• International journal of advanced smart convergence
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• v.3 no.2
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• pp.14-17
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• 2014

Precision agriculture relies on information technology, whose precondition is providing real-time and accurate information. It depends on various kinds of advanced sensors, such as environmental temperature and humidity, wind speed, light intensity, and other types of sensors. Currently, it is a hot topic how to collect accurate information, the main raw data for agricultural experts, monitored by these sensors timely. Most existing work in WSNs addresses their fundamental challenges, including power supply, limited memory, processing power and communication bandwidth and focuses entirely on their operating system and networking protocol design and implementation. However, it is not easy to find the self-localization capability of wireless sensor networks. Because of constraints on the cost and size of sensors, energy consumption, implementation environment and the deployment of sensors, most sensors do not know their locations. This paper provides maximum likelihood estimators for sensor location estimation when observations are time-of arrival (TOA) range measurement.

• 한국벤처창업학회:학술대회논문집
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• 2008.04a
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• pp.143-178
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• 2008

This study is to look into the spin-off ventures which was incorporated based on the technology developed by public research institute, but underwent difficulties confronted during the development stages focused on the growth process and the factors contributed to their success. The case study was conducted with i-Sense Co., Ltd. which is a ventures organized by professors as a form of research based spin-off venture. i-Sense Co., Ltd. is a new-technology based ventures to produce self-tester for blood sugar level which was incorporated by Prof. Cha, Keun-sik and Prof. Nam, Hak-hyun of Department of Chemistry in Kwangwoon University along with the graduate course students of the Research Laboratory of the University. The two professors operated the Chemical Sensor Research Center at the Kwangwoon University where they produced many preliminary research outputs related with bio-sensors. They also executed the service works at the specialized company they established for research development to make research fund. They established i-Sense Co., Ltd. with the aim to carry out the research they want to. But contrary to the initial intention of the founders of the company, i-Sense Co., Ltd. has grown up as manufacturing company which produces and sells the self-tester for blood sugar level and is expected to be listed by Initial Public Offering (IPO) on the KOSDAQ in 2008. This study is to analyze the foundation and the growth process of i-Sense Co., Ltd. as successful research based spin-off ventures, to find out the factors contributed to their success by enabling them to overcome the difficulties experienced during the growth process, and eventually to provide with suggestive meanings in policy and practical point of view that leaded the research based spin-off ventures to success.

• ETRI Journal
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• v.37 no.2
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• pp.222-232
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• 2015

In this paper, we propose a dual-phase approach to improve the process of heart disease prediction in a mobile environment. Firstly, only the confident frequent rules are extracted from a patient's clinical information. These are then used to foretell the possibility of the presence of heart disease. However, in some cases, subjects cannot describe exactly what has happened to them or they may have a silent disease - in which case it won't be possible to detect any symptoms at this stage. To address these problems, data records collected over a long period of time of a patient's heart rate variability (HRV) are used to predict whether the patient is suffering from heart disease. By analyzing HRV patterns, doctors can determine whether a patient is suffering from heart disease. The task of collecting HRV patterns is done by an online artificial neural network, which as well as learning knew knowledge, is able to store and preserve all previously learned knowledge. An experiment is conducted to evaluate the performance of the proposed heart disease prediction process under different settings. The results show that the process's performance outperforms existing techniques such as that of the self-organizing map and gas neural growing in terms of classification and diagnostic accuracy, and network structure.

• Journal of the Semiconductor & Display Technology
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• v.20 no.1
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• pp.48-53
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• 2021

The purpose of this study is to establish a crime prevention system through the Crime Prevention Through Environmental Design (CPTED). The research method went through the double diamond process and discovered the user's needs through the persona analysis. The most representative features are the functions that informs users of the safe and optimal route, checks the presence of streetlights or cctvs in real time to update them, and allows people with similar routs to return home together. It is a function to help safe return home with the help of an autonomous method, and a self-defense function to protect themselves. Therefore, the application presented in this study was intended to be of great help when actually returning home by adding these new functions. In particular, we help users to return home most safely by recommending the best safe route. Through the persona analysis, research method which we had chosen, the needs of users were discovered and implemented in a design that reflected those needs and requirements.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.251-256
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• 2018

There have been various studies being conducted to prepare for aging society due to the recent trend of rapid aging. The silver industry such as wellness, senior monitoring and support service, and emergency medical assistance services for the elderly is growing fast. However, due to economic problems, limited services are being provided. In addition, the problem of residence of elderly people and care of elderly patients are also becoming important issues to be solved. Aging in Place is emerging as an alternative to solve the problem of local deviation, controlled communication, and loss of self-sufficiency in the process of residents residing in the facility. In this paper, we propose IoT environment construction for ICT based Aging in Place information extension support. By building an IoT environment for Aging in Place support, users can be provided with services that can meet their needs in a familiar environment. The proposed method builds an environment that can be self-supporting based on the user's information and provides medical, transportation, and life support services for the elderly.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.3
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• pp.328-338
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• 2021

A study on common modular design based on open standards to reduce the life cycle cost of ground weapon system is underway. Since the ground weapon system includes major mission equipment such as fire control system, it is essential to apply the concept of fault tolerance through automatic reconfiguration and blocking unspecified equipment through connectivity control. However, it is difficult to generalize due to the difference in operating characteristics for each system. In this paper, we propose a plug-and-play framework, which includes plug-and-play architecture and mechanism. The proposed method can be used in common by the application of each component as it is divided into a common service layer. In addition, the proposed connectivity control and autonomous reconfiguration method facilitates reflection of operating characteristics for each system. We constructed a verification environment that can simulate ground weapon systems and components, and verified that the proposed framework works through scenario-based functional tests.

• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.93-104
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• 2005

Recently, RFID/USN is one of fundamental technologies in information and communications networks. Low-Rate WPAN, IEEE802.15.4 is a low-cost communication network that allows wireless connectivity in applications with limited Power and relaxed throughput requirements. Its applications are building automation, personal healthcare, industrial control, consumer electronics, and so on. Some applications require location information. Of course location awareness is useful to improve usability of data Low-Rate WPAN Is regarded as a key specification of the sensor network with the characteristics of wireless communication, computing, energy scavenging, self-networking, and etc. Unfortunately ZigBee alliance propose a lot of applications based on location aware technologies, but the specification and low-rate WPAN devices don't support anything about location-based services. RSSI ( Received Signal Strength indication) is for energy detection to associate, channel selection, and etc. RSSI is used to find the location of a potable device in WLAN. In this paper we studied indoor location awareness using vector matching of RSSI in low-Rate wireless PAN. We analyzed the characteristics of RSSI according to distance and experimented location awareness. We implemented sensor nodes with different shapes and configured the sensor network for the location awareness with 4 fixed nodes and a mobile node. We try to contribute developing location awareness method using RSSI in 3-dimension space.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.508-510
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• 2021

As the international standardization of 5G element technologies (e.g., 5G vertical satellite, direct communication functions between 5G NR (New Radio)-based devices) required not only in 5G verticals but also in autonomous navigation services is currently underway, it is expected to be utilized for autonomous navigation services while utilizing the economic size advantages of the scale of international standard-based solutions through 3GPP international standardization of marine communication services related to autonomous navigation vessels. In order to establish the ecosystem of ICT convergence market related to autonomous navigation vessels and to preoccupy core communication technology based on international standards, it is necessary to develop digital communication systems and gateways that have global compatibility, (2) secure core element technology based on next generation communication, and (3) promote international standardization for internationalization of related technologies. For this, data analysis and standard technology should be developed through service analysis by distance. Currently, the requirements for the operation of autonomous navigation vessels can be classified into three categories.

• 대한공업교육학회지
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• v.40 no.1
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• pp.180-200
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• 2015

The problems current robotic technology education class has are the students with different basic background knowledge levels and the class based on the instructional teaching method. This study shows the implementation of the student teams achievement divisions (STAD) learning model into an introductory robotic technology education class to resolve the problems in the current robotic technology class. The STAD learning model focuses on the ability of each team member with different knowledge levels and make team members help each other through class activities such as assignments and a project. All members get rewarded by their performance output as a team in a course grade. The outputs of STAD learning models were measured by paired sample t-test as pre-test and post-test in terms of students's transition on basic knowledge for robotic technology, students' attitudinal transition on teaching robotic technology class, and students' competencies and self-efficacy on related subject areas. The study participants were 22 pre-service technology teachers at a university. The results show that all four measured areas were improved significantly, compared to pre-test with respect to the means scores of each measurement area. The STAD learning model could be an alternate for the current robotic technology class to deliver the better class outcomes for students under the specific circumstances.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.