• Anatomy and Cell Biology
• /
• v.56 no.2
• /
• pp.236-251
• /
• 2023

Alcohol consumption alongside combination antiretroviral therapy (cART) has attracted research interest, especially because of increasing male infertility. This study investigated the combined effects of alcohol and cART on testicular morphology, biomarkers of oxidative stress, inflammation, and apoptosis. Rats, weighing 330-370 g, were divided into four groups of six animals each; control, alcohol treated (A), cART, and alcohol plus cART treated (A+cART). Following 90 days treatment period, animals were euthanized, testis extracted, and routinely processed for histology and immunohistochemical analysis. Significantly decreased epithelial area fraction, increased luminal and connective tissue area fractions, and reduction of epithelial height and spermatocyte number, were recorded in the treated groups compared to control. Extensive seminiferous epithelial lesions including widened intercellular space, karyolysis, and sloughing of germinal epithelium were recorded in all the treated groups. Furthermore, upregulation of inducible nitric oxide synthase and 8-hydroxydeoxyguanosine, interleukin-6, and caspase 3 recorded in treated animals, was more significant in A+cART group. Also, the levels of interleukin-1β and tumor necrosis factor-α were more elevated in A and cART treated groups than in A+cART, while MDA was significantly elevated in cART and A+cART treated groups compared to control group. Altogether, the results indicate testicular toxicity of the treatments. It is concluded that consuming alcohol or cART induces oxidative stress, inflammation, and apoptosis in testis of rats, which lead to testicular structural and functional derangements, which are exacerbated when alcohol and cART are consumed concurrently. The result will invaluably assist clinicians in management of reproductive dysfunctions in male HIV/AIDS-alcoholic patients on cART.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.1
• /
• pp.192-210
• /
• 2024

Most frequency-domain remote sensing image watermarking algorithms embed watermarks at random locations, which have negative impact on the watermark invisibility. In this study, we propose an adaptive watermarking scheme for remote sensing images that considers the information complexity to select where to embed watermarks to improve watermark invisibility without affecting algorithm robustness. The scheme converts remote sensing images from RGB to YCbCr color space, performs two-level DWT on luminance Y, and selects the high frequency coefficient of the low frequency component (HH^Y₂) as the watermark embedding domain. To achieve adaptive embedding, HH^Y₂ is divided into several 8*8 blocks, the entropy of each sub-block is calculated, and the block with the maximum entropy is chosen as the watermark embedding location. During embedding phase, the watermark image is also decomposed by two-level DWT, and the resulting high frequency coefficient (HH^W₂) is then embedded into the block with maximum entropy using α- blending. The experimental results show that the watermarked remote sensing images have high fidelity, indicating good invisibility. Under varying degrees of geometric, cropping, filtering, and noise attacks, the proposed watermarking can always extract high identifiable watermark images. Moreover, it is extremely stable and impervious to attack intensity interference.

• Advances in nano research
• /
• v.16 no.3
• /
• pp.231-249
• /
• 2024

When the amplitude of the vibrations is equivalent to that clearance, the vibrations for small amplitudes will really be significantly nonlinear. Nonlinearities will not be significant for amplitudes that are rather modest. Finally, nonlinearities will become crucial once again for big amplitudes. Therefore, the concrete panel system may experience a big amplitude in this work as a result of the high temperature. Based on the 3D modeling of the shell theory, the current work shows the influences of the von Kármán strain-displacement kinematic nonlinearity on the constitutive laws of the structure. The system's governing Equations in the nonlinear form are solved using Kronecker and Hadamard products, the discretization of Equations on the space domain, and Duffing-type Equations. Thermo-elasticity Equations. are used to represent the system's temperature. The harmonic solution technique for the displacement domain and the multiple-scale approach for the time domain are both covered in the section on solution procedures for solving nonlinear Equations. An effective data-driven solution is often utilized to predict how different systems would behave. The number of hidden layers and the learning rate are two hyperparameters for the network that are often chosen manually when required. Additionally, the data-driven method is offered for addressing the nonlinear vibration issue in order to reduce the computing cost of the current study. The conclusions of the present study may be validated by contrasting them with those of data-driven solutions and other published articles. The findings show that certain physical and geometrical characteristics have a significant effect on the existing concrete panel structure's susceptibility to temperature change and GPL weight fraction. For building construction industries, several useful recommendations for improving the thermo-mechanics' behavior of structural concrete panels are presented.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.34 no.1
• /
• pp.97-106
• /
• 2016

This study is to suggest the necessity of landscaping alternatives for succession of Takjok(濯足) culture by considering the background and meaning of Takjok's cultural phenomenon shown in old literatures, paintings and ruins of landscape architecture as a front morphemes. Its result is as follows. 1. An old idiom, 'Takyung Takjok(濯纓濯足)' implying a disinterested living attitude from the mundane world and an attitude complying with the nature, has been sublimated to 'Takjokjiyu(濯足之遊)' which means living in comfortable retirement through life in seclusion(隱逸). 2. The meaning of Takjok did not expand into, not only Takyung Takjok, but also into Takcheong(濯淸), Tako(濯吾), and Taksa(濯斯) with continued expansion in its meaning. The spaces the meaning of Takyung Takjok is implied on have also newly expanded into the artificial spaces, including Jeong(亭-pavilion) Jae(齋-house) Heon(軒-eaves), and Ji(池-pond), as well as the natural spaces, including Am(巖-rock) Dae(臺-flat foundation) Dam(潭-deep pond) Ban(盤-dish rock) Seok(石-stone) So(沼-shallow pond) San(山-mountain) Bong(峰-peak), and Cheon(泉-water hole). 3. As seen here, the cultural phenomenon of Takyung Takjok, which have derived from the Dangho(堂號) of buildings, the names of natural objects in Palgyung and Gugok(eight sceneries and nine curves), facilities of Byeolseo garden and Seowon, and the Amgakseo in nature, is worth noting. 4. It should be considered that Takjok includes ordinary people's wisdom to resist the hot weather as well as classical scholar's ideal and the veneration of antiquity. From this perspective, water space, Takjok rocks, and use of water based on the environmental supportability should be newly focused as a recreational space and it reminds us that the spirit of Takjok is a classical mental healing method.

• Journal of Intelligence and Information Systems
• /
• v.21 no.2
• /
• pp.131-150
• /
• 2015

Omission of noun phrases for obligatory cases is a common phenomenon in sentences of Korean and Japanese, which is not observed in English. When an argument of a predicate can be filled with a noun phrase co-referential with the title, the argument is more easily omitted in Encyclopedia texts. The omitted noun phrase is called a zero anaphor or zero pronoun. Encyclopedias like Wikipedia are major source for information extraction by intelligent application systems such as information retrieval and question answering systems. However, omission of noun phrases makes the quality of information extraction poor. This paper deals with the problem of developing a system that can restore omitted noun phrases in encyclopedia documents. The problem that our system deals with is almost similar to zero anaphora resolution which is one of the important problems in natural language processing. A noun phrase existing in the text that can be used for restoration is called an antecedent. An antecedent must be co-referential with the zero anaphor. While the candidates for the antecedent are only noun phrases in the same text in case of zero anaphora resolution, the title is also a candidate in our problem. In our system, the first stage is in charge of detecting the zero anaphor. In the second stage, antecedent search is carried out by considering the candidates. If antecedent search fails, an attempt made, in the third stage, to use the title as the antecedent. The main characteristic of our system is to make use of a structural SVM for finding the antecedent. The noun phrases in the text that appear before the position of zero anaphor comprise the search space. The main technique used in the methods proposed in previous research works is to perform binary classification for all the noun phrases in the search space. The noun phrase classified to be an antecedent with highest confidence is selected as the antecedent. However, we propose in this paper that antecedent search is viewed as the problem of assigning the antecedent indicator labels to a sequence of noun phrases. In other words, sequence labeling is employed in antecedent search in the text. We are the first to suggest this idea. To perform sequence labeling, we suggest to use a structural SVM which receives a sequence of noun phrases as input and returns the sequence of labels as output. An output label takes one of two values: one indicating that the corresponding noun phrase is the antecedent and the other indicating that it is not. The structural SVM we used is based on the modified Pegasos algorithm which exploits a subgradient descent methodology used for optimization problems. To train and test our system we selected a set of Wikipedia texts and constructed the annotated corpus in which gold-standard answers are provided such as zero anaphors and their possible antecedents. Training examples are prepared using the annotated corpus and used to train the SVMs and test the system. For zero anaphor detection, sentences are parsed by a syntactic analyzer and subject or object cases omitted are identified. Thus performance of our system is dependent on that of the syntactic analyzer, which is a limitation of our system. When an antecedent is not found in the text, our system tries to use the title to restore the zero anaphor. This is based on binary classification using the regular SVM. The experiment showed that our system's performance is F1 = 68.58%. This means that state-of-the-art system can be developed with our technique. It is expected that future work that enables the system to utilize semantic information can lead to a significant performance improvement.

• The korean journal of orthodontics
• /
• v.27 no.4 s.63
• /
• pp.559-568
• /
• 1997

For orthodontic tooth movement, optimal orthodontic force should be maintained without periodontal breakdown and alveolar bone should be remodeled physiologically Therefore, To obtain proper occlusion through tooth movement within alveolar bone, we should know the biomechanics of teeth and supporting 4issues. The present study was performed to observe histologic changes of periodontal tissue immediately after application of orthodontic force and during the retention period in growing young adult dogs. In this study, experimental group contained between mandibular left canine and 1st molar and control group contained contralateral teeth of same animal. The .018'x.022' stainless steel closed coil spring(Dentaurum Co.) was ligated on the experimental teeth at initial 200gm-force from mandibular canine to 1st molar The animals(4 to 6 months aged young adult dogs) were sacrificed on 0, 14, 28 days after the finish of appliance activation, and then tissue samples were divided into hematoxylin-eosin(HE) staining section, ground section, alkaline phosphatase(ALP) staining section, and tartrate-resistant acid phosphatase(TRAP) staining section. Thereafter, the preparations were examined under light microscopy The following results were obtained: 1. Immediately after the finish of appliance activation, the periodontal space was increased in tension side, but decreased in pressure side compared to that of control. The hyalinized zone was also observed in the periodontium. 2. After the 14-day retention, peridontal space was decreased in tension side and slightly increased in pressure side compared to that of immediately after the finish of appliance activation. The hyalinized zone was repaired and a few osteoblasts showing slightly new bone formation were seen. Osteoblasts were scarcely observed along the alveolar bone. 3. Aftter the 28-day retention, the periodontal fibers are normally repaired. A lot of TRAP(+) osteoclasts md increased alveolar bone resorption were observed in pressure side, and AP(+) osteoblast and increased new bone formation were observed in tension side.

• Asia pacific journal of information systems
• /
• v.19 no.2
• /
• pp.139-155
• /
• 2009

For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.

• Journal of Intelligence and Information Systems
• /
• v.25 no.4
• /
• pp.105-122
• /
• 2019

Dimensionality reduction is one of the methods to handle big data in text mining. For dimensionality reduction, we should consider the density of data, which has a significant influence on the performance of sentence classification. It requires lots of computations for data of higher dimensions. Eventually, it can cause lots of computational cost and overfitting in the model. Thus, the dimension reduction process is necessary to improve the performance of the model. Diverse methods have been proposed from only lessening the noise of data like misspelling or informal text to including semantic and syntactic information. On top of it, the expression and selection of the text features have impacts on the performance of the classifier for sentence classification, which is one of the fields of Natural Language Processing. The common goal of dimension reduction is to find latent space that is representative of raw data from observation space. Existing methods utilize various algorithms for dimensionality reduction, such as feature extraction and feature selection. In addition to these algorithms, word embeddings, learning low-dimensional vector space representations of words, that can capture semantic and syntactic information from data are also utilized. For improving performance, recent studies have suggested methods that the word dictionary is modified according to the positive and negative score of pre-defined words. The basic idea of this study is that similar words have similar vector representations. Once the feature selection algorithm selects the words that are not important, we thought the words that are similar to the selected words also have no impacts on sentence classification. This study proposes two ways to achieve more accurate classification that conduct selective word elimination under specific regulations and construct word embedding based on Word2Vec embedding. To select words having low importance from the text, we use information gain algorithm to measure the importance and cosine similarity to search for similar words. First, we eliminate words that have comparatively low information gain values from the raw text and form word embedding. Second, we select words additionally that are similar to the words that have a low level of information gain values and make word embedding. In the end, these filtered text and word embedding apply to the deep learning models; Convolutional Neural Network and Attention-Based Bidirectional LSTM. This study uses customer reviews on Kindle in Amazon.com, IMDB, and Yelp as datasets, and classify each data using the deep learning models. The reviews got more than five helpful votes, and the ratio of helpful votes was over 70% classified as helpful reviews. Also, Yelp only shows the number of helpful votes. We extracted 100,000 reviews which got more than five helpful votes using a random sampling method among 750,000 reviews. The minimal preprocessing was executed to each dataset, such as removing numbers and special characters from text data. To evaluate the proposed methods, we compared the performances of Word2Vec and GloVe word embeddings, which used all the words. We showed that one of the proposed methods is better than the embeddings with all the words. By removing unimportant words, we can get better performance. However, if we removed too many words, it showed that the performance was lowered. For future research, it is required to consider diverse ways of preprocessing and the in-depth analysis for the co-occurrence of words to measure similarity values among words. Also, we only applied the proposed method with Word2Vec. Other embedding methods such as GloVe, fastText, ELMo can be applied with the proposed methods, and it is possible to identify the possible combinations between word embedding methods and elimination methods.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.47 no.2
• /
• pp.117-132
• /
• 2019

The study examines the significance and limits of modern park planning by analyzing major planning documents of Gyeongseong in the Japanese colonial era. Among seven selected documents from 1925 to 1940, which show the contents related with park planning, documents of 1930 and 1940 presented the official park plan of Gyeongseong. By the 1920s, the park plan was not a major concern in urban planning of Gyeongseong; however, as the planning law as enacted in 1934, the park plan legally became a part of the official master planning process in the 1930s. In 1940, the most comprehensive park plan for Gyeongseong was published. In the beginning of modern urban planning, a park was mainly perceived as a sanitation utility. From the 1920s to the 1930s, the park planning system was significantly improved including systemic classification of parks, guideline development considering spatial planning, and introduction of a concept of infra-structural green space. Despite of the improvement in the park planning, the actual quantity of the overall green spaces barely changed and there was a huge discrepancy between the planning ideal and the reality. The Gyeongseong stadium was the only facility newly built in the 1920s, and only two parks were constructed in the 1930s. The plan to build 38 new parks in the 1930, and 140 in the 1940 was barely realized. However, there were efforts to improve parks and green spaces of Gyeongseong: Such as appropriating natural forest as parks, designating royal palaces as parks, and focusing on constructing smaller scale children's parks. Even though the ideal plan could not be fully implemented due to the war time situation and tight budget, the park system of Gyeongseong provided the framework of park planning of Seoul after the independence.

• Journal of Wetlands Research
• /
• v.26 no.1
• /
• pp.41-50
• /
• 2024

Plant Microbial Fuel Cells (P-MFCs) are biomass-based energy technologies that generate electricity from plant and root microbial communities and are suitable for natural fundamental solutions considering sustainable environments. In order to develop P-MFC technology suitable for domestic waterfront space, it is necessary to analyze international research trends first. Therefore, in this study, 700 P-MFC-related research papers were investigated in Web of Science, and the core keywords were derived using VOSviewer, a word analysis program, and the research trends were analyzed. First, P-MFC-related research has been on the rise since 1998, especially since the mid to late 2010s. The number of papers submitted by each country was "China," "U.S." and "India." Since the 2010s, interest in P-MFCs has increased, and the number of publications in the Philippines, Ukraine, and Mexico, which have abundant waterfront space and wetland environments, is increasing. Secondly, from the perspective of research trends in different periods, 1998-2015 mainly carried out microbial fuel cell performance verification research in different environments. The 2016-2020 period focuses on the specific conditions of microbial fuel cell use, the structure of P-MFC and how it develops. From 2021 to 2023, specific research on constraints and efficiency improvement in the development of P-MFC was carried out. The P-MFC-related international research trends identified through this study can be used as useful data for developing technologies suitable for domestic waterfront space in the future. In addition to this study, further research is needed on research trends and levels in subsectors, and in order to develop and revitalize P-MFC technologies in Korea, research on field applicability should be expanded and policies and systems improved.