• Molecules and Cells
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• v.39 no.2
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• pp.77-86
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• 2016

Cancer is a heterogeneous disease caused by diverse genomic alterations in oncogenes and tumor suppressor genes. Despite recent advances in high-throughput sequencing technologies and development of targeted therapies, novel cancer drug development is limited due to the high attrition rate from clinical studies. Patient-derived xenografts (PDX), which are established by the transfer of patient tumors into immunodeficient mice, serve as a platform for co-clinical trials by enabling the integration of clinical data, genomic profiles, and drug responsiveness data to determine precisely targeted therapies. PDX models retain many of the key characteristics of patients' tumors including histology, genomic signature, cellular heterogeneity, and drug responsiveness. These models can also be applied to the development of biomarkers for drug responsiveness and personalized drug selection. This review summarizes our current knowledge of this field, including methodologic aspects, applications in drug development, challenges and limitations, and utilization for precision cancer medicine.

• Structural Monitoring and Maintenance
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• v.2 no.4
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• pp.399-418
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• 2015

Automated damage detection through Structural Health Monitoring (SHM) techniques has become an active area of research in the bridge engineering community but widespread implementation on in-service infrastructure still presents some challenges. In the meantime, visual inspection remains as the most common method for condition assessment even though collected information is highly subjective and certain types of damage can be overlooked by the inspector. In this article, a Frequency Response Functions-based model updating algorithm is evaluated using experimentally collected data from the University of Central Florida (UCF)-Benchmark Structure. A protocol for measurement selection and a regularization technique are presented in this work in order to provide the most well-conditioned model updating scenario for the target structure. The proposed technique is composed of two main stages. First, the initial finite element model (FEM) is calibrated through model updating so that it captures the dynamic signature of the UCF Benchmark Structure in its healthy condition. Second, based upon collected data from the damaged condition, the updating process is repeated on the baseline (healthy) FEM. The difference between the updated parameters from subsequent stages revealed both location and extent of damage in a "blind" scenario, without any previous information about type and location of damage.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.286-293
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• 2021

Recently, the quick development rate of apps in the Android platform has led to an accelerated increment in creating malware applications by cyber attackers. Numerous Android malware detection tools have utilized conventional signature-based approaches to detect malware apps. However, these conventional strategies can't identify the latest apps on whether applications are malware or not. Many new malware apps are periodically discovered but not all malware Apps can be accurately detected. Hence, there is a need to propose intelligent approaches that are able to detect the newly developed Android malware applications. In this study, Radial Basis Function (RBF) networks are trained using known Android applications and then used to detect the latest and new Android malware applications. Initially, the optimal permission features of Android apps are selected using Information Gain Ratio (IGR). Appropriately, the features selected by IGR are utilized to train the RBF networks in order to detect effectively the new Android malware apps. The empirical results showed that RBF achieved the best detection accuracy (97.20%) among other common machine learning techniques. Furthermore, RBF accomplished the best detection results in most of the other measures.

• Genes and Genomics
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• v.40 no.11
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• pp.1249-1258
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• 2018

The Jeju horse is an indigenous Korean horse breed that is currently registered with the Food and Agriculture Organization of the United Nations. However, there is severe lack of genomic studies on Jeju horse. This study was conducted to investigate genetic characteristics of horses including Jeju horse, Thoroughbred and Jeju crossbred (Jeju${\times}$Thoroughbred) populations. We compared the genomes of three horse populations using the Equine SNP70 Beadchip array. Short-range Linkage disequilibrium was the highest in Thoroughbred, whereas $r^2$ values were lowest in Jeju horse. Expected heterozygosity was the highest in Jeju crossbred (0.351), followed by the Thoroughbred (0.337) and Jeju horse (0.311). The level of inbreeding was slightly higher in Thoroughbred (-0.009) than in Jeju crossbred (-0.035) and Jeju horse (-0.038). $F_{ST}$ value was the highest between Jeju horse and Thoroughbred (0.113), whereas Jeju crossbred and Thoroughbred showed the lowest value (0.031). The genetic relationship was further assessed by principal component analysis, suggesting that Jeju crossbred is more genetically similar to Thoroughbred than Jeju horse population. Additionally, we detected potential selection signatures, for example, in loci located on LCORL/NCAPG and PROP1 genes that are known to influence body. Genome-wide analyses of the three horse populations showed that all the breeds had somewhat a low level of inbreeding within each population. In the population structure analysis, we found that Jeju crossbred was genetically closer to Thoroughbred than Jeju horse. Furthermore, we identified several signatures of selection which might be associated with traits of interest. To our current knowledge, this study is the first genomic research, analyzing genetic relationships of Jeju horse, Thoroughbred and Jeju crossbred.

• Smart Structures and Systems
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• v.15 no.4
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• pp.997-1018
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• 2015

Structural health monitoring along with damage detection and assessment of its severity level in non-accessible reinforced concrete members using piezoelectric materials becomes essential since engineers often face the problem of detecting hidden damage. In this study, the potential of the detection of flexural damage state in the lower part of the mid-span area of a simply supported reinforced concrete beam using piezoelectric sensors is analytically investigated. Two common severity levels of flexural damage are examined: (i) cracking of concrete that extends from the external lower fiber of concrete up to the steel reinforcement and (ii) yielding of reinforcing bars that occurs for higher levels of bending moment and after the flexural cracking. The purpose of this investigation is to apply finite element modeling using admittance based signature data to analyze its accuracy and to check the potential use of this technique to monitor structural damage in real-time. It has been indicated that damage detection capability greatly depends on the frequency selection rather than on the level of the harmonic excitation loading. This way, the excitation loading sequence can have a level low enough that the technique may be considered as applicable and effective for real structures. Further, it is concluded that the closest applied piezoelectric sensor to the flexural damage demonstrates higher overall sensitivity to structural damage in the entire frequency band for both damage states with respect to the other used sensors. However, the observed sensitivity of the other sensors becomes comparatively high in the peak values of the root mean square deviation index.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9C
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• pp.908-922
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• 2003

The Public Key Infrastructure (PKI) trends to delegate the certificate path processing to the Delegated Path Discovery (DPD) Server and Delegated Path Validation (DPV) server recently. The most critical factor for the selection of the delegated server is to allow the server to be equipped with a high reliability through a low cost, and simple implementation. In this paper, we propose a new certificate path processing scheme employed the trusted CA as the DPD/DPV server by adding the capability of the Validation Authority (VA) to the trusted CA. Since our proposed scheme uses the existing trusted CA as validation server, we can achieve a high trust through a simple implementation for the processing. Besides, we propose an additional scheme for reducing an overhead on the trusted CA. it is obtained by delegating digital signature verification to CAs on the path and by skipping the repeated path processing. As the result, our proposed validation scheme can be performed efficiently with high speed and low computational overhead.

• Molecules and Cells
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• v.43 no.4
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• pp.331-339
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• 2020

Genetic modifications in noncoding regulatory regions are likely critical to human evolution. Human-accelerated noncoding elements are highly conserved noncoding regions among vertebrates but have large differences across humans, which implies human-specific regulatory potential. In this study, we found that human-accelerated noncoding elements were frequently coupled with DNase I hypersensitive sites (DHSs), together with monomethylated and trimethylated histone H3 lysine 4, which are active regulatory markers. This coupling was particularly pronounced in fetal brains relative to adult brains, non-brain fetal tissues, and embryonic stem cells. However, fetal brain DHSs were also specifically enriched in deeply conserved sequences, implying coexistence of universal maintenance and human-specific fitness in human brain development. We assessed whether this coexisting pattern was a general one by quantitatively measuring evolutionary rates of DHSs. As a result, fetal brain DHSs showed a mixed but distinct signature of regional conservation and outlier point acceleration as compared to other DHSs. This finding suggests that brain developmental sequences are selectively constrained in general, whereas specific nucleotides are under positive selection or constraint relaxation simultaneously. Hence, we hypothesize that human- or primate-specific changes to universally conserved regulatory codes of brain development may drive the accelerated, and most likely adaptive, evolution of the regulatory network of the human brain.

• Journal of Korean society of Dental Hygiene
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• v.6 no.3
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• pp.219-228
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• 2006

The research which it sees against the self concept of part dental hygienes students from the hazard which it examines dental hygienes which is located on Kyoung-Buk and students 318 people in the object un-signature it enforced a research with the entry method which it got a same result. 1. From general characteristics of part hygiene students "the employment went well from the motive which selects hygiene" and it appeared most highly. The employment will go well and the social advance will do and ease when seeing specially with characteristics of college, it has an corresponding with the fact that is a possibility of employment.. 2. The average score against the self concept of part hygiene students "me it is an existence which is isolated from this world and nothing to do with the others". It appeared most highly with 3.52. The negation self concept appeared more highly affirmative self concept than. 3. To self concept and grade, religion, health condition, hygiene selection motive, subject record and native high school of part hygiene students the difference which considers statistically did not appear(p>0.05). However it tries to observe the self concept which it follows subject satisfactory degree, it is very unsatisfactorily(3.37) with it is unsatisfactorily(3.16) gaps it was not visible the difference which considers statistically, it is very satisfied(3.37) with the difference which considers statistically it was visible(p<0.05). Students the affirmative reaction is correct phenomenon in order to establish a specialty intuition. 4. When self concept and record and the subject satisfaction sees a interrelation for, Between self concept subject satisfaction is appeare big affirmative interrelation(r=0.331) and the subject record and subject satisfaction just interrelation appeared as well(r=0.282) all they considered statistically and appeared.(p=0.000) but to self concept and subject record for the interrelation did not appear. Negation self concept of part hygiene students appears more strongly than affirmative one, And studying for self concept of the students, it leads through the program which is the possibility to pull affirmatively is demanded.

• Journal of Digital Contents Society
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• v.19 no.2
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• pp.363-370
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• 2018

Ransomware detection has become a hot topic in computer security for protecting digital contents. Unfortunately, current signature-based and static detection models are often easily evadable by compress, and encryption. For overcoming the lack of these detection approach, we have proposed the dynamic ransomware detection system using data mining techniques such as RF, SVM, SL and NB algorithms. We monitor the actual behaviors of software to generate API calls flow graphs. Thereafter, data normalization and feature selection were applied to select informative features. We improved this analysis process. Finally, the data mining algorithms were used for building the detection model for judging whether the software is benign software or ransomware. We conduct our experiment using more suitable real ransomware samples. and it's results show that our proposed system can be more effective to improve the performance for ransomware detection.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.3
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• pp.563-577
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• 2017

Due to the Internet and computing capability, new and variant malware are discovered around 1 Million per day. Companies use dynamic analysis such as behavior analysis on virtual machines for unknown malware detection because attackers use unknown malware which is not detected by signature based AV effectively. But growing number of malware types are not only PE(Portable Executable) but also non-PE such as MS word or PDF therefore dynamic analysis must need more resources and computing powers to improve detection effectiveness. This study elicits the pre-filtering system evaluation factor to improve effective dynamic malware analysis system and presents and verifies the decision making model and the formula for solution selection using AHP(Analytics Hierarchy Process)