• Steel and Composite Structures
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• v.51 no.6
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• pp.679-695
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• 2024

This paper presents a novel technique that combines machine learning (ML) with moth-flame optimization (MFO) methods to predict the axial compressive strength (ACS) of concrete filled double skin steel tubes (CFDST) columns. The proposed model is trained and tested with a dataset containing 125 tests of the CFDST column subjected to compressive loading. Five ML models, including extreme gradient boosting (XGBoost), gradient tree boosting (GBT), categorical gradient boosting (CAT), support vector machines (SVM), and decision tree (DT) algorithms, are utilized in this work. The MFO algorithm is applied to find optimal hyperparameters of these ML models and to determine the most effective model in predicting the ACS of CFDST columns. Predictive results given by some performance metrics reveal that the MFO-CAT model provides superior accuracy compared to other considered models. The accuracy of the MFO-CAT model is validated by comparing its predictive results with existing design codes and formulae. Moreover, the significance and contribution of each feature in the dataset are examined by employing the SHapley Additive exPlanations (SHAP) method. A comprehensive uncertainty quantification on probabilistic characteristics of the ACS of CFDST columns is conducted for the first time to examine the models' responses to variations of input variables in the stochastic environments. Finally, a web-based application is developed to predict ACS of the CFDST column, enabling rapid practical utilization without requesting any programing or machine learning expertise.

• Steel and Composite Structures
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• v.50 no.5
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• pp.515-529
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• 2024

Cold-formed steel (CFS) is a popular choice for construction due to its low cost, durability, sustainability, resistance to high environmental and seismic pressures, and ease of installation. The beam-column connections in residential and medium-rise structures are formed using self-drilling screws that connect two CFS channel sections and a gusset plate. In order to increase the moment capacity of these CFS screwed beam-column connections, stiffeners are often placed on the web area of each single channel. However, there is limited literature on studying the effects of stiffeners on the moment capacity of CFS screwed beam-column connections. Hence, this paper proposes a new test approach for determining the moment capacity of CFS screwed beam-column couplings. This study describes an experimental test programme consisting of eight novel experimental tests. The effect of stiffeners, beam thickness, and gusset plate thickness on the structural behaviour of CFS screwed beam-column connections is investigated. Besides, nonlinear elasto-plastic finite element (FE) models were developed and validated against experimental test data. It found that there was reasonable agreement in terms of moment capacity and failure mode prediction. From the experimental and numerical investigation, it found that the increase in gusset plate or beam thickness and the use of stiffeners have no significant effect on the structural behaviour, moment capacity, or rotational capacity of joints exhibiting the same collapse behaviour; however, the capacity or energy absorption capacities have increased in joints whose failure behaviour varies with increasing thickness or using stiffeners. Besides, the thickness change has little impact on the initial stiffness.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.5
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• pp.1073-1088
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• 2024

This study proposes a novel model to address the security, usability, and scalability challenges of cryptocurrency wallets. The model is implemented as a web application that combines FIDO2 (Fast Identity Online v2) with Account Abstraction (AA), offering enhanced security by storing private keys within the Trusted Execution Environment (TEE) of users' mobile devices. By utilizing two types of private keys, the model supports three account types, allowing users to flexibly select security levels and functionalities according to their needs. The research findings show that the proposed model provides strong security against various attack scenarios while also improving usability and scalability. By integrating hardware wallet-level security with the convenience of software wallets, this new paradigm for cryptocurrency wallets is expected to contribute to the widespread adoption of blockchain technology

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.55-75
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• 2010

Sequential pattern mining aims to discover interesting sequential patterns in a sequence database, and it is one of the essential data mining tasks widely used in various application fields such as Web access pattern analysis, customer purchase pattern analysis, and DNA sequence analysis. In general sequential pattern mining, only the generation order of data element in a sequence is considered, so that it can easily find simple sequential patterns, but has a limit to find more interesting sequential patterns being widely used in real world applications. One of the essential research topics to compensate the limit is a topic of weighted sequential pattern mining. In weighted sequential pattern mining, not only the generation order of data element but also its weight is considered to get more interesting sequential patterns. In recent, data has been increasingly taking the form of continuous data streams rather than finite stored data sets in various application fields, the database research community has begun focusing its attention on processing over data streams. The data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. In data stream processing, each data element should be examined at most once to analyze the data stream, and the memory usage for data stream analysis should be restricted finitely although new data elements are continuously generated in a data stream. Moreover, newly generated data elements should be processed as fast as possible to produce the up-to-date analysis result of a data stream, so that it can be instantly utilized upon request. To satisfy these requirements, data stream processing sacrifices the correctness of its analysis result by allowing some error. Considering the changes in the form of data generated in real world application fields, many researches have been actively performed to find various kinds of knowledge embedded in data streams. They mainly focus on efficient mining of frequent itemsets and sequential patterns over data streams, which have been proven to be useful in conventional data mining for a finite data set. In addition, mining algorithms have also been proposed to efficiently reflect the changes of data streams over time into their mining results. However, they have been targeting on finding naively interesting patterns such as frequent patterns and simple sequential patterns, which are found intuitively, taking no interest in mining novel interesting patterns that express the characteristics of target data streams better. Therefore, it can be a valuable research topic in the field of mining data streams to define novel interesting patterns and develop a mining method finding the novel patterns, which will be effectively used to analyze recent data streams. This paper proposes a gap-based weighting approach for a sequential pattern and amining method of weighted sequential patterns over sequence data streams via the weighting approach. A gap-based weight of a sequential pattern can be computed from the gaps of data elements in the sequential pattern without any pre-defined weight information. That is, in the approach, the gaps of data elements in each sequential pattern as well as their generation orders are used to get the weight of the sequential pattern, therefore it can help to get more interesting and useful sequential patterns. Recently most of computer application fields generate data as a form of data streams rather than a finite data set. Considering the change of data, the proposed method is mainly focus on sequence data streams.

• Journal of the Korean Institute of Gas
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• v.16 no.6
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• pp.128-135
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• 2012

In this paper, we proposed a system and a scenario to raise efficiency of gas safety management by developing wireless ZigBee communication modules, smart-home gas safety appliances and the system suitable for gas safety. Our designed system consists of a micom gas meter, an automatic extinguisher, sensors, and a wall-pad. A micom-gas-meter monitors gas flow, gas pressure, and earthquake. An automatic fire extinguisher checks combustible gas leaks and temperature of $100^{\circ}C$(cut off) and $130^{\circ}C$(fire). Sensors measure smoke and CO gas. In our novel system, a micom-gas meter cut off inner valve with warnings, an automatic fire extinguisher cut off middle valve and spray extinguishing materials, and sensors generate signals when detecting smoke and CO and then take a next action. Gas safety appliances and sensors automatically takes measures, and transmit those information to a wall-pad. The wall-pad again transmits real time information to server. Users can check and manage gas safety situations by connecting BcN server through web or mobile application. We hereby devised scenarios for gas safety and risk management based on the smart, and demonstrated their efficiency through test applied to filed.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.5
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• pp.1803-1811
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• 2015

Hepatoma-derived growth factor (HDGF) is a novel jack-of-all-trades in cancer. Here we quantify the prognostic impact of this biomarker and assess how consistent is its expression in solid tumors. A comprehensive search strategy was used to search relevant literature updated on October 3, 2014 in PubMed, EMBASE and WEB of Science. Correlations between HDGF expression and clinicopathological features or cancer prognosis was analyzed. All pooled HRs or ORs were derived from random-effects models. Twenty-six studies, primarily in Eastern Asia, covering 2,803 patients were included in the analysis, all of them published during the past decade. We found that HDGF overexpression was significantly associated with overall survival (OS) ($HR_{OS}=2.35$, 95%CI=2.04-2.71, p<0.001) and disease free survival (DFS) ($HR_{DFS}=2.25$, 95%CI =1.81-2.79, p<0.001) in solid tumors, especially in non-small cell lung cancer, hepatocellular carcinoma and cholangiocarcinoma (CCA). Moreover, multivariate survival analysis showed that HDGF overexpression was an independent predictor of poor prognosis ($HR_{OS}=2.41$, 95%CI: 2.02-2.81, p<0.001; $HR_{DFS}=2.39$, 95%CI: 1.77-3.24, p<0.001). In addition, HDGF overexpression was significantly associated with tumor category (T3-4 versus T1-2, OR=2.12, 95%CI: 1.17-3.83, p=0.013) and lymph node status (N+ versus N-, OR=2.37, 95%CI: 1.31-4.29, p=0.03) in CCA. This study provides a comprehensive examination of the literature available on the association of HDGF overexpression with OS, DFS and some clinicopathological features in solid tumors. Meta-analysis results provide evidence that HDGF may be a new indicator of poor cancer prognosis. Considering the limitations of the eligible studies, other large-scale prospective trials must be conducted to clarify the prognostic value of HDGF in predicting cancer survival.

• Journal of KIISE:Databases
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• v.37 no.5
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• pp.258-266
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• 2010

In this paper, we introduce a novel method to predict next update of blogs. The number of RSS feeds registered on meta-blogs is on the order of several million. Checking for updates is very time consuming and imposes a heavy burden on network resources. Since blog search engine has limited resources, there is a fix number of blogs that it can visit on a day. Nevertheless we need to maximize chances of getting new data, and the proposed method which predicts update probability on blogs could bring better chances for it. Also this work is important to avoid distributed denial-of-service attack for the owners of blogs. Furthermore, for the internet as whole this work is important, too, because our approach could minimize traffic. In this study, we assumed that there is a specific pattern to when a blogger is actively posting, in terms of days of the week and, more specifically, hours of the day. We analyzed 15,119 blogs to determine a blogger's posting preference. This paper proposes a method to predict the update probability based on a blogger's posting history and preferred days of the week. We applied proposed method to 12,115 blogs to check the precision of our predictions. The evaluation shows that the model has a precision of 0.5 for over 93.06% of the blogs examined.

• Journal of Sericultural and Entomological Science
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• v.53 no.1
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• pp.44-49
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• 2015

We characterized tissue specific-expressed genes in the posterior silk gland of Bombyx mori using by the Annealing Control Primer based differential display-PCR manner. In this study, we isolated 34 differentially expressed PCR amplicons, which one of these was identified as a novel transcript named as ACP-16 (366 bp), its expression was observed only in the posterior silk glands by Northern blot analysis. To determine promoter region of the ACP-16, we isolated and analyzed a phage DNA having 1.7 kb-long genome DNA including the open reading flame and 5'- upstream untranslated region of the ACP-16 gene from a genomic DNA library. We have estimated a promoter region of the ACP-16 gene by a web promoter prediction engine, which locates -750 ~ -165 from translation initiation site (ATG, +1). ACP-16 gene is necessary to more studies about critical biological role in order to apply the silkworm's transgenic system.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.3
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• pp.13-20
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• 2011

In this paper, we proposed a system to raise gas safety management by using the wireless communication module and intelligent gas safety appliances. Our designed systems configure a micom-gas meter, an automatic extinguisher, sensors, and a wallpad. A micom-gas-meter monitors gas flow, gas pressure, and earthquake. An automatic fire extinguisher checks gas(combustible) leaks and temperature of $100^{\circ}C$ and $130^{\circ}C$. Sensors measure smoke and CO gas. In our novel system, a micom-gas meter cut off inner valve with warnings, an automatic fire extinguisher cut off middle valve and spray extinguishing materials, and sensors generate signals for smoke and CO when occurring gas risk. Gas safety appliances and sensors takes safety measures, and transmit those signal to a wallpad. The wallpad again transmit signal like events to a control server. Users can connect web pages for gas safety through B-ISDN and control and manage them. We hereby devised scenarios for gas safety and risk management, and demonstrated their effectiveness through experiments.

• Journal of Environmental Health Sciences
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• v.42 no.1
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• pp.41-52
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• 2016

Objectives: Scrub typhus is one of the most prevalent vector-borne diseases. It is caused by Orientia tsutsugamushi, which is transmitted when people are bitten by infected chigger mites. This study aims at quantifying the association between the incidence of scrub typhus and meteorological factors in Jeollabuk-do Province over the period 2001-2015. Methods: Reported cases of scrub typhus were collected from the website of the Disease Web Statistical System supported by the Korea Centers for Disease Control and Prevention (KCDC). Simultaneous meteorological data, including temperature, rainfall, relative humidity, and sunshine duration were collected from the website of the National Climate Data Service System by the Korea Meteorological Administration. Correlation and regression analyses were applied to identify the association between the incidence of scrub typhus and meteorological factors. Results: The general epidemiological characteristics of scrub typhus in Jeollabuk-do Province were similar to those nationwide for sex, age, and geographical distribution. However, the annual incidence rate (i.e., cases per 100,000) of scrub typhus in Jeollabuk-do Province was approximately four times higher than all Korea's 0.9. The number of total cases was the highest proportion at 13.3% in Jeonbuk compared to other regions in Korea. The results of correlation analysis showed that there were significant correlations between annual cases of scrub typhus and monthly data for meteorological factors such as temperature and relative humidity in late spring and summer, especially in the case of temperature in May and June. The results of regression analysis showed that determining factors in the regression equation explaining the incidence of scrub typhus reached 46.2% and 43.5% in May and June. Using the regression equation, each 1oC rise in the monthly mean temperature in May or June may lead to an increase of 38 patients with scrub typhus compared to the annual mean of incidence cases in Jeollabuk-do Province. Conclusion: The result of our novel attempts provided rational evidence that meteorological factors are associated with the occurrence of scrub typhus in Jeollabuk-do. It should therefore be necessary to observe the trends and predict patterns of scrub typhus transmission in relation to global-scale climate change. Also, action is urgently needed in all areas, especially critical regions, toward taking steps to come up with preventive measures against scrub typhus transmission.