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关键词： artificial intelligence   big data   computer science   psychological assessment  

摘要： Psychological science can benefit from and contribute to emerging approaches from the computing and information sciences driven by the availability of real-world data and advances in sensing and computing. We focus on one such approach, machine-learned computational models (MLCMs)-computer programs learned from data, typically with human supervision. We introduce MLCMs and discuss how they contrast with traditional computational models and assessment in the psychological sciences. Examples of MLCMs from cognitive and affective science, neuroscience, education, organizational psychology, and personality and social psychology are provided. We consider the accuracy and generalizability of MLCM-based measures, cautioning researchers to consider the underlying context and intended use when interpreting their performance. We conclude that in addition to known data privacy and security concerns, the use of MLCMs entails a reconceptualization of fairness, bias, interpretability, and responsible use.

关键词： Quantum computing   Programming profession   Quantum mechanics   Linear algebra   Education   Task analysis   Python   Computer science   quantum computing   quantum information   quantum programming   science   survey   technology applications   workshop  

摘要： Contribution: In this study, an alternative educational approach for introducing quantum computing to a wider audience is highlighted. The proposed methodology considers quantum computing as a generalized probability theory rather than a field emanating from physics and utilizes quantum programming as an educational tool to reinforce the learning process. Background: Quantum computing is a topic mainly rooted in physics, and it has been gaining rapid popularity in recent years. A need for extending the educational reach to groups outside of physics has also been becoming a necessity. Intended Outcomes: This study aims to inform academics and organizations interested in introducing quantum computing to a diverse group of participants on an educational approach. It is intended that the proposed methodology would facilitate people from diverse backgrounds to enter the field. Application Design: The introductory quantum physics content is bypassed and the quantum computing concepts are introduced through linear algebra instead. Quantum programming tasks are prepared in line with the content. Pre/post-test design method and Likert scale satisfaction surveys are utilized to measure knowledge acquisition and to evaluate the perception of the learning process by the participants. Findings: Conducted pre/post-test design survey shows that there is a statistically significant increase in the basic knowledge levels of the participants on quantum computing concepts. Furthermore, no significant difference in the gain scores is observed between the participants from different STEM-related educational backgrounds. The majority of the participants were satisfied and provided positive feedback.

关键词： Computer science   Artificial intelligence   Human-computer interaction  

摘要： We propose CX-ToM, short for counterfactual explanations with theory-of-mind, a new explainable AI (XAI) framework for explaining decisions made by a deep convolutional neural network (CNN). In contrast to the current methods in XAI that generate explanations as a single shot response, we pose explanation as an iterative communication process, i.e., dialogue between the machine and human user. More concretely, our CX-ToM framework generates a sequence of explanations in a dialogue by mediating the differences between the minds of the machine and human user. To do this, we use Theory of Mind (ToM) which helps us in explicitly modeling the human's intention, the machine's mind as inferred by the human, as well as human's mind as inferred by the machine. Moreover, most state-of-the-art XAI frameworks provide attention (or heat map) based explanations. In our work, we show that these attention-based explanations are not sufficient for increasing human trust in the underlying CNN model. In CX-ToM, we instead use counterfactual explanations called fate' :fines which we define as follows: given an input image I for which a CNN classification model M predicts class C-pred, a fault-line identifies the minimal semantic-level features (e.g., stripes on zebra), referred to as exp!ainable concepts, that need to be added to or deleted from I to alter the classification category of I by M to another specified class c at . Extensive experiments verify our hypotheses, demonstrating that our CX-ToM significantly outperforms the state-of-the-art XAI models.

关键词： Computer science   Artificial intelligence   Devices  

摘要： Biological visual system can efficiently handle optical information within the retina and visual cortex of the brain, which suggests an alternative approach for the upgrading of the current low-intelligence, large energy consumption, and complex circuitry of the artificial vision system for high-performance edge computing applications. In recent years, retinomorphic machine vision based on the integration of optoelectronic image sensors and processors has been regarded as a promising cant" date to improve this phenomenon. This novel intelligent machine vision technology can perform information preprocessing near or even within the sensor in the front end, thereby reducing the transmission of redundant raw data and improving the efficiency of the back-end processor for high-level computing tasks. In this contribution, we try to present a comprehensive review on the recent progress achieved in this emergent field.

关键词： High-performance computing in bioinformatics   Applied sciences   Computer science  

摘要： Polymer memristors are preeminent candidates for low-power edge computing paradigms. Poly[chalcogenoviologen-alt-triphenylamine] (PCVTPA) has been synthesized by direct coupling of chalcogeno-viologen as electron acceptor and 4-(bromomethyl)-N-(4-(bromo-methyl)phenyl)-N-phenylaniline as electron donor. The introduction of chalcogen atoms (S, Se, Te) into viologen scaffolds can greatly improve electrical conductive, electrochemical, and electrochromic properties of the materials when compared with the conventional viologens. Taking PTeVTPA as an example, the as-fabricated electronic device with a configuration of Al/PTeVTPA/ITO exhibits excellent multilevel storage and history-dependent memristive switching performance. Associated with the unique memristive behavior, the PTeVTPA-based device can not only be used to emulate the synaptic potentiation/depression, the human's learning and memorizing functions, and the transition from short-term synaptic plasticity to long-term plasticity but also carry out decimal arithmetic operations as well. This work will be expected to offer a train of new thought for constructing high-performance synaptic biomimicking and neuromorphic computing system in the near future.

关键词： Applied computing   Computer architecture   Computer hardware   Computer science   Computer systems organization  

摘要： Ultra-high chip power densities that are expected to surpass 1-2kW/cm(2) in future high-performance systems cannot be easily handled by conventional cooling methods. Various emerging cooling methods, such as liquid cooling via micro-channels, thermoelectric coolers (TECs), two-phase vapor chambers, and hybrid cooling options have been designed to efficiently remove heat from high-performance processors. However, selecting the optimal cooling solution for a given chip and determining the optimal cooling parameters for that solution to achieve high efficiency are open problems. These problems are, in fact, computationally expensive because of the massive space of possible solutions. To address this design challenge, this article introduces a deep learning-based cooling design optimization flow that rapidly and accurately converges to the optimal cooling solution as well as the optimal cooling parameters for a given chip floorplan and its power profile.

关键词： SARS-CoV-2   Epidemiology   Research data   Computer science  

摘要： Among these models, the World Health Organization (WHO) is still working on its first global estimate, but the Institute for Health Metrics and Evaluation in Seattle, Washington, offers daily updates of its own modelled results, as well as projections of how quickly the global toll might rise. Responding to De Nicola's work, Felix zur Nieden, a demographer at Germany's statistical office, says he agrees that raw numbers should be adjusted to take age structure and other subtleties into account. More-sophisticated analyses adjust the expected deaths baseline to account for such biases, for example by raising the number of expected deaths as a population ages. Probably the most comprehensive of these excess-mortality estimates come from Ariel Karlinsky, an economist at the Hebrew University ofJerusalem in Israel, and Dmitry Kobak, a data scientist at the University of Tübingen, Germany. Since January 2021, Karlinsky and Kobak have produced a regularly updated database of all-cause mortality before and during the pandemic (2015-21) from as many sources and for as many places as possible2 - currently some 116 countries and territories.

关键词： collaborative tracking   community-based design   culturally-informed design   personal informatics  

摘要： A healthy diet and increased physical activity are essential for reducing the prevalence of cardiovascular disease and related deaths, a worldwide public health concern that disproportionately affects Black American communities. Still, Black Americans can face unique challenges meeting dietary and physical activity requirements due to inequities in access and quality of care, environmental and local factors, and difficulties in changing individual health behaviors. Personal informatics and self-tracking tools are one way of increasing awareness of health behaviors to motivate behavior change. However, there are still gaps in knowledge about what encourages different users to engage with personal informatics tools over time, particularly when used in collaborative, community-health settings. This paper contributes a nuanced understanding of fifteen participants' reasons for engaging in an existing community-based health education and behavior change program that combines collaborative self-tracking with culturally relevant content and social engagement to motivate heart-healthy behaviors. We illustrate participants' positive and negative experiences engaging in self-tracking and collaborative tasks during the program. We also discuss how participants envision that integrating technology might support or hinder participant engagement and the work of deploying community-based public health interventions. Finally, we discuss design implications for culturally informed, community-based personal informatics tools that engage Black American's in heart-healthy activities.

关键词： Feature extraction   Correlation   Transformers   Data mining   Semantics   Software   Computer science  

摘要： Multiview multilabel (MVML) learning deals with objects with diverse feature vectors and rich semantics. Existing methods are built on a shared latent space among multiple views. However, they do not well capture semantic consistency and view interactions. What's more, they neglect different contributions of each view to multilabel learning. To address these issues, a novel Personalized RElation rEfinement Network (PREEN) is proposed to sufficiently exploit associated relationships. First, common and specific information is learned in an adversarial way to prevent them from interfering with each other. Then, we adapt the standard transformer to capture cross-view interactions. Similarly, we design label-specific transformers to model label-view dependence, which associates each label with relevant views separately. Eventually, we develop an interlabel attention mechanism to exploit label correlations and refine complementary information from other labels dynamically. Extensive experiments on one real and seven public MVML datasets validate the effectiveness of our proposed PREEN.

关键词： Engineering   Mathematics and computing   Computer science  

摘要： There are two principle approaches for learning in artificial intelligence: error-driven global learning and neuroscience-oriented local learning. Integrating them into one network may provide complementary learning capabilities for versatile learning scenarios. At the same time, neuromorphic computing holds great promise, but still needs plenty of useful algorithms and algorithm-hardware co-designs to fully exploit its advantages. Here, we present a neuromorphic global-local synergic learning model by introducing a brain-inspired metalearning paradigm and a differentiable spiking model incorporating neuronal dynamics and synaptic plasticity. It can meta-learn local plasticity and receive top-down supervision information for multiscale learning. We demonstrate the advantages of this model in multiple different tasks, including few-shot learning, continual learning, and fault-tolerance learning in neuromorphic vision sensors. It achieves significantly higher performance than singlelearning methods. We further implement the model in the Tianjic neuromorphic platform by exploiting algorithm-hardware co-designs and prove that the model can fully utilize neuromorphic many-core architecture to develop hybrid computation paradigm.