• 한국소음진동공학회논문집
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• 제17권9호
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• pp.853-861
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• 2007

Currently, automotive industries improve the vehicle performance and reduce the development period of vehicle using each module part for the high quality and performance of vehicles. However each component part doesn't generate the noise and vibration problems, sometime these problems are generated on the assembly status between vehicle chassis frame and each module part. On this study, in order to analysis the dynamic characteristics of a shield door module that is a typical module part of vehicles, the acquisition and evaluation process about the vibration and noise of shield door module is developed. Also the possibility to apply to shield door module of the developed process is verified by the comparison with the dynamic characteristics between plastic and steel module plate.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.1276-1279
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• 2006

This article on environmental noise qualify is concerned with the relationships between the annoyance and perception and sound quality metrics according to exposition time for traffic noise. For invested the characteristics of noise quality, we conducted to the subjective experiments of the annoyance response using the absolute 100 scaling method for the traffic noise sources. The traffic noise sources are composed to varieties exposition time from 15sec to 1200sec. As the results, the first there are decreased the perception loud level for the increase of exposition time with logarithm scale, but increased the annoyance. Second, evaluation index of annoyance is correlated to the loudness(sones), tonality and logarithm scale time with R2=0.83. Also, the composition ratio of traffic noise according to exposition time has the change of range as the logarithm scale ($30{\sim}50%$), tonality($27{\sim}37%$) and loudness($34{\sim}20%$).

• 대한전자공학회논문지SP
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• 제47권5호
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• pp.109-116
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• 2010

본 논문에서는 하모닉 구조를 이용하여 다성 음악의 주요 멜로디를 검출하는 방법을 제안한다. 다성 음악은 다수의 음원을 동시에 포함하므로 주요 멜로디를 검출하기 위하여 다중 기본 주파수를 추출하고 각 기본 주파수의 성질을 기반으로 주요 멜로디를 구하는 과정으로 구성된다. 하모닉 구조는 기본 주파수의 배음관계를 나타내고 단일 음원 신호의 중요한 특성 파라미터이다. 따라서 제안하는 방법은 하모닉 구조의 정확도를 기준으로 다성 음악에 존재하는 모든 기본 주파수 후보를 추출하고, 추출된 기본 주파수 후보에 대하여 하모닉 성분을 조합하여 하모닉 평균 에너지를 구하여 기본 주파수 후보의 중요도 순위를 결정한다. 마지막으로 기본 주파수 후보의 순위와 기본 주파수의 연속성을 기반으로 피치 트래킹을 진행하여 최종 주요 멜로디에 해당하는 기본 주파수를 검출한다. 제안한 방법의 성능을 ADC 2004 DB와 가요 100곡에 대하여 MIREX 2005 측정 방법에 따라 측정하였으며, ADC 2004 DB에 대하여 90.42%의 검출 정확도를 가진다.

• Smart Structures and Systems
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• 제29권1호
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

• Journal of Forest and Environmental Science
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• 제30권4호
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• pp.383-392
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• 2014

In this study, we investigated the Fukiage sand dunes of southern Kyushu, Japan. We surveyed the status of recovery of coastal Japanese black pine forests damaged by pine wilt disease and their disaster prevention capability. We placed two transects: Transect 1, in an area that was severely damaged (80-90% damage rate) by pine wilt disease, and Transect 2, in an area that was mostly undamaged (<10% damage rate). Then, we installed survey lines, carried out vegetation surveys, and measured the depth and pH of humus soil. The survey lines were placed perpendicular to the coastline from the top of the fore-dune to the inland area, and divided into five 50 m sections. Before the point 100 m inland from the top of the fore-dune, the number of invasive hardwoods and of Japanese black pines were small because of the poor growth environment in both transects. Past the 100 m point, the species and number of Japanese black pines and broad-leaved trees increased further inland because the growth environment improved. In addition, the recovery metrics of tree height, diameter at breast height, age, and number in Transect 1 were much lower than those in Transect 2, and the basal area of broad-leaved trees and the depth of humus soil in Transect 1 were lower than in Transect 2, and the soil pH of humus soil in Transect 1 was higher than that of Transect 2. The shape ratio of the Japanese black pine forests indicated that they were insufficient for disaster prevention. Therefore, in order to fully promote the disaster prevention capability of coastal Japanese black pine forests, we should not only focus on prevention of pine wilt disease but also undertake continuous control efforts taking into consideration the sound growth environment such as appropriate density and soil management and removal of invasive broad-leaved trees.

• Asia pacific journal of information systems
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• 제17권4호
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• pp.207-228
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• 2007

Measuring Information Technology(IT) organizations' activities have been limited to mainly measure financial indicators for a long time. However, according to the multifarious functions of Information System, a number of researches have been done for the new trends on measurement methodologies that come with financial measurement as well as new measurement methods. Especially, the researches on IT Balanced Scorecard(BSC), concept from BSC measuring IT activities have been done as well in recent years. BSC provides more advantages than only integration of non-financial measures in a performance measurement system. The core of BSC rests on the cause-and-effect relationships between measures to allow prediction of value chain performance measures to allow prediction of value chain performance measures, communication, and realization of the corporate strategy and incentive controlled actions. More recently, BSC proponents have focused on the need to tie measures together into a causal chain of performance, and to test the validity of these hypothesized effects to guide the development of strategy. Kaplan and Norton[2001] argue that one of the primary benefits of the balanced scorecard is its use in gauging the success of strategy. Norreklit[2000] insist that the cause-and-effect chain is central to the balanced scorecard. The cause-and-effect chain is also central to the IT BSC. However, prior researches on relationship between information system and enterprise strategies as well as connection between various IT performance measurement indicators are not so much studied. Ittner et al.[2003] report that 77% of all surveyed companies with an implemented BSC place no or only little interest on soundly modeled cause-and-effect relationships despite of the importance of cause-and-effect chains as an integral part of BSC. This shortcoming can be explained with one theoretical and one practical reason[Blumenberg and Hinz, 2006]. From a theoretical point of view, causalities within the BSC method and their application are only vaguely described by Kaplan and Norton. From a practical consideration, modeling corporate causalities is a complex task due to tedious data acquisition and following reliability maintenance. However, cause-and effect relationships are an essential part of BSCs because they differentiate performance measurement systems like BSCs from simple key performance indicator(KPI) lists. KPI lists present an ad-hoc collection of measures to managers but do not allow for a comprehensive view on corporate performance. Instead, performance measurement system like BSCs tries to model the relationships of the underlying value chain in cause-and-effect relationships. Therefore, to overcome the deficiencies of causal modeling in IT BSC, sound and robust causal modeling approaches are required in theory as well as in practice for offering a solution. The propose of this study is to suggest critical success factors(CSFs) and KPIs for measuring performance for IT organizations and empirically validate the casual relationships between those CSFs. For this purpose, we define four perspectives of BSC for IT organizations according to Van Grembergen's study[2000] as follows. The Future Orientation perspective represents the human and technology resources needed by IT to deliver its services. The Operational Excellence perspective represents the IT processes employed to develop and deliver the applications. The User Orientation perspective represents the user evaluation of IT. The Business Contribution perspective captures the business value of the IT investments. Each of these perspectives has to be translated into corresponding metrics and measures that assess the current situations. This study suggests 12 CSFs for IT BSC based on the previous IT BSC's studies and COBIT 4.1. These CSFs consist of 51 KPIs. We defines the cause-and-effect relationships among BSC CSFs for IT Organizations as follows. The Future Orientation perspective will have positive effects on the Operational Excellence perspective. Then the Operational Excellence perspective will have positive effects on the User Orientation perspective. Finally, the User Orientation perspective will have positive effects on the Business Contribution perspective. This research tests the validity of these hypothesized casual effects and the sub-hypothesized causal relationships. For the purpose, we used the Partial Least Squares approach to Structural Equation Modeling(or PLS Path Modeling) for analyzing multiple IT BSC CSFs. The PLS path modeling has special abilities that make it more appropriate than other techniques, such as multiple regression and LISREL, when analyzing small sample sizes. Recently the use of PLS path modeling has been gaining interests and use among IS researchers in recent years because of its ability to model latent constructs under conditions of nonormality and with small to medium sample sizes(Chin et al., 2003). The empirical results of our study using PLS path modeling show that the casual effects in IT BSC significantly exist partially in our hypotheses.

• 지능정보연구
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• 제24권4호
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• pp.197-217
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• 2018

음악은 인간의 감성을 소리로 표현하는 창조적 예술 행위이다. 음악은 사람들의 기분을 우울하게 혹은 기쁘게 변화시킬 수 있다. 따라서 음악을 감상하는 데 있어 감성은 소비자에게 적합한 음악을 찾고 들려주는 데 매우 중요한 요소인데, 다양한 음원 서비스에서 제공하는 추천 알고리즘은 사용자의 기본적인 정보(성별, 나이, 감상 횟수 등)와 사용자의 플레이 기록에 기반한 음악 추천 방식을 주로 사용하고 있다. 본 연구에서는 음악을 감상하는 개인의 감성을 고려하여 각 음원이 가지는 고유의 감성을 기본으로 한 음악 추천 알고리즘을 제안해 보고자 한다. 구체적으로, 사용자들이 자주 듣는 음악과 그렇지 않은 음악을 기준으로 '감정 패턴'을 추출 후 상관관계를 확인하고자 하며, 앞선 결과를 기반으로 사용자들이 원하는 노래에 대한 검색과 사용자 감성 기반 추천 방법을 도출해내보고자 한다. 이를 위해 본 연구에서는 사례기반추론 기법을 이용하여 사람들이 주로 듣는 음악과 비슷한 '감성 패턴'을 갖는 특정한 곡을 추천해주는 알고리즘을 개발하였다. 먼저, 분석에 필요한 감정 형용사를 정리하여 변수화 시키고, 의미 있는 것끼리 묶어 음악 감성지수를 개발하였고, 분석의 대상이 될 음원에 대해 고유의 감성지수 점수를 측정하였다. 마지막으로 도출된 점수의 결과를 통해 유사한 감정 패턴이 나오는 곡들을 유사 곡 리스트로 분류하고 사용자들에게 추천하는 과정을 거친다. 앞선 일련의 과정을 거처 도출된 결과는 음원 추천 시스템뿐만 아니라, 인기 있는 곡과 아닌 곡에 영향을 미치는 변수 도출 및 음원 출시 전, 해당 곡의 스트리밍 수 예측 모형 구축 등 다양한 용도로 사용될 수 있을 것으로 기대한다.