Integrated Development Environment Research Articles

Інформаційна технологія оцінювання теплоізоляції багатошарових стін

In today's conditions, the problem of insulation of surfaces is very relevant for wide circles of the population of Ukraine. Everyone knows that surface insulation allows to reduce heat transfer due to the use of materials with low thermal conductivity. In the absence of permanent heating, the issue of thermal insulation of cylindrical pipes is very relevant. The issue of insulation selection and structural design requires a complex and professional approach. To calculate the problem of thermal insulation, a specialist needs to have a toolkit for calculating the temperature field and saving the obtained results for further analysis. The work presents the developed information technology that allows a specialist to calculate the temperature field for multilayer cylindrical pipes. The object-oriented programming language C# and the Microsoft Visual Studio integrated development environment were used to build the IT toolkit. It should be noted that when making calculations, there is no need to specify the characteristics of pipe and insulation materials, since all data is stored in the IT database. The object-relational database management system - PostgreSQL was used to build the data module. After the calculations, all the built calculation models and the received numerical models of the results are also stored in the database. This allows you not to recalculate if necessary, but to use the data that is already available. To analyze the results, the developed toolkit allows you to plot temperature changes of a multilayer wall. At the same time, the user selects the necessary calculation models independently from IT database data. The DirectX three-dimensional graphics development tool package is used for visual representation of numerical model calculations. The authors developed an algorithm for constructing a color temperature field according to the calculations. Red is chosen for the highest field temperature, and blue for the lowest temperature. A feature of the proposed information technology is that its functionality allows three users with different levels of access to work with the toolkit: a database administrator, a mathematical model construction engineer, and a numerical model analysis specialist.

An Approach to Track and Analyze the Trend of Antimicrobial Resistance Using Python: A Pilot Study for Anand, Gujarat, India-May 2022-August 2023.

The present work deals with the analysis and monitoring of bacterial resistance in using Python for the state of Gujarat, India, where occurrences of drug-resistant bacteria are prevalent. This will provide an insight into the portfolio of drug-resistant bacteria reported, which can be used to track resistance behavior and to suggest a treatment regime for the particular bacteria. The present analysis has been done using Python on Jupyter Notebook as the integrated development environment and its data analysis libraries such as Pandas, Seaborn, and Matplotlib. The data have been loaded from excel file using Pandas and cleaned to transform features into required format. Seaborn and Matplotlib have been used to create data visualizations and represent the data inexplicable manner using graphs, plots, and tables. This program can be used to study disaster epidemiology, tracking, analyzing, and surveillance of antimicrobial resistance with a proper system integration approach.

On the Application of Big Data in Smart Transformation Enterprises

The arrival of the digital informationization era heralds the issue of technological innovation in the intelligent transformation of enterprises, for different scenarios and different cases, the application of big data plays an important role in the accumulation of massive data, the issue of the reliability of the data and the form of data transformation with the transformation of the enterprise has undergone a significant change in the data processing software platform, and strive to deal with the accuracy and efficiency of the data is a multitude of Enterprises plan to achieve the goal, under the general software of big data, the introduction of data information software platform is undoubtedly an important initiative in today's society in order to meet the massive data research. This paper summarizes the development and application of data information software platforms on the basis of awards, data as a prerequisite, put forward for intelligent platforms to monitor the systematic approach to the integration of the Sqoop framework in the Hadoop platform for the enterprise to formulate an intelligent data monitoring indicators of the processing model.

FQN Inference in Partial Code by Prompt-tuned Language Model of Code

Partial code usually involves non-fully-qualified type names (non-FQNs) and undeclared receiving objects. Resolving the FQNs of these non-FQN types and undeclared receiving objects (referred to as type inference) is the prerequisite to effective search and reuse of partial code. Existing dictionary-lookup based methods build a symbolic knowledge base of API names and code contexts, which involve significant compilation overhead and are sensitive to unseen API names and code context variations. In this article, we propose using a p rompt-tuned c o de m asked language mod e l (MLM) as a neural knowledge base for type inference, called POME, which is lightweight and has minimal requirements on code compilation. Unlike the existing symbol name and context matching for type inference, POME infers the FQNs syntax and usage knowledge encapsulated in prompt-tuned code MLM through a colze-style fill-in-blank strategy. POME is integrated as a plug-in into web and integrated development environments (IDE) to assist developers in inferring FQNs in the real world. We systematically evaluate POME on a large amount of source code from GitHub and Stack Overflow, and explore its generalization and hybrid capability. The results validate the effectiveness of the POME design and its applicability for partial code type inference, and they can be easily extended to different programming languages (PL). POME can also be used to generate a PL-hybrid type inference model for providing a one-for-all solution. As the first of its kind, our neural type inference method opens the door to many innovative ways of using partial code.

Prompt Sapper: A LLM-Empowered Production Tool for Building AI Chains

The emergence of foundation models, such as large language models (LLMs) GPT-4 and text-to-image models DALL-E, has opened up numerous possibilities across various domains. People can now use natural language (i.e. prompts) to communicate with AI to perform tasks. While people can use foundation models through chatbots (e.g., ChatGPT), chat, regardless of the capabilities of the underlying models, is not a production tool for building reusable AI services. APIs like LangChain allow for LLM-based application development but require substantial programming knowledge, thus posing a barrier. To mitigate this, we systematically review, summarise, refine and extend the concept of AI chain by incorporating the best principles and practices that have been accumulated in software engineering for decades into AI chain engineering, to systematize AI chain engineering methodology. We also develop a no-code integrated development environment, Prompt Sapper , which embodies these AI chain engineering principles and patterns naturally in the process of building AI chains, thereby improving the performance and quality of AI chains. With Prompt Sapper, AI chain engineers can compose prompt-based AI services on top of foundation models through chat-based requirement analysis and visual programming. Our user study evaluated and demonstrated the efficiency and correctness of Prompt Sapper.

An Educational Study of Electromagnetic Phenomena on Ferromagnetic Structure Using a Software Environment

AbstractThe solution to electromagnetic problems relies on complex numerical differential equations that are difficult to understand. Therefore, it is crucial to analyze them step by step and visualize them in a computer environment, even by developing a program. This approach enhances understanding of the subject and facilitates further research. In this study, an electromagnetic phenomenon is examined on a ferromagnetic structure using the Maxwell 2D static-elliptical partial differential equation within a developed software environment. The paper covers all aspects, ranging from the mathematical model and analysis solution to the fundamental operating parameters and characteristics, with a focus on educational purposes. The modeling and software development have been executed in a user-friendly manner, enabling students to apply various numerical techniques to practical problems while maintaining control over the entire modeling process. Through this study, it is anticipated that the transition from theory to practice can be facilitated more smoothly and directly. The theoretical analysis has been conducted using Mathematica software, and a comparison with finite element magnetic method simulation on a typical magnetic structure has been presented to illustrate the analogy. A comprehensive analysis of the Maxwell static-elliptical electromagnetic equation, based on a 2D numerical solution within a specific domain, has been performed in a detailed and unambiguous manner, utilizing different equation forms, boundary conditions, and ferromagnetic materials, all for educational purposes.

VIRTUAL REALITY (VR) ASSISTED GEOMATICS LAB DEVELOPMENT

Abstract. Virtual Reality (VR) lab components provide the opportunity to explore the efficacy of this technology on Geomatics education and lay the groundwork for the VR as an emerging education paradigm. Geomatics education at UF has been innovatively optimized towards a hybrid education system, with most of the curriculum taught using distance communication. Nevertheless, Geomatics teaching still involves intensive indoor and outdoor lab components. VR labs enable learning and practicing lab techniques as an alternative or supplement to live lab activities. These technically and physically demanding activities require intensive training on expensive lab equipment. The labs often go beyond allocated lab time and are susceptible to bad weather conditions. Using VR technology provides an integrated learning experience that mixes instructions with simulated physical activities, eliminating many limitations associated with lab instruction. In this study, we demonstrate the development of the total station device centring and levelling lab activity using the Meta Quest 2 Headset on the Unity Software Development Platform, as well as Unity’s XR Interaction Toolkit. Development challenges related to different setup components (e.g., bubble-level setup, effective gravity for editing tripod placement, component intractability) are presented. Among multiple challenges of using Unity for the development of an educational VR application, adjusting the functions of the XR Toolkit in order to get the desired outcomes stands as one of the largest difficulties. Unity’s physics is not intuitive for the intended purposes of this project, so multiple technical workarounds were required including the use of Unity’s UI (User Interface) features.

Design and construction of an Ultrasounographic Device Dedicated to the Parietal Rheology Measurement in Human Carotid Artery

We present in this article a detection system of ultrasounographic signal (USG) dedicated to the measurement of parietal rheology in human carotid artery. The aim of this practical work is to develop an ultrasonic method capable of visualizing the localized velocity profile of the carotid artery wall. The device produced makes it possible to take the USG signal from carotid wall of the human neck. It comprises an ultrasonic contact probe applied during the measurement (sensor), a signal shaping circuit, an acquisition and digitization interface in conjunction with an RS232 serial communication port and a local computer terminal hosting a graphical user interface (GUI) implemented in Visual Basic integrated development environment enabling the display, archiving and the digital processing of parietal ultrasonic signal. The aim of this study is to reconnoitering the possibility of using ultrasound for a continuous and non-invasive measurement of the arteries parietal rheology. In this work, a sensor of ultrasound is used to measure the movement and the speed of the carotid artery wall, an image of the arteries parietal rheology.

AI Pair Programming Tool

Abstract: In the ever-evolving landscape of software development, the need for tools that augment developer productivity is paramount. This paper introduces a novel integration of IntelliJ IDEA, a widely used integrated development environment (IDE), with OpenAI's advanced deep learning models. The synergy between these two technologies aims to elevate the coding experience by providing intelligent code assistance, allowing developers to write code more efficiently and with greater accuracy. Our approach leverages OpenAI's natural language processing capabilities to enhance code suggestions, auto-completions, and error detection within IntelliJ IDEA. By analyzing vast code repositories and learning from diverse coding patterns, our system empowers developers with context-aware recommendations, significantly reducing the cognitive load associated with code creation. This paper presents the architecture of our solution, detailing the seamless integration of OpenAI's models into the IntelliJ IDEA IDE. We discuss the methodology behind training the models, emphasizing their adaptability to various programming languages and project structures. Furthermore, we present empirical results demonstrating the effectiveness of our approach in real-world coding scenarios.

Study On the Path To Improve the Leadership Of Sports Counselors And Students' Employability

Graduates "difficult employment" has become a prominent problem in the general college education, the so-called "graduation = unemployment" concept seriously affects the realization of the goal of talent training in colleges and universities. However, the employment channels of sports major itself are relatively narrow, and many students are engaged in jobs irrelevant to their major after graduation. Therefore, this paper aims to promote the improvement of college counselors' quality and employment rate by discussing the promotion path of sports counselors' leadership and students' employment ability. To sum up, in the face of increasingly complex computer application environment, the development of computer software has put forward more stringent and diversified requirements. Therefore, the introduction of layered technology to computer software development, constantly improve the computer software development environment, improve the development efficiency, shorten the software development cycle, save the cost of software development, so as to promote the sustainable and healthy development of computer software industry.

Food Quality Monitoring System

Food poisoning affects around 600 million people each year, with 4,20,000 people dying as a result. People frequently ingest damaged meals since there are no obvious signs of deterioration. Foods release gases like Methane, Ethylene and Ammonia when they decompose. This paper introduces Food Spoilage Detection by using sensor and displayed on character 16x2 LCD. We are living in the world, where one third food is wasted every year. It is more than enough to feed millions of people in the world. Most considerable reason for food wastage is food spoilage. Food spoilage can be detected in many ways. Our project mainly focuses food spoilage detection using Sensor. In components used in this project is LCD display, sensors and Arduino Uno. Sensors, LCD display is interfaced to Arduino Uno. By using sensors we can detect the gases coming from food. The sensor sends the data to LCD display where we can view whether food is spoiler. Software required to program Arduino Uno is Arduino Integrated development environment (IDE). Hardware required for this project is Arduino board, MQ3 sensor, character 16x2 LCD, USB cable, power supply and connecting wires

IDE vs. pen-and-paper showdown - Performance and perceptions of testing first-year IT students’ programming skills

This study analysed first-year IT students' performance and perceptions of using Integrated Development Environment (IDE) versus pen and paper (P&P) based programming testing methods. 68 participants completed two programming tests using both testing methods, and the results were evaluated on complexity, quality and other criteria. No significant difference was observed in the average scores between the two test methods. However, IDE testing showed fewer syntax errors and lower cyclomatic complexity, indicating the potential advantages of IDE's error-checking. IDE tests exhibited higher variability in student performance, suggesting varying comfort levels with the test environment. Additionally, a weaker correlation existed between actual and perceived performance in IDE tests, highlighting challenges in self-evaluation within a digital framework. Most students preferred IDE-based testing, citing efficiency, user-friendliness, and real-time feedback. Nonetheless, a minority recognised the value of P&P tests for demonstrating deep syntax understanding. This research enhances our understanding of programming pedagogy and assessment.

Adapting Jupyter for C++ Programming Education: An Empirical Study on Lab Instruction Strategies and Student Perspectives

This paper explores the use of the Jupyter platform in teaching C++ programming at the higher education level. It includes a comparative analysis between traditional integrated development environments and online judge systems. The study discusses a teaching approach that leverages JupyterHub and Xeus-Cling to create an interactive learning setting. This approach was pilot-tested during a C++ lab session at Shenzhen Technology University, and student feedback was subsequently gathered and analyzed. A substantial number of students found value in Jupyter's interactive capabilities and the seamless integration of code execution and report writing. However, others experienced difficulties with the platform due to adaptation hurdles, code compatibility issues, and the lack of functionality compared to traditional integrated development environments. The paper further explores the potential of integrating Jupyter with the Visual Studio Code environment to mitigate these limitations and amplify its benefits. The paper concludes by recommending ongoing research and evaluation to refine and adapt this innovative teaching strategy.

AIBugHunter: A Practical tool for predicting, classifying and repairing software vulnerabilities

Many Machine Learning(ML)-based approaches have been proposed to automatically detect, localize, and repair software vulnerabilities. While ML-based methods are more effective than program analysis-based vulnerability analysis tools, few have been integrated into modern Integrated Development Environments (IDEs), hindering practical adoption. To bridge this critical gap, we propose in this article AIBugHunter, a novel Machine Learning-based software vulnerability analysis tool for C/C++ languages that is integrated into the Visual Studio Code (VS Code) IDE. AIBugHunter helps software developers to achieve real-time vulnerability detection, explanation, and repairs during programming. In particular, AIBugHunter scans through developers’ source code to (1) locate vulnerabilities, (2) identify vulnerability types, (3) estimate vulnerability severity, and (4) suggest vulnerability repairs. We integrate our previous works (i.e., LineVul and VulRepair) to achieve vulnerability localization and repairs. In this article, we propose a novel multi-objective optimization (MOO)-based vulnerability classification approach and a transformer-based estimation approach to help AIBugHunter accurately identify vulnerability types and estimate severity. Our empirical experiments on a large dataset consisting of 188K+ C/C++ functions confirm that our proposed approaches are more accurate than other state-of-the-art baseline methods for vulnerability classification and estimation. Furthermore, we conduct qualitative evaluations including a survey study and a user study to obtain software practitioners’ perceptions of our AIBugHunter tool and assess the impact that AIBugHunter may have on developers’ productivity in security aspects. Our survey study shows that our AIBugHunter is perceived as useful where 90% of the participants consider adopting our AIBugHunter during their software development. Last but not least, our user study shows that our AIBugHunter can enhance developers’ productivity in combating cybersecurity issues during software development. AIBugHunter is now publicly available in the Visual Studio Code marketplace.

Deployment of Model-Based-Design-Adaptive Controllers for Monitoring and Control Mechatronic Devices

The modeling and control of complex, non-linear, and time-changing mechatronic systems requires complex software development. They are carried out in the prototyping phase with engineering software development tools, generating models, and control algorithms that are not always easily exportable to control hardware. The following work offers an alternative that considers Model-Based Design using graphics-based languages, which facilitates programming tasks for modeling and controlling mechatronic devices and their transition from prototype to control hardware. Model-Based Design with high abstraction programming level capabilities provides the user with a fast coding and testing environment, suitable for laboratory prototyping and subsequent transfer to commercial embedded controllers. The proposed solution combines control hardware based on an STM32H7 microcontroller and a software development environment using graphics-based languages developed for MATLAB. The result is a solution that integrates control hardware and software in a hardware-in-the-loop paradigm. This solution provides robust and energy-saving controllers and demonstrates that an advanced control algorithm can be set up in a critical safety-compliant low-cost embedded controller via a custom model-based design. Algorithms and tools are transferred to the controller without losing the advantages gained in the prototyping phase. Finally, experimental results implementing an adaptive controller in a DC motor and in a pneumatic system are shown to validate the system.

Multicriteria Optimization of Software Development Platform Selection

The problem of multicriteria optimization of tech stack selection in a non-linear software development environment is formalized. Approaches to solving the problem based on the formation of a compromise area of local quality criteria, additive convolution of vector criteria and their scalarization are considered. An aggregate quality criterion of the software development platform is proposed. It allows taking into account the nonlinearities of the external environment in the framework of solving the problem of extremal control. The coordinates of the vector criteria are piecewise continuous functions A comparative analysis of various approaches to changing the software development tech stack in the face of significant disturbances in the development tools market has been carried out. The possibilities of boxed solutions, custom development and Open Source software development in ensuring information security of the software development environment are shown. The information stability of a software development project using Less Code tools is established and the advantages of technological solutions are shown. The analysis of the adequacy of the obtained solutions was carried out using the Open Source Less Code of the Jmix platform. The data of a comparative analysis of the budgets of the Less Code platform and custom software from vendors are given, which showed the benefits of using Open Source software development tools for long-term operation of the development platform.

Evolvable Hardware Based Optimal Position Control of Quadcopter

Trading off performance metrics in control design for position tracking is unavoidable. This has severe consequences in mission-critical systems such as quadcopter applications. The controller area and propulsion energy are conflicting design parameters, whereas the reliability and tracking speed are related metrics to be optimized. In this research, a switching-based position controller was co-simulated with the quadcopter model. Performance analysis of the Field Programmable Gate Array (FPGA)-based controller validates a better scheme for tracking speed, propulsion energy, and reliability optimization under similar error performance. To improve the computation power and controller area, the dynamic partial reconfiguration(DPR) approach has been adapted and implemented on FPGA using the Vivado Integrated Development Environment (IDE), where a ranking-based approach brings into action either proportional derivative, sliding mode, or model predictive controllers for each dimension of position tracking. It is verified by analyzing the cumulative tracking speed, reliability, controller area, and propulsion energy metrics that the proposed controller can optimize all these metrics within three successive iterations of tracking either in the same direction or in any combination of directions. Concerning the implementation results of the controller with the switching-based controller, there is 6 % computation power and 30 % resource savings due to DPR .

Research Paper on Analysis Load Balancing Algorithm using Cloud Computing

Cloud load balancing is nothing but distributing the work load among many servers & computing property. It can manage work load demand as well as application demand. This process is done with the help of distributing resources among numerous computers. Cloud load balancing consist of circulation of workload traffic & on time demand of internet. Various techniques were represented in literature to improve performance, quality of services, cargo distribution etc. The issue of cargo balancing is same as cloud computing which is data over loading & under loading. We have to apply proper cargo balancer for cloud terrain. The study represents view of problem faced by current cargo balancing ways. The researchers make more effective algorithm. Cloud computing refers to a services & application that can accessible throughout the world from data center.all services are accessible through online. There are several issues in cloud computing such as scheduling, load balancing, quality of services & storage resources. Here we study load balancing. When many clients send request to server, server has already n number of task. In that case server is over loaded for this condition we have to apply load balancing algorithm. Cloud computing is a internet based network technology that share rapid growth in communication technology, by providing services to customer of various requirement with the help of online computing resources. It has both hardware & software application along with software development platform. Cloud computing becomes a popular word in the area of high performance distributed computing. It provide on demand access to share pool of resources over internet. Cloud computing is still much research is required for broad array of topic. One of the important research issue which need to be focus for effective performance isload balancing. Cloud computing aim is to gives computation & resources over the internet via dynamic provision of services. There are many challenges and issues associated with the implementation of cloud computing. This research paper deliberates one of cloud computing main problem that is load balancing. The main aim of load balancing is equally distribute the load on cloud server such that no host is under load & over load. Several load balancing algorithm have been implemented in literature to satisfied customer request for appropriate cloud node.

An internet of things-based touchless parking system using ESP32-CAM

<span>As technology continues to advance, governments around the world have implemented health protocols to minimize direct contact between individuals and objects, in response to the ongoing COVID-19 outbreak. To address this need, a touchless parking portal was designed using a microcontroller-based and internet of things (IoT) -based system, with the Arduino UNO microcontroller device serving as the core component. The system employs an ultrasonic sensor HC-SR04 and passive infrared (PIR) to detect vehicles as they arrive at the portal area, in addition to requiring an ESP32-CAM camera, servo motor, light-emitting diode (LED), I2C 16x2 liquid crystal display (LCD), push button, universal serial bus (USB) to transistor-transistor logic (TTL) converter, power supply, and portal bar. The system builder software was developed using Arduino integrated development environment (IDE), Android, and Blynk. The authors conducted thorough testing and analysis of the system, concluding that its overall performance reaches 100%. Nevertheless, despite the extensive experimentation conducted, there remains a possibility that certain factors could still affect the results. Therefore, caution is advised when interpreting the outcomes of this experiment.</span>

PREDICTING CREDIT WORTHINESS IN BANK LOAN APPROVAL PROCESS

Loans make up significant part in bank profits. In a bank, amongst large number of loan applications, it can be lengthy and challenging to choose genuine and eligible applications to approve the loan, if the process is done manually. The system was developed using Python 3.7 & its libraries and Jupyter Notebook cross-platform Integrated Development Environment (IDE). The developed system uses the machine learning algorithms - Naïve Bayes, Support Vector Machine (SVM) and XGBoost (Extreme Gradient Boosting) individually to classify the loan applications to automatically choose genuine and eligible applications. Based on average bank balance of the period and financial background, the system approves the loan amount to the predicted applicants with good credit history. The system’s performance in predicting the credit worthiness of applicants was evaluated. Naive Bayes algorithm predicted the credit worthiness with 79% accuracy, SVM algorithm with 81% and XGBoost algorithm with 84%.