Body Classification Based on Adaptive Made-to-Measure( MTM ) Framework

The purpose of this paper was to develop a reliable body shape analysis approach based on cluster analysis, k. nearestneighbor( KNN), and multi-class support vector machine( MSVM). Firstly,a total of 357 Chinese men were selected to make a dataset. Secondly, the experiences of these data were not accumulated to build general models. Five body angles were extracted as independent variables. Four clusters were the most efficient cluster number for our study. Finally,the accuracy of body classifications is compared between KNN and MSVM. In this study,the body classification framework was studied to transfer the body feature data to intuitive types. Moreover,the adaptive made-tomeasure( MTM) framework based on body classification was studied. The case demonstration and analysis show the effectiveness of the study.

Monitoring Surface Water Change in Northeast China in 1999–2020:Evidence from Satellite Observation and Refined Classification

As a typical region with high water demand for agricultural production,understanding the spatiotemporal surface water changes in Northeast China is critical for water resources management and sustainable development.However,the long-term variation characteristics of surface water of different water body types in Northeast China remain rarely explored.This study investigated how surface water bodies of different types(e.g.,lake,reservoir,river,coastal aquaculture,marsh wetland,ephemeral water) changed during1999–2020 in Northeast China based on various remote sensing-based datasets.The results showed that surface water in Northeast China grew dramatically in the past two decades,with an equivalent area increasing from 24 394 km^(2) in 1999 to 34 595 km^(2) in 2020.The surge of ephemeral water is the primary driver of surface water expansion,which could ascribe to shifted precipitation pattern.Marsh wetlands,rivers,and reservoirs experienced a similar trend,with an approximate 20% increase at the interdecadal scale.By contrast,coastal aquacultures and natural lakes remain relatively stable.This study is expected to provide a more comprehensive investigation of the surface water variability in Northeast China and has important practical significance for the scientific management of different types of surface water.

Study on Body Form and Garment Size Series of the Middle Age and Aged People

This paper was designed to analyze on the data, which was obtained from 'National Physique Fitness Investigation Report (2000)'. In order to get the typical body form and figure type of the middle age and aged people, it was focused on the body form data of this group (age 40 - 60). After calculation and analyzing, the distinguishing feature of body form and the distribution of figure type were deduced. Finally, the re-classification of body form for Chinese middle age and aged people was suggested. It as also suggested that a new garment size series especially for the middle age and aged should be built to fit for these people. This conclusion would be useful and significant to design and production for clothing company, especially that who take the aged people as their target consumer.

Water Quality and Agricultural Sustainability in the Mantiqueira Ecological Corridor,Brazil

The presence of fecal coliforms is one of the determinants for classification of the quality of water bodies. The aim of this study was to evaluate the relationship between the water quality and surrounding land use in the area known as the Mantiqueira Ecological Corridor, which straddles the borders of the states of Sao Paulo, Rio de Janeiro and Minas Gerais, in Brazil. More particularly, we studied ten municipalities in Minas Gerais located in the region surrounding Serra do Papagaio State Park and Ibitipoca State Park. We established a classification of water bodies in the area surrounding the collection points in drainage basins based on the principles of sustainability. Using TM/Landsat 5 images, SPOTMap mosaics and the SRTM digital elevation model, we correlated land use classes with the environmental contamination index and topographic characteristics of the area studied. The presence of agriculture and urban areas heightened the differences in water quality classification in the comparison between the dry and rainy seasons, while in forested areas there was a greater equilibrium, with the same classification between the two seasons.

Distinguishing different subclasses of water bodies for long-term and large-scale statistics of lakes:a case study of the Yangtze River basin from 2008 to 2018

Long-term and large-scale lake statistics are meaningful for the study of environment change,but many of the existing methods are labourintensive and time-consuming.To overcome this problem,a novel method for long-term and large-scale lake extraction by shape-factorsand machine-learning-based water body classification is proposed.An experiment was conducted to extract the lakes in the Yangtze River basin(YRB)from 2008 to 2018 with the Joint Research Centre’s Global Surface Water Dataset(JRC GSW)data and OSM data.The results show:1)The proposed method is automatically and successfully executed.2)The number of river–lake complexes is between 3008 and 4697,representing 3.56%–5.70%of the total water bodies.3)The areas of the lakes and rivers in the YRB were obtained,and the accuracy of water classification in each year was stable between 90.2%and 93.6%.Comparing the back propagation neural network,random forest,and support vector machine models,we found that the three machine learning models have similar classification accuracy for the scenario.4)Fragmented and incomplete small rivers in the JRC GSW data,unchecked training samples,and overlapped shape factors are the three error sources.Future work will focus on addressing these three error sources.