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Proceedings of the 29th Conference on Pattern Languages of Programs

作者： Haji Gul Wahaj Valentino Vranić Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava

ISBN: (纸本)9781941652183

Despite numerous efforts to address system outsourcing problems in the subcontract management system, the existing available solutions do not appear to be sufficient. They are fragmented into individual patterns, neither composing legible pattern languages to address the subcontract management systems nor being integrated into comprehensive pattern languages for managing system outsourcing in general. Communication among stakeholders is another issue that takes a long time because of their naturally hierarchical or multi-layered structure. And usually, false information reaches the sub-contractor at the bottom of the chain, which affects a project, and causes delays in deliverables. We attempt to overcome these problems by providing a set of four organizational patterns for the subcontract management system. Using them in combination with other available patterns and practices, we demonstrate a pattern language for better communication among different involved organizations. This paper focuses on better relationships between stakeholders. The relationships contain an inter-organizational communication and coordination among the stakeholders. A pattern story of a real case illustrates the overall use of this pattern language.

关键词： multi-sourcing organizational patterns patterns software engineering subcontract management system outsourcing

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Identifying and Involving the Real End User in software Development: Towards a Pattern Language 22

Identifying and Involving the Real End User in Software Deve...

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Proceedings of the 27th European Conference on Pattern Languages of Programs

作者： Mohammad Daud Haiderzai Valentino Vranić Institute of Informatics Information Systems and Software EngineeringFaculty of Informatics and Information Technologies Slovak University of Technology Slovakia

ISBN: (纸本)9781450395946

software development demand and identification of end users involvement have been increasing rapidly, but identifying the real end user and involving them in software development is challenging for software developers reported in the literature. One of the problems is the difficulty of designing the business domain. It takes longer to find the actual business domain when different and inexpert domain end users are engaged with developers. Another problem is the difficulty of incorporating all types of end users needs in software development. Several expectations and different information make the development process more complex and overload the project scope. software development also takes more time, and the project goal is challenging. The above problems are the leading causes that create a complex process and difficulty in software development. To overcome these problems, we established a pattern language composed of eight organizational patterns observed and documented during in practical work on many projects. These patterns and other known organizational patterns relation are described in a patterns story of a real company.

关键词： software development user involvement Organizational patterns

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Patterns of Recreating Reality in Games 22

Patterns of Recreating Reality in Games

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Proceedings of the 29th Conference on Pattern Languages of Programs

作者： Branislava Vranić Valentino Vranić Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava

ISBN: (纸本)9781941652183

There are various ways of how reality is recreated in games. These patterns recur in within a single game and throughout many games. There are contradictory forces that lead to a solution that can be reused. Clearly, these ways of recreating reality in games exhibit the properties of patterns in the Alexandrian sense, that heavily influenced the area of software development. Identifying the patterns of recreating reality in games is important in order to develop entertaining and interesting games that people will enjoy playing. Implementing them can greatly improve the quality of games. Furthermore, the patterns are flexible, thus they can be used in many creative ways. For games to be enjoyable and plausible, the reality within them needs to be recreated. Good practices in achieving this can be captured as patterns in the Alexandrian sense. This paper brings in the idea of patterns of recreating reality in games, the connections between them, how they are implemented, and how to apply them. Five patterns mined in Minecraft and other successful games are presented---The Presence of an Enjoyable Challenge, Preservation of Progress, Flexibility of the Laws of Nature, Expansion of Inventory Limits, and Fast Travel---along with the relationships between them and examples of where they can be found. A story describing gameplay of Minecraft from a player's perspective has been used to show exact examples of these patterns.

关键词： drama patterns game design game patterns laws of nature minecraft patterns

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Hardened Processor Architecture

Hardened Processor Architecture

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International Conference on Mixed Design of Integrated Circuits and Systems (MIXDES)

作者： Ján Mach Lukáš Kohútka Pavel Čičák Institute of Computer Engineering and Applied Informatics Slovak University of Technology Bratislava Slovakia Institute of Informatics Information Systems and Software Engineering Slovak University of Technology Bratislava Slovakia

Processors for terrestrial applications are protected by Earth's atmosphere and magnetic field, so the probability of single event effects (SEE) is significantly lower. Shrinking of the technology nodes allows higher operational frequency and performance, but their susceptibility to SEE is increasing. Nowadays satellites and safety critical automotive applications require more and more computational power. The hardening by design has been implemented mainly by redundancy of the whole cores. The consequences are lower frequency, larger area, and higher power consumption. We propose a novel hardening technique, which enables high frequency operation and doesn't cause large power consumption and area overhead. The protection is based redundancy and separation of the pipeline into two main sections. It provides a fast detection of faults, simple recovery by flush of the pipeline, and allows a large prediction unit to be unprotected. The whole protection scheme can be implemented at the Register Transfer Level. We present the protection scheme at the core with RISC-V instruction set. Simulations confirm the protection can handle the injected faults. Synthesis shows, the protection lowers the maximum frequency by only about 4.7%. The area increase is only about 118% and can be even lower.

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KDTL: knowledge-distilled transfer learning framework for diagnosing mental disorders using EEG spectrograms

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Neural Computing and Applications 2024年第30期36卷 18919-18934页

作者： Singh, Shreyash Jadli, Harshit Padma Priya, R. Surya Prasath, V.B. Department of Software Systems School of Computer Science and Engineering Vellore Institute of Technology Vellore India Division of Biomedical Informatics Cincinnati Children’s Hospital Medical Center CincinnatiOH45229 United States Department of Pediatrics University of Cincinnati College of Medicine CincinnatiOH45257 United States Department of Biomedical Informatics College of Medicine University of Cincinnati CincinnatiOH45267 United States Department of Computer Science University of Cincinnati CincinnatiOH45221 United States

Electroencephalography (EEG) is a well-known modality in neuroscience and is widely used in identifying and classifying neurological disorders. This paper investigates how EEG data can be used along with knowledge distillation-based deep learning models to detect mental disorders like epilepsy and sleep disorders. The EEG signals are converted into time–frequency plots using short-time Fourier transforms. Further, we propose a novel methodology for using knowledge distillation-based transfer learning (KDTL). Knowledge distillation is becoming quite prevalent in the machine learning field and is associated with various applications in our work;we propose its use in the detection of mental disorders from EEG spectrograms. We convert the EEGs using short-term Fourier transform to obtain time–frequency representation and apply teacher-student by first training a large teacher model and use knowledge distillation to train a student model. In our experiments, we found that ConvNext teacher and MobileNet student combination obtained better results. Our proposed KDTL approach is tested on two datasets with multiple cases, namely the Bonn and ISRUC datasets and obtain 98% and 95% accuracies, respectively. Further experimental results show that the overall KDTL methodology can obtain high classification accuracy across both datasets in binary and multiclass classifications and proves to be better than multiple prior works. Further, our KDTL approach provides a way to train lightweight models which have a smaller number of trainable parameters and thereby constitute lower training time overall. Our proposed KDTL-based approach obtained accurate results in diagnosing mental disorders from EEG spectrograms. Compared to other related methods, KDTL outperformed across tasks with obtained good results in both binary and multiclass classifications. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Electroencephalography

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A New RISC-V CPU for Safety-Critical Systems

A New RISC-V CPU for Safety-Critical Systems

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Mediterranean Conference on Embedded Computing (MECO)

In this paper, we propose a novel hardening technique against Single Event Effects, which enables high-frequency operation and does not cause large power consumption and area overhead. The protection is based on redundancy, separation of the pipeline into two main sections, and is fully applicable at Register Transfer Level. It provides fast detection of faults, simple recovery by a flush of the pipeline, and allows a large prediction unit to be unprotected. We present the protection scheme at the core with the RISC-V instruction set. Simulations confirm that the protection can handle the injected faults. Synthesis shows that protection lowers the maximum frequency by only 3.9%. The area increase is only 108% and can be even lower. Total power consumption increased by 119%.

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Big Data Bot with a Special Reference to Bioinformatics

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Computers, Materials & Continua 2023年第5期75卷 4155-4173页

作者： Ahmad M.Al-Omari Shefa M.Tawalbeh Yazan H.Akkam Mohammad Al-Tawalbeh Shima’a Younis Abdullah A.Mustafa Jonathan Arnold Biomedical Systems and Informatics Engineering Department Yarmouk UniversityIrbid21163Jordan Department of Medicinal Chemistry and Pharmacognosy Yarmouk UniversityIrbid21163Jordan Department of Electrical Computer and Software EngineeringUniversity of Ontario Institute of TechnologyOshawaL1H7K4Canada Department of Mechanical Engineering University of MosulMosul41001Iraq Genetics Department University of GeorgiaAthens30602GAUSA

There are quintillions of data on deoxyribonucleic acid(DNA)and protein in publicly accessible data banks,and that number is expanding at an exponential *** scientific fields,such as bioinformatics and drug discovery,rely on such data;nevertheless,gathering and extracting data from these resources is a tough *** data should go through several processes,including mining,data processing,analysis,and *** study proposes software that extracts data from big data repositories automatically and with the particular ability to repeat data extraction phases as many times as needed without human *** software simulates the extraction of data from web-based(point-and-click)resources or graphical user interfaces that cannot be accessed using command-line *** software was evaluated by creating a novel database of 34 parameters for 1360 physicochemical properties of antimicrobial peptides(AMP)sequences(46240 hits)from various MARVIN software panels,which can be later utilized to develop novel ***,for machine learning research,the program was validated by extracting 10,000 protein tertiary structures from the Protein Data *** a result,data collection from the web will become faster and less expensive,with no need for manual data *** software is critical as a first step to preparing large datasets for subsequent stages of analysis,such as those using machine and deep-learning applications.

关键词： Bioinformatics big data data extraction bot drug design

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On the Influence of Grid Cell Size on Taxi Demand Prediction 8th

On the Influence of Grid Cell Size on Taxi Demand Predict...

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8th EAI International Conference on Smart Objects and Technologies for social Goods, GOODTECHS 2022

作者： Korth, Merlin Schleibaum, Sören Müller, Jörg P. Ehlers, Rüdiger Department of Informatics Clausthal University of Technology Julius-Albert-Straße 4 Clausthal-Zellerfeld38678 Germany Institute for Software and Systems Engineering Clausthal University of Technology Julius-Albert-Straße 4 Clausthal-Zellerfeld38678 Germany

ISBN: (纸本)9783031288128

Accurate taxi demand prediction has the potential to increase customer satisfaction and hence the usage of ride-sharing by predicting the number of taxis needed at a certain place and time. When reviewing the related work on demand prediction, we observed that in taxi demand prediction different grid topologies – e.g. rectangular subdivisions of an area – and sizes are applied. However, it is not clear how and why the grid cells are configured the way they are and a systematic comparison of different topologies and sizes as regards their influence on urban demand prediction is lacking. In this paper, we compare the influence of different grid cell sizes – 250 m, 500 m, and 1000 m – on the prediction accuracy of different types of deep learning-based taxi demand prediction approaches, such as convolutional neural networks, recurrent neural networks, and graph neural networks. Therefore, we select five deep learning-based approaches from related work and evaluate their performance on the New York City TLC taxi trip dataset and three different evaluation metrics. Our results show that approaches with a grid cell of size 1000 m and 500 m achieve a higher prediction accuracy. Furthermore, we propose to consider the grid cell size as a tunable parameter in demand prediction models. © 2023, ICST institute for Computer Sciences, Social informatics and Telecommunications engineering.

关键词： Recurrent neural networks

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Fingerprint Matching for Noisy and Distorted Patterns Using a Siamese Network With ResNet50 and Multihead Attention

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IEEE Access 2025年 13卷 88047-88064页

作者： Sawhney, Tinny Sharma, Ashu Abrol, Pawanesh Kumar Lehana, Parveen Chaahat Yadav, Vaishali Scherer, Rafal Kulakov, Oleksii Ali Alzubi, Ahmad University of Jammu DSP Laboratory Department of Electronics Jammu180006 India University of Jammu Department of Computer Science and IT Jammu180006 India Chitkara University Institute of Engineering and Technology Chitkara University Department of Computer Science and Engineering Punjab Rajpura140401 India Manipal University Jaipur Department of Computer Science & Communication Engineering Jaipur303007 India Czestochowa University of Technology Department of Artificial Intelligence Częstochowa42-200 Poland Faculty of Informatics and Software Engineering National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" Kyiv03056 Ukraine King Saud University Community College Department of Computer Science Riyadh11451 Saudi Arabia

Dermatoglyphics, the study of unique ridge patterns on fingertips, plays a crucial role in fingerprint-based identification. However, skin conditions such as psoriasis, eczema, and verruca vulgaris can distort these patterns. This distortion creates challenges for fingerprint matching systems in forensic science and biometric authentication. This paper proposes a Siamese network with a modified ResNet50 architecture and multihead attention mechanisms to improve fingerprint matching under such distortions. The Siamese network enables the system to compare fingerprint pairs effectively, even under distortions. The modified ResNet50 architecture captures intricate ridge patterns, while the multihead attention mechanisms focus on critical fingerprint regions. Overall, the proposed approach enhances the system’s ability to learn discriminative features. As a result, it can effectively differentiate between matched and unmatched fingerprint pairs, even in the presence of moderate to extreme noise. The proposed system was trained on the Sokoto coventry fingerprint dataset (SOCOFing) and a custom dataset. Experimental results demonstrate high accuracy, with the system achieving 99.47% accuracy under low noise conditions and 90% under moderate noise. However, performance declined to 55.56% under extreme distortions. A comparative analysis highlighted the superiority of the proposed system over widely used minutiae-based methods. The latter exhibited a significant drop in matching scores, falling below 15% for highly distorted fingerprints. These findings underscore the limitations of traditional fingerprint recognition techniques and highlight the effectiveness of proposed approach in handling dermatoglyphic distortions. © 2013 IEEE.

关键词： Feature Selection

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B2A, A Straight-Through Approach from Basics to Advanced Level: Case Study for Python Course 11

B2A, A Straight-Through Approach from Basics to Advanced Lev...

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11th Workshop on software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2024

作者： Shazmeen, Abbasi Dakić, Pavle Zoltan, Alwahab Dhulfiqar Department of Programming Languages and Compilers Faculty of Informatics Eötvös Loránd University 1/C Pázmány Péter st. BudapestH-1117 Hungary Faculty of Informatics and Computing Singidunum University Danijelova 32 Belgrade Serbia Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Ilkovičova 2 Bratislava842 16 Slovakia

In this study, we present a straightforward teaching strategy for teaching the Python programming language. Our method emphasizes a clear progression from fundamental to sophisticated concepts. Beginning with a thorough explanation of core Python ideas, we show a beginner-level script that dissects each line of code and displays the results. One distinguishing feature of our system is that students use ChatGPT to optimize code, which encourages them to improve the core program with fewer lines. After getting the updated solutions, students carefully compare the original and optimized programs to discover improvements and potential flaws. This study underlines the effectiveness of the Straight-Through Approach, which focuses on improving Python understanding while also developing critical thinking and code optimization skills. Our findings show that this strategy is a simple and effective way for teachers to assist students in growing from basic to advanced Python abilities, resulting in a dynamic and successful learning environment. The proposed technique will teach students how to use AI-driven modules correctly, such as ChatGPT. © 2024 Copyright for this paper by its authors.

关键词： Python

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