• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 1997년도 특별강연 및 추계학술발표 개요집
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• pp.205-209
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• 1997

One of the major important tasks in the robotic $CO_2$ arc welding process is to understand how process variables affected bead geometry and to subsequently develop the mathematical models to predict the desired bead dimensions. Experiment results are compared to outputs obtained using a set of published formulae relating input variables to output parameters and also investigated process variables on bead geometry for robotic $CO_2$ arc welding process The university of results obtained using empirical equations taken from existing models provided to be limited in predicting experimental bead shapes.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 추계학술대회 논문집
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• pp.170-174
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• 2004

Despite the widespread use in the various manufacturing industries, the full automation of the robotic CO$_2$ welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this paper, an attempt has been made to develop an Radial basis function network model to predict the weld top-bead width as a function of key process parameters in the robotic CO$_2$ welding. and to compare the developed model and a simple neural network model using two different training algorithms in order to verify performance. of the developed model.

• 한국간담췌외과학회지
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• 제27권3호
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• pp.292-300
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• 2023

Backgrounds/Aims: Current literature presents limited data regarding outcomes following conversion at the time of minimally invasive pancreaticoduodenectomy (MI-PD). Methods: The National Cancer Database was queried for patients who underwent pancreaticoduodenectomy. Patients were stratified into three groups: MI-PD, converted to open pancreaticoduodenectomy (CO-PD), and open pancreaticoduodenectomy (O-PD). Multivariable modeling was applied to compare outcomes of MI-PD and CO-PD to those of O-PD. Results: Of 17,570 patients identified, 12.5%, 4.2%, and 83.4% underwent MI-PD, CO-PD, and O-PD, respectively. Robotic pancreaticoduodenectomy (R-PD) resulted in a higher lymph node yield (n = 23.2 ± 12.2) even when requiring conversion (n = 22.4 ± 13.2, p < 0.001). Margin positivity was higher in the CO-PD group (26.6%) than in the MI-PD group (21.3%) and the O-PD (22.6%) group (p = 0.017). Length of stay was shorter in the MI-PD group (laparoscopic pancreaticoduodenectomy 10.4 ± 8.6, R-PD 10.6 ± 8.8) and the robotic converted to open group (10.7 ± 6.4) than in the laparoscopic converted to open group (11.2 ± 9) and the O-PD group (11.5 ± 8.9) (p < 0.001). After adjusting for patient and tumor characteristics, both MI-PD (odds ratio = 1.40; p < 0.001) and CO-PD (odds ratio = 1.24; p = 0.020) were significantly associated with an increased likelihood of long-term survival. Conclusions: CO-PD does not negatively impact perioperative or oncologic outcomes.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.596-599
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• 2004

The robotic $CO_2$ welding is a manufacturing process to produce high quality joints for metal and it could provide a capability of full automation to enhance productivity. Despite the widespread use in the various manufacturing industries, the full automation of the robotic $CO_2$ welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this research, an attempt has been made to develop an intelligent algorithm to predict the weld geometry (top-bead width, top-bead height, back-bead width and back-bead height) as a function of key process parameters in the robotic $CO_2$welding. To achieve this above objective, Taguchi method was employed using five different process parameters (tip gap, gas flow rate, welding speed, arc current, welding voltage) as a guide for optimization of process parameters.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권3호
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• pp.185-190
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• 2002

In distributed autonomous robotic systems (DARS), each robot must behave by itself according to its states ad environments, and if necessary, must cooperate with other robots in order to carry out their given tasks. Its most significant merit is that they determine their behavior independently, and cooperate with other robots in order to perform the given tasks. Especially, in DARS, it is essential for each robot to have evolution ability in order to increase the performance of system. In this paper, a schema co-evolutionary algorithm is proposed for the evolution of collective autonomous mobile robots. Each robot exchanges the information, chromosome used in this algorithm, through communication with other robots. Each robot diffuses its chromosome to two or more robots, receives other robot's chromosome and creates new species. Therefore if one robot receives another robot's chromosome, the robot creates new chromosome. We verify the effectiveness of the proposed algorithm by applying it to cooperative search problem.

• Archives of Plastic Surgery
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• 제41권3호
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• pp.225-230
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• 2014

The increased application of the da Vinci robotic platform (Intuitive Surgical Inc.) for microsurgery has led to the development of new adjunctive surgical instrumentation. In microsurgery, the robotic platform can provide high definition $12{\times}-15{\times}$ digital magnification, broader range of motion, fine instrument handling with decreased tremor, reduced surgeon fatigue, and improved surgical productivity. This paper presents novel adjunctive tools that provide enhanced optical magnification, micro-Doppler sensing of vessels down to a 1-mm size, vein mapping capabilities, hydro-dissection, micro-ablation technology (with minimal thermal spread-$CO_2$ laser technology), and confocal microscopy to provide imaging at a cellular level. Microsurgical outcomes from the use of these tools in the management of patients with infertility and chronic groin and testicular pain are reviewed. All these instruments have been adapted for the robotic console and enhance the robot-assisted microsurgery experience. As the popularity of robot-assisted microsurgery grows, so will its breadth of instrumentation.

• 한국항행학회논문지
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• 제14권2호
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• pp.206-212
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• 2010

본 논문에서는 유비쿼터스 환경에서 로봇의 응용서비스를 제공하는데 필요한 네트워크로서 로보틱 지그비 네트워크의 개념을 소개하고 이를 이용한 응용 시나리오를 제시한다. 제시한 응용시나리오의 기본이 되는 네트워크 연결 및 데이터 전송에 관한 실험을 수행하였다. 이 실험 결과를 통해 앞으로 Robotic Zigbee Network를 이용한 위치인식 오차율을 최소화하는 로봇의 위치추정 및 추적 알고리즘 개발의 기반을 마련한다.

• 대한의용생체공학회:의공학회지
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• 제29권3호
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• pp.187-190
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• 2008

This paper presents two dimensional receiving coils to provide hundreds of milli-watt power via inductive link to in vivo robotic capsules, whose orientation are practically undetermined. The wireless power transmission system consists of a transmitter powered by class E power amplifier, and a receiver with three dimensional antenna, rectifier, and voltage regulator. As the 2D lateral antenna construction is more critical for the receiving antenna, two types of 2D antennas are introduced and evaluated by theoretic and experimental analyses. Experimental results verifies that the cross-type construction show better directional performance for receiving power than the cylindrical one for the 2D antenna. The former could deliver the power homogeneously regardless of its orientation, with less than 20 % of variation from the possible maximum power.

• International Journal of Korean Welding Society
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• 제1권1호
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• pp.17-22
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• 2001

Because the quantitative relationships between welding parameters and welding result are not yet blown, optimal values of welding parameters for $CO_2$ robotic arc welding is a difficult task. Using the various artificial data processing methods may solve this difficulty. This research aims to develop an expert system for $CO_2$ robotic arc welding to recommend the optimal values of welding parameters. This system has three main functions. First is the recommendation of reasonable values of welding parameters. For such work, the relationships in between the welding parameters are investigated by the use of regression analysis and fuzzy system. The second is the estimation of bead shape by a neural network system. In this study the welding current voltage, speed, weaving width, and root gap are considered as the main parameters influencing a bead shape. The neural network system uses the 3-layer back-propagation model and a generalized delta rule as teaming algorithm. The last is the optimization of the parameters for the correction of undesirable weld bead. The causalities of undesirable weld bead are represented in the form of rules. The inference engine derives conclusions from these rules. The conclusions give the corrected values of the welding parameters. This expert system was developed as a PC-based system of which can be used for the automatic or semi-automatic $CO_2$ fillet welding with 1.2, 1.4, and 1.6mm diameter the solid wires or flux-cored wires.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.1845-1848
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• 2005

The automatic $CO_2$ welding is a manufacturing process to produce high quality joints for metal and it could provide a capability of full automation to enhance productivity. Despite the widespread use in the various manufacturing industries, the full automation of the robotic $CO_2$ welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this research, an attempt has been made to develop an intelligent algorithm to predict the weld geometry (top-bead width, top-bead height, back-bead width and back-bead height) as a function of key process parameters in the robotic $CO_2$welding. A sensitivity analysis has been conducted and compared the relative impact of three process parameters on bead geometry in order to verify the measurement errors on the values of the uncertainty in estimated parameters.