• Geomechanics and Engineering
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• v.36 no.3
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• pp.259-276
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• 2024

The undrained shear strength is widely acknowledged as a fundamental mechanical property of soil and is considered a critical engineering parameter. In recent years, researchers have employed various methodologies to evaluate the shear strength of soil under undrained conditions. These methods encompass both numerical analyses and empirical techniques, such as the cone penetration test (CPT), to gain insights into the properties and behavior of soil. However, several of these methods rely on correlation assumptions, which can lead to inconsistent accuracy and precision. The study involved the development of innovative methods using extreme gradient boosting (XGB) to predict the pile set-up component "A" based on two distinct data sets. The first data set includes average modified cone point bearing capacity (q_t), average wall friction (f_s), and effective vertical stress (σ_vo), while the second data set comprises plasticity index (PI), soil undrained shear cohesion (S_u), and the over consolidation ratio (OCR). These data sets were utilized to develop XGBoost-based methods for predicting the pile set-up component "A". To optimize the internal hyperparameters of the XGBoost model, four optimization algorithms were employed: Particle Swarm Optimization (PSO), Social Spider Optimization (SSO), Arithmetic Optimization Algorithm (AOA), and Sine Cosine Optimization Algorithm (SCOA). The results from the first data set indicate that the XGBoost model optimized using the Arithmetic Optimization Algorithm (XGB - AOA) achieved the highest accuracy, with R2 values of 0.9962 for the training part and 0.9807 for the testing part. The performance of the developed models was further evaluated using the RMSE, MAE, and VAF indices. The results revealed that the XGBoost model optimized using XGBoost - AOA outperformed other models in terms of accuracy, with RMSE, MAE, and VAF values of 0.0078, 0.0015, and 99.6189 for the training part and 0.0141, 0.0112, and 98.0394 for the testing part, respectively. These findings suggest that XGBoost - AOA is the most accurate model for predicting the pile set-up component.

• Journal of the Korean Society of Costume
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• v.22
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• pp.263-276
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• 1994

The achievement of notable social reoforms attained during the period of 19th and 20th centuries needlessly speaking remodelded the social environmental into several different patterns such as :1) high industrialization 2) propensity to consume 3) up graded overall social stands. Accordingly the industrial world of the but-tons too established the mess production syhstem by breaking from convention of hand-craft work of 17th century. The raw materials used in the production line on buttons during the 20th century are almost all-kind of materials one can possibly named including cheap plastic which enabled production lines to produce cheaper but higher productivities of the buttons being produced, The design (incused design) used in the 19-20h centuries are : men landscape, sports features, birds, livestocks, bugs, or geomatric features, tec, 1, The classification o f the buttons by materials Techniques shapes colors marking (Incused design) used in the productionof buttons in the England United States of America Laska Italy france Denmark Japan and India are categolizzed as : natural raw materials and syntetical resines. 1) Of the natural raw materials used are : Matal Enamel Iodine Agate, Coral, Green jade(Jasper) Granite, Wood, Ivory, Horn and bone etc. 2) The sythetical resin used in the button in-dustries are : Artificial jewell glass Acrylic material Styroform Celluloid and Nylon etc. 2. The thecnique quoted in producing buttons are hand craft work inlay work precision casting press mosic dye etching, processing, engraving and embossed carving etc. 3. The major designs used in the buttons in -dustries are : Round shape however elliptical column angular and edge shape often used. 4. The colors used are : The multi-colors were highly used than mono-colored materials such as : Adjoining Color and Contrast Color. The highest consideration to be considered in choosing the colors for the buttons are harmonization and matching factor with the garment or dresses to be wore. 5. The major design(incused design) on the buttons are embodiment and the design were also used in order of abstractive-combination abstractive with has offers much surprising. The button industries during the 19th and 20th centuries were not only the determination factors those can judge the value of self-pride of Nation and which were far beyond the in-dustrial arts in those days but also highly refelected and influenced by cultural sense ideology and self-pride of the Nation of those period. The followings are details of the role of the buttons categolized in the order of functional ornamental and symbolical aspects : 1. The functional role : The functional role of the buttons were simply designed for dress how-ever the buttons beyond from this role of function now a days. 2. The ornamental role : The ornamental role of he button beyond from this role of the button were effectuated by : 1) shape materials colors 2) technique locations size and design (incused design) 3) The ramaterials used for buttons shall not be over looked because it is highly depends on the taste sense and combination of harmony with the garment to be wore. 4) The color of the buttons are made well contrasted with the color of garments just as in the case of other artistical area such as matchs with the color of garment of contrast with brigtness of colors contrasted as complementary color and so and so. 5) The technique being adoped are: precision casting press handcraft inlay work etching mosic etc,. Since the buttons are no longer a simple catching devise used to fasten together the different part of the dress but now it has formed own and occupied the independent role in the garment or dresses location can be de-termined and varying depending on the ideas of designers. The size of the buttons has no specific limits, However the variation has widely dependined on the entire circumperence rhythm contrast harmonization of the garments. 3. The symbolical role : Since the button is no longer a just a simple devise for catching and fastening device used fastening together the different part of the garments but now were built a independent area as major part of the Garment and well reflected all kinds of occupations political background cultural as-pect etc. on the buttons. The design of buttons in the western circles are more simplified but they are polished looks and their techniques of manufacturing are comination of both machanis and handcraft. The colors used in the buttons are pretty well harmonized with garment(dress). Almost all kind of materials can be used in the but-tons however materials used in the buttons are : Bone of livestocks ivory, turtle shell are no longer used because the prevention of cruely of animal. On the contraly the level of buttons indus-try of Korea is far to reach and catch up with the level of western circles. It is highly suggested therefore the but-tons industrial field of Republic of Korea shall place and encouragement in producing beter industrial environment of the buttons based on the traditional and cultural aspect of republic of Korea to produce both manufacturing of qulified and best designed and colored buttons.

• Korean Journal of Cognitive Science
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• v.34 no.3
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• pp.153-180
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• 2023

Previous research on the action effect had shown how simple action towards a stimulus can enhance the processing of that stimulus in subsequent visual search task (Buttaccio & Hahn, 2011; Weidler & Abrams, 2014). In four experiments, we investigated whether semantic representation of action word can induce the same attentional boost towards that stimulus and whether the type of action performed can modulate the action effect. In experiment 1, we replicated the same experimental paradigm displayed in previous studies. Participants were first shown an action word cue - "go" or "no". When the action cue was "go", participants were to press a designated key, but not to when the action cue was "no". Next, participants performed a visual search task, in which they reported the orientation of a tilted bar. The target could appear on top of the previously shown prime object (valid), or not (invalid). Reaction times (RTs) to the search task were measure for analysis and comparison, and the action effect had been replicated. In experiment 2, participants were instructed to respond with the keyboard for the action task, and to respond with the joystick for the visual search task. In experiment 3, participants were instructed not to press any key on the onset of prime, and then perform the visual search task to isolate the effect of semantic representation. Lastly, in experiment 4, participants were instructed to press separate keys for "go" and "no" on the onset of prime, and then perform the visual search task. Results indicate that semantic representation alone did not modulate the action effect, regardless of type of action and medium of action.

• Steel and Composite Structures
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• v.48 no.2
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• pp.163-177
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• 2023

Complex and intricate preparation techniques, the imperative for utmost precision and sensitivity in instrumentation, premature sample failure, and fragile specimens collectively contribute to the arduous task of measuring the fracture toughness of concrete in the laboratory. The objective of this research is to introduce and refine an equation based on the gene expression programming (GEP) method to calculate the fracture toughness of reinforced concrete, thereby minimizing the need for costly and time-consuming laboratory experiments. To accomplish this, various types of reinforced concrete, each incorporating distinct ratios of fibers and additives, were subjected to diverse loading angles relative to the initial crack (α) in order to ascertain the effective fracture toughness (Keff) of 660 samples utilizing the central straight notched Brazilian disc (CSNBD) test. Within the datasets, six pivotal input factors influencing the Keff of concrete, namely sample type (ST), diameter (D), thickness (t), length (L), force (F), and α, were taken into account. The ST and α parameters represent crucial inputs in the model presented in this study, marking the first instance that their influence has been examined via the CSNBD test. Of the 660 datasets, 460 were utilized for training purposes, while 100 each were allotted for testing and validation of the model. The GEP model was fine-tuned based on the training datasets, and its efficacy was evaluated using the separate test and validation datasets. In subsequent stages, the GEP model was optimized, yielding the most robust models. Ultimately, an equation was derived by averaging the most exemplary models, providing a means to predict the Keff parameter. This averaged equation exhibited exceptional proficiency in predicting the Keff of concrete. The significance of this work lies in the possibility of obtaining the Keff parameter without investing copious amounts of time and resources into the CSNBD test, simply by inputting the relevant parameters into the equation derived for diverse samples of reinforced concrete subject to varied loading angles.

• Advances in nano research
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• v.16 no.4
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• pp.375-394
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• 2024

The extensive utilization of concrete has given rise to environmental concerns, specifically concerning the depletion of river sand. To address this issue, waste deposits can provide manufactured-sand (MS) as a substitute for river sand. The objective of this study is to explore the application of machine learning techniques to facilitate the production of manufactured-sand concrete (MSC) containing stone nano-powder through estimating the splitting tensile strength (STS) containing compressive strength of cement (CSC), tensile strength of cement (TSC), curing age (CA), maximum size of the crushed stone (Dmax), stone nano-powder content (SNC), fineness modulus of sand (FMS), water to cement ratio (W/C), sand ratio (SR), and slump (S). To achieve this goal, a total of 310 data points, encompassing nine influential factors affecting the mechanical properties of MSC, are collected through laboratory tests. Subsequently, the gathered dataset is divided into two subsets, one for training and the other for testing; comprising 90% (280 samples) and 10% (30 samples) of the total data, respectively. By employing the generated dataset, novel models were developed for evaluating the STS of MSC in relation to the nine input features. The analysis results revealed significant correlations between the CSC and the curing age CA with STS. Moreover, when delving into sensitivity analysis using an empirical model, it becomes apparent that parameters such as the FMS and the W/C exert minimal influence on the STS. We employed various loss functions to gauge the effectiveness and precision of our methodologies. Impressively, the outcomes of our devised models exhibited commendable accuracy and reliability, with all models displaying an R-squared value surpassing 0.75 and loss function values approaching insignificance. To further refine the estimation of STS for engineering endeavors, we also developed a user-friendly graphical interface for our machine learning models. These proposed models present a practical alternative to laborious, expensive, and complex laboratory techniques, thereby simplifying the production of mortar specimens.