including: data mining methods, statistical analysis, data visualization and machine learning, model comparison methods, comparison of different models based on their performance and other criteria, etc. In addition, a large number of legal issues arise when implementing these systems. This applies to a greater extent to the introduction of neural networks as part of artificial intelligence. These are such issues as copyright, protection and security issues, liability for errors and damage, etc. This article is devoted to the problems of implementation.

How To Grade Law Students Taking 'Paper Classes' Given Student Access to Artificial Intelligence Programs: Some Preliminary Thoughts

How To Grade Law Students Taking 'Paper Classes' Given Student Access to Artificial Intelligence Programs: Some Preliminary Thoughts

Innovative IoT-Based Wristlet for Early COVID-19 Detection and Monitoring Among Students

The current global issue of the COVID-19 pandemic has prompted the push and utilization of all available means to halt its spread. COVID-19 is a highly infectious disease, and continuously monitoring early symptoms could help avert catastrophic devastation. This paper proposes an innovative use of the Internet of Things (IoT) enabled system to efficiently and effectively detect early COVID-19 signs at a relatively low cost. This study adopted an experimental approach in designing and constructing a low-cost hardware system using a Wi-Fi enabled microcontroller, a temperature sensor, and a heart rate sensor for students. The proposed system detected and distinguished normal and abnormal temperature, regular and irregular heartbeat and constantly displayed the student's status in a mobile application. Consistent tests proved that the developed IoT-enabled system was reliable, responsive, and cost-effective. The mass production of this device will aid in the early detection of the disease, thereby mitigating the spread among students, particularly in underdeveloped countries. The paper's merit stems from the microcontroller's intelligence programming and the sensor's operation via the mobile application, which enables low-cost early identification of abnormal temperature and heartbeat irregularities.

An accessible infrastructure for artificial intelligence using a Docker-based JupyterLab in Galaxy.

Artificial intelligence (AI) programs that train on large datasets require powerful compute infrastructure consisting of several CPU cores and GPUs. JupyterLab provides an excellent framework for developing AI programs, but it needs to be hosted on such an infrastructure to enable faster training of AI programs using parallel computing. An open-source, docker-based, and GPU-enabled JupyterLab infrastructure is developed that runs on the public compute infrastructure of Galaxy Europe consisting of thousands of CPU cores, many GPUs, and several petabytes of storage to rapidly prototype and develop end-to-end AI projects. Using a JupyterLab notebook, long-running AI model training programs can also be executed remotely to create trained models, represented in open neural network exchange (ONNX) format, and other output datasets in Galaxy. Other features include Git integration for version control, the option of creating and executing pipelines of notebooks, and multiple dashboards and packages for monitoring compute resources and visualization, respectively. These features make JupyterLab in Galaxy Europe highly suitable for creating and managing AI projects. A recent scientific publication that predicts infected regions in COVID-19 computed tomography scan images is reproduced using various features of JupyterLab on Galaxy Europe. In addition, ColabFold, a faster implementation of AlphaFold2, is accessed in JupyterLab to predict the 3-dimensional structure of protein sequences. JupyterLab is accessible in 2 ways-one as an interactive Galaxy tool and the other by running the underlying Docker container. In both ways, long-running training can be executed on Galaxy's compute infrastructure. Scripts to create the Docker container are available under MIT license at https://github.com/usegalaxy-eu/gpu-jupyterlab-docker.