Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395

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Now showing 1 - 6 of 6
  • Article
    Citation - Scopus: 1
    Robust Controller Electromyogram Prosthetic Hand With Artificial Neural Network Control and Position
    (Indian Journal of Forensic Medicine and Toxicology ijfmt@hotmail.com, 2020) Ahmed, Saygin Siddiq; Ahmed, Aydin S.; Yilmaz, Bulent; Doǧru, Nuran
    In this study, we proposed and designed a new control method for an electromyographically (EMG) controlled prosthetic hand. The objective is to increase the control efficiency of the human–machine interface and afford greater control of the prosthetic hand. The process works as follows: EMG biomedical signals acquired from Myoware sensors positioned on the relevant muscles are sent to the robot that consist of hand, Arduino and MATLAB program, which computes and controls the hand position in free space along with hand grasping operations. The Myoware device acquires muscle signals and sends them to the Arduino. The Arduino analyzes the received signals, based on which it controls the motor movement. In this design, the muscle signals are read and saved in a MATLAB system file. After program processing on the industrial hand which is applied by MATLAB simulation, the corresponding movement is transferred to the hand, enabling movements, such as, hand opening and closing according to the signal stored in the MATLAB system. In this study, hand and fingerprints were designed using a three-dimensional printer by separate recording finger and thumb signals. The muscle signals were then analyzed in order to obtain peak signal points and convert them into data. These results indicate the effectiveness of the proposed method and demonstrate the superiority of the method for amputees because of the improved controllability and perceptibility afforded by the design. © 2020 Elsevier B.V., All rights reserved.
  • Article
    Citation - WoS: 23
    Citation - Scopus: 29
    Optimal Control of Microgrids With Multi-Stage Mixed-Integer Nonlinear Programming Guided Q-Learning Algorithm
    (State Grid Electric Power Research inst, 2020) Yoldas, Yeliz; Goren, Selcuk; Onen, Ahmet
    This paper proposes an energy management system (EMS) for the real-time operation of a pilot stochastic and dynamic microgrid on a university campus in Malta consisting of a diesel generator, photovoltaic panels, and batteries. The objective is to minimize the total daily operation costs, which include the degradation cost of batteries, the cost of energy bought from the main grid, the fuel cost of the diesel generator, and the emission cost. The optimization problem is modeled as a finite Markov decision process (MDP) by combining network and technical constraints, and Q-learning algorithm is adopted to solve the sequential decision subproblems. The proposed algorithm decomposes a multi-stage mixed-integer nonlinear programming (MINLP) problem into a series of single-stage problems so that each subproblem can be solved by using Bellman's equation. To prove the effectiveness of the proposed algorithm, three case studies are taken into consideration: (1) minimizing the daily energy cost; (2) minimizing the emission cost; (3) minimizing the daily energy cost and emission cost simultaneously. Moreover, each case is operated under different battery operation conditions to investigate the battery lifetime. Finally, performance comparisons are carried out with a conventional Q-learning algorithm.
  • Article
    Citation - Scopus: 5
    Modeling and Real Time Digital Simulation of Microgrids for Campuses Malta and Jordan Based on Multiple Distributed Energy Resources
    (Institute of Advanced Engineering and Science, 2021-02-01) Khiat, Sidahmed; Chaker, Abdelkader El Kader; Zacharia, Lazaros; Onen, Ahmet
    This paper presents the modeling and real-time digital simulation of two microgrids: The malta college of arts, science and technology (MCAST) and the German jordan university (GJU). The aim is to provide an overview of future microgrid situation and capabilities with the benefits of integrating renewable energy sources (RES), such as photovoltaic panels, diesel generators and energy storage systems for projects on both campuses. The significance of this work starts with the fact that real measurements were used from the two pilots, obtained by measuring the real physical systems. These measures were used to plan different solutions regarding RES and energy storage system (ESS) topologies and sizes. Also, the demand curves for the real microgrids of MCAST and GJU have been parameterized, which may serve as a test bed for other studies in this area. Based on actual data collected from the two pilots, a real-time digital simulation is performed using an RT-LAB platform. The results obtained by this tool allow the microgrid manager to have a very accurate vision of the facility operation, in terms of power flow and default responses. Several scenarios are studied, extracting valuable insight for implementing both projects in the future. Eventually, the proposed models would be a blueprint for training and research purposes in the microgrid field. © 2020 Elsevier B.V., All rights reserved.
  • Article
    Citation - WoS: 5
    Citation - Scopus: 5
    Ineffectiveness of Flood Cooling in Reducing Cutting Temperatures During Continuous Machining
    (Springer London Ltd, 2022-09-19) Kesriklioglu, Sinan
    Water-based metalworking fluids are applied in the form of a liquid jet to flood the entire cutting zone and increase the tool life. The objective of this study is to investigate the effectiveness of flood cooling in reducing the tool chip interface temperatures during continuous cutting. An instrumented smart cutting tool with a thin film temperature sensor was fabricated to accurately measure the real-time cutting temperatures from 1.3 mu m below the tool chip interface in orthogonal turning of AISI 4140 steel under dry and flood cooling conditions. The cutting process was simulated in Deform 2D with the Johnson-Cook material model to present the transient temperature distributions on the coated cutting insert. The heat flux into the cutting tool was also estimated analytically and then three-dimensional finite element heat transfer simulations were performed to determine the maximum convective heat transfer of the cutting fluid in steady state. The measurements with the embedded thermocouple showed that flood cooling with a water-based cutting fluid slightly lowers the tool chip interface temperature. Moreover, the chip color may not be a good characteristic indicator to evaluate the cutting temperature in machining of metals. It was also found that flood cooling becomes more effective at a distance of approximately 150 mu m from the cutting edge where the chip does not contact the rake face of the cutting tool.
  • Article
    Citation - Scopus: 49
    EdgeAISim: A Toolkit for Simulation and Modelling of AI Models in Edge Computing Environments
    (Elsevier Ltd, 2024-02) Nandhakumar, Aadharsh Roshan; Baranwal, Ayush; Choudhary, Priyanshukumar; Golec, Muhammed; Gill, Sukhpal Singh
    To meet next-generation Internet of Things (IoT) application demands, edge computing moves processing power and storage closer to the network edge to minimize latency and bandwidth utilization. Edge computing is becoming increasingly popular as a result of these benefits, but it comes with challenges such as managing resources efficiently. Researchers are utilising Artificial Intelligence (AI) models to solve the challenge of resource management in edge computing systems. However, existing simulation tools are only concerned with typical resource management policies, not the adoption and implementation of AI models for resource management, especially. Consequently, researchers continue to face significant challenges, making it hard and time-consuming to use AI models when designing novel resource management policies for edge computing with existing simulation tools. To overcome these issues, we propose a lightweight Python-based toolkit called EdgeAISim for the simulation and modelling of AI models for designing resource management policies in edge computing environments. In EdgeAISim, we extended the basic components of the EdgeSimPy framework and developed new AI-based simulation models for task scheduling, energy management, service migration, network flow scheduling, and mobility support for edge computing environments. In EdgeAISim, we have utilized advanced AI models such as Multi-Armed Bandit with Upper Confidence Bound, Deep Q-Networks, Deep Q-Networks with Graphical Neural Network, and Actor-Critic Network to optimize power usage while efficiently managing task migration within the edge computing environment. The performance of these proposed models of EdgeAISim is compared with the baseline, which uses a worst-fit algorithm-based resource management policy in different settings. Experimental results indicate that EdgeAISim exhibits a substantial reduction in power consumption, highlighting the compelling success of power optimization strategies in EdgeAISim. The development of EdgeAISim represents a promising step towards sustainable edge computing, providing eco-friendly and energy-efficient solutions that facilitate efficient task management in edge environments for different large-scale scenarios. © 2023 Elsevier B.V., All rights reserved.
  • Article
    Citation - WoS: 40
    Citation - Scopus: 46
    A Modeling and Control Approach to Advanced Nuclear Power Plants With Gas Turbines
    (Pergamon-Elsevier Science Ltd, 2013-12) Ablay, Gunyaz
    Advanced nuclear power plants are currently being proposed with a number of various designs. However, there is a lack of modeling and control strategies to deal with load following operations. This research investigates a possible modeling approach and Load following control strategy for gas turbine nuclear power plants in order to provide an assessment way to the concept designs. A load frequency control strategy and average temperature control mechanism are studied to get load following nuclear power plants. The suitability of the control strategies and concept designs are assessed through linear stability analysis methods. Numerical results are presented on an advanced molten salt reactor concept as an example nuclear power plant system to demonstrate the validity and effectiveness of the proposed modeling and load following control strategies. (C) 2013 Elsevier Ltd. All rights reserved.