• Journal of the Korean Society of Industry Convergence
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• v.22 no.5
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• pp.499-509
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• 2019

This paper discusses energy use monitoring and analysis as part of a study on a low-cost energy supply management system that links an existing database with weather information with no real-time monitor for energy demand of buildings using renewable energy, generator and energy storage systems. This study is targeted at small and medium-sized buildings and aims to monitor energy use with a small number of sensors at low cost by applying an energy management system (EMS). The present study can help overcome the limitations of high-cost EMS applied to large commercial and public buildings. We developed current, indoor temperature and human motion sensors and installed them in an office of a company in a sample building. Through these sensors, we analyzed energy use patterns and the effects of weather information and human motion on the energy use. Furthermore, we analyzed the correlations between the total KEPCO energy use of the sample building and weather by comparing these two data. The results showed that the office energy use of a company was more affected by human motions than by weather information. The comparison between the total energy use of the Building and weather information found that external temperature had an effect on the energy use.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.263-272
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• 2008

The proposed system can achieve more safety of RFID system with the 2-step authentication procedures for the enhancement about the security of general RFID systems. After it has authenticated RFID tag, additionally, the proposed system extract the characteristic information in the user image for acquisition of the additional authentication information of the user with the camera. In this paper, the system which was proposed more enforce the security of the automatic entrance and exit authentication system with the cognitive characters of RFID tag and the extracted characteristic information of the user image through the camera. The RFID system which use the active tag and reader with 2.4GHz bandwidth can recognize the tag of RFID in the various output manner. Additionally, when the RFID system have errors. the characteristic information of the user image is designed to replace the RFID system as it compare with the similarity of the color, outline and input image information which was recorded to the database previously. In the experimental result, the system can acquire more exact results as compared with the single authentication system when it using RFID tag and the information of color characteristics.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.21-30
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• 2021

Unlike behaviors that are generally known, information regarding unspecific behaviors is insufficient. For an education or guidance regarding the unspecific behaviors, collection and management of data regarding the unspecific behaviors of special-needs students are needed. In this paper, a consultation management model based on behavior classification of special-needs students using machine learning is proposed. It collects data by photographing the behavior of special students in real time, analyzes the behavior pattern, composes a data set, and trains it in the suggestion system. It is possible to improve the accuracy by comparing the behavior of special students photographed later into the suggestion system and analyzing the results by comparing it with the existing data again. The test has been performed by arbitrarily applying unspecific behaviors that are not stored in the database, and the forecast model has accurately classified and grouped the input data. Also, it has been verified that it is possible to accurately distinguish and classify the behaviors through the feature data of the behaviors even if there are some errors in the input process.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.230-233
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• 2016

In this paper, we developed the ice machine conditions monitoring system that confirms conditions of the ice machine. The developed system is composed of Communication Board, Server Program, and Web-based User Application. Communication Board which is connected to the ice machine periodically sends various data, such as current, voltage, the refrigerant pressure and temperature, the external temperature and humidity. Server Program stores the data received from Communication Board into database. The manager or the ice machine operator can see the state of the own machine through User Application based on Web. When a symptom is detected on the ice machine, the manager and the operator can checks the current condition of the ice machine by using the data obtained in real time and also prevents the machine troubles by taking proper actions.

• Convergence Security Journal
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• v.17 no.5
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• pp.35-40
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• 2017

The control system can have such threats as information leakage and falsification through various routes due to communications network fusion with public network. As the issues about security and the infringe cases by new attack methods are diversified recently, with the security system that makes information data database by simply blocking and checking it is difficult to cope with new types of threats. It is also difficult to respond security threats by insiders who have security access authority with the existing security equipment. To respond the threats by insiders, it is necessary to collect and analyze Event Log occurring in the internal system realtime. Therefore, this study could find out whether there is correlation of the elements among Event Logs through correlation analysis based on Event Logs that occur real time in the control system, and based on the analysis result, the study is expected to contribute to studies in this field.

• The Journal of the Korea Contents Association
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• v.19 no.9
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• pp.637-645
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• 2019

The RFID group proof is an extension of the yoking proof proving that multiple tags are scanned by a reader simultaneously. Existing group proof schemes provide only delayed tag loss detection which detects loss of tag response in a verification phase. However, delayed tag loss detection is not suitable for real-time applications where tag loss must be detected immediately. In this study, I propose a tag response loss detection scheme which detects loss of tag response in the proof generation process quickly. In the proposed scheme, the tag responds with the sequence number assigned to the tag group, and the reader detects the loss of the tag response through the sequence number. Through an experiment for indistinguishability, I show that the sequence number is secure against an analyzing message attack to distinguish between specific tags and tag groups. In terms of efficiency, the proposed scheme requires fewer transmissions and database operations than existing techniques to determine which tags response is lost.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.6
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• pp.757-766
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• 2019

Objective: MicroRNAs are a class of endogenous small regulatory RNAs that regulate cell proliferation, differentiation and apoptosis. Recent studies on miRNAs are mainly focused on mice, human and pig. However, the studies on miRNAs in skeletal muscle of sheep are not comprehensive. Methods: RNA-seq technology was used to perform genomic analysis of miRNAs in prenatal and postnatal skeletal muscle of sheep. Targeted genes were predicted using miRanda software and miRNA-mRNA interactions were verified by quantitative real-time polymerase chain reaction. To further investigate the function of miRNAs, candidate targeted genes were enriched for analysis using gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment. Results: The results showed total of 1,086 known miRNAs and 40 new candidate miRNAs were detected in prenatal and postnatal skeletal muscle of sheep. In addition, 345 miRNAs (151 up-regulated, 94 down-regulated) were differentially expressed. Moreover, miRanda software was performed to predict targeted genes of miRNAs, resulting in a total of 2,833 predicted targets, especially miR-381 which targeted multiple muscle-related mRNAs. Furthermore, GO and KEGG pathway analysis confirmed that targeted genes of miRNAs were involved in development of skeletal muscles. Conclusion: This study supplements the miRNA database of sheep, which provides valuable information for further study of the biological function of miRNAs in sheep skeletal muscle.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.37-43
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• 2020

Recently, many researches have been actively to diagnose symptoms of heart disease using ECG signal, which is an electrical signal measuring heart status. In particular, the electrocardiogram signal can be used to monitor and diagnose arrhythmias that indicates an abnormal heart status. In this paper, we proposed 1-D convolutional neural network for arrhythmias classification systems. The proposed model consists of deep 11 layers which can learn to extract features and classify 5 types of arrhythmias. The simulation results over MIT-BIH arrhythmia database show that the learned neural network has more than 99% classification accuracy. It is analyzed that the more the number of convolutional kernels the network has, the more detailed characteristics of ECG signal resulted in better performance. Moreover, we implemented a practical application based on the proposed one to classify arrythmias in real-time.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.3
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• pp.289-296
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• 2021

The Korean construction industry has been implementing G-SEED, a certification system that evaluates the environmental properties of buildings for the purpose of reducing environmental burdens such as energy and resource consumption and pollutant emissions. Also, creating a pleasant environment in general is one more purpose of G-SEED certification system. However, G-SEED certification in practice is difficult and time consuming due to the complexity of the certification acquisition process coupled with little economic consideration for the materials of each certification item. Therefore, in this study, we present a model for the optimal selection of materials and economic assessment using a genetic algorithm. The development of the model involves building a material database based on life-cycle costing (LCC) targeted at "Application of Indoor Air Pollutant Low Emission Material" from G-SEED. Next, the model was validated using a real non-residential building case study. The result shows an average cost reduction rate of 74.5 % compared with the existing cost. This model is expected to be used as an economically efficient tool in G-SEED.

• Journal of Microbiology and Biotechnology
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• v.31 no.11
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• pp.1508-1518
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• 2021

Hsa_circ_0001947 is associated with multiple cancers, but its function in non-small cell lung cancer (NSCLC) is ambiguous and needs further research. The targeting relationship among circ_0001947, miR-661, and downstream of tyrosine kinase 7 (DOK7) was predicted by database and further verified by dual-luciferase reporter assay, while their expressions in cancer tissues and cells were detected by quantitative real-time polymerase chain reaction (qRT-PCR). After transfection, cell biological behaviors and expressions of miRNAs, miR-661 and DOK7 were determined by cell function experiments and qRT-PCR, respectively. Circ_0001947 was low-expressed in NSCLC tissues and cells. Circ_0001947 knockdown intensified cell viability and proliferation, induced cell cycle arrest at S phase, suppressed apoptosis and evidently enhanced miR-510, miR-587, miR-661 and miR-942 levels, while circ_0001947 overexpression did the opposite. MiR-661 was a target gene of circ_0001947 that participated in the regulation of circ_0001947 on cell biological behaviors. Furthermore, DOK7, the target gene of miR-661, partly participated in the regulation of miR-661 on cell viability. Hsa_circ_0001947 acts as a sponge of miR-661 to repress NSCLC development by elevating the expression of DOK7.