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Using Conceptual Blending to Teach Software Design Principles to Undergraduates

Using Conceptual Blending to Teach Software Design Principle...

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Frontiers in Education (FIE) Conference

作者： Ashraf Gaffar Mohamed Y. Selim Oliver Eulenstein Elec. & Comp. Eng. Dept. Iowa State University Ames IA Computer Science Department Iowa State University Ames IA

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

The domain of software design is gaining a long overdue recognition as a vital discipline within software eng.neering, necessitating innovative approaches to its teaching in undergraduate education. Despite the growing importance of software design, academic programs often treat it as a secondary skill, overshadowed by the strong emphasis on coding. Only a few schools offer a design degree or dedicated design courses. This disparity between industry demands and educational practices underscores the need for novel pedagogical strategies. In our innovative work, we discuss a new way of effectively teaching software design-by-analogy for undergraduates to help them rapidly acquire the essential skills needed to design complex software without getting entangled in complex code generation and management. Software design does not necessarily follow the same clear delineation/separation between modules and components naturally apparent in tangible eng.neering domains. We employ “Conceptual Blending” to help students map their everyday experiences onto software design concepts. The process begins with students analyzing a simple two-arm watch to identify its user interface and create a finite state automaton for its interaction design. Success rates decline as the complexity of the watches increases, underscoring the software design challeng.s. By comparing these exercises to software interfaces, students learn to apply design techniques such as navigation modeling and prototyping, ensuring they can create intuitive, user-friendly software.

关键词： Industries Software design Navigation Learning automata Education User interfaces Software Complexity theory Software eng.neering Software development management

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Modeling Lunar Surface Charging Using Physics-Informed Neural Networks

Modeling Lunar Surface Charging Using Physics-Informed Neura...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Zendehdel, Niloofar Mosharrof, Adib Delgado, Katherine Han, Daoru Liang, Xin Shu, Tong Missouri University of Science & Technology Mechanical & Aerospace Eng. Dept. Rolla United States University of Kentucky Dept. of Computer Science Lexington United States Missouri University of Science & Technology Mechanical & Aerospace Engr. Dept. Rolla United States University of North Texas Dept. of Computer Science & Engr. Denton United States

ISBN: (纸本)9798350362480

Modeling the elec.ric potential profile above the lunar surface is critical for understanding surface charging and interactions with the space environment. Traditional methods like Particle-in-Cell (PIC) simulations are highly accurate but computationally expensive. To address this, we propose a hybrid approach using a Multi-Layer Perceptron (MLP) architecture in both data-driven neural networks and Physics-Informed Neural Networks (PINNs). The PINN component incorporates physical laws directly into the training process, ensuring physical consistency, while the data-driven component captures complex patterns. This combination offers a significant reduction in computational cost compared to PIC methods while maintaining high modeling accuracy. Our results show that the proposed method effectively represents the elec.ric potential profile above the lunar surface, even with limited data. © 2024 IEEE.

关键词： Multilayer neural networks

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Solving Audio Inverse Problems with a Diffusion Model 48

Solving Audio Inverse Problems with a Diffusion Model

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Moliner, Eloi Lehtinen, Jaakko Välimäki, Vesa Aalto University Acoustics Lab Dept. of Information & Communications Eng. Espoo Finland Aalto University Dept. of Computer Science Espoo Finland

ISBN: (纸本)9781728163277

This paper presents CQT-Diff, a data-driven generative audio model that can, once trained, be used for solving various different audio inverse problems in a problem-agnostic setting. CQT-Diff is a neural diffusion model with an architecture that is carefully constructed to exploit pitch-equivariant symmetries in music. This is achieved by preconditioning the model with an invertible Constant-Q Transform (CQT), whose logarithmically-spaced frequency axis represents pitch equivariance as translation equivariance. The proposed method is evaluated with solo piano music, using objective and subjective metrics in three different and varied tasks: audio bandwidth extension, inpainting, and declipping. The results show that CQT-Diff outperforms the compared baselines and ablations in audio bandwidth extension and, without retraining, delivers competitive performance against modern baselines in audio inpainting and declipping. This work represents the first diffusion-based general framework for solving inverse problems in audio processing. © 2023 IEEE.

关键词： Audio systems deep learning inverse problems signal restoration

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Optimal Local Parameters For Hermite Type Cubic Splines 17

Optimal Local Parameters For Hermite Type Cubic Splines

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17th International Conference on eng.neering of Modern elec.ric Systems, EMES 2023

作者： Bica, Alexandru Mihai Laslo, Eugen Crainic, Cristian G. University of Oradea Dept. of Math. and Computer Science Oradea Romania University of Oradea Dept. of Forestry and Forest Eng. Oradea Romania

ISBN: (纸本)9798350310634

The local derivatives of Hermite type cubic splines are optimally determined on each subinterval of a given mesh through a set of five classical interpolation procedures in order to minimize a certain objective function. We construct an iterative method that selec.s on each subinterval, the adequate algorithm for providing the local derivatives which minimize the objective function such that the values of the local derivatives computed at the previous subinterval are preserved in order to keep the smoothness of the spline. The admissible set of classical interpolation procedures consists of the natural cubic spline, the Catmull-Rom cubic spline, the Akima's cubic spline, and the cubic splines with minimal derivative oscillation and those with minimal deviation by the data polygon. A numerical experiment is presented in order to illustrate the performances of the algorithm. © 2023 IEEE.

关键词： Interpolation

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Security Augmentation Approach for Internet of Things Enhanced Cryptographic Algorithm 6

Security Augmentation Approach for Internet of Things Enhanc...

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6th International Conference on Intelligent Computing and Control Systems, ICICCS 2022

作者： Kumbalavati, S.B. Bendigeri, Kirankumar Y. Mallapur, Jayashree D. Pareek, Piyushkumar Patil, Mahesh S. Dept. of Electronics & Instrumentation Eng. Karnataka Bagalkot India East West College of Engineering Dept. of Computer Science Eng. Karnataka Bangalore India KLE Technological University Dept. of Computer Science Eng. Karnataka Hubli India

ISBN: (纸本)9781665410359

The Internet of Things (IoT) is continuously achieving pragmatic attention for research and investigation as this technology have achieved considerable popularity worldwide because of rapidly connecting billions of apparatus to internet and capable enough to make a pragmatic connection among diverse devices for data communication as desired in modern world. Several investigations have been carried out on IoT secrecy in recent years for protecting the confidential data as well as information but due to rapid technological advancements in modern devices as well as communication systems along with new technologies, the protection of the confidential data or information is becoming a critical threat all over globe. In this paper, authors suggested a novel security augmentation approach for IoT utilizing an enhanced cryptographic algorithm that is capable enough to secure confidential data as well as information in faster and pragmatic manner in comparison to the conventional approaches and establish pragmatic connectivity in smart city model as demanded in present era. This experimentation work was carried out over a personal computer (PC) installed with the MATLAB R2019b software kit, 16 GB of RAM (Random Access Memory), Window 10 along with the 64-bit operating system (OS). The measured results were observed with high degree of accuracy and precision for pragmatic validation. The measured outcomes are pragmatic and improved in comparison to diverse kinds of conventional strategies. Although, multifarious investigators have suggested diverse strategies in previous years to improve secrecy of confidentiality data but there are still gigantic possibilities in this arena for more investigation. © 2022 IEEE.

关键词： Internet of things

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Exploring Data Visualization Techniques for Large Datasets 1

Exploring Data Visualization Techniques for Large Datasets

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1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Sikarwar, Shailendra Singh Kumawate, Bhawesh Vaishnav, Arun Kumar, Love Bushra, Seema Devi, S. Teitsana PGV College Dept. of Computer Science Gwalior India Madhav University Dept. of CSE Pindwara India Mangalayatan University Dept. of Computer Eng. and Applications Beswan India Deen Academics Lingayas Vidyapeeth Faridabad India Dhanalakshmi Srinivasan University Dept. of CSE Coimbatore India

ISBN: (纸本)9798350356816

In a world of Big Data, being able to easily visualize large data sets can make the difference between understanding & wisely judging that data - or not. Big Data is the word with which not many people are aware of, but these success stories make sure that organizations sit back & take notice to what this large data can show then when it collated together over time from different sources. The methods traditionally used for visualization rarely fit into the Big-Data world because they do not have scalability, given that volume (huge amounts), velocity (high speed), or variety (complex details) are now more prevalent in big-data processing. This paper then explores data visualization techniques that can be used to manage very large datasets, including streaming data visualization, dimensionality reduction (e.g. T-SNE), & hierarchical clustering among other Node XL analyses. In this paper, based on accumulated observations & implementations of these techniques over the years, an extensive review is provided for researchers or practitioners to selec. suitable visualization methodologies that not only suit the scale but also discover patterns in their data. The results highlight the need for enabling tools, methods, & practices to make sense of big data in an interactive visual context that enables better orchestration between complex systems using diverse hardware/software stacks. Additionally, the pros & cons of each method are explained, with real-world use cases & case studies demonstrating their practicality. © 2024 IEEE.

关键词： Data assimilation

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Small, but Mighty: Lightweight ML-enabled Intrusion Detection Framework for Vehicular Ad-Hoc Networks 3

Small, but Mighty: Lightweight ML-enabled Intrusion Detectio...

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3rd IEEE World Conference on Applied Intelligence and Computing, AIC 2024

作者： Dinh, Minh Patel, Megha Das, Tapadhir Shukla, Raj Mani Dept. of Elec & Comp Eng University of the Pacific Stockton United States Dept. of Computer Science University of the Pacific Stockton United States School. of Comp and Info Science Anglia Ruskin University Cambridge United Kingdom

ISBN: (纸本)9798350384598

Vehicular Ad-Hoc Networks (VANETs) have become an integral component of contemporary vehicular technology. This technology provides advanced features like traffic and weather reports and collision prevention to create a sophisticated driving experience. Unfortunately, this infrastructure can become victim to cyber-attacks like intrusions that aim to compromise VANET operations. In this paper, we propose a novel lightweight machine learning (ML)-based intrusion detection framework for VANETs. The algorithm developed utilizes dimensionality reduction to reduce the operational footprint of our training data so that it is easier to train and deploy ML-enabled intrusion detectors for protecting VANET infrastructures. Results showcase that K = 3 provides us with high performance and low operational requirements. Through this, we achieve efficient performance for protecting VANETs against intrusions while decreasing the overall operational footprint of the framework. © 2024 IEEE.

关键词： Network intrusion

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Spatial and Temporal Attention-Based Emotion Estimation on HRI-AVC Dataset

Spatial and Temporal Attention-Based Emotion Estimation on H...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Subramanian, Karthik Singh, Saurav Namba, Justin Heard, Jamison Kanan, Christopher Sahin, Ferat Rochester Institute of Technology Dept. Elect. & Microelectronic Eng. Rochester United States Rochester Institute of Technology Dept. Computer Science Rochester United States University of Rochester Dept. Computer Science Rochester United States

ISBN: (纸本)9798350337020

Many attempts have been made at estimating discrete emotions (calmness, anxiety, boredom, surprise, anger) and continuous emotional measures commonly used in psychology, namely 'valence' (The pleasantness of the emotion being displayed) and 'arousal' (The intensity of the emotion being displayed). Existing methods to estimate arousal and valence rely on learning from data sets, where an expert annotator labels every image frame. Access to an expert annotator is not always possible, and the annotation can also be tedious. Hence it is more practical to obtain self-reported arousal and valence values directly from the human in a real-time Human-Robot collaborative setting. Hence this paper provides an emotion data set (HRI-AVC) obtained while conducting a human-robot interaction (HRI) task. The self-reported pair of labels in this data set is associated with a set of image frames. This paper also proposes a spatial and temporal attention-based network to estimate arousal and valence from this set of image frames. The results show that an attention-based network can estimate valence and arousal on the HRI-AVC data set even when Arousal and Valence values are unavailable per frame. © 2023 IEEE.

关键词： Affective Computing computer Vision Human-Robot Interaction (HRI)

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Advancing COVID-19 Inquiry Responses Through Transfer Learning-Based Question Entailment Methodology 2

Advancing COVID-19 Inquiry Responses Through Transfer Learni...

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2nd International Conference on Ambient Intelligence in Health Care, ICAIHC 2023

作者： Julius, Femi Godslove Kumar Nayak, Ajit Siksha 'O' Anusandhan Deemed to be University Dept. of Computer Science & Eng. Odisha Bhubaneswar India Siksha 'O' Anusandhan Deemed to be University Dept. of Computer Science & Information Tech. Odisha Bhubaneswar India

ISBN: (纸本)9798350344882

The COVID-19 pandemic underscores the urgency for efficient solutions addressing critical questions, given the prevalence of misinformation and ambiguous answers that necessitate a dependable automated system. Public Health Question Answering (QA) within Natural Language Processing (NLP) and Artificial Intelligence (AI) poses unique challeng.s, demanding both linguistic comprehension and domain expertise. Recent advancements in Deep Learning (DL) and Deep Neural Networks (DNN) have revolutionized QA systems, leading to improved performance. In this paper, we propose a novel question entailment approach named CoviBioBERT. It employs finely-tuned ensemble neural networks to enhance precision in addressing COVID-19-related queries. CoviBioBERT is an optimized QA system based on the BioBERT pre-trained model, customized for COVID-19 inquiries, and evaluated on a benchmark dataset of question-answer pairs. The system aims to provide dependable and accurate responses to contextually relevant COVID-19 queries. Experimental findings underscore the superiority of CoviBioBERT over foundational models, exhibiting a notably higher Exact Match (EM) score and ensuring more trustworthy responses to COVID-19-related inquiries. This paper makes a significant contribution by introducing a state-of-the-art QA system for retrieving COVID-19 information. It thereby equips the general public and healthcare practitioners with reliable insights to bolster global efforts against the pandemic. © 2023 IEEE.

关键词： COVID-19

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Optimizing Mobility IoT Device Networks with Dynamic RIS in mMIMO-Cooperative NOMA 6G Systems 1

Optimizing Mobility IoT Device Networks with Dynamic RIS in ...

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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Hassan, Khalil Hassan, Mohamed Hamid, Khalid Hassan, Elmuntaser Mokhtar, Rania A. Saeed, Mamoon M. Dept. of Comm. Systems Uni. of Science & Technology Omdurman Sudan Dept. of Electrical Eng. Omdurman Islamic Uni. Omdurman Sudan Dept. of Computer Science Al-Neelain University Khartoum Sudan Department of Computer Engineering Taif University Taif Saudi Arabia Yemen

ISBN: (纸本)9798331533557

Advanced technologies like reconfigurable intelligent surfaces (RISs), massive multiple-input multiple-output (mMIMO), and non-orthogonal multiple access (NOMA) are crucial for the upcoming 6G communications landscape, particularly for IoT applications. This study uniquely explores the effects of RIS dynamics on the performance of mMIMO downlink (DL) cooperative NOMA systems in dense IoT environments. It introduces a novel methodology for modeling dynamic traffic distribution and integrating RIS, focusing on key performance metrics such as network capacity, spectral efficiency (SE), latency, and energy efficiency (EE). Various scenarios are evaluated, considering different distributions of IoT devices and signal-to-noise ratios (SNRs). Using simulation software, the research analyzes performance under unstable channel conditions with varying device distances, speeds, and power locations, employing 256-QAM modulation and successive interference cancellation (SIC). The results demonstrate that dynamic RIS significantly enhances capacity, spectrum efficiency, latency, and EE, paving the way for optimized IoT network architecture in future wireless systems. © 2024 IEEE.

关键词： Quadrature amplitude modulation

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