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Enhancing the efficiency of cabin heaters in emergency shelters after earthquakes through an optimized fuzzy controller

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Building Simulation 2023年第9期16卷 1759-1776页

作者： Erkan Duman Dila Seckin Computer Engineering Department Engineering FacultyFirat UniversityElazig 23119Turkey

In just one and half minutes,more than fifty thousand died due to the 7.7 and 7.6 magnitude earthquakes that struck Turkey’s southeast on February 6,2023;thousands of families who barely escaped struggled to survive in the freezing weather.A warm shelter was the most basic requirement of these *** buildings are a rapid and easy solution to this ***,there is a need for a more effective and safe heating option than a wood fire for these *** this study,cabin heaters,which allow truck drivers to warm up when they park their vehicles to sleep,are specially optimized for emergency shelters after an *** optimized fuzzy controller was developed to use in such buildings,which allows an air–fuel ratio in the combustion chamber of the cabin heater to be controlled adaptively based on system dynamics to get lower carbon emissions and fuel *** TRNSYS software was used to establish the transient simulation model of a cabin heater with a capacity of 4 kW for a typical 21 m^(2) shelter building in Turkey’s cold *** developed fuzzy controller carried out the heating process of this shelter from the 15th of November to the 15th of *** of using expert knowledge,the Gray Wolf Optimization(GWO)method was applied to optimize the fuzzy controller parameters developed for the cabin *** the optimized fuzzy controller,the fuel consumption at the end of the heating season was reduced by an average of 0.2 L/h,and the cabin heater’s efficiency increased by more than 13%.Our simulation results show that the intelligent controller we developed could improve diesel fuel combustion efficiency by up to 85%.

关键词： parking heater cabin heater emergency shelters fuzzy controller gray wolf optimization TRNSYS simulation

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Predictive Analysis of Sarajevo's AQI using Machine Learning Models for Varied Data Granularity and Prediction Windows 47

Predictive Analysis of Sarajevo's AQI using Machine Learning...

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47th ICT and Electronics Convention, MIPRO 2024

作者： Zolota, Emina Hasić, Vahidin Mević, Amina Delić, Amra Krivić, Senka University Of Sarajevo Faculty Of Electrical Engineering Department For Computer Science And Informatics Sarajevo Bosnia and Herzegovina

ISBN: (纸本)9798350382495

This study scrutinizes five years of Sarajevo's Air Quality Index (AQI) data using diverse machine learning models - Fourier autoregressive integrated moving average (Fourier ARIMA), Prophet, and Long short-term memory (LSTM) - to forecast AQI levels. Focusing on various prediction frames, we evaluate model performances and identify optimal strategies for different temporal granularities. Our research unveils subtle insights into each model's efficacy, shedding light on their strengths and limitations in predicting AQI across varied timeframes. This research presents a robust framework for automatic optimization of AQI predictions, emphasizing the influence of temporal granularity on prediction accuracy, automatically selecting the most efficient models and parameters. These insights hold significant implications for data-driven decision-making in urban air quality control, paving the way for proactive and targeted interventions to improve air quality in Sarajevo and similar urban environments. © 2024 IEEE.

关键词： Air quality

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Fine-Tuning GPT-4o-Mini for Programming Questions Generation

Fine-Tuning GPT-4o-Mini for Programming Questions Generation

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2024 International Conference on computer and Applications, ICCA 2024

作者： Hesham, Alaa Hamdy, Abeer The British University in Egypt Faculty of Informatics and Computer Science Department of Software Engineering Cairo Egypt

ISBN: (纸本)9798350367560

Creating programming questions that are both meaningful and educationally relevant is a critical task in computer science education. This paper introduces a fine-tuned GPT4o-mini model (C2Q). It is designed to generate meaningful questions by leveraging semantic feature extraction and well- crafted prompts. The approach addresses the limitations of traditional generative models, offering a deeper understanding of programming code and producing questions that are precise, diverse, and relevant to a given code snippets. The proposed framework incorporates essential code elements, such as control structures and method attributes, to generate questions that align with programming concepts. Evaluation metrics used were BLEU, ROUGE-1, and ROUGE-L to evaluate the model's performance. The findings reveal that the model achieves better structural coherence and conceptual relevance while focusing on contextual understanding over exact term matching. This work highlights the potential of the proposed approach to advance teaching and assessment methods in computer science. © 2024 IEEE.

关键词： Program processors

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MTR Model-Based Testing Framework

Infocommunications Journal

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Infocommunications Journal 2024年第2期16卷 11-18页

作者： Németh, Gábor Árpád Lugosi, Máté István The Department of Computer Algebra Faculty of Informatics Eötvös Loránd University Budapest Hungary

In this article we propose a novel, free and open-source model-based testing framework for finite state machine specifications. The various model handling and test generation options make the framework suitable for testing complex systems and provide a solid background for investigating different automated test design methodologies. The complexity and fault detection capabilities of the available algorithms are investigated through analytical analyses and simulations applying randomly injected faults. © 2024 Scientific Association for Infocommunications. All rights reserved.

关键词： Model checking

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EXPLORING INFLUENTIAL FACTORS IN KNOWLEDGE SHARING WITHIN INDONESIAN PRISONS 22

EXPLORING INFLUENTIAL FACTORS IN KNOWLEDGE SHARING WITHIN IN...

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22nd International Conference on e-Society 2024, ES 2024 and 20th International Conference on Mobile Learning 2024, ML 2024

作者： Imandeka, Ejo Hidayanto, Achmad Nizar Suhartanto, Heru Pidanic, Jan Department of Computer Science Faculty of Computer Science University of Indonesia Depok Indonesia Department of Electrical Engineering Faculty of Electrical Engineering and Informatics Pardubice University Pardubice Czech Republic

The exchange of knowledge is widely recognized as a crucial aspect of effective knowledge management. When it comes to sharing knowledge within Prison settings, things get complicated due to various challenges such as limited resources, social stigma, isolation, communication barriers, and security concerns. Additionally, there's a scarcity of resources dedicated to promoting knowledge sharing in secure environments. This study aims to dig deep into the key factors that influence how knowledge is shared in Indonesian prisons. To navigate this intricate terrain, the study uses questionnaires distributed among Prison officers to understand the complex relationship between the identified critical factors and knowledge sharing in Prison. Leadership support, organizational culture, organizational structure, incentives, and individual beliefs emerge as pivotal elements in knowledge sharing. It's also noted that the connection between these critical factors and the intention to share knowledge is significantly influenced by organizational structure. Recognizing and addressing critical factors in knowledge sharing within prisons not only improves rehabilitation within prison walls but also transforms the broader criminal justice system. This approach fosters evidence-based practices, better communication, and a comprehensive understanding of factors leading to successful rehabilitation and reduced recidivism, ultimately creating a more just and effective system. © 2024 International Conferences e-Society 2024 and Mobile Learning 2024. All rights reserved.

关键词： Critical Factors Indonesia Knowledge Knowledge Sharing Prison

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A new architecture based resnet for steganography in color images

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Multimedia Tools and Applications 2025年第16期84卷 16229-16248页

作者： Hashemi, Seyed Hesam Odin Majidi, Mohammad-Hassan Khorashadizadeh, Saeed Faculty of Electrical and Computer Engineering University of Birjand Birjand Iran

This paper proposes a deep-learning color image steganography scheme that employs convolutional autoencoders with ResNet architecture. In the proposed method, all images are passed through the Preproccessing model which is a convolutional deep neural network with the aim of feature extraction. Then, the Operational model generates the stego or extracted image. The advantage of the proposed structure is the identity of models in the embedding and extraction phases. The performance of the proposed method is studied using COCO and CelebA datasets. For quantitative comparisons with previous related works, the peak signal-to-noise ratio (PSNR), the structural similarity index (SSIM), and hiding capacity are evaluated. The experimental results verify that the proposed scheme performs better than traditional and previous deep steganography methods. The PSNR and SSIM are more than 35dB and 0.98, respectively which implies the high imperceptibility of the proposed method. Also, the relative capacity of the proposed method is 8 bits per pixel. To assess the robustness of the proposed scheme against various steganalysis methods, we conducted histogram, difference, and stag analyses. The outcomes demonstrated that the proposed scheme could withstand different kinds of attacks. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Steganography

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Design of a Flux-Barrier Permanent Magnet Vernier Motor with a Flux Modulation Ring to Enhance Torque Production and Efficiency Factor

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International Journal of engineering, Transactions B: Applications 2025年第6期38卷 1369-1378页

作者： Imanifar, A. Yaghobi, H. Faculty of Electrical and Computer Engineering Semnan University Semnan Iran

Flux-barrier permanent magnet Vernier motors are among the latest magnetic motors developed and optimized in the industry. In these motors, the arrangement of magnets plays a critical role and significantly impacts on the torque density in the rotor-stator gap. This is because the motor's output torque increases with an enhancement of magnetic flux intensity in this gap. The magnetic gearbox effect in the flux-barrier permanent magnet Vernier motors, along with flux modulation, is one of the most critical factors in the design and construction of these motors. Flux modulation in the air-gap generates high torque at low speeds. In this study, inspired by the concept of magnetic gearboxes and by adding a modulation ring to the air-gap of this motor, a novel design for flux-barrier permanent magnet Vernier motors with a gearbox is presented. Using the two-dimensional finite element method (FEM), it has been demonstrated that the designed motor achieves significant improvements in average output torque and power factor compared to previous designs. ©2025 The author(s).

关键词： Permanent magnets

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Optimizing the operator’s cost function in UAV-assisted multi-tier cellular networks with underlaid D2D communications, an upper bound approach

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Journal of Ambient Intelligence and Humanized Computing 2025年 1-13页

作者： Pourmohammad Abdollahi, Mehran Azarhava, Hosein Musevi Niya, Javad Nangir, Mahdi Faculty Of Electrical And Computer Engineering University of Tabriz Tabriz Iran

The vast deployment of UAVs as base stations in 5 G and beyond, provides a facile accessibility to the users as an advantage and the flight constraints as deficiencies. In this work, we study a multi-tier cellular network with underlaid D2D communications in which the out-of-service Macrocell base station has been replaced by UAV and some Femtocell Base Stations (FBSs). The outage probabilities of attached users and the operator cost function are investigated considering the interference exacerbation in shared subchannels, different fading channels in Line-of-Sight and Non-Line-of-Sight situation of UAV. Closed-form expressions are achieved for the upper bound of outage probabilities and the operator cost function, considering the intensities of physical distributions of the FBSs and the outage probabilities of co-tier and cross tier interferences. The optimization problem is defined to minimize the cost function which is a non-convex problem over the resource allocation parameters. Thus, it is solved by separation into subproblems and the sub-optimal solution is achieved by proposed iterative algorithm. The represented simulation results verify the theoretical analysis and show that the proposed method outperforms the other approach. Likewise, increasing the density of the D2Ds increases the cost function more than the growth of number of Femtocell users. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Cost functions

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Valid-IoU: an improved IoU-based loss function and its application to detection of defects on printed circuit boards

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Multimedia Tools and Applications 2025年第14期84卷 13905-13928页

作者： Vakili, Elnaz Karimian, Ghader Shoaran, Maryam Yadipour, Reza Sobhi, Jafar Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran

The printed circuit boards (PCBs) should be inspected during the manufacturing process to minimize defects such as printing errors, incorrect component selections, and incorrect soldering. Convolutional neural networks (CNNs) have emerged as a powerful tool for this purpose, owing to their robust recognition capabilities. However, the accuracy of CNNs is significantly influenced by the choice of loss function. Intersection over Union (IoU) based loss functions commonly employed for bounding box regression, achieve remarkable success, but still have some main drawbacks such as inaccurate predicting bounding box dimensions relative to ground truth data. In this paper, we propose an improved IoU called Valid-IoU (VIoU) to solve this problem. We integrated the VIoU loss into state-of-the-art YOLO object detection frameworks to show its effectiveness in PCB defect detection. The experimental results on the HRIPCB PCB dataset demonstrate that the VIoU loss has high defect detection accuracy. Using YOLOv4 helped us to improve average accuracy, and with YOLOv8, we achieved faster detection speed compared to other methods. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Object detection

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Hybrid zk-STARK and zk-SNARK Framework for Privacy-Preserving Smart Contract Data Feeds

Hybrid zk-STARK and zk-SNARK Framework for Privacy-Preservin...

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2024 International Conference on computer and Applications, ICCA 2024

作者： Nassar, Seif T. Hamdy, Abeer Nagaty, Khaled Department of Computer Networks Faculty of Informatics and Computer Science Cairo Egypt

ISBN: (纸本)9798350367560

Decentralized applications (DApps) are increasingly using off-chain data, yet growing concerns about data privacy hinder their widespread adoption. Zero-knowledge proofs (ZKPs) have emerged as a solution to this problem. This paper proposes a novel hybrid framework that combines Zero-Knowledge Scalable Transparent Arguments of Knowledge (zk-STARKs) and Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge (zk-SNARKs) to deliver an efficient, scalable, quantum-resistant, and privacy-preserving ZKP system. The framework employs zk-STARKs' ability to handle large computations with quantum resistance and zk-SNARKs' succinct proofs and fast verification. The hybrid framework utilizes advanced arithmetization techniques to balance scalability, privacy, and security, including Algebraic Intermediate Representation (AIR) for zk-STARKs and Rank-1 Constraint Systems (RlCS) or PLONKish constraints for zk-SNARKs. The framework uses the Kate-Zaverucha-Goldberg (KZG) polynomial commitment scheme for reliability and transparency and eliminates trusted setup by using Discrete-logarithm-based Argument of Recursive Knowledge (DARK) commitments and Poseidon hashing. This paper details the construction of the hybrid proof system, analyzes its complexity, and explores its potential applications. The framework solves smart contract data feed limitations, security, efficiency, and scalability while prioritizing privacy. © 2024 IEEE.

关键词： Differential privacy

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