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摘要： This study presents an automated bibliometric analysis of 6569 research papers published in thirteen Brazilian Computer Science Society (SBC) conferences from 1999 to 2021. Our primary goal was to gather data to understand the gender representation in publications in the field of Computer Science. We applied a systematic assignment of gender to 23.573 listed papers authorships, finding that the gender gap for women is significant, with female authors being under-represented in all years of the study. © 2022, CC BY.

关键词： Students  

摘要： Doctoral programs often have high rates of depression, anxiety, isolation, and imposter phenomenon. Consequently, graduating students may feel inadequately prepared for research-focused careers, contributing to an attrition of talent. Prior work identifies an important contributing factor to maladjustment: even with prior exposure to research, entering Ph.D. students often have problematically idealized views of science. These preconceptions can become obstacles for students in their own professional growth. Unfortunately, existing curricular and extracurricular programming in many doctoral programs fail to include mechanisms to systematically address students’ misconceptions of their profession. In this work, we describe a new initiative at our institution that aims to address Ph.D. mental health via a mandatory seminar for entering doctoral students. The seminar is designed to build professional resilience in students by (1) increasing self-regulatory competence, and (2) teaching students to proactively examine academic cultural values and to participate in shaping them. Our evaluation indicates that students improved in both areas after completing the seminar. Copyright © 2022, The Authors. All rights reserved.

关键词： Curricula  

摘要： We present a historical overview of how computer science (CS) was introduced in schools in Israel. We analyze the importance of the inclusion of CS in school curricula, for the individual development of pupils’ capabilities in all facets, and for Israel’s society and economy. We stress the need to expose all pupils to CS in a seamless learning gamified approach, in a spiral deepening of the two essential complementing aspects of CS—algorithms and programming. We start with perceptible physical moving robots that demonstrate an unbiased reaction of algorithms and programs, and gradually train for developing capabilities to abstract data structures, algorithms, and programs. We detail the journey of the introduction of computer science to the Israel Education system. The CS Curricula are described starting with elementary school, into middle school and then high school. Implementation issues are also briefly discussed. Finally, we discuss our vision for future developments in Israel’s CS education. © 2022 Association for Computing Machinery.

关键词： Quantum information   Computer science  

摘要： Modern quantum machine learning (QML) methods involve variationally optimizing a parameterized quantum circuit on a training data set, and subsequently making predictions on a testing data set (i.e., generalizing). In this work, we provide a comprehensive study of generalization performance in QML after training on a limited number N of training data points. We show that the generalization error of a quantum machine learning model with T trainable gates scales at worst as root T/N. When only K << T gates have undergone substantial change in the optimization process, we prove that the generalization error improves to root K/N. Our results imply that the compiling of unitaries into a polynomial number of native gates, a crucial application for the quantum computing industry that typically uses exponential-size training data, can be sped up significantly. We also show that classification of quantum states across a phase transition with a quantum convolutional neural network requires only a very small training data set. Other potential applications include learning quantum error correcting codes or quantum dynamical simulation. Our work injects new hope into the field of QML, as good generalization is guaranteed from few training data.

关键词： Bioinformatics   Computer science   Applied computing in physical science   Applied computing in medical science  

摘要： One of the top priorities in any laboratory is archiving experimental data in the most secure, efficient, and errorless way. It is especially important to those in chemical and biological research, for it is more likely to damage experiment records. In addition, the transmission of experiment results from paper to electronic devices is time-consuming and redundant, Therefore, we introduce an open-source no-code electronic laboratory notebook, Elegancy, a cloudbased/standalone web service distributed as a Docker image. Elegancy fits all laboratories but is specially equipped with several features benefitting biochemical laboratories. It can be accessed via various web browsers, allowing researchers to upload photos or audio recordings directly from their mobile devices. Elegancy also contains a meeting arrangement module, audit/revision control, and laboratory supply management system. We believe Elegancy could help the scientific research community gather evidence, share information, reorganize knowledge, and digitize laboratory works with greater ease and security.

关键词： Computer science   Ecology   Evolutionary biology  

摘要： Openly available community science digital vouchers provide a wealth of data to study phenotypic change across space and time. However, extracting phenotypic data from these resources requires significant human effort. Here, we demonstrate a workflow and computer vision model for automatically categorizing species color pattern from community science images. Our work is focused on documenting the striped/unstriped color polymorphism in the Eastern Red-backed Salamander (Plethodon cinereus). We used an ensemble convolutional neural network model to analyze this polymorphism in 20,318 iNaturalist images. Our model was highly accurate (similar to 98%) despite image heterogeneity. We used the resulting annotations to document extensive niche overlap between morphs, but wider niche breadth for striped morphs at the range-wide scale. Our work showcases key design principles for using machine learning with heterogeneous community science image data to address questions at an unprecedented scale.

关键词： Computer science   Electrical and electronic engineering   Electronic devices  

摘要： Realizing increasingly complex artificial intelligence (AI) functionalities directly on edge devices calls for unprecedented energy efficiency of edge hardware. Compute-in-memory (CIM) based on resistive random-access memory (RRAM)(1) promises to meet such demand by storing AI model weights in dense, analogue and non-volatile RRAM devices, and by performing AI computation directly within RRAM, thus eliminating power-hungry data movement between separate compute and memory(2-5). Although recent studies have demonstrated in-memory matrix-vector multiplication on fully integrated RRAM-CIM hardware(6-17), it remains a goal for a RRAM-CIM chip to simultaneously deliver high energy efficiency, versatility to support diverse models and software-comparable accuracy. Although efficiency, versatility and accuracy are all indispensable for broad adoption of the technology, the inter-related trade-offs among them cannot be addressed by isolated improvements on any single abstraction level of the design. Here, by co-optimizing across all hierarchies of the design from algorithms and architecture to circuits and devices, we present NeuRRAM-a RRAM-based CIM chip that simultaneously delivers versatility in reconfiguring CIM cores for diverse model architectures, energy efficiency that is two-times better than previous state-of-the-art RRAM-CIM chips across various computational bit-precisions, and inference accuracy comparable to software models quantized to four-bit weights across various AI tasks, including accuracy of 99.0 percent on MNIST18 and 85.7 percent on CIFAR-10(19) image classification, 84.7-percent accuracy on Google speech command recognition(20), and a 70-percent reduction in image-reconstruction error on a Bayesian image-recovery task.

关键词： Computational biology and bioinformatics   Computer science   Genomics  

摘要： Powerful ‘grammar’ allows geneticists to display their data in interactive and scalable illustrations.

关键词： Computational science   Computer science   Electrical and electronic engineering