• Progress in Medical Physics
• /
• v.28 no.3
• /
• pp.111-121
• /
• 2017

Verification of dose distribution is an essential part of ensuring the treatment planning system's (TPS) calculated dose will achieve the desired outcome in radiation therapy. Each measurement have uncertainty associated with it. It is desirable to reduce the measurement uncertainty. A best approach is to reduce the uncertainty associated with each step of the process to keep the total uncertainty under acceptable limits. Point dose patient specific quality assurance (QA) is recommended by American Association of Medical Physicists (AAPM) and European Society for Radiotherapy and Oncology (ESTRO) for all the complex radiation therapy treatment techniques. Relative and absolute point dose measurement methods are used to verify the TPS computed dose. Relative and absolute point dose measurement techniques have a number of steps to measure the point dose which includes chamber cross calibration, electrometer reading, chamber calibration coefficient, beam quality correction factor, reference conditions, influences quantities, machine stability, nominal calibration factor (for relative method) and absolute dose calibration of machine. Keeping these parameters in mind, the estimated relative percentage uncertainty associated with the absolute point dose measurement is 2.1% (k=1). On the other hand, the relative percentage uncertainty associated with the relative point dose verification method is estimated to 1.0% (k=1). To compare both point dose measurement methods, 13 head and neck (H&N) IMRT patients were selected. A point dose for each patient was measured with both methods. The average percentage difference between TPS computed dose and measured absolute relative point dose was 1.4% and 1% respectively. The results of this comparative study show that while choosing the relative or absolute point dose measurement technique, both techniques can produce similar results for H&N IMRT treatment plans. There is no statistically significant difference between both point dose verification methods based upon the t-test for comparing two means.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.15 no.1
• /
• pp.1-8
• /
• 2020

A derivation method for a quantized gradient for machine learning on an embedded system is proposed, in this paper. The proposed differentiation method induces the quantized gradient vector to an objective function and provides that the validation of the directional derivation. Moreover, mathematical analysis shows that the sequence yielded by the learning equation based on the proposed quantization converges to the optimal point of the quantized objective function when the quantized parameter is sufficiently large. The simulation result shows that the optimization solver based on the proposed quantized method represents sufficient performance in comparison to the conventional method based on the floating-point system.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2004.04a
• /
• pp.329-334
• /
• 2004

This paper proposes Internet-based checking scheme for machine-tools with a variant CNC. Checking points defined in this research are classified into two categories such as structured point and operational point. The formal includes the vibration of bearing, temperature of spindle unit and another periodical management. And the latter includes oil checking, clamp locking/unlocking and machining on/off status. Through this research, for the global management of variant CNC machines interspersed with CAC and OAC in manufacturing system, the suitable environment for Internet-based checking of variant CNC machines was designed and the checking methods for CAC and OAC machines were compared with each other.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.2
• /
• pp.152-158
• /
• 2003

A machine-vision guided inspection system with go-no gauges for inspecting eggcrate assemblies in steam generators is considered. To locate the gauge at the right place, periodic corrective actions for its position and traveling direction are required. We present a machine vision algorithm for determining inserting position and traveling direction of the go-no gauge. The overall procedure of the algorithm is composed of camera calibration, eggcrate image preprocessing, grid-height adjustment, intersection point estimation between two intersecting grids, and adjustment of position and traveling direction of the gauge. The intersection point estimation is performed by using linear regression with a constraint. A test with a real eggcrate specimen shows the feasibility of the algorithm.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.16 no.2
• /
• pp.129-134
• /
• 2017

The process of producing a fish trap frame is very complicated and manual, so it is expensive, the quality of the product is unstable, the quality is not guaranteed, the durability is weak, and it cannot be used for a long time. Therefore, we made a fish trap frame-making machine to reduce the manpower and costs and to make robust products. This machine cuts the wire of mild steel to a certain size and then makes the connecting parts into a trapezoid shape by spot welding. In this study, the weld point shear strength between manual and automatic operation was compared and analyzed.

• Journal of the Korean Society for Precision Engineering
• /
• v.20 no.11
• /
• pp.166-170
• /
• 2003

Contouring errors are important especially for high speed and precision machining. In this study, contouring errors along contours having inflection points are studied. When a table of a machine tool moves along a circular path, acceleration acts toward the center of the circle. Thus, at inflection points, acceleration as well as inertia force changes its direction abruptly. The effect of inertia force on the contouring error is investigated in this study. It is found that the contouring error at an inflection point is proportional to the acceleration. This result can be useful in determining contouring errors along general paths.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.24 no.2
• /
• pp.166-171
• /
• 2015

In this study, an automation tool was developed for rapid evaluation of machine tool spindle designs with automated three-dimensional finite element analysis (3D FEA) using solid elements. The tool performs FEA with the minimum data of point coordinates to define the section of the spindle shaft and bearing positions. Using object-oriented programming techniques, the tool was implemented in the programming environment of a CAD system to make use of its objects. Its modules were constructed with the objects to generate the geometric model and then to convert it into the FE model of 3D solid elements at the workbenches of the CAD system using the point data. Graphic user interfaces were developed to allow users to interact with the tool. This tool is helpful for identification of a near optimal design of the spindle based on, for example, stiffness with multiple design changes and then FEAs.

• Journal of the Korean Society for Precision Engineering
• /
• v.12 no.10
• /
• pp.121-129
• /
• 1995

The objective of this research is to develop an effective inspection planning strategy for sculptured surfaces by using 3-dimensional Coordinate Measuring Machine (CMM). First, the CAD/CAM database is generated by using the Bezier surface patch mathod and variable cutter step size approach for design and machining of the workpiece model. Then, optimum measuring point locations are determained based on the mean curvature analysis to obtain more effective inspection results for the given sample numbers. An optimal probe sequence generation method is proposed by implementing the Traveling Salesperson (TSP) algorithm and new guide point selection methods are suggested based on the concepts of the variable distance between the first and second guide points. Finally, simulation study and experimental work show the effectiveness of the proposed strategy.

• Journal of Korean Society of Water and Wastewater
• /
• v.35 no.6
• /
• pp.507-516
• /
• 2021

In this study, the machine learning which has been widely used in prediction algorithms recently was used. the research point was the CD(chudong) point which was a representative point of Daecheong Lake. Chlorophyll-a(Chl-a) concentration was used as a target variable for algae prediction. to predict the Chl-a concentration, a data set of water quality and quantity factors was consisted. we performed algorithms about random forest and gradient boosting with Python. to perform the algorithms, at first the correlation analysis between Chl-a and water quality and quantity data was studied. we extracted ten factors of high importance for water quality and quantity data. as a result of the algorithm performance index, the gradient boosting showed that RMSE was 2.72 mg/m³ and MSE was 7.40 mg/m³ and R² was 0.66. as a result of the residual analysis, the analysis result of gradient boosting was excellent. as a result of the algorithm execution, the gradient boosting algorithm was excellent. the gradient boosting algorithm was also excellent with 2.44 mg/m³ of RMSE in the machine learning hyperparameter adjustment result.

• Journal of the Korean Society for Precision Engineering
• /
• v.14 no.12
• /
• pp.24-29
• /
• 1997

Recently, Genetic Algorithm(GA), which is a stochastic direct search strategy that mimics the process of genetic evolution, is widely adapted into a search procedure for structural optimization. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA is very simple in their algorithms and there is no need of continuity of functions(or functionals) any more in GA. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher porbability of convergence to global optimum compared to traditional techniques which take one-point search method. The methods consist of three genetics opera- tions named selection, crossover and mutation. In this study, a method of finding the omtimum size and topology of drilling machine is proposed by using the GA, For rapid converge to optimum, elitist survival model,roulette wheel selection with limited candidates, and multi-point shuffle cross-over method are adapted. And pseudo object function, which is the combined form of object function and penalty function, is used to include constraints into fitness function. GA shows good results of weight reducing effect and convergency in optimal design of drilling machine.