• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2594-2603
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• 1997

A novel method of adaptive beam forming is presented in this paper. The proposed technique provides for a suboptimal beam pattern that increases the Signal to Noise/Interference Ratio (SNR/SIR), thus, eventually increases the capacity of the communication channel, under an assumption that the desired signal is dominant compared to each component of interferences at the receiver, which is precoditionally achieved in Code Division Multiple Access (CDMA) mobile communications by the chip correlator. The main advantages of the new technique are:(1)The procedure requires neither reference signals nor training period, (2)The signal interchoerency does not affect the performance or complexity of the entire procedure, (3)The number of antennas does not have to be greater than that of the signals of distinct arrival angles, (4)The entire procedure is iterative such that a new suboptimal beam pattern be generated upon the arrival of each new data of which the arrival angle keeps changing due tot he mobility of the signal source, (5)The total amount of computation is tremendously reduced compared to that of most conventional beam forming techniques such that the suboptimal beam pattern be produced at vevery snapshot on a real-time basis. The total computational load for generating a new set of weitht including the update of an N-by-N(N is the number of antenna elements) autocovariance matrix is $0(3N^2 + 12N)$. It can further be reduced down to O(11N) by approximating the matrix with the instantaneous signal vector.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.49 no.1
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• pp.15-24
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• 2012

In this paper, we suggest the dynamic-response-free SMPS using a new high-resolution DPWM generator based on switched-capacitor delay technique. In the proposed system, duty ratio of DPWM is controlled by voltage slope of an internal capacitor using switched-capacitor delay technique. In the proposed circuit, it is possible to track output voltage by controlling current of the internal capacitor of the DPWM generator through comparison between the feedback voltage and the reference voltage. Therefore the proposed circuit is not restricted by the dynamic-response characteristic which is a problem in the existing SMPS using the closed-loop control method. In addition, it has great advantage that ringing phenomenon due to overshoot/undershoot does not appear on output voltage. The proposed circuit can operate at switching frequencies of 1MHz~10MHz using internal operating frequency of 100 MHz. The maximum current of the core circuit is 2.7 mA and the total current of the entire circuit including output buffer is 15 mA at the switching frequency of 10 MHz. The proposed circuit has DPWM duty ratio resolution of 0.125 %. It can accommodate load current up to 1 A. The maximum ripple of output voltage is 8 mV. To verify operation of the proposed circuit, we carried out simulation with Dongbu Hitek BCD $0.35{\mu}m$ technology parameter.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.143-152
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• 2014

This paper introduces Database security to prevent the rapidly increasing issue of private information leakage. The Database security examined in the paper separates into DB access control area and DB encryption area which further leads the paper to analyze the factors of the two areas and suggest necessary elements for creating stable Database security. In addition, the paper examines previous DB security programs by areas and analyzes pros and cons from the tested result. The experiment indicated that while DB access control presents less degradation and reduced the need to modify the existing DBMS since the access control operates at the end point of the network, DB encryption presented strength in protecting the data from unauthorized access. On the other hand, DB access control is less useful in preventing the attack in advance which leaves the log to enable tracking afterward while DB encryption can only be operated by limited types of Database and causes degradation due to system load and shows higher percentage of failure when creating the system. This paper examines characteristics of Database security areas in order to be used as a reference for institutions or companies seeking stable Database security.

• Science of Emotion and Sensibility
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• v.19 no.1
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• pp.39-48
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• 2016

This research aims to identify innovative companies' attention to the emotion and sensibility and its application by analyzing the contents of the corporate annual reports. Annual report is a good reference data because it describes not only various current products and services' annual activities and business performance but also corporate future direction. Sensibility is interpreted and used with various words internationally: various related terms such as sensibility, sense, emotion, feeling and affection are analyzed not only by the definition but also the interrelationship among them, and included for the contents analysis. To select the innovative companies, the researcher used 'Fast company' that is the economic journal and deducted the companies list via 'The world's 50 most innovative companies' in 2009 and 2014. Listed companies' 2009 and 2014 annual reports' contents were analyzed to identify the rate of the recognition and the application of sensibility to their business. Even though the quantitative result of the content analysis indicates not a strong relationship between corporate innovativeness and 'sensibility' qualitative result identifies companies are paying more attention to the 'sense' and 'feeling' during five years. In conclusion, the innovation that company pursues strategically is shifting from differentiation and the technological leadership to satisfying user experiences and the number of companies which express and measure user feeling and emotions are increasing.

• Journal of Navigation and Port Research
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• v.41 no.4
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• pp.189-194
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• 2017

The Moving Search Radar System (MSRS) monitors sea areas by moving along the coast. Since the radar is initially aligned to the front of the vehicle, it is important to know the changes in the heading azimuth of the vehicle to quickly acquire the target azimuth from the radar after the MSRS has moved. The heading azimuth can be obtained using the gyro compass, the GPS compass or the electronic compass. The electronic compass is suitable for MSRS requiring fast maneuverability due to its small volume, short stabilization time and low price. However, using a geomagnetic sensor may result in an error due to the surrounding magnetic field. Errors can make early automatic tracking of the satellites difficult and can reduce the radar detection accuracy. Therefore, this paper proposes a method to automatically compensate for the error reflecting the correction value on the radar obtained by comparing the reference azimuth calculated by solving the geodesic inverse problem using two coordinates between the radar and the geostationary satellite with the actually-directed azimuth angle of the satellite antenna. The feasibility and convenience of the proposed method were verified by applying it to the MSRS in the field.

• Korean Journal of Optics and Photonics
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• v.2 no.3
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• pp.139-148
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• 1991

A fiber-optic magnetic sensor system for the detection of small ac magnetic field(200Hz-2 kHz) was constructed. Magnetic field sensing part was fabricated by bonding a section of optical fiber to amorphous metallic glass(2605SC) having large magnetostriction effect. And with the directional coupler, all fiber type Mach-Zehnder interferometer was constructed to measure the variation of the external magnetic field by translating it into the optical phase shift in the interferometer. The signal fading problem of the interferometer, which is due to random phase drifts originated from the environment, i.e., temperature fluctuation, vibrations, etc., was elliminated by feedback phase compensation. This allows the sensitivity to be maintained at the maximum by keeping the interferometer in quadrature phase condition. The frequency response of metallic glass was found to be nearly flat in the range of 90 Hz-2 kHz and dc bias field for the maximum ac response was 3.5 Oe. The interferometer output showed good linearity over the range $\pm$0.5 Oe. For 1 kHz ac magnetic field the scale factor S and the minimum detectable magnetic field were measured to be 8.0 rad/Oe and $3X10^{-6} Oe/\sqrt{Hz}$at 1 Hz detection bandwidth respectively.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.273-282
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• 2022

MPEG-VCM(Video Coding for Machine) aims to standardize video codec for machines. VCM provides data sets and anchors, which provide reference data for comparison, for several machine vision tasks including object detection, object segmentation, and object tracking. The evaluation template can be used to compare compression and machine vision task performance between anchor data and various proposed video codecs. However, performance comparison is carried out separately for each machine vision task, and information related to performance evaluation of multiple machine vision tasks on a single bitstream is not provided currently. In this paper, we propose a performance evaluation method of a video codec for AI-based multi-tasks. Based on bits per pixel (BPP), which is the measure of a single bitstream size, and mean average precision(mAP), which is the accuracy measure of each task, we define three criteria for multi-task performance evaluation such as arithmetic average, weighted average, and harmonic average, and to calculate the multi-tasks performance results based on the mAP values. In addition, as the dynamic range of mAP may very different from task to task, performance results for multi-tasks are calculated and evaluated based on the normalized mAP in order to prevent a problem that would be happened because of the dynamic range.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.199-219
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• 2018

With the everyday use of the Internet and the spread of various smart devices, users have been able to communicate in real time and the existing communication style has changed. Due to the change of the information subject by the Internet, data became more massive and caused the very large information called big data. These Big Data are seen as a new opportunity to understand social issues. In particular, text mining explores patterns using unstructured text data to find meaningful information. Since text data exists in various places such as newspaper, book, and web, the amount of data is very diverse and large, so it is suitable for understanding social reality. In recent years, there has been an increasing number of attempts to analyze texts from web such as SNS and blogs where the public can communicate freely. It is recognized as a useful method to grasp public opinion immediately so it can be used for political, social and cultural issue research. Text mining has received much attention in order to investigate the public's reputation for candidates, and to predict the voting rate instead of the polling. This is because many people question the credibility of the survey. Also, People tend to refuse or reveal their real intention when they are asked to respond to the poll. This study collected comments from the largest Internet portal site in Korea and conducted research on the 19th Korean presidential election in 2017. We collected 226,447 comments from April 29, 2017 to May 7, 2017, which includes the prohibition period of public opinion polls just prior to the presidential election day. We analyzed frequencies, associative emotional words, topic emotions, and candidate voting rates. By frequency analysis, we identified the words that are the most important issues per day. Particularly, according to the result of the presidential debate, it was seen that the candidate who became an issue was located at the top of the frequency analysis. By the analysis of associative emotional words, we were able to identify issues most relevant to each candidate. The topic emotion analysis was used to identify each candidate's topic and to express the emotions of the public on the topics. Finally, we estimated the voting rate by combining the volume of comments and sentiment score. By doing above, we explored the issues for each candidate and predicted the voting rate. The analysis showed that news comments is an effective tool for tracking the issue of presidential candidates and for predicting the voting rate. Particularly, this study showed issues per day and quantitative index for sentiment. Also it predicted voting rate for each candidate and precisely matched the ranking of the top five candidates. Each candidate will be able to objectively grasp public opinion and reflect it to the election strategy. Candidates can use positive issues more actively on election strategies, and try to correct negative issues. Particularly, candidates should be aware that they can get severe damage to their reputation if they face a moral problem. Voters can objectively look at issues and public opinion about each candidate and make more informed decisions when voting. If they refer to the results of this study before voting, they will be able to see the opinions of the public from the Big Data, and vote for a candidate with a more objective perspective. If the candidates have a campaign with reference to Big Data Analysis, the public will be more active on the web, recognizing that their wants are being reflected. The way of expressing their political views can be done in various web places. This can contribute to the act of political participation by the people.

• 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 Environment and Ecology
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• v.33 no.1
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• pp.1-8
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• 2019

Pintail (Anas acuta) is the major wintering bird in South Korea and known as a major mediator of the highly pathogenic avian influenza (HPAI). Pintail migrates long distances between Russian Siberia and Korea. This species prefers a rice paddy area as their winter habitat. The purpose of this study is to provide the data necessary for the conservation and management of bird habitats in Korea by understanding the wintering home-range and habitat of pintail in Korea. We captured six pintails using a cannon-net in the winter of 2015 and attached the GPS-mobile phone based telemetry (WT-300) on them to study the wintering home-range and wintering habitat. We analyzed the tracking location data using ArcGIS 9.0 Animal Movement Extension and calculated Kernel Density Estimation (KDE) and Minimum Convex Polygon (MCP). The average home-range in the wintering ground analyzed by MCP was $677.3km^2$ (SD=130.2, n=6) while the maximum and minimum were $847.7km^2$ and $467.5km^2$, respectively. Extents of home-range analyzed by KDE were $194.7km^2$ (KDE 90%), $77.4km^2$ (KDE 70%), and $35.3km^2$ (KDE 50%). The pintails mostly used both sea and paddy field as habitat in the winter season and utilized paddy fields more during the nighttime and than the daytime. We concluded that the home-range and habitat of pintails in the winter could be used as the reference data for the preservation of species, management of habitats, and coping with a breakout of HPAI.