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IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications

作者： Mihaela-Gabriela Boicu Ioana Făgărăşan Grigore Stamatescu Mihaela Vasluianu Cosmin-Florin Fudulu Marius-Alexandru Dobrea Faculty of Automatic Control and Computer Science University POLITEHNICA of Bucharest Romania Faculty of Hidrotechnics Technical University of Civil Engineering of Bucharest Romania

The paper presents a method of assessing thermal comfort in office rooms, using data collected from Fitbit bracelets. The result is a fuzzy system for the level of thermal comfort that wants to meet two objectives: reducing the energy consumption in the building and fulfilling the thermal comfort for the occupants. The representative factors taken into account in this study are: air temperature, relative humidity, user activity, clothing level and skin temperature. The proposed fuzzy system was modeled and simulated in the Matlab/SIMULINK development environment, showing satisfactory results after the analysis of the data taken over a period of several days.

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Energy-independent solution using a medium-power wind turbine to ensure the irrigation deficit in an isolated agricultural areal

Energy-independent solution using a medium-power wind turbin...

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International Conference on control Systems and computer Science (CSCS)

作者： Cosmin-Florin Fudulu Ioana Fagarasan Mihaela Gabriela Boicu Mihaela Vasluianu Marius - Alexandru Dobrea Giorgian Neculoiu Faculty of Automatic Control and Computer Science University POLITEHNICA of Bucharest Romania Faculty of Hidrotechnics Technical University of Civil Engineering of Bucharest Romania

Smart agricultural systems require irrigation systems powered by renewable energy sources that are also adaptable for isolated areas without connection possibility to the electricity network or the water network. For such situations, in this paper, a solution is proposed using a wind turbine and a submersible pump to feed a water basin, subsequently irrigation is done by free fall. The developed solution is designed and simulated using a model of a medium-power wind turbine, and a battery storage element with the aim of providing the necessary electricity for irrigation of an agricultural area in Buzau, where there is a water deficit.

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Description and comparison of fault detection algorithms based on a selected building automation device

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Bulletin of the Polish Academy of Sciences: Technical Sciences 2025年第3期73卷

作者： Wlostowska, Sandra Kawa, Bartlomiej Borkowski, Piotr Department of Electrical Apparatus Faculty of Electrical Electronics Computer and Control Engineering Lodz University of Technology Lódź Poland

The article compares selected classification algorithms and those dedicated to anomaly detection. The models used temperature measurements in four rooms simulated in the MATLAB Simscape environment as test signals. The empirical part of the work consists of two parts. In the first one, an example data from the simulated building heating model object, models were built using unsupervised and supervised machine learning algorithms. Then, data from the facility was collected again with changed parameters (failures occurred at times other than the test ones, and the temperature patterns differed from those recorded and used to train the models). The algorithm effects and test signals (temperature changes) were saved in the database. The results were presented graphically in the Grafana program. The second part of the work presents a solution in which the analysis of the operating status of the heating system takes place in real time. Using an OPC server, data was exchanged between the MATLAB environment and the database installed on a virtual machine in the Ubuntu system. The conclusions present the results and collect the authors’ suggestions regarding the practical applications of the discussed classification models. © 2025 The Author(s).

关键词： Support vector machines

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Energy Efficient IoT Air Quality Monitoring System

Energy Efficient IoT Air Quality Monitoring System

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International Conference on control Systems and computer Science (CSCS)

作者： Silvian-Marian Petrică Ioana Făgărăşan Nicoleta Arghira Iulia Stamatescu Giorgian Neculoiu Oana Flangea Faculty of Automatic Control and Computer Science University POLITEHNICA of Bucharest Romania Faculty of Hidrotechnics Technical University of Civil Engineering of Bucharest Romania

Air pollution is one of the major environmental issues discussed lately due to its influence on human health. Particular attention is paid to air quality monitoring today and most developed societies have implemented weather and air quality monitoring stations in various locations inside or outside cities to monitor and reduce the effects of poor air quality. Modern standards and sensors have started to be used in recent years to monitor air quality. Conventional air quality monitoring systems, on the other hand, are not able to provide real-time air quality data with acceptable spatial and temporal resolutions at a low cost, so the challenge is to achieve low-cost and energy-independent solutions. Using modern technologies, e.g. Internet of-things (IoT), an original approach is proposed for building an air quality monitoring system considering low cost equipment and efficient energy autonomous approach. Smart cities have successfully implemented air quality monitoring systems that combine both hardware and software. The results presented in the paper show the viability of the proposed solution, exposing the designed solution and different ways of presenting air quality monitoring.

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Secure transmission of medical image using a wavelet interval type-2 TSK fuzzy brain-imitated neural network

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Soft Computing 2025年第4期29卷 2311-2329页

作者： Pham, Duc-Hung Huynh, Tuan-Tu Lin, Chih-Min Giap, Van Nam Vu, Van-Phong Department of Electrical Engineering Yuan Ze University No. 135 Yuandong Road Zhongli 320 Taoyuan Taiwan Faculty of Electrical and Electronic Engineering Hung Yen University of Technology and Education Hai Duong160000 Viet Nam Faculty of Mechatronics and Electronics Lac Hong University No. 10 Huynh Van Nghe Road810000 Bien Hoa Dong Nai Viet Nam School of Electrical & Electronic Engineering Hanoi University of Science and Technology Hai Ba Trung Hanoi100000 Viet Nam Department of Automatic Control Ho Chi Minh City University of Technology and Education Ho Chi Minh70000 Viet Nam

The purpose of this research is to develop a new design of a wavelet interval type-2 takagi–Sugeno-Kang fuzzy brain-imitated neural network (WIT2TFBINN), which is a combination of the mathematical models of a Takagi–Sugeno-Kang (TSK) fuzzy system based on wavelet interval type-2 function (WIT2) and a wavelet interval type-2 fuzzy brain imitated neural network (FBINN). The proposed WIT2TFBINN is used for synchronization control of a 4D Lorentz chaotic system and has the benefits of wavelet interval type-2 membership function, TSK fuzzy inference system, decision making, and emotional activity. To provide fast training, the proposed method's parameter update laws are derived using the gradient descent method. The proposed WIT2TFBINN synchronization technique is then applied to the transmission of medical images in a secure manner. As a cipher image, a medical image is encrypted into a chaotic trajectory. After transmission, the image can be decrypted using chaotic trajectory synchronization on the received signal. The simulation results show that the proposed neural network and the encryption/decryption method are powerful and effective. The results of the static test analysis (histogram, attack analysis, image with noise, image with cropping) show that the encryption/decryption method provides high security. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Membership functions

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Decision System for Ensuring Thermal Comfort of Occupants in a Smart Building

Decision System for Ensuring Thermal Comfort of Occupants in...

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International Conference on control Systems and computer Science (CSCS)

作者： Mihaela - Gabriela Boicu Grigore Stamatescu Cosmin - Florin Fudulu Marius - Alexandru Dobrea Mihaela Vasluianu Giorgian Neculoiu Faculty of Automatic Control and Computer Science University POLITEHNICA of Bucharest Romania Faculty of Hidrotechnics Technical University of Civil Engineering of Bucharest Romania

This paper presents the development of a system that uses fuzzy logic in order to evaluate the thermal comfort conditions expressed by means of a score by the occupants of an office room The inputs of the system are represented by three datasets relevant to the study: the air temperature, the positioning of the occupant and the level of activity carried out by the occupant. Based on the comfort score obtained, the HVAC system located at the room level will maintain a comfortable environment. The proposed solution also contributes to the minimization of energy consumption in buildings. In order to collect the data sets necessary for the study, we used the *** module as a wearable device.

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Evaluation of Theoretical and Empirical Log-Normal Models for Wi-Fi Fingerprint Mapping in Indoor Positioning

Evaluation of Theoretical and Empirical Log-Normal Models fo...

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IEEE International Conference on Artificial Intelligence in engineering and Technology (IICAIET)

作者： Mohamed Aizad Bin Mohamed Ghazali Aroland Kiring Lyudmila Mihaylova Hoe Tung Yew Seng Kheau Chung Yan Yan Farm Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Sabah Malaysia Department of Automatic Control and System Engineering University of Sheffield Sheffield UK

ISBN: (数字)9798350389692

ISBN: (纸本)9798350389708

This paper evaluates both the theoretical and empirical log-normal models for Wi-Fi fingerprint mapping in indoor positioning systems. Wi-Fi fingerprinting, leveraging the ubiquitous IEEE 802.11 protocol, offers a practical solution for indoor localization where Global Positioning System (GPS) is ineffective. It involves generating empirical data by systematically measuring Wi-Fi Received Signal Strength (RSS) within a complex indoor environment and formulating a log-normal path loss model to predict signal behavior. A comparative analysis was conducted between the theoretical model, calibrated with empirical RSS data, and the actual RSS measurements. The results showed that while the theoretical model captured overall signal propagation trends, the empirical data revealed variations due to multipath effects and environmental obstacles. It demonstrated the practical use of Wi-Fi fingerprint mapping, theoretical modeling, and comparative analysis. The findings underscore the importance of empirical validation in refining theoretical models and optimizing deployment strategies for accurate and reliable indoor positioning. Future research should focus on mitigating multipath effects and enhancing the theoretical model accuracy through optimized access point (AP) placement and advanced signal processing techniques.

关键词： Analytical models Accuracy Fingerprint recognition Signal processing Reliability theory Market research Data models Mathematical models Wireless fidelity Global Positioning System

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Automated Assessment of Medical Rehabilitation of Gait by Means of Video Processing in Cloud Environment

Automated Assessment of Medical Rehabilitation of Gait by Me...

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E-Health and Bioengineering Conference (EHB)

作者： Elena-Claudia Maftei Otilia Zvorişteanu Hariton-Nicolae Costin Silviu Bejinariu Florin Rotaru Vasile Manta Ramona Luca Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iaşi Institute of Computer Science Romanian Academy Iaşi Branch Iaşi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Human gait analysis provides qualitative and quantitative information concerning different characteristics of walking of a certain person. Cloud computing proves to be a modern and valuable technology when dealing with data scalability, security and efficiency of processing and storage. Also, this paradigm has some key-benefits like real-time data sharing, fast computation as well as collaborative research. The applications gamut which uses cloud computing is getting bigger and bigger, and healthcare sector is an important domain in this respect. Our approach proposed a cloud-based service designed for the automated assessment of medical rehabilitation of human gait by using video processing. We have chosen this processing technology because it is marker-less, allows fast computation and offers a very good precision of the gait analysis. Cloud computing approach proved to be encouraging and underscores remarkable advantages in comparison with traditional on-site video processing. In this way the patient, after a short training session, can himself/herself make tests and assessments of his/her mobility status, avoiding many consultations of medical or kineto-therapeutic staff.

关键词： Legged locomotion Training Cloud computing Scalability Medical services Gain measurement People with disabilities Real-time systems Security Personnel

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Super Resolution of Unpaired MR Images Based on Domain Migration 18th

Super Resolution of Unpaired MR Images Based on Domain Migra...

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18th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2022

作者： Liu, Xiaodong Guo, Haipeng Liu, Huanyu Department of Automatic Test and Control School of Electronics and Information Engineering Harbin Institute of Technology Harbin150080 China Information Countermeasure Technique Institute School of Computer Science and Technology Harbin Institute of Technology Harbin150080 China

ISBN: (纸本)9789819901043

High-resolution magnetic resonance imaging (MRI) is very important for doctors to judge the condition. At present, the depth learning method has been widely studied in the super-resolution reconstruction of MR images. However, due to the distribution difference between the real low-resolution MR images and the down sampled MR images used to train the super-resolution model under experimental conditions, the super-resolution performance of the super-resolution method is often seriously degraded when super-resolution is applied to the real low-resolution MR images. Blind super-resolution methods used to solve such problems in natural image super-resolution are lack of image content constraints. It is not advisable to introduce additional information that will interfere with doctors’ diagnosis in the super-resolution process of MR images. These two problems hinder the application of super-resolution method in real MR images. In order to solve these problems, an unpaired MR image super-resolution network based on domain migration is proposed. The proposed DMN can use a real set of low to high-resolution unpaired MR images as input, migrate the real low-resolution MR images to the down sampled MR image domain, and then super-resolution reconstruction is carried out through the paired super-resolution network obtained through supervision training. Experiments on fast MRI datasets verify the effectiveness of this method in solving the super-resolution problem of real MR images. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Magnetic resonance imaging

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KartalOl: a new deep neural network framework based on transfer learning for iris segmentation and localization task—new dataset for iris segmentation

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Iran Journal of computer Science 2023年第4期6卷 307-319页

作者： Khiarak, Jalil Nourmohammadi Oskouei, Amin Golzari Nasab, Samaneh Salehi Jaryani, Farhang Moafinejad, Seyed Naeim Pourmohamad, Rana Amini, Yasin Noshad, Morteza Institute of Control and Computation Engineering Warsaw University of Technology Ul. Nowowiejska 15/19 Warsaw 00-665 Poland Department of Computer Engineering Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran School of Engineering Lorestan University Aleshtar Campus Aleshtar Iran Faculty of Engineering Arak University Arak Iran Department of Physics Shahid Beheshti University Tehran Iran School of Computing Informatics and Decision Systems Engineering Arizona State University AZ United States Faculty of Electrical and Computer Engineering University of Kharazmi Tehran Iran Stanford University Stanford United States

Iris segmentation and localization in unconstrained environments are challenging due to long distances, illumination variations, limited user cooperation, and moving subjects. Some existing methods in the literature have somehow mitigated some of the above-mentioned issues. In this paper, motivated by these weaknesses, we propose a framework that employs a deep neural network-based approach to iris segmentation and localization. The proposed framework is based on a U-Net architecture initialized with a pre-trained MobileNetV2 model. In addition, to better study the detectors in iris recognition scenarios, we have collected 1000 images. The provided dataset (KartalOl) is made publicly available for the research community. In the proposed framework, to have better generalization, we fine-tuned the MobileNetV2 model on the provided data for NIR-ISL 2021 from the CASIA-Iris-Asia, CASIA-Iris-M1, and CASIA-Iris-Africa and our dataset. Likewise, data augmentation techniques are applied on images. We chose the binarization threshold for the binary masks by iterating over the images in the provided dataset. The proposed framework is trained and tested in CASIA-Iris-Asia, CASIA-Iris-M1, and CASIA-Iris-Africa, along with the KartalOl dataset. The experimental results highlight that our method surpasses state-of-the-art methods on mobile-based benchmarks. The implementation source code of KartalOl is made publicly available at https://***/Jalilnkh/KartalOl-NIR-ISL2021031301. © The Author(s) 2023.

关键词： Iris segmentation Localization MobileNetV2 model Unconstrained environment

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