• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.3
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• pp.101-108
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• 2007

We follow the promising recent results of deploying the public key cryptography in sensor networks. Recent results have shown that the public key algorithms are computationally feasible on the typical sensor nodes. However, once the public key cryptography is brought to the sensor network, security services such like key authentication will be critically required. In this paper we investigate the public key authentication problem in the sensor network and provide several authentication protocols. Our protocols are mainly based on the non-solvable overhearing in the wireless environment and a distributed voting mechanism. To show the value of our protocols, we provide an extensive analysis of the used resources and the resulting security level. As well, we compare our work with other existing works. For further benefit of our protocols, we list several additional applications in the sensor network where our protocols provide a sufficient authentication under the constrained resources.

• Journal of Biomedical Engineering Research
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• v.42 no.6
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• pp.268-276
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• 2021

Functional near-infrared spectroscopy-based brain-computer interface (fNIRS-based BCI) has been receiving much attention. However, we are practically constrained to obtain a lot of fNIRS data by inherent hemodynamic delay. For this reason, when employing machine learning techniques, a problem due to the high-dimensional feature vector may be encountered, such as deteriorated classification accuracy. In this study, we employ an elastic net-based feature selection which is one of the embedded methods and demonstrate the utility of which by analyzing the results. Using the fNIRS dataset obtained from 18 participants for classifying brain activation induced by mental arithmetic and idle state, we calculated classification accuracies after performing feature selection while changing the parameter α (weight of lasso vs. ridge regularization). Grand averages of classification accuracy are 80.0 ± 9.4%, 79.3 ± 9.6%, 79.0 ± 9.2%, 79.7 ± 10.1%, 77.6 ± 10.3%, 79.2 ± 8.9%, and 80.0 ± 7.8% for the various values of α = 0.001, 0.005, 0.01, 0.05, 0.1, 0.2, and 0.5, respectively, and are not statistically different from the grand average of classification accuracy estimated with all features (80.1 ± 9.5%). As a result, no difference in classification accuracy is revealed for all considered parameter α values. Especially for α = 0.5, we are able to achieve the statistically same level of classification accuracy with even 16.4% features of the total features. Since elastic net-based feature selection can be easily applied to other cases without complicated initialization and parameter fine-tuning, we can be looking forward to seeing that the elastic-based feature selection can be actively applied to fNIRS data.

• Journal of Aerospace System Engineering
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• v.16 no.3
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• pp.63-72
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• 2022

The purpose of this paper was to understand the dynamics of deployment of large mesh antennas, and to provide a numerical method for determining the dynamic stiffness and the driving forces for the design. The deployment structure was numerically modeled using the frame elements. The eigenvalue analysis was demonstrated, with respect to the folded and unfolded configurations of the antenna. A multibody dynamic model was formulated with Kane's equation, and simulated using the pseudo upper triangular decomposition (PUTD) method for resolving the constrained problem. Based on the multibody model, the kinetics of the deployment, the motor driving forces, and the feasibility of the designed deployment structure were investigated.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.10
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• pp.691-699
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• 2022

Large aperture antennas with long focal lengths in space have important application for telecommunications, Earth observation and science missions. This paper aims to understand the dynamics of deployment of large mesh antennas and to provide a multibody model for determining the driving forces for the design of reflectors and booms. The modular deployable reflector and boom are designed based on the deployment unit cell. A multibody dynamic model is formulated with Kane's equation and simulated using the pseudo upper triangular decomposition (PUTD) method for solving the constrained problem. Based on the multibody dynamic model, the kinetics of the deployment, the motor driving forces, and the structural dynamic deformation are investigated.

• Journal of Korean Society of Steel Construction
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• v.10 no.3 s.36
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• pp.553-564
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• 1998

Recently, more and more steel-deck structural system for two story roads has been adopted as a solution against traffic congestion in urban area, mainly because of fast construction, reduced self-weight, higher stiffness and efficient erection compared to that of concrete decks. The main objective is to study on the unit-elective optimal type and proportioning of a rational steel-deck system for two story roads using an optimum design program specifically developed for steel-deck systems. The objective function for the optimization is formulated as a minimum cost design problem. The behavior and design constraints are formulated based on the ASD(Allowable Stress Design) criteria of the Korean Bridge Design Code. The optimum design program developed in this study consists of two steps - the first step for the optimization of the steel box or plate girder viaducts, and the second step for the optimum design of the steel-decks with closed or open ribs. A grid model is used as a structural analysis model for the optimization of the main girder system, while the analysis of the deck system is based on the Pelican-Esslinger method. The SQP(Sequential Quadratic Programming) is used as the optimization technique for the constrained optimization problem. By using a set of application examples, the rational type related to the optimized steel-deck system designs is investigated by comparing the cost effectiveness of each type. Based on the results of the investigation it may be concluded that the optimal linear box girder and deck system with closed ribs may be utilized as one of the most rational and economical viaducts in the construction of two-story roads.

• Journal of Advanced Navigation Technology
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• v.4 no.2
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• pp.114-131
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• 2000

An airline should consider the number of seats or size of aircraft, when it composes fleet or selects a type of aircraft for some routes. There are two major factors considered for this choice problem under the assumption that the objectives of an airline is a profit maximization: the operating cost and revenue from the aircraft operated. This research tries to solve the problem of aircraft size selection by airline. The study applies four steps to get optimal choice of aircraft size: (1) cost analysis for the relationship between airline operation cost and aircraft size: (2) market share and revenue analysis: (3) flight segment-level analysis, based on the derived cost, demand and revenue functions: and (4) network-level analysis to see how airlines make choice of aircraft size systematically at a network level. An airline can accommodate the increasing air travel demand by either increasing operation frequency, or increasing aircraft size that is represented by seat capacity, or both. Airport runway capacity and productivity depend on the size of aircraft used at airport. This paper presents the understanding of how airlines make decisions on the size of aircraft to operate, how they will adjust their choices when airport capacity is constrained, and how public regulation such as policy for landing fees could influence airlines' aircraft choice.

• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.463-472
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• 2009

Real-time operating systems must have satisfying various conditions such as effective scheduling policies, minimized interrupt delay, resolved priority inversion problems, and its applications to be completed within desired deadline. The real-time operating systems, therefore, should be designed and developed to be optimal for these requirements. MicroC/OS-II, a kind of Real-time operating systems, uses the basic priority inheritance with a mutex to solve priority inversion problems. For the implementation of mutex, the kernel in an operating system should provide supports for numerous tasks with same priority. However, MicroC/OS-II does not provide this support for the numerous tasks of same priority. To solve this problem, MicroC/OS-II cannot but using priority reservation, which leads to the waste of unnecessary resources. In this study, we have dealt with new design a protocol, so called TPSP(Temporary Priority Swap Protocol), by an effective solution for above-mentioned problem, eventually enabling embedded systems with constrained resources environments to run applications.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.475-484
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• 2021

The optimal design for water distribution system (WDS) is not only satisfying the minimum required water pressure of the nodes, but also minimizing pipe cost, etc. The number of designs of WDS increases exponentially due to the arrangement of various pipes. Various optimization algorithms were applied to propose an optimized design of WDS. In this study, Modified Hybrid Vision Correction Algorithm (MHVCA) with improved self-adapting parameter was applied to optimal design of WDS. The performance was improved by changing the Hybrid Rate (HR) of the existing Hybrid Vision Correction Algorithm (HVCA) to nonlinear HR. To verify the performance of the proposed MHVCA, it applied to mathematical problems consisting of 2 and 30 decision variables and constrained mathematical problems. In order to review the application results of MHVCA, it was compared with Harmony Search (HS), Improved Harmony Search (IHS), Vision Correction Algorithm (VCA) and HVCA. Finally, MHVCA was applied to the optimal design problem of WDS and the results were compared with other algorithms. MHVCA showed better results than other algorithms in mathematical problems and WDS problem. MHVCA will be able to show good results by applying to various water resource engineering problems as well as problems applied in this study.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.81-90
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• 2021

There are various optimization problems in real world and research continues to solve them. An optimization problem is the problem of finding a combination of parameters that maximizes or minimizes the objective function. Harmony search is a population-based metaheuristic algorithm for solving optimization problems and it is designed to mimic the improvisation of jazz music. Harmony search has been actively applied to optimization problems in various fields such as civil engineering, computer science, energy, medical science, and water quality engineering. Harmony search has a simple working principle and it has the advantage of finding good solutions quickly in constrained optimization problems. Especially there are various application cases showing high accuracy with a low number of iterations by improving the solution through the empirical derivative. In this paper, we explain working principle of Harmony search and classify the leading research in recent 3 years, review them according to category, and suggest future research directions. The research is divided into review by field, algorithmic analysis and theory, and application to real world problems. Application to real world problems is classified according to the purpose of optimization and whether or not they are hybridized with other metaheuristic algorithms.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.159-185
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• 2016

Planning a multi-day trip is a complex, yet time-consuming task. It usually starts with selecting a list of points of interest (POIs) worth visiting and then arranging them into an itinerary, taking into consideration various constraints and preferences. When choosing POIs to visit, one might ask friends to suggest them, search for information on the Web, or seek advice from travel agents; however, those options have their limitations. First, the knowledge of friends is limited to the places they have visited. Second, the tourism information on the internet may be vast, but at the same time, might cause one to invest a lot of time reading and filtering the information. Lastly, travel agents might be biased towards providers of certain travel products when suggesting itineraries. In recent years, many researchers have tried to deal with the huge amount of tourism information available on the internet. They explored the wisdom of the crowd through overwhelming images shared by people on social media sites. Furthermore, trip planning problems are usually formulated as 'Tourist Trip Design Problems', and are solved using various search algorithms with heuristics. Various recommendation systems with various techniques have been set up to cope with the overwhelming tourism information available on the internet. Prediction models of recommendation systems are typically built using a large dataset. However, sometimes such a dataset is not always available. For other models, especially those that require input from people, human computation has emerged as a powerful and inexpensive approach. This study proposes CYTRIP (Crowdsource Your TRIP), a multi-day trip itinerary planning system that draws on the collective intelligence of contributors in recommending POIs. In order to enable the crowd to collaboratively recommend POIs to users, CYTRIP provides a shared workspace. In the shared workspace, the crowd can recommend as many POIs to as many requesters as they can, and they can also vote on the POIs recommended by other people when they find them interesting. In CYTRIP, anyone can make a contribution by recommending POIs to requesters based on requesters' specified preferences. CYTRIP takes input on the recommended POIs to build a multi-day trip itinerary taking into account the user's preferences, the various time constraints, and the locations. The input then becomes a multi-day trip planning problem that is formulated in Planning Domain Definition Language 3 (PDDL3). A sequence of actions formulated in a domain file is used to achieve the goals in the planning problem, which are the recommended POIs to be visited. The multi-day trip planning problem is a highly constrained problem. Sometimes, it is not feasible to visit all the recommended POIs with the limited resources available, such as the time the user can spend. In order to cope with an unachievable goal that can result in no solution for the other goals, CYTRIP selects a set of feasible POIs prior to the planning process. The planning problem is created for the selected POIs and fed into the planner. The solution returned by the planner is then parsed into a multi-day trip itinerary and displayed to the user on a map. The proposed system is implemented as a web-based application built using PHP on a CodeIgniter Web Framework. In order to evaluate the proposed system, an online experiment was conducted. From the online experiment, results show that with the help of the contributors, CYTRIP can plan and generate a multi-day trip itinerary that is tailored to the users' preferences and bound by their constraints, such as location or time constraints. The contributors also find that CYTRIP is a useful tool for collecting POIs from the crowd and planning a multi-day trip.