• Journal of the Korean Society of Safety
• /
• v.34 no.4
• /
• pp.22-31
• /
• 2019

The flammable liquid conductivity is an important factor in determining the generation of electrostatic in fire and explosion hazardous areas, so it is necessary to study the physical properties of flammable liquids. In particular, the relevant liquid conductivity in the process of handling flammable liquids in relation to the risk assessment and risk control in fire and explosion hazard areas, such as chemical plants, is classified as a main evaluation item according to the IEC standard, and it is necessary to have flammable liquid conductivity measuring devices and related data are required depending on the handling conditions of the material, such as temperature and mixing ratio for preventing the fire and explosion related to electrostatic. In addition, IEC 60079-32-2 [Explosive Atmospheres-Part 32-2 (Electrostatic hazards-Tests)] refers to the measuring device standard and the conductivity of a single substance. It was concluded that there is no measurement data according to the handling conditions such as mixing ratio of flammable liquid and temperature together with the use and measurement examples. We have developed the measurement reliability by improving the structure, material and measurement method of measuring device by referring to the IEC standard. We have developed a measurement device that is developed and manufactured by itself. The test results of flammable liquid conductivity measurement and the data of the NFPA 77 (Recommended Practice on Static Electricity) Annex B Table B.2 Static Electric Characteristic of Liquids were compared and verified by conducting the conductivity measurement of the flammable liquid handled in the fire and explosion hazardous place by using Measuring / Data Acquisition / Processing / PC Communication. It will contribute to the prevention of static electricity related disaster by taking preliminary measures for fire and explosion prevention by providing technical guidance for static electricity risk assessment and risk control through flammable liquid conductivity measurement experiment. In addition, based on the experimental results, it is possible to create a big data base by constructing electrostatic physical characteristic data of flammable liquids by process and material. Also, it is analyzed that it will contribute to the foundation composition for adding the specific information of conductivity of flammable liquid to the physical and chemical characteristics of MSDS.

• Journal of the Korean Society of Radiology
• /
• v.13 no.5
• /
• pp.757-763
• /
• 2019

Recently, Following the recent development of flat panel detector with wide dynamic ranges, increasing numbers of healthcare providers have begun to use digital radiography. As a result, filter thickness standards should be reestablished, as current clinical practice requires the use of thicknesses recommended by the National Council on Radiation Protection and Measurements, which are based on information, acquired using conventional analog systems. Here we investigated the possibility of minimizing dose creep and optimizing patient dose using Al filters in digital radiography. The use of thicker Al filters resulted in a maximum 19.3% reduction in the entrance skin exposure dose when medical images with similar sharpness values were compared. However, resolution, which is a critical factor in imaging, had a significant change of 1.01 lp/mm. This change in resolution is thought to be due to the increased amount of scattered rays generated from the object due to the X-ray beam hardening effect. The increase in the number of scattered rays was verified using the scattering degradation factor. However, the FPD, which has recently been developed and is widely used in various areas, has greater response to radiation than analog devices and has a wide dynamic range. Therefore, the FPD is expected to maintain an appropriate level of resolution corresponding to the increase in the scattered-ray content ratio, which depends on filter thickness. Use of the FPD is also expected to minimize dose creep by reducing the exposure dose.

• Journal of the Korean Society of Radiology
• /
• v.13 no.5
• /
• pp.765-771
• /
• 2019

Noise in skull X-ray imaging is inevitable, which reduces imaging quality and diagnostic accuracy and increases errors due to the nature of digital imaging devices. Increasing the dose can attenuate noise, but that could lead to big problems with higher exposure dose received by patients. Thus, noise reduction algorithms are actively being studied at low doses to solve dose problems and reduce noise at the same time. Wiener filter and median filter have been widely used, with the disadvantages of poor noise reduction efficiency and loss of much information about imaging boundary. The purpose of this study is to apply total variation (TV) algorithm to skull X-ray imaging that can compensate for the problems of previous noise reduction efficiency to assess quantitatively and compare them. For this study, skull X-ray imaging is obtained using various kVp and mAs using the skull phantom using the X-ray device of Siemens. In addition, contrast to noise ratio (CNR) and coefficient of variation (COV) are compared and measured when noisy image, median filter, Wiener filter and TV algorithm were applied to each phantom imaging. Experiments showed that when TV algorithms were applied, CNR and COV characteristics were excellent under all conditions. In conclusion, we've been able to see if we can use TV algorithm to improve image quality and CNR could be seen to increase due to the decrease in noise as the amount of increased mAs. On the other hand, COV decreased as the amount of increased mAs, and when kVp increased, noise was reduced and the transmittance was increased, so COV was reduced.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.6
• /
• pp.77-83
• /
• 2020

The heat treatment facility is in a situation where the scope of application of the remote IOT system is expanding due to the harsh environment caused by high heat and long working hours among the root industries. In this heat treatment process environment, the IOT middleware is required to play a pivotal role in interpreting, managing and controlling data information of IoT devices (sensors, etc.). Until now, the system controlled by the heat treatment remotely was operated with the command of the operator's batch system without overall monitoring of the site situation. However, for the safety and precise control of the heat treatment facility, it is necessary to control various sensors and recognize the surrounding work environment. As a solution to this, the heat treatment safety support system presented in this paper proposes a support system that can detect the access of the work manpower to the heat treatment furnace through thermal image detection and operate safely when ordering work from a remote location. In addition, an OPEN CV-based deterioration analysis system using DNN deep learning network was constructed for faster and more accurate recognition than general fixed hot spot monitoring-based thermal image analysis. Through this, we would like to propose a system that can be used universally in the heat treatment environment and support the safety management specialized in the heat treatment industry.

• Journal of Convergence for Information Technology
• /
• v.11 no.6
• /
• pp.33-39
• /
• 2021

Speech recognition technology is being combined with deep learning and is developing at a rapid pace. In particular, voice recognition services are connected to various devices such as artificial intelligence speakers, vehicle voice recognition, and smartphones, and voice recognition technology is being used in various places, not in specific areas of the industry. In this situation, research to meet high expectations for the technology is also being actively conducted. Among them, in the field of natural language processing (NLP), there is a need for research in the field of removing ambient noise or unnecessary voice signals that have a great influence on the speech recognition recognition rate. Many domestic and foreign companies are already using the latest AI technology for such research. Among them, research using a convolutional neural network algorithm (CNN) is being actively conducted. The purpose of this study is to determine the non-voice section from the user's speech section through the convolutional neural network. It collects the voice files (wav) of 5 speakers to generate learning data, and utilizes the convolutional neural network to determine the speech section and the non-voice section. A classification model for discriminating speech sections was created. Afterwards, an experiment was conducted to detect the non-speech section through the generated model, and as a result, an accuracy of 94% was obtained.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.1
• /
• pp.82-88
• /
• 2021

Sun-induced fluorescence (SIF) retrieval using remote sensing technique has been used in an effort to understand the photosynthetic efficiency and stress condition of vegetation. Although optical devices and SIF retrieval methodologies were established in order to retrieve SIF, the SIF measurements are domestically sparse. SIF data of paddy rice w as measured in Naju, South Korea from June 10, 2020 to October 5, 2020. The SIFs based red (O2A) and far-red (O2B) w ere retrieved using a spectral fitting method and an improved Fraunhofer line depth, and photosynthetically active radiation was also produced. In addition, the SIF data was filtered considering solar zenith angle, saturation conditions, the rapid and sudden change of solar irradiance, and sun glint. The provided SIF data can help to understand a SIF product and the filtering method of SIF data can contribute to producing high-quality SIF data.

• The Journal of the Korea Contents Association
• /
• v.21 no.4
• /
• pp.77-87
• /
• 2021

Smart Factory refers to a factory that can be controlled by itself with an intelligent factory that improves productivity, quality and customer satisfaction by combining the entire process of manufacturing and production with digital automation solutions. The manufacturing industry around the world is rapidly changing, with Germany, Europe, and the United States at the center. In order to cope with such changes, the Korean government is also implementing a policy to spread the supply of smart factories for small and medium-sized companies, and related ministries and agencies such as the Ministry of Commerce, Industry and Energy, the Ministry of SMEs and Venture Business, the Korea Institute of Technology and Information Promotion, and local technoparks, as well as large companies such as Samsung, SK and LG are actively investing in smart manufacturing projects to support smart factories[1]. Factory Automation (FA) construction has many issues regarding the connection of heterogeneous equipment. The most difficult aspect of configuring various communications from various equipment is the reason. Although it may not be known if there are standards or products made up of the same company, it is not easy to build equipment that is old, up-to-date, and different use environments through a series of communications. To solve this problem, we would like to propose a method of communication using Modbus, one of FieldBus, which is one of the many industrial devices of PLC, a representative facility control system, and is used as a communication standard.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.6
• /
• pp.243-250
• /
• 2021

With the increased development of 3D VR applications augmented by recent VR/AR/MR technologies and by the advance of 3D devices, interchangeability and portability of 3D data have become essential. 3D files should be processed in a standard data format for common usage between applications. Providing standardized libraries and data structures along with the standard file format means that a more efficient system organization is possible and unnecessary processing due to the usage of different file formats and data structures depending on the applications can be omitted. In order to provide the function of using a common data file and data structure, this research is intended to provide a programming binding tool for generating and storing standardized data so that various services can be developed by accessing the common 3D files. To achieve this, this paper defines a common data structure including classes and functions to access X3D files with a standardized scheme using the Python programming language. It describes the implementation of a Python language binding viewer, which is an X3D VR viewer for rendering standard X3D data files based on the language binding interface. The VR viewer includes Python based 3D scene libraries and a data structure for creation, modification, exchange, and transfer of X3D objects. In addition, the viewer displays X3D objects and processes events using the libraries and data structure.

• Korean Chemical Engineering Research
• /
• v.60 no.1
• /
• pp.1-6
• /
• 2022

As the demand for wearable devices increases, many studies have been studied on the development of flexible electrode materials recently. In particular, the development of high-performance flexible electrode materials is very important for wearable sensors for healthcare because it is necessary to continuously monitor and accurately detect body information such as body temperature, heart rate, blood glucose, and oxygen concentration in real time. In this study, we fabricated the nonenzymatic glucose sensor based on polyaniline/carbon nanotube fiber (PANI/CNT fiber) electrode. PANI layer was synthesized on the flexible CNT fiber electrode through electrochemical polymerization process in order to improve the performance of a flexible CNT fiber based electrode material. Surface morphology of the PANI/CNT fiber electrode was observed by scanning electron microscopy. And its electrochemical characteristics were investigated by chronoamperometry, cyclic voltammetry, electrochemical impedance spectroscopy. Compared to bare CNT fiber electrode, this PANI/CNT fiber electrode exhibited small electron transfer resistance, low peak separation potential and large surface area, resulting in enhanced sensing properties for glucose such as wide linear range (0.024~0.39 and 1.56~50 mM), high sensitivity (52.91 and 2.24 ㎂/mM·cm²), low detection limit (2 μM) and good selectivity. Therefore, it is expected that it will be possible to develop high performance CNT fiber based flexible electrode materials using various nanomaterials.

• Journal of Industrial Convergence
• /
• v.20 no.3
• /
• pp.33-40
• /
• 2022

Recently, IoT-linked services have been used in various environments, and IoT and artificial intelligence technologies are being fused. However, since technologies that process IoT data stably are not fully supported, research is needed for this. In this paper, we propose a processing technique that can optimize IoT data after generating embedded vectors based on machine learning for IoT data. In the proposed technique, for processing efficiency, embedded vectorization is performed based on QR such as index of IoT data, collection location (binary values of X and Y axis coordinates), group index, type, and type. In addition, data generated by various IoT devices are integrated and managed so that load balancing can be performed in the IoT data collection process to asymmetrically link IoT data. The proposed technique processes IoT data to be orthogonalized based on hash so that IoT data can be asymmetrically grouped. In addition, interference between IoT data may be minimized because it is periodically generated and grouped according to IoT data types and characteristics. Future research plans to compare and evaluate proposed techniques in various environments that provide IoT services.