Programming Platform Research Articles

Design and implementation of the dual-center programming platform for ternary optical computer and electronic computer

In order to utilize the advantages of optical computing and promote the application and popularization of Ternary Optical Computer (TOC), this paper proposes a dual-center programming model consisting of electronic processor and optical processor, presents the theory and technologies of the dual-center model in detail, and for the first time explains the SAN ZHI GUANG (SZG) file chain technology, gives the implementation method of the dual-center model. The model tries to effectively manage the resources of optical processor and solve the problem of the distance and network connection mode of using the TOC. Experimental results show that the dual-center model is correct and the implementation method is feasible. It can improve the usability of the TOC and further simplify the TOC programming process, and makes common users apply the TOC and electronic computer to work cooperatively for the same task.

A Survey on IoT Programming Platforms: A Business-Domain Experts Perspective

The vast growth and digitalization potential offered by the Internet of Things (IoT) is hindered by substantial barriers in accessibility, interoperability, and complexity, mainly affecting small organizations and non-technical entities. This survey paper provides a detailed overview of the landscape of IoT programming platforms, focusing specifically on the development support they offer for varying end-user profiles, ranging from developers with IoT expertise to business experts willing to take advantage of IoT solutions to automate their organization processes. The survey examines a range of IoT platforms, classified according to their programming approach between general-purpose programming solutions, model-driven programming, mashups and end-user programming. Necessary IoT and programming backgrounds are described to empower non-technical readers with a comprehensive field summary. In addition, the paper compares the features of the most representative platforms and provides decision insights and guidelines to support end-users in selecting appropriate IoT platforms for their use cases. This work contributes to narrowing the knowledge gap between IoT specialists and end users, breaking accessibility barriers and further promoting the integration of IoT technologies in various domains.

ID: 330339 Study Results Demonstrating Feasibility of Novel Automated SCS Programming Platform

ID: 330339 Study Results Demonstrating Feasibility of Novel Automated SCS Programming Platform

A robust septic hermite collocation technique for dirichlet boundary condition Heat conduction equation

Abstract In the current manuscript, approximate solution for 1D heat conduction equation will be sought with the Septic Hermite Collocation Method (SHCM). To achieve this goal, by means of the roots of both Chebyschev and Legendre polynomials used at the inner collocation points, the pseudo code of the method is found out and applied using Matlab which is one of the widely utilized symbolic programming platforms. The unconditional stability of the scheme is shown by the traditional von-Neumann stability technique. To illustrate the accuracy and effectiveness of this newly current numerical scheme, a comparison among analytical and the computed numerical results is presented in tabular forms. It has been illustrated that the scheme is both accurate and effective one and at the same time can be used in a successful way for finding out numerical solutions of several nonlinear problems as well as linear ones.

Massively Parallel Computational Chemistry with the Super Instruction Architecture and ACES4.

The task of developing high-performing parallel software must be made easier and more cost-effective in order to fully exploit existing and emerging large-scale computer systems for the advancement of science. The Super Instruction Architecture (SIA) is a parallel programming platform geared toward applications that need to manage large amounts of data stored in potentially sparse multidimensional arrays during calculations. The SIA platform was originally designed for the quantum chemistry software package ACESIII. More recently, the SIA was reimplemented to overcome the limitations in the original ACESIII program. It has now been successfully employed in the new ACES4 quantum chemistry software package. This paper describes the SIA and ACES4 and illustrates their capabilities with some difficult quantum chemistry open-shell coupled-cluster benchmark calculations.

InerSens: A Block-Based Programming Platform for Learning Sensor Data Analytics in Construction Engineering Programs

InerSens: A Block-Based Programming Platform for Learning Sensor Data Analytics in Construction Engineering Programs

Development of the Basket Challenge Game Using Scratch Application

The Basketball Challenge game was created using Scratch, a visual programming platform that enables the development of educational games in an easy and interactive manner. Basketball Challenge is designed with a storyline where players must collect as many balls as possible to reach the required score to advance to the next level. If players fail to collect the balls according to the target, the game will end with a game over, and players will have to start again from the initial level. Conversely, if players manage to collect the balls to meet the target, they will proceed to the next level. This study aims to explore the development process of this game, including level design, gameplay mechanics, asset creation, as well as testing and debugging. The results indicate that Scratch is an effective tool for developing educational games that can be played by all age groups, providing an enjoyable gaming experience while also training players' cognitive and motor skills.

SIMULACIÓN AVANZADA DE UN BRAZO ROBÓTICO CON 2 GRADOS DE LIBERTAD, CONTROLADO EN SIMSCAPE

In this project, a robotic arm was developed, modeled, and implemented using the Matlab Simulink programming platform. The robotic arm was designed with 2 degrees of freedom and equipped with three motors, allowing for precise and coordinated control of its movements. For simulating the dynamic and kinematic behavior of the arm, Simscape blocks were used, facilitating a detailed three-dimensional representation of the system. The main objective of the project was to demonstrate a simulation of the robotic arm that allows for precise control of the movement angles. Through a detailed 3D simulation in Simscape, the movement and interaction of the arm's components could be visualized, validating its capability to perform tasks with high precision and efficiency. The results obtained demonstrate the effectiveness of using Simulink and Simscape in the design and simulation of robotic systems, highlighting the importance of these tools for automated development.

Elevating the RRE Framework for Geospatial Analysis with Visual Programming Platforms: An Exploration with Geospatial Analytics Extension for KNIME

Reproducibility, replicability, and expandability (RRE) have emerged as fundamental concerns in the realm of scientific research and development. Wherein, devising effective solutions for RRE within geospatial analysis stands out as a particularly critical challenge that demands immediate attention. Although there has been an evolution from basic reproducibility of code and data to a more comprehensive cyberinfrastructure, this integrated solution is still grappling with issues of limited user accessibility, steep learning curves particularly in coding skills, and difficulties in achieving collaboration with other data science platforms This study proposes a framework that combines open-source GIS with visual programming platforms, grounded in principles of standardization and educationalization, to advance the RRE framework in geographic analysis. Using the Geospatial Analytics Extension for KNIME as an example, we demonstrate the platform’s adaptability and utility through case studies in a recent textbook with an in-depth illustration of spatial accessibility analysis, specifically via the Generalized Two-Step Floating Catchment Area (G2SFCA) method. Our findings shed light on the transformative potential of such an integrative strategy, offer fresh perspectives for enhancing the RRE in geospatial analysis and craft a well-structured, intuitive, and extensive GIS knowledge tree.

High-resolution dynamic thermal programming platform based on micro thermoelectric device assisted by laser integrated manufacturing

Thermoelectric devices (TEDs) exhibit much application potential in thermal camouflage and encrypted display recently, requiring that TEDs possess large responsivity, high resolution and rapid response with flexible configuration design, which are hardly realized by the traditional complex fabrication process. In this work, an innovative laser integrated manufacturing technology including double-side-printing selective laser melting (D-SLM) and selective laser ablation (SLA) is developed for the construction of the dynamic thermal platform based on micro TEDs. Through experimentally determining the laser process window assisted by external temperature field regulation, a flat p-type film can be directly transformed from n-type Bi2Te3 film by D-SLM. Thus, high-precision p-n patterns without metal joints are obtained from a single locally modified film, whose thermoelectric properties are further boosted by increasing energy density and introducing a post-annealing process. Then, a dynamic thermal platform with designable shapes and small dimensions can be fabricated rapidly whose working principle is also demonstrated. The thermal platform with 4*4 arrays exhibits imaging function with a pixel size of 2 mm×2 mm, a temperature difference of ∼3 K, and a fast response time of 0.143 s. This work offers an exciting yet effective approach to fabricating TEDs for dynamic thermal programmable information displays.

Software Implementation of the Epps-Pulley Criterion in Matlab Modeling Environment

Purpose. Modeling systems and programming platforms provide ample opportunities for the use of statistical tools in research activities. Since the normal distribution is one of the most common distribution laws, the criterion for checking the sample for normality is in high demand among statistical assessment tools, among which the Epps-Pulley test has the status as one of the most powerful tests to check the deviation of the distribution from the normal one. There are a number of implementations of this test in the R and Python languages. However, this test is not implemented in one of the most popular Matlab modeling software. Thus, the purpose of this study is to develop a software implementation of the Epps-Pulley criterion in the Matlab environment and verify the correctness of the performed calculations.Materials and Methods. We implemented the calculation of Epps-Pulley statistics by two methods – classical, using cycles, and matrix-vector, using linear algebra operations. The classical method requires calculating the intermediate values necessary to obtain the criterion statistics using two independent cycles, the second cycle being a double one, in which one cycle is nested into the other. The matrix-vector method requires fewer code by performing calculations using linear algebra operations on matrices and vectors. We obtained critical statistical values for the sample size from 8 to 1000 observations with two-dimensional linear interpolation of tabular values. We used an approximation by a beta function of the third kind for a sample of over 1000 elements.Results. An assessment of the computational efficiency of the methods showed that the cyclic approach is about three times higher than the matrix-vector approach in terms of consumed time, which is presumably due to the processing of insignificant elements in triangular matrices when performing component-by-component operations. The correctness of the software implementation of the Epps-Pulley criterion was tested on several examples, which confirmed the compliance of the calculated values of the criterion statistics, as well as the critical values of statistics, with known data. We carried out a criterion statistical evaluation based on the empirical values of the error of the first kind. We obtained the error values correspondence to the specified significance levels. We performed comparative estimates of the Epps-Pulley test with the Anders-Darling and Shapiro-Wilk tests in terms of the criterion empirical power and tabulated the evaluation results. We published the software implementation of the Epps-Pulley test on the MATLAB Central Internet resource and for free use.Conclusion. We developed software implementation of the Epps-Pulley criterion as a new research tool that was previously unavailable in the Matlab modeling environment. We used the time spent on calculations to make a reasonable choice of the calculation algorithm for the criterion statistics. We confirmed correctness of the calculation algorithms by a set of selective checks and statistical estimates that showed the compliance with well-known theoretical provisions.

Design and Analysis of a Campus Service Platform Based on WeChat Mini Program

This paper explores the design and analysis process of a campus service mini program. As known, an increasing number of mini program platforms are emerging in the market, and the unique community of schools, consisting of teachers and students, also requires a dedicated mini program to cater to their needs. This paper covers aspects such as the functional design, page layout, technical implementation, market analysis, and future planning of the mini program. Through our research, we have found that the design and development of a mini program is a complex and meticulous task, requiring thorough consideration of user needs, technical implementation capabilities, and market demands. Utilizing front-end development technologies, the mini program achieved a simple and user-friendly interface, consolidating multiple scattered platforms commonly used by users, enhancing the platform's practicality, and improving user experience. This research article provides a detailed introduction to the design philosophy, functional modules, technical implementation, and market analysis of the mini program. Additionally, the paper outlines future development trends and offers development recommendations, enabling the mini program to better face future challenges.

Chat-ePRO: Development and pilot study of an electronic patient-reported outcomes system based on ChatGPT

ObjectiveChatbots have the potential to improve user compliance in electronic Patient-Reported Outcome (ePRO) system. Compared to rule-based chatbots, Large Language Model (LLM) offers advantages such as simplifying the development process and increasing conversational flexibility. However, there is currently a lack of practical applications of LLMs in ePRO systems. Therefore, this study utilized ChatGPT to develop the Chat-ePRO system and designed a pilot study to explore the feasibility of building an ePRO system based on LLM. Materials and MethodsThis study employed prompt engineering and offline knowledge distillation to design a dialogue algorithm and built the Chat-ePRO system on the WeChat Mini Program platform. In order to compare Chat-ePRO with the form-based ePRO and rule-based chatbot ePRO used in previous studies, we conducted a pilot study applying the three ePRO systems sequentially at the Sir Run Run Shaw Hospital to collect patients’ PRO data. ResultChat-ePRO is capable of correctly generating conversation based on PRO forms (success rate: 95.7 %) and accurately extracting the PRO data instantaneously from conversation (Macro-F1: 0.95). The majority of subjective evaluations from doctors (>70 %) suggest that Chat-ePRO is able to comprehend questions and consistently generate responses. Pilot study shows that Chat-ePRO demonstrates higher response rate (9/10, 90 %) and longer interaction time (10.86 s/turn) compared to the other two methods. ConclusionOur study demonstrated the feasibility of utilizing algorithms such as prompt engineering to drive LLM in completing ePRO data collection tasks, and validated that the Chat-ePRO system can effectively enhance patient compliance.

Enhancing computational thinking in early childhood education through ScratchJr integration

A plethora of programming platforms purports to teach preschool-aged children computational thinking (CT) and coding skills. However, the empirical evidence to support their effectiveness is still in its early stages. A three-week didactic intervention using ScratchJr was conducted to investigate its effectiveness in fostering CT and rudimentary coding skills in a cohort of preschool children (N = 34, aged 4–6 years). While the initial performance mean of the control group (M = 7.07, SD = 2.58) exhibits a statistically significant elevation t (22.64 = 2.23, p = 0.036) vis-à-vis the experimental group (M = 5.35, SD = 1.58), t (22.64) = 2.23, p = 0.0 the terminal performance means of both groups converge closely. However, meticulous data analysis unveils a statistically notable enhancement among preschool participants exposed to the educational intervention involving ScratchJr. Notably, both instructional modalities appear commensurate in nurturing elementary computational tenets, namely modularity and control structures. The experimental cohort outperforms the control group with statistical significance in comprehending potent ideational constructs encompassing representation, algorithms, and hardware/software interplay. Conversely, the control group performs better in grasping the debugging concept than their experimental counterparts. The outcomes lend substantive credence to the efficacy of the distinct programming milieu offered by ScratchJr, underscoring its effectiveness in cultivating CT and coding proficiencies within the preschool demographic.

The Impact of a Skill-Driven Model on Scrum Teams in Software Projects: A Catalyst for Digital Transformation

Human skills are a critical factor in the success or failure of a digital project. Limited studies have been conducted to identify the industry demand for skills of scrum roles (product owner, scrum master, web developer) and levels (entry, associate, mid-senior). The evaluation of skills over time benefits both decision-makers and associated team members, which leads to successful project completions. The aim of this research is to improve decision making concerning the level-specific skills of selected scrum roles for digital projects. The study identifies major and minor skills, patterns, and relationships between levels, and formulates the mathematical equations as the most important inputs to the skill-driven model’s implementation and evaluation. Both qualitative and quantitative research methods were used to analyse 900 surveyed job advertisements published on LinkedIn in Europe. Descriptive analysis was used to analyse quantitative data while the deductive approach was followed with thematic analysis. There are required skill sets for each level of roles, level-specific skills, industry-demanded skills, and formulas related to the initial and individual skill ratings that are investigated. A new mechanism for evaluation is introduced based on “the time spent with skills”. As a result, the proposed model is implemented by feeding research findings into the Mendix programming platform. The skill-driven model is a decision-support solution in software project management to evaluate skills which assist in assigning the right person to the right digital project. Further investigation on different job portals can help to improve the accuracy of industry standards and reduce the lack of progression skills by overcoming limitations identified in this paper.

Design and Development of an Intelligent Connected Access Integrated Training and Assessment Platform

This study addresses the issues of poor interdisciplinary integration and misalignment between experimental content and industry demands in the construction of applied undergraduate laboratory facilities, based on the background of industry-academia collaboration. This paper presents the design and development of an intelligent connected access integrated training and assessment platform, utilizing a full-stack development approach that combines knowledge graph, sensor principles, communication protocol integration, microcontroller programming, networking, connected access, and cloud platform development. The platform adopts a topological hierarchical structure, facilitating layered instruction for teachers and helping students to understand the logical development of Internet of Things products. Furthermore, the platform utilizes equipment commonly used in enterprises to enhance students' technical application, practical, and innovative capabilities. Through teaching practice, students' engineering awareness and practical skills have significantly improved, effectively promoting the development of relevant courses and practical training.

A Critical Appraisal: Elementary School Coding Education Effectiveness with Scratch in Alignment with Cognitive Development, Analyzed through Piagetian Lens

The digitalization has revolutionized the education sector by integrating technology and bringing about significant changes. Computational Thinking (CT), an indispensable skill for the 21st century, has now become an integral part of school curricula in several countries worldwide. Focused on enhancing CT skills, programming education, especially through Scratch, Scratch simplifies programming concepts, making it suitable for elementary school children aged 7 to 11 years. Aligned with Piaget's concrete operational stage, emphasizing organized and rational thinking. Hence, this study aims to delve deeper into how Scratch programming education can meet the cognitive developmental needs of children in this phase. The research methodology used is a literature review, employing data from textbooks, journals, scholarly articles, and literature reviews that contain concepts central to the research focus. The data analysis involves collecting relevant research findings, organizing, and systematically recording information. The results indicate that Scratch not only provides a platform for learning programming but also supports the development of concrete operational cognitive skills taught in Piaget's theory. Through creativity in designing Scratch projects, children can apply and strengthen their understanding of concepts such as seriation, classification, reversibility, conservation, and the elimination of egocentrism. But, it's essential to consider an approach tailored to the developmental characteristics of children when designing programming education at the elementary level. This study is expected to provide concise guidance for educators and policymakers in formulating programming education that optimally fosters cognitive development in elementary school children.

EL Greco Platform: A novel Python programming learning platform that uses a real robot

AbstractThis paper introduces the El Greco Platform, a Python programming platform for distance learning that employs an educational robot. This website allows prospective learners to remotely control Greco, a social humanoid robot designed to be cost‐effective, simple to construct, and appropriate for use in education. El Greco is capable of performing multiple tasks, including combined movements. These Robot capabilities can be programmed using either Python code or the Blockly library, which adds an editor to an application that visualizes coding concepts as interlocking blocks. Programming a robot appears to be a significantly more effective and creative method for students to learn a programming language. This educational tool was designed primarily for use by students and allows anyone to learn Python while controlling a robot for free. El Greco Platform features gamification elements that increase the enjoyment and engagement of the learning experience while reinforcing the concepts taught. The survey results on students aged 13–18 revealed that the El Greco Platform captivated the study participants and positively affected their attitudes toward programming and robotics. In addition, it significantly impacted their comprehension of programming and motivated them to seek additional opportunities to expand their knowledge of robotics and programming.

Research on Private Domain Traffic Operation Link Based on D2C Lead Marketing

This project aims to build an online platform, open up an integrated link integrating brand building, mental planting and effect transformation, obtain user leads through various marketing methods such as content creation and channel delivery, and establish a social customer relationship management system for the third-party automotive industry based on artificial intelligence technology. To carry out the link operation after retention collection, data cleaning, hierarchical screening, AI intelligent customer service, etc., to establish high-quality brand user clues database information. On the basis of exploring the realization of live streaming clues, this project will cooperate with the media operation room to build the mini program platform for users of Zhongqi Media, complete the introduction of the platform for prospective users of online and offline projects of Zhongqi Media, and conduct user operation through the modular construction of the platform. Build a complete private domain operation system of "public domain drainage, content planting, attracting and retaining funds, label classification, private domain precipitation, guided purchase, activation, potential customer tracking, and data duplication".

Exploring Numba and CuPy for GPU-Accelerated Monte Carlo Radiation Transport

This paper examines the performance of two popular GPU programming platforms, Numba and CuPy, for Monte Carlo radiation transport calculations. We conducted tests involving random number generation and one-dimensional Monte Carlo radiation transport in plane-parallel geometry on three GPU cards: NVIDIA Tesla A100, Tesla V100, and GeForce RTX3080. We compared Numba and CuPy to each other and our CUDA C implementation. The results show that CUDA C, as expected, has the fastest performance and highest energy efficiency, while Numba offers comparable performance when data movement is minimal. While CuPy offers ease of implementation, it performs slower for compute-heavy tasks.