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An International Examination of Non-Technical Skills and Professional Dispositions in Computing - Identifying the Present Day Academia-Industry Gap 2024

An International Examination of Non-Technical Skills and Pro...

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29th Working Group Reports on Innovation and Technology in computer science Education, ITiCSE WGR 2024

作者： Garcia, Rita Csizmadia, Andrew Pearce, Janice L. Alshaigy, Bedour Glebova, Olga Harrington, Brian Liaskos, Konstantinos Lunn, Stephanie J. Mackellar, Bonnie Nasir, Usman Pettit, Raymond Schulz, Sandra Stewart, Craig Zavaleta Bernuy, Angela School of Engineering and Computer Science Victoria University of Wellington Wellington New Zealand Newman University Birmingham United Kingdom Berea College BereaKY United States Department of Information Technology Uppsala University Uppsala Sweden University of Connecticut StorrsCT United States Computer and Mathematical Sciences University of Toronto Scarborough Toronto Canada University of Strathclyde United Kingdom SUCCEED Florida International University MiamiFL United States Computer Science Mathematics and Sciency St John's University Queens United States Blekinge Institute of Technology Karlskrona Sweden University of Virginia CharlottesvilleVA United States Faculty of Education University of Hamburg Hamburg Germany Durham University Durham United Kingdom University of Toronto Toronto Canada

ISBN: (纸本)9798400712081

Computing graduates are frequently reported by members of industry to lack in professional dispositions and/or non-technical skills (often referred to as "soft skills"). In this work, we conduct a gap analysis of the alignment between academic preparation and industry expectations through a three-pronged study. First, a literature review explored the academic perspective of how fostering professional dispositions and non-technical skills occurs in tertiary computing education. Second, a literature review identifying industry's expectations of those dispositions and skills for entry-level computing professionals. Finally, a mixed-methods approach, combining a survey and structured interviews of computing industry professionals to identify their opinions on the relative importance of those skills and dispositions. In each of these prongs, we additionally consider whether and how Diversity, Equity, Inclusion, and Accessibility (DEIA) may have been approached and/or incorporated. Our work uncovers a number of gaps. Several skills and dispositions, such as leadership, ethics, and inventiveness, are over-represented in the academic literature compared to industry's expectations, while others such as lifelong learning and professionalism are under-emphasised. Furthermore, some terms such as 'ethics' and 'professionalism' are defined differently by various stakeholder groups, leading to a gap between academic training and industry expectations. Finally, several skills and dispositions, such as collaboration, teamwork, communication, and leadership show evidence of exposure in academia, but require more scaffolded instruction to meet industry expectations. We also found a dearth of coverage in the literature and a lack of focus in industry for DEIA considerations. © 2025 ACM.

关键词： DEIA

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Frequency Analysis with Multiple Kernels and Complete Dictionary

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arXiv 2023年

作者： Lin, Cuiyun Qian, Tao Faculty of Innovation Engineering School of Computer Science and Engineering Macau University of Science and Technology Taipa999078 China Macau Center for Mathematical Sciences Macau University of Science and Technology Taipa999078 China

In signal analysis, among the effort of seeking for efficient representations of a signal into the basic ones of meaningful frequencies, to extract principal frequency components, consecutively one after another or n at one time, is a fundamental strategy. For this goal, we define the concept of mean-frequency and develop the related frequency decomposition with the complete Szegö kernel dictionary, the latter consisting of the multiple kernels, being defined as the parameter-derivatives of the Szegö kernels. Several major energy matching pursuit type sparse representations, including greedy algorithm (GA), orthogonal greedy algorithm (OGA), adaptive Fourier decomposition (AFD), pre-orthogonal adaptive Fourier decomposition (POAFD), n-Best approximation and unwinding Blaschke expansion, are analyzed and compared. Of which an order in re-construction efficiency between the mentioned algorithms is given based on detailed study of their respective remainders. The study spells out the natural connections between the multiple kernels and the related Laguerre system, and in particular shows that both, like the Fourier series, extract out the O(n−σ) order convergence rate from the functions in the Hardy-Sobolev space of order σ > 0. Existence of the n-Best approximation with the complete Szegö dictionary is proved and the related algorithm aspects are discussed. The included experiments form a significant integration part of the study, for they not only illustrate the theoretical results, but also provide cross comparison between various ways of combination between the matching pursuit algorithms and the dictionaries in use. Experiments show that the complete dictionary remarkably improves approximation efficiency. Copyright © 2023, The Authors. All rights reserved.

关键词： Expansion

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Assessing Cybersecurity Awareness among the Hashemite University Students in Terms of computer Usage 16

Assessing Cybersecurity Awareness among the Hashemite Univer...

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16th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2024

作者： Aljammal, Ashraf H. Qawasmeh, Ahmad Taamneh, Salah Wedyan, Fadi Obiedat, Mamoon Salameh, Hani Bani The Hashemite University Prince Al Hussein Bin Abdullah Ii Faculty of Information Technology Department of Computer Science and Applications Zarqa Jordan Lewis University Department of Engineering Computing and Mathematical Sciences RomeovilleIL United States The Hashemite University Prince Al Hussein Bin Abdullah Ii Faculty of Information Technology Department of Information Technology Zarqa Jordan The Hashemite University Prince Al Hussein Bin Abdullah Ii Faculty of Information Technology Department of Software Engineering Zarqa Jordan

ISBN: (纸本)9798350371154

Internet usage among information technology users has expanded substantially, as have cybercrimes with potentially disastrous repercussions. Therefore, internet users have to employ the available security measures and policies during internet usage. Nowadays, University students make up a sizable portion of internet users. This study assesses the cybersecurity awareness among The Hashemite University students In terms of computer Usage. A questionnaire survey is used to assess students' cybersecurity knowledge while using their PCs and connecting to the internet, concentrating on their behaviors and use of security measures. © 2024 IEEE.

关键词： Cybersecurity

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Vietoris thickenings and complexes have isomorphic homotopy groups

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Journal of Applied and Computational Topology 2023年第2期7卷 221-241页

作者： Adams, Henry Frick, Florian Virk, Žiga Department of Mathematics Colorado State University Fort Collins 80523 CO United States Department of Mathematical Sciences Carnegie Mellon University Pittsburgh 15213 PA United States Institute of Mathematics Freie Universität Berlin Arnimallee 2 Berlin 14195 Germany Faculty of Computer and Information Science University of Ljubljana Večna pot 113 Ljubljana 1000 Slovenia

We study the relationship between metric thickenings and simplicial complexes associated to coverings of metric spaces. Let U be a cover of a separable metric space X by open sets with a uniform diameter bound. The Vietoris complex V(U) contains all simplices with vertex set contained in some U∈ U, and the Vietoris metric thickening V^m(U) is the space of probability measures with support in some U∈ U, equipped with an optimal transport metric. We show that V^m(U) and V(U) have isomorphic homotopy groups in all dimensions. In particular, by choosing the cover U appropriately, we get isomorphisms between the homotopy groups of Vietoris–Rips metric thickenings and simplicial complexes π_k(VR ^m(X;r)) ≅ π_k(VR (X;r)) for all integers k≥ 0 , where both spaces are defined using the convention “diameter < r” (instead of ≤ r). Similarly, we get isomorphisms between the homotopy groups of Čech metric thickenings and simplicial complexes π_k(C ˇ ^m(X;r)) ≅ π_k(C ˇ (X;r)) for all integers k≥ 0 , where both spaces are defined using open balls (instead of closed balls). © 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Homotopy groups Metric thickenings Nerve lemmas Optimal transport Vietoris–Rips complexes Čech complexes

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The new soliton solutions for long and short-wave interaction system

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Journal of Ocean Engineering and science 2022年第5期7卷 485-491页

作者： Sayyed Masood Zekavatmand Hadi Rezazadeh Mustafa Inc Javad Vahidi Mohammad Bagher Ghaemi Department of Applied Mathematics Iran University of Science and TechnologyTehranIran Faculty of Engineering Technology Amol University of Special Modern TechnologiesAmolIran Department of Computer Engineering Biruni UniversityIstanbulTurkey Firat University Science FacultyDepartment of MathematicsElazig 23119 Turkey Department of Medical Research China Medical University HospitalChina Medical UniversityTaichungTaiwan Department of Mathematical Sciences University of South AfricaPretoria 0002South Africa

The goal of this paper is to discover modern soliton solutions to long and short-wave interaction system by procedures called extended rational sine-cosine and rational sinh-cosh *** assume that the equation has a hypothetical soliton *** reorganizing the resulting equations,we obtain a system of *** Maple software,we get unknown coefficients in the system and writing them in the original equation,we obtain new solition solutions of the *** results show that the soliton solutions generated by the method for the long and short-wave interaction system are bright,kink type,bright periodic and dark *** provided 3-D figures to illustrate the *** results indicate that the method employed in this paper is superior than some other methods used in the literature to solve the same system equations.

关键词： Extended rational sine-cosine method Extended rational sinh-cosh method

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Optimal Transport Guided Node Classification in Cross Networks 9th

Optimal Transport Guided Node Classification in Cross Networ...

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9th International Conference on Information Technology and Quantitative Management, ITQM 2022

作者： Zheng, Lei Quan, Pei Lei, Minglong Xiao, Yang Niu, Lingfeng School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100190 China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing100190 China Faculty of Information Technology Beijing University of Technology Beijing100124 China School of Economics and Management University of Chinese Academy of Sciences Beijing100190 China

Inspired by the huge powerful representation ability of graph neural networks (GNNs), GNNs begin to solve node classification in cross networks. However, current GNNs are designed for single graph, and overlook the distribution shift in cross network which degrades the performance on test nodes. In this paper, we firstly analyze deep cross-network embeddings based on GNNs and illustrate that in cross-network node classification training and test embedding spaces have different distributions. According to domain adaptation and our analysis, we propose a novel framework and loss function, which introduces optimal transport to GNNs and generates transferable embeddings. Extensive experiments in citation networks verify the effectiveness of our method OT-DCNE. © 2022 The Author(s).

关键词： Graph neural networks

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Discrepancy and Thematic Bibliometric Analyses of the Remaining Limitations in Artificial Intelligence

Discrepancy and Thematic Bibliometric Analyses of the Remain...

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Computing (ICOCO), IEEE International Conference on

作者： Mahayaudin M. Mansor Nurain Ibrahim Noor Fadhilah Ahmad Radi Nadirah Abdul Rahim Syarul Heiry Yahaya Mohd Aftar Abu Bakar Roslinazairimah Zakaria School of Mathematical Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Malaysia Institute of Big Data Analytics and Artificial Intelligence Universiti Teknologi MARA Malaysia Department of Electrical and Computer Engineering Kuliyyah of Engineering International Islamic University Malaysia Department of Science Computer and Mathematics Universiti Teknologi MARA (Penang Campus) Malaysia Department of Mathematical Sciences Faculty of Science & Technology Universiti Kebangsaan Malaysia Centre for Mathematical Sciences Universiti Malaysia Pahang Al-Sultan Abdullah Malaysia

ISBN: (数字)9798331530303

ISBN: (纸本)9798331530310

As artificial intelligence (AI) advances, it is essential to continuously comprehend its limitations to optimise the integration of AI into autonomous systems that empower humans. The first objective of this study is to highlight the key capabilities of both humans and AI, focusing on the differences and identifying limitations of AI from the literature. Through discrepancy analysis, this study uses a Venn diagram to visualise the remaining limitations of AI into five key domains: (i) emotional intelligence, (ii) consciousness and awareness, (iii) creative imagination, (iv) communication, and (v) ethical decision-making. Furthermore, this study employs thematic bibliometric analysis to provide a more detailed examination of each AI limitation as the second objective. This study has identified underdeveloped and emerging research themes with potential for future development, such as emotion recognition, human-computer interaction, digital health, and situational awareness, which may require further research. Additionally, this study commends the ongoing efforts to harness AI’s computational power and algorithmic innovations to enhance AI’s overall performance and applicability.

关键词： Visualization Technological innovation Ethics Emotion recognition Bibliometrics Decision making Focusing Electronic healthcare Object recognition Artificial intelligence

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Deep learning for brain age estimation: A systematic review

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Information Fusion 2023年 96卷 130-143页

作者： Tanveer, M. Ganaie, M.A. Beheshti, Iman Goel, Tripti Ahmad, Nehal Lai, Kuan-Ting Huang, Kaizhu Zhang, Yu-Dong Del Ser, Javier Lin, Chin-Teng Department of Mathematics Indian Institute of Technology Indore Simrol Indore453552 India Department of Robotics University of Michigan Ann ArborMI48109 United States Department of Human Anatomy and Cell Science Rady Faculty of Health Sciences Max Rady College of Medicine University of Manitoba WinnipegMB Canada Biomedical Imaging Lab National Institute of Technology Silchar Assam 788010 India Department of Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan Department of Electronic Engineering National Taipei University of Technology Taipei Taiwan Data Science Research Center Duke Kunshan University China School of Computing and Mathematical Sciences University of Leicester LeicesterLE1 7RH United Kingdom Derio48160 Spain Bilbao48013 Spain School of Computer Science Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia

Over the years, Machine Learning models have been successfully employed on neuroimaging data for accurately predicting brain age. Deviations from the healthy brain aging pattern are associated with the accelerated brain aging and brain abnormalities. Hence, efficient and accurate diagnosis techniques are required to elicit accurate brain age estimations. Several contributions have been reported in the past for this purpose, resorting to different data-driven modeling methods. Recently, deep neural networks (also referred to as deep learning) have become prevalent in manifold neuroimaging studies, including brain age estimation. In this review, we offer a comprehensive analysis of the literature related to the adoption of deep learning for brain age estimation with neuroimaging data. We detail and analyze different deep learning architectures used for this application, pausing at research works published to date quantitatively exploring their application. We also examine different brain age estimation frameworks, comparatively exposing their advantages and weaknesses. Finally, the review concludes with an outlook towards future directions that should be followed by prospective studies. The ultimate goal of this paper is to establish a common and informed reference for newcomers and experienced researchers willing to approach brain age estimation by using deep learning models. © 2023 Elsevier B.V.

关键词： Deep neural networks

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Ensemble-based Cyber Intrusion Detection for Robust Smart City Protection

Ensemble-based Cyber Intrusion Detection for Robust Smart Ci...

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International Conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Alaa Alhowaide Izzat Alsmadi Belal Alsinglawi Computer Science Faculty of Science Memorial University of Newfoundland Canada Computing Engineering and Mathematical Sciences Texas A&M San Antonio San Antonio USA Computational Systems Zayed University Abu Dhabi United Arab Emirates

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

The rapid rise of 5G networks has accelerated the integration of smart cities, marking the emergence of increased intelligence in urban environments, often referred to as Smart Cities. This swift integration has interconnected a wide range of devices and systems, thereby exposing them to potential vulnerabilities. As a result, a smart urban landscape has emerged where valuable and sensitive information is shared without adequate attention to security considerations. Given these challenges, it is essential to implement an effective cloud-based Intrusion Detection System (IDS) for the security of smart cities. This work examines the reliability and robustness of various ensemble learning models, focusing on evaluating the performance and efficiency of an IDS strategy based on machine learning to enhance the security of IoT in smart urban networks. We conducted experimental procedures on three commonly used datasets to achieve the objectives of our study. The results obtained from these procedures are crucial for developing practical IDS solutions that address the ever-changing challenges posed by diverse, smart, cloud-based network traffic systems in smart cities.

关键词： Measurement Cloud computing Smart cities Biological system modeling Intrusion detection Focusing Robustness

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Thunderstorm Nowcasting with Recurrent-Convolution Deep Learning: A Case Study in Ho Chi Minh City 18

Thunderstorm Nowcasting with Recurrent-Convolution Deep Lear...

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18th International Conference on Advanced Computing and Analytics, ACOMPA 2024

作者： Khang, Ta Gia Van Gia Thinh, Nguyen Van Hoai, Tran An, Phan Thanh Huu, Pham Thanh An, Nguyen Minh Bao Ho Chi Minh City University of Technology IVS Joint Stock Company Falculty of Computer Science and Engineering Ho Chi Minh City Viet Nam Ho Chi Minh City University of Technology Institute of Mathematical and Computational Sciences Ho Chi Minh City Viet Nam Ho Chi Minh City University of Technology Faculty of Computer Science and Engineering Ho Chi Minh City Viet Nam Ho Chi Minh City University of Technology IVS Joint Stock Company Falculty of Applied Science Ho Chi Minh City ADAI LAB Nha Trang City Viet Nam

ISBN: (纸本)9798331542467

Machine learning for precipitation nowcasting using radar reflectivity images is a promising approach in weather forecasting. This paper proposes a new pipeline of using Convolutional Neural Networks (CNNs) integrated with Gated Recurrent Units (LSTM) and visual Attention mechanisms for quantitative precipitation nowcasting (QPN) using radar reflectivity images. We propose an end-to-end nowcasting network that leverages a Convolutional-LSTM with Axial Attention as the backbone to develop an adaptive forecasting system. Our results demonstrate the potential of deep learning techniques to significantly improve short-term weather predictions. The models were trained and validated using real-world Doppler radar data from Nha Be, Ho Chi Minh City, ensuring both practical relevance and applicability. Experimental results highlight that the combination of 3D Convolution, Convolutional-LSTM, and Axial Attention achieves superior performance, underscoring the effectiveness of this approach. © 2024 IEEE.

关键词： Weather forecasting

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