KSII Transactions on Internet and Information Systems (TIIS)
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v.16
no.6
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pp.2018-2043
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2022
Nowadays, COVID-19 infections are influencing our daily lives which have spread globally. The major symptoms' of COVID-19 are dry cough, sore throat, and fever which in turn to critical complications like multi organs failure, acute respiratory distress syndrome, etc. Therefore, to hinder the spread of COVID-19, a Computerized Doughty Predictor Framework (CDPF) is developed to yield benefits in monitoring the progression of disease from Chest CT images which will reduce the mortality rates significantly. The proposed framework CDPF employs Convolutional Neural Network (CNN) as a feature extractor to extract the features from CT images. Subsequently, the extracted features are fed into the Adaptive Dragonfly Algorithm (ADA) to extract the most significant features which will smoothly drive the diagnosing of the COVID and Non-COVID cases with the support of Doughty Learners (DL). This paper uses the publicly available SARS-CoV-2 and Github COVID CT dataset which contains 2482 and 812 CT images with two class labels COVID+ and COVI-. The performance of CDPF is evaluated against existing state of art approaches, which shows the superiority of CDPF with the diagnosis accuracy of about 99.76%.
KSII Transactions on Internet and Information Systems (TIIS)
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v.16
no.3
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pp.813-829
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2022
In multi-view subspace clustering, how to integrate the complementary information between perspectives to construct a unified representation is a critical problem. In the existing works, the unified representation is usually constructed in the original data space. However, when the data representation in each view is very diverse, the unified representation derived directly in the original data domain may lead to a huge information loss. To address this issue, different to the existing works, inspired by the latest revelation that the data across all perspectives have a very similar or close spectral block structure, we try to construct the unified representation in the spectral embedding domain. In this way, the complementary information across all perspectives can be fused into a unified representation with little information loss, since the spectral block structure from all views shares high consistency. In addition, to capture the global structure of data on each view with high accuracy and robustness both, we propose a novel low-rank approximation via the tight lower bound on the rank function. Finally, experimental results prove that, the proposed method has the effectiveness and robustness at the same time, compared with the state-of-art approaches.
Nuclear safety-related underground liquid storage tanks, such as those used to store fuel for emergency diesel generators, are critical components for safety of hundreds of existing nuclear power plants (NPP) worldwide. Since most of those NPP will continue to operate for decades, a beyond design base (BDB) seismic screening of safety-related underground tanks in those NPP is beneficial and essential to public safety. The analytical methodology for buried tank subjected to seismic effect, including a BDB seismic evaluation, needs to consider both soil-structure and fluid-structure interaction effects. Comprehensive analysis of such a soil-structure-fluid system is costly and time consuming, often subjected to availability of state-of-art finite element tools. Simple, but practically and reasonably accurate techniques for seismic evaluation of underground liquid storage tanks have not been established. In this study, a mechanics based solution is proposed for the evaluation of a cylindrical underground liquid storage tank using hand calculation methods. For validation, a practical example of two underground diesel fuel tanks in an existing nuclear power plant is presented and application of the proposed method is confirmed by using published results of the computer-aided System for Analysis of Soil Structural Interaction (SASSI). The proposed approach provides an easy to use tool for BDB seismic assessment prior to making decision of applying more costly technique by owner of the nuclear facility.
Serious games are developed under particular purpose. This study provides a theoretical background on serious games for social change as a basis for future experiments and practice. By examining the elements of games and related theories, narrative immersion and critical participation are identified as the two main experiences of games, which are realized through role play. Based on educational theories for behavioral and cognitive change, this study suggests to use role play as a strategy on serious games for social change. Analyzing the cases of serious games in Korea, this study concludes that participants are able to experience the context of the situation through role play.
Human error (HE) is an important concern in safety-critical systems such as nuclear power plants (NPPs). HE has played a role in many accidents and outage incidents in NPPs. Despite the increased automation in NPPs, HE remains unavoidable. Hence, the need for HE detection is as important as HE prevention efforts. In NPPs, HE is rather rare. Hence, anomaly detection, a widely used machine learning technique for detecting rare anomalous instances, can be repurposed to detect potential HE. In this study, we develop an unsupervised anomaly detection technique based on generative adversarial networks (GANs) to detect anomalies in manually collected surveillance data in NPPs. More specifically, our GAN is trained to detect mismatches between automatically recorded sensor data and manually collected surveillance data, and hence, identify anomalous instances that can be attributed to HE. We test our GAN on both a real-world dataset and an external dataset obtained from a testbed, and we benchmark our results against state-of-the-art unsupervised anomaly detection algorithms, including one-class support vector machine and isolation forest. Our results show that the proposed GAN provides improved anomaly detection performance. Our study is promising for the future development of artificial intelligence based HE detection systems.
Accurately estimation of the geo-mechanical parameters in Artificial Ground Freezing (AGF) is a most important scientific topic in soil improvement and geotechnical engineering. In order for this, one way is using classical and conventional constitutive models based on different theories like critical state theory, Hooke's law, and so on, which are time-consuming, costly, and troublous. The others are the application of artificial intelligence (AI) techniques to predict considered parameters and behaviors accurately. This study presents a comprehensive data-mining-based model for predicting the Young's Modulus of frozen sand under the triaxial test. For this aim, several single and hybrid models were considered including additive regression, bagging, M5-Rules, M5P, random forests (RF), support vector regression (SVR), locally weighted linear (LWL), gaussian process regression (GPR), and multi-layered perceptron neural network (MLP). In the present study, cell pressure, strain rate, temperature, time, and strain were considered as the input variables, where the Young's Modulus was recognized as target. The results showed that all selected single and hybrid predicting models have acceptable agreement with measured experimental results. Especially, hybrid Additive Regression-Gaussian Process Regression and Bagging-Gaussian Process Regression have the best accuracy based on Model performance assessment criteria.
Poultry coccidiosis is an intestinal infection caused by an intracellular parasitic protozoan of the genus Eimeria. Coccidia-induced gastrointestinal inflammation results in large economic losses, hence finding methods to decrease its prevalence is critical for industry participants and academic researchers. It has been demonstrated that coccidiosis can be effectively controlled and managed by employing anticoccidial chemical compounds. However, as a result of their extensive use, anticoccidial drug resistance in Eimeria species has raised concerns. Phytochemical/herbal medicines (Artemisia annua, Bidens pilosa, and garlic) seem to be a promising strategy for preventing coccidiosis, in accordance with the "anticoccidial chemical-free" standards. The impact of herbal supplements on poultry coccidiosis is based on the reduction of oocyst output by preventing the proliferation and growth of Eimeria species in chicken gastrointestinal tissues and lowering intestinal permeability via increased epithelial turnover. This review provides a thorough up-to-date assessment of the state of the art and technologies in the prevention and treatment of coccidiosis in chickens, including the most used phytochemical medications, their mode of action, and the applicable legal framework in the European Union.
International Journal of Computer Science & Network Security
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v.23
no.12
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pp.213-219
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2023
In recent years, popularity of deep learning (DL) is increased due to its ability to extract features from Hyperspectral images. A lack of discrimination power in the features produced by traditional machine learning algorithms has resulted in poor classification results. It's also a study topic to find out how to get excellent classification results with limited samples without getting overfitting issues in hyperspectral images (HSIs). These issues can be addressed by utilising a new learning network structure developed in this study.EfficientNet-B4-Based Convolutional network (EN-B4), which is why it is critical to maintain a constant ratio between the dimensions of network resolution, width, and depth in order to achieve a balance. The weight of the proposed model is optimized by Search and Rescue Operations (SRO), which is inspired by the explorations carried out by humans during search and rescue processes. Tests were conducted on two datasets to verify the efficacy of EN-B4, with Indian Pines (IP) and the University of Pavia (UP) dataset. Experiments show that EN-B4 outperforms other state-of-the-art approaches in terms of classification accuracy.
Bourdieu is one of the few social science researchers who were interested in photography. Bourdieu's work on photography appears principally in two books: Un art moyen: Essai sur les usagrs sociaux de la photographie(1965) and La distinction(1979). In these books, Bourdieu analyzes the role of photography in the family life of peasants and small town and urban dwellers. He shows how different classes and groups express their esthetic worldview in response to different photographs and photographic styles. What Bourdieu analyzed is not just photography but ways of photographing and ways of looking at pictures. Through these analyses, Bourdieu explores the social definition of photography. Bourdieu's ideas on photographic practice in social life are as follows. First, the photography, especially family photography generally practiced, has the integrative function. It recreates the group by ritualizing and solemnizing the important moments of social life in which the group reaffirms its unity. Second, the photography as esthetic practice in search of legitimacy as a fine art becomes a means by which different classes are pitted against each other. Each of classes gives its own meaning to photographic practice. Despite its originality and persuasive power, Bourdieu's work on photography has its own limits. The data used by Bourdieu are 35 years old and relevant to European social life. Things has changed since. First, the technological improvement and innovation in photography was considerable. Cheap and good photographic materials, easy to operate, made photographic practice everybody's everyday activity. New media like camcorder and digital camera made photography one of the industrial discards like jukebox. It means that photography does not function as important means of distinction between classes any longer. The integrative function of the photography becomes more ambiguous too. Second, the esthetic status of the photography has changed. The family photography was already integraed into fine art. Photography is not a middle-brow art any more. Bourdieu's work on photography shows how photography was used by different social classes in European social life of the 1960's. His work is historically and geographically limited. Moreover, his work was ordered by the french affiliate of Eastman Kodak Company. And all along the analysis, Bourdieu didn't hide his intention of distinguishing his sociological method from the other methods, especially psychological one. These mean that Bourdieu's work was done in a specific context, for specific purposes. In this respect, Bourdieu's work on photography, like every sociological work, can not claim to be universal.
Cultural Studies built on the critical mind of New Left exposes the relationship between culture and power, and investigates how this relationship develops the cultural convention. It has achieved the new perspective that could make us to think culture and art in terms of political correctness. However, the critical voices against the theoretical premises of Cultural Studies have been increased as its heyday in 1980s was nearly over. For instance, Terry Eagleton, a former Marxist literary critic, declared in 2003 that the golden age of cultural theory is long past. This essay, therefore, intends to show the weak foundations on which the approaches of cultural studies to theatre rest and to clarify the general problem of their introduction to theatre studies. The approach of cultural studies to theatre takes the form of 'top-down inquiry' as it applies a theory to a particular play or historical period. In other word, from the theory the writer moves to the particular case. The result is not an inquiry but rather a demonstration. This circularity can destroy the point of serious intellectual investigation as the theory dictates answers. The goal-oriented narrow viewpoint as a logical consequence of 'top-down inquiry' makes the researcher to favor the plays or the parts of a play that are proper to test a theory. As a result it loses the fair judgment on the artistic value of a play, and brings about the misinterpretation. The interpreter-oriented reading is the other defect of cultural studies as it disregards the inherent meaning of the text, distorting a play. The approach of cultural studies also consists of a conventionality as it arrives at a stereotyped interpretation by using certain conventions of reasoning and rhetoric. The cultural theories are fundamentally the 'outside theories' that seek to explain not theatre but the very broad features of society and politics. Consequently their application to theatre risks the destructive criticism, disregarding the inherent experience of theatre. Most of, if not all, cultural theories, furthermore, are proven to be lack of empirical basis. The alternative method to them is a 'cognitive science' that proves scientifically our mind being influenced by bodily experience. The application of cultural materialism to Shakespeare's is one of the cases that reveal the limits of cultural studies. Jonathan Dollimore and Water Cohen provide a kind of 'canonical study' in this application that is imitated by the succeeding researchers. As a result the interpretation of has been flooded with repetitive critical remarks, revealing the problem of 'top-down inquiry' and conventional reasoning. Cultural Studies is antipodal to theatre in some respect. It is interested chiefly in the social and political reality while theatre aims to create the fiction world. The theatre studies, therefore, may have to risk the danger of destroying its own base when it adopts cultural studies uncritically. The different stance between theatre and cultural theories also occurs from the opposition of humanism vs. antihumanism. We have to introduce cultural theories selectively and properly not to destroy the inherent experience and domain of theatre.
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