• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.470-472
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• 2006

Sensor networks are the results of convergence of very important technologies such as wireless communication and micro electromechanical systems. In recent years, sensor networks found a wide applicability in various fields such as environment and health, industry scene system monitoring, etc. A very important step for these many applications is pattern classification and recognition of data collected by sensors installed or deployed in different ways. But, pattern classification and recognition are sometimes difficult to perform. Systematic approach to pattern classification based on modem learning techniques like Multivariate Gaussian mixture models, can greatly simplify the process of developing and implementing real-time classification models. This paper proposes a new recognition system which is hierarchically composed of many sensor nodes having the capability of simple processing and wireless communication. The proposed system is able to perform context classification of sensed data using the Multivariate Gaussian function. In order to verify the usefulness of the proposed system, it was applied to intelligent dust collecting system.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.715-717
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• 1999

In this study, an intelligent solenoid valve controller has been developed for automatic maintaining of filters in a dust collecting system. This controller has automatic controllability of solenoid valves' ON/OFF time depending on the clogging status of filters, and then it can extend the filters' lifetimes, decrease the power consumption, and make effective operation of the system possible. This controllability has been executed by the fuzzy theory that utilizes the workers' experimental knowledges, the control expert's knowledges and the differential pressures between the inlets and outlets measured by the sensors.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.239-245
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• 2000

This study is aimed to develop the historical data management system named "ACON"(Actual COst Network system) which can be used for collecting, analysis and modification of the historical data. ACON_Local is used for collecting the historical data at each spot place. It redueces the work potential of managers, spending time and cost. ACON_Analysis is to analyze the collection , modifies the data′s error and updates the historical database. ACON_Network is developed to transfer data from ACON to Web server or opposites. The proposed model, ACON, provide the easy way for the cost estimate system, "HiCOMS" to collect, analyze and modify the historical cost evaluated data, which is used to compose the historical data base.

• Plant Resources
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• v.8 no.1
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• pp.13-16
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• 2005

This study was conducted to develop effective production system in greenhouse for leaves and stems of Angelica acutiloba by fertilizing of Sta-Green in pots. The results obtained are summarized as follows. Germination rate of Angelica acutiloba seeds collected in 2003 was $13\%$, while germination rate of seeds Collected in 2004 was above $91\%$. Seed germination rate and plant biomass of Angelica acutiloba collected in 2004 were higher than seed gathering in 2003. Especially, plant growth and yield of Angelica acutiloba grown in pot(The pots was filled with soil mixtures of Sta-Green and Peat Moss mixed with 45:55 ratio.) was the highest. These results indicate that leaf and stem production of Angelica acutiloba can be improved by fertilizing of Sta-Green in pots and optimizing seed collecting time in greenhouse.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.33-40
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• 2021

Recently, wearable computers equipped with various biosensors such as smart watches, smart bands, and smart patches that support daily health management of users as well as patients have been released. Users of wearable computers such as smart watches face various difficulties in performing biometric information processes such as data sensing, collection, transmission, real-time analysis, and feedback in a weak wireless and mobile biometric information service environment. In particular, the biometric information collection interface is an important basic process that determines the quality and performance of the entire biometric information service. So far, research has focused on sensing hardware and logic. This study intensively considers the interface method for effectively sensing and collecting raw biometric information. In particular, the process of collecting biometric information is designed and analyzed from the perspective of periodicity. Therefore, we propose an efficient and stable periodic collection method.

• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.4
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• pp.53-59
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• 1990

To suggest the fundamental data for development of the soil improvement method which increases the permeability in aquifer by jet water, laboratory tests were performed. The results obtained are as follows : 1. The diameter of the improved section was maximum value when the time of water jetting was about 4 minutes, and it was not increased according as the time of water jetting was longer than 4 minutes. 2. It appeared that 2.78 mm in diameter of the nozzle was the most optimum size in the condition of using the 1/8 HP - pump and the diameter of improved section in that case was 15.9cm 3. According to removing fine - soil particles, the original soil was improved, suitable to the purpose of improving, and then the permeability of the improved soil was 100 times of that of the original soil. 4. As the improved soil was satisfied to the design criteria of filter materials, the improvement method in this study will be useful for constructing underground collecting channels or underground collecting drainage canals.

• The Korea Journal of Herbology
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• v.27 no.5
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• pp.27-35
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• 2012

Objectives : The purpose of this study was to characterize the effect of the fraction of Taraxacum officinale and T.coreanum on the learning and memory impairments induced by scopolamine. Methods : The cognition-enhancing effect of Taraxacum officinale and T.coreanum was investigated using a passive avoidance test, the Morris water maze test and Y-maze test in mice. Drug-induced amnesia was induced by treating animals with scopolamine (1 mg/kg, i.p.). Results : The results showed that the Aug harvested T.offiicinale extract-treated group (200 mg/kg, p.o.) and the tacrine-treated group (10 mg/kg, p.o.) significantly ameliorated scopolamine-induced amnesia based on the Passive avoidance Y-maze test and Watermaze test. And these results are same manner in DPPH radical scavenger effect and Acetylcholineseterase inhibition effect. Conclusions : These results suggest that Taraxacum officinale extract maybe a useful cognitive impairment treatment, and its beneficial effects are depending on the collecting time and origin plants. As a result, Taraxacum officinale harvested in August improve memory most.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.33-34
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• 2006

Computer Forensics is a research area which finds the malicious users by collecting and analyzing the intrusion or infringement evidence of the computer crime. Many research about Computer Forensics has been done. But those research have focussed on how to collect the evidence after receiving the damage reports from computer users or network administrators. This paper describes about collecting the evidence of good quality at the time of infringement occurrence by the malicious user. By calculating Infringement severity of observable and protective hosts and referring to this value, we collect the evidence at the time of infringement occurrence to minimize the information modification of the evidence. We can reduce also the amount of logs that we use to analyze the infringement and can minimize the loss of the evidence.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.4
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• pp.909-916
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• 2010

In ubiquitous GIS services is possible to use the spatio-temporal data using a mobile device at anytime. Also, client is transmitted latest spatio-temporal data from server. But traditional systems have a problem that the time of transmitting latest information from server to client takes long time because of collecting data periodically. In this paper, we proposed Two-way Synchronization system supporting field update to solve the existing problem. This system uses mobile device for collecting changed data in the real world and sending collected data to server.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.173-180
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• 2023

Smart factory companies are installing various sensors in production facilities and collecting field data. However, there are relatively few companies that actively utilize collected data, academic research using field data is actively underway. This study seeks to develop a model that detects anomalies in the process by analyzing spindle power data from a company that processes shafts used in automobile throttle valves. Since the data collected during machining processing is time series data, the model was developed through unsupervised learning by applying the Holt Winters technique and various deep learning algorithms such as RNN, LSTM, GRU, BiRNN, BiLSTM, and BiGRU. To evaluate each model, the difference between predicted and actual values was compared using MSE and RMSE. The BiLSTM model showed the optimal results based on RMSE. In order to diagnose abnormalities in the developed model, the critical point was set using statistical techniques in consultation with experts in the field and verified. By collecting and preprocessing real-world data and developing a model, this study serves as a case study of utilizing time-series data in small and medium-sized enterprises.