• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.3106-3106
• /
• 2001

Imaging spectrometry or hyperspectral imaging is a recent development that makes possible quantitative and qualitative measurement for food quality and safety. This paper presents the research results that a hyperspectral imaging system can be used effectively for detecting fecal (from duodenum, cecum, and colon) and ingesta contamination on poultry carcasses from the different feed meals (wheat, mile, and corn with soybean) for poultry safety inspection. A hyperspectral imaging system has been developed and tested for the identification of fecal and ingesta surface contamination on poultry carcasses. Hypercube image data including both spectral and spatial domains between 430 and 900 nm were acquired from poultry carcasses with fecal and ingesta contamination. A transportable hyperspectral imaging system including fiber optically fabricated line lights, motorized lens control for line scans, and hypercube image data from contaminated carcasses with different feeds are presented. Calibration method of a hyperspectral imaging system is demonstrated using different lighting sources and reflectance panels. Principal Component and Minimum Noise Fraction transformations will be discussed to characterize hyperspectral images and further image processing algorithms such as image band ratio of dual-wavelength images and its histogram stretching with thresholding process will be demonstrated to identify fecal and ingesta materials on poultry carcasses. This algorithm could be further applied for real-time classification of fecal and ingesta contamination on poultry carcasses in the poultry processing line.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.4
• /
• pp.933-939
• /
• 2015

If the Visual Aids(light wave signs) is not supplied the general power it is using solar power system. These power supply systems, the role of the charge/discharge control is very important. Introduction of IT(AIS etc.) for the effective management of the AtoN(Aids to Navigation) is a Visual Aids has been added to the device using the power to charge/discharge control, the need increases. The current charge/discharge controller is attached to the inside of the AtoN and checks on and verification of the maritime environment, depending on the difficulty. In order to resolve these issues in this paper, the Bluetooth module is mounted on the inside of the charge/discharge controller and proposed a possible system monitoring at close range. Advantage of the system implemented is a simple configuration and low installation cost. In addition, it can be applied to a variety of AtoN. Also, it has been able to check the real-time status information of the charge/discharge controller at a short distance in to reduce inspection costs, and reduce risk factors that might occur during check.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.12 no.5
• /
• pp.29-37
• /
• 2017

In this study, real-time monitoring is carried out in the factory site for product quality control such as improvement of productivity through facility automation, improvement of product quality, improvement of factory environment, check of facility maintenance status and check of product defect, And to establish a smart factory for the purpose of protecting the personal environment of the worker. The company is an auto parts company located in the province. The main research content is development of automation and monitoring system of oil filter clipping necessary for smart factory. Smart factory oil filter clipping automation is divided into electric air parts, solenoid valve and other parts processing process. Smart factory quality inspection monitoring system is implemented by server PC and S / W, client software, Operator PC, operating program, and input terminal application. This research data is expected to be very useful data for the auto parts venture companies that are promoting smart factories.

• Smart Structures and Systems
• /
• v.26 no.2
• /
• pp.227-239
• /
• 2020

Despite proven effectiveness and accuracy in laboratories, the existing damage assessment based on guided ultrasonic waves (GUWs) or acoustic emission (AE) confronts challenges when extended to real-world structural health monitoring (SHM) for railway tracks. Central to the concerns are the extremely complex signal appearance due to highly dispersive and multimodal wave features, restriction on transducer installations, and severe contaminations of ambient noise. It remains a critical yet unsolved problem along with recent attempts to implement SHM in bourgeoning high-speed railway (HSR). By leveraging authors' continued endeavours, an SHM framework, based on actively generated diffuse ultrasonic waves (DUWs) and a benchmark-free condition contrast algorithm, has been developed and deployed via an all-in-one SHM system. Miniaturized lead zirconate titanate (PZT) wafers are utilized to generate and acquire DUWs in long-range railway tracks. Fatigue cracks in the tracks show unique contact behaviours under different conditions of external loads and further disturb DUW propagation. By contrast DUW propagation traits, fatigue cracks in railway tracks can be characterised quantitatively and the holistic health status of the tracks can be evaluated in a real-time manner. Compared with GUW- or AE-based methods, the DUW-driven inspection philosophy exhibits immunity to ambient noise and measurement uncertainty, less dependence on baseline signals, use of significantly reduced number of transducers, and high robustness in atrocious engineering conditions. Conformance tests are performed on HSR tracks, in which the evolution of fatigue damage is monitored continuously and quantitatively, demonstrating effectiveness, adaptability, reliability and robustness of DUW-driven SHM towards HSR applications.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.16 no.1
• /
• pp.120-130
• /
• 2012

As long span and complex bridges are constructed often recently, safety estimation became a big issue. Various types of measuring instruments are installed in case of long span bridge. New wireless technologies for long span bridges such as sending information through a gateway at the field or sending it through cables by signal processing the sensing data are applied these days. However, The case of occurred accidents related to bridge in the world have been reported that serious accidents occur due to lack of real-time proactive, intelligent action based on recognition accidents. To solve this problem in this study, the idea of "communication among things", which is the basic method of RFID/USN technology, is applied to the bridge monitoring system. A sensor node module for USN based intelligent bridge system in which sensor are utilized on the bridge and communicates interactively to prevent accidents when it captures the alert signals and urgent events, sends RF wireless signal to the nearest traffic signal to block the traffic and prevent massive accidents, is designed and tested by performing TinyOS based middleware design and sensor test free Space trans-receiving distance.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.10 no.3
• /
• pp.165-175
• /
• 2006

To analyze the deformation and failure of slopes, generally, two types of model, Polynomial model and Growth model, are applied. These two models are focused on the behavior of the slope by time. Therefore, this research is more focused on predicting of slope failure than analyzing the slope behavior by time. Generally, Growth model is used to analyze the soil slope, to the contrary, Polynomial model is used for rock slope. However, 3-degree polynomial($y=ax^3+bx^2+cx+d$) is suggested to combine two models in this research. The main trait of this model is having an asymptote. The fields to adopt this model are Gosujae Danyang(soil slope) and Youngduk slope(rock slope), which are the cut-slope near national road. Data from Gosujae are shown the failure traits of soil slope, to the contrary, those of Youngduk slope are shown the traits of rock slope. From the real-time monitoring data of the slope, 3-degree polynomial is proved as excellent system to analyze the failure and behavior of slope. In case of Polynomial model, even if the order of polynomials is increased, the $R^2$ value and shape of the curve-fitted graph is almost the same.

• Journal of Korean Society for Geospatial Information Science
• /
• v.20 no.1
• /
• pp.33-41
• /
• 2012

BIS is an arrival guidance system which is able to supply passengers with bus service condition via Kiosks at a bus stop, internet and mobile service through pinpointing bus location in real time. It is very significant to improve the quality of traffic information by quality control of GIS-based bus network so as to maintain navigational information and to implement reliable BIS. Therefore this study aims to build criteria to quantitatively evaluate data quality of the product in accordance with the process in bus network data and to suggest guideline of quality control. To achieve this, we have categorized geometric and logical errors occurring during constructing bus network database by giving a specific case study on TAGO and set up sectional guideline and procedures to examine database for systematic and coherent quality control management. Proceeding from what has been said above, the outcome of our research leads to quality guarantee for objective and reliable bus network database and is fully expected to bring benefit of providing a more accurate public transportation information and improving reliability of BIS through preventing a variety of errors in system operation in advance.

• Journal of the Korea Society for Simulation
• /
• v.32 no.3
• /
• pp.93-108
• /
• 2023

In manufacturing productivity analysis, understanding the intricate interplay among factors like facility performance, layout design, and workforce allocation within the production line is imperative. This paper introduces a simulation-based methodology tailored to food manufacturing, progressively expanding scenarios to analyze production enhancement. The target system is a food processing plant, encompassing production processes, including warehousing, processing, subdivision, packaging, inspection, loading, and storage. First, we analyze the target system and design a simulation model according to the actual layout arrangement of equipment and workers. Then, we validate the developed model reflecting the real data obtained from the target system, such as the workers' working time and the equipment's processing time. The proposed model aims to identify optimal factor values for productivity gains through incremental scenario comparisons. To this end, three stages of simulation experiments were conducted by extending the equipment and worker models of the subdivision and packaging processes. The simulation experiments have shown that productivity depends on the placement of skilled workers and the performance of the packaging machine. The proposed method in this study will offer combinations of factors for the specific production requirements and support optimal decision-making in the real-world field.

• Convergence Security Journal
• /
• v.19 no.2
• /
• pp.83-89
• /
• 2019

In accordance with information security compliance and security regulations, there is a need to develop regular and real-time concepts for cyber-infringement attacks against network system vulnerabilities in branch and periodic forms. Vulnerability Analysis Analysis It is judged that it will be a countermeasure against new hacking attack in case of concept validation by interworking with TOOL. Vulnerability check module is standardized in event attribute management and ease of operation. Opening in terms of global sharing of vulnerability data, owasp zap / Angry ip Etc. were investigated in the SIEM system with interlocking design implementation method. As a result, it was proved that the inspection events were monitored and transmitted to the SIEM console by the vulnerability module of web and network target. In consideration of this, ESM And SIEM system In this paper, we propose a new vulnerability analysis method based on the existing information security consultation and the results of applying this study. Refer to the integrated interrelationship analysis and reference Vulnerability target Goal Hacking It is judged to be a new active concept against invasion attack.

• International conference on construction engineering and project management
• /
• 2024.07a
• /
• pp.152-159
• /
• 2024

Cracks in structural materials present a critical challenge to infrastructure safety and long-term durability. Timely and precise crack detection is essential for proactive maintenance and the prevention of catastrophic structural failures. This study introduces an innovative approach to tackle this issue using U-Net deep learning architecture. The primary objective of the intended research is to explore the potential of U-Net in enhancing the precision and efficiency of crack detection across various concrete crack detection under various environmental conditions. Commencing with the assembling by a comprehensive dataset featuring diverse images of concrete cracks, optimizing crack visibility and facilitating feature extraction through advanced image processing techniques. A wide range of concrete crack images were collected and used advanced techniques to enhance their visibility. The U-Net model, well recognized for its proficiency in image segmentation tasks, is implemented to achieve precise segmentation and localization of concrete cracks. In terms of accuracy, our research attests to a substantial advancement in automated of 95% across all tested concrete materials, surpassing traditional manual inspection methods. The accuracy extends to detecting cracks of varying sizes, orientations, and challenging lighting conditions, underlining the systems robustness and reliability. The reliability of the proposed model is measured using performance metrics such as, precision(93%), Recall(96%), and F1-score(94%). For validation, the model was tested on a different set of data and confirmed an accuracy of 94%. The results shows that the system consistently performs well, even with different concrete types and lighting conditions. With real-time monitoring capabilities, the system ensures the prompt detection of cracks as they emerge, holding significant potential for reducing risks associated with structural damage and achieving substantial cost savings.