Knowledge Of Programming Language Research Articles

Development of Augmented Reality Programming Language using Agile Scrum Methodology

The agile scrum methodology for augmented reality development increases project team efficiency. Private campus are frequently confronted with the dilemma of new students with various backgrounds that come not only from vocational high schools but also from high schools. First year students in the informatics study programme come not only from vocational informatics high schools, but also from high schools that specialize in social studies and languages. This is a difficult task in terms of imparting a comprehension of the fundamentals of programming. This study develops augmented reality in order to teach HTML and Javascript. By combining basic principles with gaming, the proposed augmented reality (AR) makes programming interesting. Players must comprehend their programming logic in order to be immersed in a virtual environment by answering coding bug questions. During usability testing, the System Usability Scale (SUS) assesses user happiness and AR knowledge. Participants from various programming backgrounds were tested on their knowledge of programming languages. According to usability research, 59% of people found AR programming languages useful for learning and understanding basic programming languages. AR and Agile Scrum make programming more enjoyable. This study demonstrates how augmented reality can be used to teach programming languages. These findings imply that Agile Scrum and AR methods can improve learning and programming foundations. More research and development could lead to more complete and complicated AR learning environments for programming instruction.

Artificial Intelligence (AI) Revolution in Research: Transforming Data into Discovery

Artificial Intelligence (AI) has emerged as a Atransformative force in the dominion of research, reshaping the landscape across diverse fields. AI refers to the simulation of human intelligence by a system or a machine. It implies a vast term that encompasses machine learning and deep learning. AI is based firstly on 'intelligence' which refers to cognitive capacity of an individual to plan learn and interpret. Secondly 'techne', a more wideranging ability to solve problems using technological objects. Although the intelligence remains the same measured by intelligence quotient (IQ) for many decades now, it is the change in techne that leads to amplification of intelligence. Use of AI in healthcare and biomedical sciences is based on development of algorithms. This requires a sound knowledge of programming languages, advanced mathematics and statistics. In healthcare AI cannot be used fairly if these skills are lacking. However visual and no code programming tools available now with free data science tools make it easy for clinicians, researchers and health journalists.

Interactive analysis of single-cell data using flexible workflows with SCTK2

Analysis of single-cell RNA sequencing (scRNA-seq) data can reveal novel insights into the heterogeneity of complex biological systems. Many tools and workflows have been developed to perform different types of analyses. However, these tools are spread across different packages or programming environments, rely on different underlying data structures, and can only be utilized by people with knowledge of programming languages. In the Single-Cell Toolkit 2 (SCTK2), we have integrated a variety of popular tools and workflows to perform various aspects of scRNA-seq analysis. All tools and workflows can be run in the R console or using an intuitive graphical user interface built with R/Shiny. HTML reports generated with Rmarkdown can be used to document and recapitulate individual steps or entire analysis workflows. We show that the toolkit offers more features when compared with existing tools and allows for a seamless analysis of scRNA-seq data for non-computational users.

ВИКОРИСТАННЯ ПАКЕТІВ МОДЕЛЮВАННЯ СИСТЕМНОЇ ДИНАМІКИ УПРАВЛІННЯ ЗАПАСАМИ В ВИРОБНИЧО-ТОРГОВИХ ОРГАНІЗАЦІЯХ, ЯКІ ПОСТАВЛЯЮТЬ МАТЕРІАЛЬНО-ТЕХНІЧНІ ЗАСОБИ ДЛЯ ЗБРОЙНИХ СИЛ УКРАЇНИ

Planning of difficult logistic structures is presently conducted with the use of the special software products and modern information technologies. Presently in this area of widest find various computer expert facilities and systems of planning of processes of logistic. Large possibilities in this area are possessed by the packages of structural design. They allow not only to prepare the proper recommendations and projects on the base of exact analytical methods but also give them an evident, visual form. In this article the considered approaches of design of system dynamics of control of inventories in production-point-of-sale organizations which supply, material and technical facilities for Military Powers of Ukraine. The example of visual model of logistic chain is described developed at to the environment of package of structural design of iThink It is marked that work with the package of iThink does not require the special skills and knowledge of programming language. A model is developed by placing in a graphics editor separate component and them subsequent connection. If necessary intercommunications are set between separate knots. Analysing the package of structural design it is possible to draw a conclusion, that facilities of structural design of are some hard limits on the process of design. A model can be developed practically for any system of financial streams and supplies any the organizations of any pattern of ownership. Also it should be noted that design of activity of economic subjects exceptionally effective and perspective direction of development of administrative technologies. World experience testifies that computer analysis of the logistic systems, a condition is needed for the effective planning of creation and management similar difficult organizations Keywords: logistic system, system of logistical support of Military Powers of Ukraine, production-point-of-sale organizations, structural design.

Gully erosion prediction method from geoenvironmental data and supervised machine learning techniques

Predictive models are statistical representations that indicate, based on the historical data analysis, the probability of triggering a given phenomenon in the future. In geosciences, such models have been essential to predict the occurrence of adverse phenomena commonly associated with environmental disasters, such as gully erosion. Therefore, this paper presents a method for producing gully erosion predictive models based on geoenvironmental data and machine learning techniques. The method's effectiveness test was produced in a region of approximately 40,000 km² in southeastern Brazil and compared the predictive performance of four models designed with different machine learning algorithms. The results demonstrated that the technique is capable of producing models with high predictive ability, with emphasis on the random forest algorithm, which, in addition to having achieved the highest levels of accuracy, also produced highly realistic maps for the study area.•The method is straightforward and may be applied to predict other geological processes.•The application of the method does not require knowledge of programming language.•The models produced achieved high predictive performance.

Integrating Machine Learning with Parametric Modeling Environments to Predict Building Daylighting Performance

Buildings account for 30% of global energy consumption. To support the development of energy-efficient built environments and cities, architects, urban planners, and engineers have begun to utilize building performance simulation (BPS). Supporting decision-making and steering design toward high performance are crucial in the early design phase, when decisions have the biggest impact on the final product’s energy consumption and costs. Architects often assess the energy performance of hundreds of different design solutions and configurations in parametric environments to find the most energy-efficient solution. To adhere to strict project due dates, architects usually shorten the time required for BPS by reducing the number of variables or parameters for the building and facade design. This practice usually results in the elimination of design parameters that could potentially contribute to an energy-optimized design configuration. To achieve time-efficient BPS processes, recent research has focused on developing machine learning (ML) algorithms that can instantly predict the energy performance of buildings. Although ML has demonstrated high levels of accuracy, ML techniques are difficult to implement because they require technical knowledge of programming languages. Furthermore, these ML algorithms were developed as standalone applications, making them inappropriate for geometric modeling environments. This paper introduces a new ML tool that can be easily accessed within Grasshopper, a parametric modeling environment. The proposed tool can instantly predict the daylighting performance of building configurations.

Voice Coding using ML

Abstract: In this digital era there are various digitization is happening like the AI is deploying so fast, various automations are happening and taking place of human and reducing the efforts of human. And all this things are happening because of programmers/developers they are doing a very hard work for the development of technology. As effect of this this work many developers/programmers are facing various physical / mental disorders like stress, carpel tunnel syndrome and more problems. So we are developing a system which will reduce their injuries or problems like this by creating solution i.e. they have to just speak they want code the system will take it and create proper code. In today’s world, many artificial intelligence applications developed using programming languages like Python, R and so on. Each language comes with its own programming structure and syntactical forms. Programmers are broadly classified into three categories namely, novice users, knowledge intermittent and expert one. For novice users, it is always a challenge to write a code without typographic errors though users know theoretical knowledge of Programming language, its structure and syntax as well as logic of program. Therefore, this paper explores use of voice recognition technique in the field of programming, specifically for writing program with Python programming language. In experimental analysis, it found helpful for new Python programmers and provide new learning curve for programmers wherein beginner can experience hassle free program writing. This paper adds new way of creating interest in beginners for judging their coding paradigm understanding and explore one of the area for user experience field for better programming Integrated Development Environment Development (IDE). Keywords: Artificial Intelligence, Learning, User Experience, Voice Recognition. Keywords: Artificial Intelligence, Learning, User Experience, Voice Recognition and Speech Recognition.

Graphical Interface to Improve Python Language Teaching and Image Processing

The increase in knowledge of programming languages is increasingly high due to current business and educational demands, in many cases it has been reflected that advanced knowledge of a programming language for careers in natural sciences and engineering have improved the possibility of getting a decent job with a good working environment. Many universities propose programming courses on a large scale and in a general way so that the student can investigate and deepen the topics, but when the course is carried out without any structure or interface with which the students present a great interest in it, they tend to fail or regularly make basic schedules to only pass the course. That is why a graphical interface system is proposed to improve the teaching of the Python language due to its various functionalities and improve the interest of image processing. Obtaining as results that, of the 100 students and teachers within the branch of natural sciences and engineering, using 9 indicators of satisfaction an average of 6 thus indicating that the graphic interface does help in the process of learning and interaction of the person did the programming and processing of images. It is concluded that the use of graphical interfaces for any type of teaching is quite useful due to the simulation mode that all these have, thus improving the level of interaction of the student and the possibilities of tests that can be carried out before the implementation or design in real. Keywords— GUI, Python, graphical interface, PyQt, artificial intelligence.

How to Build an Image-Processing Pipeline for Automating Multiparameter Histocytometry Analysis.

Until relatively recently, analysis of imaging data has been primarily quantitative and limited to 3-4 markers. The advancement of various technologies overcoming this marker limitation provided the capability of analyzing multiparameter imaging data down to the single cell level, termed histocytometry. Currently, most published end-to-end histocytometric analysis of imaging data is performed using expensive commercial programs or freely available analysis packages that require significant knowledge of programming languages for execution. Here we present a protocol that performs cell segmentation, phenotyping and spatial analysis, using software with easy-to-use GUIs (graphical user interfaces). These protocols allow the user to derive spatial and phenotypical data for the analysis of multiparameter microscopic images from most imaging platforms in a low-cost manner. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Cell Segmentation and generation of histocytometric .csv file Basic Protocol 2: Phenotyping of cell populations Basic Protocol 3: Spatial relationship analyses of phenotyped populations Support Protocol 1: Nuclei Segmentation Accuracy Test Support Protocol 2: Correcting y-axis Inversion of Histocytometry Data Relative to Original Image File.

SSAM-lite: A Light-Weight Web App for Rapid Analysis of Spatially Resolved Transcriptomics Data.

The combination of a cell’s transcriptional profile and location defines its function in a spatial context. Spatially resolved transcriptomics (SRT) has emerged as the assay of choice for characterizing cells in situ. SRT methods can resolve gene expression up to single-molecule resolution. A particular computational problem with single-molecule SRT methods is the correct aggregation of mRNA molecules into cells. Traditionally, aggregating mRNA molecules into cell-based features begins with the identification of cells via segmentation of the nucleus or the cell membrane. However, recently a number of cell-segmentation-free approaches have emerged. While these methods have been demonstrated to be more performant than segmentation-based approaches, they are still not easily accessible since they require specialized knowledge of programming languages and access to large computational resources. Here we present SSAM-lite, a tool that provides an easy-to-use graphical interface to perform rapid and segmentation-free cell-typing of SRT data in a web browser. SSAM-lite runs locally and does not require computational experts or specialized hardware. Analysis of a tissue slice of the mouse somatosensory cortex took less than a minute on a laptop with modest hardware. Parameters can interactively be optimized on small portions of the data before the entire tissue image is analyzed. A server version of SSAM-lite can be run completely offline using local infrastructure. Overall, SSAM-lite is portable, lightweight, and easy to use, thus enabling a broad audience to investigate and analyze single-molecule SRT data.

Gridlines approach for dynamic analysis in speech ultrasound data: A multimodal app

Having access to efficient technologies is essential for the accurate description and analysis of articulatory speech patterns. In the area of tongue ultrasound studies, the visualization/analysis processes generally require a solid knowledge of programming languages as well as a deep understanding of articulatory phenomena. This demands the use of a variety of programs for an efficient use of the data collected. In this paper we introduce a multimodal app for visualizing and analyzing tongue contours: UVA—Ultrasound Visualization and Analysis. This app combines the computational power of R and the interactivity of Shiny web apps to allow users to manipulate and explore tongue ultrasound data using cutting-edge methods. One of the greatest strengths of the app is that it has the capability of being modified to adapt to users’ needs. This has potential as an innovative tool for diverse academic and industry audiences.

Improving Undergraduate Novice Programmer Comprehension through Case-Based Teaching with Roles of Variables to Provide Scaffolding

A role-based teaching approach was proposed in order to decrease the cognitive load placed by the case-based teaching method in the undergraduate novice programmer comprehension. The results are evaluated by using the SOLO (Structure of Observed Learning Outcomes) taxonomy. Data analysis suggested novice programmers with role-based teaching tended to experience better performances, including the SOLO level of program comprehension, program debugging scores, program explaining scores, except for programming language knowledge scores, compared with the classical case-based teaching method. Considering the SOLO category of program comprehension and performances, evidence that the roles of variables can provide scaffolding to understand case programs through combining its program structure with its related problem domain is discussed, and the SOLO categories for relational reasoning are proposed. Meanwhile, the roles of variables can assist the novice in learning programming language knowledge. These results indicate that combing case-based teaching with the role of variables is an effective way to improve novice program comprehension.

Возможности формирования информационных и цифровых компетенций специалиста по управлению персоналом в рамках высшей школы

The article presents the results of the analysis of federal educational standards for personnel management at the undergraduate and graduate level, which showed that higher educational institutions can creatively approach the formation of information and digital competencies in students. It has been substantiated that the formation of digital competencies is based on information competencies and is associated with the ability to extract, process, store and transmit big data. For the formation of digital competencies among students studying in the field of "personnel management", it is proposed to introduce the study of the free software product KNIME distributed on the Internet in the work program of the discipline "Information technologies in personnel management", which allows working with big data at the level of large nodes without knowledge of programming languages. The article provides an example of a simple model created in KNIME to analyze the labor market of specialists required by an enterprise by extracting and processing data presented on the website hh.ru.

Skill Mismatch Assessment: Example of Software Industry in Bosnia and Herzegovina

Concept of skill mismatch is very broad and can be measured using a variety of indicators. It is used to describe so-called vertical mismatches (over-education, under-education, excessive or insufficient training), skills gaps, skills shortages, enrolment policy or ‘horizontal’ mismatches and skills obsolescence. In this paper we are analyzing skill mismatch gaps and skills shortages in software industry in Bosnia and Herzegovina using firm level assessment. The research results provide clear evidence for severe skill shortages facing IT companies in Bosnia and Herzegovina. Inadequate tertiary education enrolment policy results in numerous vacancies in software industry, especially for developer’s positions. The evidence of skills gaps are also found. Primarily as a result of inadequate curricula in higher education institutions. The problem of skill gaps is most prominent referring professional (technical) skills, but also some ‘soft’ skills, such as the ability to work with clients, communication skills, problem detection and solving, etc. In a broad group of professional (technical) skills the biggest gaps are found in a sub-group related to fundamental knowledge of programming languages and IT systems, and sub-group related to experience in working with complementary tools and project management. In a way this was expected having in mind the stage of development of software industry in Bosnia and Herzegovina. Identified skill gaps and skill shortages are somewhat lower for non-IT employees. Based on the research findings several policy options are discussed.

Restricted Move – a Smart Contract Description Language to Create and Control Finance Instruments on DFinance Blockchain Platform

Smart contracts created to issue tokens and control other digital financial assets on the majority of blockchain platforms require knowledge of programming language for specific platforms. This fact imposes a restriction on attracting financial specialists from conventional markets. This paper presents the concept of a Restricted Move language allowing the users to form a smart contract description in financial English, as well as its further development into a high-level digital asset management language, which can be extended by users and can open new opportunities to automate their market operations.

ESTUDO COMPARATIVO DA APLICAÇÃO DOS PROGRAMAS PYTHON E ORANGE PARA A ANÁLISE APROFUNDADA DE BANCOS DE DADOS

The present study aims to analyze the usability of DataScienceprograms for database analysis. Therefore, a database extracted from a public platform was used and applied in two programs, Python and Orange, in order to obtain a comparison between both. The bibliographic research served as a basis for the understanding of the programs and to base the obtained results. The Python program required work with the database, in file conversion as well as the need for programming language knowledge and learning. In the Orange program, the original database was used and its intuitive functionality allowed to obtain faster results, since their tools have names associated with what you want to get. With the obtained results it was possible to verify that the use of the Orange program proved to be more convenient for analysis of the manipulated database

Evaluating Aspects of Usability in Video Game-Based Programming Learning Platforms

Abstract Teaching computer programming is an important topic. Due to Science and Technology initiatives, these topics are considered in different training cycles. For higher education, students must cultivate fundamental concepts for the development of software applications, which not only contribute to the knowledge of programming languages but also to opening guidelines for computational thinking. However, selecting a proper tool can be complex. Especially for the diversity of alternatives on the web. Further, not all of them meet basic usability requirements. In this study, we present a set of platforms that seek to develop programming skills based on video games. The search consisted of 4 stages: (i) definition of the research questions, (ii) scope review, (iii) execution of search and (iv) platform selection. Finally, we employ a usability heuristic evaluation for a novice programming system to determine best practices.

CS1 Student Grade Prediction: Unconscious Optimism vs Insecurity?

The difficulties of many students in introductory programming courses and the consequent failure and drop out make it necessary to look for motivation strategies for them to be successful. One of the strategies that is touted in the literature is self-assessment to compromise and motivate students. As we had doubts about the possibility of this strategy, we did an experiment and asked the students to predict the grades of the two tests and the two projects during a semester. Even knowing the correction grid and exercises that involve programming languages, which shows the result to the programmer, we found that the students' forecasts were not very accurate. In the first test we found that the worst students said they were going to get reasonable grades and much better than reality, while the best students thought they had worse grades than they actually had. The other moments of evaluation did not have as severe results, but forecasts continued to be inaccurate. We did tests by gender, by age, for being a freshman or not, for having taken a computer course in high school and for previous knowledge of programming languages: none of these variables proved to be as significant as the students' grades and their corresponding insecurity-fear or optimism-unconscious.

The technology of creating a multimedia electronic textbook without knowledge of programming languages

A technology for creating a multimedia electronic textbook without knowledge of programming languages on the Auto Play Media Studio 8 platform (Indigo Rose Corporation, demo version) using the following programs: UV screen Camera (UVsoutium company, free version, video presentation recording); Paint 3D (a free application included with Windows 10, creating page layouts); “Ayren” test editor (the developer is Ostanin S., free, creation of separate executable test files) is provided in the article.

GAME DEVELOPMENT SOFTWARE TOOLS IN HIGHER EDUCATIONAL INSTITUTIONS: EXPERIENCE OF UKRAINE, TURKEY AND BULGARIA

The article features the analysis of game development software tools in higher educational institutions of Ukraine (Pereiaslav-Khmelnytskyi Hryhorii Skovoroda State Pedagogical University), Turkey (Kahramanmaras Sutcu Imam University) and Bulgaria (Trakia University). The article highlights the results of the research conducted by teachers and students of these universities. In this research, teachers with no previous experience in this field or specialized IT skills created educational games. Free software tools that can be used to create educational games were selected for this research (Construct 3, GameMaker Studio 2, Unity, Godot Engine, Unreal Engine 4). The study included two data arrays: the first was the opinion expressed by teachers who developed educational games, and the second – that of students who tested the final game product. We analyzed free tools for creating educational games according to such criteria: the need for programming language knowledge, availability of support forums and reference materials, ability to export data to multiple platforms and in many formats, add in-app purchases or various components to each object, whether both 2D and 3D games are supported, development speed. In the Ukrainian teachers’ opinion, GameMaker Studio 2 was the most effective, while teachers in Turkey and Bulgaria preferred the Unreal Engine 4. According to research results, it is worth noting a high interest of both teachers and students in the creation and use of educational computer games. It should also be noted that these results are relevant only for specific groups under study since they are based on the individual experience of a limited number of students. However, they are significant for shaping ideas about pedagogical strategies and allow teachers to learn new information, try new types of activities and interaction.