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4th IEEE Global Conference on Life Sciences and Technologies, LifeTech 2022

作者： Liang, Zilu Ubiquitous and Personal Computing Lab Faculty of Engineering Kyoto Japan

ISBN: (纸本)9781665419048

Correlation analysis is one of the most popular analytic methods for discovering the relationship between two variables in consumer health data. Nevertheless, the simple sample correlation techniques (e.g., Pearson's or Spearman's correlation) assume the independence of the observations, which is often violated when there are repeated measures from each subject (also called nested data). In this paper, we compare three methods for correlation calculation on nested consumer health data: (1) repeated measure correlation (rmcorr), (2) subject mean correlation (smcor), and (3) simple sample correlation (sscor). We contend that rmcorr is a more appropriate technique for the correlation analysis of nested data as it could explicitly capture the within-subject variations. In contrast, the smcor and sscor, which could only capture the cross-subject variations, may produce misleading and faulty results. © 2022 IEEE.

关键词： Ubiquitous computing

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Towards intelligent compiler optimization 45

Towards intelligent compiler optimization

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45th Jubilee International Convention on Information, Communication and Electronic Technology, MIPRO 2022

作者： Kovac, Mihael Brcic, Mario Krajna, Agneza Krleza, Dalibor University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (纸本)9789532331035

The future of computation is massively parallel and heterogeneous with specialized accelerator devices and instruction sets in both edge- and cluster-computing. However, software development is bound to become the bottleneck. To extract the potential of hardware wonders, the software would have to solve the following problems: heterogeneous device mapping, capability discovery, parallelization, adaptation to new ISAs, and many others. This systematic complexity will be impossible to manually tame for human developers. These problems need to be offloaded to intelligent compilers. In this paper, we present the current research that utilizes deep learning, polyhedral optimization, reinforcement learning, etc. We envision the future of compilers as consisting of empirical testing, automatic statistics collection, continual learning, device capability discovery, multiphase compiling - precompiling and JIT tuning, and classification of workloads. We devise a simple classification experiment to demonstrate the power of simple graph neural networks (GNNs) paired with program graphs. The test performance demonstrates the effectiveness and representational appropriateness of GNNs for compiler optimizations in heterogeneous systems. The benefits of intelligent compilers are time savings for the economy, energy savings for the environment, and greater democratization of software development. © 2022 Croatian Society MIPRO.

关键词： Energy conservation

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Designing Quantum-Resilient Blockchain Frameworks: Enhancing Transactional Security with Quantum Algorithms in Decentralized Ledgers

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International Journal of Advanced Computer Science and Applications 2025年第4期16卷 618-628页

作者： Kale, Meenal R. Baker El-Ebiary, Yousef A. Sathiya, L. Burugari, Vijay Kumar Yulduz, Erkiniy Muniyandy, Elangovan Alanazi, Rakan Department of Humanities Yeshwantrao Chavan College of Engineering Hingna Nagpur India Faculty of Informatics and Computing UniSZA University Malaysia Department of CSE Panimalar Engineering College Chennai India Dept of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh Guntur India Automatic Control and Computer Engineering Department Turin Polytechnic University in Tashkent Tashkent Uzbekistan Department of Biosciences-Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Applied Science Research Center Applied Science Private University Amman Jordan Department of Information Technology Faculty of Computing and Information Technology Northern Border University Rafha Saudi Arabia

Quantum computing is progressing at a fast rate and there is a real threat that classical cryptographic methods can be compromised and therefore impact the security of blockchain networks. All of the ways used to secure blockchain like Rivest–Shamir–Adleman (RSA), Elliptic Curve Cryptography (ECC) and Secure Hash Algorithm 256-bit (SHA256) are the characteristic of the traditional cryptographic techniques vulnerable to attack by quantum algorithms: Shor’s and Grover’s algorithms: can efficiently break asymmetric encryption and speed up brute force attacks. Because of this vulnerability, there exists a need to develop an advance quantum resilient blockchain framework to protect the decentralized ledgers from the future threats of the quantum. This research proposes Post-Quantum Cryptography (PQC), Quantum Key Distribution (QKD) and Quantum Random Number Generation (QRNG) as a formidable architectural integration, to fortify security of blockchain. Classical encryption is replaced with PQC, QKD with secure key exchange by detecting eavesdropping, and QRNG with improving cryptographic randomness to remove the predictable key vulnerability. Only with a small loss of transaction efficiency, we increase transaction encryption accuracy, key exchange security, and resistance to quantum attacks. In this quantum enhanced blockchain design, the idea is to preserve the decentralization, transparency and security and at the same time overcome the future quantum threat. By going through rigorous analysis and comparative evaluation, we demonstrate that the approach saves blockchain networks from the emerging quantum risks to make sure that the decentralized finance, smart contracts and cross chain transactions. © (2025), (Science and Information Organization). All rights reserved.

关键词： Quantum cryptography

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KidSwatch: Children Development Observation System 5

KidSwatch: Children Development Observation System

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5th International Conference on Advancements in computing, ICAC 2023

作者： Oshadhini, P.A.L.N. Siriwardana, K.A.D.H.O. Peshala Ranmini, H.K. Sandeepa, S.R. Weerasinghe, Lokesha Kelegama, Thamali Sri Lanka Institute of Information Technology Faculty of Computing Department of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Department of Software Engineering Malabe Sri Lanka

ISBN: (纸本)9798350358131

The kidSwatch is a mobile application designed specifically for grade 1 children aged six years. It serves as a comprehensive framework for observing and evaluating children's developmental progress. The application focuses on the main components of children's development: Cognitive development, Emotional development, Language development, and Learning development. By analyzing the results obtained from observing these four components, parents can gain valuable insights into their children's development within a matter of minutes. The kidSwatch employs a range of observational techniques, including direct observation, structured interviews, and standardized tests, to gather information on a child's talents, skills, and behaviors. Trained observers proficient in the kidSwatch framework carefully record and analyze the child's interactions, activities, problem-solving abilities, emotional expressions, and social interactions. Ultimately, the kidSwatch empowers parents with a quick and effective means of understanding and assessing their child's development. To satisfy the above features there are a Hand number detection algorithm, letter recognition algorithm, Emotion recognition algorithm, and voice-based answering algorithm They perform an accuracy between 75%-90% on CNN. © 2023 IEEE.

关键词： Emotion Recognition

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Spatial and Temporal Complexity Analysis of 4K Drone Footage 5

Spatial and Temporal Complexity Analysis of 4K Drone Footage

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5th IEEE International Conference on Smart Systems and Technologies, SST 2022

作者： Benjak, Jakov Hofman, Daniel Perleta, Martina University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (数字)9781665482158

ISBN: (纸本)9781665482158

Video encoding nowadays mostly revolves around optimizing and modifying existing encoders. Popular encoders such as H.264 and H.265 have open source implementations, and researchers oftentimes modify only certain parts of the encoder to obtain desired results. In this work, several 4K raw drone videos will be analyzed in regard to spatial and temporal complexity, which could be used for encoder optimization. In the last few years, drones have gained in popularity and their use cases have expanded. Drone racing and filmmaking evolved from being only hobbies, and today there are professional drone racers and filmmakers. Hence, drone video transmission systems must keep pace with industrial demand. It is known that scene complexity affects encoding quality. Specifically, spatial information (SI) and temporal information (TI) can be calculated in various ways and depending on SI and TI score, video bitrate must be increased/decreased in order to sustain the desired quality level. © 2022 IEEE.

关键词： Drones

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The Development and Implementation of a Microgrid SCADA System Simulator 45

The Development and Implementation of a Microgrid SCADA Syst...

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45th Jubilee International Convention on Information, Communication and Electronic Technology, MIPRO 2022

作者： Matulin, Lucija Hrga, Alen Capuder, Tomislav University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (纸本)9789532331035

Shifting the paradigm to decarbonized, distributed renewable future implies changes to conventional principles of power systems operation and requires the implementation of smart grid concepts. Microgrids have been widely recognized as a decentralized approach to successfully integrating renewable energy sources and end consumer empowerment. However, their implementation requires significant improvements and transformation of the distribution system in terms of increased observability and controllability, especially in the context of (near) real-time operation. Supervisory, Control, and Data Acquisition Systems (SCADA) enable system and infrastructure automated monitoring and control and serve as a foundation for advanced management and application of optimization-driven operation. Moreover, the development and testing of the functions mentioned above is a complex task, and today there is still a lack of holistic simulation tools, even though well-established power system simulators exist. The main objective of this paper is to introduce a novel simulation tool developed to simulate the SCADA system used in the Smart Grid Laboratory of the faculty of Electrical engineering and computing for control, integration, and interactions between a microgrid's components. This paper includes simulator system architecture design, implemented functionalities, and future directions. Simulator testing shows successful communication, measurement generation, and meaningful response to commands and reference signals, proving correct functionality. Besides significant value in testing SCADA functionality, designing such a simulator has been of great benefit during restricted access to real-world devices in the Smart Grid Laboratory during the COVID-19 pandemic lockdown. © 2022 Croatian Society MIPRO.

关键词： Simulators

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ANALYSIS of LOW-COST UAV PHOTOGRAMMETRY SOLUTIONS for BEACH MODELLING and MONITORING USING the OPENSOURCE QUANTUM GIS

ANALYSIS of LOW-COST UAV PHOTOGRAMMETRY SOLUTIONS for BEACH ...

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2022 Annual Conference, ASPRS 2022

作者： Eboigbe, M.A. Kidner, D.B. Thomas, M. Thomas, N. Aldwairy, H. University of South Wales Faculty of Engineering and Computing United Kingdom

Coastlines are fundamentally unique features. Their behavioural patterns are predominantly subjects of numerous environmental and engineering studies. With the magnitude of the effects of coastal flooding and erosion, there is a need for accurate techniques for data capture and data processing. With an emphasis on the zero-cost open source GIS software, there is no existing evaluative procedure for demonstrating the analytical capabilities of large-scale UAV-based outputs for microscale analysis for small changes on the beach such as sediment movement, erosion/accretion of individual features. There were four different drone surveys in the study area to determine microscale change over time. A three-stage analysis procedure helps in determining the overview of the coastline and highlights the region(s) of optimum change requiring further spatial analysis with micro-scale change detection. Results obtained show the analytical capabilities of large-scale UAV-based outputs for relatively small but detailed analysis using the open-source QGIS. Results obtained show that spatial analyses of the zoomed areas at different viewpoints and scales improve the confidence level of the hillshading and contour of that particular section on the coastline. The UAV photogrammetry and the three-stage analysis procedure can detect a 1cm change on the beach using the free and open-source QGIS software. It shows the profile modelling of the coastal inundations for both pre and post-flooding events at sub-centimetre intervals can be obtained from QGIS modelling, data computation, analysis, and visualization. © 2022 M. A. Eboigbe et al.

关键词： Unmanned aerial vehicles (UAV)

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Modeling the Percentage of NEET in Indonesia with Spatial Cauchy Regression through the Bayesian Analysis Approach

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IAENG International Journal of Applied Mathematics 2024年第7期54卷 1288-1295页

作者： Rantini, Dwi Fakhruzzaman, Muhammad Noor Ningrum, Ratih Ardiati Othman, Fazidah Choir, Achmad Syahrul Ramadan, Arip Alya, Najma Attaqiya Putri, Elfira Rahma Pratama, Muhammad Alfian Engineering Department Data Science Technology Study Program Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Indonesia Engineering Department Data Science Technology Study Program Faculty of Advanced Technology andMultidiscipline Universitas Airlangga Indonesia Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Malaysia Statistical Computing StudyProgram Politeknik Statistika STIS Indonesia Information System Study Program School of Industrial and System Engineering Telkom University Indonesia

Indonesia has entered a period of demographic bonus. Human resources must be optimized. The number of children who do not in employment, education or training (NEET) in each province needs attention. Several factors that could contribute to the decline in the NEET percentage are literacy rates and the number of adolescents with computer skills. Increasing these two factors is believed to be able to reduce the percentage of NEET in every province in Indonesia. To find out the relationship between these two factors and how much influence they have on the percentage of NEET, this research is modeled by Cauchy regression and includes spatial effects. The results of the analysis show that the best model is when the spatial effect is modeled by Fernandez Steel Skew Normal conditionally autoregressive (FSSN CAR). This result is seen from the smallest value of the Watanabe Akaike Information Criterion (WAIC) in this model, which is 190.5. The parameter estimated shows that the higher the literacy rate and the number of adolescents with computer skills, the lower the percentage of NEET in each province in Indonesia. The results of this research can be useful for the Indonesian government to increase the number of educational facilities related to these two factors. © (2024), (International Association of Engineers). All rights reserved.

关键词： Bayesian CAR Cauchy Education NEET

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Exploring usage of summative peer assessments in engineering education 50

Exploring usage of summative peer assessments in engineering...

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50th Annual Conference of the European Society for engineering Education, SEFI 2022

作者： Petrović, J. Pale, P. University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (纸本)9788412322262

Summative peer assessment is an assessment method where the one's work is typically graded by several other anonymous peers using predefined criteria. The value of summative peer assessments in higher education stems from the fact that they can provide scalability in assessment for large enrollment classes for a variety of different assessment types. The main disadvantages of using summative peer assessments are questionable validity and reliability. In this paper, the first results of using summative peer assessments in a large enrollment professional skills course at the University of Zagreb, faculty of Electrical engineering and computing are reported and discussed. The main research question of this work is how well, given specific conditions of the conducted summative peer assessments, do assignment credits assigned by peers correlate with assignment credits assigned by course lecturers. Data were obtained from four summative peer assessments through the course. A random sample of 50 submitted works per peer assessment was evaluated by course lecturers and corresponding assignment credits were compared to assignment credits awarded by students. Data analysis results suggest a moderate to high correlation between several measures of assignment credits awarded by peers and lecturers. © 2022 SEFI 2022 - 50th Annual Conference of the European Society for engineering Education, Proceedings. All rights reserved.

关键词： Grading

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An Exploratory Study of Diverse Models and Datasets for Transfer Learning based Image Classification on Sparse Data 10

An Exploratory Study of Diverse Models and Datasets for Tran...

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10th International Multidisciplinary engineering Research Conference on Moratuwa engineering Research, MERCon 2024

作者： Pathmarasa, Jathurshan Wijenayake, Udaya Wijesinghe, Ruchire Eranga Silva, Bhagya Nathali University of Sri Jayewardenepura Faculty of Engineering Department of Computer Engineering Nugegoda Sri Lanka Sri Lanka Institute of Information Technology Faculty of Engineering Department of Electrical and Electronic Engineering Malabe Sri Lanka Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Department of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798331529048

Transfer learning is a powerful technique for image classification, especially when dealing with limited data. However, selection of the best transfer learning approach and model remains challenging, since the strategy is highly influenced by the scenario. This work conducted a thorough analysis of four transfer learning approaches for binary classification, and multiclass classification using four pretrained models i.e. MobileNetV2, MobileNetV3Large, EfficientNetB0, and EfficientNetB5. The test accuracy was measured with respect to the sample size considering the effects of data augmentation and fine tuning. The key finding of the study revealed that data augmentation has improved the test accuracy by up to 11.8%. Moreover, the lightweight models marked a breakthrough by outperforming large scale models' accuracy for sparse data settings when fine tuning (FT) and data augmentation (DA) are applied appropriately. Hence, this work provides a comprehensive overview on selecting different transfer learning approaches for sparse data classification by exploring diverse models and datasets, while discussing the consequences and challenges for future real-world applications. © 2024 IEEE.

关键词： Data accuracy

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