• Asian Pacific Journal of Cancer Prevention
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• v.17 no.4
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• pp.2145-2150
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• 2016

Background: Infection with hepatitis B virus (HBV) is a major global public health problem, with a wide spectrum of clinical manifestations. Human cytosolic glutathione-S-transferases (GSTs) include several classes such as alpha (A), mu (M), pi (P), sigma (S), zeta (Z), omega (O) and theta (T). The present study aimed to investigate the role of GST omega genes (GSTO1 and GSTO2) in different groups of patients infected with HBV. Materials and Methods: HBV groups were classified according to clinical history, serological tests and histological analysis into normal carriers (N), acute (A), chronic (CH), cirrhosis (CI) and hepatocellular carcinoma (HCC) cases. The study focused on determination of the genotypes of GST omega genes (GSTO1 and GSTO2) and GST activity and liver function tests. Results: The results showed that GSTO1 (A/A) was decreased in N, A, CH, CI and HCC groups compared to the C-group, while, GSTO1 (C/A) and GSTO1(C/C) genotypes were increased significantly in N, A, CH, CI and HCC groups. GSTO2 (A/A) was decreased in all studied groups as compared to the C-group but GSTO2(A/G) and GSTO2(G/G) genotypes were increased significantly. In addition, GST activities, albumin and TP levels were decreased in all studied groups compared to the C-group, while the activities of transaminases were increased to differing degrees. Conclusions: The results indicate that GSTO genetic polymorphisms may be considered as biomarkers for determining and predicting the progression of HBV infection.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.201-224
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• 2016

The main objective of this study is to identify and analyze the factors affecting technology innovation of the innovative IT SMEs. A research model is established based on the previous studies on the technology innovation of SMEs. The model consists of independent variables (Adhocracy culture, R&D capability, IT capability, Leadership, and Appraisal & Reward), an intermediate variable (Knowledge management), and dependent variables (product/service innovation and process innovation). Major research results can be summarized as follows: IT SMEs pursuing technology innovation should: (1) pay attention to innovation oriented culture, IT capability, and evaluation & compensation systems of the company; (2) recognize that knowledge management is an essential activity performed by the company; (3) strengthen the R&D capabilities of the company by not only exerting internal efforts but establishing cooperative network with various parties; and (4) resolve the decoupling problem of the evaluation & compensation system.

• Advances in environmental research
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• v.9 no.1
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• pp.1-17
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• 2020

Pharmaceutically active compounds (PhACs) have become an environmental havoc in last few decades with reported cases of antibiotic resistant bacteria (ARB) and antibiotic resistant genes (ARGs), lethal effects over aquatic organisms, interference in natural decomposition of organic matter, reduced diversity of microbial communities in different environmental compartments, inhibition of growth of microbes resulting in reduced rate of nutrient cycling, hormonal imbalance in exposed organisms etc. Owing to their potential towards bioaccumulation and persistent nature, these compounds have longer residence time and activity in environment. The conventional technologies of wastewater treatment have got poor efficiency towards removal/degradation of PhACs and therefore, modern techniques with efficient, cost-effective and environment-friendly operation need to be explored. Advanced oxidation processes (AOPs) like Photocatalysis, Fenton oxidation, Ozonation etc. are some of the promising, viable and sustainable options for degradation of PhACs. Although energy/chemical or both are essentially required for AOPs, these methods target complete degradation/mineralization of persistent pollutants resulting in no residual toxicity. Considering the high efficiency towards degradation, non-toxic nature, universal viability and acceptability, AOPs have become a promising option for effective treatment of chemicals with persistent nature.

• Journal of Welding and Joining
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• v.31 no.2
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• pp.4-15
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• 2013

The laser/arc hybrid welding process is a new process combining the laser beam and the arc as welding heat source. The laser beam and arc influence and assist one another. By application of hybrid welding, synergistic effects are achievable, and disadvantage of the respective processes can be compensated. The laser-arc hybrid welding process has good potential to extend the field of applications of laser technology, and provide significant improvements in weld quality and process efficiency in manufacturing applications. This review analyses the recent advances in the fundamental understanding of hybrid welding processes using the works of the data base of Web of Science (SCI-Expanded) since the 2000 year. The research activity on the hybrid welding has been become more actively since 2006, especially in China, presenting the most research papers in the world. Since the hybrid welding process was adopted in manufacturing of the automobile in Europe in the early of 2000's, its adopting is widely expanded in the field of manufacturing of automobile, ship building, steel construction and the other various industry. The hybrid welding process is expected to advance toward higher productivity, higher precision, higher reliability through the mixing of high power and flexible fiber laser or disk laser and digitalized pulsed arc source.

• Korean Management Science Review
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• v.30 no.2
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• pp.63-77
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• 2013

Recently, many companies are interested in adopting cloud computing as their IT strategy. However, no distinct results have appeared in the substantial implementation of this technology. The main reason for such result is from the absence of research models leading to high impact studies on cloud computing. Thus, this study attempts to find a possible answer for the following research question : what factors influence an organizational assimilation of cloud computing? This study investigates Technology-Push (TP)/Need-Pull (NP) theory as a main factor affecting cloud computing assimilation. Also, the study examines the moderating role of organizational readiness. TP includes of perceived benefits, vendor pressure, cost savings, and IT activity intensity while NP includes competitor orientation, information technology policy, technological turbulence, and performance gaps. In addition, organizational readiness suggests two variables, financial resources and technological knowledge. Result from 217 adopting organizations showed that all of these factors with exception of competitor orientation and vendor pressure, have statistically significant impact on assimilation of cloud computing. The implications of the findings propose a theoretical framework for the foundation of studies on cloud computing assimilation, which can server as important practical guidelines for technology development.

• STI Policy Review
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• v.9 no.1
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• pp.133-157
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• 2018

The divide between the "digital" economy and the traditional "physical" economy is outdated. In fact, we are in a transition to a singular economy. This paper classifies economic objects (including actors) as either physical or virtual and argues that due to emerging technologies, these objects are interacting with each other in both physical and increasingly digital spheres in tandem. This paper recognizes the elemental difference between atoms and bytes but argues that physical and digital economic activities are becoming inseparably intertwined. Furthermore, arbitrarily dividing the economy into two categories - one "physical" and the other "digital" - distorts the overall view of the actual execution of economic activity. A wide range of innovations emerging concurrently is fueling the transition to a singular economy. Often referred to as the elements of the Fourth Industrial Revolution (4IR), four emerging technological areas are reviewed here: distributed ledger technology, artificial intelligence/machine learning/data sciences, biometrics and remote sensor technologies, and access infrastructure (universal internet access/electricity/cloud computing). The financial services sector is presented as a case study for the potential impact of these 4IR technologies and the blurring physical/digital line. To reach the potential of these innovations and a truly singular economy, it requires the concurrent development of social, organizational, and regulatory innovations, though they lag in terms of technological progress thus far.

• East Asian Journal of Business Economics (EAJBE)
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• v.8 no.4
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• pp.67-77
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• 2020

Purpose - This work tries to analyze the transformation of sectoral innovation pattern as time goes by to enhance the understanding on sectoral innovative activities, particularly considering the change of the nature of knowledge, and the trend of convergence. Research design, data, and methodology - This work tries to identify main factors, which determine the output of technological innovation through the econometric analysis, utilizing the result of Korean Innovation Survey and find a stylized fact on the change of the innovation pattern. Result - As a result of estimation, some major elements show different effects for two discrete years, 2002 and 2010; in chemical industry the open information source and neutral basic research become more important with the appropriation mechanism such as patents, and in machinery industry, the importance of internal information has been getting decreased with rising importance of customers. Conclusion - This work presents that some elements show different effects for two discrete years. Among three major elements, the source of information and appropriation mechanism shows different features for both industries. This means that we should explicit consider the changing nature of innovative environment, which leads to and heavily influence whether the innovative activity would be effective or not when we design innovation strategy and innovation policy.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.1-22
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• 2014

Recent technological advances provide the opportunity to use large amounts of multimedia data from a multitude of sensors with different modalities (e.g., video, text) for the detection and characterization of criminal activity. Their integration can compensate for sensor and modality deficiencies by using data from other available sensors and modalities. However, building such an integrated system at the scale of neighborhood and cities is challenging due to the large amount of data to be considered and the need to ensure a short response time to potential criminal activity. In this paper, we present a system that enables multi-modal data collection at scale and automates the detection of events of interest for the surveillance and reconnaissance of criminal activity. The proposed system showcases novel analytical tools that fuse multimedia data streams to automatically detect and identify specific criminal events and activities. More specifically, the system detects and analyzes series of incidents (an incident is an occurrence or artifact relevant to a criminal activity extracted from a single media stream) in the spatiotemporal domain to extract events (actual instances of criminal events) while cross-referencing multimodal media streams and incidents in time and space to provide a comprehensive view to a human operator while avoiding information overload. We present several case studies that demonstrate how the proposed system can provide law enforcement personnel with forensic and real time tools to identify and track potential criminal activity.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.495-502
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• 2021

The study is devoted to substantiation of directions of intensification of development of small innovative enterprise, which has a significant impact on the overall innovation activity of the country and promotes innovative development, transition to more advanced technological systems. The outlined role of small business in innovative development in the direction of intensifying innovation in the economy, improving organization and production, as well as in the form of direct participation in the innovation process, production of science-intensive products, stimulating demand for innovation. A group of factors hindering the development of small innovative entrepreneurship was identified, including: financial aspects of the activity, shortcomings of organizational and communicative nature, underdeveloped technology market, information plan problems, internal production problems of small business, market problems. The directions of intensification of the development of small innovative entrepreneurship are substantiated, namely: financial and credit support of small innovative entrepreneurship; introduction of tax incentives; material and technical support; nationwide intensification of innovation activity; information support; development of innovation infrastructure. The involvement of the outlined directions of intensification of small innovative entrepreneurship will help to obtain a synergistic effect of innovative development of both small innovative business structures and the economy as a whole.

• ETRI Journal
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• v.44 no.2
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• pp.286-299
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• 2022

Human activity recognition in real time is a challenging task. Recently, a plethora of studies has been proposed using deep learning architectures. The implementation of these architectures requires the high computing power of the machine and a massive database. However, handcrafted features-based machine learning models need less computing power and very accurate where features are effectively extracted. In this study, we propose a handcrafted model based on three-dimensional sequential skeleton data. The human body skeleton movement over a frame is computed through joint positions in a frame. The joints of these skeletal frames are projected into two-dimensional space, forming a "movement polygon." These polygons are further transformed into a one-dimensional space by computing amplitudes at different angles from the centroid of polygons. The feature vector is formed by the sampling of these amplitudes at different angles. The performance of the algorithm is evaluated using a support vector machine on four public datasets: MSR Action3D, Berkeley MHAD, TST Fall Detection, and NTU-RGB+D, and the highest accuracies achieved on these datasets are 94.13%, 93.34%, 95.7%, and 86.8%, respectively. These accuracies are compared with similar state-of-the-art and show superior performance.