• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2974-2992
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• 2021

Crowd-based outsourcing is an emerging trend in testing, which integrates advantages of crowd-based outsourcing in software testing. Open call format is used to accomplish various network tasks involving different types of testing levels and techniques at various places by software testers. Crowd-sourced software testing can lead to an improper testing process as if it does not allocate the right task to the right crowd with required skills and not choose the right crowd; it can lead to huge results, which become time-consuming and challenging crowd-source manager for the identification of improper one. The primary purpose of this research is to make crowd-based outsourced software testing more effective and reliable by relating association between the software tester, personality characteristic, and different levels of software testing, i.e., unit, integration, and system, in order to find appropriate personality characteristic for required testing level. This research has shown an observed experiment to determine which software testing level suits which personality characteristic tester in a crowd-based software testing environment. A total of 1000 software testers from different software houses and firms in Pakistan were registered to perform tasks at different software testing levels. The Myers-Briggs Type Indicator (MBTI) test is used to identify each tester's personality characteristic involved in this research study.

• Journal of Animal Science and Technology
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• v.65 no.2
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• pp.293-310
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• 2023

Protein-translated mRNA analysis has been extensively used to determine the function of various traits in animals. The non-coding RNA (ncRNA), which was known to be non-functional because it was not encoded as a protein, was re-examined as it was studied to actually function. One of the ncRNAs, long non-coding RNA (lncRNA), is known to have a function of regulating mRNA expression, and its importance is emerging. Therefore, lncRNAs are currently being used to understand the traits of various animals as well as human diseases. However, studies on lncRNA annotation and its functions are still lacking in most animals except humans and mice. lncRNAs have unique characteristics of lncRNAs and interact with mRNA through various mechanisms. In order to make lncRNA annotations in animals in the future, it is essential to understand the characteristics of lncRNAs and the mechanisms by which lncRNAs function. In addition, this will allow lncRNAs to be used for a wider variety of traits in a wider range of animals, and it is expected that integrated analysis using other biological information will be possible.

• Journal of Veterinary Science
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• v.23 no.1
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• pp.17.1-17.10
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• 2022

Background: Inspection of livestock farms using surveillance cameras is emerging as a means of early detection of transboundary animal disease such as African swine fever (ASF). Object tracking, a developing technology derived from object detection aims to the consistent identification of individual objects in farms. Objectives: This study was conducted as a preliminary investigation for practical application to livestock farms. With the use of a high-performance artificial intelligence (AI)-based 3D depth camera, the aim is to establish a pathway for utilizing AI models to perform advanced object tracking. Methods: Multiple crossovers by two humans will be simulated to investigate the potential of object tracking. Inspection of consistent identification will be the evidence of object tracking after crossing over. Two AI models, a fast model and an accurate model, were tested and compared with regard to their object tracking performance in 3D. Finally, the recording of pig pen was also processed with aforementioned AI model to test the possibility of 3D object detection. Results: Both AI successfully processed and provided a 3D bounding box, identification number, and distance away from camera for each individual human. The accurate detection model had better evidence than the fast detection model on 3D object tracking and showed the potential application onto pigs as a livestock. Conclusions: Preparing a custom dataset to train AI models in an appropriate farm is required for proper 3D object detection to operate object tracking for pigs at an ideal level. This will allow the farm to smoothly transit traditional methods to ASF-preventing precision livestock farming.

• Journal of Biomedical Engineering Research
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• v.39 no.2
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• pp.63-68
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• 2018

In modern society, speech recognition technology is emerging as an important technology for identification in electronic commerce, forensics, law enforcement, and other systems. In this study, we aim to develop an age classification algorithm for extracting only MFCC(Mel Frequency Cepstral Coefficient) expressing the characteristics of speech in Korean and applying it to deep learning technology. The algorithm for extracting the 13th order MFCC from Korean data and constructing a data set, and using the artificial intelligence algorithm, deep artificial neural network, to classify males in their 20s, 30s, and 50s, and females in their 20s, 40s, and 50s. finally, our model confirmed the classification accuracy of 78.6% and 71.9% for males and females, respectively.

• BMB Reports
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• v.47 no.10
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• pp.531-539
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• 2014

All living cells release extracellular vesicles having pleiotropic functions in intercellular communication. Mammalian extracellular vesicles, also known as exosomes and microvesicles, are spherical bilayered proteolipids composed of various bioactive molecules, including RNAs, DNAs, proteins, and lipids. Extracellular vesicles directly and indirectly control a diverse range of biological processes by transferring membrane proteins, signaling molecules, mRNAs, and miRNAs, and activating receptors of recipient cells. The active interaction of extracellular vesicles with other cells regulates various physiological and pathological conditions, including cancer, infectious diseases, and neurodegenerative disorders. Recent developments in high-throughput proteomics, transcriptomics, and lipidomics tools have provided ample data on the common and specific components of various types of extracellular vesicles. These studies may contribute to the understanding of the molecular mechanism involved in vesicular cargo sorting and the biogenesis of extracellular vesicles, and, further, to the identification of disease-specific biomarkers. This review focuses on the components, functions, and therapeutic and diagnostic potential of extracellular vesicles under various pathophysiological conditions.

• International Journal of Contents
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• v.11 no.2
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• pp.63-68
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• 2015

A citation analysis utilizes the relations among citations and is the most popular bibliometric method. This analysis is based on 1) the evaluation by paper, journal and researcher of the research output, 2) the identification of emerging research topics, 3) the production of a map of the intellectual structure of the research domain and 4) various services for academic information. However, this approach has a limitation in that a citation is treated in a very simple manner, even though the purpose of citation can vary greatly. To address this problem, new approaches have been studied that take into account the citation context. This research separates the citations according to the citation functions and tries to conduct an analysis according to the newly classified citations. Furthermore, research on the citation summarization and visualization based on both the citation context and the citation function of the citations was also attempted. However, since there are very few studies related to citation context in South Korea, more research and development is needed in this area. This study analyzes the status of the research in terms of the citation context. For this, we utilized social network analysis methods.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.225-234
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• 2017

Mixed-reality technologies have proven to be valuable in many architecture, engineering and construction / facilities management (AEC/FM) applications. However, its potential of being adapted to facilitate hazard identification and risk communication in construction workplaces has yet to be fully explored. This paper makes an attempt to evaluate the feasibility of applying mixed-reality to enhancing safety risk communication in construction workplaces. Experiments have been designed in which Microsoft HoloLens^® together with a developed application will be used to intervene in the practice of jobsite risk communication. A cross-sectional survey will then be followed to examine the effectiveness and acceptability of this technology through analysis on data collected from participants in the construction industry. The preliminary results show that this emerging HoloLens^® technology, compared to the traditional communication methods (i.e., phone calls, walking up people and talk, and video conferencing), facilitates accurate, prompt safety communication on construction sites. Such findings signify the potential of applying mixed-reality to safety performance enhancement in the construction industry.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.3
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• pp.635-644
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• 2024

Although the business model(BM) patents act as a creative bridge between technology and the marketplace, limited scholarly attention has been paid to the content analysis of BM patents. This study aims to contextualize converging BM patents by employing topic modeling technique and clustering highly marketable topics, which are expressed through a topic-market impact matrix. We relied on BM patent data filed between 2010 and 2022 to derive empirical insights into the commercial potential of emerging business models. Subsequently, nine topics were identified, including but not limited to "Data Analytics and Predictive Modeling" and "Mobile-Based Digital Services and Advertising." The 2x2 matrix allows to position topics based on the variables of topic growth rate and market impact, which is useful for prioritizing areas that require attention or are promising. This study differentiates itself by going beyond simple topic classification based on topic modeling, reorganizing the findings into a matrix format. T he results of this study are expected to serve as a valuable reference for companies seeking to innovate their business models and enhance their competitive positioning.

• Proceedings of the Korean Society of Food Science and Nutrition Conference
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• 2004.11a
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• pp.271-274
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• 2004

Nutritional genomics is a new field of study of how nutrition interacts with an individual's genome or individual responds to individual diets. Systematic approach of nutritional genomics will likely provide important clues about responders and non-responders. The current interest in personalizing health stems from the breakthroughs emerging in integrative technologies of genomics and epigenomics and the identification of genetic and epigentic diversity in individual's genetic make-up that are associated with variations in many aspects of health, including diet-related diseases. Microarray is a powerful screen system that is being also currently employed in nutritional research. Monitoring of gene expression at genome level is now possible with this technology, which allows the simultaneous assessment of the transcription of tens of thousands of genes and of their relative expression of pathological cells such tumor cells compared with that of normal cells. Epigenetic events such as DNA methylation can result in change of gene expression without involving changes in gene sequence. Recent developed technology of DNAarray-based methylation assay will facilitate wide study of epigenetic process in nutrigenomics. Some of the areas that would benefitfrom these technologies include identifying molecular targets (Biomarkers) for the risk and benefit assessment. These characterized biomarkers can reflect expose, response, and susceptibility to foods and their components. Furthermore the identified new biomarker perhaps can be utilized as a indicator of delivery system fur optimizing health.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.348-354
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• 2007

RFID system is emerging new technology for ubiquitous computing environment. RFID system, however, provides privacy problems while the technology offers incredible rich opportunities for applications in the filed of logistics, distribution, and medical services, etc. Many researches have been conducted in order to solve this problem, but the current RFID authentication protocols are still insufficient for settling the privacy problem in the point of view of privacy intrusion and system efficiency. The purpose of this paper is to present a RFID mutual authentication protocol which improves safety level, compared with current authentication protocols. The proposed authentication protocol can provide mutual authentication services, and is secure against location tracing, spoofing, reflection attack.