• Journal of Information Technology Services
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• v.20 no.1
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• pp.41-54
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• 2021

The SW-centered battlefield management information system R&D project takes a long period of 5-10 years or more by applying a complex and rigid batch acquisition strategy. In order to solve this problem, it is necessary to institutionalize a rapid and flexible battlefield management information system R&D project management procedure applying agile development methodology, and a government project management organization and contract management method to support it In this study, we analyzed the case of applying the Agile development method centered on Scrum to the US SW-centered weapon system R&D project and the characteristics and problems of the battlefield management information system R&D project in Korea, and suggested improvement measures as follows. First, the battlefield management information system R&D model applies the hybrid development method, and the system requirements analysis and system structure design use the existing waterfall development procedure, and the agile method is applied from the SW requirements analysis to the system integration stage. Second, flexible adjustment of performance, schedule, and cost by organizing an Agile IPT in which military (requirements) - DAPA (project management) - developer - functional specialized organizations (test and evaluation, quality, government research institutes, etc.) participate. Third, improving the Basic Order Agreement so that it can be applied to agile R&D.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.17-26
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• 2022

Sensor Nodes play a major role to monitor and sense the variations in physical space in various real-time application scenarios. These nodes are powered by limited battery resources and replacing those resource is highly tedious task along with this it increases implementation cost. Thus, maintaining a good network lifespan is amongst the utmost important challenge in this field of WSN. Currently, energy efficient routing techniques are considered as promising solution to prolong the network lifespan where multi-hop communications are performed by identifying the most energy efficient path. However, the existing scheme suffer from performance related issues. To solve the issues of existing techniques, a novel hybrid technique by merging particle swarm optimization and game theory model is presented. The PSO helps to obtain the efficient number of cluster and Cluster Head selection whereas game theory aids in finding the best optimized path from source to destination by utilizing a path selection probability approach. This probability is obtained by using conditional probability to compute payoff for agents. When compared to current strategies, the experimental study demonstrates that the proposed GTPSO strategy outperforms them.

• Journal of Information Technology Applications and Management
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• v.29 no.3
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• pp.43-55
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• 2022

In this study, with the goal of developing a deep learning-based product recommendation model for effective matching of influencers and products, a deep learning model with a collaborative filtering model combined with generalized matrix decomposition(GMF), a collaborative filtering model based on multi-layer perceptron (MLP), and neural collaborative filtering and generalized matrix Factorization (NeuMF), a hybrid model combining GMP and MLP was developed and tested. In particular, we utilize one-class problem free boosting (OCF-B) method to solve the one-class problem that occurs when training is performed only on positive cases using implicit feedback in the deep learning-based collaborative filtering recommendation model. In relation to model selection based on overall experimental results, the MLP model showed highest performance with weighted average precision, weighted average recall, and f1 score were 0.85 in the model (n=3,000, term=15). This study is meaningful in practice as it attempted to commercialize a deep learning-based recommendation system where influencer's promotion data is being accumulated, pactical personalized recommendation service is not yet commercially applied yet.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1838-1854
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• 2023

This paper presents a hybrid algorithm to solve the multi-objective path planning (MOPP) problem for mobile robots in a static nuclear accident environment. The proposed algorithm mimics a real nuclear accident site by modeling the environment with a two-layer cost grid map based on geometric modeling and Monte Carlo calculations. The proposed algorithm consists of two steps. The first step optimizes a path by the hybridization of improved ant colony optimization algorithm-modified A^* (IACO-A^*) that minimizes path length, cumulative radiation dose and energy consumption. The second module is the high radiation dose rate avoidance strategy integrated with the IACO-A^* algorithm, which will work when the mobile robots sense the lethal radiation dose rate, avoiding radioactive sources with high dose levels. Simulations have been performed under environments of different complexity to evaluate the efficiency of the proposed algorithm, and the results show that IACO-A^* has better path quality than ACO and IACO. In addition, a study comparing the proposed IACO-A^* algorithm and recent path planning (PP) methods in three scenarios has been performed. The simulation results show that the proposed IACO-A^* IACO-A^* algorithm is obviously superior in terms of stability and minimization the total cost of MOPP.

• Smart Structures and Systems
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• v.33 no.1
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• pp.65-91
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• 2024

The use of five optimization techniques for the prediction of a strength-based concrete mixture's best-fit model is examined in this work. Five optimization techniques are utilized for this purpose: Slime Mold Algorithm (SMA), Black Hole Algorithm (BHA), Multi-Verse Optimizer (MVO), Vortex Search (VS), and Whale Optimization Algorithm (WOA). MATLAB employs a hybrid learning strategy to train an artificial neural network that combines least square estimation with backpropagation. Thus, 72 samples are utilized as training datasets and 31 as testing datasets, totaling 103. The multi-layer perceptron (MLP) is used to analyze all data, and results are verified by comparison. For training datasets in the best-fit models of SMA-MLP, BHA-MLP, MVO-MLP, VS-MLP, and WOA-MLP, the statistical indices of coefficient of determination (R²) in training phase are 0.9603, 0.9679, 0.9827, 0.9841 and 0.9770, and in testing phase are 0.9567, 0.9552, 0.9594, 0.9888 and 0.9695 respectively. In addition, the best-fit structures for training for SMA, BHA, MVO, VS, and WOA (all combined with multilayer perceptron, MLP) are achieved when the term population size was modified to 450, 500, 250, 150, and 500, respectively. Among all the suggested options, VS could offer a stronger prediction network for training MLP.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.55-79
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• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.4
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• pp.458-465
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• 2010

To investigate the growth and nutrient uptake response of sorghum${\times}$sudangrass ($S{\times}S$) hybrid to different rate of livestock manure compost, a field experiment was conducted in the experimental grassland of Chonnam National University. Six treatments were laid out in a randomized block design with triplicates; control (no input), synthetic fertilizer (20 g N $m^{-2}$ and 20 g $P_2O_5\;m^{-2}$), compost 1 (3.4 g N $m^{-2}$ and 3.6 g $P_2O_5\;m^{-2}$), compost 2 (6.8 g N $m^{-2}$ and 7.2 g $P_2O_5\;m^{-2}$), compost 4 (13.4 g N $m^{-2}$ and 14.4 g $P_2O_5\;m^{-2}$), and compost 6 (20.2 g N $m^{-2}$ and 21.6 g $P_2O_5\;m^{-2}$). Ninety days after treatment, above-ground parts of the plants were harvested and measured for dry matter yield (DMY) and amounts of nutrients (N and P) uptake. Synthetic fertilizer application achieved the greatest DMY (2.4 kg $m^{-2}$) and nutrient uptake (38.3 g N $m^{-2}$ and 15.3 g $P_2O_5\;m^{-2}$). Increasing compost application rate tended to enhance DMY accumulation and nutrient uptake (P<0.01), but DMYs of compost 4 (1.9 kg $m^{-2}$) and 6 (1.8 kg $m^{-2}$) treatments were not different. Therefore, it was suggested that application compost alone may not achieve DMY of $S{\times}S$ hybrid compatible to synthetic fertilizer application. As nutrient uptake efficiency data showed that availability of compost P could be better than SF, it might be a strategy to apply compost as P source with supplementary N application such as liquid manure, SF or green manure if necessary considering availability of N input and the yield goals.

• Journal of Life Science
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• v.25 no.8
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• pp.925-931
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• 2015

We performed a molecular marker-based analysis of quantitative trait loci (QTLs) for traits that determine the quality of the appearance of grains, using 120 doubled-haploid (DH) lines developed by another culture from the F1 cross between ‘Cheongcheong’ (Oryza sativa L. ssp. Indica) and ‘Nagdong’ (Oryza sativa L. ssp. Japonica). The traits studied included length, width, and thickness of the grains, as well as length-to-width ratio and 1,000-grain weight. The objective of this study was to determine the genetic control of these traits in order to formulate a strategy for improving the appearance of this hybrid. Within the DH population, five traits exhibited wide variation, with mean values occurring within the range of the two parents. Three QTLs were identified for grain length on chromosomes 2, 5, and 7. Three QTLs were mapped for grain width on chromosome 2: qGW2-1, qGW2-2, and qGW2-3. Six chromosomes were identified for the grain length-to-width ratio; four of these were on chromosome 2, whereas the other two were on chromosomes 7 and 12. One QTL influencing 1,000-grain weight was identified and located on chromosome 8. The results presented in the present study should facilitate rice-breeding, especially for improved hybrid-rice quality.

• Journal of Korean Academy of Nursing
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• v.30 no.5
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• pp.1279-1291
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• 2000

The main objectives of this study were to analyze the concept of hope, so to provide basic data to develop a valid instrument to measure hope, and to develop hope enhancing nursing intervention a program for cancer patients. The hybrid model approach was applied in three phases, the theoretical phase, the empirical phase, and the analytic phase. The study was developed on universal attributes explaining generalized hope and specific hope, which were revealed in a comprehensive review of the literature. In the empirical phase, eight cancer patients undergoing chemotherapy were interviewed to reveal causes, motivation, and their resource of hope according to The Hope Assessment Guide (Farren, Herth, & Popovich, 1995). In the analytical phase, the results of the two previous stages of the study were compared. The results were as follows : In the theoretical phase, six dimensions of hope emerged; affective, cognitive, behavioral, affiliative, temporal and contextual dimension. The antecedent of hope was loss, crisis, uncertainity, and stress. The consequences were renewal, development of new methods, safety, peace and transcendental competence. In the empirical phase, these six dimensions emerged as theoretical phases were verified and specified as these descriptive terms: feeling, intention, expectation, activity, relation, future- orientation, reality and goal-setting. The antecedent factor of hope was occurrence or recurrence of cancer. The consequence of hope was ability to cope with real condition, feeling of safety and comfort, peace, development of new strategy and recovery of disease. The major content of hope in this phase was related to specific hope, but it was also influenced on by general hope. In the analytic phase, general and specific hope was renamed as trait and state hope. All attributes emerged at the empirical phases, and also emerged at the theoretical phase. However, cognitive and contextual dimensions were revised and specified. In conclusion, the concept of hope is divided into trait hope and state hope, and state hope is an anticipatory expectation that occurs at the time of a stressful stimulus, such as being diagnosed with cancer. Hope is a multidimensional dynamic energized mental state which has the dimensions of affective, cognitive, behavioral, affiliative, temporal and contextual. There should be further studies to develope the state and trait hope scale according to definition and attributes of hope investigated in this study. In addition, considering results of the empirical phase, the family is very a important factor as a resource of hope, so it is necessary to consider family in implementing a nursing intervention program to enhance hope.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.1
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• pp.99-113
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• 2004

A new architecture called SAN(Storage Area Network) was developed in response to the requirements of high availability of data, scalable growth, and system performance. In order to use SAN more efficiently, most of SAN operating softwares support storage virtualization concepts that allow users to view physical storage devices attached to SAN as a large volume virtually h logical volume manager plays a key role in storage virtualization. It realizes the storage virtualization by mapping logical addresses to physical addresses. A logical volume manager also supports a snapshot that preserves a volume image at certain time and on-line reorganization to allow users to add/remove storage devices to/from SAN even while the system is running. To support the snapshot and the on-line reorganization, most logical volume managers have used table based mapping methods. However, it is very difficult to manage mapping table because the mapping table is large in proportion to a storage capacity. In this paper, we design and implement an efficient and flexible hybrid mapping method based on mathematical equations. The mapping method in this paper supports a snapshot and on-line reorganization. The proposed snapshot and on-line reorganization are performed on the reserved area which is separated from data area of a volume. Due to this strategy normal I/O operations are not affected by snapshot and reorganization. Finally, we show the superiority of our proposed mapping method through various experiments.