• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.959-968
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• 2022

In this paper, we intend to develop a cart with the convenience of moving objects or items that are difficult to hold by the hand of the disabled and the elderly from outdoor activities to a moving location. Using GPS module, DC motor, Bluetooth module, magnetometer sensor, and Blynk application, the smart follow cart was programmed to accurately know the owner's location while following the cart. The values of latitude and longitude of the magnetometer sensor are set so that the correct leverage value can be obtained in the lead for fine adjustment of the start and stop angles so that the user's position can be freely detected. The above motor driver L298n was connected to the motor to drive the DC motor at a fine angle. A smart follow cart was implemented that receives location signals according to the direction of the owner by turning on/off the mobile phone app as a switching role by connecting the GPS through Bluetooth wireless communication using a smartphone.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.262-269
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• 2020

Recently, many attempts have been made to reduce the time required for payment in various shopping environments. In addition, for the Fourth Industrial Revolution era, artificial intelligence is advancing, and Internet of Things (IoT) devices are becoming more compact and cheaper. So, by integrating these two technologies, access to building an unmanned environment to save people time has become easier. In this paper, we propose a smart shopping cart system based on low-cost IoT equipment and deep-learning object-detection technology. The proposed smart cart system consists of a camera for real-time product detection, an ultrasonic sensor that acts as a trigger, a weight sensor to determine whether a product is put into or taken out of the shopping cart, an application for smartphones that provides a user interface for a virtual shopping cart, and a deep learning server where learned product data are stored. Communication between each module is through Transmission Control Protocol/Internet Protocol, a Hypertext Transmission Protocol network, a You Only Look Once darknet library, and an object detection system used by the server to recognize products. The user can check a list of items put into the smart cart via the smartphone app, and can automatically pay for them. The smart cart system proposed in this paper can be applied to unmanned stores with high cost-effectiveness.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.2B
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• pp.155-163
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• 2011

In this study, a soil moisture estimation model was developed using a decision tree model, an artificial neural networks (ANN) model, remotely sensed data, and ground network data of daily precipitation, soil moisture and surface temperature. Soil moisture data of the Yongdam dam basin (5 sites) were used for model validation. Satellite remote sensing data and geographical data and meteorological data were used in the classification and regression tree (CART) model for data classification and the ANNs model was applied for clustered data to estimate soil moisture. Soil moisture data of Jucheon, Bugui, Sangjeon, Ahncheon sites were used for training and the correlation coefficient between soil moisture estimates and observations was between 0.92 to 0.96, root mean square error was between 1.00 to 1.88%, and mean absolute error was between 0.75 to 1.45%. Cheoncheon2 site was used for validation. Test statistics showed that the correlation coefficient, the root mean square error, the mean absolute error were 0.91, 3.19%, and 2.72% respectively. Results demonstrated that the developed soil moisture model using CART and ANN was able to apply for the estimation of soil moisture distribution.

• Korean Journal of Construction Engineering and Management
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• v.16 no.2
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• pp.65-76
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• 2015

The Clean Development Mechanism (CDM) is the multi-lateral 'cap and trade' system endorsed by the Kyoto Protocol. CDM allows developed (Annex I) countries to buy CER credits from New and Renewable (NE) projects of non-Annex countries, to meet their carbon reduction requirements. This in effect subsidizes and promotes NE projects in developing countries, ultimately reducing global greenhouse gases (GHG). To be registered as a CDM project, the project must prove 'additionality,' which depends on numerous factors including the adopted technology, baseline methodology, emission reductions, and the project's internal rate of return. This makes it difficult to determine ex ante a project's acceptance as a CDM approved project, and entails sunk costs and even project cancellation to its project stakeholders. Focusing on hydro power projects and employing UNFCCC public data, this research developed a prediction model using logistic regression and CART to determine the likelihood of approval as a CDM project. The AUC for the logistic regression and CART model was 0.7674 and 0.7231 respectively, which proves the model's prediction accuracy. More importantly, results indicate that the emission reduction amount, MW per hour, investment/Emission as crucial variables, whereas the baseline methodology and technology types were insignificant. This demonstrates that at least for hydro power projects, the specific technology is not as important as the amount of emission reductions and relatively small scale projects and investment to carbon reduction ratios.

• Journal of the Korea Safety Management & Science
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• v.15 no.4
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• pp.123-129
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• 2013

Among various manual materials handling tasks, pushing/pulling was known to be one of the risk factors for the low back and shoulder musculoskeletal disorders (MSDs). This study was conducted to find out an optimal solution set of the handle height and distance for 4-wheel cart with two vertical handles. Ten male college students participated in the pushing force measurement experiment. The face-centered cube design, one of the central composite designs, was applied for the experiment, and the isometric voluntary pushing force was measured in 9 treatment conditions. The second order response surface model was predicted by using the pushing strength as a response variable, and the handle height and distance as independent factors. According to the 2nd order response model, the handle height and distance showed nonlinear relationship with the isometric pushing strength. To maximize the 2nd order response model (pushing force), the handle height and distance were optimized. The optimal handle height was 'xyphoid process height - stature', and the optimal handle distance was '$1.25{\times}shoulder$ width'. When calculated using the anthropometric data of the subjects of this study, the optimal handle height was $115.4{\pm}3.4$ cm, slightly higher than the elbow height, and the handle distance was $52.9{\pm}2.3$ cm.

• Transactions of the Korean Society of Mechanical Engineers
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• v.11 no.1
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• pp.19-25
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• 1987

An optimal control procedure is presented for steering of an unmanned cart which has two motored wheels on its left and right side. Steering, running and stopping are enabled by controlling the motor speed independently. An optimal proportional-plus-integral control is employed to eliminate steady state error which is sustained by a simple proportional control for tracking a circular arc path. A simple and readily-implemented suboptimal control is also examined. The suboptimal control gives comparable performance and therefore provides an effective approach for industrial application of the unmanned cart. Effects of design parameters of unmanned cart such as forward velocity, wheel radius and position of sensor are investigated. It is shown that within the practicable values of the parameters the controlled performance improves rapidly with increase of those parameters then the improvement becomes negligible, which suggests base values over which the parameters should be taken.

• The Korean Journal of Applied Statistics
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• v.22 no.5
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• pp.923-935
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• 2009

This study aims to explore a recommended model of decision tree to predict a hard-to-measure measurement in anthropometric survey. We carry out an experiment on cross validation study to obtain a recommened model of decision tree. We use three split rules of decision tree, those are CHAID, Exhaustive CHAID, and CART. CART result is the best one in real world data.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.11 s.170
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• pp.1940-1951
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• 1999

In this paper, the equations of motion of a Bernoulli-Euler cantilever beam fixed on a moving cart and carrying a lumped mass concentrated at an arbitrary position along the beam is derived. The motion of the beam-mass-cart system is analyzed through unconstrained modal analysis, and a unified characteristic equation for calculating the natural frequencies of the system is obtained. The changes of natural frequencies and the corresponding mode shapes with respect to the changes in mass ratios of the system and to the concentrated position of the lumped mass are investigated with the frequency equation, which can be generally applied to this kind of systems. The exact and assumed-mode solutions including the dynamics of the base cart are obtained, and the open-loop responses of the system by arbitrarily designed forcing function are given by numerical simulations. The results match well with physical phenomena even at the extreme cases where the concentrated mass is attached to the bottom and to the top of the beam.

• The Korean Journal of Applied Statistics
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• v.17 no.3
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• pp.459-473
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• 2004

It has well known that an exhaustive search algorithm suggested by Breiman et. a1.(1984) has a trend to select the variable having relatively many possible splits as an splitting rule. We propose an algorithm to overcome this variable selection bias problem and then construct unbiased regression trees based on the algorithm. The proposed algorithm runs two steps of selecting a split variable and determining a split rule for binary split based on the split variable. Simulation studies were performed to compare the proposed algorithm with Breiman et a1.(1984)'s CART(Classification and Regression Tree) in terms of degree of variable selection bias, variable selection power, and MSE(Mean Squared Error). Also, we illustrate the proposed algorithm with real data sets.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.85-86
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• 2015

This paper is to study the inverted pendulum system of cart type by using the method of PID control. This system is that inverted pendulum maintain a constant balance from unstable state by moving a cart. It is controlled via the PID controller. PID controller is proposed to maintain a constant balance for nonlinear system such as the inverted pendulum system so PID control is widely used in the industrial field because of superior control performance, easy implementation and relatively simple structure. To design this system, it consist of Encorder and DC motor. Encorder is used to read the angle of the pendulum and DC motor is used to change the angle. We can verify results of experiment through the Matlab simulator via the inverted pendulum system of cart type.