35 research outputs found
Social Chat AI and Its Impact on User Well-being
No full textThe dataset contains a survey conducted on the Chai platform. A total of 5,260 responses were collected. The dataset contains anonymized user IDs, email addresses (partially obscured for privacy), gender, age range, and several questions related to the impact of Social Chat AI on mental health and social anxieties. The questions are rated on a numerical scale, likely indicating the level of agreement or impact. Additionally, there are columns for optional feedback for developers and timestamps for when the survey started and was submitted
Exploring Temporal and Spatial Correlations on Circuit Variables for Enhancing Simulation-based Test Generation
No full textThe ever-increasing complexity and size of current circuit designs have made testing and verification major bottlenecks in the design flow of VLSI (Very Large Scale Integrated) circuits. Statistics show that more than 70% of the design effort can be spent on functional verification and manufacturing testing. This percentage is expected to increase in the future if no significant strides in these areas are made. In this dissertation, we target three related problems in simulation-based Design Verification and Testing: Sequential ATPG (Automatic Test Pattern Generation), Unbounded Model Checking (UMC) of safety properties, and low power testing for full-scan sequential circuits. We model these three problems as simulation-based pattern generation problems and exploit novel ATPG algorithms to increase the effectiveness of sequential ATPGs.
The main challenge for fault/error detection in sequential circuits is the large number of flip-flops (FFs) in modern designs. Due to the large number and variable length of test sequences required for such circuits, the existing deterministic ATPG algorithms fail to achieve high test coverages. Such algorithms typically work by first unrolling the sequential circuit and then performing frequent backtracking to generate test vectors for fault detection. For the hard-to-detect faults, these schemes either run out of memory or require a huge computational effort. We show that simulation-based ATPGs, on the other hand, scale very well for large circuits as they perform only forward simulation. A fundamental problem associated with simulation-based ATPGs is to avoid exhaustive circuit simulation, which is impractical for large designs in the real world, by choosing high quality test vectors that achieve a high test coverage within a low simulation time. We tackle this primary problem by exploiting different correlation-based heuristics.
The intuition behind using correlation-based heuristics is to better guide the pattern generation engine such that the specific objective of either fault detection or property verification in UMC or minimizing power consumption during the testing, is achieved in an efficient manner without resorting to exhaustive simulation. In particular, we model and explore the following correlations: (1) temporal correlations, i.e. correlations on each primary input (PI) in different time frames, and (2) spatial correlations, i.e. correlations among different FFs in the same time frame. We employ temporal correlations in the context of pattern generation of a built-in-self-test (BIST) architecture and we explore spatial correlations to guide a logic-simulation-based sequential ATPG and low power scan test generation. Experimental results on ISCAS and ITC benchmark circuits have shown that those correlations can enhance the simulation to discover more faults or design errors in a significantly shorter time.Ph. D
Social AI Improves Well-Being Among Female Young Adults
No full textThe rise of language models like ChatGPT has introduced Social AI as a new
form of entertainment, particularly among young adults who engage with
AI-powered agents. This paper investigates the effects of these interactions on
users' social and mental well-being, a subject that has incited extensive
debate among both the public and scholars. Our study involved a survey of 5,260
users of Chai, a Social AI Platform. The findings indicate significant
benefits, with notable variations across demographics. Female users, in
particular, reported the most substantial improvements: 43.4% strongly agreed
that Social AI positively impacted their mental health, exceeding male users by
10.5%. In managing social anxieties, 38.9% of females strongly agreed on a
positive impact, compared to 30.0% for males and 27.1% for other genders.
Historically, new media and technology have often been met with groundless
moral panic, with societal figures raising concerns without substantial
evidence of harm. Our research indicates the importance of approaching such
claims with caution and emphasizes the necessity of an evidence-based
perspective in discussions about the behavioral effects of emerging
technologies
The Economic Consequences of IPO Spinning
No full textUsing a sample of fifty-six companies going public in 1996--2000 in which top executives received allocations of other hot initial public offerings (IPOs) from the bookrunner, a practice known as spinning, we examine the consequences of spinning. The fifty-six IPOs had first-day returns that were, on average, 23% higher than similar IPOs. The profits collected by these executives were only a small fraction of the incremental amount of money left on the table by their companies when they went public. These companies were dramatically less likely to switch investment bankers in a follow-on offer: only 6% of issuers whose executives were spun switched underwriters, whereas 31% of other issuers switched. These findings suggest that the spinning of executives accomplished its goal of affecting corporate decisions. The Author 2010. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: [email protected]., Oxford University Press.
Research on optimized GA-SVM vehicle speed prediction model based on driver-vehicle-road-traffic system
No full textComplementary Motion Vector for Motion Prediction in Video Coding with Long-Term Reference
No full textThe expression of APE1 in triple-negative breast cancer and its effect on drug sensitivity of olaparib
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