• Journal of KIISE
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• v.43 no.1
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• pp.126-134
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• 2016

Due to the merits of OLED displays such as fast responsiveness, wide view angle, and power efficiency, their use has increased. However, despite the power efficiency of OLED displays, the portion of their power consumption among the total power consumption is still high since user interaction-based applications such as instant messaging, video play, and games are frequently used. Their power consumption varies significantly depending on the display contents and thus color transformation is one of the low-power techniques used in OLED displays. Prior low-power color transformation techniques have not been rigorously studied in terms of satisfaction of the human visual system, and have not considered optimal visual satisfaction and power consumption at the same time in relation to color transformation. In this paper, we propose a novel low-power color transformation technique which strictly considers human visual system-awareness as well as optimization of both visual satisfaction and power consumption in a balanced way. Experimental results show that the proposed technique achieves better human visual satisfaction in terms of visuality and also shows on average 13.4% and 22.4% improvement over a prior one in terms of power saving.

• Asian-Australasian Journal of Animal Sciences
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• v.12 no.3
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• pp.358-365
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• 1999

The effects of dry roasting whole lupin seeds (lupinus albus, WLS) at 110, 130 or $150{^{\circ}C}$ for 15, 30 or 45 minutes on the in sacco rumen degradation characteristics, optimal heating conditions of time and temperature and in vitro enzyme digestibility were determined. Ruminant degradation characteristics (RDC) of crude protein (CP) of WLS were determined by in sacco technique in dairy cows. Measure ROC were soluble (S), undegradable (U), potentially degradable (D) fractions, lag time (TO) and rate of degradation (Kd) of insoluble but degradable fraction. Based on measured ROC, percentage bypass CP (%BCP) and bypass CP (BCP in g/kg, DM) were calculated. Degradability of CP was significantly reduced by dry roasting (p<0.001). The interaction of dry roasting temperature and time had significant effects on D (p<0.05), Kd (p<0.01), U (p<0.01), %BCP (p<0.001) and BCP (p<0.001) but not on S (p=0.923>0.05). With increasing time and temperature, S, D, Kd and U varied from 31.8%, 67.4%, 10.3%/h and 0.8% in the raw WLS (RWLS) to 27.1 %, 35.8%, 3.6%/h, 38.4% in $150{^{\circ}C}/45\;min$, respectively. All these effects resulted in increasing %BCP from 25.9 in RWLS to 61.0% in the $150{^{\circ}C}/45\;min$. Therefore BCP increased form 111.2 to 261.2 g/kg DM, respectively. Both %BCP and BCP at $150{^{\circ}C}/45\;min$ increased nearly 2.5 times over the RWLS. The effects of dry roasting on %BCP and BCP seemed to be linear up to the highest value tested. Although ROC had been altered by dry roasting, the In vitro perpsin-cellulase digestibility was generally unchanged. It was concluded that dry roasting was effective in shifting CP degradation from rumen to the lower gastrointestinal tract to potential reduce unnecessary N loss in the rumen. It might be of great value in successfully synchronizing the rhythms of release of nitrogen and energy in the rumen, thus achieving a more efficient fermentation of diets with high proportions of lignocellulosic resources. To determine the optimal dry roasting conditions, the digestibility of each treatment in the cows will be measured in the next trial using mobile bags technique.

• Smart Media Journal
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• v.8 no.4
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• pp.58-63
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• 2019

The growth of the mobile device market has changed the education market and led to the quantitative growth of various media education. In particular, smart devices, which have better interaction than existing PCs or consoles, can develop more user-friendly content, allowing various types of educational content and inducing changes in traditional education methods for consumers. Although many researchers recently suggest viable development methods or marketing elements of contents, development companies, and developers, until now, merely rely on the human senses. Therefore, it is necessary to study the actual user's smart-device based usability and experience environment. This study aims to propose an intuitive statistical processing method for analyzing the usability of game-type educational contents in terms of form, for popular games that have been released as a basis for analyzing the user experience environment. In particular, because the game industry has a sufficient number of similar examples, it is possible to conduct research based on big data and to use them for immediate decision-making between multiple co-developers through the analysis method proposed by the research. It is expected to become an analytical model that can communicate with other industries because it is effective in securing data sources.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.4
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• pp.153-165
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• 2021

With the disappearance of boundaries between online and offline, the O2O(online to offline) platform service is rapidly growing. Unlike general products, freshness is an important decision-making factor for agri-food, and there are many limiting factors for growth as an open market among O2O platforms due to the characteristics of difficult refunds and exchanges compared to other items and new transaction methods. In order to overcome these obstacles, consumer innovation must be considered. The purpose of this study was to investigate the influence of O2O(online to offline) platform characteristics perception on agri-food repurchase intentions. And an empirical survey of the hypothesis is made that innovation will show a moderating effect between agri-food O2O platform characteristics and repurchase intention. And an empirical survey of the hypothesis is made that innovation will show a moderating effect between agri-food O2O platform characteristics and repurchase intention. For this purpose, Using a convenience sampling technique, an online survey was conducted through Google survey from April 1 to April 15, 2021. A total of final analysis data were collected from a total of 270 purchase experienced of agri-food O2O(online to offline) platform. The SPSS program was used for analysis, and multiple regression analysis was used for hypothesis verification. The results showed that Economic, Interaction, and Playfulness had a significant positive effect on agri-food repurchase intend. Also, Interactivity × innovation, playfulness × innovation were found to have a significant positive (+) effect on repurchase intention. The results of this study show that innovation reduces the burden on consumers for new systems and mobile transactions. The results of this study suggest that convenient interface design is important for activating O2O transactions of agri-food. In addition, education and support are needed to strengthen the IT competency of farmers. The results of this study will be able to contribute to the establishment of infrastructure for agri-food open market shopping malls. In future studies, the influence of the O2O platform type on the purchase intention should be studied continuously.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.