1,875 research outputs found

    Undergraduate Catalog of Studies, 2023-2024

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    Undergraduate Catalog of Studies, 2023-2024

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    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    Low- and high-resource opinion summarization

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    Customer reviews play a vital role in the online purchasing decisions we make. The reviews express user opinions that are useful for setting realistic expectations and uncovering important details about products. However, some products receive hundreds or even thousands of reviews, making them time-consuming to read. Moreover, many reviews contain uninformative content, such as irrelevant personal experiences. Automatic summarization offers an alternative – short text summaries capturing the essential information expressed in reviews. Automatically produced summaries can reflect overall or particular opinions and be tailored to user preferences. Besides being presented on major e-commerce platforms, home assistants can also vocalize them. This approach can improve user satisfaction by assisting in making faster and better decisions. Modern summarization approaches are based on neural networks, often requiring thousands of annotated samples for training. However, human-written summaries for products are expensive to produce because annotators need to read many reviews. This has led to annotated data scarcity where only a few datasets are available. Data scarcity is the central theme of our works, and we propose a number of approaches to alleviate the problem. The thesis consists of two parts where we discuss low- and high-resource data settings. In the first part, we propose self-supervised learning methods applied to customer reviews and few-shot methods for learning from small annotated datasets. Customer reviews without summaries are available in large quantities, contain a breadth of in-domain specifics, and provide a powerful training signal. We show that reviews can be used for learning summarizers via a self-supervised objective. Further, we address two main challenges associated with learning from small annotated datasets. First, large models rapidly overfit on small datasets leading to poor generalization. Second, it is not possible to learn a wide range of in-domain specifics (e.g., product aspects and usage) from a handful of gold samples. This leads to subtle semantic mistakes in generated summaries, such as ‘great dead on arrival battery.’ We address the first challenge by explicitly modeling summary properties (e.g., content coverage and sentiment alignment). Furthermore, we leverage small modules – adapters – that are more robust to overfitting. As we show, despite their size, these modules can be used to store in-domain knowledge to reduce semantic mistakes. Lastly, we propose a simple method for learning personalized summarizers based on aspects, such as ‘price,’ ‘battery life,’ and ‘resolution.’ This task is harder to learn, and we present a few-shot method for training a query-based summarizer on small annotated datasets. In the second part, we focus on the high-resource setting and present a large dataset with summaries collected from various online resources. The dataset has more than 33,000 humanwritten summaries, where each is linked up to thousands of reviews. This, however, makes it challenging to apply an ‘expensive’ deep encoder due to memory and computational costs. To address this problem, we propose selecting small subsets of informative reviews. Only these subsets are encoded by the deep encoder and subsequently summarized. We show that the selector and summarizer can be trained end-to-end via amortized inference and policy gradient methods

    Effects of municipal smoke-free ordinances on secondhand smoke exposure in the Republic of Korea

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    ObjectiveTo reduce premature deaths due to secondhand smoke (SHS) exposure among non-smokers, the Republic of Korea (ROK) adopted changes to the National Health Promotion Act, which allowed local governments to enact municipal ordinances to strengthen their authority to designate smoke-free areas and levy penalty fines. In this study, we examined national trends in SHS exposure after the introduction of these municipal ordinances at the city level in 2010.MethodsWe used interrupted time series analysis to assess whether the trends of SHS exposure in the workplace and at home, and the primary cigarette smoking rate changed following the policy adjustment in the national legislation in ROK. Population-standardized data for selected variables were retrieved from a nationally representative survey dataset and used to study the policy action’s effectiveness.ResultsFollowing the change in the legislation, SHS exposure in the workplace reversed course from an increasing (18% per year) trend prior to the introduction of these smoke-free ordinances to a decreasing (−10% per year) trend after adoption and enforcement of these laws (β2 = 0.18, p-value = 0.07; β3 = −0.10, p-value = 0.02). SHS exposure at home (β2 = 0.10, p-value = 0.09; β3 = −0.03, p-value = 0.14) and the primary cigarette smoking rate (β2 = 0.03, p-value = 0.10; β3 = 0.008, p-value = 0.15) showed no significant changes in the sampled period. Although analyses stratified by sex showed that the allowance of municipal ordinances resulted in reduced SHS exposure in the workplace for both males and females, they did not affect the primary cigarette smoking rate as much, especially among females.ConclusionStrengthening the role of local governments by giving them the authority to enact and enforce penalties on SHS exposure violation helped ROK to reduce SHS exposure in the workplace. However, smoking behaviors and related activities seemed to shift to less restrictive areas such as on the streets and in apartment hallways, negating some of the effects due to these ordinances. Future studies should investigate how smoke-free policies beyond public places can further reduce the SHS exposure in ROK

    Application of Feedback Conversation for the Efficiency of Interpersonal Communication in Teaching in Higher Education

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    Wydział Studiów EdukacyjnychCelem prowadzonych badań była ocena skuteczności zastosowania informacji zwrotnej dla efektywności komunikacji interpersonalnej w nauczaniu w szkolnictwie wyższym. Skonstruowano proces osobistego instruktarzu, który umożliwiał ocenę komunikacji interpersonalnej wykładowcy w trakcie prowadzenia zajęć ze studentami w pięciu wymiarach: organizacji lekcji, klarowności przekazu, kontaktu z grupą docelową (studentami), wzbudzania zainteresowania oraz tworzenia wartości. Aby osiągnąć cel badawczy, przeprowadzono badania jakościowe z zastosowaniem badania w działaniu, które umożliwiło uczestnikom aktywność i zaangażowanie w całym procesie. Wzięło w nim udział dziesięciu wykładowców z Beit Berl Academic College. Narzędziami badawczymi wykorzystanymi były: wywiad częściowo ustrukturyzowany (na początku i na końcu procesu), obserwacja nagrania video z prowadzonych zajęć (trzy lekcje w semestrze), rozmowa z zastosowaniem informacji zwrotnej i refleksji (po każdym filmie). Wyniki badań wskazują na zmianę, jaka zaszła w aspektach poznawczych, emocjonalnych i behawioralnych na każdym z wymiarów komunikacji interpersonalnej. Ponadto ustalenia wskazują, że dla wszystkich wykładowców rozmowy zwrotne były znaczące i przyczyniły się do zmiany ich praktyk dydaktycznych. Wykładowcy doświadczyli rozmów zwrotnych jako pozytywnych doświadczeń instruktażowych, które przyczyniły się do doskonalenie ich nauczania.The objective of this research study is to explore the application of the feedback conversation on the efficiency of interpersonal communication in higher education teaching. For this purpose, a process of personal instruction was constructed that examined the interpersonal communication of the lecturer during the lecture in five dimensions: the organization of the lesson, the clarity of the messages, the contact with the target audience (the students), the creation of interest, and the creation of value. To achieve the objective, a qualitative research was carried out in the method of action research that enabled the participants to be active and involved throughout the entire process. Ten lecturers from the Beit Berl Academic College participated in this research study. The research instruments used in the research study are a semi-structured interview (before the beginning of the process and at the end of the process), films of the lecturer’s lessons (three lessons during the semester), feedback conversation, and reflection (after each film of the lesson). The research findings indicate a change that occurred among all the lecturers in the cognitive, emotional, and behavioral aspects in each one of the dimensions of interpersonal communication during the feedback conversation. In addition, the findings indicate that for all the lecturers the feedback conversations were meaningful and contributed to the change of their teaching practices. The lecturers experienced the feedback conversations as a positive experience, instructional, which contributed to the improvement of their teaching. pracy (max 1400 znaków) The objective of this research study is to explore the application of the feedback conversation on the efficiency of interpersonal communication in higher education teaching. For this purpose, a process of personal instruction was constructed that examined the interpersonal communication of the lecturer during the lecture in five dimensions: the organization of the lesson, the clarity of the messages, the contact with the target audience (the students), the creation of interest, and the creation of value. To achieve the objective, a qualitative research was carried out in the method of action research that enabled the participants to be active and involved throughout the entire process. Ten lecturers from the Beit Berl Academic College participated in this research study. The research instruments used in the research study are a semi-structured interview (before the beginning of the process and at the end of the process), films of the lecturer’s lessons (three lessons during the semester), feedback conversation, and reflection (after each film of the lesson). The research findings indicate a change that occurred among all the lecturers in the cognitive, emotional, and behavioral aspects in each one of the dimensions of interpersonal communication during the feedback conversation. In addition, the findings indicate that for all the lecturers the feedback conversations were meaningful and contributed to the change of their teaching practices. The lecturers experienced the feedback conversations as a positive experience, instructional, which contributed to the improvement of their teaching

    QR-CLIP: Introducing Explicit Open-World Knowledge for Location and Time Reasoning

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    Daily images may convey abstract meanings that require us to memorize and infer profound information from them. To encourage such human-like reasoning, in this work, we teach machines to predict where and when it was taken rather than performing basic tasks like traditional segmentation or classification. Inspired by Horn's QR theory, we designed a novel QR-CLIP model consisting of two components: 1) the Quantity module first retrospects more open-world knowledge as the candidate language inputs; 2) the Relevance module carefully estimates vision and language cues and infers the location and time. Experiments show our QR-CLIP's effectiveness, and it outperforms the previous SOTA on each task by an average of about 10% and 130% relative lift in terms of location and time reasoning. This study lays a technical foundation for location and time reasoning and suggests that effectively introducing open-world knowledge is one of the panaceas for the tasks.Comment: Technical Report. Github: https://github.com/Shi-Wm/QR-CLI

    Undergraduate Catalog of Studies, 2022-2023

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    The Effects of the Digitally Supported Multimodal Print Texts on Students’ Summarization Skills

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    The aim of this study is to analyse the effects of the multimodal texts created from print texts through addition of digital mode on the students’s summarizing skills. Through the ROAR the digital modes were integrated into the print texts and the multimodal texts were produced. There are two such texts, one of them is an informative text, and the other one is a narrative text. The participants of the study were 128 seventh grade secondary school students from Antalya province (Türkiye) whose ages range between 12 and 13. They were randomly assigned to the experimental and control groups. At the pre-test step both groups read and summarized the print texts. At the post-test step the experimental group read and summarized the multimodal texts created by adding a digital mode whereas the control group the print texts. The results showed that there was a significant difference in favor of the experimental group in the total scores and content scores concerning the informative and narrative texts. On the other hand, it is found that the form and style scores from the informative and narrative texts did not differ significantly between the groups. In addition, in the post-test results of the experimental group, there was a significant difference in favor of the narrative text. The results suggest that the use of the multimodal texts have positive effects on the participants’ summarizing skills

    SYSTEMATIC REVIEW OF STUDIES ON WRITING IN ELEMENTARY SCHOOL

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    This paper presents a systematic literature review of studies about writing in elementary schools. A systematic search of databases was conducted to select studies. The aim was to identify and categorize difficulties and suggestions. A total of 52 articles published in peer-reviewed journals over the past 21 years were reviewed and analyzed using a well-established systematic literature review methodology, in academic-based research databases, after carefully reviewing the available literature and utilizing relevant sources. This review revealed that the studies mainly emphasize the relation between reading and writing, using technology in teaching writing, acquisition of writing and a method/approach or strategy suggestion, and structure/grammar in writing. Additionally, feedback, affective domain, and teaching writing at an early age are the focus points of other studies. The findings of this literature review allow teachers, administrators, and policy makers to employ and explore efficient writing activities to improve student engagement, motivation, and performance
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