Integrated Development Environment Research Articles

How to implement and evaluate with scrum methodology in business subjects - an experience in an educational innovation Project

The following paper arises from the Educational Innovation Project PIE 15-132 "Implementation and evaluation of the scrum methodology (project based learning) in the subjects of Business Creation and Management", funded by the Vice-Rectorate for Teaching and Research Staff of the University of Malaga. The idea stems from the analysis and study of the agile scrum methodology, focused on iterations and continuous reviews. The proposal consists of transferring the application of this methodology, widely used in software development environments, to subjects linked to the business environment, given the flexibility that characterises it. Its application made it possible to obtain interesting results, both related to the objectives of the subject "Business Creation", as well as others of a transversal nature, which are in great demand in today's environments.

Development of Surface Roughness Prediction and Monitoring System in Milling Process

High surface quality is an important indicator for high-performance machining during the manufacturing process. The surface roughness generated in machining can be affected by cutting parameters and machining vibration. To achieve processing efficiency, monitoring surface quality within the desired range is important. This study aimed to develop a surface roughness prediction system for the milling process. The predictive model was established based on data collected from machining experiments with the response surface methodology. The surface roughness is related to independent variables, including cutting parameters and machining vibration, in terms of nonlinear functions by regression analysis and the neural network approach, respectively. To be implemented in a CNC milling machine for online application, a predictive model was introduced in the Virtual Machine Extension (VMX) intelligent software development platform. This model can acquire the cutting parameters from the controller via the Open Platform Communications Unified Architecture (OPCUA) interface as well as the vibration features from the sensory module. The system can calculate the roughness based on these data and issue alert when the predicted value exceeds the preset threshold or abnormal vibration is detected.

Didactic and interactive project with PIC microcontroller and CAN network for temperature and luminosity control

Didactic and interactive project with PIC microcontroller and CAN network for temperature and luminosity control

Probabilistic Model Checking GitHub Repositories for Software Project Analysis

GitHub serves as a platform for collaborative software development, where contributors engage, evolve projects, and shape the community. This study presents a novel approach to analyzing GitHub activity that departs from traditional methods. Using Discrete-Time Markov Chains and probabilistic Computation Tree Logic for model checking, we aim to uncover temporal dynamics, probabilities, and key factors influencing project behavior. By explicitly modeling state transitions, our approach provides transparency and explainability for sequential properties. The application of our method to five repositories demonstrates its feasibility and scalability and provides insights into the long-term probabilities of various activities. In particular, the analysis provides valuable perspectives for project managers to optimize team dynamics and resource allocation. The query specifications developed for model checking allow users to generate and execute queries for specific aspects, demonstrating scalability beyond the queries we present. In conclusion, our analysis provides an understanding of GitHub repository properties, branch management, and subscriber behavior. We anticipate its applicability to various open-source projects, revealing trends among contributors based on the unique characteristics of repositories.

Multi-Agent System in Web Services

The term "service-oriented architecture" (SOA) refers to a software paradigm for creating systems made up of a variety of services that interact with one another to accomplish a certain task. The communications involve more than just transmitting data back and forth; they also connect two or more services to coordinate the required operations. Cross-platform communication is necessary for the coordinating process when services are spread across several platforms. Several web service standards and specifications are used in the present SOA implementation. Based on the prototype's implementation and simulation, this proposed research study has been validated and evaluated. The suggested cross-platform communications architecture is implemented using NetBeans, JADE, WSIG, and OWL-S. An integrated development environment for Java is offered by Oracle in the form of NetBeans. Telecom Italia's Java Agent DEvelopment Framework (JADE) is an agent software framework that is entirely built in the Java language. Web Service Integration Gateway (WSIG), which helps to facilitate JADE agent services being called by Web service clients. The core fundamental engine of the suggested framework is OWL-S. It is a web ontology language used to describe Semantic Web Services in the Semantic Web's OWL-based framework. A quantitative approach is used in this study's performance analysis and comparative investigation for evaluation and validation. The prototype's major element is the Java agent development framework (JADE), which was used to create a multi-agent system for the agent-based MOM framework that has been presented. The creation of the multi-agent systems was facilitated by the JADE platform. JADE 3.7 was the version that was employed. Two key features of JADE are a FIPA-compliant agent platform and a package for creating Java agents. The implementation results show that the proposed agent-based MOM framework was successful communicate between multiple types of SOA application with a better performance of the average of round-trip time where the proposed framework was successful in responding to all the requests.

Exploring the Impact of Vocabulary Techniques on Code Completion: A Comparative Approach

Integrated Development Environments (IDEs) are pivotal in enhancing productivity with features like code completion in modern software development. Recent advancements in Natural Language Processing (NLP) have empowered neural language models for code completion. In this study, we present an extensive investigation of the impact of open and closed vocabulary systems on the task of code completion. Specifically, we compare open and closed vocabulary systems with various vocabulary sizes to observe their impact on code completion performance. We experiment with three different open vocabulary systems: byte pair encoding (BPE), WordPiece and Unigram to compare them with closed-vocabulary systems to analyze their modeling performance. We also conduct experiments with different context sizes to study their impact on code completion performance. We have experimented using various prominent language models, including one from recurrent neural networks and five from transformers. Our results indicate that vocabulary size significantly impacts modeling performance and can artificially boost the accuracy of code completion models, especially in the case of a closed-vocabulary system. Moreover, we find that different vocabulary systems have varying impacts on token coverage, whereas open-vocabulary systems exhibit better token coverage. Our findings offer valuable insights for building effective code completion models, aiding researchers and practitioners in this field.

ALGORITHMIC LITERACY: Generative Artificial Intelligence Technologies for Data Librarians

INTRODUCTION: Artificial intelligence (AI) is a novel type of library technology. AI technologies and the needs of data librarians are hybrid and symbiotic, because academic libraries must insert AI technologies into their information and data services. Library services need AI to interpret the context of big data.OBJECTIVES: In this context, we explore the use of the the OpenAI Codex, a deep learning model trained on Python code from repositories, to generate code scripts for data librarians. This investigation examines the practices, models, and methodologies for obtaining code script insights from complex code environments linked to AI GPT technologies. METHODS: The proposed AI-powered method aims to assist data librarians in creating code scripts using Python libraries and plugins such as the integrated development environment PyCharm, with additional support from the Machinet AI and Bito AI plugins. The process involves collaboration between the data librarian and the AI agent, with the librarian providing a natural language description of the programming problem and the OpenAI Codex generating the solution code in Python.RESULTS: Five specific web-scraping problems are presented. The scripts demonstrate how to extract data, calculate metrics, and write the results to files.CONCLUSION: Overall, this study highlights the application of AI in assisting data librarians with code script creation for web scraping tasks. AI may be a valuable resource for data librarians dealing with big data challenges on the Web. The possibility of creating Python code with AI is of great value, as AI technologies can help data librarians work with various types of data sources. The Python code in Data Science web scraping projects uses a machine-learning model that can generate human-like code to help create and improve the library service for extracting data from a web collection. The ability of nonprogramming data librarians to use AI technologies facilitates their interactions with all types and data sources. The Python programming language has artificial intelligence modules, packages, and plugins such as the OpenAI Codex, which serialises automation and navigation in web browsers to simulate human behaviour on pages by entering passwords, selecting captcha options, collecting data, and creating different collections of datasets to be viewed.

Statistical analysis of lexemes generated in ‘C’ programming using fuzzy automation

The present work is an effort to support the typographical errors of keywords that are not supported by existing compilers and integrated development environment(IDE) in ’C’ language. The fuzzy automata modelling approximate string matching is proposed for error handling during lexical analysis. By introducing fuzziness to lexemes the typographical errors can be rectified at the time of compilation and flexibility of lexical analyser can be greatly improved. The recognition of fuzzy tokens during lexical analysis is described in order to correct errors caused by sticking key, deletion, typing and swapping key in keywords during C programming. Algorithms and pseudo code are being developed to measure the degree of membership of crisp and fuzzy lexemes. Accuracy is tested and examined once the fuzzy lexemes are trained using a neural network. The proposed method is an add on feature that can be incorporated in existing compilers and IDEs to increase their flexibility.

An efficient reducing mechanism for energy consumption in data center using hybrid consolidation techniques

The rise in internet user demand is a major factor in the expansion of infrastructure and the upsurge in energy use in cloud, colocation, and some business data centres. The advent of 5G has compounded the situation, as it substantially gives room for many new types of digital services, resulting in a need for richer consume a lot of energy when no scaling method is applied. Services such as mail, data storage and retrieval and other cloud services also require a lot of high energy consumption which eventually result into carbon(IV) oxide (CO2) emissions to the environment. This research therefore, focuses on lowering the energy usage of a data centre with heterogeneous power awareness either in an idle server state or high-performance state using a novel hybridized algorithm called “DyVoFesLoReMu”, comprising Dynamic Voltage Frequency Scaling (Dvfs) and a modified Local Regression Minimum Utilization (LrMu). A real dataset (workload) obtained online from PlanetLab consisting of hosts and Virtual Machines (VM) was simulated on a data center in CloudSim 3.0.3. Tool kit with preset parameters consisting of VM Allocation Policy and VM Selection Policy was used. The tool kit was utilised to create cloud infrastructure and simulate the essential features of a cloud environment. The Cloudsim was installed on Eclipse Integrated Development Environment (IDE) 2019 version on Windows 10 operating system. The hybridized algorithm was compared with other five (5) existing energy reducing algorithms and it was found to be more efficient with a range of 41-90% reduction in energy usage from the ten days workload traces and in comparison with the existing algorithms used for the simulation.

A smart contract and IPFS-based framework for secure electric vehicles synchronization at charging station

The growth of electric vehicles (EVs) at a significant pace is a promising solution for reducing harmful greenhouse gas emissions compared to conventional vehicles. Nevertheless, optimal and efficient EV charging management is a serious concern that needs to be solved for the benefit of both charging stations (CSs) and EVs. In this regard, we proposed a smart contract and Interplanetary File System (IPFS)-based secure EV synchronization framework at the CS utilizing a 5G wireless network. Blockchain technology strengthens the security of the EV charging at the CS in a synchronized and coordinated manner. The IPFS and 5G wireless network ensure efficient and reliable EVs synchronization to charge vehicles from the available number of charging points (CPs) at a CS. Furthermore, we have coordinated and synchronized the EV charging, considering various scenarios based on the waiting queue time, energy demand, and EVs (they can arrive in an emergency). We have shown the implementation interface of the proposed model based on the execution of a smart contract using the Remix Integrated Development Environment (IDE). Moreover, we have performed the security analysis of the smart contract using Echidna fuzzing-based tool to ensure the secure EVs allocation to the corresponding CS. Finally, the performance analysis of the IPFS and smart-based proposed model is evaluated and simulated considering various metrics such as transaction storage cost analysis, computational and communication overhead analysis, utilized cost based on the smart contract functions, and the number of EVs.

Logistic Model for Predicting Coliform Growth in Wastewater Effluent From the Chambo River (Ecuador)

Purpose: The objective of this work is to apply a predictive model of bacterial growth to determine the concentration of total coliforms, under controlled laboratory conditions, in wastewater from the city of Riobamba that flows into the Chambo River (Ecuador). Theoretical Framework: Wastewater pollution is a global problem that affects water quality and public health. Population growth has a drastic impact on the contamination of water bodies, particularly in Ecuador, since most of the effluents are not adequately treated, which becomes a public health and environmental problem. For this reason, over the years, total and fecal coliforms have been used as indicators of water quality. Design/Methodology/Approach: The study used a mathematical modeling approach of a logistic and deterministic type, and calculated through an executable command designed in the integrated development environment (IDE) with the Visual C# programming language (logic) and the XAML design language (interface). Findings: The results achieved are 1) the theoretical construction of a mathematical model (logistic model) starting from a differential equation and the taking of three experimental measurements, 2) the computer construction of the bacterial growth model and 3) it has been demonstrated that there is agreement between the values obtained from the model of total coliform growth and the experimental results with a margin of error of less than 1%. Research, Practical & Social Implications: This information can be used by stakeholders to determine actions that could improve current conditions. Originality/Value: The result of this study emphasizes that the model proposed can reproduce the growth of coliforms up to a maximum growth point, it is necessary to continue with the development of the same in the stationary phase of bacterial growth and then in the decay phase.

Logistic Model for Predicting Coliform Growth in Wastewater Effluent From the Chambo River (Ecuador)

Purpose: The objective of this work is to apply a predictive model of bacterial growth to determine the concentration of total coliforms, under controlled laboratory conditions, in wastewater from the city of Riobamba that flows into the Chambo River (Ecuador). Theoretical Framework: Wastewater pollution is a global problem that affects water quality and public health. Population growth has a drastic impact on the contamination of water bodies, particularly in Ecuador, since most of the effluents are not adequately treated, which becomes a public health and environmental problem. For this reason, over the years, total and fecal coliforms have been used as indicators of water quality. Design/Methodology/Approach: The study used a mathematical modeling approach of a logistic and deterministic type, and calculated through an executable command designed in the integrated development environment (IDE) with the Visual C# programming language (logic) and the XAML design language (interface). Findings: The results achieved are 1) the theoretical construction of a mathematical model (logistic model) starting from a differential equation and the taking of three experimental measurements, 2) the computer construction of the bacterial growth model and 3) it has been demonstrated that there is agreement between the values obtained from the model of total coliform growth and the experimental results with a margin of error of less than 1%. Research, Practical & Social Implications: This information can be used by stakeholders to determine actions that could improve current conditions. Originality/Value: The result of this study emphasizes that the model proposed can reproduce the growth of coliforms up to a maximum growth point, it is necessary to continue with the development of the same in the stationary phase of bacterial growth and then in the decay phase.

Teaching colour addition with a STEM educational resource based on Arduino and Processing Development Environment

STEM Education is an important topic in today’s educational paradigm. The knowledge in the STEM area will be important to everyone because to solve real-world problems it is necessary to have information from different areas of knowledge. In this perspective we present an educational resource that combines the contents of physics (colour addition with LEDs), engineering (circuit assembly), technology (Arduino platform and Processing, an open-source programming language and integrated development environment), and mathematics (number handling and unit conversion). Although there are many examples in the literature regarding the study of colour addition, the educational resource here presented brings a novelty for the students. With a very intuitive setup and a simulation, students are able to understand colour addition perceived by the human eyes from two different mechanisms simultaneously: the colour seen on a computer screen and the colour produced by an RGB LED. This STEM activity uses a very simple and affordable experimental setup (less than 30 dollars, excluding the computer) and it is a clear example of how technology enhanced learning in science can be incorporated in the classroom for teaching physics in a very engaging context.

Development and research of an intelligent control system and protection of electrical network equipment

The key element of an intelligent energy system with an active-adaptive network is relay protection, designed to ensure uninterrupted and stable operation of the energy system. The goal of the work is the development and research of intelligent control systems, protection and automation of electrical networks. Research has been carried out on an intelligent security system to determine the boundaries of restrictions in the use of artificial intelligence. The authors supplemented the existing complex with physical models of the power supply system with a digital twin, an artificial neural network, and studied the complex in order to answer some questions about the use of a neural network in relay protection. An iterative approach to software development, supervised machine learning method, and Python programming language were used. Pychram Community Edition was chosen as the integrated development environment. Intelligent system software has been developed, including a digital twin, an executive part and a neural network model, which makes it possible to recognize types of short circuits in the electrical network. The works of domestic and foreign authors on this topic are considered.

Event-driven method of measuring effectiveness of information security controls in software development environments

Event-driven method of measuring effectiveness of information security controls in software development environments

Fuzzy Logic Control System for Optimizing Dual-Axis Solar Panel Tracking

The utilization of solar energy through solar panels has gained considerable attention in renewable energy applications. However, the effectiveness of energy conversion is hindered by the misalignment of solar panels with the incident sunlight. To address this issue, a dual-axis solar tracker system is proposed to automatically adjust the orientation of solar panels, enhancing energy generation efficiency. This research introduces a novel approach using a fuzzy logic control system to regulate the movement of stepper motors responsible for adjusting the solar panel positions. The system relies on input data from Light-Dependent Resistor (LDR) sensors to detect the sunlight’s position. Additionally, voltage, current, and angle sensors are integrated to accurately determine the solar panels angular position. The fuzzy logic control system employs the Mamdani method with Mean of Maximum (MOM) defuzzification. A comprehensive analysis of the systems performance was conducted, demonstrating that the manual calculations yielded 0.87 and 0.59 micro steps, while the Fuzzy Inference System (FIS) produced 0.35 and 0.26 micro steps. These results were verified through the serial monitor in the Arduino Integrated Development Environment (IDE). This research focuses on the development of a microcontroller-based two-axis solar panel control system using fuzzy logic. The system’s primary objective is to maximize solar energy utilization by ensuring that solar panels consistently align with the direction of sunlight, both vertically and horizontally. The proposed system offers an effective means of enhancing the efficiency of solar panel energy generation by continuously optimizing their alignment with the incident sunlight.

Knowledge-aided Integrated Development Environment (K-IDE) for Control Software Development

Knowledge-aided Integrated Development Environment (K-IDE) for Control Software Development

Julia as a Universal Platform for Statistical Software Development

Julia as a Universal Platform for Statistical Software Development

CREATOR: An Educational Integrated Development Environment for RISC-V Programming

CREATOR: An Educational Integrated Development Environment for RISC-V Programming

Andrioid mobile application aimed at getting personalized recommendations when selecting references

This article presents the results of the development of a mobile recommendation application to help library readers select references. One of the tasks of a librarian is to provide consultative assistance to the reader in selecting books. Working with a librarian can be replaced by the use of electronic library systems or special programs, which will allow you to solve the same task in less time. At the moment, there are websites and digital libraries that help the user to select books for further reading. They implement various algorithms that allow you to create personalized recommendations. Such systems are designed for electronic reading and are not linked to the databases of municipal library systems. Library readers can obtain recommendations when they choose literature for further reading using a mobile application. The paper considers the process of its creation: analysis of program requirements, design, implementation, testing and implementation. The application is developed for the Android operating system in the integrated development environment Android Studio in the Java programming language. The calculation of the technical and economic indicators of the project in its implementation has shown that the use of the application will provide sufficient economic effect. Its use can simplify the process of selecting books and significantly reduce the time to search for them, thus giving the librarian the opportunity to perform other tasks. The program does not require material costs for installation, which is an obvious advantage, and the functionality and system requirements allow its use on all mobile devices with the Android operating system.