• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.10a
• /
• pp.422-424
• /
• 2018

Recently there has been growing interest in big data analysis and methods for collecting data have been developed diversely but researchers are still not easy to collect and use these large scale data. In this paper, researchers try to compare and analyze the method of collecting big data by using several methods and present it. I hope that you can provide the results of your research if you select and use methods that match your research objectives.

• Korean Parent-Child Health Journal
• /
• v.14 no.1
• /
• pp.28-35
• /
• 2011

Purpose: The aim of this study is to suggest a direction for the development of effective methods for relieving labor pain, by analyzing non-pharmacological interventions through a literature review. Methods: Collection of literature data in this study has been accomplished through theses, reports, and academic data searched on databases of the Research Information Sharing Services (Riss), PubMed, ProQuest, and the National Discovery for Science Leaders (NDSL). Results: Non-pharmacological interventions analyzed as effective in relieving labor pain, in literature published both within and outside of Korea, included: pre-delivery education, Yoga, Doula delivery care, Massage, Music therapy, Aromatherapy, Hypnosis, TENS, Sterilized water injection, and Acupuncture. Conclusion: Several different interventions have been attempted for the relief of labor pain. Since even the same intervention shows different results depending on the research method utilized, critical factors must be acknowledged that compromise the effectiveness of these methods. In addition, study of potential synergy effects of interventions that combine these various methods might also prove to be significant.

• Korean Journal of Poultry Science
• /
• v.7 no.2
• /
• pp.4-17
• /
• 1980

This is to review from the existing literatures the various methods of determination, problems involved in the determination of metabolizable energy(ME) values of poultry feedstuffs that is the most widely used energy term in poultry nutrition. An attempt will also be made to introduce the newly developed determination method of ME by Sibbald and his associates. It was found that conventional methods of ME measurements such as total collection method and indicator method require a great deal of labor and time. It should also be pointed out that these methods have some technical problems as well. Experimental evidences indicate that the ME content of feedstuffs may be affected by breed, age, substitution level of basal diet, kind of basal diet, methods of chemical analysis and chemical composition of experimental diet. Standard procedures and technical advantages of newly developed method of "True Metabolizable Energy" system are fully described.

• Journal of Preventive Medicine and Public Health
• /
• v.40 no.2
• /
• pp.108-113
• /
• 2007

When conducting large-scale cohort studies, numerous statistical issues arise from the range of study design, data collection, data analysis and interpretation. In genomic cohort studies, these statistical problems become more complicated, which need to be carefully dealt with. Rapid technical advances in genomic studies produce enormous amount of data to be analyzed and traditional statistical methods are no longer sufficient to handle these data. In this paper, we reviewed several important statistical issues that occur frequently in large-scale genomic cohort studies, including measurement error and its relevant correction methods, cost-efficient design strategy for main cohort and validation studies, inflated Type I error, gene-gene and gene-environment interaction and time-varying hazard ratios. It is very important to employ appropriate statistical methods in order to make the best use of valuable cohort data and produce valid and reliable study results.

• Journal of the Korean Society for information Management
• /
• v.33 no.3
• /
• pp.219-238
• /
• 2016

With the purpose of looking into the information service study tendency, targeted at university library, this performed a content analysis of the articles in print from 2006 to 2015 on major four academic journals of Library and Information Science. Investigation items were study number of information services, subsidiary themes classified with information service functions, study method, collection method, user object, and theory study vs. service study in reality. As a result, information service studies were performed more than other areas. Information service functions targeted at the study were that of information supply. Major subsidiary themes were electronic information service, information literacy instruction, and information (reference) services general. Major study methods were survey research method,, case study, and major material collection methods were questionnaire and web-based research methods. Major user studies were targeted at undergraduates, and service study in reality took a great share.

• Journal of Korean Society of Forest Science
• /
• v.109 no.1
• /
• pp.23-30
• /
• 2020

The use of increased computing power, machine learning, and deep learning techniques have dramatically increased in various sectors. In particular, image detection algorithms are broadly used in forestry and remote sensing areas to identify forest types and tree species. However, in South Korea, machine learning has rarely, if ever, been applied in forestry image detection, especially to classify tree species. This study integrates the application of machine learning and forest image detection; specifically, we compared the ability of two machine learning data collection methods, namely image data captured by forest experts (D1) and web-crawling (D2), to automate the classification of five trees species. In addition, two methods of characterization to train/test the system were investigated. The results indicated a significant difference in classification accuracy between D1 and D2: the classification accuracy of D1 was higher than that of D2. In order to increase the classification accuracy of D2, additional data filtering techniques were required to reduce the noise of uncensored image data.

• Clinical and Experimental Pediatrics
• /
• v.58 no.5
• /
• pp.183-189
• /
• 2015

Purpose: Catheter urine (CATH-U) and suprapubic aspiration (SPA) are reliable urine collection methods for confirming urinary tract infections (UTI) in infants. However, noninvasive and easily accessible collecting bag urine (CBU) is widely used, despite its high contamination rate. This study investigated the validity of CBU cultures for diagnosing UTIs, using CATH-U culture results as the gold standard. Methods: We retrospectively analyzed 210 infants, 2- to 24-month-old, who presented to a tertiary care hospital's pediatrics department between September 2008 and August 2013. We reviewed the results of CBU and CATH-U cultures from the same infants. Results: CBU results, relative to CATH-U culture results (${\geq}10^4$ colony-forming units [CFU]/mL) were widely variable, ranging from no growth to ${\geq}10^5CFU/mL$. A CBU cutoff value of ${\geq}10^5CFU/mL$ resulted in false-positive and false-negative rates of 18% and 24%, respectively. The probability of a UTI increased when the CBU bacterial count was ${\geq}10^5/mL$ for all infants, both uncircumcised male infants and female infants (likelihood ratios [LRs], 4.16, 4.11, and 4.11, respectively). UTIs could not be excluded for female infants with a CBU bacterial density of $10^4-10^5$ (LR, 1.40). The LRs for predicting UTIs based on a positive dipstick test and a positive urinalysis were 4.19 and 3.11, respectively. Conclusion: The validity of obtaining urine sample from a sterile bag remains questionable. Inconclusive culture results from CBU should be confirmed with a more reliable method.

• Nutrition Research and Practice
• /
• v.17 no.2
• /
• pp.175-191
• /
• 2023

BACKGROUND/OBJECTIVES: The scientific evidence of a sodium-obesity association is limited by sodium intake assessments. Our specific aim is to synthesize the association between dietary sodium intake and obesity across the sodium intake assessments as evidenced by systematic reviews in adults. SUBJECTS/METHODS: A systematic search identified systematic reviews comparing the association of dietary sodium intakes with obesity-related outcomes such as body mass index (BMI), body weight, waist circumference, and risk of (abdominal) obesity. We searched PubMed on October 24, 2022. To assess the Risk of Bias in Systematic Reviews (ROBIS), we employed the ROBIS tool. RESULTS: This review included 3 systematic reviews, consisting of 39 unique observational studies (35 cross-sectional studies and 4 longitudinal studies) and 15 randomized controlled trials (RCTs). We found consistently positive associations between dietary sodium intake and obesity-related outcomes in cross-sectional studies. Studies that used 24-h urine collection indicated a greater BMI for those with higher sodium intake (mean difference = 2.27 kg/m²; 95% confidence interval [CI], 1.59-2.51; P < 0.001; I² = 77%) compared to studies that used spot urine (mean difference = 1.34 kg/m²; 95% CI, 1.13-1.55; P < 0.001; I² = 95%) and dietary methods (mean difference = 0.85 kg/m²; 95% CI, 0.1-1.51; P < 0.05; I² = 95%). CONCLUSIONS: Quantitative synthesis of the systematic reviews has shown that cross-sectional associations between dietary sodium intake and obesity outcomes were substantially different across the sodium intake assessments. We need more high-quality prospective cohort studies and RCTs using 24-h urine collection to examine the causal effects of sodium intake on obesity.

• International Journal of Precision Engineering and Manufacturing
• /
• v.4 no.6
• /
• pp.5-11
• /
• 2003

The number of the enterprises which utilize network technology has been increasing for solving problems such as productivity improvement, market trend analysis, and material collection for making decision. Especially, the management of equipment and the recovery time reduction when machines break down are very important factors in productivity improvement of the enterprise. Currently, most of the remote trouble diagnosis of equipment using the internet have just one function of transmitting the trouble information to the user. Therefore it does not directly reflect the user's recovery experience or the developer's new recovery methods. If the user's experienced recovery methods or the developer's recovery methods as well as the basic recovery methods are reflected online or on the internet, it makes it possible to recover faster than before. In this paper, we develop a Remote Monitoring Server (RMS) for chip mounters, and make it possible to reduce the recovery time by reflecting the user's experience and developer's new methods in addition to presenting the basic recovery methods. For this, trouble recovery concept will be defined. Based on this, many functions(trouble diagnosis, the presentation of the basic recovery methods, user's and developer's recovery method, counting function of the trouble number of each code, and presentation of usage number of each recovery methods) were developed. By utilizing the reports of the actual results of chip mounter and the notice function of the parts change time, the rate of operation of the chip mounter can be improved.

• International conference on construction engineering and project management
• /
• 2009.05a
• /
• pp.30-31
• /
• 2009

Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.