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Design And Implementation Of A PID Control System On A UAV Tracker Antenna

Design And Implementation Of A PID Control System On A UAV T...

2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2023

作者： Jayadi, Akhmad Adhinata, Faisal Dharma Persada Sembiring, Jaka Setyo Adhi, Canggih Gelar Herman Selsily, Wendel Amiruddin, Ahmad Universitas Teknokrat Indonesian Faculty of Engineering and Computer Science Lampung Indonesia Institut Teknologi Telkom Purwokerto Faculty of Informatics Jawa Tengah Indonesia Universitas Bina Nusantara Faculty of Computer Science Semarang Indonesia Universitas Kristen Indonesia Maluku Faculty of Computer Science Maluku Indonesia

ISBN: (纸本)9798350309225

Antennas are essential components in communication systems, serving as both transmitters and receivers. Their efficient operation depends on precise alignment with the strongest signal source, facilitated by tracker antennas. A recent research study focused on enhancing the responsiveness of these tracker antennas. By manually inputting PID (Proportional-Integral-Derivative) values for direction control, the study achieved notable *** results demonstrated that by fine-tuning PID values, particularly setting Kp=5, Ki=0.21812, and Kd=12, and targeting an angle of 90°, the response time was reduced to 1.2 seconds with an overshoot of 28.8% and 1.6 seconds of oscillation. This optimized control mechanism significantly improved antenna direction accuracy, aligning it with the desired setpoint. Furthermore, the importance of antenna alignment and polarization matching in communication systems was emphasized. Ensuring alignment between the receiving antenna's polarization and the incoming wave polarization is crucial for maintaining a strong signal reception power level. This alignment enables accurate tracking of antenna positions, supporting real-time GPS data communication. Additionally, the study involving horizontal azimuth angle measurements with tracker antennas demonstrated their capability to transmit real-time data from multiple positions, achieving 360° horizontal azimuth angles, along with varying elevations. These precise measurements play a vital role in object monitoring and effective communication. © 2023 IEEE.

关键词： Global positioning system

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Forwarding Strategy Performance Using NFD Pipeline Measurements on Vehicular Named Data Networking (V-NDN) 9

Forwarding Strategy Performance Using NFD Pipeline Measureme...

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9th International Conference on Wireless and Telematics, ICWT 2023

作者： Ahdan, Syaiful Syambas, Nana Rachmana Iskandar School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung40132 Indonesia Faculty of Engineering & Computer Science Lampung35132 Indonesia

ISBN: (纸本)9798350305029

The Named Data Networking (NDN) paradigm has been used as a promising vehicle communication model, namely the Vehicular Named Data Networking (V-NDN) model. In NDN, delivery of interest in the NDN network is done by selecting an existing interface. The problem is as to which interface is right in terms of fulfilling the request that suits the user. In this study, we compare the effectiveness of each forwarding strategy by creating new scenarios, such as variations in the number of interests and simulation time. We also measure the effectiveness of the forwarding strategy using the parameters specified in the NFD Forwarding Pipeline. The conclusion from the experiment is that superior forwarding strategy recommendations are based on content store (CS) management and data compatibility obtained based on consumer demand for producers. © 2023 IEEE.

关键词： Pipelines

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The Impact of Interest Flooding Attack (IFA) and Collusive IFA on Named Data Networking (NDN) 6

The Impact of Interest Flooding Attack (IFA) and Collusive I...

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6th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2023

作者： Jupriyadi Mulyana, Eueung Syambas, Nana Rachmana School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Universitas Teknokrat Indonesia Faculty of Engineering and Computer Lampung Indonesia

ISBN: (纸本)9798350358346

Named Data Networking (NDN) is a proposed future Internet architecture that has the advantage of bringing content data closer to users. NDN focuses on securing content data rather than securing transmission channels. The NDN network is also not free from threats and attacks that can disrupt network performance. One of the attacks on the NDN network is a denial of service (DoS) attack. The attacker carries out this attack by sending a large number of request packets. This attack is known as an interest flooding attack (IF A). The IF A attack itself has developed into a collusive IFA to avoid existing detection systems. In this paper, we examine the comparative impact of IF A and CIF A attacks on clients or consumers. Knowing the impact and characteristics of IF A and CIF A attacks can be used as a reference in the attack detection system. Attacks are carried out locally and remotely by looking at 3 types of attacks, namely attacks by sending requests for packets that are on the network, attacks by sending requests for containers that are not available on the net, hybrid attacks, and 1 collusive IF A attack. Based on the exploration carried out, it was found that local attacks had a very significant impact compared to remote attacks. IFA attacks that have a major impact on the network are attacks that send content that is not available on the net. The effect of this attack meant that requests sent by consumers were only served by 40% of the total bids. © 2023 IEEE.

关键词： Denial-of-service attack

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Numerical P Systems: Variants and Applications 24

Numerical P Systems: Variants and Applications

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24th Conference Information Technologies - Applications and Theory, ITAT 2024

作者： Bobe, Radu Traian Gheorghe, Marian Ipate, Florentin Niculescu, Ionuţ Mihai Department of Computer Science Faculty of Mathematics and Computer Science University of Bucharest Str Academiei 14 Bucharest010014 Romania Faculty of Engineering and Informatics University of Bradford Bradford West YorkshireBD7 1DP United Kingdom

Numerical P systems are compuational models which are inspired by cellular processes and use numerical values inside the membrane structure. In this paper we will present the variants of numerical P systems that have been proposed in the literature. In particular, we will discuss the advantages introduced by these extensions in terms of Turing completeness and potential applications. Moreover, using a reference example, we will experiment a mapping between some important numerical P systems variants. © 2024 CEUR-WS. All rights reserved.

关键词： Membrane structures

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Machine Learning-Based Calibration Approaches for Single-Beam and Multiple-Beam Distance Sensors

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IEEE Sensors Journal 2024年第1期24卷 975-983页

作者： Syu, Jia-Hao Lin, Jerry Chun-Wei Biernacki, Piotr Ziebinski, Adam National Taiwan University Department of Computer Science and Information Engineering Taipei10617 Taiwan Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Department of Distributed Systems and Informatics Devices Gliwice44-100 Poland Silesian University of Technology Department of Distributed Systems and Informatic Devices Gliwice44-100 Poland

Sensors are the foundation to facilitate smart cities, smart grids, and smart transportation, and distance sensors are especially important for sensing the environment and gathering information. Researchers have developed various methods to calibrate distance sensors;however, they mainly focus on using external information for calibration, which is inefficient and computationally expensive. To alleviate the above problems, we propose machine learning (ML)-based calibration approaches for distance sensors. We develop two calibration mechanisms, where the naive mechanism directly predicts the true distance, while the residual mechanism predicts the residual for calibration. The conventional ML regression algorithms are then adopted to predict the true distance or calibration residual. Experimental results show that the designed residual calibration mechanism outperforms the naive mechanism by reducing the root mean square error (RMSE) by 92.2% and mean absolute error (MAE) by 93.3% in the fitting task. In prediction, the proposed 2-D-residual mechanism achieves an improvement of 78.6% and 65.7% compared to the state-of-the-art method. The experimental results show the effectiveness and generalization of the proposed ML-based calibration method, especially for the 2-D mechanism, which achieves the highest robustness in all fitting and prediction tasks. © 2001-2012 IEEE.

关键词： Calibration

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Overview of Load Disaggregation Models, Methods and Hardware 59

Overview of Load Disaggregation Models, Methods and Hardware

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59th International Universities Power engineering Conference, UPEC 2024

作者： Lancranjan, Mircea N. Muresan, Alexandru Jurj, Dacian I. Berciu, Alexandru Polycarpou, Alexis Czumbil, Levente Micu, Dan D. Technical University of Cluj-Napoca Department Electrical Engineering Cluj-Napoca Romania Technical University of Cluj-Napoca Faculty of Automation and Computer Science Cluj-Napoca Romania Department of Electrical and Computer Engineering and Informatics Frederick University Nicosia Cyprus

ISBN: (纸本)9798350379730

In the dynamic landscape of energy efficiency, a domain garnering ever increasing attention and urgency, the cornerstone of informed decision-making resides in the acquisition of reliable data. This paper summarizes the main approaches, methods and hardware used to gather, process and disaggregate such data on an appliance-by-appliance basis. The paper explores a critical analysis of the various models and techniques that support the gathering of energy data at the appliance level. A range of approaches, including hardware-based solutions such as smart meters, submeters, and sensor arrays, placing a special focus on intrusive load monitoring (ILM) and non-intrusive load monitoring (NILM) algorithms that employ advanced signal processing and machine learning techniques, are examined for their effectiveness, scalability, and suitability for both industrial and commercial contexts. Furthermore, the challenges of data acquisition capabilities, reconciling scalability, cost-effectiveness, and user-friendliness - prerequisites for widespread acceptance and uptake are also investigated. © 2024 IEEE.

关键词： AI Data Cleaning Energy Efficiency Energy Signature Load Disaggregation Load Monitoring NILM

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A comparative analysis of the effectiveness of feature engineering techniques on thyroid disease prediction 1

A comparative analysis of the effectiveness of feature engin...

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1st Zimbabwe Conference of Information and Communication Technologies, ZCICT 2022

作者： Mashonga, Aidah Kudzainyandoro, Leslie Zvarevashe, Kudakwashe University of Zimbabwe Faculty of Computer Engineering Informatics and Communication Analytics and Informatics Department Harare Zimbabwe

ISBN: (纸本)9781665475761

The thyroid gland's edge experiences an abnormal proliferation of thyroid tissue, which causes thyroid illness. The two primary types of thyroid disorders are hypothyroidism and hyperthyroidism which typically result when this gland releases excessive amounts of hormones. To identify and diagnose thyroid disease, this study suggests employing effective classifiers and feature selection strategies that consider accuracy and other performance evaluation measures. This study offers a thorough examination of various classifiers that includes the support vector machine, logistic regression, and extreme gradient boosting algorithms. The algorithms use three feature removal strategies that is recursive feature elimination, Pearson's correlation and chi-squared statistics. To determine thyroid illness, thyroid data from the Kaggle datasets were used. Numerous aspects of the experiment have been evaluated and analyzed, including accuracy, precision, and the receiver operating curve's area under the curve. The outcome showed that classifiers that use feature selection have a greater overall accuracy(Xtreme Gradient Boost 98%and support vector machine 95%) compared to without feature selection technique (support vector machine 89%). Logistics regression performed better without at 95% than 94% with feature selection. © 2022 IEEE.

关键词： Feature Selection

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An Evaluation of the Dual Vectors Based Solutions for Robot-World/Hand-Eye Calibration 1

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25th International Symposium on Measurement and Control in Robotics, ISMCR 2023

作者： Ganciu, Aura Burlacu, Adrian Department of Automatic Control and Applied Informatics Faculty of Automatic Control and Computer Engineering "Gheorghe Asachi" Technical University of Iași Iași Romania

ISBN: (数字)9783031510854

ISBN: (纸本)9783031510847

The hand-eye calibration problem represents a major challenge in robotics, arising from the widespread usage of robotic systems along with robot-mounted sensors. Briefly, consisting of estimating the position and orientation of a visual sensor (usually a camera attached to the robot’s end-effector) with respect to the robot itself, calibration is critical in tracking rigid bodies—a common task within mixed reality applications. Hand-eye calibration implies solving the problem formulated as AX = XB or AX = YB equations. The solution lies in computing the unknown homogeneous transformation matrices X and Y, given the A and B parameterizations of rigid body motions. We present the dual vectors based approaches for AX = XB and AX = YB calibration problems, making use of the isomorphism between the special Euclidean group and the orthogonal dual tensor group. Comparisons with state-of-the-art algorithms are used to assess our obtained results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Mixed reality

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Test-Driven Simulation of Robots Controlled by Enzymatic Numerical P Systems Models 15th

Test-Driven Simulation of Robots Controlled by Enzymatic N...

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15th EAI International Conference on Simulation Tools and Techniques, SIMUTools 2023

ISBN: (纸本)9783031575228

The simulation of robots behavior and the use of robust models are very important for building controllers. Testing is an important aspect in this process. In this paper, a test-driven approach for designing robot controllers based on enzymatic numerical P systems models is introduced. Four such models are defined and tested using three distinct scenarios. The paper reveals an effective way of using modelling, simulation and testing in a coherent way. © ICST Institute for computer Sciences, Social informatics and Telecommunications engineering 2024.

关键词： Controllers

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Fake News Detection using 5L-CNN 1

Fake News Detection using 5L-CNN

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1st Zimbabwe Conference of Information and Communication Technologies, ZCICT 2022

作者： Collen, Demo Rangarirai Nyandoro, Leslie Kudzai Zvarevashe, Kudakwashe University of Zimbabwe Faculty of Computer Engineering Informatics and Communication Analytics and Informatics Department Harare Zimbabwe

ISBN: (纸本)9781665475761

With the advent of websites and social media technologies, the internet has been a great method of transmitting news and information around the globe. However, due to lack of editorial scrutiny and monitoring by the media authorities, the news distribution has been seriously abused leading to the fast spreading of fake news. Fake news involves misleading broadcasting of information from sources that target to intentionally manipulate the way how people view some events or statements. This study seeks to develop a fake news detection model which will be able to analyze the title and text information attached to the news articles. From the researches done by previous scholars, it showed that the models did not perform very well because of the lack of sufficient feature extraction and fine tuning of the classification of the text. This research will therefore, articulate the gap by employing 5L-CNN deep learning model which will use inbuilt tokenizers for word embedding and will show better accuracy compared to the traditional machine learning models. In this paper, we compare machine learning algorithms (Decision trees, Random Forest, Logistic Regression & Naive Bayes) and deep learning algorithms (RNN, 5L-CNN & LSTM) to classify the authenticity of news articles. The model developed in this paper attained the best accuracy with 5L-CNN which had a result of 99.99%. © 2022 IEEE.

关键词： Decision trees

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