• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.136-141
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• 2023

Artificial intelligence is becoming a global hot topic and is being actively applied in various industrial fields. Not only is artificial intelligence being applied to industrial sites in an on-premises method, but cloud-based artificial intelligence platforms are expanding into "as a service" type. The purpose of this study is to develop and verify a measurement tool for an evaluation framework for the adoption of a cloud-based artificial intelligence platform and test the interrelationships of evaluation variables. To achieve this purpose, empirical testing was conducted to verify the hypothesis using an expanded technology acceptance model, and factors affecting the intention to adopt a cloud-based artificial intelligence platform were analyzed. The results of this study are intended to increase user awareness of cloud-based artificial intelligence platforms and help various industries adopt them through the evaluation framework.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.22-28
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• 2015

In this paper, we studied the evolution of behavioral logic of artificial individuals using cell-level evolution framework. We first implemented cell-level evolution framework and then investigated the evolution of behavioral logic that artificial individuals ate foods on the framework. A logic frame for behavioral decisions of artificial individuals was devised and applied to the framework. From extensive tests, we found that most artificial individuals could evolve the behavioral logic that they could eat food in a short generation. It was also confirmed that most behavioral logics showed nearly same behaviors of artificial individuals in most tests. Our method has the differences from existing algorithms using evolutionary algorithms and evolvable hardwares in that it is a basically different approach. These results showed that our framework could be a good tool for investigating the evolution of artificial individuals in a cell-level.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.4
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• pp.701-710
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• 2002

The framework, described in this paper, involves artificial evolutionary systems that re -produce aimed solutions through a simulated Darwinian evolution process. Through this process the framework designs structures of machines innovatively and emergently especially in the stages of conceptual and basic design. Since the framework simulates the evolution of nature, it inevitably involves processes that converse the natural evolution to the artificial evolution. For the conversion, based on several methods as the building block modeling, Artificial Life, evolutionary computation and the law of natural selection, we propose a series of processes that consists of modeling, evaluation, selection, evolution etc. We have demonstrated the implementation of the framework with the design of multi-step gear systems.

• ETRI Journal
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• v.46 no.1
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• pp.106-117
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• 2024

Large language models (LLMs) have revolutionized various applications in natural language processing and exhibited proficiency in generating programming code. We propose a framework for evaluating the code generation ability of LLMs and introduce a new metric, pass-ratio@n, which captures the granularity of accuracy according to the pass rate of test cases. The framework is intended to be fully automatic to handle the repetitive work involved in generating prompts, conducting inferences, and executing the generated codes. A preliminary evaluation focusing on the prompt detail, problem publication date, and difficulty level demonstrates the successful integration of our framework with the LeetCode coding platform and highlights the applicability of the pass-ratio@n metric.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.969-976
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• 2019

A lightweight artificial intelligence hardware has made great strides in many application areas. In general, a lightweight artificial intelligence system consist of lightweight artificial intelligence engine and preprocessor including feature selection, generation, extraction, and normalization. In order to achieve optimal performance in broad range of applications, lightweight artificial intelligence system needs to choose a good preprocessing function and set their respective hyper-parameters. This paper proposes a unified framework for a lightweight artificial intelligence system and utilization method for finding models with optimal performance to use on a given dataset. The proposed unified framework can easily generate a model combined with preprocessing functions and lightweight artificial intelligence engine. In performance evaluation using handwritten image dataset and fall detection dataset measured with inertial sensor, the proposed unified framework showed building optimal artificial intelligence models with over 90% test accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.36.2-36
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• 2002

.Developing a skeletal framework artificial hand similar to real human hand. .Developing a micro artificial muscle actuated by pneumatic power. .Building a micro pneumatic system including micro atuators and its control devices. .Building a soft driving system for Service robots. .Designning and Fabricating a multi-channel micro pneumatic valve using MEMS technology.

• The Journal of Korea Robotics Society
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• v.9 no.4
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• pp.232-241
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• 2014

This paper proposes an underwater localization algorithm using probabilistic object recognition. It is organized as follows; 1) recognizing artificial objects using imaging sonar, and 2) localizing the recognized objects and the vehicle using EKF(Extended Kalman Filter) based SLAM. For this purpose, we develop artificial landmarks to be recognized even under the unstable sonar images induced by noise. Moreover, a probabilistic recognition framework is proposed. In this way, the distance and bearing of the recognized artificial landmarks are acquired to perform the localization of the underwater vehicle. Using the recognized objects, EKF-based SLAM is carried out and results in a path of the underwater vehicle and the location of landmarks. The proposed localization algorithm is verified by experiments in a basin.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.453-462
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• 2020

With the development of artificial intelligence, a lot of platforms have emerged that enable anyone to easily access and learn about artificial intelligence or create artificial intelligence models. Therefore, in this study, we analyzed various artificial intelligence education platforms and developed and proposed a SW education class plan using a framework-based artificial intelligence education platform for activating artificial intelligence based SW education. The artificial intelligence-based SW education framework aims to cultivate artificial intelligence literacy on the basis of computational thinking. In addition, a learner-centered project class was formed to include elements that could be fused with real life contexts or other subjects. Using this, with the theme of creating an artificial intelligence program to help separate garbage collection, a six-hour project-based class was developed and proposed using practical arts, social studies, and creative experiential activities. This project class was organized using a platform that is not difficult, such as AI Oceans and Entry.

• Smart Structures and Systems
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• v.32 no.1
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• pp.49-59
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• 2023

A bridge transportation network supplies products from various source nodes to destination nodes through bridge structures in a target region. However, recent frequent earthquakes have caused damage to bridge structures, resulting in extreme direct damage to the target area as well as indirect damage to other lifeline structures. Therefore, in this study, a surrogate model-based comprehensive framework to estimate the seismic resilience of bridge transportation networks is proposed. For this purpose, total system travel time (TSTT) is introduced for accurate performance indicator of the bridge transportation network, and an artificial neural network (ANN)-based surrogate model is constructed to reduce traffic analysis time for high-dimensional TSTT computation. The proposed framework includes procedures for constructing an ANN-based surrogate model to accelerate network performance computation, as well as conventional procedures such as direct Monte Carlo simulation (MCS) calculation and bridge restoration calculation. To demonstrate the proposed framework, Pohang bridge transportation network is reconstructed based on geographic information system (GIS) data, and an ANN model is constructed with the damage states of the transportation network and TSTT using the representative earthquake epicenter in the target area. For obtaining the seismic resilience curve of the Pohang region, five epicenters are considered, with earthquake magnitudes 6.0 to 8.0, and the direct and indirect damages of the bridge transportation network are evaluated. Thus, it is concluded that the proposed surrogate model-based framework can efficiently evaluate the seismic resilience of a high-dimensional bridge transportation network, and also it can be used for decision-making to minimize damage.

• Archives of Craniofacial Surgery
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• v.10 no.2
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• pp.109-113
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• 2009

Purpose: Materials for ear reconstruction are autogeneous cartilage and artificial implants. Despite their potential for donor site complications, autogeneous cartilage frameworks remain the accepted standard for external ear reconstruction. The purposes of this study were to investigate our ear reconstruction cases for 12 years. Methods: During twelve years from January 1996 to December 2008, 70 patients visited our hospital for ear reconstruction of microtia. Among them, 65 cases used autogenous cartilage frameworks, 3 cases used tissue expander and 2 cases used artificial implants. We investigated sex & age, common site, combined malformation, operation methods & their complications, donor site & their complications, anterior chest wall deformity and aesthetic evaluation. Results: Males were affected more often than females. Male to female ratio was 1.8 : 1. The common site of microtia was right ear (72%). And hemifacial microsomia was the most common associated congenital malformation. Surgical techniques included Tanzer-Ruecker method, Tissue-expander and Artificial framework ($Medpore^{(R)}$). Incidence of complication was higher with Tissue-expander & artificial framework than with Tanzer-Ruecker method. But There are few reports of using Tissue-expander & artificial framework and there was no acceptable statistical difference. And costal cartilage was harvested in ipsilateral side and anterior chest wall deformity reported only 2 cases under 10 year-old patients. Other minor complications reported such as, wound disruption and chest wall scar, but without any serious complications. Aesthetic result was evaluated by surgeons and patients for postoperative satisfaction and clinical evaluation. Conclusion: In ear reconstruction of microtia patient, delicate surgical strategy is important for natural shape and maintenance of postoperative contour. However, many methods were introduced for reconstrucion of microtia, the authors reconstructed an auricle in Tanzer-Ruecker method, Tissue-expander and Artificial famework ($Medpore^{(R)}$) for 70 patients. In our study, we generally chose Tanzer-Ruecker method and this treatment modality was satisfactory for patients and the postoperative result was acceptable for surgeons.