• 분석과학
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• 제36권5호
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• pp.224-235
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• 2023

An analytical method was developed for the determination of phenol (P) and the seven substituted phenols in water samples and fish tissue samples collected from three streams located in eastern Gangwon State in spring and summer. The phenols were extracted and then derivatized to phenyl acetates using acetic anhydride. The derivatives were subsequently identified and quantified using gas chromatography coupled with mass spectrometry. P and 4-nitrophenol (4NP) were found at relatively high levels in water, ranging from below the method detection limit (MDL) to 3.32 ㎍/L and from < MDL to 4.91 ㎍/L, respectively. P and 4NP were also the dominant compounds in the fish tissue, ranging from < MDL to 407 ㎍/kg and from < MDL to 870 ㎍/kg, respectively. Phenol concentrations were significantly higher in spring than in summer. The ecological risk quotient calculated for P was higher than 4NP but not high enough to pose any risk of adverse effects to fish health.

• International Journal of Stem Cells
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• 제17권3호
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• pp.298-308
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• 2024

Sine oculis homeobox 1 (Six1) is an important factor for embryonic development and carcinoma malignancy. However, the localization of Six1 varies due to protein size and cell types in different organs. In this study, we focus on the expression and localization of Six1 in male reproductive organ via bioinformatics analysis and immunofluorescent detection. The potential interacted proteins with Six1 were also predicted by protein-protein interactions (PPIs) and Enrichr analysis. Bioinformatic data from The Cancer Genome Atlas and Genotype-Tissue Expression project databases showed that SIX1 was highly expressed in normal human testis, but low expressed in the testicular germ cell tumor sample. Human Protein Atlas examination verified that SIX1 level was higher in normal than that in cancer samples. The sub-localization of SIX1 in different reproductive tissues varies but specifically in the cytoplasm and membrane in testicular cells. In mouse cells, single cell RNA-sequencing data analysis indicated that Six1 expression level was higher in mouse spermatogonial stem cells (mSSCs) and differentiating spermatogonial than in other somatic cells. Immunofluorescence staining showed the cytoplasmic localization of Six1 in mouse testis and mSSCs. Further PPIs and Enrichr examination showed the potential interaction of Six1 with bone morphogenetic protein 4 (Bmp4) and catenin Beta-1 (CtnnB1) and stem cell signal pathways. Cytoplasmic localization of Six1 in male testis and mSSCs was probably associated with stem cell related proteins Bmp4 and CtnnB1 for stem cell development.

• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1657-1662
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• 2017

Facial expression recognition systems using video devices have emerged as an important component of natural human-machine interfaces which contribute to various practical applications such as security systems, behavioral science and clinical practices. In this work, we present a new method to analyze, represent and recognize human facial expressions using a sequence of facial images. Under our proposed facial expression recognition framework, the overall procedure includes: accurate face detection to remove background and noise effects from the raw image sequences and align each image using vertex mask generation. Furthermore, these features are reduced by principal component analysis. Finally, these augmented features are trained and tested using Hidden Markov Model (HMM). The experimental evaluation demonstrated the proposed approach over two public datasets such as Cohn-Kanade and AT&T datasets of facial expression videos that achieved expression recognition results as 96.75% and 96.92%. Besides, the recognition results show the superiority of the proposed approach over the state of the art methods.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권1호
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• pp.41-48
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• 2007

Latest advances in network sensor technology and state of the art of mobile robot, and artificial intelligence research can be employed to develop autonomous and distributed monitoring systems. In this study, as the preliminary step for developing a multi-purpose "Intelligent Space" platform to implement advanced technologies easily to realize smart services to human. We will give an explanation for the ISpace system architecture designed and implemented in this study and a short review of existing techniques, since there exist several recent thorough books and review paper on this paper. Instead we will focus on the main results with relevance to the DIND data fusion with CI of Intelligent Space. We will conclude by discussing some possible future extensions of ISpace. It is first dealt with the general principle of the navigation and guidance architecture, then the detailed functions tracking multiple objects, human detection and motion assessment, with the results from the simulations run.

• ETRI Journal
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• 제44권2호
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권12호
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• pp.3991-4007
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• 2022

In the public healthcare, a computational system that can automatically and efficiently detect and classify falls from a video sequence has significant potential. With the advancement of deep learning, which can extract temporal and spatial information, has become more widespread. However, traditional 3D CNNs that usually adopt shallow networks cannot obtain higher recognition accuracy than deeper networks. Additionally, some experiences of neural network show that the problem of gradient explosions occurs with increasing the network layers. As a result, an enhanced three-dimensional ResNet-based method for fall detection (3D-ERes-FD) is proposed to directly extract spatio-temporal features to address these issues. In our method, a 50-layer 3D residual network is used to deepen the network for improving fall recognition accuracy. Furthermore, enhanced residual units with four convolutional layers are developed to efficiently reduce the number of parameters and increase the depth of the network. According to the experimental results, the proposed method outperformed several state-of-the-art methods.

• Nuclear Engineering and Technology
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• 제53권2호
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• pp.657-665
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• 2021

Nondestructive evaluation methods play an important role in ensuring component integrity and safety in many industries. Operator fatigue can play a critical role in the reliability of such methods. This is important for inspecting high value assets or assets with a high consequence of failure, such as aerospace and nuclear components. Recent advances in convolution neural networks can support and automate these inspection efforts. This paper proposes using residual neural networks (ResNets) for real-time detection of corrosion, including iron oxide discoloration, pitting and stress corrosion cracking, in dry storage stainless steel canisters housing used nuclear fuel. The proposed approach crops nuclear canister images into smaller tiles, trains a ResNet on these tiles, and classifies images as corroded or intact using the per-image count of tiles predicted as corroded by the ResNet. The results demonstrate that such a deep learning approach allows to detect the locus of corrosion via smaller tiles, and at the same time to infer with high accuracy whether an image comes from a corroded canister. Thereby, the proposed approach holds promise to automate and speed up nuclear fuel canister inspections, to minimize inspection costs, and to partially replace human-conducted onsite inspections, thus reducing radiation doses to personnel.

• 융합정보논문지
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• 제9권9호
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• pp.1-12
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• 2019

대화시스템은 인간과 컴퓨터 사이의 새로운 의사소통 수단으로 떠오르고 있다. 대화시스템은 인간의 음성을 입력으로 취하여, 적절한 음성 답변 또는 서비스를 제공하게 된다. 아마존 에코, 네이버 웨이브 등과 같은 대화시스템 제품들이 등장하고 있음에도 불구하고, 이 대화시스템들은 공통적으로 미지원 도메인을 제대로 처리하지 못한다는 문제점을 안고 있다. 이와 관련한 몇몇 연구들이 있었지만, 이 문제를 풀기 위한 더욱 많은 연구가 진행될 필요가 있다. 이 논문에서는, 미지원 도메인 검출과 관련한 기존 연구들에 대하여 3가지 관점, 즉 데이터, 자질, 방법에 대한 관점으로 요약한 정보를 제공한다. 데이터셋이 부족하다는 점으로 인해 타 연구분야에 비해 적은 연구가 수행되어왔으므로, 앞으로 가장 시급한 연구 주제는 대화시스템의 미지원 도메인 검출을 위한 공개용 데이터셋을 구축하고 배포하는 것이다.

• Asian Pacific Journal of Cancer Prevention
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• 제17권6호
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• pp.2767-2773
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• 2016

Human glioma, arising from glial cells of the central nervous system, accounts for almost 30%of all brain tumours, neoplasms with a poor prognosis and high mortality rates worldwide. In the present study we assessed tissue architectural modifications associated with macrophage lineage cells, controversial major immune effector cells within the brain, in human glioma tissue samples from eastern India. Ethically cleared post-operative human glioma samples from our collaborative neurosurgery unit with respective CT/MRI and patient history were collected from the Nodal Centre of Neurosciences in Kolkata, over 9 months. Along with conventional histopathology, samples were subjected to silver-gold staining and fluorescence tagged immunophenotyping for the detection of electron dense brain macrophage/microglia cells in glioma tissue, followed by immune-phenotyping of cells. With higher grades, CD11b+/Iba-1+ macrophage/microglia architecture with de-structured boundaries of glioma lesions indicated malfunction and invasive effector state. Present study documented a contribution of microglia to glioma progression in Eastern India.

• Asian Pacific Journal of Cancer Prevention
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• 제13권7호
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• pp.3173-3178
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• 2012

The enhancer of zeste homolog 2 (EZH2) methyl transferase and histone 3 lysine 27 (H3K27me3) protein can repress gene transcription, and their aberrant expression has been observed in various human cancers. This study determined their expression levels in gastric cancer tissues with reference to clinicopathological features and patient survival. We collected 117 gastric cancer and corresponding normal tissues for immunohistochemistry analysis. In gastric cancers, 82/117 (70.1%) were positive for EZH2 and 66/117 (56.4%) for H3K27me3 proteins in contrast to only 5.41% and 7.25% of normal gastric mucosa specimens, respectively. Kaplan-Meier survival data showed the average overall and disease-free survival of EZH2 high expression patients was 25.2 and 20.2 months, respectively, shorter than that with EZH2 low expression (40.5 and 35.9 months). The average overall survival and disease-free survival of high H3K27me3 expression patients was 23.4 and 17.4 months, shorter than without H3K27me3 expression (37.6 and 34.5 months). The average overall survival and disease-free survival of patients with both EZH2 and H3K27me3 expression was 18.8 and 12.9 months, respectively, shorter than that with either alone (34.7 and 31.2 months) or with low levels of both (43.9 and 39.9 months). Multivariate Cox regression analysis showed that H3K27me3 and EZH2 expression, tumor size differentiation and clinical stage were all independent prognostic factors for predicting patient survival. This study demonstrated that detection of both EZH2 and H3K27me3 proteins can predict poor survival of gastric cancer patients, superior to single protein detection. In addition, H3K27me3 and EZH2 protein expression could predict lymph node metastasis.