• Fisheries and Aquatic Sciences
• /
• v.22 no.12
• /
• pp.31.1-31.12
• /
• 2019

Background: The black-chinned tilapia, Sarotherodon melanotheron, is the most abundant fish species in the Nakwa (an open lagoon) and Brenu (a closed lagoon) in the Central Region of Ghana. Aspects of the life history characteristics and the ecology of the fish populations in both lagoons were studied to assess the bio-ecological status of this important resource. Methods: Fish samples were obtained from fishermen that fish on the Nakwa and Brenu lagoons using cast, drag and gill nets. The age of the fish was assessed from otoliths analysis and its growth modelled following the von Bertalanffy growth function. Morphometric characteristics of the fish populations were analysed using power regression and ANOVA for parameters comparisons, and Student's t test to determine whether species grew isometrically. The percentage occurrence method was used to analyse the stomach contents of the fish. Results: A total of 382 fish samples from both lagoons were measured, comprising 209 from Nakwa lagoon and 176 from Brenu lagoon. The size and weight of fish samples ranged between 3.9-11.5 cm total length and 1.0-27.3 g for Nakwa Lagoon and 5.6-12.8 cm total length and 3.2-29.8 g for the Brenu Lagoon. The estimated von Bertalanffy growth parameters were L∞ = 12.04 cm and K = 2.76/year for the Nakwa Lagoon samples and L∞ = 13.44 cm and K = 3.27/year for Brenu Lagoon samples. Daily otolith incremental rate ranged from 0.01-0.03 mm per day to 0.01-0.02 mm per day for Nakwa and Brenu lagoons, respectively. Stomach content analysis of the fish samples revealed that the species are planktivorous and the range of food varied between the lagoons. Green algae were the most prevalent food item in the stomachs of the fish samples from Nakwa with the frequency of 69% whilst diatoms (80.5%) were most prevalent phytoplanktonic food item for the fish in Brenu lagoon. Conclusions: The estimates of asymptotic length for the species in both lagoons are close to known values of the species length at first sexual maturity and points to intensive fishing pressure. As a consequence, a comprehensive sample-based survey is required in both lagoons to derive estimates of management reference points. The results of the stomach content analysis are beneficial to the construction of diet matrix for ecosystem models of the two systems.

• International Journal of Contents
• /
• v.11 no.1
• /
• pp.41-51
• /
• 2015

Management systems for electronic library have been developed on the basis of Client/Server or ASP framework in domestic market for a long time. Therefore, both service provider and user suffer from their high cost and effort in management, maintenance, and repairing of software as well as hardware. Recently in addition, mobile devices like smartphone and tablet PC are frequently used as terminal devices to access computers through the Internet or other networks, sophisticatedly customized or personalized interface for n-screen service became more important issue these days. In this paper, we propose a new scheme of integrated management system for electronic library based on SaaS and Web Standard. We design and implement the proposed scheme applying Electronic Cabinet Guidelines for Web Standard and Universal Code System. Hosted application management style and software on demand style service models based on SaaS are basically applied to develop the management system. Moreover, a newly improved concept of duplication check algorithm in a hierarchical evaluation process is presented and a personalized interface based on web standard is applied to implement the system. Algorithms of duplication check for journal, volume/number, and paper are hierarchically presented with their logic flows. Total framework of our development obeys the standard feature of Electronic Cabinet Guidelines offered by Korea government so that we can accomplish standard of application software, quality improvement of total software, and reusability extension. Scope of our development includes core services of library automation system such as acquisition, list-up, loan-and-return, and their related services. We focus on interoperation compatibility between elementary sub-systems throughout complex network and structural features. Reanalyzing and standardizing each part of the system under the concept on the cloud of service, we construct an integrated development environment for generating, test, operation, and maintenance. Finally, performance analyses are performed about resource usability of server, memory amount used, and response time of server etc. As a result of measurements fulfilled over 5 times at different test points and using different data, the average response time is about 62.9 seconds for 100 clients, which takes about 0.629 seconds per client on the average. We can expect this result makes it possible to operate the system in real-time level proof. Resource usability and memory occupation are also good and moderate comparing to the conventional systems. As total verification tests, we present a simple proof to obey Electronic Cabinet Guidelines and a record of TTA authentication test for topics about SaaS maturity, performance, and application program features.

• Journal of Christian Education in Korea
• /
• v.61
• /
• pp.203-232
• /
• 2020

The purpose of this study was to analyze various factors that influence the academic life of students through a theoretical review. As a result of the analysis, sub-factors were derived to diagnose the factors. From the study's findings, principles and models for developing learning status diagnosis tools were designed. The study first, based upon the competencies of university students, university life, students' low academic achievement, and academic probation studies, confirmed what factors affect student learning and from them derived a set of sub-factors. The setting dimension was divided into psychology, learning, and career factors, while also including a factor of faith for Christian university students. Next, in the draft model, sub-factors were constructed for each factor: faith maturity and faith training in the faith factor, positive thinking, emotion regulation, and self-esteem in the psychology factor, self-directed learning ability, learning motivation, and learning strategies in the learning factor, and career reflection, career exploration, career management, and career barriers in the career factor. By using the Delphi method, the final model of learning status diagnosis was confirmed. As a result, we completed the model comprised of nine sub-factors in four parts. A follow-up study should be conducted that examines learning status diagnosis tools development research.

• Journal of Internet Computing and Services
• /
• v.10 no.5
• /
• pp.195-209
• /
• 2009

The embedded software has been become more important than the hardware in mobile systems in ubiquitous society. The improvement models such as CMMI(Capability Maturity Model Integration) and SPICE(Software Process Improvement and Capability dEtermination) are used to improve the quality of software in general systems. Software process improvement is also necessary for mobile embedded software development to improve its quality. It is not easy to apply the general software improvement model to the mobile embedded software development due to the high cost effectiveness and heavy process. On the other hand, XP has the characteristics on focused communications with customers and iteration development. It is specially suitable for mobile embedded software development as depending on customer's frequent requirement changes and hardware attributes. In this paper, we propose a framework for development small process improvement based XP(eXtreme Programming)'s practice in order to accomplish CMMI level 2 or 3 in mobile embedded software development at the small organizations. We design and implement the Mobile Embedded Software Process Improvement System(MESPIS) to support process improvement. We also suggest the evaluation method for the mobile embedded software development process improvement framework with CMMI coverage check by comparing other process improvement model. In the future, we need to apply this proposed framework to real project for practical effectiveness and the real cases quantitative. It also include the enhance the functionality of MESPIS.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.19 no.4
• /
• pp.246-251
• /
• 2017

Crop models have been used to predict a heading date for efficient management of fertilizer application. Recently, the ORYZA (v3) model was developed to improve the ORYZA2000 model, which has been used for simulation of rice growth in Korea. Still, little effort has been made to assess applicability of the ORYZA (v3) model to rice farms in Korea. The objective of this study was to evaluate reliability of heading dates predicted using the the ORYZA (v3) model, which would indicate applicability of the model to a decision support system for fertilizer application. Field experiments were conducted from 2015-2016 at the Rural Development Administration (RDA) to obtain rice phenology data. Shindongjin cultivar which is mid-late maturity type was grown under a conventional fertilizer management, e.g., application of fertilizer at the rate of 11 Kg N/10a. Another set of heading dates was obtained from annual reports at experiment farms operated by the National Institute of Crop Science and Agricultural Technology Centers in each province. The input files for the ORYZA (v3) model were prepared using weather and soil data collected from the Korean Meteorology Administration (KMA) and the Korean Soil Information System, respectively. Input parameters for crop management, e.g., transplanting date and planting density, were set to represent management used for the field experiment. The ORYZA (v3) model predicted heading date within 1 day for two seasons. The crop model also had a relatively small error in prediction of heading date for three ecotypes of rice cultivars at experiment farms where weather input data were obtained from a near-by weather station. Those results suggested that the ORYZA (v3) model would be useful for development of a decision support system for fertilizer application when reliable input data for weather variables become available.

• Korean Journal of Poultry Science
• /
• v.49 no.4
• /
• pp.229-237
• /
• 2022

This study investigated the growth characteristics of four strains of newly developed synthetic Korean native commercial chickens (KNCs). We investigated a suitable growth curve model in KNCs and estimated the number of days to reach a 2 kg market weight. Body weight was measured at 2-week intervals from birth to 12 weeks of age. The growth curves were estimated using von Berteralanffy, Gompertz, and logistic functions. The results showed that males were significantly heavier than females at all ages, but there were no significant differences in body weight between strains, except at birth and 2 and 6 weeks of age. The coefficients of determination and adjusted determination of growth function had high goodness-of-fit (97.4~99.7). Of the growth curve parameters, the mature weight and growth ratio were higher in males than in females, but the maturity rate was similar in males and females. The inflection point occurred at approximately 7 weeks of age for females and 8 to 9 weeks of age for males. The weights estimated from the growth curve functions almost agreed with the actual weights, except for male weights estimated using the von Bertalanffy function. The coefficients of determination of the regression equations for weight to age were 0.9583 to 0.9746. The 8- and 10-week-old body weights estimated using the regression equation, and the 12-week-old weight estimated using the logistic function were most similar to the actual weight. Using these models, the estimated age of KNCs to reach 2 kg was 62.0~64.6 days for males and 74.9~78.6 days for females.

• The korean journal of orthodontics
• /
• v.31 no.2 s.85
• /
• pp.159-172
• /
• 2001

Three dimensional analysis of malocclusion and craniofacial deformation is essential for the successful orthodontic treatment. But the orthodontists are not familiar with diagnosis and treatment plane based on lateral cephalometric analysis. Since orthodontists do not posses a sufficient knowledge in standard value of posteroanterior cephalometric anaysis and of clinical importance for transverse jaw growth. In this study male(n=130) and female(n=171) aged from 6 to 16 and diagnosed as Class I malocclusion were selected to analysis width of cranium, maxilla and mandible on the posteroanterior cephalogram. The changes as a function of chronologic age and cervical vertebrae maturity index(CVXI) were examined. The Proper regression model was selected by sex with polynominal regression models and method of variable selection. Mean of each measurements and 70% confidence interval of individual measurement according to age was assesed and a graphs were made. Results are as follows :1. All the measurements for the width are gradually incresed as increase in chronologic age and CVMI. From the total amount of change between age 6 and 16, there is a tendency that mandibular width is broader than maxillary width and the width of male is broader than female. 2. There is no statistically significant sexual difference in Mx-Mn difference, Mx-Mn width differential, Mx/Mn ratio according to age and CVMI. 3. Mean of each measurement and 70% confidence interval of individual measurement according to age and sex were assessed and graphs were made for maxillary width, mandibular width, Mx-Mn difference, Mx/Mn ratio. 4. The width of maxilla and mandible in Korean children are broader than Western children during growth period.

• Journal of Intelligence and Information Systems
• /
• v.20 no.4
• /
• pp.141-154
• /
• 2014

The adoption of International Financial Reporting Standards (IFRS) is the one of important issues in the recent accounting research because the change from local GAAP (Generally Accepted Accounting Principles) to IFRS has a substantial effect on accounting information. Over 100 countries including Australia, China, Canada and the European Union member countries adopt IFRS (International Financial Reporting Standards) for financial reporting purposes, and several more including the United States and Japan are considering the adoption of IFRS (International Financial Reporting Standards). In Korea, 61 firms voluntarily adopted Korean International Financial Reporting Standard (K-IFRS) in 2009 and 2010 and all listed firms mandatorily adopted K-IFRS (Korea-International Financial Reporting Standards) in 2011. The adoption of IFRS is expected to increase financial statement comparability, improve corporate transparency, increase the quality of financial reporting, and hence, provide benefits to investors This study investigates whether recognized accounts receivable discounting (AR discounting) under Korean International Financial Reporting Standard (K-IFRS) is more value relevant than disclosed AR discounting under Korean Generally Accepted Accounting Principles (K-GAAP). Because more rigorous standards are applied to the derecognition of AR discounting under K-IFRS(Korea-International Financial Reporting Standards), most AR discounting is recognized as a short term debt instead of being disclosed as a contingent liability unless all risks and rewards are transferred. In this research, I try to figure out industrial responses to the changes in accounting rules for the treatment of accounts receivable toward more strict standards in the recognition of sales which occurs with the adoption of Korea International Financial Reporting Standard. This study examines whether accounting information is more value-relevant, especially information on accounts receivable discounting (hereinafter, AR discounting) is value-relevant under K-IFRS (Korea-International Financial Reporting Standards). First, note that AR discounting involves the transfer of financial assets. Under Korean Generally Accepted Accounting Principles (K-GAAP), when firms discount AR to banks before the AR maturity, firms conventionally remove AR from the balance-sheet and report losses from AR discounting and disclose and explain the transactions in the footnotes. Under K-IFRS (Korea-International Financial Reporting Standards), however, most firms keep AR and add a short-term debt as same as discounted AR. This process increases the firms' leverage ratio and raises the concern to the firms about investors' reactions to worsening capital structures. Investors may experience the change in perceived risk of the firm. In the study sample, the average of AR discounting is 75.3 billion won (maximum 3.6 trillion won and minimum 18 million won), which is, on average 7.0% of assets (maximum 38.6% and minimum 0.002%), 26.2% of firms' accounts receivable (maximum 92.5% and minimum 0.003%) and 13.5% of total liabilities (maximum 69.5% and minimum 0.004%). After the adoption of K-IFRS (Korea-International Financial Reporting Standards), total liabilities increase by 13%p on average (maximum 103%p and minimum 0.004%p) attributable to AR discounting. The leverage ratio (total liabilities/total assets) increases by an average 2.4%p (maximum 16%p and minimum 0.001%p) and debt-to-equity ratio increases by average 14.6%p (maximum 134%p and minimum 0.006%) attributable to the recognition of AR discounting as a short-term debt. The structure of debts and equities of the companies engaging in factoring transactions are likely to be affected in the changes of accounting rule. I suggest that the changes in accounting provisions subsequent to Korea International Financial Reporting Standard adoption caused significant influence on the structure of firm's asset and liabilities. Due to this changes, the treatment of account receivable discounting have become critical. This paper proposes an intelligent diagnostic system for estimating negative impact on stock value with self-organizing maps and case based reasoning. To validate the usefulness of this proposed model, real data was analyzed. In order to get the significance of this proposed model, several models were compared to the research model. I found out that this proposed model provides satisfactory results with compared models.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.2 no.2
• /
• pp.47-61
• /
• 2000

Agroclimatic zoning was done for paddy rice culture in North Korea based on a simulation experiment. Daily weather data for the experiment were generated by 3 steps consisting of spatial interpolation based on topoclimatological relationships, zonal summarization of grid cell values, and conversion of monthly climate data to daily weather data. Regression models for monthly climatological temperature estimation were derived from a statistical procedure using monthly averages of 51 standard weather stations in South and North Korea (1981-1994) and their spatial variables such as latitude, altitude, distance from the coast, sloping angle, and aspect-dependent field of view (openness). Selected models (0.4 to 1.6$^{\circ}C$ RMSE) were applied to the generation of monthly temperature surface over the entire North Korean territory on 1 km$\times$l km grid spacing. Monthly precipitation data were prepared by a procedure described in Yun (2000). Solar radiation data for 27 North Korean stations were reproduced by applying a relationship found in South Korea ([Solar Radiation, MJ m$^{-2}$ day$^{-1}$ ] =0.344 + 0.4756 [Extraterrestrial Solar Irradiance) + 0.0299 [Openness toward south, 0 - 255) - 1.307 [Cloud amount, 0 - 10) - 0.01 [Relative humidity, %), $r^2$=0.92, RMSE = 0.95 ). Monthly solar irradiance data of 27 points calculated from the reproduced data set were converted to 1 km$\times$1 km grid data by inverse distance weighted interpolation. The grid cell values of monthly temperature, solar radiation, and precipitation were summed up to represent corresponding county, which will serve as a land unit for the growth simulation. Finally, we randomly generated daily maximum and minimum temperature, solar irradiance and precipitation data for 30 years from the monthly climatic data for each county based on a statistical method suggested by Pickering et a1. (1994). CERES-rice, a rice growth simulation model, was tuned to accommodate agronomic characteristics of major North Korean cultivars based on observed phenological and yield data at two sites in South Korea during 1995~1998. Daily weather data were fed into the model to simulate the crop status at 183 counties in North Korea for 30 years. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to score the suitability of the county for paddy rice culture.

• Journal of Intelligence and Information Systems
• /
• v.24 no.1
• /
• pp.101-124
• /
• 2018

Recently, most of the technologies have been developed in various forms through the advancement of single technology or interaction with other technologies. Particularly, these technologies have the characteristic of the convergence caused by the interaction between two or more techniques. In addition, efforts in responding to technological changes by advance are continuously increasing through forecasting promising convergence technologies that will emerge in the near future. According to this phenomenon, many researchers are attempting to perform various analyses about forecasting promising convergence technologies. A convergence technology has characteristics of various technologies according to the principle of generation. Therefore, forecasting promising convergence technologies is much more difficult than forecasting general technologies with high growth potential. Nevertheless, some achievements have been confirmed in an attempt to forecasting promising technologies using big data analysis and social network analysis. Studies of convergence technology through data analysis are actively conducted with the theme of discovering new convergence technologies and analyzing their trends. According that, information about new convergence technologies is being provided more abundantly than in the past. However, existing methods in analyzing convergence technology have some limitations. Firstly, most studies deal with convergence technology analyze data through predefined technology classifications. The technologies appearing recently tend to have characteristics of convergence and thus consist of technologies from various fields. In other words, the new convergence technologies may not belong to the defined classification. Therefore, the existing method does not properly reflect the dynamic change of the convergence phenomenon. Secondly, in order to forecast the promising convergence technologies, most of the existing analysis method use the general purpose indicators in process. This method does not fully utilize the specificity of convergence phenomenon. The new convergence technology is highly dependent on the existing technology, which is the origin of that technology. Based on that, it can grow into the independent field or disappear rapidly, according to the change of the dependent technology. In the existing analysis, the potential growth of convergence technology is judged through the traditional indicators designed from the general purpose. However, these indicators do not reflect the principle of convergence. In other words, these indicators do not reflect the characteristics of convergence technology, which brings the meaning of new technologies emerge through two or more mature technologies and grown technologies affect the creation of another technology. Thirdly, previous studies do not provide objective methods for evaluating the accuracy of models in forecasting promising convergence technologies. In the studies of convergence technology, the subject of forecasting promising technologies was relatively insufficient due to the complexity of the field. Therefore, it is difficult to find a method to evaluate the accuracy of the model that forecasting promising convergence technologies. In order to activate the field of forecasting promising convergence technology, it is important to establish a method for objectively verifying and evaluating the accuracy of the model proposed by each study. To overcome these limitations, we propose a new method for analysis of convergence technologies. First of all, through topic modeling, we derive a new technology classification in terms of text content. It reflects the dynamic change of the actual technology market, not the existing fixed classification standard. In addition, we identify the influence relationships between technologies through the topic correspondence weights of each document, and structuralize them into a network. In addition, we devise a centrality indicator (PGC, potential growth centrality) to forecast the future growth of technology by utilizing the centrality information of each technology. It reflects the convergence characteristics of each technology, according to technology maturity and interdependence between technologies. Along with this, we propose a method to evaluate the accuracy of forecasting model by measuring the growth rate of promising technology. It is based on the variation of potential growth centrality by period. In this paper, we conduct experiments with 13,477 patent documents dealing with technical contents to evaluate the performance and practical applicability of the proposed method. As a result, it is confirmed that the forecast model based on a centrality indicator of the proposed method has a maximum forecast accuracy of about 2.88 times higher than the accuracy of the forecast model based on the currently used network indicators.