• International Journal of Computer Science & Network Security
• /
• v.23 no.1
• /
• pp.112-119
• /
• 2023

Traditionally used for networking computers and communications, the Internet has been evolving from the beginning. Internet is the backbone for many things on the web including social media. The concept of social networking which started in the early 1990s has also been growing with the internet. Social Networking Sites (SNSs) sprung and stayed back to an important element of internet usage mainly due to the services or provisions they allow on the web. Twitter and Facebook have become the primary means by which most individuals keep in touch with others and carry on substantive conversations. These sites allow the posting of photos, videos and support audio and video storage on the sites which can be shared amongst users. Although an attractive option, these provisions have also culminated in issues for these sites like posting offensive material. Though not always, users of SNSs have their share in promoting hate by their words or speeches which is difficult to be curtailed after being uploaded in the media. Hence, this article outlines a process for extracting user reviews from the Twitter corpus in order to identify instances of hate speech. Through the use of MPCA (Modified Principal Component Analysis) and ECNN, we are able to identify instances of hate speech in the text (Enhanced Convolutional Neural Network). With the use of NLP, a fully autonomous system for assessing syntax and meaning can be established (NLP). There is a strong emphasis on pre-processing, feature extraction, and classification. Cleansing the text by removing extra spaces, punctuation, and stop words is what normalization is all about. In the process of extracting features, these features that have already been processed are used. During the feature extraction process, the MPCA algorithm is used. It takes a set of related features and pulls out the ones that tell us the most about the dataset we give itThe proposed categorization method is then put forth as a means of detecting instances of hate speech or abusive language. It is argued that ECNN is superior to other methods for identifying hateful content online. It can take in massive amounts of data and quickly return accurate results, especially for larger datasets. As a result, the proposed MPCA+ECNN algorithm improves not only the F-measure values, but also the accuracy, precision, and recall.

• Journal of Korea Water Resources Association
• /
• v.56 no.10
• /
• pp.619-629
• /
• 2023

Recent intensification of climate change has led to an increase in damages caused by droughts. Currently, in Korea, the Standardized Precipitation Index (SPI) is used as a criterion to classify the intensity of droughts. Based on the accumulated precipitation over the past six months (SPI-6), meteorological drought intensities are classified into four categories: concern, caution, alert, and severe. However, there is a limitation in classifying drought intensity solely based on precipitation. To overcome the limitations of the meteorological drought warning criteria based on SPI, this study collected emergency water supply damage data from the National Drought Information Portal (NDIP) to classify drought intensity. Factors of SPI, such as precipitation, and factors used to calculate evapotranspiration, such as temperature and humidity, were indexed using min-max normalization. Coefficients for each factor were determined based on the Genetic Algorithm (GA). The drought intensity based on emergency water supply was used as the dependent variable, and the coefficients of each meteorological factor determined by GA were used as coefficients to derive a new Drought Severity Classification Index (DSCI). After deriving the DSCI, cumulative distribution functions were used to present intensity stage classification boundaries. It is anticipated that using the proposed DSCI in this study will allow for more accurate drought intensity classification than the traditional SPI, supporting decision-making for disaster management personnel.

• Journal of the Institute of Convergence Signal Processing
• /
• v.24 no.3
• /
• pp.134-139
• /
• 2023

Rehabilitators perform outpatient treatment and daily rehabilitation exercises to recover physical function with the aim of quickly returning to society after surgical treatment. Unlike performing exercises in a hospital with the help of a professional therapist, there are many difficulties in performing rehabilitation exercises by the patient on a daily basis. In this paper, we propose a CNN-LSTM-based upper limb rehabilitation real-time monitoring system so that patients can perform rehabilitation efficiently and with correct posture on a daily basis. The proposed system measures biological signals through shoulder-mounted hardware equipped with EMG and IMU, performs preprocessing and normalization for learning, and uses them as a learning dataset. The implemented model consists of three polling layers of three synthetic stacks for feature detection and two LSTM layers for classification, and we were able to confirm a learning result of 97.44% on the validation data. After that, we conducted a comparative evaluation with the Teachable machine, and as a result of the comparative evaluation, we confirmed that the model was implemented at 93.6% and the Teachable machine at 94.4%, and both models showed similar classification performance.

• Nutrition Research and Practice
• /
• v.18 no.5
• /
• pp.633-646
• /
• 2024

BACKGROUND/OBJECTIVES: Cladophora glomerata extract (CGE), rich in polyphenols, was reported to exhibit antidiabetic and renoprotective effects by modulating the functions of protein kinases-mediated organic anion transporter 1 (Oat1) and 3 (Oat3) in rats with type 2 diabetes mellitus (T2DM). Nevertheless, the antioxidant effects of CGE on such renoprotection have not been investigated. This study examined the mechanisms involved in the antioxidant effects of CGE on renal organic anion transport function in an in vivo study. MATERIALS/METHODS: Diabetes was induced in the rats through a high-fat diet combined with a single dose of 40 mg/kg body weight (BW) streptozotocin. Subsequently, normal-diet rats were supplemented with a vehicle or 1,000 mg/kg BW of CGE, while T2DM rats were supplemented with a vehicle, CGE, or 200 mg/kg BW of vitamin C for 12 weeks. The study evaluated the general characteristics of T2DM and renal oxidative stress markers. The renal organic transport function was assessed by measuring the para-aminohippurate (PAH) uptake using renal cortical slices and renal inflammatory cytokine expression in the normal diet (ND) and ND + CGE treated groups. RESULTS: CGE supplementation significantly reduced hyperglycemia, hypertriglyceridemia, insulin resistance, and renal lipid peroxidation in T2DM rats. This was accompanied by the normalization of high expressions of renal glutathione peroxidase and nuclear factor kappa B by CGE and vitamin C. The renal anti-inflammation of CGE was evidenced by the reduction of tumor necrosis factor-1α and interleukin-1β. CGE directly blunted sodium nitroprusside-induced renal oxidative/nitrosative stresses and mediated the PAH uptake in the normally treated CGE in rats was particularly noteworthy. These data also correlated with reduced nitric oxide production, highlighting the potential of CGE as a therapeutic agent for managing T2DM-related renal complications. CONCLUSION: These findings suggest that CGE has antidiabetic effects and directly prevents diabetic nephropathy through oxidative/nitrosative stress pathways.

• Journal of the Korean earth science society
• /
• v.27 no.4
• /
• pp.475-485
• /
• 2006

The physical properties of the central and southwestern crust of South Korea were estimated by comparing values of ${Q_P}^{-1}\;and\;{Q_S}^{-1}$ in the Kimcheon and Mokpo areas. In order to get ${Q_P}^{-1}\;and\;{Q_S}^{-1}$ values, seismic data were collected from two stations of the KIGAM network (KMC and MUN) and four stations of the KMA network (CPN, KUC, MOP, and WAN). An extended coda-normalization method was applied to these data. Estimates of ${Q_P}^{-1}\;and\;{Q_S}^{-1}$ show variations depending on frequency. As frequencies vary from 3 Hz to 24 Hz, the estimates decrease from $(1.4{\pm}3.9){\times}10^{-3}\;to\;(2.3{\pm}3.5){\times}10^{-4}\;for\;{Q_P}^{-1}\;and\;(1.8{\pm}1.3){\times}10^{-3}\;to\;(1.9{\pm}1.5){\times}10^{-4}\;for\;{Q_S}^{-1}$ in central South Korea, and $(5.9{\pm}4.8){\times}10^{-3}\;to\;(2.2{\pm}3.8){\times}10^{-4}\;for\;{Q_P}^{-1}\;and\;(0.5{\pm}2.8){\times}10^{-3}\;to\;(1.8{\pm}1.6){\times}10^{-4}\;for\;{Q_S}^{-1}$ in southwestern South Korea. According that a frequency-dependent power law is applied to the data, the best fits of ${Q_P}^{-1}\;and\;{Q_S}^{-1}\;are\;0.003f^{-0.49}\;and\;0.005f^{-1.03}$ in central South Korea, and $0.026f^{-1.47}$ and $0.001f^{-0.49}$ in southwestern South Korea, respectively. These values almost correspond to those of seismically stable regions although ${Q_P}^{-1}$ values of southwestern South Korea are a little high due to lack of data used.

• The Korean Journal of Nuclear Medicine
• /
• v.38 no.3
• /
• pp.241-252
• /
• 2004

Purpose: Population based structural and functional maps of the brain provide effective tools for the analysis and interpretation of complex and individually variable brain data. Brain MRI and PET standard templates and statistical probabilistic maps based on image data of Korean normal volunteers have been developed and probabilistic maps based on cytoarchitectonic data have been introduced. A quantification method using these data was developed for the objective assessment of regional intensity in the brain images. Materials and Methods: Age, gender and ethnic specific anatomical and functional brain templates based on MR and PET images of Korean normal volunteers were developed. Korean structural probabilistic maps for 89 brain regions and cytoarchitectonic probabilistic maps for 13 Brodmann areas were transformed onto the standard templates. Brain FDG PET and SPGR MR images of normal volunteers were spatially normalized onto the template of each modality and gender. Regional uptake of radiotracers in PET and gray matter concentration in MR images were then quantified by averaging (or summing) regional intensities weighted using the probabilistic maps of brain regions. Regionally specific effects of aging on glucose metabolism in cingulate cortex were also examined. Results: Quantification program could generate quantification results for single spatially normalized images per 20 seconds. Glucose metabolism change in cingulate gyrus was regionally specific: ratios of glucose metabolism in the rostral anterior cingulate vs. posterior cingulate and the caudal anterior cingulate vs. posterior cingulate were significantly decreased as the age increased. 'Rostral anterior'/'posterior' was decreased by 3.1% per decade of age ($P<10^{-11}$, r=0.81) and 'caudal anterior'/'posterior' was decreased by 1.7% ($P<10^{-8}$, r=0.72). Conclusion: Ethnic specific standard templates and probabilistic maps and quantification program developed in this study will be useful for the analysis of brain image of Korean people since the difference in shape of the hemispheres and the sulcal pattern of brain relative to age, gender, races, and diseases cannot be fully overcome by the nonlinear spatial normalization techniques.

• Monthly Notices of the Royal Astronomical Society
• /
• v.501 no.4
• /
• pp.5616-5645
• /
• 2021

We analyse the large-scale clustering in Fourier space of emission line galaxies (ELG) from the Data Release 16 of the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey. The ELG sample contains 173 736 galaxies covering 1170 deg² in the redshift range 0.6 eff = 0.845 we measure D_V(z_eff)/r_drag = 18.33^+0.57_-0.62, with D_V the volume-averaged distance and r_drag the comoving sound horizon at the drag epoch. In combination with the RSD measurement, at z_eff = 0.85 we find fσ₈(z_eff) = 0.289^+0.085_-0.096, with f the growth rate of structure and σ₈ the normalization of the linear power spectrum, D_H(z_eff)/r_drag = 20.0^+2.4_-2.2 and D_M(z_eff)/r_drag = 19.17 ± 0.99 with D_H and D_M the Hubble and comoving angular distances, respectively. These results are in agreement with those obtained in configuration space, thus allowing a consensus measurement of fσ₈(z_eff) = 0.315 ± 0.095, D_H(z_eff)/r_drag = 19.6^+2.2_-2.1 and D_M(z_eff)/r_drag = 19.5 ± 1.0. This measurement is consistent with a flat ΛCDM model with Planck parameters.

• Childhood Kidney Diseases
• /
• v.3 no.2
• /
• pp.153-160
• /
• 1999

Purpose : Present study was undertaken to find out significance of clinical presentation, initial laboratory data and renal biopsy findings on subsequent clinical course of IgA nephropathy in children. Methods : Clinical and laboratory data were analysed retrospectively from 60 children who have been admitted to the Pediatric Department of Kyungpook National University Hospital for the past 11 years and diagnosed as IgA nephropathy. Renal biopsy findings were graded according to the pathologic subclass proposed by Haas. Results : Pathologic grading according to Haas subclassification showed 10 cases in subclass I, 36 in II, 12 in IV and 2 in V and none in subclass II. Sex distribution showed male predominance (male to female ratio = 3 : 1) and mean age at onset of disease was $10.4{\pm}2.8$ years. Episodes of gross hematuria was seen in 71.7% and IgA level increased in 28.3% of children and these were not associated with pathologic grading nor clinical outcomes. With increasing subclass grading, serum protein and albumin decreased and 24 hours urinary protein excretion increased. Normalization of urinalysis (disappearance of hematuria) was seen in 14% at 1-2 years and 37.1% at 3-4 years of follow up period. In 3 cases, renal function deteriorated progressively and they belonged one each to the Haas subclass III, IV and V. Conclusion : In children with IgA nephropathy, progression to chronic renal failure appears to be quite high and pathologic grading according to Haas' subclassification seems to predict patient's outcome faily well. However, firm conclusion cannot be drawn from present study due to the small numbers of patients and short follow-up period. Therefore further multicenter study involving larger numbers of patients and longer periods of follow-up over 10 years was to be undertaken.

• Korean Journal of Soil Science and Fertilizer
• /
• v.43 no.5
• /
• pp.705-715
• /
• 2010

The adoption of carbon foot print system is being activated mostly in the developed countries as one of the long-term response towards tightened up regulations and standards on carbon emission in the agricultural sector. The Korean Ministry of Environment excluded the primary agricultural products from the carbon foot print system due to lack of LCI (life cycle inventory) database in agriculture. Therefore, the research on and establishment of LCI database in the agriculture for adoption of carbon foot print system is urgent. Development of LCA (life cycle assessment) methodology for application of LCA to agricultural environment in Korea is also very important. Application of LCA methodology to agricultural environment in Korea is an early stage. Therefore, this study was carried out to find out the effect of lettuce cultivation on agricultural environment by establishing LCA methodology. Data collection of agricultural input and output for establishing LCI was carried out by collecting statistical data and documents on income from agro and livestock products prepared by RDA. LCA methodology for agriculture was reviewed by investigating LCA methodology and LCA applications of foreign countries. Results based on 1 kg of lettuce production showed that inputs including N, P, organic fertilizers, compound fertilizers and crop protectants were the main sources of major emission factor during lettuce cropping process. The amount of inputs considering the amount of active ingredients was required to estimate the actual quantity of the inputs used. Major emissions due to agricultural activities were $N_2O$ (emission to air) and ${NO_3}^-$/${PO_4}^-$ (emission to water) from fertilizers, organic compounds from pesticides and air pollutants from fossil fuel combustion in using agricultural machines. The softwares for LCIA (life cycle impact assessment) and LCA used in Korea are 'PASS' and 'TOTAL' which have been developed by the Ministry of Knowledge Economy and the Ministry of Environment. However, the models used for the softwares are the ones developed in foreign countries. In the future, development of models and optimization of factors for characterization, normalization and weighting suitable to Korean agricultural environment need to be done for more precise LCA analysis in the agricultural area.

• Journal of KIISE:Software and Applications
• /
• v.30 no.9
• /
• pp.829-842
• /
• 2003

In this Paper, we propose the new face detection and tracking method based on template matching for real-time applications such as, teleconference, telecommunication, front stage of surveillance system using face recognition, and video-phone applications. Since the main purpose of paper is to track a face regardless of various environments, we use template-based face tracking method. To generate robust face templates, we apply wavelet transform to the average face image and extract three types of wavelet template from transformed low-resolution average face. However template matching is generally sensitive to the change of illumination conditions, we apply Min-max normalization with histogram equalization according to the variation of intensity. Tracking method is also applied to reduce the computation time and predict precise face candidate region. Finally, facial components are also detected and from the relative distance of two eyes, we estimate the size of facial ellipse.