• BMB Reports
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• v.54 no.10
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• pp.497-504
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• 2021

EGR1 (early growth response 1) is dysregulated in many cancers and exhibits both tumor suppressor and promoter activities, making it an appealing target for cancer therapy. Here, we used a systematic multi-omics analysis to review the expression of EGR1 and its role in regulating clinical outcomes in breast cancer (BC). EGR1 expression, its promoter methylation, and protein expression pattern were assessed using various publicly available tools. COSMIC-based somatic mutations and cBioPortal-based copy number alterations were analyzed, and the prognostic roles of EGR1 in BC were determined using Prognoscan and Kaplan-Meier Plotter. We also used bc-GenEx-Miner to investigate the EGR1 co-expression profile. EGR1 was more often downregulated in BC tissues than in normal breast tissue, and its knockdown was positively correlated with poor survival. Low EGR1 expression levels were also associated with increased risk of ER+, PR+, and HER2- BCs. High positive correlations were observed among EGR1, DUSP1, FOS, FOSB, CYR61, and JUN mRNA expression in BC tissue. This systematic review suggested that EGR1 expression may serve as a prognostic marker for BC patients and that clinicopathological parameters influence its prognostic utility. In addition to EGR1, DUSP1, FOS, FOSB, CYR61, and JUN can jointly be considered prognostic indicators for BC.

• Transactions of the Korean hydrogen and new energy society
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• v.33 no.5
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• pp.470-498
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• 2022

Recently, the world has been considering hydrogen energy as the primary energy transition means to achieve carbon neutrality by 2050. In order to achieve the goal of reducing greenhouse gas emissions, Korea is also promoting a clean hydrogen economy. However, it is necessary to introduce various clean hydrogen from overseas so that the projected demand can not meet the domestically produced. For this study, we conducted the policy comparison approach between countries other than the generally considered technical and economic approaches. The finding proposes the direction of bilateral cooperation for a strategy of securing overseas clean hydrogen from a geopolitical perspective. Germany was a target country for the policy comparison since it has a high proportion of manufacturing, like Korea, and is taking the lead in the renewable-based energy transition policy. According to the survey and analysis of the policy establishment status and new projects of the two countries, Germany is promoting bilateral international cooperation in the hydrogen area with about 33 countries based on 7 types of activities. In comparison, Korea is involved in bilateral cooperation with about 12 countries on relatively few activities. Among the types of bilateral cooperation, R&D cooperation with advanced countries for hydrogen technology was a common activity type. Germany preemptively promotes cooperation for demonstration and commercialization, considering geopolitical means and strengthening manpower training and assistance on policy and regulation to preoccupy the market for the future. Therefore, it is necessary to consider establishing a network of an entire life cycle of supply and demand network that links the future market with securing clean hydrogen considering the geopolitical distribution. To this end, Korea also needs to expand bilateral cooperation countries by activity type, and it seems necessary to seek various geopolitical-based bilateral cooperation and support measures for developing countries to diversify the supply sources of hydrogen.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.9-23
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• 2020

Microsoft's Windows system is widely used as an operating system for the desktops and enterprise servers of companies or organizations, and is a major target of cyber attacks. Microsoft provides various protection technologies and strives for defending the attacks through periodic security patches, however the threats such as DLL injection and process injection still exist. In this paper, we analyze 12 types of injection techniques in Microsoft Windows, and perform injection attack experiments on four application programs. Through the results of the experiments, we identify the risk of injection techniques, and verify the effectiveness of the mitigation technology for defending injection attacks provided by Microsoft. As a result of the experiments, we have found that the current applications are vulnerable to several injection techniques. Finally, we have presented the mitigation techniques for these injection attacks and analyzed their effectiveness.

• KNOM Review
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• v.24 no.2
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• pp.24-34
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• 2021

Service providers using edge computing provide a high level of service. As a result, devices store important information in inner storage and have become a target of the latest cyberattacks, which are more difficult to detect. Although experts use a security system such as intrusion detection systems, the existing intrusion systems have low detection accuracy. Therefore, in this paper, we proposed a machine learning model for more accurate intrusion detections of devices in edge computing. The proposed model is a hybrid model that combines a stacked sparse autoencoder (SSAE) and a convolutional neural network (CNN) to extract important feature vectors from the input data using sparsity constraints. To find the optimal model, we compared and analyzed the performance as adjusting the sparsity coefficient of SSAE. As a result, the model showed the highest accuracy as a 96.9% using the sparsity constraints. Therefore, the model showed the highest performance when model trains only important features.

• Journal of the Korea Society of Computer and Information
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• v.14 no.6
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• pp.51-57
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• 2009

Wireless sensor networks consist of numerous sensor nodes that have inexpensive and limited resources. Generally, most of the sensors are assigned to the hazardous or uncontrollable environments. If the sensor nodes are randomly assigned to the wide target area, it is very hard to see the accurate locations of sensor nodes. Therefore, this study provides an efficient key distribution scheme to solve these problems. Based on the provided scheme, the study enabled the closely neighboring nodes to exchange information with each other after securing safe links by using the pre-distributed keys. At the same time, the provided scheme could increase the probability of multiparty key detection among nodes by using the location information of sensor node. Lastly, the study intended to show the superiority of the limitation method through a performance test.

• Korean Journal of Environmental Agriculture
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• v.41 no.1
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• pp.32-40
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• 2022

BACKGROUND: Climate-smart agriculture (CSA) has been proposed for sustainable agriculture and food security in an agricultural ecosystem disturbed by climate change. However, scientific approaches to local agricultural ecosystems to realize CSA are rare. This study attempted to evaluate the weather condition, rice production, and greenhouse gas emissions from the rice cultivation in Hwaseong-si, Gyeonggi-do to fulfill CSA of the rice cultivation. METHODS AND RESULTS: Over the past 3 years (2017~2019), Chucheong rice cultivar yield and methane emissions were analyzed from the rice field plot (37°13'15"N, 127° 02'22"E) in the Gyeonggi-do Agricultural Research and Extension Services located in Gisan-dong, Hwaseong-si, Gyeonggi-do. Methane samples were collected from three automated closed chambers installed in the plot. The weather data measured through automatic weather station located in near the plot were analyzed. CONCLUSION(S): The rice productivity was found to vary with weather environment in the agricultural ecosystem. And methane emissions are high in a favorable weather condition for rice growth. Therefore, it is necessary to minimize the trade-off between the greenhouse gas emission target for climate change mitigation and productivity improvement for CSA in a local rice cultivation.

• International Journal of High-Rise Buildings
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• v.12 no.2
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• pp.179-193
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• 2023

It is undeniable that urban greenspace is the soul of a city. Conventional urban greenspace such as parks, community gardens, playgrounds etc. located within a city reduce the negative effects of pollution, play a major role in the survival of the urban ecosystem, and promote healthy lifestyles. Today, 55% of the world's population lives in urban areas, which is expected to increase to 68% by 2050. Projections show that urbanization and the gradual migration to urban areas combined with the fast growth of the world's population, could add another 2.5 billion people to urban areas by 2050 and almost 90% of this increase will take place in Asia(UN, 2018). As a result, many plots in the cities are and will continue to be occupied with buildings to provide residential support to the increased population. This will dangerously decrease urban greenspaces. Moreover, worldwide, food crisis, energy crisis, and social crisis is posing a great threat to the existence of mankind. Additionally, the COVID - 19 has introduced a new lifestyle where from work culture to community configuration has drastically transformed. In this scenario, residential buildings will have to serve more than just providing privacy and shelter. As urban greenspaces are being occupied by concrete residential buildings, these buildings will have to compensate for the percentage of urban green they are destroying and the issues they are imposing in the process. The goal of this thesis is to design, architecturally define and, categorize comprehensive 'sustainable Greenspace'(S.G.S) for the multi-family housing scenario. These will be different than the conventional green (veranda, rooftop green) we commonly see in residential buildings. An old, dilapidated apartment building will be the target of remodeling to fulfill the purpose of this thesis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1706-1727
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• 2023

Under Water Sensor Networks (UWSN) has gained attraction among various communities for its potential applications like acoustic monitoring, 3D mapping, tsunami detection, oil spill monitoring, and target tracking. Unlike terrestrial sensor networks, it performs an acoustic mode of communication to carry out collaborative tasks. Typically, surface sink nodes are deployed for aggregating acoustic phenomena collected from the underwater sensors through the multi-hop path. In this context, UWSN is constrained by factors such as lower bandwidth, high propagation delay, and limited battery power. Also, the vulnerabilities to compromise the aquatic environment are in growing numbers. The paper proposes an Energy-Efficient standalone Intrusion Detection System (EEIDS) to entail the acoustic environment against malicious attacks and improve the network lifetime. In EEIDS, attributes such as node ID, residual energy, and depth value are verified for forwarding the data packets in a secured path and stabilizing the nodes' energy levels. Initially, for each node, three agents are modeled to perform the assigned responsibilities. For instance, ID agent verifies the node's authentication of the node, EN agent checks for the residual energy of the node, and D agent substantiates the depth value of each node. Next, the classification of normal and malevolent nodes is performed by determining the score for each node. Furthermore, the proposed system utilizes the sheep-flock heredity algorithm to validate the input attributes using the optimized probability values stored in the training dataset. This assists in finding out the best-fit motes in the UWSN. Significantly, the proposed system detects and isolates the malicious nodes with tampered credentials and nodes with lower residual energy in minimal time. The parameters such as the time taken for malicious node detection, network lifetime, energy consumption, and delivery ratio are investigated using simulation tools. Comparison results show that the proposed EEIDS outperforms the existing acoustic security systems.

• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.207-213
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• 2023

Korea is facing a population cliff and a decline in the fertility rate, and the competition rate for recruiting officers in our military is rapidly decreasing every year. This situation is a serious problem in terms of national security and requires efforts to obtain excellent manpower. To this end, it is necessary to understand their occupational values through consideration of the MZ generation, which is the main recruitment target of the military, and to find diagnosis and solutions for each problem by closely analyzing the military's internal and external environment based on their understanding of soldiers as a job. Therefore, we diagnose the current situation in consideration of military specificity, examine the occupational values of the MZ generation, which is a resource for military officers recruitment. Since the subject of military officer acquisition is the MZ generation, efforts are needed to focus on occupational values of MZ generations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.1-14
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• 2023

As markets and industries continue to evolve rapidly, technology opportunity discovery (TOD) has become critical to a firm's survival. From a common consensus that TOD based on a firm's capabilities is a valuable method for small and medium-sized enterprises (SMEs) and reduces the risk of failure in technology development, studies for TOD based on a firm's capabilities have been actively conducted. However, previous studies mainly focused on a firm's technological capabilities and rarely on business capabilities. Since discovered technologies can create market value when utilized in a firm's business, a firm's current business capabilities should be considered in discovering technology opportunities. In this context, this study proposes a TOD method that considers both a firm's business and technological capabilities. To this end, this study uses patent data, which represents the firm's technological capabilities, and trademark data, which represents the firm's business capabilities. The proposed method comprises four steps: 1) Constructing firm technology and business capability matrices using patent classification codes and trademark similarity group codes; 2) Transforming the capability matrices to preference matrices using the fuzzy function; 3) Identifying a target firm's candidate technology opportunities using the collaborative filtering algorithm; 4) Recommending technology opportunities using a portfolio map constructed based on technology similarity and applicability indices. A case study is conducted on a security firm to determine the validity of the proposed method. The proposed method can assist SMEs that face resource constraints in identifying technology opportunities. Further, it can be used by firms that do not possess patents since the proposed method uncovers technology opportunities based on business capabilities.