• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.12
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• pp.165-170
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• 2005

In this paper, influences of a ultra wideband (UWB) antenna on impulse channel measurement are investigated in time domain (TD) and frequency domain (FD) as well. Firstly, impulse response of an UWB antenna is obtained and then using the result of impulse response of the UWB antenna, influences of the antenna on impulse radio channel is analyzed. Furthermore, using the impulse response of the UWB anenna, method of impulse radio channel analysis is presented by excluding the effect of the antenna from an impulse radio channel. For verifying the theory, a modified conical monopole antenna is designed for measuring impulse radio channel and its impulse response is obtained. After that, in order to investigate the effects of the UWB antenna on an impulse radio channel, multipath environments are set up in an anechonic chamber and transmission coefficient for each multipath environment is measured with an aid of vector network analyzer. Data measured in frequency domain is transformed into those in time domain by way of signal processing. Measurement shows that such properties of the antenna as dispersion and ringing affect impulse radio channel. Moreover, using the impulse response of the antenna, impulse response of only multipath channel is obtained.

• Korean Journal of Agricultural Science
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• v.32 no.1
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• pp.81-94
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• 2005

This study is aimed at giving the basic information for individual farm households to make decisions for optimizing their farm sizes and for the government to implement farm size optimization policies through the identification of combinations among rice production factors in plain areas like Cheolwon district and the suggestion of the optimal farm sizes of individual farmers based on the scale of economy calculated. The data of agricultural production costs of 50 rice farmers in the plain area which is located in Dongsong-eup Cholwon district, Kangwon province were used in the analysis. The 'translog' cost function among various methods which is a flexible function type was adopted to calculate the scale of economy in rice production. Seemingly unrelated regression(SUR) method was used in forecasting functions and processing other statistics by SHAZAM which is one of the computer aid program for quantitative econometric analysis. In conclusion, the long-run average cost(LAC) curve showed 'U-shape' which was different from 'L-type' one which was shown in the previous studies by others. The lowest point of the LAC was 9.764ha and the concerned production cost amounted to 633 Won/kg. Based on these results, it have to be suggested that around 10 ha of paddy is the target size for policy assistances to save costs under the present level of farming practices and technology. The above results show that the rice production costs could be saved up to 10ha in Cheolwon plain area which is a typical paddy field. However, land use, land condition, land ownership and manager's ability which may affect scale of economy should be considered. Furthermore, reasonable management will have to be realized by means of labor saving technology and cost saving management skill like enlargement of farm size of rice.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1772-1781
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• 2017

In this study, the design methodology for alleviating the overfitting problem of Polynomial Neural Networks(PNN) is realized with the aid of two kinds techniques such as L2 regularization and Sum of Squared Coefficients (SSC). The PNN is widely used as a kind of mathematical modeling methods such as the identification of linear system by input/output data and the regression analysis modeling method for prediction problem. PNN is an algorithm that obtains preferred network structure by generating consecutive layers as well as nodes by using a multivariate polynomial subexpression. It has much fewer nodes and more flexible adaptability than existing neural network algorithms. However, such algorithms lead to overfitting problems due to noise sensitivity as well as excessive trainning while generation of successive network layers. To alleviate such overfitting problem and also effectively design its ensuing deep network structure, two techniques are introduced. That is we use the two techniques of both SSC(Sum of Squared Coefficients) and $L_2$ regularization for consecutive generation of each layer's nodes as well as each layer in order to construct the deep PNN structure. The technique of $L_2$ regularization is used for the minimum coefficient estimation by adding penalty term to cost function. $L_2$ regularization is a kind of representative methods of reducing the influence of noise by flattening the solution space and also lessening coefficient size. The technique for the SSC is implemented for the minimization of Sum of Squared Coefficients of polynomial instead of using the square of errors. In the sequel, the overfitting problem of the deep PNN structure is stabilized by the proposed method. This study leads to the possibility of deep network structure design as well as big data processing and also the superiority of the network performance through experiments is shown.

• The KIPS Transactions:PartD
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• v.16D no.2
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• pp.249-256
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• 2009

This paper introduces an efficient USN (ubiquitous sensor network) for monitoring blind areas in a skiing resort, developed as a part of u-Sport showcase project of Gangwon Province. Blind areas of a skiing resort are dangerous and/or steep areas located aroud ski slopes, which are rarely traveled and not easily seen by a ski patrol. If an accident occurs in such a blind area, the main control center of the sking resort can hardly recognize the accident and provide first aid and rescue services promptly. The blind area monitoring system proposed in this paper monitors a blind area of a skiing resort using five battery-powered sensor nodes each of which has an image sensor on it and wirelessly transmits images around the blind area to the main control center on a regular basis, therebly allowing real-time monitoring of the blind area and prompt rescue services in case of accidents. Additionally, the monitoring system provides an emergency button which skiers injured in the blind area can push. If the button is pushed, an image around the button and an alarm signal are transmitted to the main control center and therefore the main control center can take prompt actions for rescuing the injured skiers.

• Journal of the Korea Computer Industry Society
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• v.2 no.7
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• pp.975-982
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• 2001

In this study, a solid-state laser system adopting a new real time multi-discharge (RTMD) method in which three flashlamps are turned on consecutively was designed and fabricated to examine the pulse width and the pulse shape of the laser beams depending upon the changes in the lamp rum-on time. That is, this study shows a technology that makes it possible to make various pulse shapes by turning on three flashlamps consecutively on a real-time basis with the aid of a PIC one-chip microprocessor. With this technique, the lamp turn-on delay time can be varied more diversely from 0 to 10 ms and the real-time control is possible with an external keyboard, enabling various pulse shapes. In addition, longer pulses can be more widely used for industrial processing and lots of medical purposes

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.3
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• pp.116-127
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• 2009

One of the criteria provided by the law to spatially determine the zones to levy the so-called development impact fee requires that the increase rate of the development permit should exceed that of the entire locality by more than 20 percent. Since the permits are issued to scattered parcels, however, it renders significant difficulties in accurately figuring out the finite local areas that exceed such legal criteria. This study, in this context, tries to join the development permit time-series data with the Korea Land Information System (KLIS) so that, with the aid of the landform layer and existing infrastructure layer, it could pinpoint the local area where the development activities are concentrating. Taking a sector in Yangpyong County as the case, the study demonstrates the methods to designate the zone by processing the permit information data.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.19-29
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• 2021

High-performing athletes possess the ability to read the game, known as the "sports brain". However, a cognitive battery to measure such sports brain has not been developed yet. The purpose of the study, thus, is to develop a computerized cognitive test battery to measure athletes' cognitive function. Based on a systematic review, information processing speed, execution function, and spatial ability were selected as sports-related cognitive functions. Simple and choice response times test, trail-making test, Flanker test, and mental rotation task were developed. After providing manual and practice trials, main tests were executed and all primary variables were statistically processed and automatically saved. The test battery is expected to aid in the discovery and recruitment of athletes in the future after verifying the validity and reliability of this battery.

• Korean Journal of Poultry Science
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• v.46 no.1
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• pp.47-53
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• 2019

The aim of this study was to investigate the difficulties that Korean farmers and processors currently experience with respect to the market for Korean native chicken (KNC). This study also provides suggestions by which they can overcome these difficulties. In all, sixty-nine farmers and sixty-two processors participated in our investigation, which addressed 1) the current difficulties that KNC farmers face, 2) the current importance-satisfaction measures among KNC farmers and processors, and 3) the future direction of the KNC market: farmer and processor opinions. The respondents stated that the limited number of sales stores was the most difficult market condition they faced in raising KNC, followed by feed cost, animal disease, and poor production environment. Regarding issues of importance and satisfaction, origin in raising step and slaughtering in the processing and distribution step were considered the areas most in urgent need of improvement, given farmers' and processors' high levels of dissatisfaction with these. Both the free-range farming system and the concept of animal welfare are growing in importance, given consumers' interests in these areas. As to opinions on the direction of KNC development, menu development was cited as most important, followed by public advertisement, accessibilities, business aid, and breed development. Consequently, the results show that well-organized support from both the government and related industries is needed, as chicken farmers and processors cannot resolve certain limitations inherent in the KNC industry on their own.

• KIPS Transactions on Computer and Communication Systems
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• v.13 no.1
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• pp.31-37
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• 2024

Conventional secret sharing techniques often derive shares from randomly generated polynomials or planes, resulting in lengthy and complex shares that are challenging to memorize and/or manage without the aid of a separate computer or specialized device. Modifying existing secret sharing methods to use a predetermined value, such as a memorizable password or bio-metric information, offers a solution. However, this approach raises concerns about security, especially when the predetermined value lacks randomness or has low entropy. In such cases, adversaries may deduce a secret S with just (t - 1) shares by guessing the predetermined value or employing brute force attacks. In this paper, we introduce a share hardening method designed to ensure the security of secret sharing while enabling the use of memorizable passwords or biometric information as predetermined shares.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.119-126
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• 2024

In building information model (BIM), it is difficult to train an artificial intelligence (AI) model due to the lack of sufficient data about individual projects in an architecture firm. In this paper, we present a methodology to correctly train an AI neural network model based on a large language model (LLM) to predict the steel structure product weight ratios in BIM. The proposed method, with the aid of the LLM, can overcome the inherent problem of limited data availability in BIM and handle a combination of natural language and numerical data. The experimental results showed that the proposed method demonstrated significantly higher accuracy than methods based on a smaller language model. The potential for effectively applying large language models in BIM is confirmed, leading to expectations of preventing building accidents and efficiently managing construction costs.