This paper aims to present a comprehensive pathway for high school students in grades nine to twelve to pursue careers in cybersecurity. In an era described by way of virtual ubiquity, the paper highlights the vital i...
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ISBN:
(数字)9798350351507
ISBN:
(纸本)9798350363067
This paper aims to present a comprehensive pathway for high school students in grades nine to twelve to pursue careers in cybersecurity. In an era described by way of virtual ubiquity, the paper highlights the vital importance of cybersecurity. It explores the demand for cybersecurity specialists, where there is a significant shortage of skilled professionals, and emphasizes the relevance of cybersecurity in safeguarding online sensitive information. The paper also explores key motivators for high school students, such as the allure of ethical hacking, the opportunity for innovative, hassle-fixing, and the promising profession prospects within the subject. There is a discussion about cybersecurity education for high school students, existing educational initiatives, and programs. This way, the paper presents an overview of various career pathways using cybersecurity career pathway tools. There is a discussion about the obstacles which high school students face on a regular basis in terms of cybersecurity, and some proposals about how to overcome those challenges.
In recent years, Field-Programmable Gate Arrays (FPGAs) are gaining attention as computational acceleration devices in the field of high-performance computing. By implementing specialized circuits that can be customiz...
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ISBN:
(数字)9798350383454
ISBN:
(纸本)9798350383461
In recent years, Field-Programmable Gate Arrays (FPGAs) are gaining attention as computational acceleration devices in the field of high-performance computing. By implementing specialized circuits that can be customized to specific problems, FPGAs can achieve efficient parallelization with low latency even for complex tasks.
Federated learning has become an emerging technology for data analysis for IoT applications. This paper implements centralized and decentralized federated learning frameworks for crop yield prediction based on Long Sh...
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Artificial Intelligence (AI), with ChatGPT as a prominent example, has recently taken center stage in various domains including higher education, particularly in computer Science and Engineering (CSE). The AI revoluti...
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ISBN:
(数字)9798350394023
ISBN:
(纸本)9798350394030
Artificial Intelligence (AI), with ChatGPT as a prominent example, has recently taken center stage in various domains including higher education, particularly in computer Science and Engineering (CSE). The AI revolution brings both convenience and controversy, offering substantial benefits while lacking formal guidance on their application. The primary objective of this work is to comprehensively analyze the pedagogical potential of ChatGPT in CSE education, understanding its strengths and limitations from the perspectives of educators and learners. We employ a systematic approach, creating a diverse range of educational practice problems within CSE field, focusing on various subjects such as data science, programming, AI, machine learning, networks, and more. According to our examinations, certain question types, like conceptual knowledge queries, typically do not pose significant challenges to ChatGPT, and thus, are excluded from our analysis. Alternatively, we focus our efforts on developing more in-depth and personalized questions and project-based tasks. These questions are presented to ChatGPT, followed by interactions to assess its effectiveness in delivering complete and meaningful responses. To this end, we propose a comprehensive five-factor reliability analysis framework to evaluate the responses. This assessment aims to identify when ChatGPT excels and when it faces challenges. Our study concludes with a correlation analysis, delving into the relationships among subjects, task types, and limiting factors. This analysis offers valuable insights to enhance ChatGPT's utility in CSE education, providing guidance to educators and students regarding its reliability and efficacy.
We propose a coarse symbol timing scheme for wireless orthogonal frequency division multiplexing (OFDM) systems using an optimal correlation-based circular-shifted preamble (CSP). Our proposed scheme is implemented by...
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We propose a coarse symbol timing scheme for wireless orthogonal frequency division multiplexing (OFDM) systems using an optimal correlation-based circular-shifted preamble (CSP). Our proposed scheme is implemented by off-line correlation-ranking and on-line processing. The on-line processing derives an optimal CSP for transmission according to the off-line correlation-ranking, and employs a delayed multiplication operation for symbol timing. The conducted simulation results show that our proposed scheme outperforms the other existing representative schemes over typical multi-path fading channels in terms of mean square error (MSE) while keeping the computational complexity low. IEEE
In the current field of object detection, the YOLOv7 model demonstrates significant advantages in terms of both detection speed and accuracy. However, the model shows deficiencies in focussing on key information, and ...
In the current field of object detection, the YOLOv7 model demonstrates significant advantages in terms of both detection speed and accuracy. However, the model shows deficiencies in focussing on key information, and its loss function's sensitivity to bounding boxes results in suboptimal performance in densely populated environments and small target detection scenarios. To address these issues, this study proposes a mask target detection method based on YOLOv7. By integrating a channel attention mechanism into the YOLOv7 model, this method enhances the model's focus on important information in images, effectively reducing interference from background factors. Additionally, the method incorporates Normalized Wasserstein Distance (NWD) into the loss function to optimize the model's evaluation of small target detection. Experimental verification shows that the improved model maintains its original detection speed while increasing the overall accuracy to 92.1%, a 2.9% improvement over the original YOLOv7 model. It achieves a 3.3% increase in the mAP.5 metric. This indicates that the optimised YOLOv7 model has superior detection capabilities, allowing it to perform mask-wearing detection tasks more rapidly and accurately in natural environments.
PurposeThe impact of AI on healthcare is widely recognized there remains a scarcity of studies examining how doctors perceive and approach its use in medicine. This study aims to gather insights from healthcare provid...
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PurposeThe impact of AI on healthcare is widely recognized there remains a scarcity of studies examining how doctors perceive and approach its use in medicine. This study aims to gather insights from healthcare providers in Jordan concerning the advantages of integrating AI into practices, their perspectives on AI applications in healthcare, and their views on the future role of AI in replacing key tasks within health *** survey was conducted among healthcare professionals working at facilities in Jordan. An online questionnaire was used to collect data on demographics, attitudes toward using AI for tasks, and opinions on the benefits of AI adoption. Categorical variables were presented as counts and percentages, while the continuous variables were interpreted as mean and standard deviation. The associations between the determinants and the outcomes were done using one-way ANOVA. Any test with a P-value 0.05 was considered *** total of 612 healthcare professionals participated in the survey with females comprising a majority of respondents (52.8%). The majority of respondents showed optimism about AI’s potential to improve and revolutionize the field, although there were concerns about AI replacing human roles. Generally, physical therapists, medical researchers, and pharmacists displayed openness to incorporating AI into their work routines. Younger individuals aged between 18 and 40 seemed accepting of AI in the domain. A significant portion of participants believed that AI could negatively impact job opportunities and reduce the time needed for diagnosing conditions, but did not find any correlation, between responses and *** conclude, the results of this study suggest that healthcare professionals, in Jordan, hold receptive views on incorporating artificial intelligence in the medical field similar to their counterparts in developed nations. However, there is a concern about the implications of AI, on job stability a
Mostly Drugstores do not have any system that exclusively connect to access E-commerce system because the marketing concept of drugstores still use conventional store to sell their products. According to this situatio...
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Prior research on AI-assisted human decision-making has explored several different explainable AI (XAI) approaches. A recent paper has proposed a paradigm shift calling for hypothesis-driven XAI through a conceptual f...
This paper introduces a physically-intuitive notion of inter-area dynamics in systems comprising multiple interconnected energy conversion modules. The idea builds on an earlier general approach of setting their struc...
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ISBN:
(数字)9798350373974
ISBN:
(纸本)9798350373981
This paper introduces a physically-intuitive notion of inter-area dynamics in systems comprising multiple interconnected energy conversion modules. The idea builds on an earlier general approach of setting their structural properties by modeling internal dynamics in stand-alone modules (components, areas) using the fundamental conservation laws between energy stored and generated, and then constraining explicitly their Tellegen’s quantities (power and rate of change of power). In this paper we derive, by following the same principles, a transformed state-space model for a general nonlinear system. Using this model we show the existence of an area-level interaction variable, intVar, whose rate of change depends solely on the area internal power imbalance and is independent of the model complexity used for representing individual module dynamics in the area. Given these structural properties of stand-alone modules, we define in this paper for the first time an inter-area variable as the difference of power wave incident to tie-line from Area I and the power reflected into tie-lie from Area II. Notably, these power waves represent the interaction variables associated with the two respective interconnected areas. We illustrate these notions using a linearized case of two lossless inter-connected areas, and show the existence of a new inter-area mode when the areas get connected. We suggest that lessons learned in this paper open possibilities for computationally-efficient modeling and control of inter-area oscillations, and offer further the basis for modeling and control of dynamics in changing systems comprising faster energy conversion processes.
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