• Fisheries and Aquatic Sciences
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• v.21 no.2
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• pp.6.1-6.10
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• 2018

The intention of this study was to identify the bacterial pathogens infecting Oreochromis niloticus (Nile tilapia) and Clarias gariepinus (African catfish), and to establish the antibiotic susceptibility of fish bacteria in Uganda. A total of 288 fish samples from 40 fish farms (ponds, cages, and tanks) and 8 wild water sites were aseptically collected and bacteria isolated from the head kidney, liver, brain and spleen. The isolates were identified by their morphological characteristics, conventional biochemical tests and Analytical Profile Index test kits. Antibiotic susceptibility of selected bacteria was determined by the Kirby-Bauer disc diffusion method. The following well-known fish pathogens were identified at a farm prevalence of; Aeromonas hydrophila (43.8%), Aeromonas sobria (20.8%), Edwardsiella tarda (8.3%), Flavobacterium spp. (4.2%) and Streptococcus spp. (6.3%). Other bacteria with varying significance as fish pathogens were also identified including Plesiomonas shigelloides (25.0%), Chryseobacterium indoligenes (12.5%), Pseudomonas fluorescens (10.4%), Pseudomonas aeruginosa (4.2%), Pseudomonas stutzeri (2.1%), Vibrio cholerae (10.4%), Proteus spp. (6.3%), Citrobacter spp. (4.2%), Klebsiella spp. (4.2%) Serratia marcescens (4.2%), Burkholderia cepacia (2.1%), Comamonas testosteroni (8.3%) and Ralstonia picketti (2.1%). Aeromonas spp., Edwardsiella tarda and Streptococcus spp. were commonly isolated from diseased fish. Aeromonas spp. (n = 82) and Plesiomonas shigelloides (n = 73) were evaluated for antibiotic susceptibility. All isolates tested were susceptible to at-least ten (10) of the fourteen antibiotics evaluated. High levels of resistance were however expressed by all isolates to penicillin, oxacillin and ampicillin. This observed resistance is most probably intrinsic to those bacteria, suggesting minimal levels of acquired antibiotic resistance in fish bacteria from the study area. To our knowledge, this is the first study to establish the occurrence of several bacteria species infecting fish; and to determine antibiotic susceptibility of fish bacteria in Uganda. The current study provides baseline information for future reference and fish disease management in the country.

• Journal of the Korean Society of Marine Environment & Safety
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• v.17 no.3
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• pp.257-264
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• 2011

On April 20, 2010, semi-submersible offshore drilling unit Deepwater Horizon was exploded and sank, and 4.9 million barrels(about 778 thousand tons) of crude oil was spilled into the Gulf of Mexico. As more than one year has been passed since the incident, a lot of investigation reports and lessons learned have been made public and also a lot more will be released soon. This paper studies the final report of the National Commission on "the BP Deepwater Horizon Oil Spill and Offshore Drilling", which was organized by the executive directive of U.S. President Barack Obama, and the interim report of Joint Investigation team of U.S. Coast Guard and BOEMRE of "Report of Investigation into the Circumstances Surrounding the Explosion, Fire, Sinking and Loss of Eleven Members Aboard the Mobile Offshore Drilling Unit Deepwater Horizon". The review is focused on the response to the oil spill. And the paper suggests how to improve national marine pollution response policy. In the paper, the Korean governments is suggested to reinforce the capability for instructing and supervising the responsible party's source control measures, to review how to introduce in-situ burning and vessel of opportunity program into our country, and to continue monitoring on the progress of developments of R&D projects related to oil spill response in the U.S..

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.169-177
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• 2020

In South Korea, the results of R&D in science and technology are submitted to the National Science and Technology Information Service (NTIS) in reports that have Korea national science and technology standard classification codes (K-NSCC). However, considering there are more than 2000 sub-categories, it is non-trivial to choose correct classification codes without a clear understanding of the K-NSCC. In addition, there are few cases of automatic document classification research based on the K-NSCC, and there are no training data in the public domain. To the best of our knowledge, this study is the first attempt to build a highly performing K-NSCC classification system based on NTIS report meta-information from the last five years (2013-2017). To this end, about 210 mid-level categories were selected, and we conducted preprocessing considering the characteristics of research report metadata. More specifically, we propose a convolutional neural network (CNN) technique using only task names and keywords, which are the most influential fields. The proposed model is compared with several machine learning methods (e.g., the linear support vector classifier, CNN, gated recurrent unit, etc.) that show good performance in text classification, and that have a performance advantage of 1% to 7% based on a top-three F1 score.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.17-34
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• 2021

This study aimed to examine the Factor Structure of the teacher satisfaction scale (TSS) with distance education during the Covid-19 pandemic, as well as affirming the (Factorial Invariance) according to gender variable. It also aimed at identifying the degree of satisfaction according to some demographic variables of the sample. The study population consisted of all teachers in public education and faculty members in higher education in the Kingdom of Saudi Arabia. The (TSS) was applied to a random sample representing the study population consisting of (2399) respondents. The results of the study showed that the scale consists of five main factors, with a reliability value of (0.94). The scale also showed a high degree of construct validity through fit indices of the confirmatory factor analysis. The results have shown a gradual consistency of the measure's invariance that reaches the third level (Scalar-invariance) of the Measurement Invariance across the gender variable. The results also showed that the average response of the study sample on the scale reached (3.74) with a degree of satisfaction, as there are no statistically significant differences between the averages of the study sample responses with respect to the gender variable. While there were statistically significant differences in the averages with respect to the variable of the educational level in favor of the middle school and statistically significant differences in the averages attributed to the years of experience variable in favor of those whose experience is less than (5) years.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.565-572
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• 2019

As a public research institute, government-supported institutes have led the industrial development and the advancement of science and technology in Korea. Robert Levering has annually selected 'Fortune 100 GPTW(Great Place to Work)' by measuring the Trust Index which was originated by himself. The objectives of this study are to attempt newly to analyze the inter-relations among 5 elements of GPTW trust index such as credibility, respect, fairness, camaraderie, and pride perceived by the K institute's 262 employees; to verify that GPTW trust index is valid for the selection of the fortune 100 GPTW. Amart PLS 2.0 and SPSS 18 were utilized for the statistical analysis. The results of this study are as follows. Credibility has positive effect to pride; respect has positive effect to pride and camaraderie; fairness has positive effect to camaraderie; and camaraderie has positive to pride. Pride and camaraderie have positive effect to the perceived GPTW. Recent studies mainly focused on the relations between GPTW trust index as independent, mediating variables or parameters and organizational performances. It is meaningful that this study has firstly tried to analyze the inter-relations among 5 elements of the trust index for the employees of research institute. This study has implication that the in order to enhance the performance the institute has to manage GPTW trust index perceived by the employees.

• The Korean Journal of Applied Statistics
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• v.32 no.2
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• pp.173-185
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• 2019

Causal questions are prevalent in scientific research, for example, how effective a treatment was for preventing an infectious disease, how much a policy increased utility, or which advertisement would give the highest click rate for a given customer. Causal inference theory in statistics interprets those questions as inferring the effect of a given intervention (treatment or policy) in the data generating process. Causal inference has been used in medicine, public health, and economics; in addition, it has received recent attention as a tool for data-driven decision making processes. Many recent datasets are observational, rather than experimental, which makes the causal inference theory more complex. This review introduces key concepts and recent trends of statistical causal inference in observational studies. We first introduce the Neyman-Rubin's potential outcome framework to formularize from causal questions to average treatment effects as well as discuss popular methods to estimate treatment effects such as propensity score approaches and regression approaches. For recent trends, we briefly discuss (1) conditional (heterogeneous) treatment effects and machine learning-based approaches, (2) curse of dimensionality on the estimation of treatment effect and its remedies, and (3) Pearl's structural causal model to deal with more complex causal relationships and its connection to the Neyman-Rubin's potential outcome model.

• Animal Bioscience
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• v.35 no.8
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• pp.1250-1257
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• 2022

Objective: Low fat duck meat sausages were prepared by replacing the fat in the formulations with soy protein isolate (SPI) and inulin to find the best formulation having superior shelf-life without affecting its quality attributes. Methods: Four sausage mix formulations were prepared viz.control (0% SPI and inulin), T₁ (2.5% inulin), T₂ (2.5% SPI), and T₃ (2.5% SPI+2.5% inulin) replacing duck fat as per the recipe. Five batches of duck meat sausages of each formulation were prepared, and the final products were evaluated for physico-chemical, organoleptic, and microbiological qualities. Results: The % moisture and crude protein content of the sausages revealed an increasing trend (p<0.01) from control to the treated formulations, while the % total ash contents were found to be non-significant (p>0.05). On the contrary, the per cent ether extract decreased significantly (p<0.01) from the control to the treated groups. In terms of calorie value, control samples exhibited the highest values with a significant (p<0.01) regression from control to treated formulation, respectively. The colour profile study (L, a^*, b^*) of the formulations were found to be non-significant. Texture profile study in terms of springiness, cohesiveness, chewiness, and resilience revealed no significant difference in all the treatment groups except the hardness scores, which revealed a significantly (p<0.01) increasing trend from control to the treated formulations. The total viable count showed a significant decrease in the treated groups. However, there was a significant increase in the bacterial load during the storage till day 15th. The total viable psychrophilic bacterial count showed a significant (p<0.01) increase in bacterial load from day 5th to 15th day of storage. Colititre counts were negative for all the formulations until the 15th day of storage. Conclusion: The present study results may conclude that duck meat sausages could be prepared satisfactorily by replacing duck fat with SPI and inulin at the rate of 2.5% of each with superior quality attributes.

• Resources Recycling
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• v.31 no.4
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• pp.3-11
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• 2022

Owing to the increasing demand for electric vehicles (EVs), appropriate management of their waste batteries is required urgently for scrapped vehicles or for addressing battery aging. With respect to technological developments, data-driven diagnosis of waste EV batteries and management technologies have drawn increasing attention. Moreover, robot-based automatic dismantling technologies, which are seemingly interesting, require industrial verifications and linkages with future battery-related database systems. Among these, it is critical to develop and disseminate various advanced battery diagnosis and assessment techniques to improve the efficiency and safety/environment of the recirculation of waste batteries. Incorporation of lithium-related chemical substances in the public pollutant release and transfer register (PRTR) database as well as in-depth risk assessment of gas emissions in waste EV battery combustion and their relevant fire safety are some of the necessary steps. Further research and development thus are needed for optimizing the lifecycle management of waste batteries from various aspects related to data-based diagnosis/classification/disassembly processes as well as reuse/recycling and final disposal. The idea here is that the data should contribute to clean design and manufacturing to reduce the environmental burden and facilitate reuse/recycling in future production of EV batteries. Such optimization should also consider the future technological and market trends.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.179-184
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• 2021

Along with the development of the fourth industry, the public sector has increasingly paid more attention to search using drones and real-time monitoring, for various goals. The drones are used and researched to complete a variety of searching and monitoring missions, including search for missing persons, security, coastal patrol and monitoring, speed enforcement, highway and urban traffic monitoring, fire and wildfire monitoring, monitoring of illegal fishing in reservoirs and protest rally monitoring. Police stations, fire departments and military authorities, however, concentrate on the hardware part, so there are little research on efficient communication systems for the real-time monitoring of data collected from high-performance resolution and infrared thermal imagining cameras, and analysis programs suitable for special missions. In order to increase the efficiency of drones with the searching mission, this paper, therefore, attempts to propose an image analysis technique to increase the precision of search by producing image data suitable for searching missions, based on images obtained from drones and provide the foundation for improving relevant policies and establishing proper platforms, based on actual field cases and experiments.

• Journal of Industrial Convergence
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• v.20 no.12
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• pp.87-96
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• 2022

The Ministry of Land, Infrastructure and Transport has also been promoting the commercialization of land transport technology to commercialize the technologies owned by small and medium-sized venture companies, and to support the transfer and commercialization of public technologies. At this point, in order to improve the investment effect of subsequent new projects and to select excellent research institutes, it is necessary to establish a valid evaluation index system suitable for the purpose of the project. The evaluation index system for subsequent new projects should be linked to the project objectives and goals of the preceding project, and should be selected in consideration of existing evaluation indicators to prevent interruption of research results. Therefore, this thesis sets the evaluation index system into multiple scenarios through hierarchical cluster analysis using the evaluation result data for each evaluation committee for small and medium venture companies participating in the land transportation technology commercialization support project, and then analyzes the structural equation model. As a result of scenario analysis, considering the measurement effect of each path representing the causal relationship between evaluation indicators and the effect of each evaluation index on evaluation items, the scenario with the highest impact on the evaluation result was selected as an improvement plan.