Demand for cosmetics with functionality and eco-friendliness has increased dramatically due to recent aging, well-being trends, and increased interest in beauty. Cosmetics production in 2014 was 8,970.4 billion won, an increase of about 50% compared to 6,014.6 billion won in 2010. In the midst of this, similar companies in intense competition are pursuing differentiated strategies and innovation activities to solve quality, price and delivery problems. In particular, cosmetics packaging work is getting more difficult due to the increasing bill of materials (BOM) and difficult assembly methods. Therefore, in this study, the following problems were identified and suggestions for the improvement of the packaging Many research laboratories such as biotechnology, chemistry, and pharmaceuticals, which are undergoing various studies, are equipped with ready-made laboratory safety equipments such as bio-safety workbenches, aseptic bases, and exhaust workbenches. However, most researchers are disadvantaged in using existing safety equipment. This is because existing safety equipment can not take into account all of the unique characteristics of the research. For this reason, researchers are demanding the development of customized safety equipment that is well suited to their research needs. process of Company C, which is facing difficult situation to respond to the customer 's delivery due to the 52 - hour work week. First, we used the stopwatch to find the difficulty process in the packaging process and show ways to improve it. Second, to improve the efficiency of line balancing in the packaging process, we integrate processes, improve work methods, and perform simple automation. As a result, the prepare loss for replacement was reduced by 1 minute from 5 minutes, resulting in a 23% increase in productivity from 112 ea./hour to 137ea./ hour per person. At this time, the LOB of the packaging process was improved from 70% to 82% by operating one more production line through one person per line, total 9 people saving.

This study explored the effect of writing activity on EFL participants’ speaking performance. In order to attain this purpose, three research questions were presented; 1) What are the characteristics of learners’ writing? 2) How does their speaking fluency change during the writing sessions?, and 3) What is the effect of writing practice on learners’ speaking fluency, in terms of features of spoken grammar? Four college students participated in this study. Pre- and post-oral proficiency test scores, the participants’ writing products, and recorded data of their speaking performance were used for data analysis. Results of data analysis showed that, first, the more proficient participants were, the fewer the errors they made in their writing. Second, there was an increase in scores of intermediate- and beginning-level of students between the pre- and post- oral tests while the scores of advanced level of students did not show any differences between those two tests. Lastly, the result shows that the learners with higher proficiency in writing ability have higher recognition to the spoken grammar. Pedagogical implications are also made on the effective teaching of English writing and speaking in the Korean classroom setting.

Google Trends is a useful tool not only for setting search periods, but also for providing search volume to specific countries, regions, and cities. Extant research showed that the big data from Google Trends could be used for an on-line market analysis of opinion sensitive products instead of an on-site survey. This study investigated the market share of tumor necrosis factor-alpha (TNF-α) inhibitor, which is in a great demand pharmaceutical product, based on big data analysis provided by Google Trends. In this case study, the consumer interest data from Google Trends were compared to the actual product sales of Top 3 TNF-α inhibitors (Enbrel, Remicade, and Humira). A correlation analysis and relative gap were analyzed by statistical analysis between sales-based market share and interest-based market share. Besides, in the country-specific analysis, three major countries (USA, Germany, and France) were selected for market share analysis for Top 3 TNF-α inhibitors. As a result, significant correlation and similarity were identified by data analysis. In the case of Remicade’s biosimilars, the consumer interest in two biosimilar products (Inflectra and Renflexis) increased after the FDA approval. The analytical data showed that Google Trends is a powerful tool for market share estimation for biosimilars. This study is the first investigation in market share analysis for pharmaceutical products using Google Trends big data, and it shows that global and regional market share analysis and estimation are applicable for the interest-sensitive products.

We examined the role of L1 writing on L2 writing performance by repeating the same topic twice through L1 writing first and L2 writing later. We designed what we call a ‘L1 + L2 writing task’ and a ‘L2-only writing task’ respectively. In the L1 + L2 writing task, students wrote a text in their L1, and wrote the same topic in L2, by removing the initial L1 essay. We focused on validating which task conditions (± L1 writing) account for the variation in linguistic performance in EFL high-school students’ writing. Our study was conducted with two intact classes (n = 60) assigned to the L2-only, and students from the other two classes (n = 60) assigned to the L1 + L2. The findings indicate that L1 writing may push students to direct their attentional resources toward effective text construction, thereby mitigating a large number of simultaneous demands on attention. We add to empirical knowledge on the effects of L1 writing in task repetition, by exploring how task repetition affected our students’ L2 writing performance.

There are several methods of peak-shaving, which reduces grid power demand, electricity bought from electricity utility, through lowering “demand spike” during On-Peak period. An optimization method using linear programming is proposed, which can be used to perform peak-shaving of grid power demand for grid-connected PV+ system. Proposed peak shaving method is based on the forecast data for electricity load and photovoltaic power generation. Results from proposed method are compared with those from On-Off and Real Time methods which do not need forecast data. The results also compared to those from ideal case, an optimization method which use measured data for forecast data, that is, error-free forecast data. To see the effects of forecast error 36 error scenarios are developed, which consider error types of forecast, nMAE (normalizes Mean Absolute Error) for photovoltaic power forecast and MAPE (Mean Absolute Percentage Error) for load demand forecast. And the effects of forecast error are investigated including critical error scenarios which provide worse results compared to those of other scenarios. It is shown that proposed peak shaving method are much better than On-Off and Real Time methods under almost all the scenario of forecast error. And it is also shown that the results from our method are not so bad compared to the ideal case using error-free forecast.

This article attempts to elaborate upon the notion that anyway seems to play specific discursive functions in the institutional talk, Donald Trump Speech relevant to monologues rather than any other institutional talk related to turn-sequences, taking heed of how its usage is connoted in disparate settings of his monologic speeches. Drawing upon the observation pertaining to the monologic speeches of anyway in spoken language, it was shown that the use of anyway indicates the four certain discursive functions including resumptive, transitive, incremental, and strengthening markers in order to acquire his vested rights, or receive his votes, and maintain his favorable reputation. As for the heterogeneous nature of anyway between monologues and turn-sequences, it may be presumed that monologic anyway does not tend to function to close or alter ongoing narratives or themes, whereas its anyway may be utilized to indicate that interlocutors have the intention of increasing supplementary information or thoughts and highlighting absolute contentions; in addition, this may be related to a contemptuous function.

Many countries around the world are pursuing various support policies to foster start-ups national widely in order to secure new economic growth engines in the era of the Fourth Industrial Revolution. The South Korean government announced the diffusion strategy for the 2’nd round Start-up Boom in March 2019 and is promoting the support policies for start-up incubating by various programs. Many incubators and startup accelerators operate various kinds of programs to foster start-ups using government financial supports. The purpose of this study is to investigate the effects of entrepreneurship and technical capability of entrepreneurs as the internal factors of the technology-based start-ups and the effects of programs supported by the government as an external factor on the corporate performance of a start-up company, and the mediating effects of core competence of start-ups were analyzed using SPSS and AMOS. The results show that the entrepreneurship, technical capability and the programs supported by incubators or accelerators had no direct effects on the corporate performance of a start-up, but the core competence of the company had complete mediating effects. In addition, the type of program supported by the comprehensive accelerator programs or the marketing supports had effects on the core competence rather than simple financial supports. Lastly, the policy proposals for incubating program support and future research directions along with the limitation are suggested.

This is a longitudinal case study using a mixed-methods research design to track how two Korean university students improved their English writing competence over one year with the aid of automated writing evaluation (AWE) program, Criterion. The participants wrote essays outside of class every month for one year, submitting first and later second drafts. The participants completed a TOEIC writing test at the beginning and end of the study; students’ reflections on their writing development, obtained through interviews and journal entries, were also examined. A comparison of scores, errors, and quantitative measures of fluency and grammatical complexity indicated writing improvement. Both participants used Criterion feedback effectively to render informed judgments and valid corrections. Essay revision based on Criterion feedback yielded more self-directed learning and greater comfort with writing in content courses. It is suggested that the effect of AWE feedback transfers to long-term improvement. The results point to the potential benefit of AWE use in individual out-of-class writing practices.

Systems such as database and socal network systems have been broadly used, and their unexpected failure, with great losses and sometimes a social confusion, has received attention in recent years. Therefore, it is an important issue to find optimal maintenance plans for such kind of systems from the points of system reliability and maintaining cost. However, it is difficult to maintain a system during its working cycle, since stopping works might incur users some troubles. From the above viewpoint, this paper discusses minimal repair maintenance policy with periodic replacement, while considering the random working cycles. The random working cycle and periodic replacement policies with minimal repair has been discussed in traditional literatures by usually analyzing cases for the nonstopping works. However, maintenance can be more conveniently done at discrete time and even during the working cycle in real applications. So, we propose that periodic replacement is planned at discrete times while considering the random working cycle, and moreover provide a model in which system, with a minimal repair at failures between replacements, is replaced at the minimum of discrete times KT and random cycles Y. The average cost rate model is used to determine the optimal number of periodic replacement.

Vegetation segmentation in a field color image is a process of distinguishing vegetation objects of interests like crops and weeds from a background of soil and/or other residues. The performance of the process is crucial in automatic precision agriculture which includes weed control and crop status monitoring. To facilitate the segmentation, color indices have predominantly been used to transform the color image into its gray-scale image. A thresholding technique like the Otsu method is then applied to distinguish vegetation parts from the background. An obvious demerit of the thresholding based segmentation will be that classification of each pixel into vegetation or background is carried out solely by using the color feature of the pixel itself without taking into account color features of its neighboring pixels. This paper presents a new pixel-based segmentation method which employs a multi-layer perceptron neural network to classify the gray-scale image into vegetation and nonvegetation pixels. The input data of the neural network for each pixel are 2-dimensional gray-level values surrounding the pixel. To generate a gray-scale image from a raw RGB color image, a well-known color index called Excess Green minus Excess Red Index was used. Experimental results using 80 field images of 4 vegetation species demonstrate the superiority of the neural network to existing threshold-based segmentation methods in terms of accuracy, precision, recall, and harmonic mean.