• Asian-Australasian Journal of Animal Sciences
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• v.21 no.11
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• pp.1544-1550
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• 2008

The retinoids (vitamin A and its derivatives) play a critical role in vision, growth, reproduction, cell differentiation and embryonic development. Using the IMpRH panel, porcine cellular retinol binding protein genes 5 and 7 (RBP5 and RBP7) were assigned to porcine chromosomes 5 and 6, respectively. The complete coding sequences (CDS) of the RBP5 and RBP7 genes were amplified using the reverse transcriptase polymerase chain reaction (RT-PCR) method, and the deduced amino acid sequences of both genes were compared to human corresponding proteins. The mRNA distributions of the two genes in adult Wuzhishan pig tissues (lung, skeletal muscle, spleen, heart, stomach, large intestine, lymph node, small intestine, liver, brain, kidney and fat) were examined. A total of nine single nucleotide polymorphisms (SNPs) were identified in two genes. Three of these SNPs were analyzed using the polymerase chain reaction-restriction-fragment length polymorphism (PCR-RFLP) method in Laiwu, Wuzhishan, Guizhou, Bama, Tongcheng, Yorkshire and Landrace pig breeds. Association analysis of genotypes of these SNP loci with economic traits was done in our experimental populations. Significant associations of different genotypes of $RBP5-A/G^{63}$, $RBP5-A/G^{517}$ and $RPB5-T/C^{intron1-90}$ loci with traits including maximum carcass length (LM), minimum carcass length (LN), marbling score (MS), back fat thickness at shoulder (SBF), meat color score (MCS) and hematocrit (HCT) were detected. These SNPs may be useful as genetic markers in genetic improvement for porcine production.

• Korean Journal of Bronchoesophagology
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• v.8 no.1
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• pp.35-41
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• 2002

Background and Objectives : Angiogenesis within malignant tumors has been considered to be essential for the growth and expansion of cancer cells, especially for solid tumors, and has been implicated in the overall growth and metastases of tumors. Such angiogenesis within tumors depends upon the secretion of vascular growth factor to allow the growth of newly formed vessels from peripheral tissue into the malignant tumor. %n, an exploration of the relations between cancer cells and vascular growth factors is absolutely critical to understanding the growth of malignant tumors. According to recent reports, vascular endothelial growth factor(VEGF) has been found to play a role in lymphatic metastases, tumor recurrence and survival in various human tumors. To evaluate the role of VEGF in head and neck squamous cell carcinoma(HNSCC) we performed this study. Materials and Methods : We examined the expression of VEGF and microvessel density in 39 HNSCC by immunohistochemistry and correlated them with various clinical data such as stage, cervical lymphatic metastasis, recurrence, and overall survival. Results : The expression of VEGF was not correlated with overall stage, T stage and N stage. There was no statistical correlation between the expression of VEGF and recurrence in the Primary site, cervical lymph node, and the distant metastases. There was no statistical correlation between the expression of VEGF and microvessel density. Conclusion : Based on these results, it is suggested that the expression of vascular endothelial growth factor is not a major prognostic factor for head and neck squamous cell carcinoma. Further studies are needed to evaluate significance of VEGF expression in head and neck squamous cell carcinoma.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5C
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• pp.527-539
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• 2009

In this paper, we propose an asynchonous ICI (Inter-Cell Interference) mitigation techniques for 3GPP LTE MIMO-OFDMA down-link receiver. An increasing in symbol timing misalignments may occur relative to sychronous network as the result of BS (Base Station) timing differences. Such symbol synchronization errors that exceed the guard interval or the cyclic prefix duration may result in MAI (Multiple Access Interference) for other carriers. In particular, at the cell boundary, this MAI becomes a critical factor, leading to degraded channel throughput and severe asynchronous ICI. Hence, many researchers have investigated the interference mitigation method in the presence of asynchronous ICI and it appears that the knowledge of the SCM (Spatial Covariance Matrix) of the asynchronous ICI plus background noise is an important issue. Generally, it is assumed that the SCM estimated by using training symbols. However, it is difficult to measure the interference statistics for a long time and training symbol is also not appropriate for MIMO-OFDMA system such as LTE. Therefore, a noise reduction method is required to improve the estimation accuracy. Although the conventional time-domain low-pass type weighting method can be effective for noise reduction, it causes significant estimation error due to the spectral leakage in practical OFDM system. Therefore, we propose a time-domain sinc type weighing method which can not only reduce the noise effectively minimizing estimation error caused by the spectral leakage but also implement frequency-domain moving average filter easily. By using computer simulation, we show that the proposed method can provide up to 3dB SIR gain compared with the conventional method.

• The KIPS Transactions:PartC
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• v.16C no.2
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• pp.151-164
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• 2009

The importance of sensor networks as a base of ubiquitous computing realization is being highlighted, and espicially the security is recognized as an important research isuue, because of their characteristics.Several efforts are underway to provide security services in sensor networks, but most of them are preventive approaches based on cryptography. However, sensor nodes are extremely vulnerable to capture or key compromise. To ensure the security of the network, it is critical to develop security Intrusion Detection System (IDS) that can survive malicious attacks from "insiders" who have access to keying materials or the full control of some nodes, taking their charateristics into consideration. In this perper, we design a distributed and adaptive IDS architecture on sensor networks, respecting both of energy efficiency and IDS efficiency. Utilizing a modified HEED algorithm, a clustering algorithm, distributed IDS nodes (dIDS) are selected according to node's residual energy and degree. Then the monitoring results of dIDSswith detection codes are transferred to dIDSs in next round, in order to perform consecutive and integrated IDS process and urgent report are sent through high priority messages. With the simulation we show that the superiorities of our architecture in the the efficiency, overhead, and detection capability view, in comparison with a recent existent research, adaptive IDS.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.3
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• pp.155-163
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• 2023

Real-time monitoring technology is critical for ensuring the safety and reliability of nuclear power plant structures. However, the current seismic monitoring system has limited system identification capabilities such as modal parameter estimation. To obtain global behavior data and dynamic characteristics, multiple sensors must be optimally placed. Although several studies on optimal sensor placement have been conducted, they have primarily focused on civil and mechanical structures. Nuclear power plant structures require robust signals, even at low signal-to-noise ratios, and the robustness of each mode must be assessed separately. This is because the mode contributions of nuclear power plant containment buildings are concentrated in low-order modes. Therefore, this study proposes an optimal sensor placement methodology that can evaluate robustness against noise and the effects of each mode. Indicators, such as auto modal assurance criterion (MAC), cross MAC, and mode shape distribution by node were analyzed, and the suitability of the methodology was verified through numerical analysis.

• Structural Engineering and Mechanics
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• v.87 no.3
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• pp.283-296
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• 2023

Free-vibration and buckling analyses of plate problems are investigated with the aid of the strain gradient notation finite element method (SGN-FEM). As SGN-FEM employs physically interpretable polynomials in developing finite elements, parasitic shear sources, which are the cause of shear locking, can be precisely identified and subsequently eliminated. This allows two mutually complementary objectives to be defined in this work, namely, evaluate the efficiency of free-vibration and buckling results provided by corrected models, and study the severity of parasitic shear effects on plate models performance. Parasitic shear are flexural terms erroneously present in shear strain polynomials. It is reviewed here that six parasitic shear terms arise during the formulation of the four-node Mindlin plate element. Two parasitic shear terms have been identified in the in-plane shear strain polynomial while other two have been identified in each of the transverse shear strain polynomials. The element is corrected a-priori, i.e., during development, by simply removing the spurious terms from the shear strain polynomials. The computational implementation of the element in its two versions, namely, containing the parasitic shear terms (PS) and corrected for parasitic shear (SG), allows for assessments of the accuracy of results and of the deleterious effects of parasitic shear in free vibration and buckling analyses. This assessment of the parasitic shear effects is a novelty of this work. Validation of the SG model is done comparing its results with analytical results and results provided by other numerical procedures. Analyses are performed for square plates with different thickness-to-length ratios and boundary conditions. Results for thin plates provided by the PS model do not converge to the correct solutions, which indicates that parasitic shear must be eliminated. That is, analysts should not rely on refinement alone. For thick plates, PS model results can be considered acceptable as deleterious effects are really critical in thin plates. On the other hand, results provided by the SG model converge well for both thin and thick plates. The effectiveness of the SG model is established via high-accuracy results obtained in several examples. It is concluded that corrected SGN-FEM models are efficient alternatives for free-vibration and buckling analysis of Mindlin plate problems, and that precise elimination of parasitic shear is a requirement for sound analyses.

• Journal of the Korean Society of Radiology
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• v.82 no.4
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• pp.903-913
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• 2021

Purpose To identify the imaging features indicative of sarcoid-like reactions in patients with intrathoracic lymphadenopathy after complete remission of malignancies. Materials and Methods This study enrolled five patients with histopathologically confirmed sarcoid-like reactions that developed after cancer remission. The clinical features and findings of CT and ¹⁸F-fluorodeoxyglucose (FDG) PET/CT were assessed. Results The underlying malignancies included breast, nasopharyngeal, colon, and endometrial cancer and lymphoma. The time intervals between complete remission of malignancy and the diagnosis of sarcoid-like reaction ranged from 6 to 78 months. CT findings of sarcoid-like reaction included bilateral hilar and mediastinal lymphadenopathies (n = 5), pulmonary nodules (1-15 mm) with peribronchovascular, fissural, or subpleural distribution, and interlobular interstitial thickening in the lungs (n = 4). ¹⁸F-FDG PET/CT revealed hypermetabolic uptake in the mediastinal and hilar lymph nodes and both lungs in the absence of extrathoracic uptake (n = 3). The sarcoid-like reactions resolved in all patients after corticosteroid treatment. Conclusion In patients with complete remission of malignancies, newly developed bilateral hilar and mediastinal lymphadenopathies with or without pulmonary nodules of perilymphatic distribution, in the absence of recurrence at the primary tumor site and extrathoracic metastasis, may suggest a sarcoid-like reaction. Such cases warrant histologic evaluation of the lymph nodes to prevent unnecessary systemic chemotherapy.

• Journal of the Korean Society of Radiology
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• v.84 no.6
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• pp.1290-1308
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• 2023

Purpose To compare the diagnostic performance of rectal CT with that of high-resolution rectal MRI and histopathology in assessing rectal cancer. Materials and Methods Sixty-seven patients with rectal cancer who underwent rectal CT with rectal distension using sonographic gel and high-resolution MRI were enrolled in this study. The distance from the anal verge/anorectal junction, distance to the mesorectal fascia (MRF), extramural depth (EMD), extramesorectal lymph node (LN) involvement, extramural venous invasion (EMVI), and T/N stages in rectal CT/MRI were analyzed by two gastrointestinal radiologists. The CT findings of 20 patients who underwent radical surgery without concurrent chemoradiotherapy were compared using histopathology. Interclass correlations and kappa statistics were used. Results The distance from the anal verge/anorectal junction showed an excellent intraclass correlation between CT and MRI for both reviewers. For EMD, the distance to the MRF, presence of LNs, extramesorectal LN metastasis, EMVI, T stage, and intermodality kappa or weighted kappa values between CT and MRI showed excellent agreement. Among the 20 patients who underwent radical surgery, T staging, circumferential resection margin involvement, EMVI, and LN metastasis on rectal CT showed acceptable concordance rates with histopathology. Conclusion Dedicated rectal CT may be on par with rectal MRI in providing critical information to patients with rectal cancer.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.31-59
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• 2007

We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.49-65
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• 2014

Word of Mouth (WOM) is a behavior used by consumers to transfer or communicate their product or service experience to other consumers. Due to the popularity of social media such as Facebook, Twitter, blogs, and online communities, electronic WOM (e-WOM) has become important to the success of products or services. As a result, most enterprises pay close attention to e-WOM for their products or services. This is especially important for movies, as these are experiential products. This paper aims to identify the network factors of an online movie community that impact box office revenue using social network analysis. In addition to traditional WOM factors (volume and valence of WOM), network centrality measures of the online community are included as influential factors in box office revenue. Based on previous research results, we develop five hypotheses on the relationships between potential influential factors (WOM volume, WOM valence, degree centrality, betweenness centrality, closeness centrality) and box office revenue. The first hypothesis is that the accumulated volume of WOM in online product communities is positively related to the total revenue of movies. The second hypothesis is that the accumulated valence of WOM in online product communities is positively related to the total revenue of movies. The third hypothesis is that the average of degree centralities of reviewers in online product communities is positively related to the total revenue of movies. The fourth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. The fifth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. To verify our research model, we collect movie review data from the Internet Movie Database (IMDb), which is a representative online movie community, and movie revenue data from the Box-Office-Mojo website. The movies in this analysis include weekly top-10 movies from September 1, 2012, to September 1, 2013, with in total. We collect movie metadata such as screening periods and user ratings; and community data in IMDb including reviewer identification, review content, review times, responder identification, reply content, reply times, and reply relationships. For the same period, the revenue data from Box-Office-Mojo is collected on a weekly basis. Movie community networks are constructed based on reply relationships between reviewers. Using a social network analysis tool, NodeXL, we calculate the averages of three centralities including degree, betweenness, and closeness centrality for each movie. Correlation analysis of focal variables and the dependent variable (final revenue) shows that three centrality measures are highly correlated, prompting us to perform multiple regressions separately with each centrality measure. Consistent with previous research results, our regression analysis results show that the volume and valence of WOM are positively related to the final box office revenue of movies. Moreover, the averages of betweenness centralities from initial community networks impact the final movie revenues. However, both of the averages of degree centralities and closeness centralities do not influence final movie performance. Based on the regression results, three hypotheses, 1, 2, and 4, are accepted, and two hypotheses, 3 and 5, are rejected. This study tries to link the network structure of e-WOM on online product communities with the product's performance. Based on the analysis of a real online movie community, the results show that online community network structures can work as a predictor of movie performance. The results show that the betweenness centralities of the reviewer community are critical for the prediction of movie performance. However, degree centralities and closeness centralities do not influence movie performance. As future research topics, similar analyses are required for other product categories such as electronic goods and online content to generalize the study results.