• Annual Conference of KIPS
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• 2011.04a
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• pp.590-593
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• 2011

Time goes on, Ad Hoc network is hot issues. So far, there are a lot of protocols have been proposed for Ad Hoc routing protocol to support the mobility. This paper presents an enhanced DSDV(Destination-Sequenced Distance Vector) routing protocol which nominates one node to take care of a specific area. Simply Area-Aware(AA) DSDV routing protocol has one nominee to take care of some area. It has two jobs. One is to take care of its neighbour and another is to transfer the routing table to its other node as it works. It is called as Area Nominee(AN). The new scheme extends the routing table to include the nominee in the area. The general node is the same as the previous DSDV routing protocol. In the other hands, the node which is nominated has two routing protocols. One is for Regional Routing(RR) table which is the same routing table in DSDV. Another is Global Routing(GR) table which is about the area round its area which it cares nearby. GR table is the table for the designated node like the nominee. Each area has one nominee to transfer between ANs. It has only nominee's information about every area. This concept decreases the topology size and makes the information of topology more accurate.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.6
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• pp.93-103
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• 2023

This study aimed to analyze the impact of water curtain cultivation in the greenhouse complexes on groundwater's electric conductivity and water temperature. The greenhouse complexes are mainly situated along rivers to secure water resources for water curtain cultivation. We classified the groundwater monitoring well into the greenhouse (riverside) and field cultivation areas (plain) to compare the groundwater impact of water curtain cultivation in the greenhouse complex. The groundwater observation network in Miryang, Gyeongsangnam-do, located downstream of the Nakdong River, was selected for the study area. As a result of analyzing the electric conductivity and water temperature, the following differences were found in the observed characteristics by region. 1) The electric conductivity and water temperature of the riverside area, where the permeability is high and close to rivers, showed a constant pattern of annual changes due to the influence of river flow and precipitation. 2) The flat land in general agricultural areas showed general characteristics of bedrock observation in the case of water temperature. Still, it seemed more affected by the surrounding well's water use and water quality. The electric conductivity did not show any particular trend and was influenced by the surrounding environment according to the location of each point.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2701-2717
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• 2023

In this paper, a hybrid fuzzy-based method is suggested for determining India's best system for power generation. This suggested approach was created using a fuzzy-based combination of the Giza Pyramids Construction (GPC) and Recalling-Enhanced Recurrent Neural Network (RERNN). GPC is a meta-heuristic algorithm that deals with solutions for many groups of problems, whereas RERNN has selective memory properties. The evaluation of the current load requirements and production profile information system is the main objective of the suggested method. The Central Electricity Authority database, the Indian National Load Dispatch Centre, regional load dispatching centers, and annual reports of India were some of the sources used to compile the data regarding profiles of electricity loads, capacity factors, power plant generation, and transmission limits. The RERNN approach makes advantage of the ability to analyze the ideal power generation from energy data, however the optimization of RERNN factor necessitates the employment of a GPC technique. The proposed method was tested using MATLAB, and the findings indicate that it is effective in terms of accuracy, feasibility, and computing efficiency. The suggested hybrid system outperformed conventional models, achieving the top result of 93% accuracy with a shorter computation time of 6814 seconds.

• Korea Trade Review
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• v.47 no.2
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• pp.69-88
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• 2022

This paper aims to predict Busan's regional product and employment using the logistic regression models and machine learning models. The following are the main findings of the empirical analysis. First, the OLS regression model shows that the main industries such as electricity and electronics, machine and transport, and finance and insurance affect the Busan's income positively. Second, the binomial logistic regression models show that the Busan's strategic industries such as the future transport machinery, life-care, and smart marine industries contribute on the Busan's income in large order. Third, the multinomial logistic regression models show that the Korea's main industries such as the precise machinery, transport equipment, and machinery influence the Busan's economy positively. And Korea's exports and the depreciation can affect Busan's economy more positively at the higher employment level. Fourth, the voting ensemble model show the higher predictive power than artificial neural network model and support vector machine models. Furthermore, the gradient boosting model and the random forest show the higher predictive power than the voting model in large order.

• IMMUNE NETWORK
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• v.22 no.1
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• pp.4.1-4.22
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• 2022

In the era of immunotherapeutic control of cancers, many advances in biotechnology, especially in Ab engineering, have provided multiple new candidates as therapeutic immuno-oncology modalities. Bispecific Abs (BsAbs) that recognize 2 different antigens in one molecule are promising drug candidates and have inspired an upsurge in research in both academia and the pharmaceutical industry. Among several BsAbs, T cell engaging BsAb (TCEB), a new class of therapeutic agents designed to simultaneously bind to T cells and tumor cells via tumor cell specific antigens in immunotherapy, is the most promising BsAb. Herein, we are providing an overview of the current status of the development of TCEBs. The diverse formats and characteristics of TCEBs, in addition to the functional mechanisms of BsAbs are discussed. Several aspects of a new TCEB-Blinatumomab-are reviewed, including the current clinical data, challenges of patient treatment, drawbacks regarding toxicities, and resistance of TCEB therapy. Development of the next generation of TCEBs is also discussed in addition to the comparison of TCEB with current chimeric antigen receptor-T therapy.

• Journal of Korea Technology Innovation Society
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• v.17 no.4
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• pp.820-844
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• 2014

Various innovation theories, such as innovation system, innovation cluster, triple helix model, are different in their focus. However they all emphasize the interaction between innovation actors in order to generate, diffuse, and appropriate technological innovations successfully. This study analyzes how the interaction of innovation actors in Daedeok Innopolis has been changed since the introduction of innovation cluster policy like the designation of Daedeok Innopolis. Based on the analysis of survey data, Innopolis statistics, and patent joint-application data, we come to the conclusions that the Daedeok Innopolis has characteristics of multi-level governance structure, in which innovation cluster, i.e. Daedeok Innopolis, regional innovation system, and national innovation system directly overlap under the framework of innovation system. In addition, from the perspectives of triple helix model, we are able to verify that the inter-domain interactions between innovation actors, such as tri-lateral network, have been constantly increased in the Daedeok Innopolis. Based on our analysis, we identify some policy suggestions in order to strengthen the competitiveness of the Daedeok Innopolis as well as other innovation clusters in Korea. First, the network activities between innovation actors within innovation cluster should be strengthened based on the geographical accessibility. Second, private intermediate organizations should be established and their roles should be extended. Third, the entrepreneurial activities of universities within innovation cluster should be strengthened. In other words, the roles of universities within the Innopolis should be activated. Finally, the government should provide relevant policy supports to activate the interactions between innovation actors within innovation cluster.

• Journal of Astronomy and Space Sciences
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• v.23 no.4
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• pp.385-396
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• 2006

The International GNSS Service (IGS) has prepared for a transition from the relative phase conte. variation (PCV) to the absolute PCV, because the terrestrial scale problem of the absolute PCV was resolved by estimating the PCV of the GPS satellites. Thus, the GPS data will be processed by using the absolute PCV which will be an IGS standard model in the near future. It is necessary to compare and analyze the results between the relative PCV and the absolute PCV for the establishment of the reliable processing strategy. This research analyzes the effect caused by the absolute PCV via the GPS network data processing. First, the four IGS stations, Daejeon, Suwon, Beijing and Wuhan, are selected to make longer baselines than 1000km, and processed by using the relative PCV and the absolute PCV to examine the effect of the antenna raydome. Beijing and Wuhan stations of which the length of baselines are longer than 1000km show the average difference of 1.33cm in the vertical component, and 2.97cm when the antenna raydomes are considered. Second, the 7 permanent GPS stations among the total 9 stations, operated by Korea Astronomy and Space Science Institute, are processed by applying the relative PCV and the absolute PCV, and their results are compared and analyzed. An insignificant effect of the absolute PCV is shown in Korea regional network with the average difference of 0.12cm in the vertical component.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.19-33
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• 2020

This study aims to analyze on the changes of opinion in terms of Sejong City construction using big data. The research data are newspaper articles related to the argument of construction in Sejong City. The newspaper article data was reported by Hankyoreh, Dong-A Ilbo and Hankook Ilbo. The arguments related to the construction of Sejong City was included the new administrative capita, multifunctional administrative city and amendments of Sejong City. The analysis method used in this study is frequency analysis, sentiment analysis and social network analysis using python and gephi 0.9.2 programs. The results of the analysis are as follows. First, as a result of frequency analysis, the keywords of Hankyoreh showed the characteristics of consent - consent - dissent according to the construction period of Sejong City. The Dong-A Ilbo showed positions of dissent - dissent - consent. In addition, the Hankook Ilbo was analyzed to have the characteristics of dissent - consent - dissent tendency. Secondly, results of sentiment analysis, The Hankyoreh showed positive - positive - negative tone. The characteristic of Dong-A Ilbo is that the focus has changed from negative to negative to positive. The Hankook Ilbo showed that changed from negative to positive to negative. Finally, the results of social network analysis are as follows. At the time of the construction of Sejong City, each opinion of media was showed a changes in issues according to political and ideological characteristics such as conservative, progressive and moderation. In detail, Hankyoreh focused on balanced regional development. The Dong-A Ilbo represented the opinion of the Conservative Party. The Hankook Ilbo was highlighting the issues confronting the conservative party and progressive party during the construction of Sejong City.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.108-113
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• 2012

Routing paths are mightily important for the network security in WSNs. To maintain such routing paths, sustained path re-selection and path management are needed. Region segmentation based path selection method (RSPSM) provides a path selection method that a sensor network is divided into several subregions, so that the regional path selection and path management are available. Therefore, RSPSM can reduce energy consumption when the path re-selection process is executed. However, it is hard to guarantee optimized secure routing path at all times since the information using the path re-selection process is limited in scope. In this paper, we propose partial path selection method in each subregion using preselected partial paths made by RSPSM for routing path optimization in SEF based sensor networks. In the proposed method, the base station collects the information of the all partial paths from every subregion and then, evaluates all the candidates that can be the optimized routing path for each node using a evaluation function. After the evaluation process is done, the result is sent to each super DN using the global routing path information (GPI) message. Thus, each super DN provides the optimized secure routing paths using the GPI. We show the effectiveness of the proposed method via the simulation results. We expect that our method can be useful for the improvement of RSPSM.

• The Journal of Bigdata
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• v.4 no.1
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• pp.63-72
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• 2019

For power energy, optimal generation and distribution plans based on accurate demand forecasts are necessary because it is not recoverable after they have been delivered to users through power generation and transmission processes. Failure to predict power demand can cause various social and economic problems, such as a massive power outage in September 2011. In previous studies on forecasting power demand, ARIMA, neural network models, and other methods were developed. However, limitations such as the use of the national average ambient air temperature and the application of uniform criteria to distinguish seasonality are causing distortion of data or performance degradation of the predictive model. In order to improve the performance of the power demand prediction model, we divided Korea into five major regions, and the power demand prediction model of the linear regression model and the neural network model were developed, reflecting seasonal characteristics through regional characteristics and migration period learning techniques. With the proposed approach, it seems possible to forecast the future demand in short term as well as in long term. Also, it is possible to consider various events and exceptional cases during a certain period.