Hasil untuk "American literature"

Sydney Klein, Alaina Brenick, Megan Clark Kelly et al.

IntroductionWhen thinking about intergroup exclusion, adolescents weigh prosociality and fairness with the influences of their families and peers. However, research has yet to address whether these group norms influence youth similarly across gender and age. The current study addresses this gap in the literature by assessing and interaction between subjective outgroup norms and developmental period on youth's evaluations of exclusion and their justifications for those evaluations, and does so within an understudied dynamic between Jewish American and Arab American adolescents.MethodsThis study assessed whether gender and age moderate the influence of parent and peer outgroup attitudes on 241 Jewish American 9th graders' (MAge9thGrade = 14.18; SD = 0.42) and 12th (MAge12thGrade = 17.21; SD = 0.43) acceptance and reasoning about intergroup exclusion toward Arab American peers.ResultsResults revealed that gender was associated with the malleability to influence of 9th graders' attitudes, whereas their 12th grade counterparts were unaffected. Furthermore, positive peer groups served as a buffer against the detrimental effects of parents' prejudiced attitudes.DiscussionAge and context play a meaningful role in adolescents' evaluation and justifications of outgroup social exclusion. These findings contribute to the understanding of the development of prosocial reasoning and behaviors in adolescence.

C. Mills

Élodie Brun, Ana Covarrubias

Abstract The article addresses the question of autonomy in Mexico’s and Brazil’s foreign policies in the context of increasing tensions between the United States and China. Although Mexico’s and Brazil’s relations with China —and to a lesser extent the United States— are very different in nature, both Latin American countries face the same challenge of finding a balance in relations with both great powers. The article analyzes Mexico’s and Brazil’s handling of a “triangular relationship” since 2018, illustrating the scope and limits of each country’s autonomy. In the case of Mexico, economic integration with the United States explains the place of China as both an opportunity and a threat; in the case of Brazil, although China is its major trade partner, domestic interests become as important as structural elements, and its government cannot disregard US concerns. In addition to the review of secondary literature, the article uses a series of interviews of Mexican and Brazilian diplomats.

Aditya Singhal, Nikita Neveditsin, Hasnaat Tanveer et al.

BackgroundThe use of social media for disseminating health care information has become increasingly prevalent, making the expanding role of artificial intelligence (AI) and machine learning in this process both significant and inevitable. This development raises numerous ethical concerns. This study explored the ethical use of AI and machine learning in the context of health care information on social media platforms (SMPs). It critically examined these technologies from the perspectives of fairness, accountability, transparency, and ethics (FATE), emphasizing computational and methodological approaches that ensure their responsible application. ObjectiveThis study aims to identify, compare, and synthesize existing solutions that address the components of FATE in AI applications in health care on SMPs. Through an in-depth exploration of computational methods, approaches, and evaluation metrics used in various initiatives, we sought to elucidate the current state of the art and identify existing gaps. Furthermore, we assessed the strength of the evidence supporting each identified solution and discussed the implications of our findings for future research and practice. In doing so, we made a unique contribution to the field by highlighting areas that require further exploration and innovation. MethodsOur research methodology involved a comprehensive literature search across PubMed, Web of Science, and Google Scholar. We used strategic searches through specific filters to identify relevant research papers published since 2012 focusing on the intersection and union of different literature sets. The inclusion criteria were centered on studies that primarily addressed FATE in health care discussions on SMPs; those presenting empirical results; and those covering definitions, computational methods, approaches, and evaluation metrics. ResultsOur findings present a nuanced breakdown of the FATE principles, aligning them where applicable with the American Medical Informatics Association ethical guidelines. By dividing these principles into dedicated sections, we detailed specific computational methods and conceptual approaches tailored to enforcing FATE in AI-driven health care on SMPs. This segmentation facilitated a deeper understanding of the intricate relationship among the FATE principles and highlighted the practical challenges encountered in their application. It underscored the pioneering contributions of our study to the discourse on ethical AI in health care on SMPs, emphasizing the complex interplay and the limitations faced in implementing these principles effectively. ConclusionsDespite the existence of diverse approaches and metrics to address FATE issues in AI for health care on SMPs, challenges persist. The application of these approaches often intersects with additional ethical considerations, occasionally leading to conflicts. Our review highlights the lack of a unified, comprehensive solution for fully and effectively integrating FATE principles in this domain. This gap necessitates careful consideration of the ethical trade-offs involved in deploying existing methods and underscores the need for ongoing research.

Karsi Widiawati, Bertha M. Sopha, Naly Rakoto

France is one of the pioneer countries in the use of Electric Vehicles (EVs). The French government aims to complete the transition to EVs by 2040. Therefore, modeling related to the adoption of EVs is needed in order to determine the potential policies needed to achieve this goal. This modeling is based on a literature study to identify the factors and the causal relationship between those factors. The systematic literature review (SLR) analysis was performed on 20 journals selected based on PRISMA filtering. From this SLR analysis, five direct factors and four indirect factors were obtained which were then used as the basis for modeling. Based on the model developed, four balancing (B) loops and three reinforcing (R) loops were obtained. From the analysis, it was found that the advertising factor has a goal seeking structure, while the word of mouth, environmentally friendly image, and total cost of ownership factors have an S-shaped structure.

Wilson Chango, Teresa Olivares, Francisc oDelicado

The bibliographic review is a fundamental phase in a research project, and it must guarantee that the most relevant information in the field of study is obtained. Our main objective was to know the works related to the Internet of medical things, from now on (IoMT). We analyzed a total of 535 articles searched in association for Computing Machinery in Adelante ACM, Web of Science and Scopus the search domain was IoMT, we established 3 parameters, (problematic, artifact and artifact evaluation), this according to the Research of Design Science in Adelante DSR, is a research approach for the construction of artifacts to provide a useful solution to a problem in each domain. The equation (Internet of things AND mesh) resulted in 535, (Internet of things AND medicine) a total of 417 and finally (Internet of medical things AND mesh) with 8, this means that there is a lot to investigate in this research domain. The advantages identified in this type of topology is to carry messages from one node to another by different paths, there can be absolutely no interruption in communications, each server has its own communications with all other servers. Health and IT issues have been drastically influenced by the large data from IoMT devices. In this paper, we conducted a review of the scientific literature and mapped research trends on the IoMT paradigm in the health domain. Finally, this paper expands on the literature, and the findings of this study can serve as a basis for future studies.

Filippo Ricca, Alessandro Marchetto, Andrea Stocco

Context: Test Automation (TA) techniques are crucial for quality assurance in software engineering but face limitations such as high test suite maintenance costs and the need for extensive programming skills. Artificial Intelligence (AI) offers new opportunities to address these issues through automation and improved practices. Objectives: Given the prevalent usage of AI in industry, sources of truth are held in grey literature as well as the minds of professionals, stakeholders, developers, and end-users. This study surveys grey literature to explore how AI is adopted in TA, focusing on the problems it solves, its solutions, and the available tools. Additionally, the study gathers expert insights to understand AI's current and future role in TA. Methods: We reviewed over 3,600 grey literature sources over five years, including blogs, white papers, and user manuals, and finally filtered 342 documents to develop taxonomies of TA problems and AI solutions. We also cataloged 100 AI-driven TA tools and interviewed five expert software testers to gain insights into AI's current and future role in TA. Results: The study found that manual test code development and maintenance are the main challenges in TA. In contrast, automated test generation and self-healing test scripts are the most common AI solutions. We identified 100 AI-based TA tools, with Applitools, Testim, Functionize, AccelQ, and Mabl being the most adopted in practice. Conclusion: This paper offers a detailed overview of AI's impact on TA through grey literature analysis and expert interviews. It presents new taxonomies of TA problems and AI solutions, provides a catalog of AI-driven tools, and relates solutions to problems and tools to solutions. Interview insights further revealed the state and future potential of AI in TA. Our findings support practitioners in selecting TA tools and guide future research directions.

W. J. T. Mollema

Is it sensical to ascribe psychological predicates to AI systems like chatbots based on large language models (LLMs)? People have intuitively started ascribing emotions or consciousness to social AI ('affective artificial agents'), with consequences that range from love to suicide. The philosophical question of whether such ascriptions are warranted is thus very relevant. This paper advances the argument that LLMs instantiate language users in Ludwig Wittgenstein's sense but that ascribing psychological predicates to these systems remains a functionalist temptation. Social AIs are not full-blown language users, but rather more like Italo Calvino's literature machines. The ideas of LLMs as Wittgensteinian language users and Calvino's literature-producing writing machine are combined. This sheds light on the misguided functionalist temptation inherent in moving from equating the two to the ascription of psychological predicates to social AI. Finally, the framework of mortal computation is used to show that social AIs lack the basic autopoiesis needed for narrative façons de parler and their role in the sensemaking of human (inter)action. Such psychological predicate ascriptions could make sense: the transition 'from quantity to quality' can take place, but its route lies somewhere between life and death, not between affective artifacts and emotion approximation by literature machines.

Yuhao Liu, Yingnan Zhou, Hanfeng Zhang et al.

Software misconfiguration has consistently been a major reason for software failures. Over the past two decades, much work has been done to detect and diagnose software misconfigurations. However, there is still a gap between real-world misconfigurations and the literature. It is desirable to investigate whether existing taxonomy and tools are applicable for real-world misconfigurations in modern software. In this paper, we conduct an empirical study on 772 real-world misconfiguration issues, based on which we propose a novel classification of the root causes of software misconfigurations, i.e., constraint violation, resource unavailability, component-dependency error, and configuration semantic misinterpretation. Then, we systematically review the literature on misconfiguration troubleshooting to study the trends of research and the practicality of the tools and datasets in this field. We find that the research targets have changed from system and infrastructure software to advanced applications (e.g., cloud service). In the meanwhile, the research on non-crash misconfigurations also has significant growth. Despite the progress, a majority of studies lack reproducibility due to the unavailable tools and evaluation datasets. In total, only ten tools and four datasets are publicly available. We analyze the trends of existing literature on misconfiguration troubleshooting, summarize the challenges that users are faced with, and highlight the suggestions to mitigate and diagnose software misconfigurations. We release the real-world dataset of misconfiguration issues for follow-up research.

Malay Kumar, S. Sarvajit Visagan, Tanish Sarang Mahajan et al.

We have come up with a research that hopes to provide a bridge between the users of American Sign Language and the users of spoken language and Indian Sign Language (ISL). The research enabled us to create a novel framework that we have developed for Learner Systems. Leveraging art of Large models to create key features including: - Real-time translation between these two sign languages in an efficient manner. Making LLM's capability available for seamless translations to ISL. Here is the full study showing its implementation in this paper. The core of the system is a sophisticated pipeline that begins with reclassification and recognition of ASL gestures based on a strong Random Forest Classifier. By recognizing the ASL, it is translated into text which can be more easily processed. Highly evolved natural language NLP (Natural Language Processing) techniques come in handy as they play a role in our LLM integration where you then use LLMs to be able to convert the ASL text to ISL which provides you with the intent of sentence or phrase. The final step is to synthesize the translated text back into ISL gestures, creating an end-to-end translation experience using RIFE-Net. This framework is tasked with key challenges such as automatically dealing with gesture variability and overcoming the linguistic differences between ASL and ISL. By automating the translation process, we hope to vastly improve accessibility for sign language users. No longer will the communication gap between ASL and ISL create barriers; this totally cool innovation aims to bring our communities closer together. And we believe, with full confidence in our framework, that we're able to apply the same principles across a wide variety of sign language dialects.

Ornela Danushi, Stefano Forti, Jacopo Soldani

The ICT sector, responsible for 2% of global carbon emissions, is under scrutiny calling for methodologies and tools to design and develop software in an environmentally sustainable-by-design manner. However, the software engineering solutions for designing and developing carbon-efficient software are currently scattered over multiple different pieces of literature, which makes it difficult to consult the body of knowledge on the topic. In this article, we precisely conduct a systematic literature review on state-of-the-art proposals for designing and developing carbon-efficient software. We identify and analyse 65 primary studies by classifying them through a taxonomy aimed at answering the 5W1H questions of carbon-efficient software design and development. We first provide a reasoned overview and discussion of the existing guidelines, reference models, measurement solutions and techniques for measuring, reducing, or minimising the carbon footprint of software. Ultimately, we identify open challenges and research gaps, offering insights for future work in this field.

Yao Yuan

The article analyzes the history of the concept of the “American Dream” in Chinese American literature, and particularly in the work of the Chinese American writer Charles Yu. In his novel Interior Chinatown, he examines the stereotypical perception of Chinese Americans in the eyes of white Americans and highlights the problems that Asian Americans have to deal with, e.g. national identity or discrimination. The novel shows how difficult the process of achieving the American dream is for Asian Americans and how difficult it is for them to find the answer to the question “Who am I,” which is closely connected with the realization of their “American Dream.”

Marco Antonio Stranisci, Eleonora Bernasconi, Viviana Patti et al.

Digital media have enabled the access to unprecedented literary knowledge. Authors, readers, and scholars are now able to discover and share an increasing amount of information about books and their authors. However, these sources of knowledge are fragmented and do not adequately represent non-Western writers and their works. In this paper we present The World Literature Knowledge Graph, a semantic resource containing 194,346 writers and 965,210 works, specifically designed for exploring facts about literary works and authors from different parts of the world. The knowledge graph integrates information about the reception of literary works gathered from 3 different communities of readers, aligned according to a single semantic model. The resource is accessible through an online visualization platform, which can be found at the following URL: https://literaturegraph.di.unito.it/. This platform has been rigorously tested and validated by $3$ distinct categories of experts who have found it to be highly beneficial for their respective work domains. These categories include teachers, researchers in the humanities, and professionals in the publishing industry. The feedback received from these experts confirms that they can effectively utilize the platform to enhance their work processes and achieve valuable outcomes.

Laura Marie Marciano

The kind of twenty-first-century poetry that contains the language of late capitalism, products and brands, and resembles the syntax of text messaging, Instagram comments and memes, is a result of the collective rhetoric of a Millennial group of writers that came of age on the Internet. Online communities and publications that emerged between 2010 and 2016 such as Alt Lit, Internet Poetry, Illuminati Girl Gang, and others, have in fact paved the way for provocative multimodal poetry books such as Rachel Rabbit White’s Porn Carnival (2019). These groups of writers, now many in their early to mid-thirties, are the founders of new digital discourse communities, online journals, and digital reading series, which experienced renewed relevance during the Covid-19 crisis when in-person readings were not possible. This paper discusses the aesthetic and social effects of online discourse communities on the production of poetry books, emphasizing how digital communities function as a continuous and collective writing project on their own.

Aislinn McDougall

This article defines “.compostmodernism” as a successor to postmodernism by explicating of Mark Z. Danielewski’s The Familiar as an example of .compostmodern textual machinery—a system of two interconnected “machines” (one abstract, the other physical) that are co-dependent and mobilized by the novel’s typography and materiality. Beginning by illustrating how The Familiar exemplifies .compostmodern textual machinery through its experimental typography which becomes the visual manifestation of literary cyber-consciousness, this article indicates how, in visually manifesting character cyber-consciousness, the novel’s typography actualizes the digitality of character interiority, ultimately drawing attention to the work’s status not only as literary artifice, but also as textual machinery. The demands of such experimental typography instantiate a physical relationship between reader and codex that emphasizes the novel’s materiality and requires the reader to engage with the text both physically and digitally. Ultimately, this digital engagement incorporates the internet not only as a crucial supplement for the reader to seek reference, translation apps, and supplementary (albeit obscure) Danielewski publications, but also as a medium for the reader to supplement the novel via social media output and online reading communities.

Giovanni Maria Biancofiore, Yashar Deldjoo, Tommaso Di Noia et al.

Question answering systems are recognized as popular and frequently effective means of information seeking on the web. In such systems, information seekers can receive a concise response to their query by presenting their questions in natural language. Interactive question answering is a recently proposed and increasingly popular solution that resides at the intersection of question answering and dialogue systems. On the one hand, the user can ask questions in normal language and locate the actual response to her inquiry; on the other hand, the system can prolong the question-answering session into a dialogue if there are multiple probable replies, very few, or ambiguities in the initial request. By permitting the user to ask more questions, interactive question answering enables users to dynamically interact with the system and receive more precise results. This survey offers a detailed overview of the interactive question-answering methods that are prevalent in current literature. It begins by explaining the foundational principles of question-answering systems, hence defining new notations and taxonomies to combine all identified works inside a unified framework. The reviewed published work on interactive question-answering systems is then presented and examined in terms of its proposed methodology, evaluation approaches, and dataset/application domain. We also describe trends surrounding specific tasks and issues raised by the community, so shedding light on the future interests of scholars. Our work is further supported by a GitHub page with a synthesis of all the major topics covered in this literature study. https://sisinflab.github.io/interactive-question-answering-systems-survey/

Ishika Sahni, Araftoz Kaur

It is expected that the creation of next-generation wireless networks would result in the availability of high-speed and low-latency connectivity for every part of our life. As a result, it is important that the network is secure. The network's security environment has grown more complicated as a result of the growing number of devices and the diversity of services that 5G will provide. This is why it is important that the development of effective security solutions is carried out early. Our findings of this review have revealed the various directions that will be pursued in the development of next-generation wireless networks. Some of these include the use of Artificial Intelligence and Software Defined Mobile Networks. The threat environment for 5G networks, security weaknesses in the new technology paradigms that 5G will embrace, and provided solutions presented in the key studies in the field of 5G cyber security are all described in this systematic literature review for prospective researchers. Future research directions to protect wireless networks beyond 5G are also covered.

Vinicius dos Santos, Rick Kazman, Rafael Capilla et al.

Systematic literature reviews (SLR) have been increasingly conducted in software engineering and they provide significant benefits in terms of summarizing the state of the research. The process of conducting SLR is complex, involving several activities and consuming considerable effort and time from researchers. Researchers often skip or poorly conduct essential activities, which introduce threats to validity, resulting in lower-quality SLR. But researchers are often unaware of what they could do to mature their SLR process, thus improving the SLR quality. The main goal of this paper is to introduce a maturity model for the SLR process named MM4SLR. To this end, we were inspired by well-known models like CMMI (Capability Maturity Model Integration). We first identified 39 key practices for SLR from the literature and grouped them into nine goals that were further grouped into five process areas. We then organized the process areas into five maturity levels which compose our model. Our proof of concept, applying the MM4SLR to four published SLR showed that the MM4SLR is suitable for appraising SLR and can identify important flaws in SLR quality. MM4SLR can therefore support researchers in creating their SLR processes and selecting practices that could be adopted to mature their processes.

Samuel Solgon Santos, Marcelo Brutti Righi, Eduardo de Oliveira Horta

Risk measures satisfying the axiom of comonotonic additivity are extensively studied, arguably because of the plethora of results indicating interesting aspects of such risk measures. Recent research, however, has shown that this axiom is incompatible with central properties in specific contexts. In this paper, we present a literature review of these incompatibilities. In addition, we use the Choquet representation of comonotonic additive risk measures to show they cannot be surplus invariant.

Nada Sahlab, Hesham Kahoul, Nasser Jazdi et al.

Systematic Literature Reviews aim at investigating current approaches to conclude a research gap or determine a futuristic approach. They represent a significant part of a research activity, from which new concepts stem. However, with the massive availability of publications at a rapid growing rate, especially digitally, it becomes challenging to efficiently screen and assess relevant publications. Another challenge is the continuous assessment of related work over a long period of time and the consequent need for a continuous update, which can be a time-consuming task. Knowledge graphs model entities in a connected manner and enable new insights using different reasoning and analysis methods. The objective of this work is to present an approach to partially automate the conduction of a Systematic Literature Review as well as classify and visualize the results as a knowledge graph. The designed software prototype was used for the conduction of a review on context-awareness in automation systems with considerably accurate results compared to a manual conduction.