• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.51-61
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• 2020

The study aims to compare whether using Earnings Response Coefficient (ERC) is better than using the new concept of Accounting Earnings Response Coefficient (AERC) in determining the earnings quality response coefficient value. Also, the study seeks to explain the effect of company characteristics and corporate governance on AERC through voluntary disclosure and information asymmetry. Research samples include 69 manufacturing companies listed on the Indonesian Stock Exchange over the period 2014-2017. The data come from annual reports, stock market prices, CSPI, EPS, stock returns and market returns. The research model is tested using the structural equation model (SEM) with partial least square (PLS). The results showed the value of the earnings response coefficient produced by AERC and ERC was different. Earnings quality resulting from AERC regression by adding CFO values better reflects the actual earnings quality. These results are consistent with the concept built from the proposition about earnings quality at AERC, that quality earnings are informative accounting earnings. The theoretical findings of this study provide an explanation that operational cash flow plays a role in evaluating earnings quality, while providing reinforcement that the ERC regression model fails to detect stock market reactions to information relevant to the aggregated values of accounting earnings.

• Journal of Plant Biotechnology
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• v.40 no.2
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• pp.88-101
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• 2013

Eating quality of rice attracts more and more attention from rice-eating consumers in the recent years. Thus, improvement of eating quality of cooked rice has become one of the most important breeding goals in japonica rice. Here, the generation of transgenic japonica rice with improved eating quality and grain yield are reported. Overexpression of OsSbe1 gene encoding rice starch branching enzyme 1 was driven by 35S promoter. Eleven independent homozygous $T_3$ transgenic lines were characterized and had shown higher palatability (71.2 ~ 72.6) than wild type Gopum (70.4). Moreover, transgenic rice lines showed an increase in 1000-grain weight and number of spikelets per panicle compared with the wild type. The yield of milled rice was 562.8 ~ 596.7 kg/10a in eight $T_3$ lines, but 542.1 kg/10a in wild type. Gene expression analyses in mRNA transcription and enzyme activity levels suggest that improved eating quality is due to the up-regulation of OsSbe1 gene.

• Animal Bioscience
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• v.34 no.10
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• pp.1663-1673
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• 2021

Objective: Pork belly is considered as the most commercially important and preferable primal cut by consumers worldwide. Thus, this study was conducted to determine the effects of fat levels on the meat quality characteristics of pork bellies. Methods: Seventy-eight growing-finishing pigs collected from different commercial pig farms were slaughtered and used in the present study. After slaughter 24 h, bellies were fabricated according to the Korean Pork Cutting Specification, and immediately sampled for analysis of their fat content. Based on the fat levels, the bellies were segregated into three different groups: low fat (LF, fat ≤20%, n = 15), medium fat (MF, fat 21% to 30%, n = 30), and high fat (HF, fat ≥31%, n = 33). The bellies were then analyzed for meat quality traits, fatty acids, flavor compounds and eating quality properties. Results: The HF group had lower moisture and cooking loss levels compared to the other groups (p<0.05). The LF group presented higher proportions of polyunsaturated fatty acids compared to the other groups (p<0.05). The LF group showed higher amounts of the Maillard reaction-derived flavor compounds (e.g., 2,5-dimethyl pyrazine, 2-ethyl-3,5-dimethyl, and 4-methylthiazole) associated with meaty and roasty flavors whereas, the HF group showed higher amounts of oleic acid- derived compounds (e.g., nonanal and octanal) associated with the fatty and oily flavors. Interestingly, significantly higher scores for all the eating quality attributes (flavor, juiciness, tenderness, and overall acceptance) were found in the HF group compared to those in the LF or MF group (p<0.05). Conclusion: The high-fat bellies (fat ≥31%) had a better technological quality and eating quality compared to the low-fat bellies (fat ≤20%). Thus, increasing the fat content may improve the technological quality and eating quality traits of pork bellies, however, this increase may also result in more trimmed loss due to excessively deposited body fat.

• Corrosion Science and Technology
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• v.23 no.2
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• pp.131-138
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• 2024

This paper introduces Primetals Technologies' Through-Process Optimization (TPO) Services and Through-Process Quality Control (TPQC) System, which integrate domain knowledge, software, and automation expertise to assist steel producers in achieving operational excellence. TPQC collects high-resolution process and product data from the entire production route, providing visualizations and facilitating quality assurance. It also enables the application of artificial intelligence techniques to optimize processes, accelerate steel grade development, and enhance product quality. The main objective of TPO is to grow and digitize operational know-how, increase profitability, and better meet customer needs. The paper describes the contribution of these systems to achieving operational excellence, with a focus on quality assurance. Transparent and traceable production data is used for manual and automatic quality evaluation, resulting in product quality status and guiding the product disposition process. Deviation management is supported by rule-based and AI-based assistants, along with monitoring, alarming, and reporting functions ensuring early recognition of deviations. Embedded root cause proposals and their corrective and compensatory actions facilitate decision support to maintain product quality. Quality indicators and predictive quality models further enhance the efficiency of the quality assurance process. Utilizing the quality assurance software package, TPQC acts as a "one-truth" platform for product quality key players.

• Journal of Biosystems Engineering
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• v.40 no.2
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• pp.124-136
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• 2015

Purpose: Grain quality is a general concept that covers many characteristics, ranging from physical to biochemical and physiochemical properties. Rice aging during storage is currently a challenge in the rice industry, and is a complicated process involving changes in all of the above properties. Spectroscopic techniques can be used to obtain information on the quality of rice samples in a non-destructive manner. Methods: The objective of this review was to highlight the factors that contribute to rice quality and aging, and to describe various spectroscopic modalities, particularly vibrational and hyperspectral imaging, for the assessment of rice quality. Results: Starch and protein are the main components of the rice endosperm, and are therefore key factors contributing to eating and cooking quality. While the overall starch, protein, and lipid content in the rice grain remains essentially unchanged during storage, structural changes do occur. These changes affect pasting and gel properties, and ultimately the flavor of cooked rice. In addition, grain quality is significantly affected by growing and environmental conditions, such as water availability, temperature, fertilizer application, and salinity stress. These properties can be evaluated using spectroscopic techniques, and rice samples can be discriminated by using multivariate statistical analysis methods. Conclusion: Hyperspectral imaging and vibrational spectroscopy techniques have good potential for determining rice quality properties in a non-invasive manner, i.e., not requiring the introduction of instruments into the rice grain.

• Food Science of Animal Resources
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• v.43 no.3
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• pp.531-539
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• 2023

The objective of this study was to determine the effects of quality grade (QG), and back-fat thickness on the carcass traits and meat quality properties of Hanwoo steers. Fifty carcasses were sorted into two QG (QG 1+ and 1) and three back-fat thickness (<10 mm, 10 to 19 mm and ≥19 mm) groups. After investigating the carcass traits (rib eye, back-fat thickness, weight, color, yield index, maturity, marbling score, and texture), the longissimus lumborum muscles from the carcass groups were collected and analyzed for meat quality (pH, color, cooking loss, and moisture), texture profiles [Warner-Bratzler shear force (WBSF), and tensile tests], and fatty acid. Results showed that marbling score (p<0.001), moisture (p<0.05) and tensile tests values (p<0.05) had a significant differences between QG1+ and QG1. No differences in pH, color traits, cooking loss and WBSF values occurred between the QG groups. Regarding the back-fat thickness effect, we observed that the carcass weight, yield index (p<0.001), yield grade (p<0.001) and marbling score (p<0.05) had a significant differences among the back-fat thickness groups. Regarding the meat quality, moisture content and WBSF values (p<0.01) among the back-fat thickness groups. The back-fat thickness did not affect the pH, color, cooking loss and tensile tests. The QG and back-fat thickness did not affect the fatty acids contents (p>0.05). It may be concluded that the carcass traits and meat quality were significantly affected the QG and back-fat thickness.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.31-42
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• 2024

Different industries mostly rely on quality certification for promoting their products or brands. Although getting quality certification, specifically by human experts is a tough job to do. But the field of machine learning play a vital role in every aspect of life, if we talk about quality certification, machine learning is having a lot of applications concerning, assigning and assessing quality certifications to different products on a macro level. Like other brands, wine is also having different brands. In order to ensure the quality of wine, machine learning plays an important role. In this research, we use two datasets that are publicly available on the "UC Irvine machine learning repository", for predicting the wine quality. Datasets that we have opted for our experimental research study were comprised of white wine and red wine datasets, there are 1599 records for red wine and 4898 records for white wine datasets. The research study was twofold. First, we have used a technique called backward elimination in order to find out the dependency of the dependent variable on the independent variable and predict the dependent variable, the technique is useful for predicting which independent variable has maximum probability for improving the wine quality. Second, we used a robust machine learning algorithm known as "XGBoost" for efficient prediction of wine quality. We evaluate our model on the basis of error measures, root mean square error, mean absolute error, R2 error and mean square error. We have compared the results generated by "XGBoost" with the other state-of-the-art machine learning techniques, experimental results have showed, "XGBoost" outperform as compared to other state of the art machine learning techniques.

• Preventive Nutrition and Food Science
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• v.4 no.1
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• pp.23-27
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• 1999

To evaluate the quality of fish extracts with spicy vegetables (garlic, onion and ginger) in suppressing fishy oder, fish extracts of crucian carp, loach, bastard halibut and jacopever were processed at 100 $^{\circ}C$ for 6 hours, and their in vitro and in vivo protein qualities were determined . Protein and total lipid contents were closely related to the degree of discarding floated lipid on fish extracts and the kinds of added apicy vegetables . Boiling (10$0^{\circ}C$) , appeared to improve in vitro protein qualities slightly more than hydrocooking (11$0^{\circ}C$), but those with mild processing tended to result in better protein qualities than high temperature cooking (136-14$0^{\circ}C$). Spicy vegetables did not have remarkable effects on improving in vitro protein quality parameters. Fish extracts with 10% ginger were generally higher in in vitro protein quality than with the other vegetables . In spite of higher in vivo protein digestibility of fish extracts containing spicy vegetables processed under mild conditions(10$0^{\circ}C$), PERs of those extracts were not higher htan those of extranct processed at high temperature.

• Journal of Applied Reliability
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• v.15 no.3
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• pp.216-221
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• 2015

Sintering behavior of 3%yttria-stabilized zirconia was comparatively studied using a spray-dried powder produced by a domestic and global company. Quality of the sintered block was analysed in terms of relative density, shrinkage rate, grain growth, hardness, and fracture toughness. Relative density, shrinkage rate, and hardness value of the finally sintered block was similar between domestic and global zirconia powder, respectively. But, flexural strength of the domestic powder specimen was about 70% of the sintered block produced by using a global powder. The poor sintering quality of the domestic powder was discussed in relation with compressibility of the spray-dried granule-type powder and the amount of monoclinic phase in the as-received powder.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.3
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• pp.13-26
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• 1999

Recently, information technology and information system(IS) are rapidly diffused throughout the world. In the global competitive environment, the success of IS becomes the important one among the critical success factors(CSF) of the firm. For achieving it, the firm must continually involve itself in the quality evaluation and improvement of IS. The quality concept was changed into the customer-oriented quality one. There is no exception to the quality of IS. In the past, IS quality was determined by the IS developer or IS department offering service. Now it is evaluated by the user of IS service, and then the customer-oriented user satisfaction becomes an important issue. The purpose of this study is to develope the total quality evaluation model of IS through TQM approach. First, all success factors of the domestic IS are extracted from the foreign and domestic literatures of IS success factors contained the technical and behavioral aspects. And the extracted factors are classified with evaluation levels for quality evaluation and developed into a total quality evaluation model. Finally the model usefulness is analyzed.