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IEEE International Conference on automation, Quality and Testing, Robotics, AQTR

作者： Claudiu Bâlc Alexandru Cretu Dan Iudean Horaţiu Laslo Szilárd Enyedi Radu Munteanu Faculty of Electrical Engineering Technical University of Cluj-Napoca Cluj-Napoca Romania Faculty of Automation and Computer Science Technical University of Cluj-Napoca Cluj-Napoca Romania

An Automatic Level Control System is an important process that needs to be properly designed and monitored in order to determine and eliminate the critical failures that could result in the loss of the system. Water resource availability is an important problem and in a water distribution process the level and flow must be always known and monitored to keep the system running at full capacity and with minimal disruptions. If the systems are properly designed and the critical failures eliminated the process availability increases considerably. This paper presents a Failure Modes and Effects Analysis for an automatic level control system. This analysis gives an overview on the critical components of the system.

关键词： Level control Reliability Standards Sensor systems Manufacturing processes Process control

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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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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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RF chain reduction for MIMO systems: A hardware prototype

arXiv

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arXiv 2019年

作者： Gong, Tierui Shlezinger, Nir Ioushua, Shahar Stein Namer, Moshe Yang, Zhijia Eldar, Yonina C. State Key Lab of Robotics Key Lab of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel School of Electrical Engineering Tel Aviv University Tel Aviv Israel Faculty of Electrical Engineering Technion Haifa Israel

RF chain circuits play a major role in digital receiver architectures, allowing passband communication signals to be processed in baseband. When operating at high frequencies, these circuits tend to be costly. This increased cost imposes a major limitation on future multiple-input multiple-output (MIMO) communication technologies. A common approach to mitigate the increased cost is to utilize hybrid architectures, in which the received signal is combined in analog into a lower dimension, thus reducing the number of RF chains. In this work we present a hardware prototype implementing analog combining for RF chain reduction. The prototype consists of a specially designed configurable combining board as well as a dedicated experimental setup. Our hardware prototype allows to evaluate the effect of analog combining in MIMO systems using actual communication signals. The experimental study, which focuses on channel estimation accuracy in MIMO channels, demonstrates that using the proposed prototype, the achievable channel estimation performance is within a small gap in a statistical sense from that obtained using a costly receiver in which each antenna is connected to a dedicated RF chain. Furthermore, in the considered scenarios, this gap becomes negligible when the reduction rate, i.e., the ratio of the number of RF chains to the number of antennas, is above 62.5%. Copyright © 2019, The Authors. All rights reserved.

关键词： Channel estimation

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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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Influence of CNC milling strategies on complex surface machining

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IOP Conference Series: Materials Science and engineering 2020年第1期776卷

作者： T Dodok N Čuboňová M Císar V Ivanov D Wiecek Department of Automation and Production systems Faculty of Mechanical Engineering University of Žilina Univerzitná 1 010 26 Žilina Slovak Republic Department of Manufacturing Engineering Machines and Tools Sumy State University 2 Rymskogo-Korsakova St. Sumy 40007 Ukraine Faculty of Mechanical Engineering and Computer Science University of Bielsko-Biala ul. Willowa 2 43-309 Bielsko-Biała Poland

Milling strategies are an integral part of CAD/CAM systems. Every CAD/CAM system offers unique strategies to differentiate itself from the competition. The article deals with analysis of CNC milling strategies in CAD/CAM system Edgecam 2017 R2. Analysis is divided into two parts. In first part are analysed roughing strategies with focus based on time necessary for removal of material. Second part is focused on finishing strategies and achieving the highest quality of surface. In conclusion, the article deals with the analysis of existing milling strategies and the creation of a database for the assignment of optimal roughing and finishing strategies for specified components.

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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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Progressive LiDAR adaptation for road detection

arXiv

引用

arXiv 2019年

作者： Chen, Zhe Zhang, Jing Tao, Dacheng UBTECH Sydney Artificial Intelligence Centre School of Computer Science Faculty of Engineering and Information Technologies University of Sydney 6 Cleveland St DarlingtonNSW2008 Australia School of Software and Advanced Analytics Institute University of Technology Sydney 15 Broadway UltimoNSW2007 Australia School of Automation Hangzhou Dianzi University

Despite rapid developments in visual image-based road detection, robustly identifying road areas in visual images remains challenging due to issues like illumination changes and blurry images. To this end, LiDAR sensor data can be incorporated to improve the visual image-based road detection, because LiDAR data is less susceptible to visual noises. However, the main difficulty in introducing LiDAR information into visual image-based road detection is that LiDAR data and its extracted features do not share the same space with the visual data and visual features. Such gaps in spaces may limit the benefits of LiDAR information for road detection. To overcome this issue, we introduce a novel Progressive LiDAR Adaptation-aided Road Detection (PLARD) approach to adapt LiDAR information into visual image-based road detection and improve detection performance. In PLARD, progressive LiDAR adaptation consists of two subsequent modules: 1) data space adaptation, which transforms the LiDAR data to the visual data space to align with the perspective view by applying altitude difference-based transformation;and 2) feature space adaptation, which adapts LiDAR features to visual features through a cascaded fusion structure. Comprehensive empirical studies on the well-known KITTI road detection benchmark demonstrate that PLARD takes advantage of both the visual and LiDAR information, achieving much more robust road detection even in challenging urban scenes. In particular, PLARD outperforms other state-of-the-art road detection models and is currently top of the publicly accessible benchmark leader-board. Copyright © 2019, The Authors. All rights reserved.

关键词： computer vision

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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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Simulation of wood biomass combustion in hot water boiler

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IOP Conference Series: Materials Science and engineering 2020年第1期776卷

作者： I Klačková I Zajačko R Lenhard I Gritsuk D Wiecek Department of Automation and Production systems Faculty of Mechanical Engineering University of Žilina Univerzitná 1 010 26 Žilina Slovak Republic Department of Power Engineering Faculty of Mechanical Engineering University of Žilina Univerzitná 1 010 26 Žilina Slovak Republic Center RUDN University 117198 Moscow Miklukho-Maklaya str.6 Moscow Russia Faculty of Mechanical Engineering and Computer Science University of Bielsko-Biala ul. Willowa 2 43-309 Bielsko-Biala Poland

Calculation methods based on finite volume methods (CFD method) have proven to be very useful in optimizing (efficiency, emission) heat sources for wood burning. Such heat sources also include gasification hot-water boilers for the combustion of dry wood. One of the important parts of the entire process of converting the primary energy contained in the fuel to the transfer of heat to the heat carrier is the gasification of the fuel in the feed chamber and the subsequent burning of wood gas. The paper presents CFD simulation of wood gasification process in the filling chamber and subsequent burning of wood gas on a model heat source. As a model heat source, was selected a hot-water boiler with lower fuel firing with a flue gas-water heat exchanger tubular heat exchanger. It is a gasification hot water boiler for the combustion of dry wood. The interior of the boiler consists of a filling chamber where the fuel is dried and fused. The wood gas then passes through the nozzle to the combustion chamber, where it burns with the aid of secondary air. The flue gases pass their heat in the heat exchanger through the walls of the pipes into the water.

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