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关键词： Machine learning   Technology   Policy   Computer science  

摘要： Establish an independent scientific body to test and certify generative artificial intelligence, before the technology damages science and public trust.

关键词： Computer science   Optics and photonics  

摘要： A single chip that integrates optical and electronic analog computing modules provides a strategy for creating all-analog computing processors with a speed and energy efficiency that are several orders of magnitude higher than those of state-of-the-art digital processors.

关键词： Paper  

摘要： Mental health conversational agents (a.k.a. chatbots) are widely studied for their potential to offer accessible support to those experiencing mental health challenges. Previous surveys on the topic primarily consider papers published in either computer science or medicine, leading to a divide in understanding and hindering the sharing of beneficial knowledge between both domains. To bridge this gap, we conduct a comprehensive literature review using the PRISMA framework, reviewing 534 papers published in both computer science and medicine. Our systematic review reveals 136 key papers on building mental health-related conversational agents with diverse characteristics of modeling and experimental design techniques. We find that computer science papers focus on LLM techniques and evaluating response quality using automated metrics with little attention to the application while medical papers use rule-based conversational agents and outcome metrics to measure the health outcomes of participants. Based on our findings on transparency, ethics, and cultural heterogeneity in this review, we provide a few recommendations to help bridge the disciplinary divide and enable the cross-disciplinary development of mental health conversational agents. © 2023, CC BY.

ISBN: (纸本)9798400708503

关键词： Trees (mathematics)  

摘要： This study delves into the intricate world of knowledge evolution within academic genealogies. Leveraging a rich dataset amalgamating information from the Academic Family Tree and Microsoft Academic Graph, we meticulously dissect the dynamics of knowledge transmission and development among computer science scholars. Our analysis employs knowledge units as a micro-level representation of scholars' knowledge, allowing us to discern nuanced patterns in knowledge inheritance and mutation. Key findings underscore the prevalence of incremental knowledge evolution, with a quarter of scholars undergoing knowledge mutation. Strikingly, the history of computing emerges as a dominant theme in terms of knowledge expression, intriguingly surpassing fields like computer networks and software engineering. We posit this phenomenon akin to recessive inheritance, prompting intriguing avenues for further exploration. Additionally, we observe diverse evolutionary patterns across knowledge units, from incremental changes to abrupt mutations. Certain domains such as processor architectures and system design logic, thrive on knowledge mutations, integrating cross-disciplinary insights for evolutionary leaps. This study, while shedding light on the intricacies of knowledge evolution, acknowledges the data limitations and the multifaceted nature of knowledge pathways. Future research endeavors are encouraged to embrace larger datasets and explore the multifarious facets of knowledge evolution within academic communities. © 2023, The Authors. All rights reserved.

关键词： Computer science   Materials science  

摘要： Defects are prevalent in two-dimensional (2D) materials due to thermal equilibrium and processing kinetics. The presence of various defect types can affect material properties significantly. With the development of the advanced transmission electron microscopy (TEM), the property-related structures could be investigated in multiple dimensions. It produces TEM datasets containing a large amount of information. Traditional data analysis is influenced by the subjectivity of researchers, and manual analysis is inefficient and imprecise. Recent developments in deep learning provide robust methods for the quantitative identification of defects in 2D materials efficiently and precisely. Taking advantage of big data, it breaks the limitations of TEM as a local characterization tool, making TEM an intelligent macroscopic analysis method. In this review, the recent developments in the TEM data analysis of defects in 2D materials using deep learning technology are summarized. Initially, an in-depth examination of the distinctions between TEM and natural images is presented. Subsequently, a comprehensive exploration of TEM data analysis ensues, encompassing denoising, point defects, line defects, planar defects, quantitative analysis, and applications. Furthermore, an exhaustive assessment of the significant obstacles encountered in the accurate identification of distinct structures is also provided.

关键词： Sports medicine   Computer science   Engineering  

摘要： Postural abnormalities have become a prevalent issue affecting individuals of all ages, resulting in a dimin-ished quality of life. Easy-use and reliable posture assessment tools can aid in screening for and correcting posture deviation at an early stage. In this study, we present a depth camera-based static posture assess-ment system to screen for common postural anomalies such as uneven shoulders, pelvic tilt, bowlegs and knock-knees, forward head, scoliosis, and shoulder blade inclination. The system consists of an Azure Kinect camera, a laptop, and evaluation software. Our system accurately measures skeleton and posture indexes and shows favorable agreement with a golden standard optical infrared motion capture system. The findings indicate that the system is a low-cost posture assessment tool with high precision and accu-racy, suitable for initial screening of postural abnormalities in individuals of all ages.

关键词： Health sciences   Medicine   Computer science  

摘要： Ongoing HIV transmission is a public health priority in Indonesia. We developed a new multiassay algorithm (MAA) to identify recent HIV infection. The MAA is a sequential decision tree based on multiple biomarkers, starting with CD4(+) T cells >200/mu L, followed by plasma viral load (pVL) > 1,000 copies/ml, avidity index (AI) < 0 . 7, and pol ambiguity <0 . 47%. Plasma from 140 HIV-infected adults from 19 hospitals across Indonesia (January 2018 - June 2020) was studied, consisting of a training set (N = 60) of longstanding infection (>12-month) and a test set (N = 80) of newly diagnosed (<= 1-month) antiretroviral (ARV) drug naive individuals. Ten of eighty (12 . 5%) newly diagnosed individuals were classified as recent infections. Drug resistance mutations (DRMs) against reverse transcriptase inhibitors were identified in two individuals: one infected with HIV subtype C (K219Q, V179T) and the other with CRF01_AE (V179D). Ongoing HIV transmission, including infections with DRMs, is substantial in Indonesia.

关键词： Natural sciences   Computer science   Engineering  

摘要： An improved whale optimization algorithm (SWEWOA) is presented for global optimization issues. Firstly, the sine mapping initialization strategy (SS) is used to generate the population. Secondly, the escape energy (EE) is introduced to balance the exploration and exploitation of WOA. Finally, the wormhole search (WS) strengthens the capacity for exploitation. The hybrid design effectively reinforces the optimization capability of SWEWOA. To prove the effectiveness of the design, SWEWOA is performed in two test sets, CEC 2017 and 2022, respectively. The advantage of SWEWOA is demonstrated in 26 superior comparison algorithms. Then a new feature selection method called BSWEWOA-KELM is developed based on the binary SWEWOA and kernel extreme learning machine (KELM). To verify its performance, 8 high-performance algorithms are selected and experimentally studied in 16 public datasets of different difficulty. The test results demonstrate that SWEWOA performs excellently in selecting the most valuable features for classification problems.

关键词： Students  

摘要： Randomized A/B comparisons of alternative pedagogical strategies or other course improvements could provide useful empirical evidence for instructor decision-making. However, traditional experiments do not provide a straightforward pathway to rapidly utilize data, increasing the chances that students in an experiment experience the best conditions. Drawing inspiration from the use of machine learning and experimentation in product development at leading technology companies, we explore how adaptive experimentation might aid continuous course improvement. In adaptive experiments, data is analyzed and utilized as different conditions are deployed to students. This can be achieved using machine learning algorithms to identify which actions are more beneficial in improving students’ learning experiences and outcomes. These algorithms can then dynamically deploy the most effective conditions in subsequent interactions with students, resulting in better support for students’ needs. We illustrate this approach with a case study that provides a side-by-side comparison of traditional and adaptive experiments on adding self-explanation prompts in online homework problems in a CS1 course. This work paves the way for exploring the importance of adaptive experiments in bridging research and practice to achieve continuous improvement in educational settings. Copyright © 2023, The Authors. All rights reserved.