Methodology For Creation Research Articles

Features of the methodological views of Rizaetdin Fakhretdinov (1859-1936) on the concept of ijma‘

This article is devoted to the study of the nature and essence of one of the fundamental sources of Islamic Law - ijma‘ in the methodological views of the Qadi and the Mufti of the Central Spiritual Administration of Muslims of Russia Rizaetdin Fakhretdinov (1859-1936). The conceptual features of Fakhretdinov’s characteristic views on the nature of ijma‘, its essence, the conditions of its emergence and the specifics of its practical adaptation allowed him to raise important questions regarding the competence of participants making a consolidated decision, the categoricalness and duration of the legal force of such decisions. His views on the institutionalization of ijma‘ may indicate the presence of regional competence of ijma‘ representatives. The study of ijma‘ was carried out on the basis of an analysis of Fakhretdinov’s views with the views of classical methodologists (usuliyyun), during which the author attempts to substantiate them within the framework of Hanafi methodological thought. The article is intended to make a modest contribution to the study of the nature of ijma‘ and its role in the religious and legal life of Muslims. The nature of the article is also on rethinking the assessment of the classical heritage of fiqh, the development of a critical and practice-oriented approach in individual and collegial forms of the methodology of fatwa creation. Moreover, the paper means to attract the attention of modern researchers in the field of methodology to these issues within the Islamic Law.

An optimization framework to provide volunteers with task selection autonomy and group opportunities

Nonprofit Organizations (NPOs) rely on volunteers to support community needs but struggle with making strategic volunteer-to-task assignments to enable volunteer satisfaction, and completion of complex tasks. Creation of volunteer groups and their assignment to NPO tasks can help achieve these goals by providing volunteers with opportunity for networking, collaboration, and peer learning. However, strategically creating ideal assignments is challenging because (i) there are exponentially many ways a set of volunteers can be assigned in groups; and (ii) NPOs tend to have limited and uncertain data concerning volunteers’ personal preferences, availabilities, and motivations to participate. To address these challenges, this research contributes by introducing an integer programming framework to offer volunteers a menu of tasks to choose from and then based on volunteers’ willingness information, creates ideal homogenous volunteer group assignments. These groups are created such that the group collectively meet a task’s skill requirements and groups of volunteers of similar skill and affinity levels are prioritized. We apply the developed methodology to a case study based on a partner NPO that works with remote volunteers from multiple countries to produce online educational content. The menu creation method can improve NPO and volunteer-based performance metrics, where the most improvement is observed when a NPO is faced with very picky volunteers. Presenting volunteers with larger menus of tasks also leads to an improvement in ideal group creations. Implementing the group creation methodology helps obtain a statistically significant increase in ideal group creations but results in a tradeoff of decreased benefits to volunteers and the NPO. Finally, implementing a minimum desired group size does not severely impact most KPIs and would be beneficial for an NPO to implement as it encourages the creation and assignment of volunteer groups to tasks.

Advances in Artificial Intelligence-aided Intraoral Imaging Analysis in Periodontics

Artificial intelligence has increasingly influenced the field of periodontology by enhancing diagnostic accuracy and treatment planning through advanced data-driven techniques. It was aimed to examine the integration of artificial intelligence, particularly deep learning and machine learning, in analyzing intraoral photographs for periodontal conditions in this review. Periodontal assessments rely on clinical and radiographic evaluations, but artificial intelligence introduces a transformative approach by analyzing large datasets to improve clinical decision-making. The review investigates the effectiveness of artificial intelligence-enhanced intraoral photograph analysis, focusing on methodologies for dataset creation, model development, training, and performance evaluation. A thorough search of databases such as PubMed, Scopus, Google Scholar, and IEEE Xplore identified 338 articles, with 16 meeting the inclusion criteria. These studies primarily utilized convolutional neural networks and architectures like DeepLabv3+ and U-Net, demonstrating high accuracy in detecting conditions such as gingivitis, dental plaque, and other periodontal issues. The dataset sizes ranged from 110 to 7220 images, affecting the models' generalizability. Most studies employed supervised learning, with models trained on labeled datasets to achieve precise diagnostic outcomes. The review highlights that while artificial intelligence and machine learning techniques, including convolutional neural networks and U-Net, offer significant improvements in periodontal diagnostics, the choice of model and the quality of the dataset are crucial for performance. Hybrid approaches that combine automated and expert-driven methods might provide a balance between efficiency and accuracy. The successful integration of artificial intelligence into clinical practice requires continuous validation and adaptation to ensure that these technologies remain accurate and relevant. Future research should focus on enhancing model robustness, expanding dataset diversity, and refining clinical applications to fully exploit the potential of artificial intelligence in periodontology.

On responsible machine learning datasets emphasizing fairness, privacy and regulatory norms with examples in biometrics and healthcare

Artificial Intelligence (AI) has seamlessly integrated into numerous scientific domains, catalysing unparalleled enhancements across a broad spectrum of tasks; however, its integrity and trustworthiness have emerged as notable concerns. The scientific community has focused on the development of trustworthy AI algorithms; however, machine learning and deep learning algorithms, popular in the AI community today, intrinsically rely on the quality of their training data. These algorithms are designed to detect patterns within the data, thereby learning the intended behavioural objectives. Any inadequacy in the data has the potential to translate directly into algorithms. In this study we discuss the importance of responsible machine learning datasets through the lens of fairness, privacy and regulatory compliance, and present a large audit of computer vision datasets. Despite the ubiquity of fairness and privacy challenges across diverse data domains, current regulatory frameworks primarily address human-centric data concerns. We therefore focus our discussion on biometric and healthcare datasets, although the principles we outline are broadly applicable across various domains. The audit is conducted through evaluation of the proposed responsible rubric. After surveying over 100 datasets, our detailed analysis of 60 distinct datasets highlights a universal susceptibility to fairness, privacy and regulatory compliance issues. This finding emphasizes the urgent need for revising dataset creation methodologies within the scientific community, especially in light of global advancements in data protection legislation. We assert that our study is critically relevant in the contemporary AI context, offering insights and recommendations that are both timely and essential for the ongoing evolution of AI technologies.

Agile future creation methodology. Innovation method for startups to build future-proof solutions

Agile future creation methodology. Innovation method for startups to build future-proof solutions

THE CONSTRUCTION OF CONCEPT MAPS: ENHANCING LEARNING AND KNOWLEDGE REPRESENTATION

Concept maps are graphical tools that represent knowledge in a structured format, illustrating relationships between concepts. This paper explores the construction of concept maps, their theoretical foundations, methodologies for effective creation, and their applications in various fields such as education, business, and research. The study highlights the cognitive benefits of using concept maps, including enhanced understanding, retention, and critical thinking skills. Furthermore, it discusses the challenges faced in their construction and offers recommendations for best practices.

Optimizing Supply Chain Network Design Under Uncertainty: A Practical Methodology for Sustainable Value Creation

Evaluating supply chain network (SCN) designs is critical for organizations striving to optimize operations and achieve sustainable value creation. However, conventional models often oversimplify, failing to account for the complexities inherent in real-world supply chain environments. In this study, we propose an advanced approach to SCN evaluation that strikes a balance between practicality and sophistication, leveraging real-world data to inform decision-making. Our methodology aims to bridge the gap between theoretical models and practical implementation, offering a pathway to sustainable value creation in SCN design. By incorporating risk analysis, resilience modeling, and solution methods tailored to uncertainty, our approach provides a comprehensive framework for addressing the challenges of SCN design under uncertainty. Simulation results validate the efficacy of our methodology in facilitating informed decision-making and strategic planning within organizations.

PSYCHOANALYSIS OF BULGARIAN LITERATURE: A HISTORICAL PERSPECTIVE

The article is devoted to the development of the psychoanalytic movement in Bulgaria between the 1920s and the 1940s, when it reached its apogee. After this period, the communist regime came to power in Bulgaria and it banned all philosophical currents other than Marxist-Leninist philosophy. Psychoanalysis was also banned and it was declared to be a “bourgeois and unscientific doctrine”. The meta-analysis of the work of the Bulgarian Freudians makes it possible to distinguish the following main problem areas in which they worked: philosophical and methodological issues of psychoanalysis; the topic of religion; the “reading” of socio-political and social phenomena; issues of education and training; psychopathology and abnormal personality development; and the application of psychoanalysis as a methodology of artistic creation. This text examines the application of psychoanalysis as a methodology of artistic creation and its possibilities for analyzing the personality of the author and the literary works. It presents the interpretations of Bulgarian psychoanalytically oriented authors of the literary works of the poets Hristo Botev and Peyo Yavorov, as well as their reflections on some problems of art and aesthetics.

Mathematical modeling of the creation process and aging of polymer composite materials

Based on the analysis of the literature on the possibility of using neural networks to create new materials with high functional properties, the article considers a solution to the problem of determining the operational stability of polymeric composite materials by creating physical and chemically sound mathematical prediction models. Epoxy resins of the UP-637 and EA brands with an isophorone diamine hardener were chosen as the matrix of the model composite material, and oligobutadiene rubber of the SKN-10 KTR brand was chosen as the modifier. It justifies directions of work necessary for development of new materials creation methodology with optimal characteristics, building a model for changing the properties of materials at variation of composition and implementation of full-scale mathematical modeling of physical and chemical processes of polymer composite materials aging at changing level and time of climatic factors influence. Verification of the obtained dependence of service characteristics on the composition of the material and the level of influencing climatic factors was carried out on the basis of data from full-scale tests in a temperate climate. The proposed methodology for modelling the properties of polymer composite materials will reduce the development time of new materials and allow creation of polymer composites based on epoxy resin containing fillers of various natures (carbon, mineral and polymer) with high performance parameters.

Review of codelists used to define hypertension in electronic health records and development of a codelist for research

Background and aimsHypertension is a leading risk factor for cardiovascular disease. Electronic health records (EHRs) are routinely collected throughout a person’s care, recording all aspects of health status, including current...

Геоінформаційна система інженерних мереж та комунікацій морського торгового порту

The work is devoted to researching the process of development, implementation and operation of the geoinformation system of engineering networks and communications (GISIS) in the Odesa Sea Trade Port. The beginning of the development of the system began more than twenty years ago. The beginning of the works was preceded by the stage of pre-project studies, the result of which were the technical tasks for the implementation of the works and the project of the structure of information support. The work was carried out in stages, which corresponded to a separate territory and type of work. The purpose of this work is to research the processes of performing field and camera geodetic, photogrammetric, cartographic works, designing and creating a geoinformation database, selecting and adapting specialized geoinformation software, operating and supporting the system during the full life cycle of the geoinformation system. The methodology mainly corresponds to the following algorithm of work performance. At the stage of preliminary design studies: – collection and analysis of data on the exchange of cartographic and analytical information between external organizations, – collection and analysis of data on the exchange of cartographic and analytical information within the enterprise, primarily between engineering services, – description of the existing document circulation system with cartographic and analytical information, – a description of the shortcomings of the existing document management system, – determination of requirements for geo-information software and justification of the configuration of the geo-information software package and its architecture. At the stage of field work: – construction of a shooting justification and definition of data for communication with other coordinate systems, – reconnaissance on the territory of performance of works. Planning field work. – execution of topographical and geodetic works for the purpose of building or updating 1:500, 1:2000 scale plans. Construction of outlines. – performance of engineering and geodetic works for the study of underground communications in order to design the sections of wells and other engineering nodes. At the stage of design (camera works): – based on outlines and electronic survey protocols, development or correction of 1:500, 1:2000 scale plans using geoinformation software. – based on outlines, photofixation materials, construction of diagrams of sections of wells and other engineering nodes in electronic form. – formation of a geo-informational database of the object on the territory of execution of works. – debugging the project in the environment of geoinformation software. – coordination of the project with the engineering services of the enterprise and external organizations. – commissioning the developed project to the customer. Scientific novelty and practical significance – for the first time, research and development of the methodology of creation and support at all stages of the life cycle of the geoinformation system of engineering networks and communications of a large seaport was carried out. The methodology was developed for a long time during the entire life cycle of the system. The methodology was used by other ports and large industrial enterprises.

CoVR: Learning Composed Video Retrieval from Web Video Captions

Composed Image Retrieval (CoIR) has recently gained popularity as a task that considers both text and image queries together, to search for relevant images in a database. Most CoIR approaches require manually annotated datasets, comprising image-text-image triplets, where the text describes a modification from the query image to the target image. However, manual curation of CoIR triplets is expensive and prevents scalability. In this work, we instead propose a scalable automatic dataset creation methodology that generates triplets given video-caption pairs, while also expanding the scope of the task to include composed video retrieval (CoVR). To this end, we mine paired videos with a similar caption from a large database, and leverage a large language model to generate the corresponding modification text. Applying this methodology to the extensive WebVid2M collection, we automatically construct our WebVid-CoVR dataset, resulting in 1.6 million triplets. Moreover, we introduce a new benchmark for CoVR with a manually annotated evaluation set, along with baseline results. Our experiments further demonstrate that training a CoVR model on our dataset effectively transfers to CoIR, leading to improved state-of-the-art performance in the zero-shot setup on both the CIRR and FashionIQ benchmarks. Our code, datasets, and models are publicly available at https://imagine.enpc.fr/~ventural/covr.

A new methodology for automatic creation of concept maps of Turkish texts

A new methodology for automatic creation of concept maps of Turkish texts

Conceptualization of a methodology for circular value creation in SMEs in one-off production

Implementing a circular economy (CE) is essential to achieving the long-term goal of carbon neutrality. Therefore, circular economy becomes increasingly relevant in the manufacturing industry. As small and medium-sized enterprises (SMEs) constitute a large part of the manufacturing industry, without them, a wide-ranging circular economy would not be possible. However, various structural barriers across the three dimensions of value creation – process, resource and organization – hinder the adoption of circular practices in SMEs. The difficulty of implementing circular practices is especially true for SMEs in one-off production with highly customized products and low process repeatability. Corporate survival in a circular world means these SMEs must transform themselves in the long term. Therefore, this paper aims to conceptualize a methodology for transforming SMEs in one-off production towards circular value creation. To this end, this research summarizes and analyzes existing barriers in the literature and then derives the requirements for the methodology. It finishes by conceptualizing the methodology by outlining the individual steps.

CoVR-2: Automatic Data Construction for Composed Video Retrieval.

Composed Image Retrieval (CoIR) has recently gained popularity as a task that considers both text and image queries together, to search for relevant images in a database. Most CoIR approaches require manually annotated datasets, comprising image-text-image triplets, where the text describes a modification from the query image to the target image. However, manual curation of CoIR triplets is expensive and prevents scalability. In this work, we instead propose a scalable automatic dataset creation methodology that generates triplets given video-caption pairs, while also expanding the scope of the task to include composed video retrieval (CoVR). To this end, we mine paired videos with a similar caption from a large database, and leverage a large language model to generate the corresponding modification text. Applying this methodology to the extensive WebVid2M collection, we automatically construct our WebVid-CoVR dataset, resulting in 1.6 million triplets. Moreover, we introduce a new benchmark for CoVR with a manually annotated evaluation set, along with baseline results. We further validate that our methodology is equally applicable to image-caption pairs, by generating 3.3 million CoIR training triplets using the Conceptual Captions dataset. Our model builds on BLIP-2 pretraining, adapting it to composed video (or image) retrieval, and incorporates an additional caption retrieval loss to exploit extra supervision beyond the triplet, which is possible since captions are readily available for our training data by design. We provide extensive ablations to analyze the design choices on our new CoVR benchmark. Our experiments also demonstrate that training a CoVR model on our datasets effectively transfers to CoIR, leading to improved state-of-the-art performance in the zero-shot setup on the CIRR, FashionIQ, and CIRCO benchmarks. Our code, datasets, and models are publicly available at https://imagine.enpc.fr/~ventural/covr.

Incorporating Artificial Intelligence Into Athletic Training Education: Developing Case-Based Scenarios Using ChatGPT

Context ChatGPT is an AI-based large language model platform capable of mimicking human language patterns by responding to user queries. Although concerns over AI-generated content exist in health care and higher education, the ChatGPT platform can assist athletic training educators in creating academic content to alleviate aspects of their academic workload and responsibilities. Objective To provide a brief historical overview of ChatGPT, accepted positives and negatives, and examples of how athletic training educators can use ChatGPT for case-based scenario contention creation. Background The initial development of ChatGPT began in 2018, with its public launch in November 2022. ChatGPT uses machine and in-context learning to replicate human language expression. Since its public launch, students, researchers, educators, clinicians, governments, and companies have sought to determine how to incorporate ChatGPT into their workflow operations. Data Synthesis Athletic training educators can incorporate ChatGPT into their academic content creation methodology. With the capability of ChatGPT, athletic training educators have the potential to facilitate athletic training student learning more efficiently. Results ChatGPT can ease the academic workload of athletic training educators while being a beneficial clinical tool that athletic training students may use in their future workplace settings. Recommendation(s) Athletic training educators should consider using ChatGPT or a similar AI-based large language model platform when developing education content and simulation scenarios. Conclusions ChatGPT can lessen athletic training educator workload and potentially facilitate athletic training student learning.

Methodology of creation and development of information systems for technological safety of mining facilities

Purpose. To develop methodological approaches to the process of informatization of technological security (TS) and to propose a project of step-by-step development of the architecture of information system (IS) of TS, which will contribute to effective integration of digital and mining technologies. To develop a mathematical model for finding the number of sensors required for probabilistic assessment of the concentration gradients of hazardous gases. Methodology. General and special methods of knowledge are used: structural analysis – to establish the structure and tasks of IS of TS; logical generalization – for formation of methodological system of directions of TS information measures; system analysis – to establish synergistic effect of complex implementation of the indicated directions; scientific abstraction – for development of a project for IS architecture derivation; mathematical formalization – for development of mathematical model for estimating gradients of concentration gases and the number of sensors. Findings. A project for the phased development of IS architecture of mining facilities based on the implementation of diffusion principle is developed, which will allow solving a complex of issues: integrated monitoring of danger of gas environment of underground structure for detection of gas traps and permanent determination of concentration gradients of hazardous gases, implementation of intelligent safety loops using analytical resources of technological mining process. A methodological system of directions for diffusion implementation of TS information measures is formed. The use of the method of system analysis made it possible to point out the synergistic effect of the complex implementation of the directions of implementation of TS information measures. Originality. A project for the phased development of the information system architecture of the technological safety of mining enterprises has been developed. A mathematical model has been developed to estimate the concentration gradients of hazardous gases and the number of sensors to ensure the appropriate level of probability of finding a sensor in each cell of the underground mine. Practical value. The methodological approach makes it possible to form an IS that implements a comprehensive approach to ensuring the appropriate level of technological safety of mining facilities.

Green logistics performance Index as a benchmarking tool for EU countries environmental sustainability

Logistics performance has a significant impact on the natural environment. The paper analyses it from a broad macro perspective of European Union countries. Also, it proposes the methodology of creation and possibilities of use of the Green Logistics Performance Index (GLPI) to deepen the analyses and compare countries. The paper's primary goal is to introduce and justify the implementation of the GLPI. First, a literature review is provided, covering the concept of green logistics and environmental problems. Next, the Logistics Performance Index (LPI) and Environmental Performance Index (EPI) are described in detail as the components of GLPI, and the methodology of GLPI creation is presented. Finally, the GLPI is calculated for all European Union countries in 2018 (the latest data) and 2010 to compare the differences and see the progress or regress. This part of the paper gives an overview of GLPI as a benchmarking tool, pointing out the positives and negatives, and transferring the best environmental practices from leading counties to others. In the end, the benefits of GLPI are described together with its utility suggestions.

SUITABILITY AND CHALLENGES OF OPEN MAPS FOR EUROPE DATA FOR CREATING A GENERAL PURPOSE SMALL-SCALE MAP OF CROATIA

Abstract. The adoption of the Open Data Directive in 2019 compelled the launch of the Open Maps for Europe project, aiming to provide accessible and harmonized geospatial data from over 40 European countries. This research investigates the suitability of Open Maps for Europe data for creating a general purpose small-scale map of Croatia. The study applies digital cartographic procedures to produce the map, while assessing data quality and fitness for this task. The methodology for map creation involved seven key steps: (1) extracting data from the 1:250,000 scale EuroRegionalMap dataset, (2) performing geometric, topological, and attribute conversions, (3) applying cartographic generalization to adapt the map content to a 1:500,000 scale, (4) conducting data quality checks, (5) addressing exceptions, (6) symbolizing and placing names, and (7) designing a printable map. The resulting general-purpose map of Croatia at a 1:500 000 scale demonstrates that Open Maps for Europe data is generally suitable for map creation at this scale. However, challenges such as data heterogeneity among countries, data gaps in certain areas, inappropriate levels of generalization, and disordered geometry may arise. The map created should be considered an intermediate, rather than a reliable and trustworthy final product since rigorous quality control measures should be undertaken to produce the final map.

ABDUCTIVE REASONING AS A MODEL FOR MUSICAL CREATION IN JULIO ESTRADA’S MUSICAL WORKS

The paper deals with two philosophical postulates that although at first sight both do not have a direct link, it is my hypothesis that there may be a connection between them since in each one imagination plays an important role in the process of scientific discovery. On the one hand, it deals with the abductive reasoning by Charles Sanders Pierce (1839–1914), focusing on the problem related with abduction and scientific imagination, graphicacy or the ability to represent ideas through images, beelddenken or “pictorial thinking” as a form of communicating ideas without the use of any verbal form, and synthetic topology responsible for studying the qualitative relations of any 3-D geometrical structure. On the other hand, the author presents the philosophical postulates of the Theory of Composition: discontinuum-continuum by Julio Estrada (*1941), where reality and imagination play an important role in the process of musical creation, presenting a two-fold methodology of creation, (1) the macro timbre where the homogenization of the components of the rhythmsound takes place, and (2) the chronography, a graphic representation of the rhythmsound in movement. The latter is exemplified in this paper with the three examples of Estrada’s musical compositions, (1) the graphical score of eua’on UPIC (1980), (2) graphical recording for the series yuunohui’ (1983–2020), and (3) the topological variations included in the ishini’ioni String Quartet (1984–1990).