• Journal of Life Science
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• v.33 no.10
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• pp.828-834
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• 2023

The cDNA that encodes transmembrane protein 258 (Tmem258) was cloned from Gryllus bimaculatus and named GbTmem258. This protein comprises 80 amino acids, has no N-glycosylation site, and contains five potential phosphorylation sites at two serines, two threonines, and one tyrosine. The predicted molecular mass of GbTmem258 is 9.06 kDa, and its theoretical isoelectric point is 5.5. The tertiary structure of GbTmem258 was predicted using the available secondary structure information, which suggests the presence of alpha helices (52.5%), random coils (22.5%), extended strands (16.25%), and beta turns (8.75%). Homology analysis revealed that GbTmem258 exhibits high similarity at the amino-acid level to Tmem258 found in other species. The effect of starvation and refeeding on GbTmem258 mRNA expression was also examined in this study. It was found that GbTmem258 mRNA expression in the hindgut progressively increased throughout the starvation period, peaking at almost 1.5 times the control level after six days of starvation. However, refeeding for one to two days after the six-day starvation period restored GbTmem258 mRNA expression to the control level. In fat body, GbTmem258 mRNA expression was almost 3-fold higher during starvation compared to the control level. Refeeding for one to two days after the six-day fast resulted in a decline in the expression to about a 2.5-fold increase over the control level. Throughout the starving and refeeding periods, no other tissues showed any discernible alterations in GbTmem258 mRNA expression.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.4
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• pp.305-314
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• 2007

We studied spatial and temporal distributions of the phytoplankton and their relationships to physico-chemical environmental factors in the western Jinhae Bay, Korea from November 2003 to August 2004. In most cases, physico-chemical environmental factors showed homogeneous distribution. The phytoplankton communities were composed of mainly diatoms and dinoflagellates, and their standing crops ranged from $16{\times}10^3\;cells\;l^{-1}\;to\;5,845{\times}10^3\;cells\;l^{-1}$ (with a mean value of $555{\times}10^3\;cells\;l^{-1}$). The bloom of phytoplankton was observed in Gohyun Port in the summer. Seasonal variation of phytoplankton standing crops was higher in winter and summer than in spring and autumn. The dominant species were Skeletonema costatum, Akashiwo sanguinea, Pseudo-nitzschia pungens, Dactyliosolen sp., Leptocylindrus danicus, cryptomonads and etc. Especially, S. costatum was predominant in the summer and A. sanguinea (spring and autumn), Pseudo-nitzschia sp. (summer), Guinardia striata (spring), unidentified flagellates (summer) and cryptomonads (spring) appeared to be an opportunistic species. Concentrations of Chl a ranged from $0.6{\mu}g{\cdot}l^{-1}\;to\;16.7{\mu}g{\cdot}l^{-1}$ (with a mean value of $3.4{\mu}g{\cdot}l^{-1}$). The results of the canonical correspondence analysis implies the study area was grouped into the 2 water masses (inner and outer waters of Gohyun Port) and inner waters had higher abundance and Chl a concentration than outer waters. Also, phytoplankton sanding crops were related with temperature, DO and nutrients ($SiO^2$, TN, TP and etc.) in inner waters. Inner water-mass of Gohyun Port expanded between Gacho Is. and Chilchon Is. during the winter.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

• Therapeutic Science for Rehabilitation
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• v.13 no.1
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• pp.35-47
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• 2024

Objective : This study aimed to investigate the association between lifestyle factors and risk of frailty and depressive symptoms among older South Korean adults. Methods : This study included 10,072 individuals aged 65 or older from the 2017 National Survey of Older Koreans, a cohort of community-dwelling older South Koreans. The following lifestyle factors were assessed: physical activity, nutrition management (NM), and leisure/social activity participation (AP). Frailty was measured using the frail scale and depressive symptoms were measured using the Geriatric Depression Scale. Logistic regression analyses were performed to determine the odds ratios. Results : All lifestyle factors were associated with the risk of frailty and depressive symptoms in the study population. Regular exercise (≥3 times/wk, odds ratio [OR] = 0.59, 95% confidence interval [95% CI] = 0.52~0.91; OR = 0.66, 95% CI = 0.59~0.75), active NM (OR = 0.86, 95% CI = 0.80~0.91; OR = 0.81, 95% CI = 0.76~0.86), leisure AP (OR = 0.79, 95% CI = 0.74~0.84; OR = 0.71, 95% CI = 0.66~0.77) and social AP (OR = 0.92, 95% CI = 0.88~0.96; OR = 0.82, 95% CI = 0.78~0.87) were correlated with lower odds ratios of frailty and depressive symptoms. Conclusion : Adopting a healthier lifestyle characterized by regular exercise, balanced nutrition, and active engagement in various activities can effectively reduce the risk of frailty and depressive symptoms among the older population. Ultimately, this study emphasized the essential role of lifestyle choices in promoting the physical and mental well-being of older adults.

• Journal of Astronomy and Space Sciences
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• v.22 no.2
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• pp.147-174
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• 2005

To understand the physical processes that control the high-latitude lower thermospheric dynamics, we quantify the forces that are mainly responsible for maintaining the high-latitude lower thermospheric wind system with the aid of the National Center for Atmospheric Research Thermosphere-Ionosphere Electrodynamics General Circulation Model (NCAR-TIEGCM). Momentum forcing is statistically analyzed in magnetic coordinates, and its behavior with respect to the magnitude and orientation of the interplanetary magnetic field (IMF) is further examined. By subtracting the values with zero IMF from those with non-zero IMF, we obtained the difference winds and forces in the high-latitude 1ower thermosphere(<180 km). They show a simple structure over the polar cap and auroral regions for positive($B_y$ > 0.8|$\overline{B}_z$ |) or negative($B_y$ < -0.8|$\overline{B}_z$|) IMF-$\overline{B}_y$ conditions, with maximum values appearing around -80$^{\circ}$ magnetic latitude. Difference winds and difference forces for negative and positive $\overline{B}_y$ have an opposite sign and similar strength each other. For positive($B_z$ > 0.3125|$\overline{B}_y$|) or negative($B_z$ < -0.3125|$\overline{B}_y$|) IMF-$\overline{B}_z$ conditions the difference winds and difference forces are noted to subauroral latitudes. Difference winds and difference forces for negative $\overline{B}_z$ have an opposite sign to positive $\overline{B}_z$ condition. Those for negative $\overline{B}_z$ are stronger than those for positive indicating that negative $\overline{B}_z$ has a stronger effect on the winds and momentum forces than does positive $\overline{B}_z$ At higher altitudes(>125 km) the primary forces that determine the variations of tile neutral winds are the pressure gradient, Coriolis and rotational Pedersen ion drag forces; however, at various locations and times significant contributions can be made by the horizontal advection force. On the other hand, at lower altitudes(108-125 km) the pressure gradient, Coriolis and non-rotational Hall ion drag forces determine the variations of the neutral winds. At lower altitudes(<108 km) it tends to generate a geostrophic motion with the balance between the pressure gradient and Coriolis forces. The northward component of IMF By-dependent average momentum forces act more significantly on the neutral motion except for the ion drag. At lower altitudes(108-425 km) for negative IMF-$\overline{B}_y$ condition the ion drag force tends to generate a warm clockwise circulation with downward vertical motion associated with the adiabatic compress heating in the polar cap region. For positive IMF-$\overline{B}_y$ condition it tends to generate a cold anticlockwise circulation with upward vertical motion associated with the adiabatic expansion cooling in the polar cap region. For negative IMF-$\overline{B}_z$ the ion drag force tends to generate a cold anticlockwise circulation with upward vertical motion in the dawn sector. For positive IMF-$\overline{B}_z$ it tends to generate a warm clockwise circulation with downward vertical motion in the dawn sector.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.

• Journal of Animal Science and Technology
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• v.54 no.2
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• pp.111-124
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• 2012

Feeding trial was conducted with 80 Hanwoo steers (7.5 months of age, 204.4 kg body weight) for 680 days from growing period to late fattening period to examine the feeding value of whole crop barley silage TMR (BS-TMR) and whole crop rye silage TMR (RS-TMR) on body gain, feed cost, slaughter characteristics and quality characteristics of $longissimus$ $dorsi$ muscle. Dietary treatments were conventional separate feeding of concentrate and rice straw (control), feeding BS TMR up to middle fattening period and same diet as for control during late fattening period (BS-TMR I), feeding BS-TMR for whole experimental period (BS-TMR II), feeding RS TMR up to middle fattening period and same diet as for control during late fattening period (RS-TMR I) and RS TMR for whole experimental period (RS-TMR II). Sixteen castrated calves were assigned to each treatment (4 pens, 4 heads per pen). Pens in each treatment were randomly distributed. Feeding both BS silage TMR and RS silage TMR slightly increased body gain of Hanwoo steers at the stages of growing and early fattening, and increased (P<0.0001) at middle fattening compared to feeding control diet while control diet tended to increase body gain at late fattening stage compared to feeding BS-TMR I, BS-TMR II and RS-TMR I diets. Total body gain was slightly increased in Hanwoo steers fed both I and II for BS and RS TMR compared to that in control diet. Feed cost per kg gain per head was relatively low in the Hanwoo steers fed silage TMRs to that fed control diet. Carcass weight, back fat thickness and $longissimus$ $dorsi$ area of Hanwoo steers tended to increase but lowered (P<0.047) yield index by feeding silage TMRs. Feeding BS TMR slightly decreased marbling score but no difference was found in the number of head over grade 1 between diets. Control diet tended to improve yield grade compared to silage TMRs. Chemical composition, water holding capacity, drip loss, cooking loss and pH, color and fatty acid composition of $longissimus$ $dorsi$ were not affected by experimental diets and feeding duration of silage TMRs. Shear force, however, was increased (P<0.046) by silage TMRs without difference between them compared to control diet. Based on the results of the current study, BS TMR and RS TMR could improve body gain and reduce feed cost without deteriorating meat quality compared to separate feeding of concentrate and rice straw. Overall feeding value was similar between BS TMR and RS TMR.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of Animal Environmental Science
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• v.10 no.1
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• pp.11-22
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• 2004

This work was carried out to measure volatile fatty acids emissions from different manure (poultry, swine, cattle) incubated at $10^{\circ}C$, $25^{\circ}C$, and $37^{\circ}C$ for 6 days under anaerobic condition. Following are summary of these tests results. 1. Amounts of Acetic acid generated were 1,128.05mg/kg, 628.21mg/kg and 592.50mg/kg for swine, poultry, and cattle manure, respectively, during the period of incubation. In the case of swine and cattle manure, 83.87%(946.10mg/kg) and 57.49%(340.63mg/kg) from all the temperature treatments were produced in the $25^{\circ}C$, respectively. 83.57% in swine and 78.79% in cattle manure were intensively emerged from 3 day, 4 day and 5 day of the $25^{\circ}C$ treatment. In the case of poultry manure, 45.36%(284.93mg/kg) and 45.36%(284.93mg/kg) in the $25^{\circ}C$ and in the $37^{\circ}C$, respectively, were produced. Accordingly, acetic acid generated from poultry manure was characteristic of being mainly produced in more than $25^{\circ}C$. 2. Amounts of propionic acid generated were 238.56mg/kg, 162.14mg/kg and 155.49mg/kg for swine, poultry, and cattle manure, respectively, during the period of incubation. In the case of swine manure, 78.52%(187.32mg/kg) of propionate emitted from all the temperature treatments was produced in the $25^{\circ}C$ and 79.1% of them was intensively emerged from 3day, 4day and 5day of the $25^{\circ}C$ treatment. In the case of poultry manure, 35.12%(56.95mg/kg) and 45.89%(74.40mg/kg) of the propionate amounts were produced in the $25^{\circ}C$ and in the $37^{\circ}C$, respectively. In the case of cattle manure, 28.21% (43.86mg/kg) and 49.30% (76.66mg/kg) of the propionate amounts were produced in the $10^{\circ}C$ and in the $25^{\circ}C$, respectively. Accordingly, propionate evolved from poultry manure was characteristic of being mainly produced in more than $25^{\circ}C$ and from cattle manure, in less than $25^{\circ}C$, respectively. 3. Amount of butyric acid generated were 1,463.87mg/kg, 96.72mg/kg and 129.18mg/kg for swine, poultry, and cattle manure, respectively, during the period of incubation. The time intensively emerged from the period of incubation was differently generated from the incubation temperature and animal feces. 4. Amounts of iso-valeric acid generated were 6,885.99mg/kg, 399.28mg/kg and 307.47mg/kg for swine, cattle and poultry manure, respectively, during the period of incubation. In the case of swine and cattle manure, 28.22%(1,943.52mg/kg) and 48.56%(193.90mg/kg) in the $25^{\circ}C$, 68.76%(4,734.90mg/kg) and 46.93%(187.40mg/kg) in the $37^{\circ}C$, respectively, were occupied. Accordingly, iso-valeric acid evolved from swine and cattle manure was characteristic of being mainly produced in more than $25^{\circ}C$. In the case of poultry manure, 59.89%(184.13mg/kg) of iso-valeric acid generated from all the temperature treatments was produced in the $37^{\circ}C$ and 100% of them was intensively emerged from 2 day and 3 day of the $37^{\circ}C$ treatment.