Journal of the Korea Institute of Information Security & Cryptology
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v.21
no.3
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pp.143-154
/
2011
SQLite is a small sized database engine largely used in embedded devices and local application software. The availability of portable devices, such as smartphones, has been extended over the recent years and has contributed to growing adaptation of SQLite. This implies a high likelihood of digital evidences acquired during forensic investigations to include SQLite database files. Where intentional deletion of sensitive data can be made by a suspect, forensic investigators need to recover deleted records in SQLite at the best possible. This study analyzes data management rules used by SQLite and the structure of deleted data in the system, and in turn suggests a recovery Tool of deleted data. Further, the study examines major SQLite suited software as it validates feasible possibility of deleted data recovery.
Communications for Statistical Applications and Methods
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v.30
no.2
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pp.119-133
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2023
With the rapid growth of the economy and fossil fuel consumption, the concentration of air pollutants has increased significantly and the air pollution problem is no longer limited to small areas. We conduct statistical analysis with the actual data related to air quality that covers the entire of South Korea using R and Python. Some factors such as SO2, CO, O3, NO2, PM10, precipitation, wind speed, wind direction, vapor pressure, local pressure, sea level pressure, temperature, humidity, and others are used as covariates. The main goal of this paper is to predict air quality index (AQI) spatio-temporal data. The observations of spatio-temporal big datasets like AQI data are correlated both spatially and temporally, and computation of the prediction or forecasting with dependence structure is often infeasible. As such, the likelihood function based on the spatio-temporal model may be complicated and some special modelings are useful for statistically reliable predictions. In this paper, we propose several methods for this big spatio-temporal AQI data. First, random effects with spatio-temporal basis functions model, a classical statistical analysis, is proposed. Next, neural networks model, a deep learning method based on artificial neural networks, is applied. Finally, random forest model, a machine learning method that is closer to computational science, will be introduced. Then we compare the forecasting performance of each other in terms of predictive diagnostics. As a result of the analysis, all three methods predicted the normal level of PM2.5 well, but the performance seems to be poor at the extreme value.
Housing is an essential element of human living environments. The type of housing occupancy can vary based on age, family composition, occupation, education level, and economic situation. In this study, we used social survey statistics to investigate the relationship between housing ownership types and individual and societal characteristics. The research findings revealed that apartment residency rates were high across all age groups. Married individuals tended to have higher apartment residency rates compared to unmarried individuals. Additionally, as the number of household members and generations increased, so did the likelihood of apartment residency. Overall, higher income levels and stable employment were associated with a preference for homeownership. However, there was no significant correlation between homeownership and education level or employment status. National and local authorities should focus on housing supply that aligns with the purchasing capacity and characteristics of potential homebuyers.
Femy M. Sahami;Sri Nuryatin Hamzah;Philippe Keith;Sitty Ainsyah Habibie
Fisheries and Aquatic Sciences
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v.27
no.5
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pp.294-305
/
2024
Tomini Bay in Gorontalo offers significant potential for amphidromous goby-fry, a group of fish found in at least five estuaries in the area, namely Bone-Bolango, Paguyaman, Bilungala, Tombulilato, and Taludaa Estuaries. Preliminary results were limited to only two locations in estuarine waters, namely the Bone-Bolango and Paguyaman rivers. Further exploration of goby-fry species in various locations within Tomini Bay is essential to enhance knowledge about the abundance and aid conservation efforts. Therefore, this study identified the goby-fry species and created their distribution map in the waters of Tomini Bay Gorontalo. The samples used were obtained from daily catches of fishermen in the five estuaries during the recruitment period from February to September 2022. These samples were categorized based on their morphological similarities and specific melanophore patterns. Distinct groups with different melanophore patterns from those previously reported were identified as newly recorded species, photographed, and described in terms of their morphology. Furthermore, two specimens from each newly recorded species underwent molecular identification using the cytochrome oxidase subunit 1 (COI) gene for DNA amplification and were analyzed through the Basic Local Alignment Search Tool (BLAST) method. The phylogenetic tree was constructed using the Maximum Likelihood Method. The results showed the existence of nongoby-fry species caught together with goby fry school. A total of 75,881 goby-fry and 1,687 nongoby-fry were successfully collected. Among the goby-fry species, 13 were identified, including three new records, namely Eleotris fusca (Forster, 1801), Sicyopterus microcephalus (Bleeker, 1855), and Sicyopus zosterophorus (Bleeker, 1856). This study also documented the existence of nongoby-fry species, namely Anguilla celebesensis (Kaup, 1856), Moringua microchir (Bleeker, 1853), and Microphis leiaspis (Bleeker, 1854). It significantly contributed to the understanding of fish biodiversity in Tomini Bay.
Real-time Object tracking is an important field in developing vision applications such as surveillance systems and vision based navigation. mean-shift algerian and Condensation algorithm are widely used in robust object tracking systems. Since the mean-shift algorithm is easy to implement and is effective in object tracking computation, it is widely used, especially in real-time tracking systems. One of the drawbacks is that it always converges to a local maximum which may not be a global maximum. Therefore, in a cluttered environment, the Mean-shift algorithm does not perform well. On the other hand, since it uses multiple hypotheses, the Condensation algorithm is useful in tracking in a cluttered background. Since it requires a complex object model and many hypotheses, it contains a high computational complexity. Therefore, it is not easy to apply a Condensation algorithm in real-time systems. In this paper, by combining the merits of the Condensation algorithm and the mean-shift algorithm we propose a new model which is suitable for real-time tracking. Although it uses only a few hypotheses, the proposed method use a high-likelihood hypotheses using mean-shift algorithm. As a result, we can obtain a better result than either the result produced by the Condensation algorithm or the result produced by the mean-shift algorithm.
Seong Bin Youn;Gyojun Hwang;Hyun-Gon Kim;Jae Seong Kang;Hyung Cheol Kim;Sung Han Oh;Mi-Kyung Kim;Bong Sub Chung;Jong Kook Rhim;Seung Hun Sheen
Journal of Korean Neurosurgical Society
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v.66
no.5
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pp.536-542
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2023
Objective : Surgical site infection is the most detrimental complication following cranioplasty. In other surgical fields, intrawound vancomycin powder application has been introduced to prevent surgical site infection and is widely used based on results in multiple studies. This study evaluated the effect of intrawound vancomycin powder in cranioplasty compared with the conventional method without topical antibiotics. Methods : This retrospective study included 580 patients with skull defects who underwent cranioplasty between August 1, 1998 and December 31, 2021. The conventional method was used in 475 (81.9%; conventional group) and vancomycin powder (1 g) was applied on the dura mater and bone flap in 105 patients (18.1%; vancomycin powder group). Surgical site infection was defined as infection of the incision, organ, or space that occurred after cranioplasty. Surgical site infection within 1-year surveillance period was compared between the conventional and vancomycin powder groups with logistic regression analysis. Penalized likelihood estimation method was used in logistic regression to deal with zero events. All local and systemic adverse events associated with topical vancomycin application were also evaluated. Results : Surgical site infection occurred in 31 patients (5.3%) and all were observed in the conventional group. The median time between cranioplasty and detection of surgical site infection was 13 days (range, 4-333). Staphylococci were the most common organisms and identified in 25 (80.6%) of 31 cases with surgical site infections. The surgical site infection rate in the vancomycin powder group (0/105, 0.0%) was significantly lower than that in the conventional group (31/475, 6.5%; crude odds ratio [OR], 0.067; 95% confidence interval [CI], 0.006-0.762; adjusted OR, 0.068; 95% CI, 0.006-0.731; p=0.026). No adverse events associated with intrawound vancomycin powder were observed during the follow-up. Conclusion : Intrawound vancomycin powder effectively prevented surgical site infections following cranioplasty without local or systemic adverse events. Our results suggest that intrawound vancomycin powder is an effective and safe strategy for patients undergoing cranioplasty.
Lee, Bae Hun;Kim, Ji Yung;Sung, Kyung Il;Kim, Byong Wan
Journal of The Korean Society of Grassland and Forage Science
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v.39
no.2
/
pp.89-96
/
2019
This study was conducted to investigate 106 grassland farms in six provinces including Chungcheongbuk-do, Gangwon-do, Gyeonggi-do, Gyeongsangbuk-do, Gyeongsangnam-do, Jeju-do, and Jeollanam-do to present their problems and causes by surveying the actual state of grassland farms during three years(2014~2016). The grassland survey was divided into three categories; used as the perennial grasses and annual forage crops (Complied with Grassland Act), not used as the perennial grasses and annual forage crops (Not complied with Grassland Act) and failed to meet the farmer and some items are missing or inaccurate (Insufficient contents). Among the surveyed grassland farm, 68 farms (64.2 %) were complied with Grassland Act but 30 farms (28.3 %) were not complied with Grassland Act. Especially, the 8 farms (26.7 %) not complied with Grassland Act used the grassland as other purposes such as tree growing, golf club and swine farm etc.. Therefore, strict on-site investigation by local governments is required to prevent the grassland from being used by illegal purposes. And there's a strong likelihood that 5 farms (62.5 %) avoided the survey violate the positive law. Grassland grades used by the local administrative agencies were not influenced by the factors affecting the yield (existence and non-existence of overseeding and fertilization by grassland grade, soil pH and organic matter content). This results suggest that there is a fundamental problem on the current grassland grade system based on the yield and the irregular time of investigation and lack of on-site investigation are another causes for inaccurate grassland grade. Therefore, the new method evaluating grassland grades which is not based on yield and the thorough on-site investigation by local administrative agencies are necessary when the grassland grade is evaluated.
Korean Journal of Agricultural and Forest Meteorology
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v.16
no.4
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pp.403-417
/
2014
Increased frequency of climate extremes is another face of climate change confronted by humans, resulting in catastrophic losses in agriculture. While climate extremes take place on many scales, impacts are experienced locally and mitigation tools are a function of local conditions. To address this, agrometeorological early warning systems must be place and location based, incorporating the climate, crop and land attributes at the appropriate scale. Existing services often lack site-specific information on adverse weather and countermeasures relevant to farming activities. Warnings on chronic long term effects of adverse weather or combined effects of two or more weather elements are seldom provided, either. This lecture discusses a field-specific early warning system implemented on a catchment scale agrometeorological service, by which volunteer farmers are provided with face-to-face disaster warnings along with relevant countermeasures. The products are based on core techniques such as scaling down of weather information to a field level and the crop specific risk assessment. Likelihood of a disaster is evaluated by the relative position of current risk on the standardized normal distribution from climatological normal year prepared for 840 catchments in South Korea. A validation study has begun with a 4-year plan for implementing an operational service in Seomjin River Basin, which accommodates over 60,000 farms and orchards. Diverse experiences obtained through this study will certainly be useful in planning and developing the nation-wide disaster early warning system for agricultural sector.
Korean Journal of Agricultural and Forest Meteorology
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v.19
no.3
/
pp.93-101
/
2017
The distribution of inter-annual variation in temperature would help evaluate the likelihood of a climatic risk and assess suitable zones of crops under climate change. In this study, we evaluated two methods to estimate the standard deviation of temperature in the areas where weather information is limited. We calculated the monthly standard deviation of temperature by collecting temperature at 0600 and 1500 local standard time from 10 automated weather stations (AWS). These weather stations were installed in the range of 8 to 1,073m above sea level within a mountainous catchment for 2011-2015. The observed values were compared with estimates, which were calculated using a geospatial correction scheme to derive the site-specific temperature. Those estimates explained 88 and 86% of the temperature variations at 0600 and 1500 LST, respectively. However, it often underestimated the temperatures. In the spring and fall, it tended to had different variance (e.g., increasing or decreasing pattern) from lower to higher elevation with the observed values. A regression analysis was also conducted to quantify the relationship between the standard deviation in temperature and the topography. The regression equation explained a relatively large variation of the monthly standard deviation when lapse-rate corrected temperature, basic topographical variables (e.g., slope, and aspect) and topographical variables related to temperature (e.g., thermal belt, cold air drainage, and brightness index) were used. The coefficient of determination for the regression analysis ranged between 0.46 and 0.98. It was expected that the regression model could account for 70% of the spatial variation of the standard deviation when the monthly standard deviation was predicted by using the minimum-maximum effective range of topographical variables for the area.
Silicone fluid(polydimethylsiloxane) is widely used in breast augmentation and other cosmetic procedures because of little incidence of complications and low mortality rate. However, local reaction following silicone injections can be occurred sometimes leading to serious complications. Especially, illicit silicone injections have resulted in severe reactions within the pulmonary area, and some have resulted in acute respiratory distress syndrome subsequently. We experienced a case of acute respiratory distress syndrome induced by subcutaneous injections of silicone at vaginal wall. The patients was 39-year-old, previously healthy woman who had complained of dyspnea related to silicone injection at vaginal wall. Chest X-ray and chest CT scan show diffuse air consolidation with ground glass opacities and perfusion lung scan revealed likelihood of pulmonary embolism as showing multiple perfusion defects. We report a case of acute respiratory distress syndrome occured after silicone injection with review of literature.
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