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关键词： Computational neuroscience   Development of the nervous system   Computer science  

摘要： Neuroscience has long inspired AI, however the neuroevolutionary search that produces sophisticated behaviors has not been systematized. This paper defines neurodevelopmental ML as a discovery process for structures that promote complex computations. Machine learning (ML) models have long overlooked innateness: how strong pressures for survival lead to the encoding of complex behaviors in the nascent wiring of a brain. Here, we derive a neurodevelopmental encoding of artificial neural networks that considers the weight matrix of a neural network to be emergent from well-studied rules of neuronal compatibility. Rather than updating the network's weights directly, we improve task fitness by updating the neurons' wiring rules, thereby mirroring evolutionary selection on brain development. We find that our model (1) provides sufficient representational power for high accuracy on ML benchmarks while also compressing parameter count, and (2) can act as a regularizer, selecting simple circuits that provide stable and adaptive performance on metalearning tasks. In summary, by introducing neurodevelopmental considerations into ML frameworks, we not only model the emergence of innate behaviors, but also define a discovery process for structures that promote complex computations.

关键词： Computer science   Information storage   Surface patterning   Surfaces   interfaces and thin films  

摘要： A physical unclonable function (PUF) is a foundation of anti-counterfeiting processes due to its inherent uniqueness. However, the self-limitation of conventional graphical/spectral PUFs in materials often makes it difficult to have both high code flexibility and high environmental stability in practice. In this study, we propose a universal, fractal-guided film annealing strategy to realize the random Au network-based PUFs that can be designed on demand in complexity, enabling the tags' intrinsic uniqueness and stability. A dynamic deep learning-based authentication system with an expandable database is built to identify and trace the PUFs, achieving an efficient and reliable authentication with 0% "false positives". Based on the roughening-enabled plasmonic network platform, Raman-based chemical encoding is conceptionally demonstrated, showing the potential for improvements in security. The configurable tags in mass production can serve as competitive PUF carriers for high-level anti-counterfeiting and data encryption. In order to be used on a large scale, unclonable tags for anti-counterfeiting should allow mass production at low cost, as well as fast and easy authentication. Here, the authors show how to use one-step annealing of gold films to quickly realize robust tags with high capacity, allowing fast deep-learning based authentication via smartphone readout.

摘要： We have analyzed all preprints on ChatGPT (N=501) and selected the most influential preprints (according to Altmetric) about ChatGPT across scientific disciplines to provide the most discussed research results about ChatGPT. We prompted ChatGPT to create a structured review article based on them. The results are surprisingly promising, suggesting that the future of creating review articles can lie in ChatGPT. Copyright © 2023, The Authors. All rights reserved.

关键词： Engineering education  

摘要： ChatGPT has become the most popular regenerative AI application, used for obtaining responses for queries in different domains. Some responses of ChatGPT reported in the internet are accurate, others are funny, and some are fictitious. This article focuses on the application of ChatGPT for academic instructional purposes in the field of Computer engineering and related majors. The capability of ChatGPT for instructional purposes is evaluated by providing responses to different questions pertaining to these engineering streams. This article explores different opportunities with use cases, ChatGPT can provide in augmenting the learning experience. It also provides scenarios of limitations and modifying the evaluation process to prevent the use of ChatGPT for unethical means of learning. © 2023, CC BY.

关键词： Data structures  

摘要： The application of Artificial intelligence for teaching and learning in the academic sphere is a trending subject of interest in the computing education. ChatGPT, as an AI-based tool, provides various advantages, such as heightened student involvement, cooperation, accessibility and availability. This paper addresses the prospects and obstacles associated with utilizing ChatGPT as a tool for learning and assessment in undergraduate Computer Science curriculum in particular to teaching and learning fundamental programming courses. Students having completed the course work for a Data Structures and Algorithms (a sophomore level course) participated in this study. Two groups of students were given programming challenges to solve within a short period of time. The control group (group A) had access to text books and notes of programming courses, however no Internet access was provided. Group B students were given access to ChatGPT and were encouraged to use it to help solve the programming challenges. The challenge was conducted in a computer lab environment using Programming Contest Control (PC2) environment which is widely used in ACM International Collegiate Programming Contest (ICPC). Each team of students address the problem by writing executable code that satisfies certain number of test cases. Student teams were scored based on their performance in terms of number of successful passed testcases. Results show that students using ChatGPT had an advantage in terms of earned scores, however there were inconsistencies and inaccuracies in the submitted code consequently affecting the overall performance. After a thorough analysis, the paper's findings indicate that incorporating AI in higher education brings about various opportunities and challenges. Nonetheless, universities can efficiently manage these apprehensions by adopting a proactive and ethical stance towards the implementation of such tools. Copyright © 2023, The Authors. All rights reserved.

关键词： Computer science   Information theory and computation  

摘要： Automatic extraction of consistent governing laws from data is a challenging problem. The authors propose a method that takes as input experimental data and background theory and combines symbolic regression with logical reasoning to obtain scientifically meaningful symbolic formulas. Scientists aim to discover meaningful formulae that accurately describe experimental data. Mathematical models of natural phenomena can be manually created from domain knowledge and fitted to data, or, in contrast, created automatically from large datasets with machine-learning algorithms. The problem of incorporating prior knowledge expressed as constraints on the functional form of a learned model has been studied before, while finding models that are consistent with prior knowledge expressed via general logical axioms is an open problem. We develop a method to enable principled derivations of models of natural phenomena from axiomatic knowledge and experimental data by combining logical reasoning with symbolic regression. We demonstrate these concepts for Kepler's third law of planetary motion, Einstein's relativistic time-dilation law, and Langmuir's theory of adsorption. We show we can discover governing laws from few data points when logical reasoning is used to distinguish between candidate formulae having similar error on the data.

摘要： No abstract available.

关键词： Computer science   Quantum chemistry   Quantum simulation  

摘要： Quantum computing is moving beyond its early stage and seeking for commercial applications in chemical and biomedical sciences. In the current noisy intermediate-scale quantum computing era, the quantum resource is too scarce to support these explorations. Therefore, it is valuable to emulate quantum computing on classical computers for developing quantum algorithms and validating quantum hardware. However, existing simulators mostly suffer from the memory bottleneck so developing the approaches for large-scale quantum chemistry calculations remains challenging. Here we demonstrate a high-performance and massively parallel variational quantum eigensolver (VQE) simulator based on matrix product states, combined with embedding theory for solving large-scale quantum computing emulation for quantum chemistry on HPC platforms. We apply this method to study the torsional barrier of ethane and the quantification of the protein-ligand interactions. Our largest simulation reaches 1000 qubits, and a performance of 216.9 PFLOP/s is achieved on a new Sunway supercomputer, which sets the state-of-the-art for quantum computing emulation for quantum chemistry.

关键词： Statistical tests  

摘要： This paper presents general equations of environmental issues, environmental quality and environmental destruction. The paper employed the concepts of the Ideal Gas equation, Malthus model, IPAT model and population dynamics to relate human population and resource depletion in order to estimate environmental issues over time. This resulted in the generation of three equations;equations for estimating environmental issues, environmental quality and environmental destruction. The dataset on global population growth and resource records was obtained from World Bank and Food and Agricultural Organisation Indicators to test and validate the equations. The findings of the study demonstrated that the models are ecologically efficient and sound. However, the only limitation of the models is that they are resource, population and time-dependent. © 2023, The Authors. All rights reserved.

关键词： Teacher professional development   computer science online   teacher knowledge and skills   teacher recommendations  

摘要： Based on a current Research to Practice Partnership (RPP) between a southeastern public university and a state virtual public school in the United States, ten high school teachers from a virtual school who teach Computer Science (CS) online participated in a summer workshop to collaborate through a participatory action research project regarding design, facilitation, and evaluation strategies to be included in effective professional development. The questions were posed through an online collaborative Jamboard during the summer workshop. The teacher posts were qualitatively analyzed to identify common themes. Recommendations for professional development on design included CS content, how to teach CS, and CS tools and activities. For facilitation, they recommended resources for supplemental instruction and feedback tools for providing feedback in various modalities and a tool repository. For assessment, they recommended content knowledge assessments, including lab assignments, single and pair programming, and coding assessments. Overall recommendations for a professional development course to teach CS online were also offered.