• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.683-690
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• 2006

Reducing power consumption to extend network lifetime is one of the most important challenges in designing wireless sensor networks. One promising approach to conserving system energy is to keep only a minimal number of sensors active and put others into low-powered sleep mode, while the active sensors can maintain a connected covet set for the target area. The problem of computing such minimum working sensor set is NP-hard. In this paper, a centralized Voronoi tessellation (CVT) based approximate algorithm is proposed to construct the near optimal cover set. When sensor's communication radius is at least twice of its sensing radius, the covet set is connected at the same time; In case of sensor's communication radius is smaller than twice of its sensing radius, a connection scheme is proposed to calculate the assistant nodes needed for constructing the connectivity of the cover set. Finally, the performance of the proposed algorithm is evaluated through theoretical analysis and extensive numerical experiments. Experimental results show that the proposed algorithm outperforms the greedy algorithm in terms of the runtime and the size of the constructed connected cover set.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.5
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• pp.531-536
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• 2006

Recently, many of researchers have been studied in data processing oriented middleware for wireless sensor networks with the rapid advances on sensor and wireless communication technologies. In a wireless sensor network, a middleware should handle the data loss problem at an intermediate sensor node caused by instantaneous data burstness to support efficient processing and fast delivering of the sensing data. To handle this problem, a simple data discarding or data compressing policy for reducing the total amount of data to be transferred is typically used. But, data discarding policy decreases the correctness of a collected data, in other hand, data compressing policy requires additional processing overhead with the high complexity of the given algorithm. In this paper, it proposes a data-average method for enhancing the efficiency of data aggregation and correctness where the sensed data should be delivered only with the limited computing power and energy resource. With the proposed method, unnecessary data transfer of the overlapped data is eliminated and data correctness is enhanced by using the proposed averaging scheme when an instantaneous data burstness is occurred. Finally, with the TOSSTM simulation results on TinyBB, we show that the correctness of the transferred data is enhanced.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.123-132
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• 2012

Gas sensors has been used very differently that depending on following purposes; Automotive (exhaust gas, fuel mixture gas, oxygen, particulates), agriculture / food industry (fresh, stored, CO2, humidity, NH3, nitrogen oxide gas, organic gas, toxic gas emitted from pesticides and insecticides), industrial / medical (chemical gas, hydrogen, oxygen and toxic gases), military (chemical weapon), environmental measurements (CO and other air pollution consisting of sulfur and nitrogen gas), residential (LNG, LPG, butane, indoor air, humidity). The types of industrial toxic substances are known about 700 species and many of these exist in gaseous form under normal conditions. he multi-gas detection sensors will be developed for casualties that detect the most important and find easy three kinds of gases in marine plant; carbon dioxide(CO2), carbon(CO), ammonia(NH3). Package block consists of gas sensing device minor ingredient, rf front end, zigbee chip. Develope interworking technology between the sensor and zigbee chip inside a package. Conduct a performance test through test jig about prototype zigbee sensor module with rf output power and unwanted emission test. This research task available early address when poisonous gas leaked from large industrial site and contribution for workers' safety at the enclosed space.

• Journal of Korean Philosophical Society
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• v.147
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• pp.239-260
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• 2018

Is an artificial intelligence robot, a non-human beings newly emerging in the age of technology, a threat to human beings, or a mutual cooperation or ensemble with human beings? The desire to control nature through the use of the power of science and technology is manifested in the fear that humans can annihilate themselves. This study attempts to identify the problems of Cartesian epistemology underlying these questions and fears and to answer these questions based on Merleau - Ponty 's ontological ontology using the Ontology and Latour' s ontology and technological philosophy. The cogito derived from the Cartesian philosophy became the basis of the structure of dichotomous epistemology of 'subjectivity and objectivity' based on human - reason. In the human-centered world, all non-human beings were tools or controls for humans. The problem of the modern people is not only to get help from the natural scientific methods to control the nature including man, but also to think that scientific method is the only way to understand the world. In criticizing this, Merleau-Ponty shows that the body mediates between human beings and non-human beings, and provides a possible ontological basis for the ontology. Merleau - Ponty 's phenomenological methodology and ontology are newly developed by Simondon under the influence of phenomenological philosopher and phenomenology. The relationship between human beings and nonhuman beings by Simondon appears as an ensemble of human and technical objects or a mutual co - operation of human and technical objects. In particular, Latour goes a step further in Simondon and defines all the bodies living in the world as actor-network theory, denying the core concept of modernity. Merleau - Ponty 's phenomenological view can be a new possible basis for the philosophical discussion of the technological age. We will see that the problem itself can be solved by shifting modern fear to a phenomenological attitude.

• Journal of Korea Port Economic Association
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• v.34 no.4
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• pp.17-38
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• 2018

The purpose of this study is to establish shipping companies' selection factors related to a classification society and to explore the relative importance of each factor using the analytical hierarchy process(AHP) technique. Insufficient research exists on the hierarchial structure of shipping companies' factors of selecting a classification society. The factors are identified and classified into two tiers of major and detailed factors, by referring to the related industrial linkages, prior research related to the determinants, and the process and service delivery of the classification society's activities. The empirical analysis of this study is based on the relative importance of determinants when selecting a classification society, and experts engaged with shipping companies were surveyed using questionnaires. The results of the AHP methodology on the main factors of shipping companies in selecting a classification society are as follows. The relative importance of the main factors was 0.373 for technical and survey services, 0.284 for recognized organizations(RO) functions, 0.177 for cost and 0.167 for market(related industry) expectations. The relative importance of the detailed factors is 0.144 for the ability to respond to a port state control(PSC) inspection, 0.143 for technical services, 0.090 for the requirements of financial institutions/ shippers/shipyards, 0.087 for class maintenance costs, 0.086 for the survey network, 0.085 for surveyor competency, 0.072 for cooperation with IMO and government authorities, 0.067 for recognition for RO, 0.058 for the business power of the classification society, 0.052 for the initial inspection costs, 0.040 for reputation and trustworthiness, 0.038 for the costs related to the class, and 0.037 for connections to related industries.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.221-230
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• 2018

Most of researchers and business futurists agree that traditional organizational designs are inadequate for coping with today's turbulent and increasingly networked world. Executives in small firms find that their organizations must tap into an extended network of partners to achieve the scale and power needed to succeed in industries dominated by large, global firms. As they attempt to build lean yet agile businesses, these executives are finding that they no longer rely on gut instinct alone. Neither can they simply copy organizational model that worked in the past. They must understand how organizational design choices influence operational efficiency and flexibility and, even more important, how to best align the organization with the environment and the strategy chosen to quickly and effectively sense and respond to opportunities and threats This research examines the capabilities required to build businesses that can survive and prosper in today's fast-faced and uncertain environment. The insights presented in this research have emerged from over 30 years of work with hundreds of executives and entrepreneurs as they struggled to build businesses that could cope with the demands of a rapidly changing, networked global economy. The insights from this research suggest that IT is an important enabler for developing the best capabilities required for success.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.161-171
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• 2019

Varied methods have been researched continuously because the past as the daily maximum electricity demand expectation has been a crucial task in the nation's electrical supply and demand. Forecasting the daily peak electricity demand accurately can prepare the daily operating program about the generating unit, and contribute the reduction of the consumption of the unnecessary energy source through efficient operating facilities. This method also has the advantage that can prepare anticipatively in the reserve margin reduced problem due to the power consumption superabundant by heating and air conditioning that can estimate the daily peak load. This paper researched a model that can forecast the next day's daily peak load when considering the influence of temperature and weekday, weekend, and holidays in the Seasonal ARIMA, TBATS, Seasonal Reg-ARIMA, and NNETAR model. The results of the forecasting performance test on the model of this paper for a Seasonal Reg-ARIMA model and NNETAR model that can consider the day of the week, and temperature showed better forecasting performance than a model that cannot consider these factors. The forecasting performance of the NNETAR model that utilized the artificial neural network was most outstanding.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.561-566
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• 2021

Schools are highly feared to spread widely in the event of an infectious disease, and systematic management and prompt response are needed as it can undermine students' health and learning rights. This study was conducted to identify the current status of infectious diseases common to elementary, middle and high school students and to provide basic data to protect students and faculty from the threat of infectious diseases and maintain normal school functions. Sejong City was selected for investigation. The three major infectious diseases are influenza, chickenpox and aquarium, all of which are classified as acute viral infectious diseases and have fast propagation speed and strong propagation power, which can have fatal consequences for students living in groups. The research data were analyzed using the 2019 infectious disease report data from the Education Ministry's Education Administration Information Network (NEIS), and the current status data reported by elementary, middle and high schools nationwide were analyzed. The research method was to compare the current status of infectious diseases across the country and Sejong City, compare the status of issuance by each school level, compare the status of infectious diseases by item, and analyze the status of infectious diseases by time. The results of the survey on the status of the three major infectious diseases are expected to be used as basic data for managing infectious diseases not only in Sejong City but also in the nation, so that they can be used to establish measures to manage student infectious diseases in the future.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.149-156
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• 2021

This study started from the question of what we think about big data as the term "big data" was used and discussed in our daily lives in the era of the 4th industrial revolution. For the analysis, the final 30 Q samples were selected based on prior research related to big data, and 23 respondents were secured for Q analysis, and the following results were derived. First, the explanatory power of each type was 34.30% for , 8.03% for , 7.21% for , and 6.24% for , showing a total of 55.69%. Second, the Q sample emphasized by respondents by each type shows various occupational distributions in , and for 'big data', it is 'digital' and future'. So they were named 「Digital Type」. In , the distribution of 'social workers' was high, and for 'big data', 'future', 'collaboration', 'welfare', 'local residents', and 'defense' were emphasized. It was named 「welfare type」. In , the job distribution of respondents appeared evenly, and it was named as 「Convergence Type」. Because it emphasized statements such as 'convergence', 'digital', 'future', and 'sports'. is composed of association officials, sports instructors, and graduate students, and was named 「Artificial Intelligence Type」, because it emphasizes 'artificial intelligence', 'new paradigm', 'network', and 'sports'. In the age of knowledge industrialization and knowledge informatization that followed industrialization and informatization, how to process and utilize the numerous data accumulated over the years is an important task. Right now, in sports, more than anything else, it is necessary to continuously seek ways to utilize and activate accumulated big data.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.222-230
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• 2022

Recently, Korea's cultural content industry is developing, and behind the growing recognition around the world is the real-time sharing service of global network users due to the development of science and technology. In particular, in the case of YouTube, its propagation power is fast and powerful in that everyone, not limited users, can become potential video providers. As more than 80% of mobile phone users are using YouTube in Korea, YouTube's information means that psychological factors of users are reflected. For example, information such as the number of video views, likes, and comments of a channel with a specific personality shows a measure of the channel's personality interest. This is highly related to the fact that information such as the frequency of keyword search on portal sites is closely related to the stock market economically and psychologically. Therefore, in this study, YouTube information from a representative entertainment company is collected through a crawling algorithm and analyzed for the causal relationship with major variables related to stock prices. This study is considered meaningful in that it conducted research by combining cultural content, IT, and financial fields in accordance with the era of the fourth industry.