1,720,957 research outputs found
The disruptive nature of AI-Powered technologies: balancing the dichotomy of dependence and autonomy for IT Professionals
Get PDFThis paper critically examined the impact of over-dependence on Artificial Intelligence (AI) by Information Technology (IT) Professionals, exploring the impact on cognitive functions such as critical thinking, decision-making, and problem-solving, and how these affect the autonomy of IT Professionals. Using quantitative research methodology, the study surveyed 180 IT Professionals to gauge their usage of and dependence on AI-powered tools, as well as their perceptions about AI technologies and the effects these might have on their cognitive abilities. The findings showed a very significant integration of AI by the respondents in both their personal and professional capacities, as well as a substantial dependence on AI-powered tools, particularly for decision-making purposes. Furthermore, there appeared to be a possible underestimation of the effects that AI usage has on cognitive abilities, as expressed through the paradoxical survey results. Moreover, several ethical issues were identified such as bias, privacy and the lagging behind of laws and regulations, further serving to complicate the effects of over-dependence on AI. Based on its findings this paper makes recommendations for the development of clear guidelines for the use of AI, continuous learning and development programs, focusing on AI advancements and risks, as well as the implementation of frequent impact and security assessments. These recommendations aim to assist organisations and IT Professionals to benefit from the advantages of AI while maintaining critical skills, human oversight and intuition
Anti-intrusion strategy MANET inspired by the bacterial foraging optimization algorithm
Get PDFMobile ad hoc networks (MANET) are reflexivity, fast, versatile wireless networks that are particularly useful when traditional radio infrastructure is unavailable, such as during outdoor events, natural disasters, and military operations. Security may be the weakest link in a network due to its dynamic topology, which leaves it susceptible to eavesdropping, rerouting, and application modifications. More security problems with MANET exist than with its service Quality of Service (QoS). Therefore, intrusion detection, which controls the system to find further security issues, is strongly suggested. Keeping an eye out for intrusions is essential to forestall future attacks and beef up security. If a mobile node loses its power supply, it may be unable to continue forwarding packets, which depends on the structure\u27s condition. The proposed study presents a security of trust and optimization that conserves energy methods for MANETs based on integrating the K means algorithm and Bacteria Foraging Optimization Algorithm (KBFOA). This work proposes a method for quickly and accurately determining which nodes should serve as Cluster Heads (CHs) by K means algorithm. This approach aims to choose a node with a high Sustainable Cell (SC) rate as the Header of a Cluster (HC). Each node will calculate its SC according to its unique factors, such as energy consumption, degree, remaining energy, mobility, and distance from the HC and base stations. The security of MANETs is improved by the inclusion of an algorithm in the proposed approach that detects and eliminates rogue nodes. This suggested approach will increase network stability and performance using a high-sustainable cluster head. The proposed approach will be achieved the highest reliability of clustering rate of 97%. The intended research will be accomplished Maximum security measures rate will be accomplished by 96%, the maximum rate of data transmission will be obtained of 96%, and greater efficient detection of malicious nodes ratio will be enhanced by 95%, lower energy consumption rate will be achieved by 0.09 m joules
Nanorobots target search strategies using swarm intelligence
Get PDFControlling a swarm of bee-like nanorobots in search of a target in a human body-like environment is a challenge. The challenge lies in the causal factors of emergence. This research focused on designing and developing a bee-inspired algorithm to provide instructions to coordinate simple and naïve nanorobots in search of a target. Experiments were conducted through simulations to determine the rate at which myriads of agents converge at a target. A maze environment depicting human blood vessels was used to deploy the nanorobots. Different sample population sizes were used, and the results indicate that the bigger the sample size, the higher the convergence speed. Compared with a single complicated robot, the swarm of intelligently controlled nanorobots proved efficient and effective in finding a target in a human-like environment
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Modelling intrusion detection systems using swarm intelligence
Get PDFConventional intrusion detection systems encounter difficulties in addressing advanced cyber threats and handling the increasing volume of network data. This research presents a modernisation strategy by integrating swarm intelligence algorithms to enhance the efficiency and efficacy of intrusion detection. This research employs qualitative observational and content analysis methodologies to investigate the utilisation of swarm intelligence in improving intrusion detection systems. Findings demonstrate substantial enhancements in detection rates and system efficacy, with swarm intelligence algorithms attaining a true positive detection rate of over 99% and minimising false positives to as low as 2%. These findings highlight the impending substitution of conventional intrusion detection systems with swarm intelligence-based alternatives, offering significant enhancement in cybersecurity capabilities
Variations on the Author
Get PDF“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
Get PDFWe 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
Get PDFWe 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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