본 논문의 주된 연구목적은 무작위합역 절차의 다양성을 검토하고 서로 다른 무작위합역 절차의 특성을 비교 분석함으로써 상대적으로 적절성이 높은 무작위합역 절차를 선정하여 제시하는 것이다. 기본적인 무작위합역 절차가 정식화되고, 효율적인 실행 알고리즘으로서 공간근접성행렬에 기반한 방법이 소개된다. 무작위합역 절차의 다양성을 제공해주는 두 가지 차원을 바탕으로 모두 여섯 가지의 서로 다른 무작위합역 유형이 도출되었다. 이 유형의 서로 다른 특성을 파악하기 위해 시뮬레이션 실험이 이루어졌 고, 그 결과가 연접도와 원형도의 두 가지 규준에 의거해 평가되었다. 시뮬레이션 실험의 주요 결과를 요약하면 다음과 같다. 첫째, 방식 B가 방식 A와 방식 C에 비해 연접도 측면에서 상대적으로 일관성 있는 결과를 산출해 준다. 둘째, 방식 2가 방식 1에 비해 최종구역의 형태를 보다 원형에 가까워지도록 만들어준다. 셋째, 방식 B, C(특히 B)가 원형도 측면에서 상대적으로 일관성 있는 결과를 산출해 준다. 시뮬레이션 연구 결과, B2 유형이 가장 적절한 무작위합역 절차인 것으로 드러났다. B2 유형은 상대적으로 원형도가 높은 최종구역을 산출할 뿐만 아니라, 연접도와 원형도 두 가지 측면 모두에서 상대적으로 일관성 있는 결과를 산출하는 것으로 평가되었다. 본 연구는 무작위합역 절차가 고정불변의 것이 아니라 다양하게 정의될 수 있으며, 그 다양성 속에서도 무작위성과 현실유관성의 관점에서 상대적으로 더 적절한 선택이 가능할 수 있다는 점을 실험 연구를 통해 보여주었다는 점에서 그 학문적인 의의가 있다고 평가할 수 있다.

Acoustic surveys were conducted in the seas surround the South Korea (South Sea A, South Sea B (waters around the Jeju Island), West Sea and East Sea) in spring and autumn in 2016. First, the vertical and horizontal distributions of fisheries resources animals were examined. In most cases vertical acoustic biomass was high in surface water and mid-water layers other than South Sea A in autumn and West Sea. The highest vertical acoustic biomass showed at the depth of 70-80 m in the South Sea A in spring (274.4 m2/nmi2) and the lowest one was 10-20 m in the West Sea in autumn (0.4 m2/nmi2). With regard to the horizontal distributions of fisheries resources animals, in the South Sea A, the acoustic biomass was high in eastern and central part of the South Sea and the northeast of Jeju Island (505.4-4099.1 m2/nmi2) in spring while it was high in eastern South Sea and the coastal water of Yeosu in autumn (1046.9-2958.3 m2/nmi2). In the South Sea B, the acoustic biomass was occurred high in the southern and western seas of Jeju Island in spring (201.0-1444.9 m2/nmi2) and in the southern of Jeju Island in autumn (203.7-1440.9 m2/nmi2). On the other hand, the West Sea showed very low acoustic biomass in spring (average NASC of 1.1 m2/nmi2), yet high acoustic biomass in the vicinity of 37 N in autumn (562.6-3764.2 m2/nmi2). The East Sea had high acoustic biomass in the coastal seas of Busan, Ulsan and Pohang in spring (258.7~976.4 m2/nmi2) and of Goseong, Gangneung, Donghae, Pohang and Busan in autumn (267.3-1196.3 m2/nmi2). During survey periods, fish schools were observed only in the South Sea A and the East Sea in spring and the West Sea in autumn. Fish schools in the South Sea A in spring were small size (333.2 ± 763.2 m2) but had a strong SV (–49.5 ± 5.3 dB). In the East Sea, fish schools in spring had low SV (–60.5 ± 14.5 dB) yet had large sizes (537.9 ± 1111.5 m2) and were distributed in the deep water depth (83.5 ± 33.5 m). Fish schools in the West Sea in autumn had strong SV (–49.6 ± 7.4 dB) and large sizes (507.1 ± 941.8 m2). It was the first time for three seas surrounded South Korea to be conducted by acoustic surveys to understand the distribution and aggregation characteristics of fisheries resources animals. The results of this study would be beneficially used for planning a future survey combined acoustic method and mid-water trawling, particularly deciding a survey location, a time period, and a targeting water depth.

Properties of aggregation and spatial distribution of fish were examined based on three lines in the South Sea of Korea using three frequencies (18, 38, and 120 kHz) of a scientific echosounder. The vertical distribution of fish was displayed using acoustic biomass namely nautical area scattering coefficient (NASC). As a result, at 120 kHz high NASC showed from water surface to 20 meters in deep while at 18 and 38 kHz very high NASC presented in 70 ~ 90 meters in depth, especially at line 3. Among three lines, the line 2 had lowest NASC. The horizontal distribution of fish using three frequencies together exhibited high NASC between the eastern South Sea and center of South Sea. In especial, NASC (801 ~ 1,920 m2/n·mile2) was observed along coastal waters from Busan to Tongyeong, Geoje, and Namhae. In regard with the property of aggregation of fish schools, the volume back-scattering strength (SV) of three lines presented close each other, however, the range of SV in the line 2 was shortest (-53.5 ~ -43.4 dB). The average distributional depth was deep in the order of L3 (32.8 ± 9.0 m), L1 (45.2 ± 9.5m), L2 (49.7 ± 5.6 m). The average altitude was high in the order of L3 (13.4 ± 10.3 m), L1 (17.0 ± 12.6 m), L2 (56.7 ± 5.6 m). The average length, thickness, and area were large in the order of L1, L3, and L2. This means that small sized fish schools were distributed near water surface in the line 2 while relatively large and similar sized fish aggregations between line 1 and line 3 appeared however, fish schools at line 3 had lower distributional depth and smaller compared to those at line 1. Acoustic data were visualized for demonstrating the entire circumstances of survey area. Additionally, there was no correlation between acoustic and trawl results.

PURPOSES: This investigational survey is to observe a proper spatial aggregation method for path travel time estimation using the hi-pass DSRC system. METHODS: The links which connect the nodes of section detectors location are used for path travel time estimation traditionally. It makes some problem such as increasing accumulation errors and processing times. In this background, the new links composition methods for spatial aggregation are considered by using some types of nodes as IC, JC, RSE combination. Path travel times estimated by new aggregation methods are compared with PBM travel times by MAE, MAPE and statistical hypothesis tests. RESULTS : The results of minimum sample size and missing rate for 5 minutes aggregation interval are satisfied except for JC link path travel time in Seoul TG~Kuemho JC. Thus, it was additionally observed for minimum sample size satisfaction. In 15, 30 minutes and 1 hour aggregation intervals, all conditions are satisfied by the minimum sample size criteria. For accuracy test and statistical hypothesis test, it has been proved that RSE, Conzone, IC, JC links have equivalent errors and statistical characteristics. CONCLUSIONS : There are some errors between the PBM and the LBM methods that come from dropping vehicles by rest areas. Consequently, this survey result means each of links compositions are available for the estimation of path travel time when PBM vehicles are missed.