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检索条件"任意字段=International Conference on Learning and Teaching in Computing and Engineering"

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A Foundation Programme Preparing Students for Future Study in computing and engineering Degrees 4

A Foundation Programme Preparing Students for Future Study i...

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4th international conference on learning and teaching in computing and engineering (LaTICE)

作者： Spooner, Kerri Clear, Tony Auckland Univ Technol Sch Engn Comp & Math Sci Auckland New Zealand

ISBN: (纸本)9781509025046

This paper presents the Certificate of Science and Technology (CertScT) a pre-degree programme at Auckland University of Technology in New Zealand, developed with the aim of preparing students to undertake degree level study in Science, Technology, engineering and Mathematics (STEM) subjects. The history, context and rationale for the programme is outlined together with its structure and content, and pedagogical and programme level strategies that have been adopted to encourage student success. The authors reflect on the success of the programme to date in achieving its aims, based upon observation, reflections and data from internal evaluations of the programme. The paper notes the challenges for the programme posed by external metrics which the New Zealand Government has adopted. The paper concludes with a commentary on the success of the programme in achieving its goals, and the risks to its continuation.

关键词： computing Education engineering Education STEM Education Certificate Degree Access Equity

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Comparative Analysis of nnUNet and MedNeXt for Head and Neck Tumor Segmentation in MRI-Guided Radiotherapy 1st

Comparative Analysis of nnUNet and MedNeXt for Head and Neck...

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1st Challenge on Head and Neck Tumor Segmentation for MRI-Guided Applications, HNTS-MRG 2024, Held in Conjunction with 27th international conference on Medical Image computing and Computer-Assisted Intervention, MICCAI 2024

作者： Moradi, Nikoo Ferreira, Andre Puladi, Behrus Kleesiek, Jens Fatemizadeh, Emad Luijten, Gijs Alves, Victor Egger, Jan Department of Electrical Engineering Sharif University of Technology Tehran Iran University Medicine Essen Girardetstraße 2 Essen45131 Germany Center Algoritmi/LASI University of Minho Braga4710-057 Portugal Computer Algorithms for Medicine Laboratory Graz Austria Department of Oral and Maxillofacial Surgery University Hospital RWTH Aachen Aachen Germany Institute of Medical Informatics University Hospital RWTH Aachen Aachen Germany Essen Germany Partner Site Essen Essen Germany Department of Physics TU Dortmund University Dortmund Germany University Medicine Essen Essen Germany Graz University of Technology Inffeldgasse 16/II Graz8010 Austria

ISBN: (纸本)9783031832734

Radiation therapy (RT) is essential in treating head and neck cancer (HNC), with magnetic resonance imaging(MRI)-guided RT offering superior soft tissue contrast and functional imaging. However, manual tumor segmentation is time-consuming and complex, and there- fore remains a challenge. In this study, we present our solution as team TUMOR to the HNTS-MRG24 MICCAI Challenge which is focused on automated segmentation of primary gross tumor volumes (GTVp) and metastatic lymph node gross tumor volume (GTVn) in pre-RT and mid- RT MRI images. We utilized the HNTS-MRG2024 dataset, which con- sists of 150 MRI scans from patients diagnosed with HNC, including original and registered pre-RT and mid-RT T2-weighted images with corresponding segmentation masks for GTVp and GTVn. We employed two state-of-the-art models in deep learning, nnUNet and MedNeXt. For Task 1, we pretrained models on pre-RT registered and mid-RT images, followed by fine-tuning on original pre-RT images. For Task 2, we com- bined registered pre-RT images, registered pre-RT segmentation masks, and mid-RT data as a multi-channel input for training. Our solution for Task 1 achieved 1st place in the final test phase with an aggregated Dice Similarity Coefficient of 0.8254, and our solution for Task 2 ranked 8th with a score of 0.7005. The proposed solution is publicly available at Github Repository. © The Author(s) 2025.

关键词： Image segmentation

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Assuring the Quality of engineering Education 3

Assuring the Quality of Engineering Education

引用

international conference on learning and teaching in computing and engineering

作者： Pears, Arnold Uppsala Univ Dept Informat Technol Box 325 S-75105 Uppsala Sweden

ISBN: (纸本)9781479999675

Only the foolhardy would question the importance and status that quality assurance holds in the current political climate that prevails for higher education. This paper critiques the culture of higher education quality assurance and accreditation that has emerged over the last twenty years. An underlying trend that influences quality systems for higher education is the focus on process and service. This results in quality systems that focus on documenting educational processes, and which often assume that students are a type of customer, and education a type of service. This paper argues that this educational epistemology oversimplifies the nature and role of higher education. We argue that a more holistic quality evaluation model is needed, including often overlooked aspects of quality such as curriculum, pedagogical aspects of instructional design combined with industrial and educational quality assurance processes that can better meet the needs of practitioners and institutions.

关键词： How computer works binary concept teaching case-based instruction higher education engineering education Case Method (teaching Technique) Quality assurance Instructional Design Education quality system Accreditation Quality management institutions

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PreZ-DGGAN: A Drug Graph GAN Based on Pre-learning of Implicit Variables 2nd

PreZ-DGGAN: A Drug Graph GAN Based on Pre-Learning of Implic...

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2nd international conference on Applied Intelligence, ICAI 2024

作者： Liu, Yixin Fan, Yueqin Li, Zhipeng Zhang, Qinhu Big Data and Intelligent Computing Research Center Guangxi Academy of Science Nanning530007 China School of Mechanical Engineering Guangxi University Nanning530004 China Ningbo Institute of Digital Twin Eastern Institute of Technology Ningbo315201 China Institute for Regenerative Medicine Medical Innovation Center and State Key Laboratory of Cardiology School of Medicine Shanghai East Hospital Tongji University Shanghai200123 China College of Advanced Agricultural Sciences Zhejiang Agriculture and Forestry University Hangzhou311300 China

ISBN: (纸本)9789819619061

In the field of drug discovery and development, deep learning techniques have become a powerful tool to accelerate the discovery and development of new drugs. In the design and optimization of lead molecules, generative adversarial network and graph neural network are one of the prime techniques for accelerating research and development, because the former is based on the idea of two-player game to learn drug features to generate effective molecules, while the unstructured inputs of the latter are well-suited for the analysis of molecular data. Therefore, this study develops a new graph generative adversarial model, called PreZ-DGGAN, by inserting the graph neural network layer into the generative adversarial network. Within PreZ-DGGAN, the latent variable input of the generator is pre-learned by an improved graph variational autoencoder, which effectively avoids the mode collapse of the generative adversarial network, whereas the hidden layer of the discriminator is graph neural network layer, which is able to better learn the real molecules and judge the generated molecules as true or false. Experiments on two molecule datasets show that the molecules generated by PreZ-DGGAN have higher validity (100% on average) and uniqueness (91.5% on average), and the generated molecules are more diverse in structure. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Generative adversarial networks

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Study of a pedagogy adopted to generate interest in students taking a programming course 4

Study of a pedagogy adopted to generate interest in students...

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4th international conference on learning and teaching in computing and engineering (LaTICE)

作者： Venugopal-Wairagade, Gayatri Symbiosis Int Univ SICSR Pune Maharashtra India

ISBN: (纸本)9781509025046

With mobile application development becoming one of the most sought-after choices by computer science students, developers and companies, an instructor teaching a course on the same to a batch of beginners should ensure that the best possible teaching-learning methodologies are adopted to generate interest among students in the classroom. The author used a blended approach consisting of traditional, e-learning and m-learning strategies. These in turn, consisted of various teaching and evaluation methods. Through this paper, the author discusses the impact of the methods adopted as part of the experiment, on the interest of the students and their respective performance. The sample consisted of 22 postgraduate computer science students. Their responses to the instruments administered, their scores and their LMS access logs were analyzed. The author was able to achieve statistically significant results with respect to the students' interest and their performance, for mainly two strategies - integration of LMS, and teaching the topics by developing an application in multiple phases throughout the duration of the course. It was found that with regards to project work, continuous interaction with the instructor was a desired and accepted approach by the students. The study also revealed the misconceptions that an instructor may have when teaching a programming language or when using mobile devices for teaching. The results of this study may be used by instructors teaching any programming language in higher education.

关键词： blended learning e-learning m-learning

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Automated Detection of COVID-19 Using Deep Convolutional Neural Network (CNNs) Using Chest Radiograph and CT Scan Images 1st

Automated Detection of COVID-19 Using Deep Convolutional Neu...

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1st international conference on computing and Emerging Technologies, ICCET 2023

作者： Uallah, Naeem Khan, Javed Ali Raza, Asaf Shah, Syed Yaqub Assam, Muhammad Arshad, Hasna Department of Software Engineering University of Engineering and Technology Taxila Taxila Pakistan Department of Software Engineering University of Science and Technology Bannu Bannu Pakistan Department of Computer Science HITEC University Taxila Pakistan

ISBN: (纸本)9783031776199

Many countries are severely affected by COVID-19, and massive efforts are required to mitigate the terrible impacts of the COVID-19 global epidemic. To stop COVID-19 from spreading widely and minimize COVID-19 patient treatment issues, early discovery of the virus in its early stages is essential. Conventional methods for COVID-19 detection are time-consuming, cumbersome, unreliable, and yield an incorrect diagnosis. Most deep learning (DL) methods for COVID-19 identification described in the past only support one data type (chest radiographs or CT scan images). Examining unusual patterns in various data types may yield high classification performance. For this purpose, we use two image datasets: chest radiographs and chest computer tomography (CT). This research study proposed an excellent COVID-19 detection strategy based on the Resnet-18 deep convolutional neural network (CNN) to timely and efficiently identify COVID-19 spread. Also, we used each image data type to conduct extensive Covid-19 detection experiments with the proposed DL model. We performed a trinary classification task (normal, covid-19, and pneumonia) using chest radiographs and a binary classification (COVID-19 and Normal) using CT scan images. We validated the performance of the proposed approach on two standard Kaggle datasets, i.e., the COVID-19 Radiography Database and the SARS-CoV-2 CT scan dataset. The Resnet model's detection accuracy of 99.42% using chest radiographs (CRs) and 100% using CT scans for COVID-19 detection indicates its efficacy in detecting COVID-19. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： COVID-19

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Design and implementation of MobileEdu m-learning application for computing education in Nigeria: A design research approach 4

Design and implementation of MobileEdu m-learning applicatio...

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4th international conference on learning and teaching in computing and engineering (LaTICE)

作者： Oyelere, Solomon Sunday Suhonen, Jarkko Univ Eastern Finland Sch Comp Joensuu Finland

ISBN: (纸本)9781509025046

The convergence of Wi-Fi technologies and mobile devices present prospects to design and implement applications that will support learning on the move. Mobile learning (m-learning) is the study and practice of using mobile devices, such as smart phones, mobile phones, tablets, PDAs, MP3s and pocket PCs to support learning for anyone, anytime and anywhere. Through well-situated and flexible mobile devices and network infrastructure, researchers and developers endeavor to offer users with new learning applications and services. We have applied the design research (DR) approach in the course of developing m-learning application, MobileEdu, for computing education in Nigerian higher education context. The application is intended to facilitate the learning of computer science courses on mobile devices, support ubiquitous, collaborative, and social learning for undergraduate students. Moreover, the application eases access to learning resources. In this article we present the analysis, design and implementation activities related to the development of the first MobileEdu prototype. The research also deliberated on the characteristics and scope of the adherence of MobileEdu to the traits and ideas of DR.

关键词： M-learning Mobile learning Mobile devices Design research Design science Design-based research Artifact Mobile application Apps teaching learning MobileEdu Android App Nigeria Higher education computing education Blended learning Computer science education

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Innovative Pedagogical Practices in the Craft of computing 4

Innovative Pedagogical Practices in the Craft of Computing

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4th international conference on learning and teaching in computing and engineering (LaTICE)

作者： Davenport, James H. Hayes, Alan Hourizi, Rachid Crick, Tom Univ Bath Dept Comp Sci Bath BA2 7AY Avon England Cardiff Metropolitan Univ Dept Comp & Informat Syst Cardiff CF5 2YB S Glam Wales

ISBN: (纸本)9781509025046

teaching programming is much more like teaching a craft skill than it is a purely theoretical subject. Hence an "apprenticeship" model, where apprentices learn by watching the master do, and then do themselves, and are criticised in their doing, is, we claim, more appropriate than the "lecturer/lecturee" model that universities implicitly adopt. Furthermore, there are generally many more apprentices than the master can personally supervise. Universities will therefore use various tutors, who should be regarded as the analogue of the guild-master's journeymen. However, how does one encourage this mindset in students who, for their other courses, are indeed lecturees? What are the implications for the journeymen?

关键词： Apprentices

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A Hybrid Approach to Cardiovascular Disease Detection: The Synergy of YOLOv9, CapsNet, and XGBoost 3rd

A Hybrid Approach to Cardiovascular Disease Detection: The S...

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3rd international conference on Advancements in Smart computing and Information Security, ASCIS 2024

作者： Srinivasa Rao, Gorapalli Muneeswari, G. School of Computer Science and Engineering VIT-AP University Andhrapradesh Amaravathi India

ISBN: (纸本)9783031862953

Cardiovascular Stroke is a potentially fatal condition that requires careful attention to achieve the best results. Early detection and intervention are crucial to reduce mortality and long-term damage associated with stroke. This study provides new solutions to these urgent needs by offering instant stroke detection based on deep learning and machine learning to increase performance. The most important goal of this research is to create a reliable and accurate system that can instantly distinguish strokes, allowing doctors to make informed decisions. Traditional stroke diagnosis technology relies on the interpretation of medical images, which is laborious and prone to human error. Although ML and DL approaches have demonstrated potential for automating this procedure, difficulties still exist since large and varied datasets are required. In order to overcome these obstacles, we suggest YOLOv9 + Capsnet in conjunction with XG-BOOST algorithms on large-scale datasets that include stroke and non-stroke cases according to the cardiovascular disease of the subjects seen in the pictures. Through this process of training, the model gains the ability to recognise complex patterns and features related to strokes, which improves the accuracy of its diagnosis. With the ability to increase patient caring and diagnosis of strokes, this optimised model has great promise for saving lives and raising the standard of healthcare. This article aims to identify the most effective and practical machine learning and deep learning algorithms for the prediction of cardiac illnesses by summarising some of the recent research in this area. Prediction systems’ future directions have also been taken into account. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Electrotherapeutics

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Usability Impact of Conversational Chatbot 1st

Usability Impact of Conversational Chatbot

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1st international conference on computing and Emerging Technologies, ICCET 2023

作者： Rasheed, Maryam Iqbal, Muhammad Waseem Fatima, Anam Saleem, Maryam Bhatti, Sohail Masood Ahsan, Muhammad Junaid Department of Computer Science Superior University Lahore Lahore54000 Pakistan Department of Software Engineering Superior University Lahore Lahore54000 Pakistan

ISBN: (纸本)9783031776199

The resurgence of the chatbot has been facilitated by recent developments in machine learning. Recently, chatbot technology has been more widely available on the web and on mobile devices. According to recent statistics, 57% of businesses have already used or plan to execute a chatbot in the close to future. As a result, chatbots will be crucial in a future powered by AI. The goal of chatbots, which can be text-based computer systems, is to mimic human communication skills. In numerous industries, including customer service, e-coaching, and entertainment, they are spreading like wildfire. The effectiveness of these virtual agents cannot yet be evaluated in a consistent manner. As an alternative, a variety of individuals and groups have developed their guiding principles, either exclusively for their chatbot project or with some inspiration from other groups. In this paper, we explore the trends and evaluation techniques currently in use for chatbots. We investigate chatbot evaluation techniques and rank them in accordance with the ISO 9214 usability characteristics of efficiency, effectiveness and satisfaction. After that, we examine the techniques applied in the literature between 1970 and 2022 and contrast the outcomes. We find a clear trend toward examining the efficacy of chatbots in several recent studies, which is likely due to the growing popularity of task-based chatbots, which are increasingly being deployed in many business situations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Chatbots

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