• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.1025-1031
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• 2000

Pre-existing pattern recognition techniques, in the case of character recognition, have limited on the application field. But CAI character learning system and writer's recognition system are very important parts. The application field of pre-existing system can be expanded in the content that the learning of characters and the recognition of writers in the proposed paper. In order to achieve these goals, the development contents are the following: Firstly, pre-processing method by understanding the image structure is proposed, secondly, recognition of characters are accomplished b the histogram distribution characteristics. Finally, similarity measure functions are defined from standard character pattern for matching of the input character pattern. Also the effectiveness of this system is demonstrated by experimenting the standard primitive image.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.08a
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• pp.37-40
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• 2002

Ground connection began by experimenting lightning with the use of a kite and it means electric appliances, communication equipments, measuring instruments and so on connecting the Earth in order to flow away overcharged electricity. There are two kinds of earth connection: Power Ground and Signal Ground. Power Ground is for preventing an electric shock and in general there's no current in the connector. However in an accident, there's a quick flow of electricity out to the Earth. Signal Ground is not only for the safety of appliances but also for the safety of equipment operation. This paper is about connection for noise and interference reduce in order to prevent wrong operation and distortion of signal in the electrical appliances which can take place in cable TV.

• Annual Conference of KIPS
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• 2015.04a
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• pp.331-333
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• 2015

사물인터넷에 대한 연구가 활발해지면서 많은 분야에 접목이 시작되면서, 스마트 홈 자동화에 대한 관심도 새롭게 확대되고 있다. 본 논문에서는, SmartX-mini 로 호칭하는 소형 IoT-Cloud 테스트베드를 활용하여, 스마트 홈 자동화의 일례로 집 내부 문들의 정보를 실시간으로 확인하는 스마트 도어 서비스를 빠르고 효율적으로 시험적으로 구현해 본다.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.3
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• pp.9-15
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• 2021

In this paper, the Embedded MEMS system to the power apparatus used Edge Impulse machine learning tools and therefore an improved predictive system design is implemented. The proposed MEMS embedded system is developed based on nRF52840 system and the sensor with 3-Axis Digital Magnetometer, I2C interface and magnetic measurable range ±120 uT, BM1422AGMV which incorporates magneto impedance elements to detect magnetic field and the ARM M4 32-bit processor controller circuit in a small package. The MEMS embedded platform is consisted with Edge Impulse Machine Learning and system driver implementation between hardware and software drivers using SensorQ which is special queue including user application temporary sensor data. In this paper by experimenting, TensorFlow machine learning training output is applied to the power apparatus for analyzing the status such as "Normal, Warning, Hazard" and predicting the performance at level of 99.6% accuracy and 0.01 loss.

• International Journal of Aerospace System Engineering
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• v.5 no.2
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• pp.8-15
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• 2018

For small earth observation satellites, alignment between the optical components is important for precise observation. However, satellite cameras are structurally subject to misalignment in the launch environment where vibration excitations and impacts apply, and in space environments where zero gravity, vacuum, radiant heat and degassing occur. All of these variables can cause misalignment among the optical components. The misalignment among optical components results in degradation of image quality, and a re-alignment process is needed to compensate for the misalignment. This process of re-alignment between optical components is referred to as a refocusing process. In this paper, we proposed a 3 - axis focusing mechanism to perform the refocusing process. This mechanism is attached to the back of the secondary mirror and consists of three piezoelectric inertia-friction actuators to compensate the x-axis, y-axis tilt, and de-space through three-axis motion. The fabricated focus mechanism demonstrated excellent servo performance by experimenting with PD servo control.

• Journal of Environmental Science International
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• v.30 no.5
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• pp.407-412
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• 2021

This study aims to present basic data on long-term sexual effects of Savory (Satureja hortensis) by analyzing its zinc and V.B3 contents. These contents result in the activation of sexual functions induced by the blood concentration of sex hormones, thus improving menopauale symptoms. Results were obtained on August 20, 2020 after experimenting with 100 g of the herb from six indoor (green-house) experimental plots. The V.B3 results were analyzed using 100 g of Savory planted in open soil. Zinc had the highest values at 2.161 mg from the bed soil compounded with sapolite and poultry manure in the indoor condition and 2.077 mg from bed soil mixed with clay in the outdoor condition. The presence of V.B3 in Savory was also confirmed. Further research should be conducted on the interactions between Savory and other herbs.

• Journal of the Korea Society of Computer and Information
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• v.14 no.5
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• pp.175-182
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• 2009

We extracted protein signal delivery path from protein interaction data, using location information and weight of protein. We obtained the protein interaction data by experimenting in two-hybrid system using Yeast. We simulated function's data of Hypotonic Shock comparing to signal delivery path provided in KEGG from the results. We measured process running period as well. In future, this research can be key to discover the origin of various genetic diseases and develop treatment.

• Asia pacific journal of information systems
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• v.28 no.4
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• pp.308-319
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• 2018

This paper aims at providing valuable insights on Financial Fraud Detection on a mobile money transactional activity. We have predicted and classified the transaction as normal or fraud with a small sample and massive data set using Azure and Spark ML, which are traditional systems and Big Data respectively. Experimenting with sample dataset in Azure, we found that the Decision Forest model is the most accurate to proceed in terms of the recall value. For the massive data set using Spark ML, it is found that the Random Forest classifier algorithm of the classification model proves to be the best algorithm. It is presented that the Spark cluster gets much faster to build and evaluate models as adding more servers to the cluster with the same accuracy, which proves that the large scale data set can be predictable using Big Data platform. Finally, we reached a recall score with 0.73, which implies a satisfying prediction quality in predicting fraudulent transactions.

• Journal of Venture Innovation
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• v.4 no.3
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• pp.69-87
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• 2021

This study was conducted focusing on the innovative behavior necessary for the long-term survival of an organization in a business environment in which uncertainty and complexity are increasing. To this end, the relationship between issue leadership and innovative behavior of organizational members was investigated from the perspective of Signaling theory, Path-Goal theory and Job Demands-Resources theory. In addition, the mediating role of learning agility and sub-components of learning agility was empirically analyzed. For empirical analysis, a survey was conducted with a total of 252 team leaders and team members working in multinational companies (142 in Korea, 110 in the US). The results of this study are as follows. Issue leadership was analyzed to have a positive (+) effect on the innovative behavior of employees. Learning agility was found to play a mediating role between issue leadership and innovative behavior. On the other hand, the mediating effect was tested for each of the sub-components of learning agility, such as feedback seeking, information seeking, reflecting, experimenting, agility. As a result, all five sub-components were found to play a mediating role between issue leadership and innovative behavior. In particular, it was analyzed that the mediating effect of agility was the largest. Next, information seeking appeared to be large. Although there are some studies that have identified the mediating role of learning agility between issue leadership and innovative behavior, this study is considered to have academic implication as there are few cases of subdivided study. At the practical level, it is expected to provide implications for where to focus more when trying to improve an organization's learning agility and innovation behavior

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.441-448
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• 2008

The molecular docking system needs a large amount of computation and requires super-computing power. Since the experiment requires a large amount of time, the experiment is conducted in the distributed environment or in the grid environment. Recently, researches on using parallel GPU of far higher performance than that of CPU in scientific computing have been very actively conducted. CUDA is an open technique by which a parallel GPU programming is made possible. This study proposes the molecular docking system using CUDA. It also proposes algorithm that parallels energy-minimizing-computation. To verify such experiments, this study conducted a comparative analysis on the time required for experimenting molecular docking in general CPU and the time and performance of the parallel GPU-based molecular docking which is proposed in this study.