• Title/Summary/Keyword: Distributed Control Algorithm

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A Review on Advanced Methodologies to Identify the Breast Cancer Classification using the Deep Learning Techniques

  • Bandaru, Satish Babu;Babu, G. Rama Mohan
    • International Journal of Computer Science & Network Security
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    • v.22 no.4
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    • pp.420-426
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    • 2022
  • Breast cancer is among the cancers that may be healed as the disease diagnosed at early times before it is distributed through all the areas of the body. The Automatic Analysis of Diagnostic Tests (AAT) is an automated assistance for physicians that can deliver reliable findings to analyze the critically endangered diseases. Deep learning, a family of machine learning methods, has grown at an astonishing pace in recent years. It is used to search and render diagnoses in fields from banking to medicine to machine learning. We attempt to create a deep learning algorithm that can reliably diagnose the breast cancer in the mammogram. We want the algorithm to identify it as cancer, or this image is not cancer, allowing use of a full testing dataset of either strong clinical annotations in training data or the cancer status only, in which a few images of either cancers or noncancer were annotated. Even with this technique, the photographs would be annotated with the condition; an optional portion of the annotated image will then act as the mark. The final stage of the suggested system doesn't need any based labels to be accessible during model training. Furthermore, the results of the review process suggest that deep learning approaches have surpassed the extent of the level of state-of-of-the-the-the-art in tumor identification, feature extraction, and classification. in these three ways, the paper explains why learning algorithms were applied: train the network from scratch, transplanting certain deep learning concepts and constraints into a network, and (another way) reducing the amount of parameters in the trained nets, are two functions that help expand the scope of the networks. Researchers in economically developing countries have applied deep learning imaging devices to cancer detection; on the other hand, cancer chances have gone through the roof in Africa. Convolutional Neural Network (CNN) is a sort of deep learning that can aid you with a variety of other activities, such as speech recognition, image recognition, and classification. To accomplish this goal in this article, we will use CNN to categorize and identify breast cancer photographs from the available databases from the US Centers for Disease Control and Prevention.

The Control System of a Medical Robot Bed for Prevention and Healing of Pressure Ulcer (욕창 예방 및 치유를 위한 의료용 로봇 침대 제어 시스템)

  • Lee, Youngdae;Kim, Changyoung;Chang, Changjun;Kim, Jung Ae;Lim, Jae-Young
    • The Journal of the Convergence on Culture Technology
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    • v.6 no.3
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    • pp.353-359
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    • 2020
  • In this study, the controller structure and control algorithm of medical robot bed developed for pressure ulcer prevention and healing are described. The existing pressure ulcer prevention mattress is operated manually and the remaining maximum body pressure exceeds the pressure of ulcer generation, so there is always room for pressure ulcers. However, the system developed in this study does not generate the pressure ulcers because the body pressure drops to zero when the keyboard of the bed descends using the active electric driving keyboard. In addition, even if the bed is raised and the pressure above the critical body ulcer pressure is abnormal, the device and the control algorithm are designed so that the lasting time is within the pressure ulcer generation critical time and the pressure ulcer itself is not generated. The bed key board motor is a motor designed with the BLDC servos suitable for medical use and these can communicate each other easily through CAN(Car Area Network). The system is new medical robot bed that is effective in preventing pressure ulcers and will be distributed to many patients suffering from pressure ulcers.

Viewing Path Search and Congestion Control Algorithms For Comfortable Museum Viewing (편안한 박물관 관람을 위한 관람 경로 탐색 및 혼잡제어 알고리즘)

  • Seo, Yoon-Deuk;Ahn, Jin-Ho
    • Journal of Internet Computing and Services
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    • v.11 no.3
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    • pp.131-137
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    • 2010
  • Today, many museums are changing their forms with ubiquitous environment. Unlike traditional museums providing only static text-based information attached to its corresponding artifacts to visitors, those ubiquitous museums provide not only artifacts' text information, but also many different forms of information such as sound or media through personal digital assistance or cell phones. However, these existing ubiquitous museums still provide each visitor only with artifact-centric information in very simple ways. Also this disadvantageous feature causes high gallery congestion problem resulting from providing a uniform path for every visitor. These limitations may be the biggest barrier to providing more various and useful information about artifacts to visitors through considering each visitor's preference. This paper propose a new optimal viewing path search algorithm to provide comfortable museum viewing for each visitor according to its preference. Also, a new congestion control method is developed to protect visitors from being put in some hot spots on their museum viewing, improving its comfort to a maximum.

Adaptive Cross-Layer Resource Optimization in Heterogeneous Wireless Networks with Multi-Homing User Equipments

  • Wu, Weihua;Yang, Qinghai;Li, Bingbing;Kwak, Kyung Sup
    • Journal of Communications and Networks
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    • v.18 no.5
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    • pp.784-795
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    • 2016
  • In this paper, we investigate the resource allocation problem in time-varying heterogeneous wireless networks (HetNet) with multi-homing user equipments (UE). The stochastic optimization model is employed to maximize the network utility, which is defined as the difference between the HetNet's throughput and the total energy consumption cost. In harmony with the hierarchical architecture of HetNet, the problem of stochastic optimization of resource allocation is decomposed into two subproblems by the Lyapunov optimization theory, associated with the flow control in transport layer and the power allocation in physical (PHY) layer, respectively. For avoiding the signaling overhead, outdated dynamic information, and scalability issues, the distributed resource allocation method is developed for solving the two subproblems based on the primal-dual decomposition theory. After that, the adaptive resource allocation algorithm is developed to accommodate the timevarying wireless network only according to the current network state information, i.e. the queue state information (QSI) at radio access networks (RAN) and the channel state information (CSI) of RANs-UE links. The tradeoff between network utility and delay is derived, where the increase of delay is approximately linear in V and the increase of network utility is at the speed of 1/V with a control parameter V. Extensive simulations are presented to show the effectiveness of our proposed scheme.

Optimal Aerodynamic Design and Performance Analysis for Pitch-Controlled HAWT (가변 피치형 수평축 풍력 터빈의 공력 최적설계 및 피치제어 성능 연구)

  • Ryu, Ki-Wahn
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.35 no.10
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    • pp.891-898
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    • 2007
  • Optimal aerodynamic design for the pitch-controlled horizontal axis wind turbine and its aerodynamic performance for various pitch angles are performed numerically by using the blade element momentum theory. The numerical calculation includes effects such as Prandtl‘s tip loss, airfoil distribution, and wake rotation. Six different airfoils are distributed along the blade span, and the special airfoil i.e. airfoil of 40% thickness ratio is adopted at the hub side to have structural integrity. The nonlinear chord obtained from the optimal design procedure is linearized to decrease the weight and to increase the productivity with very little change of the aerodynamic performance. From the comparisons of the power, thrust, and torque coefficients with corresponding values of different pitch angles, the aerodynamic performance shows delicate changes for just $3^{\circ}$ increase or decrease of the pitch angle. For precisive pitch control, it requires the pitch control algorithm and its drive mechanism below $3^{\circ}$ increment of pitch angle. The maximum torque is generated when the speed ratio is smaller than the designed one.

Design of a Photovoltaic PCS with Compensation Control of Reactive Power and Unbalance Current in Three-phase systems (3상 시스템의 무효전력, 불평형 전류 보상 기능을 갖는 태양광 전력변환장치 설계)

  • Park, Sang-Min;Kim, Chang-Soon;Le, Dinh Vuong;Park, Minwon;Yu, In-Keun
    • Journal of Korea Society of Industrial Information Systems
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    • v.21 no.3
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    • pp.29-33
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    • 2016
  • Development of the distributed energy resources such as photovoltaic, wind, and fuel cell has increased rapidly due to the rising demand for clean energy utilization. On the other hand, the distribution system became complex and has problems such as degradation of power factor and current unbalance caused by power converters, reactive power and unbalanced loads. To solve these problems, this paper proposes a 3-phase 4-leg type power conditioning system with compensation control algorithm for the reactive power and unbalance current in distribution system using photovoltaic resource. It is simulated in PSCAD/EMTDC and the effectiveness is confirmed.

A Study on a Multi-period Inventory Model with Quantity Discounts Based on the Previous Order (주문량 증가에 따른 할인 정책이 있는 다기간 재고 모형의 해법 연구)

  • Lim, Sung-Mook
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.32 no.4
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    • pp.53-62
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    • 2009
  • Lee[15] examined quantity discount contracts between a manufacturer and a retailer in a stochastic, two-period inventory model where quantity discounts are provided based on the previous order size. During the two periods, the retailer faces stochastic (truncated Poisson distributed) demands and he/she places orders to meet the demands. The manufacturer provides for the retailer a price discount for the second period order if its quantity exceeds the first period order quantity. In this paper we extend the above two-period model to a k-period one (where k < 2) and propose a stochastic nonlinear mixed binary integer program for it. In order to make the program tractable, the nonlinear term involving the sum of truncated Poisson cumulative probability function values over a certain range of demand is approximated by an i-interval piecewise linear function. With the value of i selected and fixed, the piecewise linear function is determined using an evolutionary algorithm where its fitness to the original nonlinear term is maximized. The resulting piecewise linear mixed binary integer program is then transformed to a mixed binary integer linear program. With the k-period model developed, we suggest a solution procedure of receding horizon control style to solve n-period (n < k) order decision problems. We implement Lee's two-period model and the proposed k-period model for the use in receding horizon control style to solve n-period order decision problems, and compare between the two models in terms of the pattern of order quantities and the total profits. Our computational study shows that the proposed model is superior to the two-period model with respect to the total profits, and that order quantities from the proposed model have higher fluctuations over periods.

MPPT and Yawing Control of a New Horizontal-Axis Wind Turbine with Two Parallel-Connected Generators (수평 병렬형 풍력 발전기의 요각 및 MPPT 제어)

  • Lee, Kook-Sun;Choy, Ick;Cho, Whang;Back, Ju-Hoon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.1
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    • pp.81-89
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    • 2012
  • Commonly used horizontal-axis wind turbines (HAWT) have the following structure: two or three blades, a nacelle which contains power converting equipments, generators, and a tower which supports the nacelle. The generated power is transmitted from the nacelle to the ground. Due to this structure, the power transmission lines are twisted when the nacelle is yawing. Thus, slip ring or additional yaw control mechanism is required. We propose a new structure of HAWT which is free of this transmission line problem. Moreover, the size of inverter can be reduced since two generators are connected in parallel in our mechanism so that power is distributed. A controller for yawing is developed so that it works in harmony with the controller for power generation. A MPPT (Maximum Power Point tracking) algorithm is implemented for the proposed system and efficiency of the system is validated by simulation.

Case Study: Cost-effective Weed Patch Detection by Multi-Spectral Camera Mounted on Unmanned Aerial Vehicle in the Buckwheat Field

  • Kim, Dong-Wook;Kim, Yoonha;Kim, Kyung-Hwan;Kim, Hak-Jin;Chung, Yong Suk
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.64 no.2
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    • pp.159-164
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    • 2019
  • Weed control is a crucial practice not only in organic farming, but also in modern agriculture because it can lead to loss in crop yield. In general, weed is distributed in patches heterogeneously in the field. These patches vary in size, shape, and density. Thus, it would be efficient if chemicals are sprayed on these patches rather than spraying uniformly in the field, which can pollute the environment and be cost prohibitive. In this sense, weed detection could be beneficial for sustainable agriculture. Studies have been conducted to detect weed patches in the field using remote sensing technologies, which can be classified into a method using image segmentation based on morphology and a method with vegetative indices based on the wavelength of light. In this study, the latter methodology has been used to detect the weed patches. As a result, it was found that the vegetative indices were easier to operate as it did not need any sophisticated algorithm for differentiating weeds from crop and soil as compared to the former method. Consequently, we demonstrated that the current method of using vegetative index is accurate enough to detect weed patches, and will be useful for farmers to control weeds with minimal use of chemicals and in a more precise manner.

A Tunable Transmitter - Tunable Receiver Algorithm for Accessing the Multichannel Slotted-Ring WDM Metropolitan Network under Self-Similar Traffic

  • Sombatsakulkit, Ekanun;Sa-Ngiamsak, Wisitsak;Sittichevapak, Suvepol
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.777-781
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    • 2004
  • This paper presents an algorithm for multichannel slotted-ring topology medium access protocol (MAC) using in wavelength division multiplexing (WDM) networks. In multichannel ring, there are two main previously proposed architectures: Tunable Transmitter - Fixed Receiver (TTFR) and Fixed Transmitter - Tunable Receivers (FTTR). With TTFR, nodes can only receive packets on a fixed wavelength and can send packets on any wavelengths related to destination of packets. Disadvantage of this architecture is required as many wavelengths as there are nodes in the network. This is clearly a scalability limitation. In contrast, FTTR architecture has advantage that the number of nodes can be much larger than the number of wavelength. Source nodes send packet on a fixed channel (or wavelength) and destination nodes can received packets on any wavelength. If there are fewer wavelengths than there are nodes in the network, the nodes will also have to share all the wavelengths available for transmission. However the fixed wavelength approach of TTFR and FTTR bring low network utilization. Because source node with waiting data have to wait for an incoming empty slot on corresponding wavelength. Therefore this paper presents Tunable Transmitter - Tunable Receiver (TTTR) approach, in which the transmitting node can send a packet over any wavelengths and the receiving node can receive a packet from any wavelengths. Moreover, the self-similar distributed input traffic is used for evaluation of the performance of the proposed algorithm. The self-similar traffic performs better performance over long duration than short duration of the Poison distribution. In order to increase bandwidth efficiency, the Destination Stripping approach is used to mark the slot which has already reached the desired destination as an empty slot immediately at the destination node, so the slot does not need to go back to the source node to be marked as an empty slot as in the Source Stripping approach. MATLAB simulator is used to evaluate performance of FTTR, TTFR, and TTTR over 4 and 16 nodes ring network. From the simulation result, it is clear that the proposed algorithm overcomes higher network utilization and average throughput per node, and reduces the average queuing delay. With future works, mathematical analysis of those algorithms will be the main research topic.

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