• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.1
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• pp.171-190
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• 2023

This study aims to develop algorithms for automatic extraction landmarks from the lower body of women aged 20-54 using the Grasshopper programming language, based on 3D scan data in the 8th SizeKorea dataset. First, 11 landmarks were defined using the morphological features of 3D body surfaces and clothing applications, from which automatic landmark extraction algorithms were developed. To verify the accuracy of the algorithm, this study developed an additional algorithm that could automatically measure 16 items, and algorithm-derived measurements and SizeKorea measurements were compared using paired t-test analysis. The statistical differences between the scan-derived measurements and the SizeKorea measurements were compared, with an allowable tolerance of ISO 20685-1:2018. This study found that the algorithm successfully identified most items except for the crotch point and gluteal fold point. In the case of landmarks with significant differences, the algorithms were modified. This study was significant because scan editing, landmark search, and measurement extraction were successfully performed in one interface, and the developed algorithm has a high efficiency and strong adaptability.

• Journal of Korean Association for Spatial Structures
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• v.16 no.2
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• pp.31-38
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• 2016

The objective of this study is to propose methods to design and analyze a catenary shell using a computer program without experiments and measurements. The intial idea stems from Pendergrast's study, but his method should be improved. In this study, the process of making catenary shell using computer was reproduced by Grasshopper script. In order to enhance credibility, two models from Grasshopper script were analyzed by SAP2000; one was just a square-based catenary shell, while the other was the re-created shell originated from the Naturtheater $Gr{\ddot{o}}tzingen$. The outcome of analysis was reasonable.

• Computers and Concrete
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• v.21 no.6
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• pp.661-667
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• 2018

The purpose of this study was to model and design a concrete catenary shell using a modern computer program without performing experiments. The modeling idea stems from the study by Pendergrast, but he listed supplementary items that should be improved in his paper. This study aims to resolve those issues and overcome the drawbacks of the study by Pendergrast. The process of experiment for the design of a catenary shell was reproduced by Grasshopper script. In order to ensure credibility, two models designed from the Grasshopper script were analyzed using a finite element program, SAP2000; one is a square-based catenary shell and the other is a special catenary shell called as the Naturtheater $Gr{\ddot{o}}tzingen$ shell, which was completed in 1977. First, the developed modeling approach was proved to be reasonable from the analysis of the square-based shell. The reliability was further confirmed by a comparison between the current and previous analysis results for the Naturtheater $Gr{\ddot{o}}tzingen$ shell.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.261-273
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• 2022

Over the last decade, the scientific community has been actively developing technologies for automated software bug fixes called Automated Program Repair (APR). Several APR techniques have recently been proposed to effectively address multiple classroom programming errors. However, little attention has been paid to the advances in effective APR techniques for software bugs that are widely occurring during the software life cycle maintenance phase. To further enhance the concept of software testing and debugging, we recommend an optimized automated software repair approach based on hybrid technology (OAPR-HOML'1). The first contribution of the proposed OAPR-HOML'1 technique is to introduce an improved grasshopper optimization (IGO) algorithm for fault location identification in the given test projects. Then, we illustrate an opposition learning based artificial neural network (OL-ANN) technique to select AST node-level transformation schemas to create the sketches which provide automated program repair for those faulty projects. Finally, the OAPR-HOML'1 is evaluated using Defects4J benchmark and the performance is compared with the modern technologies number of bugs fixed, accuracy, precession, recall and F-measure.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.504-507
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• 2011

3D graphic softwares have brought design spaces beyond the limitations of Euclidean space. Moreover, as computational geometry has been considered together with algorithms, generative algorithms are being evolved. Recently 3D graphic softwares with the embedded generative algorithms allow designers to design free form curves and surfaces in a systematic way. While architectural design has been greatly affected by the advancement of 3D graphic technology, such attention has not given in the realm of structural design. Grasshopper is a platform in Rhino to deal with these Generative Algorithms and Associative modelling techniques. This study has tried to develop a module for preliminary structural configuration using Rhino with Grasshopper. To verify the proposed concept in this study, a module for designing a basic type of suspension structure is introduced.

• Journal of KIBIM
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• v.13 no.2
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• pp.1-15
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• 2023

Since the 1960s, the Korean Peninsula, which consists of 77.4 of the country's land and mountains, has seen a surge in demand for buildings due to population concentration due to urbanization and industrialization. Since then, the development of slopes has been inevitable due to the concentration and expansion of the city's population. When building a building on a slope, it is important to set the height of the surface. In this case, the means of regulating buildings in construction-related laws, such as the building closure ratio, floor area ratio, number of floors and total floor area of buildings, have an overall effect on buildings through the height of the surface. In the Korean Building Act, the setting of the height of the ground affects the calculation of the building height limit standard and the calculation of the underground floor, and it takes a long time to calculate. Therefore, the time required for attempts to change various design plans of buildings increases. The purpose of this study is to speed up the time required to calculate the weighted average of the surface when constructing buildings on slopes. In addition, the existing calculation process allows various design attempts compared to the same time given.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.520-541
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• 2023

In CRNs, SS is of utmost significance. Every CR user generates a sensing report during the training phase beneath various circumstances, and depending on a collective process, either communicates or remains silent. In the training stage, the fusion centre combines the local judgments made by CR users by a majority vote, and then returns a final conclusion to every CR user. Enough data regarding the environment, including the activity of PU and every CR's response to that activity, is acquired and sensing classes are created during the training stage. Every CR user compares their most recent sensing report to the previous sensing classes during the classification stage, and distance vectors are generated. The posterior probability of every sensing class is derived on the basis of quantitative data, and the sensing report is then classified as either signifying the presence or absence of PU. The ISVM technique is utilized to compute the quantitative variables necessary to compute the posterior probability. Here, the iterations of SVM are tuned by novel GO-PSA by combining GOA and PSO. Novel GO-PSA is developed since it overcomes the problem of computational complexity, returns minimum error, and also saves time when compared with various state-of-the-art algorithms. The dependability of every CR user is taken into consideration as these local choices are then integrated at the fusion centre utilizing an innovative decision combination technique. Depending on the collective choice, the CR users will then communicate or remain silent.

• Geomechanics and Engineering
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• v.31 no.1
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• pp.113-127
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• 2022

The undrained shear strength of soil is considered one of the engineering parameters of utmost significance in geotechnical design methods. In-situ experiments like cone penetration tests (CPT) have been used in the last several years to estimate the undrained shear strength depending on the characteristics of the soil. Nevertheless, the majority of these techniques rely on correlation presumptions, which may lead to uneven accuracy. This research's general aim is to extend a new united soft computing model, which is a combination of random forest (RF) with grasshopper optimization algorithm (GOA) to the pile set-up parameters' better approximation from CPT, based on two different types of data as inputs. Data type 1 contains pile parameters, and data type 2 consists of soil properties. The contribution of this article is that hybrid GOA - RF for the first time, was suggested to forecast the pile set-up parameter from CPT. In order to do this, CPT data and related bore log data were gathered from 70 various locations across Louisiana. With an R² greater than 0.9098, which denotes the permissible relationship between measured and anticipated values, the results demonstrated that both models perform well in forecasting the set-up parameter. It is comprehensible that, in the training and testing step, the model with data type 2 has finer capability than the model using data type 1, with R² and RMSE are 0.9272 and 0.0305 for the training step and 0.9182 and 0.0415 for the testing step. All in all, the models' results depict that the A parameter could be forecasted with adequate precision from the CPT data with the usage of hybrid GOA - RF models. However, the RF model with soil features as input parameters results in a finer commentary of pile set-up parameters.

• Fashion & Textile Research Journal
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• v.25 no.5
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• pp.603-614
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• 2023

Body shape is the most influential factor in determining the quality of clothing fit. Women's body shape begins to change significantly in their mid-30s; therefore, this study aimed to classify and analyze the torso shapes of women aged 35-54 years. This study selected 200 3D body scans of women from the 8th Size Korea Survey database (2021). Using the Grasshopper algorithm developed in a previous study, 17 landmarks were automatically detected and 57 measurement values were generated. Using principal component analysis, 11 components (overall body size, upper body length, back protrusion, upper body slope, neck position, neck inclination, hip length, bust prominence, abdominal prominence, shoulder slope, and buttock prominence) were extracted. Three torso types were identified using K-means cluster analysis. The three body types were significantly different on nine component scores. Among the three torso types, Type 1 (37.5%) has the longest upper body and the flattest back and hips. Type 2 (31.0%) has the most curved back and forward upper body. Its abdomen is the flattest, and its shoulders are the most sloped. Type 3 (31.5%) has the shortest upper body, the most protruding hips, and the largest overall body size. This paper proposes two discriminant functions for identifying a new person's torso type.

• Fashion & Textile Research Journal
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• v.25 no.1
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• pp.92-103
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• 2023

As the body shape change which occurs after middle age is the main factor affecting the fit of ready-to-wear clothes, this study was designed to classify and analyze the torso shapes of middle-aged men. This study sorted 3D body scans of 200 men aged 40-64 from the 8th Size Korea (2021) database and extracted their 47 measurement values using the Grasshopper algorithm for automatic extraction landmarks and measurements, developed by the previous research (Ryu & Song, 2022). Eight principal components (torso length, shoulder size, overall body size, abdomen prominence, back protrusion, neck inclination, upper body slope, and hip prominence) were identified and four torso shapes were classified. Shape 1 (28.5%) exhibited the shortest torso length, the narrowest shoulders, and the most protruding back. Shape 2 (21.0%) exhibited the skinniest body and the largest backward inclination of the upper body. Hence, the back appeared to be protruding, and the abdomen looked prominent. Shape 3 (25.5%) had the largest overall body size. Thus, the abdomen looked the least protruding, and it exhibited the flattest back. Shape 4 (25.0%) had the longest torso, widest shoulders, straightest neck, and the least protruding hips. This study suggested these three discriminant functions to identify a new person's torso type.