• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1801-1816
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• 2014

Because HTTP-related ports are allowed through firewalls, they are an obvious point for launching cyber attacks. In particular, malware uses HTTP protocols to communicate with their master servers. We call this an HTTP-based command and control (C&C) server. Most previous studies concentrated on the behavioral pattern of C&Cs. However, these approaches need a well-defined white list to reduce the false positive rate because there are many benign applications, such as automatic update checks and web refreshes, that have a periodic access pattern. In this paper, we focus on finding new discriminative features of HTTP-based C&Cs by analyzing HTTP activity sets. First, a C&C shows a few connections at a time (low density). Second, the content of a request or a response is changed frequently among consecutive C&Cs (high content variability). Based on these two features, we propose a novel C&C analysis mechanism that detects the HTTP-based C&C. The HAS-Analyzer can classify the HTTP-based C&C with an accuracy of more than 96% and a false positive rate of 1.3% without using any white list.

• Genomics & Informatics
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• v.11 no.4
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• pp.289-291
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• 2013

Human papillomavirus (HPV) infection is the leading cause of cancer mortality among women worldwide. The molecular understanding of HPV proteins has significant connotation for understanding their intrusion in the host and designing novel protein vaccines and anti-viral agents, etc. Genomic, proteomic, structural, and disease-related information on HPV is available on the web; yet, with trivial annotations and more so, it is not well customized for data analysis, host-pathogen interaction, strain-disease association, drug designing, and sequence analysis, etc. We attempted to design an online reserve with comprehensive information on HPV for the end users desiring the same. The Human Papillomavirus Proteome Database (hpvPDB) domiciles proteomic and genomic information on 150 HPV strains sequenced to date. Simultaneous easy expandability and retrieval of the strain-specific data, with a provision for sequence analysis and exploration potential of predicted structures, and easy access for curation and annotation through a range of search options at one platform are a few of its important features. Affluent information in this reserve could be of help for researchers involved in structural virology, cancer research, drug discovery, and vaccine design.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1158-1167
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• 2017

Many real-world applications information are organized and represented with graph structure which is often used for representing various ubiquitous networks, such as World Wide Web, social networks, and protein-protein interactive networks. In particular, similarity evaluation between graphs is a challenging issue in many fields such as graph searching, pattern discovery, neuroscience, chemical compounds exploration and so forth. There exist some algorithms which are based on vertices or edges properties, are proposed for addressing this issue. However, these algorithms do not take both vertices and edges similarities into account. Towards this end, this paper pioneers a novel approach for similarity evaluation between graphs based on formal concept analysis. The feature of this approach is able to characterize the relationships between nodes and further reveal the similarity between graphs. Therefore, the highlight of our approach is to take vertices and edges into account simultaneously. The proposed algorithm is evaluated using a case study for validating the effectiveness of the proposed approach on detecting and measuring the similarity between graphs.

• Genomics & Informatics
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• v.16 no.4
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• pp.28.1-28.6
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• 2018

Due to the increasing interest in synonymous codons, several codon bias-related terms were introduced. As one measure of them, the tRNA adaptation index (tAI) was invented about a decade ago. The tAI is a measure of translational efficiency for a gene and is calculated based on the abundance of intracellular tRNA and the binding strength between a codon and a tRNA. The index has been widely used in various fields of molecular evolution, genetics, and pharmacology. Afterwards, an improved version of the index, named specific tRNA adaptation index (stAI), was developed by adapting tRNA copy numbers in species. Although a subsequently developed webserver (stAIcalc) provided tools that calculated stAI values, it was not available to access pre-calculated values. In addition to about 100 species in stAIcalc, we calculated stAI values for whole coding sequences in 148 species. To enable easy access to this index, we constructed a novel web database, named STADIUM (Species-specific tRNA adaptive index compendium). STADIUM provides not only the stAI value of each gene but also statistics based on pathway-based classification. The database is expected to help researchers who have interests in codon optimality and the role of synonymous codons. STADIUM is freely available at http://stadium.pmrc.re.kr.

• Mycobiology
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• v.49 no.6
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• pp.559-581
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• 2021

The coastal marine ecosystems of Vietnam are one of the global biodiversity hotspots, but the biodiversity of marine fungi is not well known. To fill this major gap of knowledge, we assessed the genetic diversity (ITS sequence) of 75 fungal strains isolated from 11 surface coastal marine and deeper waters in Nha Trang Bay and Van Phong Bay using a culture-dependent approach and 5 OTUs (Operational Taxonomic Units) of fungi in three representative sampling sites using next-generation sequencing. The results from both approaches shared similar fungal taxonomy to the most abundant phylum (Ascomycota), genera (Candida and Aspergillus) and species (Candida blankii) but were different at less common taxa. Culturable fungal strains in this study belong to 3 phyla, 5 subdivisions, 7 classes, 12 orders, 17 families, 22 genera and at least 40 species, of which 29 species have been identified and several species are likely novel. Among identified species, 12 and 28 are new records in global and Vietnamese marine areas, respectively. The analysis of enzyme activity and the checklist of trophic mode and guild assignment provided valuable additional biological information and suggested the ecological function of planktonic fungi in the marine food web. This is the largest dataset of marine fungal biodiversity on morphology, phylogeny and enzyme activity in the tropical coastal ecosystems of Vietnam and Southeast Asia. Biogeographic aspects, ecological factors and human impact may structure mycoplankton communities in such aquatic habitats.

• Earthquakes and Structures
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• v.23 no.3
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• pp.297-313
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• 2022

Composite steel plate shear wall (CSPSW) is a relatively novel structural system proposed to improve the performance of steel plate shear walls by adding one or two layers of concrete walls to the infill plate. In addition, the buckling of the infill steel plate has a significant negative effect on the shear strength and energy dissipation capacity of the overall systems. Accordingly, in this study, using the finite element (FE) method, the performance and behavior of composite steel shear walls using T-shaped stiffeners to prevent buckling of the infill steel plate and increase the capacity of CSPSW systems have been investigated. In this paper, after modeling composite steel plate shear walls with and without steel plates with finite element methods and calibration the models with experimental results, effects of parameters such as several stiffeners, vertical, horizontal, diagonal, and a combination of T-shaped stiffeners located in the composite wall have been investigated on the ultimate capacity, web-plate buckling, von-Mises stress, and failure modes. The results showed that the arrangement of stiffeners has no significant effect on the capacity and performance of the CSPSW so that the use of vertical or horizontal stiffeners did not have a significant effect on the capacity and performance of the CSPSW. On the other hand, the use of diagonal hardeners has potentially affected the performance of CSPSWs, increasing the capacity of steel shear walls by up to 25%.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.11-20
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• 2023

The primary aim of this study is to investigate the influence of Service Provider Quality (SPQ), System Quality (SQ), Information Quality (IQ), and Training Quality (TQ) on the interconnected aspect of organizational performance known as growth and development (GD). The study examined the influence of information systems (IS) on organisational performance and provided a theory-based technique for conducting research. The theoretical foundation for this study is derived from the widely employed [1]. IS success model in information systems research. The study's framework incorporates several novel elements, drawn from a comprehensive review of both recent and earlier literature, which researchers have utilized to evaluate the dimensions of [1]. In this study, we collected data from a diverse group of 348 individuals representing various industries through a web-based questionnaire. The collected data were subjected to analysis using SPSS. We conducted a multiple regression analysis involving 15 factors to assess several hypotheses regarding the relationship between the independent construct IS effectiveness and the dependent construct organizational performance. Several noteworthy descriptive statistics emerged, which hold significance for management. The study's findings strongly indicate that information systems exert a significant and beneficial influence on organizational performance. To sustain and continually enhance organizational effectiveness, the study recommends that managers periodically scrutinize and assess their information systems.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.11 no.2
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• pp.92-96
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• 2006

NLPCA(Nonlinear Principal Component Analysis) is a novel technique for multivariate data analysis, similar to the well-known method of principal component analysis. NLPCA operates by a feedforward neural network called AANN(Auto Associative Neural Network) which performs the identity mapping. In this work, a sensor fault detection system based on NLPCA is presented. To verify its applicability, simulation study on the data supplied from risk management system is executed.

• Journal of Microbiology and Biotechnology
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• v.34 no.9
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• pp.1748-1756
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• 2024

Biofilm formation by bacteria poses a significant challenge across diverse industries, displaying resilience against conventional antimicrobial agents. Nanoparticles emerge as a promising alternative for addressing biofilm-related issues. This review aims to assess the efficacy of metal and metal oxide nanoparticles in inhibiting or disrupting biofilm formation by various bacterial species. It delineates trends, identifies gaps, and outlines avenues for future research, emphasizing best practices and optimal nanoparticles for biofilm prevention and eradication. Additionally, it underscores the potential of nanoparticles as substitutes for traditional antibiotics in healthcare and combating antibiotic resistance. A systematic literature search, encompassing Web of Science, PubMed, and Google Scholar from 2015 to 2023, yielded 48 publications meeting the review criteria. These studies employed diverse methods to explore the antibacterial activity of nanoparticles against biofilm-forming bacteria strains. The implications of this study are profound, offering prospects for novel antimicrobial agents targeting biofilm-forming bacteria, often resistant to conventional antibiotics. In conclusion, nanoparticles present a promising frontier in countering biofilm-forming bacteria. This review delivers a structured analysis of current research, providing insights into the potential and challenges of nanoparticle utilization against biofilm-related challenges. While nanoparticles exhibit inherent antimicrobial properties with applications spanning healthcare, agriculture, and industries, the review acknowledges limitations such as the narrow scope of tested nanoparticles and the imperative need for extensive research on long-term toxicity and environmental impacts.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.236-251
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• 2020

As remote sensing technologies are evolving, and more satellites are orbited, the demand for using satellite data for disaster monitoring is rapidly increasing. Although natural and social disasters have been monitored using satellite data, constraints on establishing an integrated satellite-based near real-time disaster monitoring system have not been identified yet, and thus a novel framework for establishing such system remains to be presented. This research identifies constraints on establishing satellite data-based near real-time disaster monitoring systems by devising and testing a new conceptual framework of disaster monitoring, and then presents a feasible disaster monitoring system that relies mainly on acquirable satellite data. Implementing near real-time disaster monitoring by satellite remote sensing is constrained by technological and economic factors, and more significantly, it is also limited by interactions between organisations and policy that hamper timely acquiring appropriate satellite data for the purpose, and institutional factors that are related to satellite data analyses. Such constraints could be eased by employing an integrated computing platform, such as Amazon Web Services(AWS), which enables obtaining, storing and analysing satellite data, and by developing a toolkit by which appropriate satellites'sensors that are required for monitoring specific types of disaster, and their orbits, can be analysed. It is anticipated that the findings of this research could be used as meaningful reference when trying to establishing a satellite-based near real-time disaster monitoring system in any country.