1,720,956 research outputs found
Adaptive Learning through Artificial Intelligence
Full text linkThis article explores the integration of artificial intelligence (AI) into adaptive learning systems for the purpose of individualizing education through machine learning and predictive analytics. It examines the benefits, challenges and implications of this merger and highlights its potential to revolutionize education by providing a customized and streamlined learning experience. It discusses the role of AI in learner modeling, content customization, and feedback mechanisms, along with considerations such as privacy, data security, and algorithmic bias. AI-powered adaptive learning promises to shape the future of education in the digital age by enabling learners and educators to achieve optimal outcomes
The Security Risks of Generative Artificial Intelligence
Full text linkGenerative Manufactured Insights (AI) frameworks, competent of creating human-like yields such as content, pictures, and recordings, have seen surprising progressions in later a long time. Whereas these frameworks offer different benefits in inventive assignments, amusement, and robotization, they moreover posture noteworthy security dangers. This paper looks at the security suggestions of generative AI advances, centering on potential dangers and vulnerabilities they present over diverse spaces. We talk about the abuse of generative AI for pernicious purposes, counting the creation of modern fake substance, pantomime assaults, and the spread of disinformation and purposeful publicity. Furthermore, we analyze the challenges in recognizing and moderating these dangers, given the quick advancement and complexity of generative AI models. Besides, we investigate the moral contemplations encompassing the advancement and arrangement of generative AI, emphasizing the significance of capable AI administration and direction to address security concerns. By highlighting these dangers, this paper points to raise mindfulness among analysts, policymakers, and specialists to create proactive techniques for overseeing the security challenges postured by generative AI advances.
 
AI-Empowered Malware Detection System for Iot
Full text linkThe Internet of Things (IoT) has revolutionized the way we live and work. However, the increased connectivity of IoT devices has also made them a target for malware attacks. Traditional malware detection methods are not always effective against IoT malware, as they often rely on signatures that attackers can easily circumvent. In this paper, we propose an AI-powered malware detection system for IoT. Our system uses a hybrid deep learning approach that combines convolutional neural networks (CNN) and long short-term memory networks (LSTM). CNNs are used to extract features from IoT malware binary code, and LSTM networks are used to model the temporal relationships between these features. We evaluate the system against his three datasets of publicly available IoT malware. As a result, we found that our system achieved him a high accuracy of 99.98% in detecting his IoT malware. We also show that our system is effective against zero-day IoT malware, malware that has not yet been discovered by security researchers
The Advancement of Artificial Intelligence
Full text linkArtificial Intelligence (AI) has undergone remarkable progress in recent years, revolutionizing diverse industries and aspects of human life. This article explores the rapid evolution of AI technology, discussing key breakthroughs, challenges, and the implications of its growth. The advancements in AI have been fueled by significant improvements in computing power, data availability, and algorithmic developments, enabling machines to perform complex tasks and learn from vast datasets. This article covers major areas of AI advancement, including machine learning, natural language processing, computer vision, robotics, and AI ethics. It analyzes the potential benefits and risks of AI development, showcasing how AI has achieved human-level performance in various domains, such as language understanding, image recognition, and game-playing. Additionally, the article delves into the ethical considerations arising from the proliferation of AI technologies, emphasizing the need for responsible and ethical AI implementation to ensure fairness, transparency, and user privacy. As AI's impact on society and the economy becomes increasingly pronounced, it is essential to understand the potential of AI for innovation and progress while addressing its challenges to harness its full potential for the greater good
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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