• Journal of KIISE:Databases
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• v.33 no.1
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• pp.69-85
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• 2006

Broadcast has been often used to disseminate the frequently requested data efficiently to a large volume of mobile clients over a single or multiple channels. Conventional concurrency control protocols for mobile transactions are not suitable for the wireless broadcast environments due to the limited bandwidth of the up-link communication channel. In wireless broadcast environments, the server often broadcast different data items with different frequency to incorporate the data access patterns of mobile transactions. The previously proposed concurrency control protocols for mobile transactions in wireless broadcast environments are focused on the mobile transactions with uniform data access patterns. However, these protocols perform poorly when the data access pattern of update mobile transaction are not uniform but skewed. The update mobile transactions with skewed data access patterns will be frequently aborted and restarted due 4o the update conflict of the same data items with a high access frequency. In this paper, we propose an energy-efficient concurrence control protocol for mobile transactions with skewed data access as well as uniform data access patterns. Our protocol use a random back-off technique to avoid the frequent abort and restart of update mobile transactions. We present in-depth experimental analysis of our method by comparing it with existing concurrency control protocols. Our performance analysis show that it significantly decrease the average response time, the amount of upstream and downstream bandwidth usage over existing protocols.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.163-172
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• 2007

The web as global network includes text document, video, sound, etc and connects each distributed information using link Through development of web, it accumulates abundant information and the main is text based documents. Most of user use the web to retrieve information what they want. So, numerous researches have progressed to retrieve the text documents using the many methods, such as probability, statistics, vector similarity, Bayesian, and so on. These researches however, could not consider both the subject and the semantics of documents. As a result user have to find by their hand again. Especially, it is more hard to find the korean document because the researches of korean document classification is insufficient. So, to overcome the previous problems, we propose the korean document classification method for semantic retrieval. This method firstly, extracts TF value and RV value of concepts that is included in document, and maps into U-WIN that is korean vocabulary dictionary to select the topic of document. This method is possible to classify the document semantically and showed the efficiency through experiment.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.1-7
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• 2019

As the cloud environment has become more prevalent among large companies, small and medium-sized companies are also trying to utilize various technologies (IoT, blockchain, etc.) that use cloud services as a way to coexist with large companies. In this paper, a blockchain-based IoT information collection model is proposed to efficiently handle large volumes of IoT data produced by small businesses in order to improve information efficiency of SMEs. The proposed model allowe d small businesses to improve their production efficiency by independently creating groups of the same information so that data that could be generated at the endpoints of small businesses can be block-chained and forwarded to the data center for analysis. In addition, the proposed model's performance assessment was assumed to handle the production throughput of data processed in IoT for small and medium businesses, not large enterprises, so the link between large volumes of data processed in the proposed model could be maintained evenly. One of the biggest features of the proposed model is the ability to expand processes to efficiently control the information of prod ucts produced, as well as the productivity of small and medium enterprises.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2534-2546
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• 2021

Nuclear emergency preparedness and response is an essential part to ensure the safety of nuclear power plant (NPP). Key support technologies of nuclear emergency decision-making usually consist of accident diagnosis, source term estimation, accident consequence assessment, and protective action recommendation. Source term estimation is almost the most difficult part among them. For example, bad communication, incomplete information, as well as complicated accident scenario make it hard to determine the reactor status and estimate the source term timely in the Fukushima accident. Subsequently, it leads to the hard decision on how to take appropriate emergency response actions. Hence, this paper aims to develop a method for rapid source term estimation to support nuclear emergency decision making in pressurized water reactor NPP. The method aims to make our knowledge on NPP provide better support nuclear emergency. Firstly, this paper studies how to build a Bayesian network model for the NPP based on professional knowledge and engineering knowledge. This paper presents a method transforming the PRA model (event trees and fault trees) into a corresponding Bayesian network model. To solve the problem that some physical phenomena which are modeled as pivotal events in level 2 PRA, cannot find sensors associated directly with their occurrence, a weighted assignment approach based on expert assessment is proposed in this paper. Secondly, the monitoring data of NPP are provided to the Bayesian network model, the real-time status of pivotal events and initiating events can be determined based on the junction tree algorithm. Thirdly, since PRA knowledge can link the accident sequences to the possible release categories, the proposed method is capable to find the most likely release category for the candidate accidents scenarios, namely the source term. The probabilities of possible accident sequences and the source term are calculated. Finally, the prototype software is checked against several sets of accident scenario data which are generated by the simulator of AP1000-NPP, including large loss of coolant accident, loss of main feedwater, main steam line break, and steam generator tube rupture. The results show that the proposed method for rapid source term estimation under nuclear emergency decision making is promising.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.179-192
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• 2019

Additional frequencies are allocated in maritime digital data exchange to alleviate overload of the VHF data link. The shipborne ad-hoc network (SANET) for this frequencies was subsequently proposed, which provides various IP-based services to ships on behalf of satellite communications. In SANET, a ship should determine its own IP address to achieve IP connectivity to the shore. Accordingly, this paper proposes a SANET configuration (SANETconf) protocol as an IP configuration protocol. SANETconf propagates non-overlapping IP addresses across the network from the shore to ships. A ship obtains its IP address by exchanging Request and Response messages with its neighbors. Therefore, SANETconf eliminates the process of DAD and managing the movement of ships. Extensive simulations were performed to verify the applicability of SANETconf. Based on results, 85% of the ships can determine their own IP address within one frame. Also, SANETconf has a high resource efficiency by using 0.024 percent of resources for IP configuration.

• Journal of Convergence for Information Technology
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• v.10 no.12
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• pp.15-21
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• 2020

Although IoT systems are used in a variety of heterogeneous environments as cloud environments develop, all IoT devices are not provided with reliable protocols and services. This paper proposes an IoT data management technique that can extend the IoT cloud environment to an n-layer multi-level structure so that information collected from different heterogeneous IoT devices can be efficiently sorted and processed. The proposed technique aims to classify and process IoT information by transmitting routing information and weight information through wireless data link data collected from heterogeneous IoT devices. The proposed technique not only delivers information classified from IoT devices to the corresponding routing path but also improves the efficiency of IoT data processing by assigning priority according to weight information. The IoT devices used in the proposed technique use each other's reliable protocols, and queries for other IoT devices locally through a local cloud composed of hierarchical structures have features that ensure scalability because they maintain a certain cost.y channels of IoT information in order to make the most of the multiple antenna technology.

• Journal of Industrial Convergence
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• v.20 no.3
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• pp.33-40
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• 2022

Recently, IoT-linked services have been used in various environments, and IoT and artificial intelligence technologies are being fused. However, since technologies that process IoT data stably are not fully supported, research is needed for this. In this paper, we propose a processing technique that can optimize IoT data after generating embedded vectors based on machine learning for IoT data. In the proposed technique, for processing efficiency, embedded vectorization is performed based on QR such as index of IoT data, collection location (binary values of X and Y axis coordinates), group index, type, and type. In addition, data generated by various IoT devices are integrated and managed so that load balancing can be performed in the IoT data collection process to asymmetrically link IoT data. The proposed technique processes IoT data to be orthogonalized based on hash so that IoT data can be asymmetrically grouped. In addition, interference between IoT data may be minimized because it is periodically generated and grouped according to IoT data types and characteristics. Future research plans to compare and evaluate proposed techniques in various environments that provide IoT services.

• Journal of Korea Foundry Society
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• v.41 no.6
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• pp.550-557
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• 2021

With the advent of the fourth industrial revolution, the interest in the internet of things (IoT) in manufacturing is growing, even at foundries. There are several types of process data that can be automatically collected at a foundry, but considerable amounts of process data are still managed based on handwriting for reasons such as the limited functions of outdated production facilities and process design based on operator know-how. In particular, despite recognizing the importance of converting process data into big data, many companies have difficulty adopting these steps willingly due to the burden of system construction costs. In this study, the field applicability of IoT-based devices was examined by manufacturing devices and applying them directly to the site of a centrifugal foundry. For the centrifugal casting process, the temperature and humidity of the working site, the molten metal temperature, and mold rotation speed were selected as process parameters to be collected. The sensors were selected in consideration of the detailed product specifications and cost required for each process parameter, and the circuit was configured using a NodeMCU board capable of wireless communication for IoT-based devices. After designing the circuit, PCB boards were prepared for each parameter, and each device was installed on site considering the working environment. After the on-site installation process, it was confirmed that the level of satisfaction with the safety of the workers and the efficiency of process management increased. Also, it is expected that it will be possible to link process data and quality data in the future, if process parameters are continuously collected. The IoT-based device designed in this study has adequate reliability at a low cast, meaning that the application of this technique can be considered as a cornerstone of data collecting at foundries.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.351-357
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• 2021

IoT devices, which are used in various ways in distributed environments, are becoming more important in data transmitted and received from IoT devices as fields of use such as medical, environment, transportation, bio, and public places are diversified. In this paper, as a method to ensure the reliability of IoT data, an autoencoder-based IoT-linked processing technique is proposed to classify and process numerous data by various important attributes. The proposed technique uses correlation indices for each IoT data so that IoT data is grouped and processed by blockchain by characteristics for IoT linkage processing based on autoencoder. The proposed technique expands and operates into a blockchain-based n-layer structure applied to the correlation index to ensure the reliability of IoT data. In addition, the proposed technique can not only select IoT data by applying weights to IoT collection data according to the correlation index of IoT data, but also reduce the cost of verifying the integrity of IoT data in real time. The proposed technique maintains the processing cost of IoT data so that IoT data can be expanded to an n-layer structure.

• Journal of Korean Elementary Science Education
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• v.41 no.2
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• pp.267-282
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• 2022

This study aims to analyze the continuity and sequence between the intelligent life curriculum for grades 1-2 and the science curriculum for grades 3-4 with a focus on knowledge and inquiry process skills. The results demonstrate that contents related to science in the intelligent life curriculum consisted of only 10 out of 32 elements. Five elements were related to the science curriculum for grades 3-4 and limited to the 'life sciences' area. Particularly, the intelligent life curriculum did not address topics related to 'matter' and 'motion and energy'. Developmental connection was established in the 'life sciences' area and dramatic changes were noted for the topics related to 'earth and space' area. In terms of inquiry process skills, the levels of observation, measurement, inference, and communication naturally increased, whereas a developmental connection was noted between the intelligent life and science curricula. Classification can be viewed as a developmental link; however, viewing the classification as scientific from the epistemic perspectives was insufficient. In the case of expectation, a gap was observed in both curricula due to the absence of expectation activities in the intelligent life curricula. The study discussed the implications for securing the connection between the intelligent life and science curricula on the basis of these results.