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programming in school technology education: the shaping of a new subject content

INTERNATIONAL JOURNAL OF TECHNOLOGY AND DESIGN EDUCATION 2023年第4期33卷 1449-1470页

作者： Vinnervik, Peter Umea Univ Dept Sci & Math Educ S-90187 Umea Sweden

In Sweden, as in many other countries, programming has been added to the curriculum in recent years. This paper explores how and under what conditions programming is transformed into teaching in technology education. Teachers in grade 7-9 were interviewed about what and how they teach about programming in the context of technology education, and what influenced the choices they made. Data was analysed using content analysis. The results suggest that teachers mainly see programming as a medium to explore and understand technological systems and construction work. The results further implies that teachers are uncertain of what programming means in terms of practices and concepts, and how programming knowledge can be assessed. The process of transformation presents teachers with several challenges, related to their own knowledge of programming, quality of teaching materials, and knowing pupils' prior knowledge about programming. In addition, the results indicate that technology teachers work in isolation. In consequence, the intended interdisciplinary collaboration between technology and mathematics teachers on programming is largely absent.

关键词： programming Curriculum implementation Compulsory school Technology education Teacher challenges

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programming Weights to Analog In-Memory Computing Cores by Direct Minimization of the Matrix-Vector Multiplication Error

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IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS 2023年第4期13卷 1052-1061页

作者： Buechel, Julian Vasilopoulos, Athanasios Kersting, Benedikt Lammie, Corey Brew, Kevin Philip, Timothy Saulnier, Nicole Narayanan, Vijay Le Gallo, Manuel Sebastian, Abu IBM Res Zurich CH-8803 Ruschlikon Switzerland IBM Res Albany Albany NY 12203 USA IBM Res Yorktwon Hts Yorktwon Hts NY 10598 USA

Accurate programming of non-volatile memory (NVM) devices in analog in-memory computing (AIMC) cores is critical to achieve high matrix-vector multiplication (MVM) accuracy during deep learning inference workloads. In this paper, we propose a novel programming approach that directly minimizes the MVM error by performing stochastic gradient descent optimization with synthetic random input data. The MVM error is significantly reduced compared to the conventional unit-cell by unit-cell iterative programming. We demonstrate that the optimal hyperparameters in our method are agnostic to the weights being programmed, enabling large-scale deployment across multiple AIMC cores without further fine tuning. It also eliminates the need for high-resolution analog to digital converters (ADCs) to decipher the small unit-cell conductance during programming. We experimentally validate this approach by demonstrating an inference accuracy increase of 1.26% on ResNet-9. The experiments were performed using phase change memory (PCM)-based AIMC cores fabricated in 14nm CMOS technology.

关键词： programming Economic indicators System-on-chip Performance evaluation Hardware Phase change materials Voltage Analog in-memory computing device programming neural network inference

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MLMD:a programming-free AI platform to predict and design materials

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npj Computational Materials 2024年第1期10卷 2636-2647页

作者： Jiaxuan Ma Bin Cao Shuya Dong Yuan Tian Menghuan Wang Jie Xiong Sheng Sun Materials Genome Institute Shanghai UniversityShanghai 200444China Zhejiang Laboratory Hangzhou 311100China Guangzhou Municipal Key Laboratory of Materials Informatics Advanced Materials ThrustHong Kong University of Science and Technology(Guangzhou)Guangzhou 510000China Shanghai Frontier Science Center of Mechanoinformatics Shanghai UniversityShanghai 200444China

Accelerating the discovery of advanced materials is crucial for modern industries,aerospace,biomedicine,and ***,only a small fraction of materials are currently under experimental investigation within the vast chemical *** scientists are plagued by timeconsuming and labor-intensive experiments due to lacking efficient material discovery *** intelligence(AI)has emerged as a promising instrument to bridge this *** numerous AI toolkits or platforms for material science have been developed,they suffer from many *** include primarily focusing on material property prediction and being unfriendly to material scientists lacking programming experience,especially performing poorly with limited ***,we developed MLMD,an AI platformfor materials *** is capable of effectively discovering novel materials with high-potential advanced properties end-to-end,utilizing model inference,surrogate optimization,and even working in situations of data scarcity based on active ***,it integrates data analysis,descriptor refactoring,hyper-parameters auto-optimizing,and properties *** also provides a web-based friendly interface without need programming and can be used anywhere,*** is dedicated to the integration of material experiment/computation and design,and accelerate the new material discovery with desired one or multiple *** demonstrates the strong power to direct experiments on various materials(perovskites,steel,high-entropy alloy,etc).MLMD will be an essential tool for materials scientists and facilitate the advancement of materials informatics.

关键词： alloy programming utilizing

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programming with ChatGPT: How far can we go?

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MACHINE LEARNING WITH APPLICATIONS 2024年 15卷

作者： Bucaioni, Alessio Ekedahl, Hampus Helander, Vilma Nguyen, Phuong T. Malardalen Univ Vasteras Sweden Univ Laquila Dept Informat Engn Comp Sci & Math Laquila Italy

Artificial intelligence (AI) has made remarkable strides, giving rise to the development of large language models such as ChatGPT. The chatbot has garnered significant attention from academia, industry, and the general public, marking the beginning of a new era in AI applications. This work explores how well ChatGPT can write source code. To this end, we performed a series of experiments to assess the extent to which ChatGPT is capable of solving general programming problems. Our objective is to assess ChatGPT's capabilities in two different programming languages, namely C++ and Java, by providing it with a set of programming problem, encompassing various types and difficulty levels. We focus on evaluating ChatGPT's performance in terms of code correctness, run-time efficiency, and memory usage. The experimental results show that, while ChatGPT is good at solving easy and medium programming problems written in C++ and Java, it encounters some difficulties with more complicated tasks in the two languages. Compared to code written by humans, the one generated by ChatGPT is of lower quality, with respect to runtime and memory usage.

关键词： ChatGPT Large language models programming

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programming Strategy Optimization of RRAM Fabricated by 28 nm Standard CMOS Process

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IEEE TRANSACTIONS ON ELECTRON DEVICES 2023年第3期70卷 1025-1028页

作者： Sun, Yue Wang, Xiaohu Wang, Junyi Cheng, Shenghua Liu, Yongbo Shen, Tingying Li, Xinyi Gao, Bin Qian, He Dalian Univ Technol Sch Mech Engn Dalian 116024 Peoples R China Xiamen Ind Technol Res Inst Xiamen 361000 Fujian Peoples R China Tsinghua Univ Sch Integrated Circuits Beijing 100084 Peoples R China

The switching characteristics of HfOx-based resistive switching random access memory (RRAM) fabricated on front-end of 28 nm standard CMOS process are investigated. The integration of RRAM in the front-end of the CMOS process would minimize the influence of parasitic parameters caused by interconnection line and interlayer oxide on the one transistor one RRAM (1T1R) cells. By adopting pulse program-verify measurement for cycling test, we observe two nonideal phenomena in the commercialized RRAM devices for the first time: 1) low resistance state (LRS) current periodically decays exponentially accompanied by incremental SET pulse number and then increases abruptly when the cycle reaches a certain level and 2) high resistance state (HRS) current fluctuated dramatically during RESET operation. The current fluctuation is mainly due to the generation of new oxygen vacancies (Vos) near the bottom electrode and gap region by electrons trapping/detrapping. By adopting efficient pulse amplitude modulation, the optimized programming strategy has greatly reduced the switching instability and improved the endurance of the devices. Mechanisms of the instability and the optimization strategy are explained by a modified trap-assisted tunneling (TAT) model based on the generation and redistribution of Vos during cycling operations.

关键词： Fluctuations programming Switches Resistance Tunneling Transistors Switching circuits Current fluctuation HfOx resistive switching random access memory (RRAM) switching characteristic trap-assisted tunneling (TAT)

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A multi-objective mathematical programming model for a novel capability-based university course timetabling problem

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GA...

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JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY 2025年第1期40卷 365-379页

作者： Subula, Kemal Dokuz Eylul Univ Fac Engn Dept Ind Engn TR-35397 Izmir Turkiye

he university course timetabling is a tactical level problem that almost all academic departments encounterbefore each semester. Nowadays, in order to meet some standards, set by educational accreditation agencieswithin the scope of higher education quality assurance, it is required to generate efficient course timetables,which ensure optimal distribution of basic capabilities. Actually, these capabilities should be first specifiedbased on the learning outcomes defined by lecturers for each course that are also associated with programoutcomes and are aimed to be acquired by all of the students. Based on this motivation, a multi-objective mixed-integer non-linear programming model is developed for a novel capability-based course timetabling problem. Its validity and practicality are tested on a real-life application in an Industrial EngineeringDepartment. When the balanced solutions provided by compromise and fuzzy goal programming techniqueswere compared with the existing schedules of the previous years, it was revealed that significantimprovements could be achieved in terms of several conflicting objectives (i.e., optimal capabilitydistribution over the timetable, acquisition of maximum number/variety of different capabilities by thestudents, meeting expectations of lecturers by minimizing total temporal difference between the periodshis/her courses are assigned, total penalty cost related to soft constraints).

关键词： University course timetabling problem mixed integer non-linear programming multi-objective optimization capability-based approach compromise programming

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Weighted Sum-Rate Maximization With Transceiver and Passive Beamforming Design for IRS-Aided MIMO-BC Communications via Matrix Fractional programming

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IEEE TRANSACTIONS ON COMMUNICATIONS 2025年第2期73卷 1383-1398页

作者： Qiu, Jing Yu, Jiguo Dong, Anming Yu, Kan Chen, Honglong Qufu Normal Univ Sch Math Sci Qufu 273165 Peoples R China Univ Elect Sci & Technol China Sch Comp Sci & Engn Chengdu 611731 Peoples R China Qilu Univ Technol Big Data Inst Jinan 250353 Peoples R China Qilu Univ Technol Key Lab Comp Power Network & Informat Secur Shandong Comp Sci Ctr Shandong Acad SciMinist Educ Jinan 250353 Shandong Peoples R China Shandong Fundamental Res Ctr Comp Sci Shandong Prov Key Lab Comp Networks Jinan 250353 Shandong Peoples R China Beijing Univ Posts & Telecommun Key Lab Universal Wireless Commun Minist Educ Beijing 100876 Peoples R China China Univ Petr Coll Control Sci & Engn Qingdao 266580 Peoples R China

This paper investigates the joint active transceiver and passive beamforming design to maximize the weighted sum-rate (WSR) of an IRS-aided multi-streams multiuser multiple-input multiple-output broadcast channel (MIMO-BC) downlink transmission system. Due to the coupling of the transceiver parameters, the considered WSR optimization problem is highly non-convex and thus challenging to solve. Different from the normally used methods, such as the weighted minimum mean-square error (WMMSE), we rely on the matrix fractional programming (MFP) theory to derive an effective algorithm to the WSR problem. Specifically, we reformulate the original problem into a tractable one by exploiting the special structure of the objective function, i.e., a MFP which involves a matrix ratio inside a logarithm in the objective function. An alternating optimization (AO) framework is then devised to decompose the reformulated problem into four subproblems, which optimize the introduced auxiliary variable, the transmit beamforming matrix, the receive matrix, and the reflecting beamforming matrix by fixing other variables respectively. Through the matrix quadratic transform, we reformulate the MFP problem as a convex one, and thus obtain the optimal transmit beamforming matrix. By leveraging the optimality conditions for unconstrained optimization problems, the optimal receive beamforming matrix and the introduced auxiliary variable are derived in closed form. For solving the passive beamforming subproblem, we propose an iterative algorithm based on successive convex approximation (SCA). Since the computational complexity of SCA is relatively high, we propose a computationally efficient method based on manifold optimization (MO) to optimize the passive beamforming matrix. Finally, we also consider the robust beamforming design when the system suffers from imperfect CSI. Simulation results demonstrate the effectiveness of the proposed methods.

关键词： Optimization Array signal processing Transceivers MIMO communication Transforms programming Matrix decomposition Matrix Fractional programming (MFP) alternating optimization (AO) intelligent reflecting surface (IRS) manifold optimization (MO) beamforming

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programming Errors and Academic Performance in an Introductory Data Structures Course: A Per Gender Analysis 26th

Programming Errors and Academic Performance in an Introducto...

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26th International Conference on Interactive Collaborative Learning (ICL) - Towards a Hybrid, Flexible and Socially Engaged Higher Education / 52nd IGIP International Conference on Engineering Pedagogy

作者： Dagklis, Evangelos Satratzemi, Maya Koloniari, Georgia Karakasidis, Alexandros Univ Macedonia Egnatia 56 Thessaloniki 54636 Greece

ISBN: (纸本)9783031533815;9783031533822

Computer Science studies is among the primary fields usually dominated by male audiences. But can the empirical data explain this preference or are other types of factors responsible for its perpetuation? This study aims to contribute by examining the student performance in a per gender manner from an introductory Data Structures course taught in the second semester of a university's undergraduate program. The years whose data was used are 2021 and 2022. Visualization and statistical analysis tests are applied on the programming errors and grades per student as an attempt to monitor said performance per gender throughout the semester and determine if any differences arise. Association rule mining is also used in order to uncover the role of the students' different attributes in shaping their course pass status. The findings suggest that the student's gender does not considerably affect their performance, while the two genders' results rarely were statistically different. Moreover, in all the cases where differences emerge, women are the gender with the higher academic performance.

关键词： Gender Gap Data Structures programming Learning Analytics

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Multiform Genetic programming Framework for Symbolic Regression Problems

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IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 2025年第2期29卷 429-443页

作者： Zhong, Jinghui Dong, Junlan Liu, Wei-Li Feng, Liang Zhang, Jun South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Peoples R China Guangdong Polytech Normal Univ Sch Comp Sci Guangzhou 510006 Peoples R China Chongqing Univ Coll Comp Sci Chongqing 400044 Peoples R China Nankai Univ Coll Artificial Intelligence Tianjin 300071 Peoples R China Hanyang Univ ERICA Seoul 15588 South Korea

Genetic programming (GP) is a widely recognized and powerful approach for symbolic regression (SR) problems. However, existing GP methods rely on a single form to solve the problem, which limits their search diversity and increases the likelihood of getting stuck in local optima, especially in complex scenarios. In this article, we propose a general multiform GP (MFGP) framework to improve the performance of GP on complicated SR problems. As far as we know, this articel is the first attempt to integrate the multiform optimization paradigm with GP to accelerate the search performance. The key idea of the proposed framework is to construct multiple forms to solve the same problem cooperatively at the same time. During the evolution process, knowledge gained from different forms is shared among the solvers to improve the search diversity and efficiency. A knowledge transfer mechanism is specifically designed to facilitate knowledge transfer among GP solvers with different modeling forms. In addition, an adaptive resource control mechanism is designed to reallocate computing resources according to the problem solving efficiency of different solvers to further improve search efficiency. To demonstrate the effectiveness of the proposed framework, a multiform gene expression programming algorithm is designed and tested on 20 problems, including physical datasets, synthetic datasets, and real-world datasets. The experimental results have demonstrated the effectiveness of the proposed framework.

关键词： Optimization Search problems Multitasking Adaptation models Semantics programming Mathematical models Transfer learning Resource management Knowledge transfer Genetic programming (GP) multiform optimization multitasking optimization transfer learning (TL) symbolic regression (SR)

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Operational Coordination Optimization of Electricity and Natural Gas Networks Based on Sequential Symmetrical Second-Order Cone programming

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JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY 2025年第2期13卷 488-499页

作者： Min, Liang Lou, Chengwei Yang, Jin Yu, James Yu, Zhibin Power Grid Dispatching & Control Branch Co NARI Te Nanjing Peoples R China China Agr Univ Coll Informat & Elect Engn Beijing Peoples R China Univ Glasgow Sch Engn Glasgow G12 8QQ Scotland Scottish Power Energy Network Glasgow G2 5AD Scotland Univ Liverpool Dept Mech & Aerosp Engn Liverpool England

The variable and unpredictable nature of renewable energy generation (REG) presents challenges to its large-scale integration and the efficient and economic operation of the electricity network, particularly at the distribution level. In this paper, an operational coordination optimization method is proposed for the electricity and natural gas networks, aiming to overcome the identified negative impacts. The method involves the implementation of bi-directional energy flows through power-to-gas units and gas-fired power plants. A detailed model of the three-phase power distribution system up to each phase is employed to improve the representation of multi-energy systems to consider real-world end-user consumption. This method allows for the full consideration of unbalanced operational scenarios. Meanwhile, the natural gas network is modelled and analyzed with steady-state gas flows and the dynamics of the line pack in pipelines. The sequential symmetrical second-order cone programming (SS-SOCP) method is employed to facilitate the simultaneous analysis of three-phase imbalance and line pack while accelerating the solution process. The efficacy of the operational coordination optimization method is demonstrated in case studies comprising a modified IEEE 123-node power distribution system with a 20-node natural gas network. The studies show that the operational coordination optimization method can simultaneously minimize the total operational cost, the curtailment of installed REG, the voltage imbalance of three-phase power system, and the overall carbon emissions.

关键词： Natural gas Power systems Pipelines Electricity Optimization Mathematical models Load flow programming Numerical models Power system dynamics Operational coordination multi-energy system power-to-gas electricity network natural gas network second-order cone programming

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