• Journal of Distribution Science
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• v.16 no.7
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• pp.67-75
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• 2018

Purpose - In the 21st century, as information technology advances alongside the emergence of the 4th generation, industrial age, industrial environment has become individualized and customized. It is important to hire good quality employees for good service in the industry. The e-learning market is growing every year. Although e-learning companies are finding better quality employees in e-learning, it is not easy to find it. Companies also spend a lot of time and cost to find employee. On the employees side, they want to get a job freely when they want, but they cannot find their job easily. Furthermore, the labor market environment is changing fast. In the 4th generation, industrial age, employers require to find manpower whenever they need and want at little cost. So of their own accord, we have considered the necessity of management of human resources for employees and employers in e-learning. The purpose of this study is to propose a human cloud platform framework for enabling an efficient management of human resources in e-learning industry. Research design, data, and methodology - To pinpoint the items of a human cloud platform framework, the study was initiated according to the following process. First, items of competency relating to e-learning instructional designer was analyzed. Second, based on the items of information from this analysis, selection and validity verification took place with 5 e-learning specialists group. Third, the opinion of experts who were in charge of hiring in e-learning companies were collated with the questionnaire. Lastly, the human cloud platform framework was proposed based on opinion results. Results - The framework was comprised of 7 domains and 27 items in order to develop the human cloud platform for e-learning instructional designer. The analysis results showed that the most highly considered item were 'skill (4.60)' that employee already have the capability. Following this (in order) were 'project type (4.56)', 'work competency (4.56)', and 'strength area of instructional design (4.52)'. Conclusions - The 27 items in the human cloud platform framework were suggested in this study. Following this, we can consider to develop the human cloud platform for finding a job and hiring e-learning instructional designer easily. For successful platform operation, we need to consider reliability between employer and employee. In addition, we need quality assurance system based on operation has public confidence.

• Proceedings of the KSRS Conference
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• v.1
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• pp.25-28
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• 2006

We propose a new method of masking cloud-affected pixels in satellite ocean color imageries such as of GLI. Those pixels, mostly found around cloud pixels or in scattered cloud area, have anomalous features in either in chlorophyll-a estimate or in water reflectance. This artifact is most likely caused by residual error of inter-band registration correction. Our method is to check the pixel-wise 'soundness' of the spectral water reflectance Rw retrieved after the atmospheric correction. First, we define two spectral ratio between water reflectance, IRR1 and IRR2, each defined as RW(B1)/RW (B3) RW (B3) and as RW (B2)/RW(B4) respectively, where $B1{\sim}B4$ stand for 4 consecutive visible bands. We show that an almost linear relation holds over log-scaled IRR1 and IRR2 for shipmeasured RW data of SeaBAM in situ data set and for GLI cloud-free Level 2 sub-scenes. The method we propose is to utilize this nature, identifying those pixels that show significant discrepancy from that relationship. We apply this method to ADEOS-II/GLI ocean color data to evaluate the performance over Level-2 data, which includes different water types such as case 1, turbid case 2 and coccolithophore bloom waters.

• Proceedings of the KSRS Conference
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• v.1
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• pp.316-319
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• 2006

Monthly-mean aerosol parameters derived from the 1998-2004 SeaWiFS observations over East Asian waters are analyzed. SeaWiFS GAC Level 1 data covering the Northeast Asian area are collected and processed by the standard atmospheric correction algorithm released by the SeaWiFS Project to produce daily aerosol optical thickness (AOT) and ${{\AA}}ngstr{\ddot{o}}m$ exponent imageries. Monthly mean AOT and ${{\AA}}ngstr{\ddot{o}}m$ exponent values are extracted from the daily composite images for six study areas chosen from the surrounding waters of Japan. A slight increasing trend of ${{\AA}}ngstr{\ddot{o}}m$ exponent is found and interpreted as about 4-5% increase in submicron fraction of aerosol optical thickness at 550nm. Two cloud screening methods, including the standard cloud masking method of SeaWiFS and the one based on the local variance method, are applied to the SeaWiFS data processing, in an attempt to inspect the influence to the observed statistical uptrend which probably induced by different cloud mask algorithms. The variability comes from the different cloud masking algorithms are discussed.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.55-61
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• 2014

Various human-friendly robot services have been developed and mobile cloud computing is a real time computing service that allows users to rent IT resources what they want over the internet and has become the new-generation computing paradigm of information society. The enterprises and nations are actively underway of the business process using mobile cloud computing and they are aware of need for implementing mobile cloud computing to their business practice, but it has some week points such as authentication services and distributed processing technologies of big data. Sometimes it is difficult to clarify the objective of cloud computing service. In this study, the vulnerability of authentication services on mobile cloud computing is analyzed and mobile cloud computing model is constructed for efficient and safe business process. We will also be able to study how to process and analyze unstructured data in parallel to this model, so that in the future, providing customized information for individuals may be possible using unstructured data.

• Annual Conference on Human and Language Technology
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• 2010.10a
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• pp.172-176
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• 2010

본 논문에서는 위키피디아의 '틀(temp late)'을 기조로 하여 작성된 온톨로지인 OntoCloud의 신뢰도를 보장하고 공유 및 재사용을 가능하게 하기 위하여 또 다른 어휘집합체인 워드넷(WordNet)과의 매핑을 한다. 온톨로지 매핑 기술은 온톨로지 개발 기술의 한 방법으로, 서로 비슷한 도메인을 대상으로 이미 구축되어진 서로 다른 다수의 온롤로지를 연결시킴으로서 하나의 풍부한 정보를 가지고 있는 연결망을 구축하는 방법이다. 본 논문에서는 OntoCloud와 워드넷을 두개의 온톨로지로 정의하고 각 온톨로지의 개념에 대한 정의문 비교 방법을 통해서 두개의 온톨로지에 존재하는 유사한 개념을 연결한다. 이렇게 매핑된 정보들은 OntoCloud 개념을 워드넷 어휘로 연결함으로써 개념에 대한 직관적인 이해를 돕고, 워드넷에 연결된 다른 시소러스 (예: SUMO, CoreNet 등)와 간접적으로 연결할 수 있는 틀을 마련한다. 또한 온톨로지의 상하위 계층정보를 자동으로 보강하는 등의 OntoCloud 유지보수에 활용될 수 있다. 본 논문의 실험에서는 두개의 서로 다른 온톨로지의 정의문에 사용된 어휘의 겹침 정도로 두개의 개념의 유사성을 판별하는 방법을 보인다. 본 논문에서 제시한 방법으로 약 73%의 개념 매핑에 성공하였으나, 추후 매핑 프로세스의 전처리 과정(약자 처리 및 복합명사 대응 모듈)을 추가하고 온톨로지의 구조적 특성을 활용하여 유사 개념 자동 매핑 기술을 향상시키고자 한다.

• Bulletin of the Korean Chemical Society
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• v.27 no.11
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• pp.1780-1784
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• 2006

Cloud point extraction was used to extract mefenamic acid (MF) from human urine, and spectrofluorimetry and spectrophotometry were used to analyze extracted MF. The variables affecting extraction and phase separation, i.e. HCl and Triton X-114 concentration, temperature and time of equilibration, were optimized. Under the experimental conditions used the limit of detection for extraction of 25 mL of sample was 0.006 and 0.045 mg $L^{-1}$, with relative standard deviations of 2.52 and 1.45% (n = 5) for spectrofluorimetric or spectrophotometric methods, respectively. Good recoveries in the range of 95-107% were obtained for spiked samples. The proposed methods were applied to the determination of MF in human urine.

• International journal of advanced smart convergence
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• v.4 no.1
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• pp.31-34
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• 2015

Recently, the various types of data are began to increase. In order to manage the data efficiently, a variety of cloud services are being made. However, while providing a cloud service, the problem is the cost and waste a lot of human power to manage the data that is generated and managed by the server. To solve this problem, it is build the cloud environment using a single board computer with Raspberry pi. In this paper, we used Raspberry pi as a cloud server to provide services for the users. And we construct a Total Server to manage the generated data. It can separate the processing of data and the provision of services. We ensure the efficient operation by building a cloud environment with Raspberry pi and by managing the data which generated in cloud environment with the total server.

• Journal of Information Technology Applications and Management
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• v.26 no.3
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• pp.135-157
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• 2019

Information technology has economic, social and cultural impacts is closely linked to our lives. This information technology is becoming a key to the change of human civilization through connecting people and objects on the earth. In addition, future information technology is becoming more intelligent and personalized with the development of computing technology, and due to the rapid development of alcohol, environment without time and space constraint is realized, Is spreading. Since existing portable storage media are made of physical form, there is a limit to usage due to the risk of loss and limitation of capacity. Cloud services can overcome these limitations. Due to the problems of existing storage media, it is possible to overcome the limitations of storing, managing and reusing information through cloud services. Despite the large number of cloud service users, the existing research has focused mainly on the concept of cloud service and the effect of introduction on the companies. This study aims to conduct a study on individual characteristics that affect the degree of cloud use. We will conduct research on the causes of IT knowledge, personal perception of security, convenience, innovation, economical trust, and platform dependency affecting the intention to use the cloud. These results show that the variables affecting individual 's use of cloud service are influenced by individuals, and this study can be used as a basic data for individuals to use cloud service.

• Bulletin of the Korean Chemical Society
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• v.27 no.10
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• pp.1604-1608
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• 2006

A simple and efficient cloud point extraction-spectrofluorimetric method for the determination of thiamine in human urine is proposed. The procedure is based on the oxidation of thiamine with ferricyanide to form thiochrome, its extraction to Triton X-114 micelles and spectrofluorimetric determination. The variables affecting oxidation of thiamine, extraction and phase separation were studied and optimized. Under the experimental conditions used, the calibration graphs were linear over the range 2.5-1000 ng $mL^{-1}$. The limit of detection was 0.78 ng $mL^{-1}$ of thiamine and the relative standard deviation for 5 replicate determinations of thiamine at 400 ng $mL^{-1}$ concentration level was 2.42%. Average recoveries between 93-107% were obtained for spiked samples. The proposed method was applied to the determination of thiamine in human urine.

• International journal of advanced smart convergence
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• v.6 no.3
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• pp.29-37
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• 2017

The current behavior recognition system don't match data formats between sensor data measured by user's sensor module or device. Therefore, it is necessary to support data processing, sharing and collaboration services between users and behavior recognition system in order to process sensor data of a large capacity, which is another formats. It is also necessary for real time interaction with users and behavior recognition system. To solve this problem, we propose fog cloud based behavior recognition system for human body sensor data processing. Fog cloud based behavior recognition system solve data standard formats in DbaaS (Database as a System) cloud by servicing fog cloud to solve heterogeneity of sensor data measured in user's sensor module or device. In addition, by placing fog cloud between users and cloud, proximity between users and servers is increased, allowing for real time interaction. Based on this, we propose behavior recognition system for user's behavior recognition and service to observers in collaborative environment. Based on the proposed system, it solves the problem of servers overload due to large sensor data and the inability of real time interaction due to non-proximity between users and servers. This shows the process of delivering behavior recognition services that are consistent and capable of real time interaction.