Seasonal variations in the community structure of larval fish assemblage in Jinhae Bay were investigated in February, May, August and November of 2015, and in the same months in 2016. During the study period, a total of 28 larvae species belonging to 24 families were collected. The dominant species were Clupea pallasii, Liparis tanakae, Callionymidae sp., Sillago japonica, Ernogrammus hexagrammus and Engraulis japonica. These six species accounted for 77.6% of the total number of larvae during the survey period. The larvae of C. pallasii and L. tanakae were exclusively caught in February 2015 and 2016, while those of Apogon lineatus and Sillago japonica were exclusively caught in August 2015 and 2016. Overall, species diversity of the fish larvae was highest in February and August, although it was relatively low in May. The results of the non-metric multidimensional scaling (nMDS) analysis using the number of individual larval fish showed that they are divided into four seasonal groups. Our results showed that the community of larval fish in Jinhae Bay was affected by seasonal changes in temperature and the emergence of spawning fish species. Additionally, we suggest that the high abundance of larval fish came from around Jam-do and the northern part of Chilcheon-do; these locations are the main spawning grounds of Jinhae Bay.
Dietary niches can support the coexistence of sympatric species in marine ecosystems, which can lead to the presence of greater abundances of those species. Stomach contents of silver croaker (Pennahia argentata) and Japanese sillago (Sillago japonica) inhabiting the Nakdong River estuary, Korea were analyzed to determine diet compositions and the presence of any size-related and inter-specific feeding relationships. These species were bottom-feeding predators that consumed mainly benthic crustaceans and mollusks, but polychaetes were also important in the S. japonica diets. Non-metric multidimensional scaling (nMDS) ordination and multivariate analyses based on weight contributions of the different prey taxa to stomach contents revealed significant inter-specific dietary differences. Size-related change was also significant for P. argentata diets, but not for S. japonica. Canonical analysis of principal coordinate (CAP) ordination plot further demonstrated that differences in the type and range of prey ingested by the two species contributed such an inter-specific difference in the diet compositions. The results from this study provide clear evidence of niche segregation between co-occurring P. argentata and S. japonica in the Nakdong River estuary, which would reduce the likelihood of inter-specific competition for food resources.
Recently, the effect of using social media on psychological well-being has been highlighted. However, studies exploring factors that may predict the quality of social media relationships are relatively rare. The present study investigated whether social media activity and psychological states, such as loneliness and depression, can predict the quality of social media relationships during the COVID-19 quarantine period using a machine learning technique. Ninety-five participants completed a self-report survey on loneliness, Instagram activity, quality of social media relationships, and depression at different time points (during the self-isolation and after the release of self-isolation). Similarity analyses, including multidimensional scaling (MDS), representational similarity analysis (RSA), and classification analyses, were conducted separately at each point in time. The results of MDS revealed that time spent on social media and depression were distinguished from others in the first dimension, and loneliness and passive use were distinguished from others in the second dimension. We divided the data into two groups based on the quality of social media relationships (high and low), and we conducted RSA on each group. Findings indicated an interaction between the quality of the social media relationships and the situation. Specifically, the effect of self-isolation on the high-quality social media relationship group is more pronounced than that on the low-quality group. The classification results also revealed that the predictors of social media relationships depend on whether or not they are isolated. Overall, the results of this study imply that social media relationship could be well predicted when people are not in isolated situations.
Environmental risk assessment of living modified (LM) crops is essential for their cultivation. In this study, we cultivated β-carotene enhanced transgenic soybean (LM soybean) and non-LM soybean (Gwangan) in living modified organism (LMO) isolated fields, and investigated changes in the insect fauna using three types of collection methods for three years. In total, 331,483 individual insects and arachnids, representing 82 families in 14 orders, were captured during the study. Totals of 166,518 and 164,965 individual insects and arachnids were collected from LM soybean and Gwangan, respectively. Throughout the study, although there were differences between the investigation year, region, and methods, there were no significant differences between the population densities of insect pests, natural enemies, and other insects on LM soybean and non-LM soybean. Also, there were no statistically significant differences between varieties in the results of the species diversity analysis. The data on insect species population densities were subjected to multidimensional scaling (MDS), which did not distinguish between the two varieties, LM soybean and the non-LM soybean, in all cultivated fields. However, the results of the MDS analysis were completely divided into six groups based on the yearly survey areas. These results provided the insect diversity for an environmental risk assessment of LM soybean and suggested that the guideline could be useful to detect LM crops.
This paper presents a facial animation method that enables the user to select a sequence of facial frames from the facial expression space, whose level of details the user can select hierarchically Our system creates the facial expression space from about 2400 captured facial frames. To represent the state of each expression, we use the distance matrix that represents the distance between pairs of feature points on the face. The shortest trajectories are found by dynamic programming. The space of facial expressions is multidimensional. To navigate this space, we visualize the space of expressions in 2D space by using the multidimensional scaling(MDS). But because there are too many facial expressions to select from, the user faces difficulty in navigating the space. So, we visualize the space hierarchically. To partition the space into a hierarchy of subspaces, we use fuzzy clustering. In the beginning, the system creates about 10 clusters from the space of 2400 facial expressions. Every tine the level increases, the system doubles the number of clusters. The cluster centers are displayed on 2D screen and are used as candidate key frames for key frame animation. The user selects new key frames along the navigation path of the previous level. At the maximum level, the user completes key frame specification. We let animators use the system to create example animations, and evaluate the system based on the results.
This study, for learners using online and offline tools, understood the structural relationship of user experience of smart learning app on continuous use intention through the technology acceptance model, and classified the learning type characteristics. In addition, based on the experience of using the smart learning app, we explored ways to improve the design of the user experience design for learning tools and contents. For this purpose, the usage perception of 84 middle and high school students of the developed smart learning learning app was investigated after using it for 2 months, and the data were analyzed using the PLS structural equation technique. The main results of this study are as follows. First, system and content user experience had a significant effect on perceived usability and perceived ease of use, and the effect on continued use intention through attitude was significant. Second, there was a significant difference in the effect of system user experience on perceived usefulness in multi-group comparative analysis and gender group. In the preferred learning group, it was the path from perceived ease of use and perceived usefulness to attitude and intention to continue using that showed a significant path difference. Third, as a result of classifying the most commonly used learning types by the multidimensional scale method, the types separated into low dimensions were found to be four types: offline sync type, online sync type, ubiquitous learning type, and self-direct learning type.
Journal of the Korean Institute of Landscape Architecture
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v.36
no.4
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pp.83-99
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2008
Images of Seong-Nam appears different according to diverse conditions. This study was intended to analyze the differences of cognition by personal characteristics such as age, gender, location, and period when an individual evaluates an urban image. This research focused on the interpretation of the visualized results from Multidimensional Scaling (MDS) and Individual Difference Scaling (INDSCAL) with two questionnaires. This study can be summarized as follows: 1. Namhan Sansung was ranked as the first symbolic property by citizens in Seong-Nam. Next was Yuldong Park, followed by Bundang Central Park, Seohyun Station including Samsung Plaza, and, finally, Moran Market. This trend also similarly appeared in the selection of preferred places. 2. There were no statistical differences in trends of choice of symbolic landmarks and preferred places according to age, gender, and period; however, there were meaningful differences according to location. 3. The total image of Seong-Nam was positioned to be separated from images of other districts and landmarks on the image spatial plot by MDS; however, images of the old and new district were plotted close to symbolic landmarks where located around each district. 4. INDSCAL illustrated that men weighted the historical meaning while women weighted preference and city size when evaluating an urban image. On the other hand, there was no difference in cognitive trends according to age, location, and period. Until now, an individual difference in the cognition and evaluation of an urban image was a socially accepted notion. However, this study verified the difference according to personal characteristics and developed a practical tool to analyze an individual cognition trend about a city image.
This paper propose a method that controls facial expression of 3D avatar by having the user select a sequence of facial expressions in the space of facial expressions. And we setup its system. The space of expression is created from about 2400 frames consist of motion captured data of facial expressions. To represent the state of each expression, we use the distance matrix that represents the distances between pairs of feature points on the face. The set of distance matrices is used as the space of expressions. But this space is not such a space where one state can go to another state via the straight trajectory between them. We derive trajectories between two states from the captured set of expressions in an approximate manner. First, two states are regarded adjacent if the distance between their distance matrices is below a given threshold. Any two states are considered to have a trajectory between them If there is a sequence of adjacent states between them. It is assumed . that one states goes to another state via the shortest trajectory between them. The shortest trajectories are found by dynamic programming. The space of facial expressions, as the set of distance matrices, is multidimensional. Facial expression of 3D avatar Is controled in real time as the user navigates the space. To help this process, we visualized the space of expressions in 2D space by using the multidimensional scaling(MDS). To see how effective this system is, we had users control facial expressions of 3D avatar by using the system. As a result of that, users estimate that system is very useful to control facial expression of 3D avatar in real-time.
The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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v.16
no.1
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pp.27-38
/
2011
The distributions of phytoplankton assemblages and environmental factors in Jinhae Bay and their relationships were investigated to estimate the potential limiting nutrient for phytoplankton growth and community structure. In situ algal bioassay experiments were also conducted to assess the species-specific characteristics in phytoplankton responses under different nutrient conditions (control, N(+) and P(+) treatment). During the study periods, bacillariophyceae and cryptophyceae occupied more than 90% of total phytoplankton assemblages. Phytoplankton standing crops in the inner part of Masan Bay were higher than that of Jinhae Bay. The DIN:DIP ratio, pH and transparency showed the significant positive correlation with phytoplankton biomass. According to cluster and multidimensiolnal scaling (MDS) analysis based on phytoplankton community data from each station, the bay was divided into three groups. The first group included stations from the south-western part of Jinhae bay where cryptophyta species were dominated. The second group was distinguished from inner stations in Masan Bay. These stations showed low transpancy and high DIN:DIP ratio. The other cluster included the stations from the eastern part and central part of Jinhae Bay, which was characterized by the high DSi:DIP ratio and dominant of diatom species. Phosphorous (P) was limited in Masan Bay due to significantly increases in the phytoplankton abundances. Based on stoichiometric limitation and algal bio-assay in Jinhae Bay, nitrogen (N) was a major limiting factor for phytoplankton production. However, silicate (Si) was not considered as limiting factor, since Si/DIN and Si/P ratio and absolute concentration of nutrient did not create any potential stoichiometric limitation in the bay. This implies that high Si availability in winter season contributes favorably to the maintenances of diatom species.
The purpose of this study is to perform clustering of the habitat types and to identify the characteristics of species in the habitat types using mammal data (70,562) of the 3rd National Ecosystem Survey conducted from 2006 to 2012. The 15 habitat types recorded in the field-paper of the 3rd National ecosystem survey were reclassified, which was followed by the statistical analysis of mammal habitat types. In the habitat types cluster analysis, non-hierarchical cluster analysis (k-means cluster analysis), hierarchical cluster analysis, and non-metric multidimensional scaling method were applied to 14 habitat types recorded more than 30 times. A total of 7 Orders, 16 Families, and 39 Species of mammals were identified in the 3rd National Ecosystem Survey collected nationwide. When 11 clusters were classified by habitat types, the simple structure index was the highest (ssi = 0.07). As a result of the similarities and hierarchies between habitat types suggested by the hierarchical clustering analysis, the residential areas were the most different habitat types for mammals; the next following type was a cluster together with rivers and coasts. The results of the non-metric multidimensional scaling analysis demonstrated that both Mus musculus and Rattus norvegicus restrictively appeared in a residential area, which is the most discriminating habitat type. Lutra lutra restrictively appeared in coastal and river areas. In summary, according to our results, the mammalian habitat can be divided into the following four types: (1) the forest type (using forest as the main habitat and migration route); (2) the river type (using water as the main habitat); (3) the residence habitat (living near residential area); and (4) the lowland type (consuming grain or seeds as the main feeding resource).
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