• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.127-133
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• 2013

As an essential part of current industrial society, electric power energy is contantaly increasing in pace with the development of science and technology. In order to meet the demand of electric power, power facilities which take care of the higher voltage and bigger capacity is required. To produce and supply electric power on a sound basis the electric facilities should operate with reliability. To prevent disasters in advance, the high quality facilities should be manufactured, and a constant management should be done. When the power facilities cause accidents, the result is huge national deficits. Since the power facilities play a pivotal role in the key industry of national infrastructures of they should operate for a long time in maintaining a stable state, and the accidents can be prevented in advance. The lifetime of a power cable is considered to be 30 years at the time of manufacture, but in real fields, accidents of cable occur 8-12 years from the start of operation, resulting in a heavy loss of properties. In this paper, we will show that we have found out the cause and process of the deterioration of 22kV cable systems in operation. The result is that the process of deterioration does not follow the Weibull distribution only ; but rather, after the heat deterioration the Weibull distributed deterioration comes, then the cable is destroyed due to the partial discharge resulting from the Weibull distributed deterioration.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.155-161
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• 2020

In general, optimization problems are difficult to solve simply. The reason is that the given problem is solved as soon as it is simple, but the more complex it is, the very large number of cases. This study is about the optimization of AI neural network. What we are dealing with here is the relief method for constructing AI network. The main topics deal with non-deterministic issues such as the stability and unstability of the overall network state, cost down and energy down. For this one, we discuss associative memory models, that is, a method in which local minimum memory information does not select fake information. The simulated annealing, this is a method of estimating the direction with the lowest possible value and combining it with the previous one to modify it to a lower value. And nonlinear planning problems, it is a method of checking and correcting the input / output by applying the appropriate gradient descent method to minimize the very large number of objective functions. This research suggests a useful approach to relief method as a theoretical approach to solving optimization problems. Therefore, this research will be a good proposal to apply efficiently when constructing a new AI neural network.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.109-116
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• 2020

With the advent of high-speed railways, railways are one of the most frequently used means of transportation at home and abroad. In addition, in terms of environment, carbon dioxide emissions are lower and energy efficiency is higher than other transportation. As the interest in railways increases, the issue related to railway safety is one of the important concerns. Among them, visual abnormalities occur when various obstacles such as animals and people suddenly appear in front of the railroad. To prevent these accidents, detecting rail tracks is one of the areas that must basically be detected. Images can be collected through cameras installed on railways, and the method of detecting railway rails has a traditional method and a method using deep learning algorithm. The traditional method is difficult to detect accurately due to the various noise around the rail, and using the deep learning algorithm, it can detect accurately, and it combines the two algorithms to detect the exact rail. The proposed algorithm determines the accuracy of railway rail detection based on the data collected.

• Journal of Internet Computing and Services
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• v.16 no.3
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• pp.117-126
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• 2015

The concept of Creating Shared Value (CSV) has emerged as a solution for companies' sustainable growth and social problems through collaboration of business activities and social demand. Therefore, studies on shared value creativity and measurement of companies' performances are required. However, most recent studies have applied the CSV concept to existing business models or measure shared value considering only economic value. Few studies have considered the appropriateness of applying the CSV or discussed performance measurement with respect to industry characteristics. This study selects the industry expected to have the greatest created value with applying the CSV, and then suggests measurement of performance in this industry. First, through the expert interview, the study selects one from among South Korea's 10 main industries, which is expected to solve social demand through convergence with the IT industry, and to create new value for a traditional industry. The Home Appliance industry was selected as appropriate, because it has industrial growth stagnation under the smart environment. Moreover, it is facing problems such as energy savings and environmental issues. The study goes on to suggest, based on Michael Porter's three strategic levels, measurement variables of the value creation process and performance. This study has limitations from an empirical perspective. However, as the interest of applying CSV to business is growing, it is meaningful to explore the CSV strategies activities and measurement performance based on industry-specific characteristics.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.71-81
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• 2020

The digital bio-healthcare industry is one of the three major fostering industries of the Korean Moon Jae-In government. The purpose of this study is to compare and analyze the ripple effect and investment effect in digital bio-healthcare industry. Analyzing the ripple effects of the digital bio-healthcare industry is very important to induce policies on industry and technology development. First, the research methods were reclassified into 33 industries in the standard industry classification and rewritten into 35 industry classification tables. Second, various trigger coefficients and ripple effects coefficients were rewritten by the analysis framework of the industrial association table. Third, we compared the ripple effects of related industries in the production, investment, value-added and jobs sectors of the digital bio-healthcare industry. Finally, in terms of investment effects, the effects of in-house and related industries were compared. The result of this study would be helpful in the establishment of industrial policy and technology development policy.

• Journal of KIISE
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• v.43 no.6
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• pp.710-717
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• 2016

Recently, several research studies on things abstraction framework have been proposed in order to implement the multi-service Internet of Things (IoT) system, where various IoT services share the thing devices. Distributed things abstraction has an IoT service duplication problem, which aggravates power consumption of mobile devices and network traffic. On the other hand, cloud server-centric things abstraction cannot cover real-time interactions due to long network delay. Fog server-centric things abstraction has limits in insufficient IoT interfaces. In this paper, we propose Smart Fog which is a fog server-centric things abstraction framework to resolve the problems of the existing things abstraction frameworks. Smart Fog consists of software modules to operate the Smart Gateway and three interfaces. Smart Fog is implemented based on IoTivity framework and OIC standard. We construct a smart home prototype on an embedded board Odroid-XU3 using Smart Fog. We evaluate the network performance and energy efficiency of Smart Fog. The experimental results indicate that the Smart Fog shows short network latency, which can perform real-time interaction. The results also show that the proposed framework has reduction in the network traffic of 74% and power consumption of 21% in mobile device, compared to distributed things abstraction.

• Journal of the Korean Society for information Management
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• v.24 no.2
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• pp.161-179
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• 2007

As increasingly diverse kinds of information materials are available on the Internet, it becomes a challenge to define an adequate level of metadata provision for each different type of material in the context of digital libraries. This study explores issues of metadata provision for a particular type of material, statistical tables. Statistical data always involves numbers and numeric values which should be interpreted with an understanding of underlying concepts and constructs. Because of the unique data characteristics, metadata in the statistical domain is essential not only for finding and discovering relevant data, but also for understanding and using the data found. However, in statistical metadata research, more emphasis has been put on the question of what metadata is necessary for processing the data and less on what metadata should be presented to users. In this study, a case study was conducted to gauge the status of metadata provision for statistical tables on the Internet. The websites of two federal statistical agencies in the United States were selected and a content analysis method was used for that purpose. The result showing insufficient and inconsistent provision of metadata demonstrate the need for more discussions on statistical metadata from the ordinary web users' perspective.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.43-50
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• 2017

Embedded System includes touch, GPS, motion, and acceleration sensor, and can communicate with neighbor devices using wireless communication. Because Arduino with embedded system provides good environment for development and application, developers, engineers, designers, as well as artists, students have a great interest. They utilize Arduino in the robot, home appliances, fashion, culture and so on. In this paper, we design and implement a game using Arduino with embedded system which recognizes the human movement by moving away from one-dimensional game of the existing touch method. Implemented embedded system game measures gyro-sensor to recognize human movement and detects the attack success of the opponent by using touch sensor. Moreover, health of the game player is updated in the real time through the android phone-based database. In this paper, implemented embedded system-based game provides GUI screen of android phone. It is possible to select watching mode and competition mode. Also, it has low energy consumption and easy to expand because it send and receive data packet through recent Bluetooth communication.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.51-59
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• 2017

With the growth of Cloud computing, it is important to consider resource management techniques to minimize the overall costs of management. In cloud environments, each host's utilization and virtual machine's request based on user preferences are dynamic in nature. To solve this problem, efficient allocation method of virtual machines to hosts where the classification of virtual machines and hosts is undetermined should be studied. In reducing the number of active hosts to reduce energy consumption, thresholds can be implemented to migrate VMs to other hosts. By using Fuzzy logic in classifying resource requests of virtual machines and resource utilization of hosts, we proposed an adaptive VM allocation and migration approach. The allocation strategy classifies the VMs according to their resource request, then assigns it to the host with the lowest resource utilization. In migrating VMs from overutilized hosts, the resource utilization of each host was used to create an upper threshold. In selecting candidate VMs for migration, virtual machines that contributed to the high resource utilization in the host were chosen to be migrated. We evaluated our work through simulations and results show that our approach was significantly better compared to other VM allocation and Migration strategies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.49-59
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• 2017

Smart sensing plays a key role in a variety of IoT applications, and its importance is growing more and more together with the development of artificial intelligence. Therefore the importance of smart sensors cannot be overemphasized. However, most studies related to smart sensors have been focusing on specific application purposes, for example, security, energy saving, monitoring, and there are not much effort on researches on how to efficiently configure various types of smart sensors to be needed in the future. In this paper, a component-based framework with hierarchical structure for efficient construction of smart sensor is proposed and its application to smart home is designed and implemented. The proposed method shows that various types of smart sensors to be appeared in the near future can be configured through the design and development of necessary components within the proposed software framework. In addition, since it has a layered architecture, the configuration of the smart sensor can be expanded by inserting the internal or external layers. In particular, it is possible to independently design the internal and external modules when designing an IoT application service through connection with the external device layer. A small-scale smart home system is designed and implemented using the proposed method, and a home cloud operating as an external layer, is further designed to accommodate and manage multiple smart homes. By developing and thus adding the components of each layer, it will be possible to efficiently extend the range of applications such as smart cars, smart buildings, smart factories an so on.