• The Journal of the Acoustical Society of Korea
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• v.25 no.6
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• pp.277-281
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• 2006

This paper presents a method for the automatic recognition of pitch accents over syllables. The method that we propose is based on the time-delay recursive neural network (TDRNN). which is a neural network classifier with two different representation of dynamic context: the delayed input nodes allow the representation of an explicit trajectory F0(t) along time. while the recursive nodes provide long-term context information that reflects the characteristics of pitch accentuation in spoken English. We apply the TDRNN to pitch accent recognition in two forms: in the normal TDRNN. all of the prosodic features (pitch. energy, duration) are used as an entire set in a single TDRNN. while in the distributed TDRNN. the network consists of several TDRNNs each taking a single prosodic feature as the input. The final output of the distributed TDRNN is weighted sum of the output of individual TDRNN. We used the Boston Radio News Corpus (BRNC) for the experiments on the speaker-independent pitch accent recognition. π 1e experimental results show that the distributed TDRNN exhibits an average recognition accuracy of 83.64% over both pitch events and non-events.

• The KIPS Transactions:PartA
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• v.13A no.1 s.98
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• pp.11-18
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• 2006

In the Internet of various networks, it is difficult to reduce real routing time by just minimizing their hop count. We propose an adaptive proximity route selection method in DHT-based peer-to-peer systems, in which nodes select the nぉe with smallest lookup latency among their routing table entries as a next routing node. Using Q-Routing algorithm and exponential recency-weighted average, each node estimates the total latency and establishes a lookup table. Moreover, without additional overhead, nodes exchange their lookup tables to update their routing tables. Several simulations measuring the lookup latencies and hop-to-hop latency show that our method outperforms the original Chord method as well as CFS' server selection method.

• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.389-398
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• 2010

The Vehicle Routing and Scheduling Problem with Time Windows(VRSPTW) is to establish a delivery route of minimum cost satisfying the time constraints and capacity demands of many customers. The VRSPTW takes a long time to generate a solution because this is a NP-hard problem. To generate the nearest optimal solution within a reasonable time, we propose the heuristic by using an ACO(Ant Colony Optimization) with multi-cost functions. The multi-cost functions can generate a feasible initial-route by applying various weight values, such as distance, demand, angle and time window, to the cost factors when each ant evaluates the cost to move to the next customer node. Our experimental results show that our heuristic can generate the nearest optimal solution more efficiently than Solomon I1 heuristic or Hybrid heuristic applied by the opportunity time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7A
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• pp.569-580
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• 2012

In this paper, an enhanced initial ranging algorithm for large-cell coverage fixed wireless communication system is proposed. In typical wireless communication system such as WiBro, because a round-trip delay between a transmitter and a receiver is within one OFDM (Orthogonal Frequency Division Multiplexing) symbol duration, a frequency-domain differential correlation method is generally used. However, the conventional method cannot be applied due to an increase of a maximum time delay in large-cell system. In case of an accumulative differential method, estimation errors can occur because of frequent sign transitions. In this paper, therefore, we propose an algorithm which can estimate a total timing offset in a ranging channel structure for 15 km cell. The proposed method can improve performance by sign comparison based sign error correction rule between the estimated values and using a weighting scheme based on channel correlation, the number of accumulations, and the noise reduction effect in normalization process. Also, it can estimate the integer timing offset of symbol duration by comparing peak-powers after compensating for the fractional timing offset of symbol duration.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.6
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• pp.503-511
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• 2013

This paper presents a speech enhancement method using non-negative matrix factorization. In training phase, we can obtain each basis matrix from speech and specific noise database. After training phase, the noisy signal is separated from the speech and noise estimate using basis matrix in enhancement phase. In order to improve the performance, we model the change of encoding matrix from training phase to enhancement phase using independent Gaussian distribution models, and then use the constraint of the objective function almost same as that of the above Gaussian models. Also, we perform a smoothing operation to the encoding matrix by taking into account previous value. Last, we apply the Log-Spectral Amplitude type algorithm as gain function.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1C
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• pp.67-77
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• 2007

Virus throttling technique, one of many early worm detection techniques, detects Internet worm propagation by limiting connect requests within a certain ratio. The typical virus throttling controls the period of rate limiter autonomically by utilizing weighted average delay queue length to reduce connection delay time without hanving a large effect on worm detection time. In the existing virus throttling research, a minimum period of variable rate limiter is fired and a turning point which is a point that the period of rate limiter has been being decreased and starts to be increased is also fixed. However, these two performance factors have different effects on worm detection time and connection delay. In this paper, we analyze the effect of minimum period and turning point of variable rate limiter, and then propose an algorithm which determines values of performance factors by referencing current traffic pattern. Through deep experiments, it is verified that the proposed technique is more efficient in respect of reducing worm detection time and connection delay than the existing virus throttling which fixed the performance factors.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.485-493
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• 2006

This study is to combine precipitation data with different spatial-temporal characteristics using an optimal weighting method. This optimal weighting method is designed for combination of AWS rain gage data and S-band RADAR-estimated rain data with weighting function in inverse proportion to own mean square error for the previous time step. To decide the optimal weight coefficient for optimized precipitation according to different training time, the method has been performed on Changma case with a long spell of rainy hour for the training time from 1 hour to 10 hours. Horizontal field of optimized precipitation tends to be smoothed after 2 hours training time, and then optimized precipitation has a good agreement with synoptic station rainfall assumed as true value. This result suggests that this optimal weighting method can be used for production of high-resolution quantitative precipitation rate using various data sets.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.93-100
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• 2022

In the era of information overload on the Internet, the recommendation system, which is an indispensable function, is a service that recommends products that a user may prefer, and has been successfully provided in various commercial sites. Recently, studies to reflect the rating time of items to improve the performance of collaborative filtering, a representative recommendation technique, are active. The core idea of these studies is to generate the recommendation list by giving an exponentially lower weight to the items rated in the past. However, this has a disadvantage in that a time function is uniformly applied to all items without considering changes in users' preferences according to the characteristics of the items. In this study, we propose a time-aware collaborative filtering technique from a completely different point of view by developing a new similarity measure that integrates the change in similarity values between items over time into a weighted sum. As a result of the experiment, the prediction performance and recommendation performance of the proposed method were significantly superior to the existing representative time aware methods and traditional methods.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.429-429
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• 2021

2019년 발생한 인천광역시 붉은 수돗물 사태로 급수구역에 포함된 26만 1천 세대, 63만 5천 명이 직·간접적인 피해를 입은 바 있다. 경제적 피해액으로 추정할 경우 최소 1,280억 원 이상으로 보고된 바 있으며, 이와 같은 상수관망의 수질사고 확산은 장기간 동안 시민의 건강과 생활환경 수준을 저하시킨다. 따라서 상수도시스템의 수질사고확산 모델링 및 방지기술을 통한 수질안전성의 재확인이 필요하며, 이것은 상수도시스템의 지속가능성을 높여 국민이 체감하는 물 환경 수준 제고에 기여가 가능하다. 관망 내 수질해석을 직접적으로 수행하는 모델은 국외적으로 다양하게 개발(PODDS, EPANET-MSX, EPANET2.2 등)된 바 있으나 검·보정을 위한 수질측정 자료 부족 등으로 적용이 제한적이라는 한계가 현재에도 존재한다. 이를 보완하기 위해 수질자료에 비해 그 양이 많고 획득방법이 상대적으로 수월한 수리학적 계측자료 및 해석결과를 활용한 관로 내 체류시간 등을 활용한 연구가 수행된 바 있다. 그러나 이와 같은 수리학적 해석 결과를 활용하는 경우에도 계측자료를 기반으로 한 수리학적 검·보정은 필수적이라 할 수 있다. 본 연구에서는 관로 내 체류시간에 직접적인 영향을 미치는 유량 및 유속자료를 중심으로 수리학적 관망해석의 결과를 최적 검·보정하는 방법론을 제안하였다. 기존 상수관망 수리해석의 검·보정은 일부 지점에서 수압을 측정하고, 수리해석 결과로 도출되는 해당 지점의 수압이 실측된 결과와 유사하도록 관로의 유속계수를 적절히 보정하는 형태로 진행되었다. 그러나 본 연구에서는 관로유량과 유속자료의 목적함수 내 가중치를 수압자료보다 크게 설정하여 체류시간 중심의 검·보정이 수행될 수 있도록 하였으며, 검·보정 대상인자 역시 대수용가의 수요량, 수요패턴, 그리고 관로유속계수로 확장된 모형을 구축하였다. 최적화 기법으로는 메타휴리스틱 기법중 하나인 화음탐색법을 활용하였다. EPANET 2.2 Toolkit과 Visual Basic .Net을 연계하여 프로그래밍하였으며, 개발된 모형을 실제 지방상수도 시스템에 적용하여 분석하였다.

• Journal of KIISE:Software and Applications
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• v.30 no.9
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• pp.876-884
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• 2003

It is essential to identify both the pupil and iris boundaries for iris recognition. The circular edge detector proposed by Daugman is the most common and powerful method for the iris region extraction. The method is accurate but requires lots of computational time since it is based on the exhaustive search. Some heuristic methods have been proposed to reduce the computational time, but they are not as accurate as that of Daugman. In this paper, we propose a pupil and iris boundary finding algorithm which is faster than and as accurate as that of Daugman. The proposed algorithm searches the boundaries using the Daugman's circular edge detector, but reduces the search region using the problem domain knowledge. In order to find the pupil boundary, the search region is restricted in the maximum and minimum bounding circles in which the pupil resides. The bounding circles are obtained from the binarized pupil image. Two iris boundary points are obtained from the horizontal line passing through the center of the pupil region obtained above. These initial boundary points, together with the pupil point comprise two bounding circles. The iris boundary is searched in this bounding circles. Experiments show that the proposed algorithm is faster than that of Daugman and more accurate than the conventional heuristic methods.