• The Journal of the Convergence on Culture Technology
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• v.6 no.3
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• pp.105-109
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• 2020

The Future Army in 2050 should prepare for various future threats and effectively utilize its superintelligence and hyper-connected weapons systems to develop ways of fighting new concepts to dominate multi-regional battlefields and achieve victory. First, the establishment of active and offensive military strategies based on ability. Second, the battle of central strike for enemy combat will paralysis. Third, the battle of simultaneous integrated mosaic using multidisciplinary areas. Fourth, cyber warfare based on artificial intelligence that transcends time and space. Fifth, Combined Platform War. After all, future wars will be won or lost by invisible wars on cyber space.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.503-508
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• 1992

A new method for making automatic electroencephalogram(EEG) report based on the automatic quantitative interpretation of awake EEG was developed. We first analysed a. relationship between EEG reports and quantitative EEG interpretation done by a qualified electroencephalographer(EEGer) for 22 subjects. Based on the analysed relationship and usual process of report making by the EEGer, we defined all terminology necessary for EEG report and established rules for EEG report making. By the combined use of the proposed EEG report making and the method for automatic quantitative EEG interpretation presented at '90 KACC, we were able to make the automatic EEG reports which were equivalent to the EEG reports written by the EEGer. As all the procedures were programmed in a personal computer equipped with an AD (analogue-to-digital) converter, the automatic EEG reports were obtained in almost real time in usual actual EEG recording situation with only a few seconds time lag for the analysis in the computer. The proposed report making method and the quantitative EEG interpretation method will be effectively applicable to the clinical use as an assistant tool for physicians.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.45-48
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• 1999

Model predictive control algorithm requires a relevant model of the system to be controlled. Unfortunately, the first principle model describing a polymerization reaction system has a large number of parameters to be estimated. Thus there is a need for the identification and control of a polymerization reactor system by using available input-output data. In this work, the polynomial auto-regressive moving average (ARMA) models are employed as the input-output model and combined into the nonlinear model predictive control algorithm based on the successive linearization method. Simulations are conducted to identify the continuous styrene polymerization reactor system. The input variables are the jacket inlet temperature and the feed flow rate whereas the output variables are the monomer conversion and the weight-average molecular weight. The polynomial ARMA models obtained by the system identification are used to control the monomer conversion and the weight-average molecular weight in a continuous styrene polymerization reactor It is demonstrated that the nonlinear model predictive controller based on the polynomial ARMA model tracks the step changes in the setpoint satisfactorily. In conclusion, the polynomial ARMA model is proven effective in controlling the continuous styrene polymerization reactor.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.57-60
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• 1999

An optimal control technique designed for simultaneous tracking and quality control for batch processes. The proposed technique is designed by transforming quadratic-criterion based iterative learning control(Q-ILC) into linear quadratic control problem. For real-time quality inferential control, the quality is modeled by linear combination of control input around target qualify and then the relationship between quality and control input can be transformed into time-varying linear state space model. With this state space model, the real-time quality inferential control can be incorporated to LQ control Problem. As a consequence, both the quality variable as well as other controlled variables can progressively reduce their control error as the batch number increases while rejecting real-time disturbances, and finally reach the best achievable states dictated by a quadratic criterion even in case that there is significant model error Also the computational burden is much reduced since the most computation is calculated in off-line. The Proposed control technique is applied to a semi-batch reactor model where series-parallelreactions take place.

• Animal cells and systems
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• v.8 no.1
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• pp.49-55
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• 2004

In vertebrates, multisubunit cofactors regulate gene expression through interacting with cell-type- and gene-specific DNA-binding proteins in a chromatin-selective manner. ADD1/SREBP1c regulates fatty acid metabolism and insulin-dependent gene expression through binding to SRE and E-box motif with dual DNA binding specificity. Although its transcriptional and post-translational regulation has been extensively studied, its regulation by interacting proteins is not well understood. To identify cellular proteins that associate with nuclear form of ADD1/SEBP1c, we employed the GST pull-down system with Hela cell nuclei extract. In this study, we demonstrated that Ku proteins interact specifically with ADD1/SREP1c protein. GST pull-down combined with peptide sequencing analysis revealed that Ku80 binds to ADD1/SREBP1c in vitro. Additionally, western blot analysis showed that Ku70, a heterodimerizing partner of Ku80, also associates with ADD1/SREBP1c. Furthermore, co-transfection of Ku70/Ku80 with ADD1/SREBP1c enhanced the transcriptional activity of ADD1/SREBP1c. Taken together, these results suggest that the Ku proteins might be involved in the lipogenic and/or adipogenic gene expression through interacting with ADD1/SREBP1c.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.159-168
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• 2011

As e-commerce and social media service evolves, studies on recommender systems advance, especially concerning the application of collective intelligence to personalized custom service. With the development of smartphones and mobile environment, studies on customized service are accelerated despite physical limitations of mobile devices. A typical example is combined with location-based services. In this study, we propose a recommender system using movie genre similarity and preferred genres. A profile of movie genre similarity is generated and designed to provide related service in mobile experimental environment before prototyping and testing with data from MovieLens.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.327-334
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• 2017

Common-cause failure (CCF) events can significantly impact the availability of safety systems of nuclear power plants. For this reason, the International Common Cause Data Exchange (ICDE) project was initiated by several countries in 1994. Since 1997 it has been operated within the Organisation for Economic Co-operation and Development (OECD)/Nuclear Energy Agency (NEA) framework and has successfully been operated over six consecutive terms (the current term being 2015-2017). The ICDE project allows multiple countries to collaborate and exchange CCF data to enhance the quality of risk analyses, which include CCF modeling. As CCF events are typically rare, most countries do not experience enough CCF events to perform meaningful analyses. Data combined from several countries, however, have yielded sufficient data for more rigorous analyses. The ICDE project has meanwhile published 11 reports on the collection and analysis of CCF events of specific component types (centrifugal pumps, emergency diesel generators, motor operated valves, safety and relief valves, check valves, circuit breakers, level measurement, control rod drive assemblies, and heat exchangers) and two topical reports. This paper presents recent activities and lessons learnt from the data collection and the results of topical analysis on emergency diesel generator CCF impacting entire exposed population.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2251-2270
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• 2015

More than 1 billion mobile apps (smartphone applications) have been released worldwide. Competition among developers of apps that are available in app stores has intensified because of increasing demand. App icons with an appealing design can instantly increase attention. Miryoku Engineering methods were used and combined with the Kansei interface model to examine the relationship between attractive icons and users. The evaluation grid method (EGM) is a qualitative method that was used to evaluate the icons, and Quantification Theory Type I is a quantitative method that was used to analyze the influence of design elements in icons. Eight attractive factors of app icons were determined using EGM, and six specific factors were identified using questionnaires. The quantitative results indicated that user cognition and emotion were influenced by the various design elements. The impact on the attractive factors of a single design element differed among users with diverse backgrounds. App icons were assessed on the basis of aesthetics to identify attractive factors and thereby assist designers in understanding and implementing design elements and improving the overall visual appeal of their apps. The result of this investigation is crucial to the presentation of app icons in online app stores.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1111-1130
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• 2016

Cooperative communications can significantly improve the wireless transmission performance with the help of relay nodes. In cooperative communication networks, relay selection and power allocation are two key issues. In this paper, we propose a relay selection and power allocation scheme RS-PA-PSACO (Relay Selection-Power Allocation-Particle Swarm Ant Colony Optimization) based on PSACO (Particle Swarm Ant Colony Optimization) algorithm. This scheme can effectively reduce the computational complexity and select the optimal relay nodes. As one of the swarm intelligence algorithms, PSACO which combined both PSO (Particle Swarm Optimization) and ACO (Ant Colony Optimization) algorithms is effective to solve non-linear optimization problems through a fast global search at a low cost. The proposed RS-PA-PSACO algorithm can simultaneously obtain the optimal solutions of relay selection and power allocation to minimize the SER (Symbol Error Rate) with a fixed total power constraint both in AF (Amplify and Forward) and DF (Decode and Forward) modes. Simulation results show that the proposed scheme improves the system performance significantly both in reliability and power efficiency at a low complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1264-1286
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• 2018

In this paper, a novel background prior-based salient object detection framework is proposed to deal with images those are more complicated. We take the superpixels located in four borders into consideration and exploit a mechanism based on image boundary information to remove the foreground noises, which are used to form the background prior. Afterward, an initial foreground prior is obtained by selecting superpixels that are the most dissimilar to the background prior. To determine the regions of foreground and background based on the prior of them, a threshold is needed in this process. According to a fixed threshold, the remaining superpixels are iteratively assigned based on their proximity to the foreground or background prior. As the threshold changes, different foreground priors generate multiple different partitions that are assigned a likelihood of being foreground. Last, all segments are combined into a saliency map based on the idea of similarity voting. Experiments on five benchmark databases demonstrate the proposed method performs well when it compares with the state-of-the-art methods in terms of accuracy and robustness.