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Memristor Neural Networks for Linear and Quadratic programming problems

IEEE TRANSACTIONS ON CYBERNETICS 2022年第3期52卷 1822-1835页

作者： Di Marco, Mauro Forti, Mauro Pancioni, Luca Innocenti, Giacomo Tesi, Alberto Univ Siena Dept Informat Engn & Math I-53100 Siena Italy Univ Florence Dept Informat Engn I-50139 Florence Italy

This article introduces a new class of memristor neural networks (NNs) for solving, in real-time, quadratic programming (QP) and linear programming (LP) problems. The networks, which are called memristor programming NNs (MPNNs), use a set of filamentary-type memristors with sharp memristance transitions for constraint satisfaction and an additional set of memristors with smooth memristance transitions for memorizing the result of a computation. The nonlinear dynamics and global optimization capabilities of MPNNs for QP and LP problems are thoroughly investigated via a recently introduced technique called the flux-charge analysis method. One main feature of MPNNs is that the processing is performed in the fluxcharge domain rather than in the conventional voltage-current domain. This enables exploiting the unconventional features of memristors to obtain advantages over the traditional NNs for QP and LP problems operating in the voltage-current domain. One advantage is that operating in the flux-charge domain allows for reduced power consumption, since in an MPNN, voltages, currents, and, hence, power vanish when the quick analog transient is over. Moreover, an MPNN works in accordance with the fundamental principle of in-memory computing, that is, the nonlinearity of the memristor is used in the dynamic computation, but the same memristor is also used to memorize in a nonvolatile way the result of a computation.

关键词： Global optimization memristor neural networks (NNs) nonsmooth analysis programming problems stability

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An Effective Approach of Evaluating Cognitive Weight and Equivalent Distribution of programming problems 2

An Effective Approach of Evaluating Cognitive Weight and Equ...

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2nd International Conference on Sustainable Technologies for Industry 4.0 (STI)

作者： Bashir, Golam Md Muradul Muhtasim, Muhammad Ahmed, Md Monsur Patuakhali Sci & Technol Univ Fac Comp Sci & Engn Patuakhali Bangladesh

ISBN: (纸本)9781665404891

Equal distribution of programming problems among the students is so significant during the examination within limited times. But how could we determine that how student feels about whether a given program is either easy or difficult? So Complexity measurement according to their brain thinking capability is necessary. In this article, we have improved the approach of complexity measurement procedure that gives us more accurate value of cognitive weight which contract the constraints of existing measures. The idea of cognitive weight of any basic control structure is ethically based on the logical capacity of the human brain. As per our cognitive data gathering from various level of students, we have built up a new software tool using Java Standard Edition and MySQL for equivalent distribution of programming problems dependent on our developed algorithm. The problems is categorized according to three difficulty level (simple, medium, hard) for each level of students. This will help instructor allocate problems while maintaining an equivalent level of problems for students.

关键词： Cognitive Weights Basic Control Structures Weight Measurement Equivalent Distribution programming problems Java SE MySQL Database

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Classification of Strategies for Solving programming problems using AoI Sequence Analysis 19

Classification of Strategies for Solving Programming Problem...

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11th ACM Symposium On Eye Tracking Research and Applications (ETRA)

作者： Obaidellah, Unaizah Raschke, Michael Blascheck, Tanja Univ Malaya Kuala Lumpur Malaysia Blickshift Gmbh Stuttgart Germany INRIA Saclay France

ISBN: (纸本)9781450367097

This eye tracking study examines participants' visual attention when solving algorithmic problems in the form of programming problems. The stimuli consisted of a problem statement, example output, and a set of multiple-choice questions regarding variables, data types, and operations needed to solve the programming problems. We recorded eye movements of students and performed an Area of Interest (AoI) sequence analysis to identify reading strategies in terms of participants' performance and visual effort. Using classical eye tracking metrics and a visual AoI sequence analysis we identified two main groups of participants-effective and ineffective problem solvers. This indicates that diversity of participants' mental schemas leads to a difference in their performance. Therefore, identifying how participants' reading behavior varies at a finer level of granularity warrants further investigation.

关键词： Eye tracking visual analytics reading strategies programming problems

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Cognitive Complexity: A Model for Distributing Equivalent programming problems

Cognitive Complexity: A Model for Distributing Equivalent Pr...

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International Conference on Electrical, Computer and Communication Engineering (ECCE)

作者： Dey, Samrat Kumar Tariq, S. S. M. Islam, Md. Shariful Bashir, Golam Md. Muradul Mil Inst Sci & Technol Dept CSE Dhaka Bangladesh BJIT Ltd Dhaka Bangladesh Dhaka Univ Engn & Technol Dept CSE Dhaka Bangladesh Patuakhali Sci & Technol Univ Dept CSE Patuakhali Bangladesh

ISBN: (纸本)9781509056279

Traditional distribution of programming problems seems to create dissatisfaction among students. To overcome this problem, complexity measurement of programming problems is necessary. Although software is the outcome of human ingenious activity, cognitive informatics plays a significant role in understanding its ultimate characteristics. In this article, we have proposed a software complexity measurement algorithm based on cognitive weight of basic control structure that shrink the limitations of existing measures. Cognitive weight concept of any basic control structure are morally based on the rational capacity of Human Brain. According to cognitive data, we have developed a new software tool using Java Standard Edition and MySQL to measure the cognitive complexity by following our developed algorithm. This software is structured and developed based on the outcome of our research data which is capable of determining the complexity value of several programming languages. This will assist the instructors allocating the problems among the learners by preserving the equivalent level of difficulty. Therefore, the developed complexity measurement tool will ensure the students to get problems with identical difficulty level for assessment.

关键词： cognitive weight complexity measurement equivalent distribution programming problems java SE MySQL database problems bank

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Some programming problems for teaching foundations of group theory

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INTERNATIONAL JOURNAL OF MATHEMATICAL EDUCATION IN SCIENCE AND TECHNOLOGY 2014年第3期45卷 438-445页

作者： Shilin, I. A. Sholokhov Moscow State Univ Humanities Dept Math & Phys Moscow Russia Moscow Inst Aviat Technol Dept Math Simulat Moscow Russia

This paper contains some programming problems which can be suggested for students starting to learn group theory. These problems are related to important notations such as subgroup, coset, normal divisor, symmetric group, normalizer, centralizer, homomorphism and automorphism. Carefully selected problems provide a successful understanding of the basic themes of finite group theory.

关键词： finite group theory programming programming problems

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Small-sample size problems solving based on incremental learning: an adaptive Bayesian quadrature approach

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APPLIED INTELLIGENCE 2023年第12期53卷 15174-15187页

作者： Feng, Yiding Feng, Xiang Yu, Huiqun East China Univ Sci & Technol Dept Comp Sci & Engn Shanghai 200237 Peoples R China Shanghai Engn Res Ctr Smart Energy Shanghai 200237 Peoples R China

When solving programming problems with objectives, we are often faced with the challenge of insufficient samples. And when new samples are generated, re-modeling based on historical and incremental samples is costly. Many Bayesian based approaches have been proposed to update the original models using newly coming samples which are called incremental learning. In this paper, we derive a calculation method of information value based on Bayesian quadrature technology, and use multi-start Adaptive Momentum (ADAM) stochastic gradient algorithm to design independent adaptive learning rates by computing the first-order moment and the second-order moment of the gradient then we propose a small-sample size problems solving based on incremental learning called Adaptive Bayesian Quadrature Approach (ABQA) We use a numerical validation experiment to verify the effectiveness of our approach, and then use two programming problems, shared bike system and newsvendor problem, to verify the effectiveness of our approach on incremental learning and small-samples size problems. In all these experiments, ABQA outperforms the benchmarks and state-of-the-art Bayesian algorithms. Performance and speed are improved by 2.8% and 8.6%, respectively.

关键词： Incremental learning Bayesian quadrature Small-sample size problems Multi-startADAM programming problems

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Generative AI-Driven Approach to Converting Numerical Code into Mathematical Functions 2

Generative AI-Driven Approach to Converting Numerical Code i...

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2nd International Conference on Automation, Computing and Renewable Systems, ICACRS 2023

作者： Adwaith Krishna, E.R. Sha, Akhbar Anvesh, Kalwa Reddy, Nancharla Abhinay Raj, Bhupathi Shwejan Nisha, K.S. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9798350340235

In the era of Artificial Intelligence (AI), the role of Generative AI models has witnessed a paradigm shift in addressing programming challenges. This research delves into the evolving landscape of Generative AI-driven code generation for programming problems, with a focus on the convergence behavior, algorithmic efficiency, learning dynamics, and code-length-performance dynamics of AI models, exemplified by ChatGPT and BARD. Through meticulous experimentation and analysis, this study elucidates key findings that illuminate the strengths and nuances of these models in code generation contexts. ChatGPT demonstrates rapid initial convergence, making it advantageous in time-sensitive scenarios, while BARD exhibits potential for precision-critical tasks. Algorithmic efficiency comparisons reveal subtle differences, emphasizing the need for further investigation into runtime influences. Learning curve analysis underscores the significance of early iterations in training, while code length-performance dynamics present intriguing correlations that warrant in-depth exploration. These insights provide a foundation for informed model selection and training strategies, while highlighting the ethical considerations and future avenues in AI-driven code generation. © 2023 IEEE.

关键词： BARD ChatGPT Code Generation Convergence Behavior Generative AI programming problems

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Mixing Cognitive and Affective Approaches in Teaching Introductory programming 21

Mixing Cognitive and Affective Approaches in Teaching Introd...

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26th Conference on Innovation and Technology in Computer Science Education

作者： Borovina Josko, Joao Marcelo Fed Univ ABC Ctr Comp Mathmet & Cognit Santo Andre SP Brazil

ISBN: (纸本)9781450383974

Gaining computer programming depends on both intrinsic and extrinsic factors of the students. Many studies have provided various viewpoints to engage students in introductory programming learning. Still, there is a lack of works that interweave different teaching methods from cognitive and affective dimensions or considered the latter in face-to-face classes consistently. This poster introduces our approach that combines pair programming, formative feedback, aspects of the affective dimension, and creative programming problems. We outline how the methods above are connected, preliminary results, and future works intentions.

关键词： Pair programming Formative Feedback Affective Dimension Non-Computer Science Students programming problems Supportive Learning Environment

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Increasing student motivation in computer programming with gamification 11

Increasing student motivation in computer programming with g...

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IEEE Global Engineering Education Conference (IEEE EDUCON)

作者： Figueiredo, Jose Jose Garcia-Penalvo, Francisco Polytech Guarda Res Unit Inland Dev Guarda Portugal Univ Salamanca Dept Comp Sci Res Inst Educ Sci GRIAL Res Grp Salamanca Spain

ISBN: (纸本)9781728109305

Games have important motivational power. They take advantage of a set of tools to encourage people to engage with them just for the joy of playing and the possibility to win. While gamification is gaining ground in a lot of areas in our society, its application in education is still an emerging trend. In recent years, gamification has attracted the attention of researchers from different areas such as teaching and learning computer programming. Ever since the first programming languages emerged, the problems inherent to programming teaching and learning have been studied and investigated. The theme is very serious, not only for the important concepts underlying computer science courses but also for reducing the lack of motivation, failure, and abandonment that result from student frustration. In most of these studies and research one factor prevails, lack of student motivation or how to motivate students to learn programming. One way to combat this problem is to use gamification. Using game design elements in non-game contexts is one of the good ways to motivate and encourage students to learn programming. To assess how gamification impacted the learning experience, we compared data from one gamified and non-gamified year. In general, the results show significant improvements in terms of attendance to class, participation, and proactivity. They also suggest that our approach can reduce the high rate of failure grade among students. In conclusion, this case study, we show how the use of concepts related to gamification can improve motivation, passion, beauty, joy, awe, e naturally the succeed in programming.

关键词： Gamification learning programming teaching programming programming problems

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Optimization Approach for Bounds Involving Generalized Normalized δ-Casorati Curvatures 4th

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4th International Conference on Harmony Search, Soft Computing and Applications (ICHSA)

作者： Bansal, Pooja Shahid, Mohammad Hasan Jamia Millia Islamia Dept Math New Delhi 110025 India

ISBN: (纸本)9789811307614;9789811307607

By using T. Oprea's optimization method on a real hypersurfaces of complex quadric Q(m) with QSMC, we prove extremal inequalities concerning normalized scalar curvature and generalized normalized delta-Casorati curvatures. Moreover, we show the equilibrium cases at all points which signalize the invariantly quasi-umbilical real hypersurfaces. Finally, applications of this technique as a constrained programming problem.

关键词： Optimization methods programming problems Real hypersurface Complex quadric Scalar curvature Generalized normalized delta-Casorati curvature

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