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arXiv 2019年

作者： Bondarenko, Valeria Filipova-Petrakieva, Simona Taralova, Ina Andreev, Desislav University of Beira Covilha Portugal Bulgarian Section Technical University of Sofia Bulgaria Department "Theory of Electrical Engineering" Faculty of Automation Sofia Bulgaria Laboratoire des Sciences du Numerique de Nantes Ecole Centrale de Nantes Nantes France Technical University of Sofia Bulgaria Department "Computer Science" Faculty of Computer Systems and Technologies "Advance Driver Assistance Systems" Company Visteon Electronics Bulgaria Sofia Bulgaria

In the present paper will be discussed the problem related to the individual household electric power consumption of objects in different areas - industry, farmers, banks, hospitals, theaters, hostels, supermarkets, universities. The main goal of the directed research is to estimate the active P and full S power consumptions for all studied buildings. The defined goal is achieved by solving of the following three problems. The first problem studies which buildings increase their power consumption. The second one finds which objects have the greatest increase of power consumption. And the third problem regards if it is possible to make a short-term forecast, based on the solutions of previous two problems. The present research and solving of the aforementioned problems is conducted using fractional Brownian motion theory. The applicability of this approach is illustrated on the example with 20 real objects in different areas. The paper ends with conclusion notes about possibilities to make short-term forecasts about power consumption of the considered buildings. Copyright © 2019, The Authors. All rights reserved.

关键词： Electric power utilization

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Availability factor of a PV power plant: evaluation based on generation and inverter running periods

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Energy Procedia 2018年 147卷 71-77页

作者： Nallapaneni Manoj Kumar Srikar Dasari Jagathpally Bhagwan Reddy Faculty of Electrical and Electronics Engineering Universiti Malaysia Pahang Pahang Pekan 26600 Malaysia Automation and Power Engineering Faculty of Electrical Engineering Media Engineering and Computer Science THD Technische Hochschule Deggendorf Edlmairstr Deggendorf 94469 Germany Department of Electrical and Electronics Engineering Nalla Malla Reddy Engineering College Ghatkesar Telangana 500 088 India

In a solar PV power plant, the plant availability factor is one of the important factors to be evaluated. This depends on the operative functioning of various components and grid regulation. In this paper, a simple method is proposed to evaluate the availability factors of a solar PV plant by considering the real time data of 1 MWp solar power plant that was commissioned in 2011 in south India. Generation start time, end time, and actual running periods of the inverter were selected as prominent data in the study. A consecutive five financial years of data (2011–2012; 2012–2013; 2013–2014; 2014–2015; 2015–2016) was used to observe the variations in availability factors of inverters, as well as the plant availability factors. From the analysis, it is observed that tripping time greatly effects the availability factor of inverter as well as the PV plant. The variation in availability factor over the five consecutive financial years is seen to be within the range of 92.44 % to 95.69 %. This clearly states that, on average 4.31 % to 7.56 %, the installed solar PV power is technically not generated any power. Hence, estimating the availability factor could be very much essential to deal with the performance of the PV systems and possible options of reducing energy losses due to availability factors could be suggested.

关键词： solar energy PV power plant inverter availability factor plant availability factor inverter outages PV plant generation periods

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An invisible DWT watermarking algorithm using noise removal with application to dermoscopic images

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Journal of Physics: Conference Series 2021年第1期1730卷

作者： S Moldovanu F A (Damian) Michis L Moraru Dunarea de Jos University of Galati Department of Computer Science and Information Technology Faculty of Automation Computers Sciences Electronics and Electrical Engineering 2 Stiintei Street RO-800210 Galati Romania Dunarea de Jos University of Galati Modelling & Simulation Laboratory Galati Romania Dunarea de Jos University of Galati Faculty of Science and Environment 111 Domneasca Street RO-800201 Galati Romania Department of Chemistry Physics and Environment Faculty of Sciences and Environment Dunarea de Jos University of Galati 47 Domneasca Street 800008 Galati Romania

A new approach for the digital watermarking process is proposed to be part of the pre-processing stage of a computer-aided diagnosis system. We propose to embed a denoised image acting as the watermark image in the original host image with the final goal of improving the quality of demoscopic images for further image processing operation related to CAD. The proposed algorithm uses Discrete Wavelet Transform (DWT) corroborated with some basic properties of Human Visual System such as Contrast Sensitive Function (CSF) and Noise Visibility Function (NVF) with the goal of correlating the texture properties and noise. This approach hides the watermark (i.e. denoised version of the host image) in high-pass subbands that are focused on image features. The main concern is to evaluate the distortion produced to the host image by watermarking and an objective quality measure function, i.e. Weighted Peak Signal-to-Noise Ratio (WPSNR), is used to evaluate the existing differences between the original and watermarked images. The proposed approach is tested using the available skin lesion images from the digital image archive of the Department of Dermatology of the University Medical Center Groningen. The experiment results show the improved performance of the proposed scheme against a 3 × 3 median filtering attack in comparison with the a 5 × 5 median filtering attack.

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Automated stroke lesion detection and diagnosis system

Automated stroke lesion detection and diagnosis system

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2017 International MultiConference of Engineers and computer Scientists, IMECS 2017

作者： Saad, N. Mohd Noor, N.S.M. Abdullah, A.R. Muda, Sobri Muda, A.F. Rahman, N. N. S. Abdul Center for Robotics and Industrial Automation Faculty of Electronics and Computer Engineering Universiti Teknikal Malaysia Melaka Malaysia Center for Robotics and Industrial Automation Faculty of Electronics and Computer Engineering Universiti Teknikal Malaysia Melaka Malaysia Center for Robotics and Industrial Automation Faculty of Electrical Engineering Universiti Teknikal Malaysia Melaka Malaysia Radiology Department Fakulti Perubatan dan Sains Kemanusiaan Universiti Putra Malaysia Malaysia Faculty for Electronics and Computer Engineering Universiti Teknikal Malaysia Melaka Malaysia Center for Robotics and Industrial Automation Faculty of Electronics and Computer Engineering Universiti Teknikal Malaysia Melaka Malaysia

ISBN: (纸本)9789881404732

This study proposes a technique for automated detection and diagnosis of stroke lesions based on diffusion-weighted imaging (DWI). The technique consists of several stages which are pre-processing, segmentation, feature extraction, and classification. The proposed analytical framework of this study is based on Fuzzy C-Means (FCM) segmentation, statistical parameters for features extraction and rule-based classification. The three-dimensional (3D) view is developed to enable observing directions of the gained 3D structure along the three axes. The segmentation results have been validated by using Jaccard and Dice indices, false positive rate (FPR), and false negative rate (FNR). The results for Jaccard, Dice, FPR and FNR of acute stroke are 0.7, 0.84, 0.049 and 0.205, respectively. The accuracy for acute stroke is 90% and chronic stroke is 70%, while the sensitivity and the specificity is 84.38% and 83.33%, respectively.

关键词： Extraction

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Benchmarking the CoW with the TopCoW Challenge: Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA

arXiv

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arXiv 2023年

作者： Yang, Kaiyuan Musio, Fabio Ma, Yihui Juchler, Norman Paetzold, Johannes C. Al-Maskari, Rami Höher, Luciano Li, Hongwei Bran Hamamci, Ibrahim Ethem Sekuboyina, Anjany Shit, Suprosanna Huang, Houjing Prabhakar, Chinmay de la Rosa, Ezequiel Waldmannstetter, Diana Kofler, Florian Navarro, Fernando Menten, Martin Ezhov, Ivan Rueckert, Daniel Vos, Iris Ruigrok, Ynte Velthuis, Birgitta Kuijf, Hugo Hämmerli, Julien Wurster, Catherine Bijlenga, Philippe Westphal, Laura Bisschop, Jeroen Colombo, Elisa Baazaoui, Hakim Makmur, Andrew Hallinan, James Wiestler, Bene Kirschke, Jan S. Wiest, Roland Montagnon, Emmanuel Letourneau-Guillon, Laurent Galdran, Adrian Galati, Francesco Falcetta, Daniele Zuluaga, Maria A. Lin, Chaolong Zhao, Haoran Zhang, Zehan Ra, Sinyoung Hwang, Jongyun Park, Hyunjin Chen, Junqiang Wodzinski, Marek Müller, Henning Shi, Pengcheng Liu, Wei Ma, Ting Yalçin, Cansu Hamadache, Rachika E. Salvi, Joaquim Llado, Xavier Estrada, Uma Maria Lal-Trehan Abramova, Valeriia Giancardo, Luca Oliver, Arnau Liu, Jialu Huang, Haibin Cui, Yue Lin, Zehang Liu, Yusheng Zhu, Shunzhi Patel, Tatsat R. Tutino, Vincent M. Orouskhani, Maysam Wang, Huayu Mossa-Basha, Mahmud Zhu, Chengcheng Rokuss, Maximilian R. Kirchhoff, Yannick Disch, Nico Holzschuh, Julius Isensee, Fabian Maier-Hein, Klaus Sato, Yuki Hirsch, Sven Wegener, Susanne Menze, Bjoern Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Center for Computational Health Zurich University of Applied Sciences Zurich Switzerland Department of Neuroradiology University Hospital of Zurich Zurich Switzerland Department of Neurosurgery Zhongnan Hospital of Wuhan University Wuhan China Department of Computing Imperial College London London United Kingdom Helmholtz Center Munich Germany Athinoula A. Martinos Center for Biomedical Imaging Harvard Medical School Boston United States School of Medicine Technical University of Munich Munich Germany Department of Informatics Technical University of Munich Munich Germany Helmholtz AI Helmholtz Munich Munich Germany Image Sciences Institute UMC Utrecht Utrecht Netherlands Department of Neurology UMC Utrecht Utrecht Netherlands Department of Radiology UMC Utrecht Utrecht Netherlands Department of Clinical Neurosciences Division of Neurosurgery Geneva University Hospitals Geneva Switzerland Department of Neurology University Hospital of Zurich Zurich Switzerland Department of Physiology University of Toronto Toronto Canada Department of Neurosurgery University Hospital of Zurich Zurich Switzerland Department of Diagnostic Imaging National University Hospital Singapore Department of Diagnostic and Interventional Neuroradiology University Hospital Berne University of Berne Berne Switzerland Montreal Canada Universitat Pompeu Fabra Barcelona Spain EURECOM Biot France Institute of Medical Technology Peking University Health Science Center Beijing China Hangzhou Genlight Medtech Co. Ltd. Hangzhou China Department of Artificial Intelligence Sungkyunkwan University Seoul Korea Republic of Department of Electrical and Computer Engineering Sungkyunkwan University Seoul Korea Republic of Shanghai MediWorks Precision Instruments Co. Ltd. Shanghai China Institute of Informatics HES-SO Valais-Wallis Switzerland Department of Measurement and Electronics AGH University

The Circle of Willis (CoW) is an important network of arteries connecting major circulations of the brain. Its vascular architecture is believed to affect the risk, severity, and clinical outcome of serious neuro-vascular diseases. However, characterizing the highly variable CoW anatomy is still a manual and time-consuming expert task. The CoW is usually imaged by two angiographic imaging modalities, magnetic resonance angiography (MRA) and computed tomography angiography (CTA), but there exist limited public datasets with annotations on CoW anatomy, especially for CTA. Therefore we organized the TopCoW Challenge in 2023 with the release of an annotated CoW dataset. The TopCoW dataset was the first public dataset with voxel-level annotations for thirteen possible CoW vessel components, enabled by virtual-reality (VR) technology. It was also the first large dataset with paired MRA and CTA from the same patients. TopCoW challenge formalized the CoW characterization problem as a multiclass anatomical segmentation task with an emphasis on topological metrics. We invited submissions worldwide for the CoW segmentation task, which attracted over 140 registered participants from four continents. The top performing teams managed to segment many CoW components to Dice scores around 90%, but with lower scores for communicating arteries and rare variants. There were also topological mistakes for predictions with high Dice scores. Additional topological analysis revealed further areas for improvement in detecting certain CoW components and matching CoW variant topology accurately. TopCoW represented a first attempt at benchmarking the CoW anatomical segmentation task for MRA and CTA, both morphologically and topologically. © 2023, CC BY-NC-ND.

关键词： Large datasets

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Home automation monitoring system based on Internet-of-Things application

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Journal of Physics: Conference Series 2020年第1期1502卷

作者： N. A. Ali A.R. Syafeeza A. S. Ja'afar Norihan Abdul Hamid Ts Saleha binti Mohamad Saleh Machine Learning and Signal Processing (MLSP) Research Group Centre for Telecommunication Research & Innovation (CeTRI) Faculty of Electronics and Computer Engineering (FKEKK) Universiti Teknikal Malaysia Melaka (UTeM) Melaka. Rehabilitation Engineering and Assistive (REAT) Research Group Centre for Robotics & Industrial Automation (CeRIA) Faculty of Electrical and Electronic Engineering Technology (FTKEE) Universiti Teknikal Malaysia Melaka (UTeM) Melaka.

The design of a smart green environment of home automation for appliances monitoring systems is developed based on an IoT(Internet of Things) application. The smart home concept represents a motivating platform for innovation of information technology services to produce more operative house devices and system that can improve the standard of life. This project aims at controlling home appliances via Smartphone using Wi-Fi as a communication protocol and the Raspberry Pi as a server system. The user here can move directly with the system through a web-based interface over the net. The designed system not solely monitors the sensor data but also actuates a process according to the need. Therefore, globally accessible automation of electronic appliances is created attainable with the utilization of a Raspberry Pi micro-controller board, a web affiliation and relay switches in a user-friendly way for the users to regulate home electronic appliances with high flexibility and security.

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Omparative study of growth rate evaluation for ash (Frasinus excelsior) in southeastern Romania 18

Omparative study of growth rate evaluation for ash (Frasinus...

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18th International Multidisciplinary Scientific Geoconference, SGEM 2018

作者： Murariu, Gabriel Murariu, Adrian Gabriel Barbuta-Misu, Nicoleta Vlad, Ciprian Marin, Ionuț-Dorin Faculty of Sciences and Environment Chemistry Physics and Environment Department "Dunărea de Jos" University of Galati Romania Imperial College London Physics Department Prince Consort Rd Kensington LondonSW7 2BB United Kingdom Faculty of Economics and Business Administration "Dunărea de Jos" University of Galati Romania Faculty of Automation Computer sciences Electronics and Electrical engineering Romania

ISBN: (纸本)9786197408355

At present, the monitoring of forest areas is a national requirement. The importance of protecting forests in mitigating climate change is well known. On the other hand, the economic aspects involving the efficiency of forest management imply correlation with the growing demand for wood on the market. From this point of view, the inventory and the evaluation of the rate of growth and yield of forest areas is extremely important. Estimating the growth rate per unit of hectare and the level of production of wooded areas for accurate obtaining and inventory is important in determining the supply of wood. The present paper is based on the evaluation of six ash (F. excelsior) growth seasons. The monitored sectors are located along areas with a relatively low altitude (280-450 m). The climatic gradient can also be neglected due to the nature of the studied areas. The research was conducted in the south-eastern part of Romania. The timeframe in which the study was conducted ranged from 2010 to 2015. Technological factors such as consistency, density, etc. were carefully assessed based on observations and field measurements in the field. The results obtained through numerical approaches have shown that: (1) estimates of the growth rate can vary significantly when using different statistical and numerical methods;(2) using numerical optimization models, computer simulations can provide accurate estimates of the growth rate and hence the effectiveness of a given forest inventory;(3) common methods of numerical interpolation or uses of neural networks that do not always yield acceptable results. © SGEM2018.

关键词： Interpolation

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Disaster management system

Disaster management system

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International Symposium on Electrical and electronics engineering (ISEEE)

作者： Gabriel Murariu Silviu Epure Dan Munteanu Ciprian Vlad Violeta Cornelia Domnitanu George Danut Mocanu Constantin Ionescu Razvan-Adrian Tudoran “Dunărea de Jos” University of Galati Romania Galati Romania Faculty of Automation Computer Sciences Electronics and Electrical Engineering “Dunărea de Jos” University of Galati Romania Galati Romania Faculty of Physical Education and Sport “Dunărea de Jos” University of Galati Romania Galati Romania National Institute for Earth Physics (NIEP) Călugăreni st no 12 Magurele Ilfov County Romania

ISBN: (数字)9781728129068

ISBN: (纸本)9781728129075

The project has as a priority to contribute to the intervention and implementation of an emergency plan in case of an earthquake, by developing a system of solutions that will ensure the continuity of the activity as follows: - Monitoring: evaluating the performance of the building or dangerous infrastructures in real time; - Alarm: offers alerts when the design parameters are exceeded and transforms the information into useful data; - Emergency interventions: implement rapid response procedures leading to decision-making measures; - Communication and Dissemination: manages the transmission of information that is imperative for making business continuity decisions. During an emergency situation, the faster the community resumes daily activity, the less the losses are reduced. The alarm system transforms a building system into a network of infrastructures monitored in the case of seismic events. The two-way collective information offers a complete picture of the earthquake effect, followed by the road to the previous activity or restoration. The conclusion will be to avoid unnecessary evacuations, stopping work processes and minimizing response times, stress and reducing panic. The proposed solution to ensure continuity of activity in the event of an earthquake, must be available on the desktop and smartphone.

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Personal seismograph system - a functional prototype

Personal seismograph system - a functional prototype

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International Symposium on Electrical and electronics engineering (ISEEE)

作者： Gabriel Murariu Ciprian Vlad Dan Munteanu George Danut Mocanu Silviu-Nicolae Iancu Violeta Cornelia Domnitanu Constantin Ionescu Razvan-Adrian Tudoran Silviu Epure “Dunaărea de Jos” University of Galati Romania Galati Romania Faculty of Automation Computer Sciences Electronics and Electrical Engineering “Dunărea de Jos” University of Galati Romania Galati Romania Faculty of Physical Education and Sport “Dunărea de Jos” University of Galati Romania Galati Romania National Institute for Earth Physics (NIEP) Călugăreni st no 12 Magurele Ilfov County Romania

ISBN: (数字)9781728129068

ISBN: (纸本)9781728129075

Disaster management system consists of administrative policies, decisions and operational activities that are linked to various stages of disasters at all levels. With the passing of the years and the evolution of the society, it can be noticed that the extreme phenomena are becoming more and more numerous. About 90% of all disaster victims belong to poor countries or areas where the seismic risk is very high. The current interest is to monitor and evaluate these natural phenomena more closely in order to reduce losses. This work is intended to show the functioning of a seismograph system implementation being done on a Raspberry model 3B + development board together with a mpu6050 accelerometer-gyroscope module. The information recorded by the mpu 6050 module will be analyzed and stored in a database. of graph. Every vibration felt by the accelerometer-gyroscope module will send an SMS alert to the mobile phone through an IFTTT service. The notification will contain the type of produced earthquake according to the magnitude (minor, light, moderate, strong) as well as its classification in a number of degrees on the Richter scale and the time of its production. In this way, a database can be created for a more accurate assessment of the intensity distribution of the recorded earthquake.

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Large margin multi-modal multi-task feature extraction for image classification

arXiv

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arXiv 2019年

作者： Luo, Yong Wen, Yonggang Tao, Dacheng Gui, Jie Xu, Chao School of Electronics Engineering and Computer Science Peking University Beijing China Division of Networks and Distributed Systems School of Computer Engineering Nanyang Technological University Singapore Centre for Quantum Computation & Intelligent Systems Faculty of Engineering & Information Technology University of Technology Sydney Sydney Australia Centre for Quantum Computation & Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney 81 Broadway Street UltimoNSW2007 Australia Hefei Institute of Intelligent Machines Chinese Academy of Sciences Hefei230031 China Center for Research on Intelligent Perception and Computing National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing100190 China

The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task feature extraction approaches, which often outperform single-task feature extraction approaches. However, most of these methods are limited in that they only consider data represented by a single type of feature, even though features usually represent images from multiple modalities. We therefore propose a novel large margin multi-modal multi-task feature extraction (LM3FE) framework for handling multi-modal features for image classification. In particular, LM3FE simultaneously learns the feature extraction matrix for each modality and the modality combination coefficients. In this way, LM3FE not only handles correlated and noisy features, but also utilizes the complementarity of different modalities to further help reduce feature redundancy in each modality. The large margin principle employed also helps to extract strongly predictive features so that they are more suitable for prediction (e.g., classification). An alternating algorithm is developed for problem optimization and each sub-problem can be efficiently solved. Experiments on two challenging real-world image datasets demonstrate the effectiveness and superiority of the proposed method. Copyright © 2019, The Authors. All rights reserved.

关键词： Feature extraction

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