• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.740-748
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• 2018

This study was conducted to investigate the effects of dietary supplementation of enzyme complex (metalloprotease and xylanase) on growth performance, carcass characteristics and meat storability of broiler chickens. The experiment utilized a 2 (basal and low spec diets) ${\times}$ 3 (0, 0.5 or 1 g/kg of enzyme supplementation) factorial arrangement. A total of 360 male Ross broilers were randomly assigned into the following six groups: BD-T0 (basal diet + enzyme complex 0 g/kg), BD-T1 (basal diet + enzyme complex 0.5 g/kg), BD-T2 (basal diet + enzyme complex 1 g/kg), LD-T0 (low spec diet + enzyme complex 0 g/kg), LD-T1 (low spec diet + enzyme complex 0.5 g/kg), LD-T2 (low spec diet + enzyme complex 1 g/kg). Feed and water were provided ad libitum for 42 days, during which time feed intake and body weight were measured at one-week intervals. After the feeding trial, chickens were slaughtered by exsanguination and samples were collected. Feed intake was lower in the enzyme supplemented groups than the non-supplemented groups (p<0.05), as were body weight and gain (p<0.05). Thus, the feed conversion ratio improved in the enzyme supplemented groups relative to the non-supplemented groups (p<0.05). The carcass rate and production index were also significantly improved by supplementation with enzyme complex (p<0.05). Finally, the thiobarbituric acid reactive substances (TBARS) values were lower in the enzyme supplementation groups after 6 storage days (p<0.05). In conclusion, dietary supplementation with enzyme complex including metalloprotease and xylanase improved growth performance, carcass characteristics, and storability of broiler chicken meat.

• Journal of Animal Science and Technology
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• v.45 no.2
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• pp.251-264
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• 2003

This study was conducted to make on-site survey on the output pattern and utilization situation of 19 by-products selected, to evaluate their nutritional characteristics, to find out a reliable index with which digestion of by-products can be predicted on the basis of chemical compositions analyzed and to diagnose the risk of using book values in the absence of the actual values analyzed for diet formulation. Production and utilization situations of by-products were quite various. Nutritionally, fruit processing by-products such as apple pomace (AP), pear pomace (PP), grape pomace (GP), and persimmon peel (PSP), and bakery by-products (BB) were classified as energy feeds. Soybean curd meal (SCM), animal by- products such as blood (BD), feather meal (FM) and poultry by-products (PB), and activated milk processing sludge (AMS) were classified as protein feeds. Soy hulls (SH), spent mushroom compost (SMC), barley malt hulls (BMH), waste paper (WP) and broiler litter (BL) were classified as roughage. Rumen contents (RC) and restaurant food waste (FW) were nutritionally analogous to complete diets for cattle and swine, respectively. Compared to soybean meal (SBM), BD and FM contained high (P<0.05) levels of amino acids and barley malt sprouts (BMS), AMS and FW contained low (P<0.05) levels of amino acids. Enzymatic (pepsin) digestibilities of proteinaceous feeds ranged between 99 and 66%. In vitro DM digestibility was high (P<0.05) in the order of FW, BB, AP, SH, PP, PSP, BMH, BMS, SCM, GP, RC, PB, BL, WP, SMC, AMS, FM and BD. In vitro DM digestibility had the highest correlation (r=0.68) with nonfibrous carbohydrate among chemical components. Differences between analyzed values of chemical components and book values were considerable. Caution is required in using book values when large amount of by-products are used in diets.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.77-97
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• 2019

The large amount of data that emerges from the initial connection environment of the Fourth Industrial Revolution is a major factor that distinguishes the Fourth Industrial Revolution from the existing production environment. This environment has two-sided features that allow it to produce data while using it. And the data produced so produces another value. Due to the massive scale of data, future information systems need to process more data in terms of quantities than existing information systems. In addition, in terms of quality, only a large amount of data, Ability is required. In a small-scale information system, it is possible for a person to accurately understand the system and obtain the necessary information, but in a variety of complex systems where it is difficult to understand the system accurately, it becomes increasingly difficult to acquire the desired information. In other words, more accurate processing of large amounts of data has become a basic condition for future information systems. This problem related to the efficient performance of the information system can be solved by building a semantic web which enables various information processing by expressing the collected data as an ontology that can be understood by not only people but also computers. For example, as in most other organizations, IT has been introduced in the military, and most of the work has been done through information systems. Currently, most of the work is done through information systems. As existing systems contain increasingly large amounts of data, efforts are needed to make the system easier to use through its data utilization. An ontology-based system has a large data semantic network through connection with other systems, and has a wide range of databases that can be utilized, and has the advantage of searching more precisely and quickly through relationships between predefined concepts. In this paper, we propose a defense ontology as a method for effective data management and decision support. In order to judge the applicability and effectiveness of the actual system, we reconstructed the existing air force munitions situation management system as an ontology based system. It is a system constructed to strengthen management and control of logistics situation of commanders and practitioners by providing real - time information on maintenance and distribution situation as it becomes difficult to use complicated logistics information system with large amount of data. Although it is a method to take pre-specified necessary information from the existing logistics system and display it as a web page, it is also difficult to confirm this system except for a few specified items in advance, and it is also time-consuming to extend the additional function if necessary And it is a system composed of category type without search function. Therefore, it has a disadvantage that it can be easily utilized only when the system is well known as in the existing system. The ontology-based logistics situation management system is designed to provide the intuitive visualization of the complex information of the existing logistics information system through the ontology. In order to construct the logistics situation management system through the ontology, And the useful functions such as performance - based logistics support contract management and component dictionary are further identified and included in the ontology. In order to confirm whether the constructed ontology can be used for decision support, it is necessary to implement a meaningful analysis function such as calculation of the utilization rate of the aircraft, inquiry about performance-based military contract. Especially, in contrast to building ontology database in ontology study in the past, in this study, time series data which change value according to time such as the state of aircraft by date are constructed by ontology, and through the constructed ontology, It is confirmed that it is possible to calculate the utilization rate based on various criteria as well as the computable utilization rate. In addition, the data related to performance-based logistics contracts introduced as a new maintenance method of aircraft and other munitions can be inquired into various contents, and it is easy to calculate performance indexes used in performance-based logistics contract through reasoning and functions. Of course, we propose a new performance index that complements the limitations of the currently applied performance indicators, and calculate it through the ontology, confirming the possibility of using the constructed ontology. Finally, it is possible to calculate the failure rate or reliability of each component, including MTBF data of the selected fault-tolerant item based on the actual part consumption performance. The reliability of the mission and the reliability of the system are calculated. In order to confirm the usability of the constructed ontology-based logistics situation management system, the proposed system through the Technology Acceptance Model (TAM), which is a representative model for measuring the acceptability of the technology, is more useful and convenient than the existing system.

• Proceedings of the Safety Management and Science Conference
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• 2004.11a
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• pp.355-380
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• 2004

I test the hypothesis that the gradual diffusion of information across asset markets leads to cross-asset return predictability in Korea. Using thirty-six industry portfolios and the broad market index as our test assets, I establish several key results. First, a number of industries such as semiconductor, electronics, metal, and petroleum lead the stock market by up to one month. In contrast, the market, which is widely followed, only leads a few industries. Importantly, an industry's ability to lead the market is correlated with its propensity to forecast various indicators of economic activity such as industrial production growth. Consistent with our hypothesis, these findings indicate that the market reacts with a delay to information in industry returns about its fundamentals because information diffuses only gradually across asset markets. Traditional theories of asset pricing assume that investors have unlimited information-processing capacity. However, this assumption does not hold for many traders, even the most sophisticated ones. Many economists recognize that investors are better characterized as being only boundedly rational(see Shiller(2000), Sims(2201)). Even from casual observation, few traders can pay attention to all sources of information much less understand their impact on the prices of assets that they trade. Indeed, a large literature in psychology documents the extent to which even attention is a precious cognitive resource(see, eg., Kahneman(1973), Nisbett and Ross(1980), Fiske and Taylor(1991)). A number of papers have explored the implications of limited information- processing capacity for asset prices. I will review this literature in Section II. For instance, Merton(1987) develops a static model of multiple stocks in which investors only have information about a limited number of stocks and only trade those that they have information about. Related models of limited market participation include brennan(1975) and Allen and Gale(1994). As a result, stocks that are less recognized by investors have a smaller investor base(neglected stocks) and trade at a greater discount because of limited risk sharing. More recently, Hong and Stein(1999) develop a dynamic model of a single asset in which information gradually diffuses across the investment public and investors are unable to perform the rational expectations trick of extracting information from prices. Hong and Stein(1999). My hypothesis is that the gradual diffusion of information across asset markets leads to cross-asset return predictability. This hypothesis relies on two key assumptions. The first is that valuable information that originates in one asset reaches investors in other markets only with a lag, i.e. news travels slowly across markets. The second assumption is that because of limited information-processing capacity, many (though not necessarily all) investors may not pay attention or be able to extract the information from the asset prices of markets that they do not participate in. These two assumptions taken together leads to cross-asset return predictability. My hypothesis would appear to be a very plausible one for a few reasons. To begin with, as pointed out by Merton(1987) and the subsequent literature on segmented markets and limited market participation, few investors trade all assets. Put another way, limited participation is a pervasive feature of financial markets. Indeed, even among equity money managers, there is specialization along industries such as sector or market timing funds. Some reasons for this limited market participation include tax, regulatory or liquidity constraints. More plausibly, investors have to specialize because they have their hands full trying to understand the markets that they do participate in