• Title/Summary/Keyword: Machine Part

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An insight into the prediction of mechanical properties of concrete using machine learning techniques

  • Neeraj Kumar Shukla;Aman Garg;Javed Bhutto;Mona Aggarwal;M.Ramkumar Raja;Hany S. Hussein;T.M. Yunus Khan;Pooja Sabherwal
    • Computers and Concrete
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    • v.32 no.3
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    • pp.263-286
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    • 2023
  • Experimenting with concrete to determine its compressive and tensile strengths is a laborious and time-consuming operation that requires a lot of attention to detail. Researchers from all around the world have spent the better part of the last several decades attempting to use machine learning algorithms to make accurate predictions about the technical qualities of various kinds of concrete. The research that is currently available on estimating the strength of concrete draws attention to the applicability and precision of the various machine learning techniques. This article provides a summary of the research that has previously been conducted on estimating the strength of concrete by making use of a variety of different machine learning methods. In this work, a classification of the existing body of research literature is presented, with the classification being based on the machine learning technique used by the researchers. The present review work will open the horizon for the researchers working on the machine learning based prediction of the compressive strength of concrete by providing the recommendations and benefits and drawbacks associated with each model as determining the compressive strength of concrete practically is a laborious and time-consuming task.

A Cyber-Physical Information System for Smart Buildings with Collaborative Information Fusion

  • Liu, Qing;Li, Lanlan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.5
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    • pp.1516-1539
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    • 2022
  • This article shows a set of physical information fusion IoT systems that we designed for smart buildings. Its essence is a computer system that combines physical quantities in buildings with quantitative analysis and control. In the part of the Internet of Things, its mechanism is controlled by a monitoring system based on sensor networks and computer-based algorithms. Based on the design idea of the agent, we have realized human-machine interaction (HMI) and machine-machine interaction (MMI). Among them, HMI is realized through human-machine interaction, while MMI is realized through embedded computing, sensors, controllers, and execution. Device and wireless communication network. This article mainly focuses on the function of wireless sensor networks and MMI in environmental monitoring. This function plays a fundamental role in building security, environmental control, HVAC, and other smart building control systems. The article not only discusses various network applications and their implementation based on agent design but also demonstrates our collaborative information fusion strategy. This strategy can provide a stable incentive method for the system through collaborative information fusion when the sensor system is unstable in the physical measurements, thereby preventing system jitter and unstable response caused by uncertain disturbances and environmental factors. This article also gives the results of the system test. The results show that through the CPS interaction of HMI and MMI, the intelligent building IoT system can achieve comprehensive monitoring, thereby providing support and expansion for advanced automation management.

Development of Safety Sensor for Vehicle-Type Forest Machine in Forest Road

  • Ki-Duck Kim;Hyun-Seung Lee;Gyun-Hyung Kim;Boem-Soo Shin
    • Journal of Forest and Environmental Science
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    • v.39 no.4
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    • pp.254-260
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    • 2023
  • A sensor system has been developed that uses an ultrasonic sensor to detect the downhill slope on the side of a forest road and prevents a vehicle-type forest machine from rolling down a mountainside. A specular reflection of ultrasonic wave might cause severe issues in measuring distances to targets. By investigating the installation angle of the sensor to minimize the negative effects of specular reflection, the installation angle of lateral monitoring ultrasonic sensor could be determined based on the width of road shoulder. Obstacles such as small rocks or piece of log in a forest road may cause the forest machine to be overturned while the machine riding over due to excessive its posture change. It was determined that the laser sensor could be a part of a sensor system capable of specifying the location and size of small obstacles. Not only this sensor system including ultrasonic and laser sensors can issue a warning of dangerous sections to drivers in forest forwarders currently in use, but also it can be used as a driving safety sensor in autonomous forest machine or remote-control forest machine in the future.

Development of an Automatic Seeding System Using Machine Vision for Seed Line-up of Cucurbitaceous Vegetables (기계시각을 이용한 박과채소 종자 정렬파종시스템 개발)

  • Kim, Dong-Eok;Cho, Han-Keun;Chang, Yu-Seob;Kim, Jong-Goo;Kim, Hyeon-Hwan;Son, Jae-Ryoung
    • Journal of Biosystems Engineering
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    • v.32 no.3
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    • pp.179-189
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    • 2007
  • Most of the seeds of cucurbitaceous rootstock species used for grafting were mainly sown by hand. This study was carried out to develop an on-line discriminating algorithm of seed direction using machine vision and an automatic seeding system. The seeding system was composed of a supplying device, feeding device, machine vision system, reversing device, seeding device and system control section. Machine vision was composed of a color CCD camera, frame grabber, image inspection chamber, lighting and personal computer. The seed image was segmented into a region of seed part and background part using thresholding technique in which H value of HSI color coordinate system. A seed direction was discriminated by comparing position between the center of circumscribed rectangle to a seed and the center of seed image. It took about 49ms to identify and redirect seed. Line-up status of seed was good the more than 95% of a sowed seed. Seeding capacity of this system was shown to be 10,140 grains per hour, which is three times faster than that of a typical worker.

Vibration Suppression Control for a Geared Mechanical System;Simulation Study on Vibration Suppression Effects Using a Model-Based Control with a Rotational Speed Sensor

  • Itoh, Masahiko
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.694-699
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    • 2005
  • This paper deals with a control technique of eliminating the transient vibration of a geared mechanical system. This technique is based on a model-based control with a rotational speed sensor in order to establish the damping effect at the driven machine part. A rotational speed sensor is installed in a driven gear, namely a bull gear. A control model is composed of a reduced-order mechanical part expressed as a transfer function between the rotational speed of the motor and that of the bull gear. This control model estimates a load speed after the rotational speed of the bull gear is acted on the transfer function. The difference between the estimated load speed and the motor speed is calculated dynamically and it is added to the velocity command to suppress the transient vibration generated at the load. This control technique is applied to a dies driving spindle of a form rolling machine. In this paper, the performance of this control method is examined by simulations. The settling time of the residual vibration generated at the loading inertia can be shortened down to about 1/2 of the uncompensated vibration level.

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A Study on the Natural Language Generation by Machine Translation (영한 기계번역의 자연어 생성 연구)

  • Hong Sung-Ryong
    • Journal of Digital Contents Society
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    • v.6 no.1
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    • pp.89-94
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    • 2005
  • In machine translation the goal of natural language generation is to produce an target sentence transmitting the meaning of source sentence by using an parsing tree of source sentence and target expressions. It provides generator with linguistic structures, word mapping, part-of-speech, lexical information. The purpose of this study is to research the Korean Characteristics which could be used for the establishment of an algorism in speech recognition and composite sound. This is a part of realization for the plan of automatic machine translation. The stage of MT is divided into the level of morphemic, semantic analysis and syntactic construction.

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Influences of Wet-Pressing Types on Internal Structure of Paper (습부압착 방식이 종이의 내부구조에 미치는 영향)

  • Lee Jin-Ho;Park Jong-Moon
    • Journal of Korea Technical Association of The Pulp and Paper Industry
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    • v.37 no.4 s.112
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    • pp.32-37
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    • 2005
  • To Increase the productivity of a paper machine, the maximization of the machine speed is a kind of simple way As the machine speed increases, more intense wet pressing is required to persist the outlet consistency of press part and reduce the water removal of dryer part. With more intense pressing, there are concerns that the quality of paper will be affected. This study was carried out to evaluate the influence of wet-pressing on internal structure of paper, The nip pressure at the first and third nip in triple nip press was controlled. Paper structures, strength properties and pore properties were evaluated. As a result, first nip pressure more strongly influenced the paper structural properties than third nip pressure in triple nip pressing condition. Because of the high water content and low wet-web strength of paper web in first nip, increasing the first nip pressure induced the incipient crushing of wet-web and then caused a potential of web break during the following coating or printing processes.

An Efficient Decision Maki ng Method for the Selectionof a Layered Manufacturing (3차원 조형장비 선정을 위한 효율적인 의사결정 방법)

  • Byun, Hong-Seok
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.18 no.1
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    • pp.59-67
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    • 2009
  • The purpose of this study is to provide a decision support to select an appropriate layered manufacturing(LM) machine that suits the application of a part. Selection factors include concept model, form/fit/functional model, pattern model far molding, material property, build time and part cost that greatly affect the performance of LM machines. However, the selection of a LM is not an easy decision because they are uncertain and vague. For this reason, the aim of this research is to propose hybrid multiple attribute decision making approaches to effectively evaluate LM machines. In addition, because subjective considerations are relevant to selection decision, a fuzzy logic approach is adopted. The proposed selection procedure consists of several steps. First, we identify LM machines that the users consider After constructing the evaluation criteria, we calculate the weights of the criteria by applying the fuzzy Analytic Hierarchy Process(AHP) method. Finally, we construct the fuzzy Technique of Order Preference by Similarity to Ideal Solution(TOPSIS) method to achieve the ranking order of all machines providing the decision information for the selection of LM machines.

Estimation of Automatic Video Captioning in Real Applications using Machine Learning Techniques and Convolutional Neural Network

  • Vaishnavi, J;Narmatha, V
    • International Journal of Computer Science & Network Security
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    • v.22 no.9
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    • pp.316-326
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    • 2022
  • The prompt development in the field of video is the outbreak of online services which replaces the television media within a shorter period in gaining popularity. The online videos are encouraged more in use due to the captions displayed along with the scenes for better understandability. Not only entertainment media but other marketing companies and organizations are utilizing videos along with captions for their product promotions. The need for captions is enabled for its usage in many ways for hearing impaired and non-native people. Research is continued in an automatic display of the appropriate messages for the videos uploaded in shows, movies, educational videos, online classes, websites, etc. This paper focuses on two concerns namely the first part dealing with the machine learning method for preprocessing the videos into frames and resizing, the resized frames are classified into multiple actions after feature extraction. For the feature extraction statistical method, GLCM and Hu moments are used. The second part deals with the deep learning method where the CNN architecture is used to acquire the results. Finally both the results are compared to find the best accuracy where CNN proves to give top accuracy of 96.10% in classification.

Virtual Machine Code Optimization using Profiling Data (프로파일링 데이터를 이용한 가상기계 코드 최적화)

  • Shin, Yang-Hoon;Yi, Chang-Hwan;Oh, Se-Man
    • The KIPS Transactions:PartA
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    • v.14A no.3 s.107
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    • pp.167-172
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    • 2007
  • VM(Virtual Machine) can be considered as a software processor which interprets the machine code. Also, it is considered as a conceptional computer that consists of logical system configuration. But, the execution speed of VM system is much slower than that of a real processor system. So, it is very important to optimize the code for virtual machine to enhance the execution time. Especially the optimizer for a virtual machine code on embedded devices requires the highly efficient performance to the ordinary optimizer in the respect to the optimized ratio about cost. Fundamentally, functions and basic blocks which influence the execution time of virtual machine is found, and then an optimization for them nay get the high efficiency. In this paper, we designed and implemented the optimizer for the virtual(or abstract) machine code(VMC) using profiling. Firstly, we defined the profiling information which is necessary to the optimization of VMC. The information can be obtained from dynamically executing the machine code. And we implemented VMC optimizer using the profiling information. In our implementation, the VMC is SIL(Standard Intermediate Language) that is an intermediate code of EVM(Embedded Virtual Machine). Also, we tried a benchmark test for the VMC optimizer and obtained reasonable results.