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关键词： Artificial intelligence  

摘要： This research explores the interdisciplinary interaction between psychoanalysis and computer science, suggesting a mutually beneficial exchange. Indeed, psychoanalytic concepts can enrich technological applications involving the human factor, such as social media and other interactive digital platforms. By providing deeper insights into elusive, unconscious aspects of communication, psychoanalytic methods can enhance content-centric applications like fake news detection and mental health diagnostics. Conversely, computer science, especially Artificial Intelligence (AI), can contribute quantitative concepts and methods to psychoanalysis, identifying patterns and emotional cues in human expression. In particular, this research aims to apply computer science methods to establish fundamental relationships between emotions and Lacanian discourses. Such relations are discovered in our approach via empirical investigation and statistical analysis, and are eventually validated in a theoretical (psychoanalytic) way. It is worth noting that, although emotions have been sporadically studied in Lacanian theory, to the best of our knowledge a systematic, detailed investigation of their role is missing. Such fine-grained understanding of the role of emotions can also make the identification of Lacanian discourses more effective and easy in practise. In particular, our methods indicate the emotions with highest differentiation power in terms of corresponding discourses;conversely, we identify for each discourse the most characteristic emotions it admits. As a matter of fact, we develop a method which we call Lacanian Discourse Discovery (LDD), that simplifies (via systematizing) the identification of Lacanian discourses in texts. Although the main contribution of this paper is inherently theoretical (psychoanalytic), it can also facilitate major practical applications in the realm of interactive digital systems. Indeed, our approach can be automated through Artificial Intelligence

关键词： Market culture   Innovation performance   Absorptive capacity   Resistance to change  

摘要： PurposeThis study aims to investigate the relationship between market culture and innovation performance and to reveal the role of absorptive capacity and resistance to change by building on the resource-based ***/methodology/approachData was gathered from 222 firm managers of manufacturing firms by using the survey method. Structural equation modeling and PROCESS macro were used to analyze the *** results indicate that market culture is positively related to innovation performance and absorptive capacity mediates this relationship. It is also found that resistance to change negatively moderates the relationship between market culture and innovation performance, but it has no moderating effect on the relationship between absorptive capacity and innovation ***/valuePrevious research examining the association between market culture and innovation performance is scarce and provides contradictory findings. This indicates that there is an underlying mechanism of this association neglected before. This study is an attempt to reconcile contradictory findings and enlighten the fuzzy areas of this relationship. Accordingly, this study focuses on absorptive capacity as a mediator and proves its role empirically. Moreover, this study is the first to examine the role of resistance to change and demonstrates its buffer role in the market culture-innovation performance link. It is also revealed that resistance to change does not moderate the relationship between absorptive capacity and innovation performance. The findings elucidate the underlying mechanism of the relationship between market culture and innovation performance, reconcile contradictory findings of extant research, expand the current knowledge, and provide practical implications.

关键词： Machine learning   Computer science   Society  

关键词： Machine learning   Computer science   Mathematics and computing   Society  

摘要： Scientists are closing in on a tool that can reliably identify AI-generated text without affecting the user's experience. But the technology's robustness remains a challenge.

关键词： Careers   Computer science   Software  

摘要： Minh Ha Quang’s work at a Japanese AI research centre aims to understand how machines extract image data from the real world.

摘要： This study evaluates the effectiveness of incorporating makerspace workshops into computer science education by assessing 21st-century skills-critical thinking, collaboration, communication, and creativity-before and after the intervention. Using a pre-test and post-test approach with the "21st Century Skills Survey Instrument," the study quantifies the impact of makerspace activities on student skill development. Participants included students enrolled in two computer science courses at Cyprus College. Statistical analysis, conducted using Python, revealed significant improvements across all assessed skills, indicating that makerspace workshops enhance essential competencies needed for the modern workforce. These findings provide valuable insights into how experiential learning environments can transform traditional computer science education, promoting a more interactive and engaging learning experience. Future research should focus on larger, more diverse samples and explore specific components of makerspace activities that most effectively contribute to skill development. © 2024, CC BY.

关键词： Engineering education  

摘要： Large language models (LLMs) are becoming increasingly better at a wide range of Natural Language Processing tasks (NLP), such as text generation and understanding. Recently, these models have extended their capabilities to coding tasks, bridging the gap between natural languages (NL) and programming languages (PL). Foundational models such as the Generative Pre-trained Transformer (GPT) and LLaMA series have set strong baseline performances in various NL and PL tasks. Additionally, several models have been fine-tuned specifically for code generation, showing significant improvements in code-related applications. Both foundational and fine-tuned models are increasingly used in education, helping students write, debug, and understand code. We present a comprehensive systematic literature review to examine the impact of LLMs in computer science and computer engineering education. We analyze their effectiveness in enhancing the learning experience, supporting personalized education, and aiding educators in curriculum development. We address five research questions to uncover insights into how LLMs contribute to educational outcomes, identify challenges, and suggest directions for future research. © 2024, CC BY.

关键词： physics   biological sciences   computer science   engineering  

摘要： How actin filaments (F-actins) are dynamically reorganized in motile cells at the level of individual filaments is an open question. To find the answer, a high-speed atomic force microscopy (HS-AFM) system has been developed to live-imagine intracellular dynamics of the individual F-actins. However, noise and low resolution made it difficult to fully recognize individual F-actins in the HS-AFM images. To tackle this problem, we developed a new machine learning method that quantitatively recognizes individual F-actins. The method estimates F-actin orientation from the image while improving the resolution. We found that F-actins were oriented at +/- 35 degrees toward the membrane in the lamellipodia, which is consistent with Arp2/3 complex-induced branching. Furthermore, in the cell cortex our results showed non-random orientation at four specific angles, suggesting a new mechanism for F-actin organization demonstrating the potential of our newly developed method to fundamentally improve our understanding of the structural dynamics of F-actin networks.