In this study, we introduce a novel TiN/Ag embedded TiO2/FTO resistive random-access memory (RRAM) device. This distinctive device was fabricated using an environmentally sustainable, solution-based thin film manufacturing process. Utilizing the peroxo titanium complex (PTC) method, we successfully incorporated Ag precursors into the device architecture, markedly enhancing its performance. This innovative approach effectively mitigates the random filament formation typically observed in RRAM devices, and leverages the seed effect to guide filament growth. As a result, the device demonstrates switching behavior at substantially reduced voltage and current levels, heralding a new era of low-power RRAM operation. The changes occurring within the insulator depending on Ag contents were confirmed by X-ray photoelectron spectroscopy (XPS) analysis. Additionally, we confirmed the correlation between Ag and oxygen vacancies (Vo). The current-voltage (I-V ) curves obtained suggest that as the Ag content increases there is a change in the operating mechanism, from the space charge limited conduction (SCLC) model to ionic conduction mechanism. We propose a new filament model based on changes in filament configuration and the change in conduction mechanisms. Further, we propose a novel filament model that encapsulates this shift in conduction behavior. This model illustrates how introducing Ag alters the filament configuration within the device, leading to a more efficient and controlled resistive switching process.

Henricia specimens were collected using a dual approach of trimix scuba diving and fishing nets. This inclusive collection encompasses the discovery of two species highlighted in this study and introduces and provides comprehensive descriptions for Henricia kinkasana and Henricia longispina aleutica. The descriptions offered in this study were derived from the thorough examinations of external morphological characteristics. The documentation provides detailed insight into key traits related to the abactinal and actinal skeletons and spines of these newly recorded species in Korea. This comprehensive examination contributes to our understanding of the distinct morphological characteristics defining each species within the genus Henricia.

As technologies have been more quickly developed in this 4th Industry Revolution era, their application to defense industry has been also growing. With these much advanced technologies, we attempt to use Manned-Unmanned Teaming systems in various military operations. In this study, we consider the Location-Routing Problem for reconnaissance surveillance missions of the maritime manned-unmanned surface vehicles. As a solution technique, the two-phase method is presented. In the first location phase, the p-median problem is solved to determine which nodes are used as the seeds for the manned vehicles using Lagrangian relaxation with the subgradient method. In the second routing phase, using the results obtained from the location phase, the Vehicle Routing Problems are solved to determine the search routes of the unmanned vehicles by applying the Location Based Heuristic. For three network data sets, computational experiments are conducted to show the performance of the proposed two-phase method.

Effects-Based Operations (EBO) refers to a process for achieving strategic goals by focusing on effects rather than attrition-based destruction. For a successful implementation of EBO, identifying key nodes in an adversary network is crucial in the process of EBO. In this study, we suggest a network-based approach that combines network centrality and optimization to select the most influential nodes. First, we analyze the adversary’s network structure to identify the node influence using degree and betweenness centrality. Degree centrality refers to the extent of direct links of a node to other nodes, and betweenness centrality refers to the extent to which a node lies between the paths connecting other nodes of a network together. Based on the centrality results, we then suggest an optimization model in which we minimize the sum of the main effects of the adversary by identifying the most influential nodes under the dynamic nature of the adversary network structure. Our results show that key node identification based on our optimization model outperforms simple centrality-based node identification in terms of decreasing the entire network value. We expect that these results can provide insight not only to military field for selecting key targets, but also to other multidisciplinary areas in identifying key nodes when they are interacting to each other in a network.

Lovenia elongata is a member of the family Loveniidae and is one of the most common tropical echinoids. This species has a broad distribution range in the sub- and tropical regions of the Indo-Pacific Ocean, extending from the Mozambique to the Hawaiian Islands, and from southern Japan to northern Australia. It is commonly found in subtidal areas and on coral reefs within these regions. This species was for the first time recorded from the Ulleungdo Island, Korea. This species is characterized by a teardrop-shaped test that reaches up to 5 cm in length, with a deep groove at the front and tapered at the back end. The petaloid is not obvious, and the primary spines are long and banded. This study is the first to report the newly recorded L. elongata in Korea.

A spin coating process for RRAM, which is a TiN/TiO2/FTO structure based on a PTC sol solution, was developed in this laboratory, a method which enables low-temperature and eco-friendly manufacturing. The RRAM corresponds to an OxRAM that operates through the formation and extinction of conductive filaments. Heat treatment was selected as a method of controlling oxygen vacancy (VO), a major factor of the conductive filament. It was carried out at 100 oC under moisture removal conditions and at 300 oC and 500 oC for excellent phase stability. XRD analysis confirmed the anatase phase in the thin film increased as the heat treatment increased, and the Ti3+ and OH- groups were observed to decrease in the XPS analysis. In the I-V analysis, the device at 100 oC showed a low primary SET voltage of 5.1 V and a high ON/OFF ratio of 104. The double-logarithmic plot of the I-V curve confirmed the device at 100 oC required a low operating voltage. As a result, the 100 oC heat treatment conditions were suitable for the low voltage driving and high ON/OFF ratio of TiN/TiO2/FTO RRAM devices and these results suggest that the operating voltage and ON/OFF ratio required for OxRAM devices used in various fields under specific heat treatment conditions can be compromised.

This paper considers the Prisoner’s Dilemma Game in which there exists a dilemma that the best response is that both players are to confess, but doing not confess can give a higher gain to the both players in a social perspective. To resolve such a dilemma in the game, an incentive model to encourage to confess and a penalty model for being imposed when not confessing are introduced, respectively. Then, the conditions are characterized under which incentive or penalty involved in the game’s payoffs can make the game rational without a dilemma on both the personal and social perspectives, by taking the payoff values as variables with the incentive and penalty factors. Furthermore, it turns out that the resulting values of incentive and penalty are inversely proportional to each other, and thus, obtaining one of these amounts can provide the other. Simple examples are shown to interpret the theoretical verifications of our models, and randomly generated data based simulation results investigate the tendency of incentive and penalty and the resulting game values for a variety of instances. These results can provide a framework on resolving the dilemma by artificially putting incentive or penalty, although it is careful to apply more generalized real world games.

In this study, we proposed a model for forecasting power energy demand by investigating how outside temperature at a given time affected power consumption and. To this end, we analyzed the time series of power consumption in terms of the power spectrum and found the periodicities of one day and one week. With these periodicities, we investigated two time series of temperature and power consumption, and found, for a given hour, an approximate linear relation between temperature and power consumption. We adopted an exponential smoothing model to examine the effect of the linearity in forecasting the power demand. In particular, we adjusted the exponential smoothing model by using the variation of power consumption due to temperature change. In this way, the proposed model became a mixture of a time series model and a regression model. We demonstrated that the adjusted model outperformed the exponential smoothing model alone in terms of the mean relative percentage error and the root mean square error in the range of 3%~8% and 4kWh~27kWh, respectively. The results of this study can be used to the energy management system in terms of the effective control of the cross usage of the electric energy together with the outside temperature.

The pine wilt disease that blocks the path for water and nutrition in pine trees is caused by the nematode, Bursaphelenchus xylophilus (Nematoda: Aphelenchoididae). The nematode relies on the longhorn pine sawyer beetle Monochamus alternatus and Monochamus saltuaris (Coleoptera: Cerambycidae) as vectors. Recently, 2-(undecyloxy)ethanol was identified as a male-produced aggregation pheromone of Monochamus species. In this study, we investigated the effect of 2-(undecyloxy) ethanol along with host plant volatiles -pinene and ethanol on attracting M. alternatus at a pine forest in Pohang, Korea from May, 2014 to July, 2014. To sustain the volatility of 2-(undecyloxy)ethanol and host plant volatiles, a superabsorbent polymer based on polyacrylic acids and water were added to the pheromone mixture. A total of 46 M. alternatus were collected from two field bioassays. Our results indicate that 2-(undecyloxy)ethanol is effective in attracting M. alternatus in Korea. Our study suggests that the aggregation pheromone could be used for detection and population monitoring of the beetles as well as for the effective mass trapping in outbreak situations.

Whey is a major by-product of cheese manufacture and contains many valuable constituents, such as β-lactoglobulin, lactoferrin and immunoglobulin. The current study determined the anti-biofilm activity of bioconversion of whey by Lactobacillus plantarum (LP-W), L. rhamnosus GG (LR-W), L. brevis (LB-W) and Enterococcus faecium (EF-W) against foodborne pathogenic bacteria, Escherichia coli O157:H7 and Listeria monocytogenes. When the foodborne pathogenic bacteria were co-incubated with LP-W, LR-W, LB-W or EF-W, biofilms by E. coli O157:H7 and L. monocytogenes were significantly reduced by all bioconversion of whey. Moreover, LP-W, LR-W, LB-W and EF-W also dramatically reduced pre-formed biofilm by E. coli O157:H7 and L. monocytogenes, suggesting that the bioconversion of whey effectively suppress the development and disruption of biofilm by foodborne pathogenic bacteria. Furthermore, in order to determine the growth kinetics of E. coli O157 and L. monocytogenes planktonic cells in the presence the bioconversion of whey, LP-W, LR-W, LB-W and EF-W did not significantly inhibited the growth of foodborne pathogenic bacteria, implying that the bioconversion of whey reduces the biofilm without the decrease of bacterial growth. Taken together, these results suggest that bioconversion of whey by lactic acid bacteria could be a promising agent for the reduction of microbial biofilm.

Although renewable power is regarded a way to active response to climate change, the stability of whole power system could be a serious problem in the future due to its uncertainties such as indispatchableness and intermittency. From this perspective, the peak time impact of stochastic wind power generation is estimated using simulation method up to year 2030 based on the 3rd master plan for the promotion of new and renewable energy on peak time. Result shows that the highest probability of wind power impact on peak time power supply could be up to 4.41% in 2030. The impact of wind power generation on overall power mix is also analyzed up to 2030 using SCM model. The impact seems smaller than expectation, however, the estimated investment cost to make up such lack of power generation in terms of LNG power generation facilities is shown to be a significant burden to existing power companies.