• Journal of Digital Convergence
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• v.17 no.9
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• pp.471-477
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• 2019

The purpose of this study is to analyse the attacking pattern of the key player through plenty of passes on field hockey between the winning games and losing ones through the preliminary game and the tournament. It has shown that the Korean women national team on field hockey is analysed all the passes through the sportscode for the 6 games of the World-League Final, and is investigated the centrality through the social network analysis using the R analytic software. The result is followed : First, It has shown three tendencies on the preliminary games that it has shown a lower Degree-Centrality, a same with Closeness, and a higher Betweenness than the tournament. Second, It has also described on winning games that it has explained a lower Degree-Centrality, a same with Closeness, and a higher Betweenness than losing games. On the conclusion, it has revealed that Korean women national team on field hockey showed a tendency that prefer to use a counter-attacking. Based on these study, expect to be used as a way to analyze performance in the field.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.21-31
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• 2021

As the COVID-19 pandemic rapidly changes healthcare around the globe, the need for smart healthcare that allows for remote diagnosis is increasing. The current classification of respiratory diseases cost high and requires a face-to-face visit with a skilled medical professional, thus the pandemic significantly hinders monitoring and early diagnosis. Therefore, the ability to accurately classify and diagnose respiratory sound using deep learning-based AI models is essential to modern medicine as a remote alternative to the current stethoscope. In this study, we propose a deep learning-based respiratory sound classification model using data collected from medical experts. The sound data were preprocessed with BandPassFilter, and the relevant respiratory audio features were extracted with Log-Mel Spectrogram and Mel Frequency Cepstral Coefficient (MFCC). Subsequently, a Parallel CNN network model was trained on these two inputs using stacking ensemble techniques combined with various machine learning classifiers to efficiently classify and detect abnormal respiratory sounds with high accuracy. The model proposed in this paper classified abnormal respiratory sounds with an accuracy of 96.9%, which is approximately 6.1% higher than the classification accuracy of baseline model.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.38-43
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• 2017

Sensor Networks (WSNs) can be defined as a self-configured and infrastructure-less wireless networks to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants and to cooperatively pass their data through the network to a main location or base-station where the data can be observed and analyzed. Typically a wireless sensor network contains hundreds of thousands of sensor nodes. The sensor nodes can communicate among themselves using radio signals. A wireless sensor node is equipped with sensing and computing devices, radio transceivers and power components. The individual nodes in a wireless sensor network (WSN) are inherently resource constrained: they have limited processing speed, storage capacity, communication bandwidth and limited-battery power. At present time, most of the research on WSNs has concentrated on the design of energy- and computationally efficient algorithms and protocols In order to extend the network life-time, in this paper we are looking into a routing protocol, especially LEACH and LEACH-related protocol. LEACH protocol is a representative routing protocol and improves overall network energy efficiency by allowing all nodes to be selected to the cluster head evenly once in a periodic manner. In LEACH, in case of movement of sensor nodes, there is a problem that the data transmission success rate decreases. In order to overcome LEACH's nodes movements, LEACH-Mobile protocol had proposed. But energy consumption increased because it consumes more energy to recognize which nodes moves and re-transfer data. In this paper we propose the new routing protocol considering nodes' mobility. In order to simulate the proposed protocol, we make a scenario, nodes' movements randomly and compared with the LEACH-Mobile protocol.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12C
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• pp.174-180
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• 2001

The technology to efficiently manage computer communication network is in need as the computer communication network becomes more complicated and users want services more diversified. This has brought industries, research institutes and standadization organizations to consider an effective network management protocol. CMIP and the SNMP have considerable differences in structure and capacity Therefore, it is essential to have enables differences between network management protocol to gear for the two communication management system which is the most widely used and will be continuously used. In this thesis we suggest an interworking function Integrated Network Management for the Design of Proxy. According to the suggest algorithm, by using scoping, it stores the management information, so that it may pass the related information at the inner cash efficiently. Therefore, we can not only reduce some unnecessary management operation considerably but also bring some efficiency of saving the total management system response time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1224-1248
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• 2022

In various sensor network applications, such as climate observation organizations, sensor nodes need to collect information from time to time and pass it on to the recipient of information through multiple bounces. According to field tests, this information corresponds to most of the energy use of the sensor hub. Decreasing the measurement of information transmission in sensor networks becomes an important issue.Compression sensing (CS) can reduce the amount of information delivered to the network and reduce traffic load. However, the total number of classification of information delivered using pure CS is still enormous. The hybrid technique for utilizing CS was proposed to diminish the quantity of transmissions in sensor networks.Further the energy productivity is a test task for the sensor nodes. However, in previous studies, a clustering approach using hybrid CS for a sensor network and an explanatory model was used to investigate the relationship between beam size and number of transmissions of hybrid CS technology. It uses efficient data integration techniques for large networks, but leads to clone attacks or attacks. Here, a new algorithm called SBEA (Snowball Endurance Algorithm) was proposed and tested with a bow. Thus, you can extend the battery life of your WSN by running effective copy detection. Often, multiple nodes, called observers, are selected to verify the reliability of the nodes within the network. Personal data from the source centre (e.g. personality and geographical data) is provided to the observer at the optional witness stage. The trust and reputation system is used to find the reliability of data aggregation across the cluster head and cluster nodes. It is also possible to obtain a mechanism to perform sleep and standby procedures to improve the life of the sensor node. The sniffers have been implemented to monitor the energy of the sensor nodes periodically in the sink. The proposed algorithm SBEA (Snowball Endurance Algorithm) is a combination of ERCD protocol and a combined mobility and routing algorithm that can identify the cluster head and adjacent cluster head nodes.This algorithm is used to yield the network life time and the performance of the sensor nodes can be increased.

• Journal of Broadcast Engineering
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• v.22 no.2
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• pp.162-172
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• 2017

In this paper, we propose facial expression recognition using CNN (Convolutional Neural Network), one of the deep learning technologies. To overcome the disadvantages of existing facial expression databases, various databases are used. In the proposed technique, we construct six facial expression data sets such as 'expressionless', 'happiness', 'sadness', 'angry', 'surprise', and 'disgust'. Pre-processing and data augmentation techniques are also applied to improve efficient learning and classification performance. In the existing CNN structure, the optimal CNN structure that best expresses the features of six facial expressions is found by adjusting the number of feature maps of the convolutional layer and the number of fully-connected layer nodes. Experimental results show that the proposed scheme achieves the highest classification performance of 96.88% while it takes the least time to pass through the CNN structure compared to other models.

• The Journal of the Acoustical Society of Korea
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• v.38 no.1
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• pp.23-29
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• 2019

In this paper, a deep learning-based detection and classification using multi-band frequency signals is presented for detecting earthquakes prevalent in Korea. Based on an analysis of the previous earthquakes in Korea, it is observed that multi-band signals are appropriate for classifying earthquake signals. Therefore, in this paper, we propose a deep CNN (Convolutional Neural Network) using multi-band signals as training data. The proposed algorithm extracts the multi-band signals (Low/Medium/High frequency) by applying band pass filters to mel-spectrum of earthquake signals. Then, we construct three CNN architecture pipelines for extracting features and classifying the earthquake signals by a late fusion of the three CNNs. We validate effectiveness of the proposed method by performing various experiments for classifying the domestic earthquake signals detected in 2018.

• The Journal of the Acoustical Society of Korea
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• v.28 no.6
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• pp.491-498
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• 2009

This paper presents the design method of an impedance matching network using an isolation transformer and the Chebyshev filter function for the high efficiency and the flat power driving of an underwater acoustic piezoelectric transducer. The proposed impedance matching network is designed for minimizing the reactance component of transducer and having the flat power response in the wide frequency range. We design a low pass filter with ladder-type circuit using the Chebyshev function as standard prototype filter function. In addition, we design the impedance matching network which is suitable for the equivalent circuit of transducer and the turn ratio of transformer through the bandpass frequency transformation. The proposed method is applied to the simulated dummy load of the tonpilz-type transducer operating in the middle frequency range. The simulation results are compared with the measured characteristics and the validity of the proposed method is verified.

• Journal of the Korea society of information convergence
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• v.5 no.2
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• pp.67-76
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• 2012

XML-based open protocol, XMPP users to pass messages to other users, which means that a decentralized communication network is the network infrastructure and enable it. In addition, XMPP servers using a professional server-to-server protocol to communicate with each other and decentralized social networks and collaboration framework provides an important possibility. In this paper, the features of XMPP messaging protocol is applicable to automotive telematics terminals XMPP-based platform design, and presence of two-way communication point for the problem, point-to-point session setup issues, security issues, compatibility issues, and to solve the scalability problem XMPP-based messaging system was implemented.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.77-82
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• 2013

The filtering characteristics of planar distributed feedback (DFB) waveguides composed by gratings with different period are solved using equivalent transmission-line network. To analyze explicitly its band-pass and resonance properties, a longitudinal modal transmission-line theory (L-MTLT) based on Floquet's theorem and Babinet's principle is newly developed. The numerical results reveal that this approach offers a simple and analytic algorithm to analyze the filtering characteristics of cascaded DFB structure with different period, and the bandwidth and side-lobe suppression of cascaded DFB filter are sensitively dependent on the variation of aspect ratio and the number of grating at each region.