• Analytical Science and Technology
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• v.27 no.5
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• pp.243-247
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• 2014

Formaldehyde is defined as carcinogen causing leukaemia, lymphoma or nasopharyngeal carcinoma at high level of exposure. Furniture-manufacturing workers can be exposed to formaldehyde, which implies serious impact on health of the workers. The authors carried out ambient monitoring of formaldehyde in the field, and identified the source of formaldehyde generated during the working process by testing the condition in the laboratory settings. After sampling formaldehyde in the air with 2,4-DNPH (2,4-dinitrophenylhydrazine) coated silica gel, we extracted formaldehyde derivative with acetonitrile and analyzed the extract using HPLC with UV detector at 360 nm. Formaldehyde was separated by ACQUITY UPLC BEH $C_{18}$ column at a flow rate of 0.5 mL/min using 45% acetonitrile as mobile phase. The workers were exposed to higher level of formaldehyde than normal air. Formaldehyde up to 0.31 ppm was detected in the process of veneer attachment, which exceeded 0.3 ppm, the ceiling value of ACGIH standard. The laboratory test of measuring formaldehyde generated from the glue and veneer used in the attachment process resulted in more formaldehyde generation as the temperature increased, and more from the veneer. Heating the veneer to $100-150^{\circ}C$ following the real condition of the manufacturing site generated 1.14-2.70 ppm of formaldehyde from the sample, which was 2-5 times higher level than Korean limit of exposure (0.5 ppm). As the workers handling and processing the veneer which was produced by wet process had high possibility to be exposed to formaldehyde, urgent improvement and management of working environment of furniture manufacturer is demanded.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.285-290
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• 2016

In rural area, our farmers confront decreasing benefits owing to imported crops and increased cost. Recently, the government encourage the 6th Industry that merges farming, rural resources, and information and communication technology. Therefor the government makes an investment in supplying 'smart greenhouse' in which a farmer monitor growing crops and environment information to control growing condition. The objective of this study is developing an Moving Monitor and Control System for crops in green House. This system includes a movable sensing unit, a controlling unit, and a server PC unit. The movable sensing unit contains high resolution IP camera, temperature and humidity sensor and WiFi repeater. It rolls on a rail hanging beneath the ceiling of a green house. The controlling unit contains embedded PC, PLC module, WiFi router, and BLDC motor to drive the movable sensing unit. And the server PC unit contains a integrated farm management software and home pages and databases in which the images of crops and environment informations. The movable sensing unit moves widely in a green house and gathers lots of information. The server saves these informations and provides them to customers with the direct commercing web page. This system will help farmers to control house environment and sales their crops in online market. Eventually It will be helpful for farmers to increase their benefits.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.3
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• pp.167-171
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• 2004

The growth of soybean sprout was greatly influenced by watering systems： Fixed watering system (water tub was loaded at ceiling upper of culture box and water was showered by bottom holes) was estimated the better than that of reciprocating watering and tub immersing watering because it could cool down the temperature in culture box and wash the organic substances on the body of sprout. The fixed watering system showed good body color and preventing effect of partial rotting of sprout because it could discharge $\textrm{CO}_2$ gas effectively in culture box and keep the concentration below 5%. The concentration of gases at the bottom (about 30 cm height from basal plate) of culture box in fourth or fifth days was L6% for $\textrm{CO}_2$ and 13-16% for $\textrm{O}_2$, respectively. The optimum gas concentration in culture box was considered to be over 10% for $\textrm{O}_2$ and below 5% for $\textrm{CO}_2$.