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International Conference on control Systems and computer science (CSCS)

作者： Andrei C. Nae Ioan Dumitrache Faculty of Automatic Control and Computer Science University Politehnica Bucharest Bucharest Romania

This work is based on the implementation of new concepts for adaptive traffic signal controller using a neurofuzzy system approach and simulations on reference test cases. In our neuro-fuzzy controller, the parameters of the fuzzy membership functions are adjusted using a neural network. The neural learning algorithm may then be considered as reinforcement learning. However, the major difficulty for this neuro-fuzzy system under consideration is such that the most usual neural learning algorithms cannot be used. A specific learning algorithm is proposed to be used both for constant traffic volumes and also for changing volumes. Starting from the initial membership functions, the learning algorithm modifies the parameters of the membership functions in different ways at different but constant traffic volumes. The membership functions after the proposed learning algorithm produce smaller delays than the initial membership functions. An additional contribution is for specific changes in the rule base of the fuzzy traffic signal controller in order to reduce delays in various traffic volumes conditions in a test/reference traffic junction.

关键词： Neurons Fuzzy logic Adaptation models Training Artificial neural networks Junctions Adaptive systems

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Hierarchical Processing of Signals for Smart Crop Monitoring*

Hierarchical Processing of Signals for Smart Crop Monitoring...

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International Conference on Systems and control (ICSC)

作者： Dan Popescu Loretta Ichim Florin Stoican Cristian Dragana Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Bucharest Romania

Smart crop monitoring is a new concept for different modern agricultural research and production management. The paper presents a hierarchical structure of data processing from the sensors used in crop monitoring. The proposed system consists in the integration of multi WSN network at ground level, a team of UAVs at aerial level, with the mission of both direct data acquisition and data collecting from WSN. The information from UAV is next transmitted to a central data analysis and interpretation via internet. To this end, a multi levels data processing structure is proposed: in field processing, fog computing processing and cloud computing processing. The design of an efficient UAV trajectory for collecting of data and obstacle avoidance and, also, a model of intelligent data processing and transmission are proposed.

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UAV to Satellite Communication Systems

UAV to Satellite Communication Systems

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Radio and Antenna Days of the Indian Ocean (RADIO)

作者： Gabriel Militaru Dan Popescu Loretta Ichim Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Bucharest Romania

Integrating innovative technologies in terrestrial-satellite networks are needed to enable Unmanned Aerial Vehicles (UAV) application developers to achieve better results and optimize solutions. Managing a complex UAV - Satellite modem integration process, the authors of this study have performed a series of measurement of throughput and latency time to evaluate the feasibility of the Satellite communication system for remote control and command of a distant UAV.

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Color Texture Classification Combining LBP Images and Fractal Features

Color Texture Classification Combining LBP Images and Fracta...

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IEEE Conference on Cybernetics and Intelligent Systems

作者： Jan-Iliuţă-Romeo Cojocaru Dan Popescu Loretta Ichim Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Bucharest Romania

ISBN: (数字)9781728134581

ISBN: (纸本)9781728134598

This paper describes a color texture classification scheme that uses fractal features like: box-counting fractal dimension and differential box-counting fractal dimension. Color textured images can be represented on multiple color spaces and recent developments for color texture analysis and classification are increasing. Following this concept, a texture image is obtained using Local Binary Pattern whereupon fractal features are extracted from it. For testing this color texture classification scheme two datasets (BarkTex and VisTex) are used, and the results are compared with three other methods. We propose a modified formula for calculating the Local Binary Pattern of a color textured image and advance the algorithm for this technique. The fractal features prove to be suitable in the classification process and the accuracy rates we had obtained are close to state-of-the-art approaches using a much smaller feature space.

关键词： Image color analysis Fractals Feature extraction Classification algorithms Binary codes Color Support vector machines

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Trajectory Design for Effective and Secure Communication in UAV-WSN Systems

Trajectory Design for Effective and Secure Communication in ...

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Radio and Antenna Days of the Indian Ocean (RADIO)

作者： Florin Stoican Dan Popescu Loretta Ichim Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Bucharest Romania

Nowadays, unmanned aerial vehicles (UAVs) and wireless sensor networks (WSNs) are often integrated in collaborative systems for data collection. In this paper, a specific UAV trajectory design for effective and secure data collection from ground sensors is presented. Depending of the amount of data and radio communication characteristics, two types of trajectory are designed: segment tracking and loitering in a circle around the WSN cluster head.

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Real time Image Recognition Based on low cost Processing Platform

Real time Image Recognition Based on low cost Processing Pla...

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International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Service (TELSIKS)

作者： Diana Baicu Mihai Crăciunescu Ştefan Mocanu Maria Cîrciumaru Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Bucharest Romania

ISBN: (数字)9781728108780

ISBN: (纸本)9781728108797

In this paper, the traffic sign recognition module of a small-scale autonomous car prototype will be presented. The process undergoing the choice of an appropriate algorithm, as well as the factors taken into consideration will be presented in the form of a case study. The current literature presents various ways of achieving the recognition of traffic signs, but most of them are computational expensive, or have difficulty in offering consistent results in conditions that are different from the prerecorded ones. Since the processing on the car is carried on an embedded platform from Nvidia (Jetson TX2), this study is based on the same board, the stream being captured with a low-cost webcam. Classical algorithms like SURF (Speeded Up Robust Features), SIFT (Scale Invariant Feature Transform) or ORB (Oriented fast and Rotated Brief) offer reliable results when the lighting condition between the reference image and the image obtained from the camera are similar. In our setup, the algorithms mentioned above start to behave badly in low light conditions. Therefore, this paper discusses the possibility of using Haar like features alongside a classifier for detecting traffic signs.

关键词： Feature extraction Cameras Image color analysis Automobiles Machine learning algorithms Object recognition Detectors

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Observability in Kubernetes Cluster: automatic Anomalies Detection using Prometheus

Observability in Kubernetes Cluster: Automatic Anomalies Det...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Octavian Mart Catalin Negru Florin Pop Aniello Castiglione Faculty of Automatic Control and Computer Science University POLITEHNICA of Bucharest Romania National Institute for Research and Development in Informatics – ICI Bucharest Romania Dipartimento di Scienze e Tecnologie University of Naples Parthenope Italy

ISBN: (纸本)9781728176505

Kubernetes is a portable, extensible, open-source platform for managing containers. It comes with features such as automatic scaling, service discovery, load balancing, fault tolerance, etc. Being such a complex system, which has a lot of internal services and with the ability to manage a lot more user services, Kubernetes comes with a monitoring system, which provides metrics and logs for every service in the cluster. However, most of the time, the monitoring system needs human intervention for detection and troubleshooting defects. Human intervention usually occurs when it is too late, when a defect appears. We think that detecting anomalies in metrics provided by the monitoring system will help to prevent defects. In this paper, we analyze current solutions for automatic anomaly detection and alerting, and also we propose a new solution that will help system administrators to catch and predict anomalies earlier, which may lead to defects. Our solution, which is a technical one, is developed around Prometheus, an open-source monitoring system for metrics.

关键词： Measurement Fault tolerance High performance computing Fault tolerant systems Containers Load management Observability

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Polish Language Modelling Based on Deep Learning Methods and Techniques

Polish Language Modelling Based on Deep Learning Methods and...

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Signal Processing Algorithms, Architectures, Arrangements and Applications (SPA)

作者： Piotr Kłosowski Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland

ISBN: (纸本)9781728139906

The article presents an example of deep learning methods application for language modelling in Polish. Language modelling helps to predict a sequence of recognized words or characters, and it can be used for improving speech processing and speech recognition. However, currently the field of language modelling is shifting from statistical language modelling methods to neural networks and deep learning methods. There are still many difficult problems to solve in natural language modelling. Nevertheless, deep learning methods achieve the most modern results for some specific language modelling problems. In this paper are presented the most interesting natural language modelling tasks, such as word-based and character-based language modelling, in which deep learning methods achieve some progress. New research results presented in this paper, in reference to previous articles, are focused on how to develop a character-based language model using a recurrent neural network and deep machine learning techniques. The use of both language modelling methods at the same time allow to develop hybrid language models that are characterized by even better properties and can greatly improve speech recognition. The presented results relate to the modelling of the Polish language but the achieved research results and conclusions can also be applied to language modelling application for other languages.

关键词： Speech recognition Deep learning Data models Computational modeling Load modeling Context modeling Natural languages

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Measurement and Calculation of the Impedance of an Eddy Current Probe Placed Above a Disc with Two Layers of Different Diameters

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Materials (Basel, Switzerland) 2025年第10期18卷 2376页

作者： Yike Xiang Grzegorz Tytko Yao Luo Jolanta Makowska State Key Laboratory of Power Grid Environmental Protection School of Electrical Engineering and Automation Wuhan University Wuhan 430072 China. School of Electrical Engineering and Automation Wuhan University Wuhan 430072 China. Faculty of Automatic Control Electronics and Computer Science The Silesian University of Technology Akademicka 16 44-100 Gliwice Poland. Institute of Materials Engineering Faculty of Science and Technology University of Silesia 75 Pułku Piechoty 1A 41-500 Chorzow Poland.

This work presents a system developed to determine changes in the impedance of an eddy current probe placed above a conductive disc containing two layers of different diameters. In the first step, an analytical model was derived with an employment of the truncated region eigenfunction expansion (TREE) method. The final formula for the probe impedance change was presented in a closed form, which makes it possible to implement it in any programming language or computer algebra system. The mathematical model was implemented in MATLAB and used to design probes and to determine the optimal test parameters. In the next step, two eddy current probes with a single coil with different geometric dimensions were constructed. Impedance measurements were carried out using an LCR meter for three sets of double-layer discs. The tested discs were made of materials with different electrical conductivities. The upper and lower layers of the disc also differed in terms of the geometric dimensions, i.e., the diameter and thickness. The tests were performed for the operating frequency of the probe ranging from 1 kHz to 10 kHz. In all cases, a very good agreement was obtained between the measurement and the calculation results. Both the error in the changes in resistance and the error in the changes in reactance did not exceed 3.5%.

关键词： analytical model coil reactance coil resistance conductive disc eddy current testing probe impedance truncated region eigenfunction expansion (TREE)

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Identification of information technology security issues specific to industrial control systems 13th

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13th International Conference on Dependability and Complex Systems, DepCoS-RELCOMEX 2018

作者： Rogowski, Dariusz Faculty of Automatic Control Electronics and Computer Science Institute of Informatics Silesian University of Technology Akademicka 16 Gliwice44-100 Poland Institute of Innovative Technologies EMAG Leopolda 31 Katowice40-189 Poland

ISBN: (纸本)9783319914459

The paper presents current cybersecurity issues in industrial automation and control systems (IACS). It also reviews the state of the art in literature, standards and frameworks used to evaluate and certify industrial control devices. Nowadays the Common Criteria (CC) security assurance methodology is commonly used for the vast majority of information technology (IT) products but not for IACS components. The paper proposes a security evaluation method of IACS to be based on the CC approach. The CC standard has not been used in industry so far and this is why it became the main motivation of the author’s doctoral research work in that field. The implementation of CC security requirements can enhance the "safety" of functional features in control devices by adding "security" measures typical of IT products. The paper delivers input information to the first stage of the author’s research whose goal is the identification of design needs and requirements for building the security evaluation method. As a result, in the next stage, the evaluation method can be built according to the model of a control system and to the criteria taken from the CC standard adjusted to IACS needs. Coupling both "security" and "safety" for industrial control systems is a promising way of using the CC assurance methodology for a new kind of devices. © Springer International Publishing AG, part of Springer Nature 2019.

关键词： Accident prevention

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