• Journal of forensic and investigative science
• /
• v.1 no.2
• /
• pp.5-19
• /
• 2006

Data mining is an information extraction activity to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis. Law enforcement agencies deal with mass data to investigate the crime and its amount is increasing due to the development of processing the data by using computer. Now new challenge to discover knowledge in that data is confronted to us. It can be applied in criminal investigation to find offenders by analysis of complex and relational data structures and free texts using their criminal records or statement texts. This study was aimed to evaluate possibile application of data mining and its limitation in practical criminal investigation. Clustering of the criminal cases will be possible in habitual crimes such as fraud and burglary when using data mining to identify the crime pattern. Neural network modelling, one of tools in data mining, can be applied to differentiating suspect's photograph or handwriting with that of convict or criminal profiling. A case study of in practical insurance fraud showed that data mining was useful in organized crimes such as gang, terrorism and money laundering. But the products of data mining in criminal investigation should be cautious for evaluating because data mining just offer a clue instead of conclusion. The legal regulation is needed to control the abuse of law enforcement agencies and to protect personal privacy or human rights.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.42 no.6
• /
• pp.924-932
• /
• 2013

This study investigated the antioxidant activities of processed Deoduck (Codonopsis lanceolata) extracts treated through high-pressure extraction and steaming with fermentation. The antioxidant activities were determined for DPPH and ABTS radical-scavenging activity, SOD-like activity, ferric reducing antioxidant power (FRAP), and $Fe^{2+}$ chelating. Total phenolic and flavonoid contents were also measured. Among eight Deoduck extracts, the S5FDW extract had the highest total phenolic and flavonoid content, 73.9 mg GAE/g and 50.9 mg QUE/g, respectively. The S5FDW extract had the highest DPPH radical-scavenging activity (27%) at a 1.0 mg/mL concentration. The ABTS radical-scavenging activity was highest for S5FDW extract (82.1%) at a 10 mg/mL concentration. The HFDE extract showed the highest SOD-like activity (29.7%) at a 1.0 mg/mL concentration. FRAP was highest in S5FDW extract (140.8 ${\mu}M$) at a 1.0 mg/mL concentration. The DE extract showed the highest $Fe^{2+}$ chelating (46%) at a 1.0 mg/mL concentration. The phenolic and flavonoid contents significantly correlated with the antioxidant activity of several processed Deoduck extracts and was higher in the processed Deoduck extracts compared to the raw Deoduck extracts. Therefore, processing techniques can be useful methods for making Deoduck a more potent and natural antioxidant.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.12 no.4
• /
• pp.277-288
• /
• 2010

The multi-level $H_2O/CO_2$ profile system has been widely used to quantify the storage and advection effects on energy and mass fluxes measured by eddy covariance systems. In this study, we expanded the utility of the profile system by accommodating air sampling devices for isotope analyses of water vapor and $CO_2$. A pre-evacuated 2L glass flask was connected to the discharge of an Infrared Gas Analyzer (IRGA) of the profile system so that airs with known concentration of $H_2O$ and $CO_2$ can be sampled. To test the performance of this sampling system, we sampled airs from 8 levels (from 0.1 to 40 m) at the KoFlux tower of Gwangneung deciduous forest, Korea. Air samples in the 2L flask were separated into its component gases and pure $H_2O$ and $CO_2$ were extracted by using a vacuum extraction line. This novel technique successfully produced vertical profiles of ${\delta}D$ of $H_2O$ and ${\delta}^{13}C$ of $CO_2$ in a mature forest, and estimated ${\delta}D$ of evapotranspiration (${\delta}D_{ET}$) and ${\delta}^{13}C$ of $CO_2$ from ecosystem respiration (${\delta}^{13}C_{resp}$) by using Keeling plots. While technical improvement is still required in various aspects, our sampling system has two major advantages over other proposed techniques. First, it is cost effective since our system uses the existing structure of the profile system. Second, both $CO_2$ and $H_2O$ can be sampled simultaneously so that net ecosystem exchange of $H_2O$ and $CO_2$ can be partitioned at the same temporal resolution, which will improve our understanding of the coupling between water and carbon cycles in terrestrial ecosystems.

• Journal of Internet Computing and Services
• /
• v.16 no.2
• /
• pp.109-115
• /
• 2015

The new medical device technologies for bio-signal information and medical information which developed in various forms have been increasing. Information gathering techniques and the increasing of the bio-signal information device are being used as the main information of the medical service in everyday life. Hence, there is increasing in utilization of the various bio-signals, but it has a problem that does not account for security reasons. Furthermore, the medical image information and bio-signal of the patient in medical field is generated by the individual device, that make the situation cannot be managed and integrated. In order to solve that problem, in this paper we integrated the QR code signal associated with the medial image information including the finding of the doctor and the bio-signal information. bio-signal. System implementation environment for medical imaging devices and bio-signal acquisition was configured through bio-signal measurement, smart device and PC. For the ROI extraction of bio-signal and the receiving of image information that transfer from the medical equipment or bio-signal measurement, .NET Framework was used to operate the QR server module on Window Server 2008 operating system. The main function of the QR server module is to parse the DICOM file generated from the medical imaging device and extract the identified ROI information to store and manage in the database. Additionally, EMR, patient health information such as OCS, extracted ROI information needed for basic information and emergency situation is managed by QR code. QR code and ROI management and the bio-signal information file also store and manage depending on the size of receiving the bio-singnal information case with a PID (patient identification) to be used by the bio-signal device. If the receiving of information is not less than the maximum size to be converted into a QR code, the QR code and the URL information can access the bio-signal information through the server. Likewise, .Net Framework is installed to provide the information in the form of the QR code, so the client can check and find the relevant information through PC and android-based smart device. Finally, the existing medical imaging information, bio-signal information and the health information of the patient are integrated over the result of executing the application service in order to provide a medical information service which is suitable in medical field.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.43 no.8
• /
• pp.1236-1247
• /
• 2014

Gamma irradiated-treatment of natural medicinal plants can be used to improve extraction transference number and for qualitative improvement of color when applied to functional material exploration. This study investigated the biological activities of Aralia elata cortex extracts upon gamma irradiation. In addition, different physical techniques [photostimulated luminescence (PSL) and thermoluminescence (TL)] were used for irradiation identification of Aralia elata cortex. In PSL analysis, non-irradiated (0 kGy) sample showed a negative result of 400 photon counts (PCs), whereas irradiated (5, 10, and 30 kGy) samples showed positive results of 90,100.00, 312,614.33, and 321,661.67 PCs, respectively. In the TL method, growth curve showed very unusual behaviors around $200^{\circ}C$ upon natural-irradiation of the non-irradiated (0 kGy) sample and around $150{\sim}250^{\circ}C$ for the irradiated (5, 10, and 30 kGy) samples. The TL ratio was 0.1 in non-irradiated samples at 0.011, whereas the values of irradiated samples (5, 10, and 30 kGy) were 0.1 at 1.105, 1.009, and 2.206, respectively. For phenolics of gamma-irradiated Aralia elata cortex, water and 50% ethanol extracts had the highest amounts, $17.30{\pm}0.40mg/g$ and $18.87{\pm}0.46mg/g$ at 10 kGy irradiation, respectively. The inhibitory activities of angiotensin-converting enzyme and xanthin oxidase were higher in both irradiated water and 50% ethanol extracts than in non-irradiated ones. For pancreatin ${\alpha}$-amylase and ${\alpha}$-glucosidase inhibitory activities, water and 50% ethanol extracts containing $200{\mu}g/mL$ of phenolics showed high inhibitory activities of 60~100% at all irradiation doses (0~30 kGy). This result confirmed that Aralia elata cortex extracts have greater anti-diabetic effects than acabose as a diabetic remedy. Gamma-irradiated Aralia elata cortex extracts are useful as a functional material with anti-diabetic effects. Thus, Aralia elata cortex extracts can be used as a functional material with various biological activities, and gamma-irradiation can be used to amplify biological activities in plants.

• Journal of Intelligence and Information Systems
• /
• v.21 no.1
• /
• pp.65-82
• /
• 2015

Recently, there has been a surge of interest in finding core issues and analyzing emerging trends for the future. This represents efforts to devise national strategies and policies based on the selection of promising areas that can create economic and social added value. The existing studies, including those dedicated to the discovery of future promising fields, have mostly been dependent on qualitative research methods such as literature review and expert judgement. Deriving results from large amounts of information under this approach is both costly and time consuming. Efforts have been made to make up for the weaknesses of the conventional qualitative analysis approach designed to select key promising areas through discovery of future core issues and emerging trend analysis in various areas of academic research. There needs to be a paradigm shift in toward implementing qualitative research methods along with quantitative research methods like text mining in a mutually complementary manner. The change is to ensure objective and practical emerging trend analysis results based on large amounts of data. However, even such studies have had shortcoming related to their dependence on simple keywords for analysis, which makes it difficult to derive meaning from data. Besides, no study has been carried out so far to develop core issues and analyze emerging trends in special domains like the aviation industry. The change used to implement recent studies is being witnessed in various areas such as the steel industry, the information and communications technology industry, the construction industry in architectural engineering and so on. This study focused on retrieving aviation-related core issues and emerging trends from overall research papers pertaining to aviation through text mining, which is one of the big data analysis techniques. In this manner, the promising future areas for the air transport industry are selected based on objective data from aviation-related research papers. In order to compensate for the difficulties in grasping the meaning of single words in emerging trend analysis at keyword levels, this study will adopt topic analysis, which is a technique used to find out general themes latent in text document sets. The analysis will lead to the extraction of topics, which represent keyword sets, thereby discovering core issues and conducting emerging trend analysis. Based on the issues, it identified aviation-related research trends and selected the promising areas for the future. Research on core issue retrieval and emerging trend analysis for the aviation industry based on big data analysis is still in its incipient stages. So, the analysis targets for this study are restricted to data from aviation-related research papers. However, it has significance in that it prepared a quantitative analysis model for continuously monitoring the derived core issues and presenting directions regarding the areas with good prospects for the future. In the future, the scope is slated to expand to cover relevant domestic or international news articles and bidding information as well, thus increasing the reliability of analysis results. On the basis of the topic analysis results, core issues for the aviation industry will be determined. Then, emerging trend analysis for the issues will be implemented by year in order to identify the changes they undergo in time series. Through these procedures, this study aims to prepare a system for developing key promising areas for the future aviation industry as well as for ensuring rapid response. Additionally, the promising areas selected based on the aforementioned results and the analysis of pertinent policy research reports will be compared with the areas in which the actual government investments are made. The results from this comparative analysis are expected to make useful reference materials for future policy development and budget establishment.

• Journal of Intelligence and Information Systems
• /
• v.21 no.1
• /
• pp.143-159
• /
• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• Journal of the Korean Applied Science and Technology
• /
• v.18 no.1
• /
• pp.67-77
• /
• 2001

In search for several fatty acid with unusual structure in vegetable oils, we have found that unknown peaks were shown on GLC in the analysis of fatty acids of the lipids from the pulp of ripened jujube (Zizypus jujuba var. inermis) fruits. These fatty acids were identified as a series of cis-monoenoic acids with ${\omega}-5$ double bond system such as $C_{14:1{\omega}5}$, $C_{16:1{\omega}5}$ and $C_{18:1{\omega}5}$, including ${\omega}-7$ fatty acid as $C_{16:1{\omega}7}$ and $C_{18:1{\omega}7}$, by GLC, solid-phase extraction silver ion-column chromatographic, GLC-mass spectrometric and IR techniques. First of all, total fatty acid methyl esters were resolved into saturated and branched fatty acid, monoenoic acid, dienoic acid, and trienoic acid fraction, respectively, with 100% dichloromethane (DCM), DCM/acetone (9:1, v/v) 100% acetone, and acetone/ acetonitrile (97:3, v/v) solvent system. Unknown fatty acids were included in the monoenoic fraction and were confirmed to have cis-configuration by IR. Picolinyl esters of monoenoic fatty acids gave distinct molecular ion peak and dominant diagnostic peaks, for example, m/z 317, 220 and 260 fragment for $cis-C_{14:1{\omega}5}$, m/z 345, m/z 248 and 288 fragment for $cis-C_{16:1{\omega}5}$ and m/z 373, m/z 276 and 316 fragment for $cis-C_{18:1{\omega}5}$. In this way the occurrence of $cis-C_{16:1{\omega}7}$ and $cis-C_{18:1{\omega}7}$ could be deduced from the appearance of prominent fragments as m/z 345, 220 and 260, and m/z 373, 248 and 280. Level of total ${\omega}-5$ fatty acids amounted to about 30% in the fatty acid composition with the predominance of $C_{16:1{\omega}5}$ $ (18.7{\sim}25.0%)$, in the semi-ripened and/or ripened samples collected in September 14 ($C_{16:1{\omega}5}$ ; 18.7%, $C_{14:1{\omega}5}$ ; 3.6% and $C_{18:1{\omega}5}$ ; 3.0%), September 22 ($C_{16:1{\omega}5}$ ; 25.0%, $C_{14:1{\omega}5}$ ; 1.4% and $C_{18:1{\omega}5}$ ; 2.6%), and October $7 (C_{16:1{\omega}5}$ ; 24.7%, $C_{14:1{\omega}5}$ ; 7.7% and $C_{18:1{\omega}5}$ ; 2.5%). However, the lipids extracted from unripened jujube in July and August contain these unusual fatty acids as low as negligible. It could be observed that the level of ${\omega}-5$ fatty acids in the pulps increased sharply with an elapse of ripening time of jujube fruits. Other monoenoic fatty acids with ${\omega}-7$ series, $C_{16:1{\omega}7}$ (palmitoleic acid) and $C_{18:1{\omega}7}$ (cis-vaccenic acid) could be detected. And in the lipids of the kernel and leaf of jujube, none of ${\omega}-5$ fatty acids could be detected.

• Korean Journal of Remote Sensing
• /
• v.37 no.6_1
• /
• pp.1657-1667
• /
• 2021

Anthropogenic activities and natural processes have been causes of land subsidence which is sudden sinking or gradual settlement of the earth's solid surface. Mexico City, the capital of Mexico, is one of the most severe land subsidence areas which are resulted from excessive groundwater extraction. Because groundwater is the primary water resource occupies almost 70% of total water usage in the city. Traditional terrestrial observations like the Global Navigation Satellite System (GNSS) or leveling survey have been preferred to measure land subsidence accurately. Although the GNSS observations have highly accurate information of the surfaces' displacement with a very high temporal resolution, it has often been limited due to its sparse spatial resolution and highly time-consuming and high cost. However, space-based synthetic aperture radar (SAR) interferometry has been widely used as a powerful tool to monitor surfaces' displacement with high spatial resolution and high accuracy from mm to cm-scale, regardless of day-or-night and weather conditions. In this paper, advanced interferometric approaches have been applied to get a time-series of land subsidence of Mexico City using four-year-long twenty ALOS PALSAR L-band observations acquired from Feb-11, 2007 to Feb-22, 2011. We utilized persistent scatterer interferometry (PSI) and small baseline subset (SBAS) techniques to suppress atmospheric artifacts and topography errors. The results show that the maximum subsidence rates of the PSI and SBAS method were -29.5 cm/year and -27.0 cm/year, respectively. In addition, we discuss the different subsidence rates where the study area is discriminated into three districts according to distinctive geotechnical characteristics. The significant subsidence rate occurred in the lacustrine sediments with higher compressibility than harder bedrock.

• Clean Technology
• /
• v.25 no.1
• /
• pp.91-97
• /
• 2019

Oxidative desulfurization (ODS) has received much attention in recent years because refractory sulfur compounds such as dibenzothiophenes can be oxidized selectively to their corresponding sulfoxides and sulfones, and these products can be removed by extraction and adsorption. In this work, The oxidative desulfurization of marine diesel fuel was performed in a batch reactor with hydrogen peroxide ($H_2O_2$) in the presence of various supported heteropoly acid catalysts. The catalysts were characterized by XRD, XRF, XPS and nitrogen adsorption isotherm techniques. Based on the sulfur removal efficiency of promising silica supported heteropoly acid catalysts, the ranking of catalytic activity was: $30\;H_3PW_{12}/SiO_2$ > $30\;H_3PMo_{12}/SiO_2$ > $30\;H_4SiW_{12}/SiO_2$, which appears to be related with their intrinsic acid strength. The $30\;H_3PW_{12}/SiO_2$ catalyst showed the highest initial sulfur removal efficiency of about 66% under reaction conditions of $30^{\circ}C$, $0.025g\;mL^{-1}$ (cat./oil), 1 h reaction time. However, through the recycle test of the $H_3PW_{12}/SiO_2$ catalyst, significant deactivation was observed, which was attributed to the elution of the active component $H_3PW_{12}$. By introducing cesium cation ($Cs^+$) into the $H_3PW_{12}/SiO_2$ catalyst, the stability of the catalyst was improved with changing the solubility, and the $Cs^+$ ion exchanged catalyst could be recycled for at least five times without severe elution.