• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.3
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• pp.269-277
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• 2019

Since 2020, according to the International Convention for the Prevention of Pollution from Ships (MARPOL) amended in 2016, each Administration shall transfer the annual fuel consumption of its registered ships of 5,000 gross tonnage and above to the International Maritime Organization (IMO) after verifying them. The Administration needs stacks of materials, which must not be manipulated by ship companies, including the Engine log book and also bears an administrative burden to verify them by May every year. This study considers using the Automatic Identification System (AIS), mandatory navigational equipment, as an objective and efficient tool among several verification methods. Calculating fuel consumption using a ship's speed in AIS information based on the theory of a relationship between ship speed and fuel consumption was reported in several examples of relevant literature. After pre-filtering by excluding AIS records which had speed errors from the raw data of five domestic cargo vessels, fuel consumptions calculated using Excel software were compared to actual bunker consumptions presented by ship companies. The former consumptions ranged from 96 to 123 percent of the actual bunker consumptions. The difference between two consumptions could be narrowed to within 20 percent if the fuel consumptions for boilers were deducted from the actual bunker consumption. Although further study should be carried out for more accurate calculation methods depending on the burning efficiency of the engine, the propulsion efficiency of the ship, displacement and sea conditions, this method of calculating annual fuel consumption according to the difference between two consumptions is considered to be one of the most useful tools to verify bunker consumption.

• Fisheries and Aquatic Sciences
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• v.21 no.11
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• pp.34.1-34.13
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• 2018

Sexual maturity ($L_{50}$), the length at which 50% of fish in a size class are mature, is a key aspect of domestication of new fish species because it guides the procedure for identification of appropriate broodstock size for artificial spawning. In this study, the $L_{50}$ was determined for 1083 Barbus altianalis samples obtained from Lake Edward and the Upper Victoria Nile. Gonads of freshly killed samples were examined macroscopically and verified with standard histological procedures for the maturation stages that were used to determine $L_{50}$. Oocytes and spermatogenic cell sizes were compared for fish obtained from both water bodies. Results indicated that there were no variations in macro gonad features observed for fish from Lake Edward and Upper Victoria Nile. Similarly, there were no significant differences in oocyte sizes (P > 0.05) between the two populations but significant differences in spermatogenic cell sizes were noted (P < 0.05) except for spermatozoa (P > 0.05). This however did not suggest peculiar differences between the two populations for staging the gonads. Consequently, no staging variations were suggested for both populations in determination of $L_{50}$. Sexual maturity was found in the same class size of fork length (FL) 20-24.9 cm and 35-39.9 cm for males and females from both water bodies, respectively. At this FL, however, males were too small, and for good selection of vigor broodstocks for spawning and conservation purposes, they are better picked from class size of 30-34.9 cm FL and above. These findings were crucial for integration of appropriate breeding size in spawning protocol by farmers and fisheries scientists conserving wild B. altianalis populations.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.186-198
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• 2021

The introduction of digital technologies affects most socio-economic processes and activities in the economy, from agriculture to public services. Even though the world is currently only in the early stages of digital transformation, the digital economy is growing rapidly, especially in developing countries. Shortly, digital platforms will be able to replace the "invisible hand" of the market and turn it into digital. Some digital platforms have already reached global reach in some sectors of the economy. The growing value of data and artificial intelligence is reflected in the high capitalization of these enterprises. Their growing role has far-reaching consequences for the organization of economic activity and integration into the field of e-business. However, their importance and level of development in different countries differ significantly. The main purpose of this article is an assessment of the level and trends of the digital economy in the world and the identification of homogeneous groups of states following the main trends in the development of its components from among the EU countries. The methodology of the conducted research is based on the use of general scientific research methods in the analysis of secondary sources and the application of statistical methods of correlation-regression and cluster analysis. Macroeconomic indicators and components of DESI (Digital Economy and Society Index) were used for the analysis. Results. Based on the analysis established that most developed countries have a medium level of digitalization of the business environment and a high level of digitalization of socially oriented public services, while countries with lower GDP focus their policies on building digital infrastructure and training qualified personnel. The study summarizes and analyzes current trends in digital technology, analyzes the level and dynamics of integration of digital technologies of the studied EU countries, the level of development of e-business and e-commerce. The conceptualization of mechanisms of creation of added value in the digital economy is offered and the possible consequences of digitalization of the economy of developing countries are generalized.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.2
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• pp.379-390
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• 2012

This study is to consider political implication of indicators to measure personal information security in public sector studied by Ministry of Public Adminstration and Security from 2008 to 2011. The study analyzed the priority of personal information security policy dividing into personal information security infrastructure, personal information management with life cycle, correspondence of information infringement by scholars, experts, and chargers. As the results, to progress personal information security policy is important to management of personal identification information on web site; specially institutional infrastructure as responsible organization, exclusive manpower, and security budget; personal information security infrastructure. As like the results, it would be reflected in the progress of personal information security policy and tried to provide systematic management program with improving safe information distribution and usefulness.

• Animal Bioscience
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• v.35 no.7
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• pp.1048-1058
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• 2022

Objective: The present study was to investigate the extraction conditions of dietary fiber from dried cassava pulp (DCP) and cassava distiller's dried grains (CDG) under different NaOH concentrations, and the Fourier transform infrared (FTIR) was used to determine the dietary fiber components. Methods: The dried samples (DCP and CDG) were treated with various concentrations of NaOH at levels of 2%, 4%, 6%, and 8% using a completely randomized design with 4 replications of each. After extraction, the residual DCP and CDG dietary fiber were dried in a hot air oven at 55℃ to 60℃. Finally, the oven dried extracted dietary fiber was powdered to a particle size of 1 mm. Both extracted dietary fibers were analyzed for their chemical composition and determined by FTIR. Results: The DCP and CDG treated with NaOH linearly or quadratically or cubically (p<0.05) increased the total dietary fiber (TDF) and insoluble fiber (IDF). The optimal conditions for extracting dietary fiber from DCP and CDG were under treatment with 6% and 4% NaOH, respectively, as these conditions yielded the highest TDF and IDF contents. These results were associated with the FTIR spectra integration for a semi-quantitative analysis, which obtained the highest cellulose content in dietary fiber extracted from DCP and CDG with 6% and 4% NaOH solution, respectively. The principal component analysis illustrated clear separation of spectral distribution in cassava pulp extracted dietary fiber (DFCP) and cassava distiller's dried grains extracted dietary fiber (DFCDG) when treated with 6% and 4% NaOH, respectively. Conclusion: The optimal conditions for the extraction of dietary fiber from DCP and CDG were treatment with 6% and 4% NaOH solution, respectively. In addition, FTIR spectroscopy proved itself to be a powerful tool for fiber identification.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.294-302
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• 2022

Detection of fake news is a complex and a challenging task. Generation of fake news is very hard to stop, only steps to control its circulation may help in minimizing its impacts. Humans tend to believe in misleading false information. Researcher started with social media sites to categorize in terms of real or fake news. False information misleads any individual or an organization that may cause of big failure and any financial loss. Automatic system for detection of false information circulating on social media is an emerging area of research. It is gaining attention of both industry and academia since US presidential elections 2016. Fake news has negative and severe effects on individuals and organizations elongating its hostile effects on the society. Prediction of fake news in timely manner is important. This research focuses on detection of fake news spreaders. In this context, overall, 6 models are developed during this research, trained and tested with dataset of PAN 2020. Four approaches N-gram based; user statistics-based models are trained with different values of hyper parameters. Extensive grid search with cross validation is applied in each machine learning model. In N-gram based models, out of numerous machine learning models this research focused on better results yielding algorithms, assessed by deep reading of state-of-the-art related work in the field. For better accuracy, author aimed at developing models using Random Forest, Logistic Regression, SVM, and XGBoost. All four machine learning algorithms were trained with cross validated grid search hyper parameters. Advantages of this research over previous work is user statistics-based model and then ensemble learning model. Which were designed in a way to help classifying Twitter users as fake news spreader or not with highest reliability. User statistical model used 17 features, on the basis of which it categorized a Twitter user as malicious. New dataset based on predictions of machine learning models was constructed. And then Three techniques of simple mean, logistic regression and random forest in combination with ensemble model is applied. Logistic regression combined in ensemble model gave best training and testing results, achieving an accuracy of 72%.

• Genomics & Informatics
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• v.19 no.4
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• pp.38.1-38.7
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• 2021

Kawasaki disease (KD) is an acute pediatric vasculitis that affects genetically susceptible infants and children. To identify coding variants that influence susceptibility to KD, we conducted whole exome sequencing of 159 patients with KD and 902 controls, and performed a replication study in an independent 586 cases and 732 controls. We identified five rare coding variants in five genes (FCRLA, PTGER4, IL17F, CARD11, and SIGLEC10) associated with KD (odds ratio [OR], 1.18 to 4.41; p = 0.0027-0.031). We also performed association analysis in 26 KD patients with coronary artery aneurysms (CAAs; diameter > 5 mm) and 124 patients without CAAs (diameter < 3 mm), and identified another five rare coding variants in five genes (FGFR4, IL31RA, FNDC1, MMP8, and FOXN1), which may be associated with CAA (OR, 3.89 to 37.3; p = 0.0058- 0.0261). These results provide insights into new candidate genes and genetic variants potentially involved in the development of KD and CAA.

• Genomics & Informatics
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• v.20 no.3
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• pp.35.1-35.9
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• 2022

Microsatellites or simple sequence repeats are motifs of 1 to 6 nucleotides in length present in both coding and non-coding regions of DNA. These are found widely distributed in the whole genome of prokaryotes, eukaryotes, bacteria, and viruses and are used as molecular markers in studying DNA variations, gene regulation, genetic diversity and evolutionary studies, etc. However, in vitro microsatellite identification proves to be time-consuming and expensive. Therefore, the present research has been focused on using an in-house built java pipeline to identify, analyse, design primers and find related statistics of perfect and compound microsatellites in the seven complete genome sequences of coronavirus, including the genome of coronavirus disease 2019, where the host is Homo sapiens. Based on search criteria among seven genomic sequences, it was revealed that the total number of perfect simple sequence repeats (SSRs) found to be in the range of 76 to 118 and compound SSRs from 01 to10, thus reflecting the low conversion of perfect simple sequence to compound repeats. Furthermore, the incidence of SSRs was insignificant but positively correlated with genome size (R² = 0.45, p > 0.05), with simple sequence repeats relative abundance (R² = 0.18, p > 0.05) and relative density (R² = 0.23, p > 0.05). Dinucleotide repeats were the most abundant in the coding region of the genome, followed by tri, mono, and tetra. This comparative study would help us understand the evolutionary relationship, genetic diversity, and hypervariability in minimal time and cost.

• Earthquakes and Structures
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• v.22 no.2
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• pp.185-201
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• 2022

Structural Health Monitoring (SHM) is used to provide reliable information about the structure's integrity in near realtime following extreme incidents such as earthquakes, considering the inevitable aging and degradation that occurs in operating environments. This paper experimentally investigates an integrated wireless sensor network (Wi-SN) based monitoring technique for damage detection in concrete structures. An effective SHM technique can be used to detect potential structural damage based on post-earthquake data. Two novel methods are proposed for damage detection in reinforced concrete (RC) building structures including: (i) Jerk Energy Method (JEM), which is based on time-domain analysis, and (ii) Modal Contributing Parameter (MCP), which is based on frequency-domain analysis. Wireless accelerometer sensors are installed at each story level to monitor the dynamic responses from the building structure. Prior knowledge of the initial state (immediately after construction) of the structure is not required in these methods. Proposed methods only use responses recorded during ambient vibration state (i.e., operational state) to estimate the damage index. Herein, the experimental studies serve as an illustration of the procedures. In particular, (i) a 3-story shear-type steel frame model is analyzed for several damage scenarios and (ii) 2-story RC scaled down (at 1/6th) building models, simulated and verified under experimental tests on a shaking table. As a result, in addition to the usual benefits like system adaptability, and cost-effectiveness, the proposed sensing system does not require a cluster of sensors. The spatial information in the real-time recorded data is used in global damage identification stage of SHM. Whereas in next stage of SHM, the damage is detected at the story level. Experimental results also show the efficiency and superior performance of the proposed measuring techniques.

• Physical Therapy Korea
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• v.30 no.2
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• pp.136-143
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• 2023

Background: The International Classification of Functioning, Disability and Health (ICF) model, created by the World Health Organization, provides a theoretical framework that can be applied in the diagnosis and treatment of various disorders. Objects: Our research purposed to ascertain the relationship between structure/function, activity, and participation domain variables of the ICF and pain, pain-associated disability, activities of daily living (ADL), and quality of life in patients with chronic low back pain (LBP). Methods: Two-hundred patients with chronic LBP (mean age: 35.5 ± 8.8 years, females, n = 40) were recruited from hospital and community settings. We evaluated the body structure/function domain variable using the Numeric Pain Rating Scale (NPRS) and Roland-Morris disability (RMD) questionnaire. To evaluate the activity domain variable, we used the Oswestry Disability Index (ODI) and Quebec Back Pain Disability Scale (QBDS). For clinical outcome measures, we used Short-form 12 (SF-12). Pearson's correlation coefficient was used to ascertain the relationships among the variables (p < 0.05). All the participants with LBP received 30 minutes of conventional physical therapy 3 days/week for 4 weeks. Results: There were significant correlations between the body structure/function domain (NPRS and RMD questionnaire), activity domain (ODI and QBDS), and participation domain variables (SF-12), rending from pre-intervention (r = -0.723 to 0.783) and postintervention (r = -0.742 to 0.757, p < 0.05). Conclusion: The identification of a significant difference between these domain variables point to important relationships between pain, disability, performance of ADL, and quality in participants with LBP.