Journal of the Korean Institute of Intelligent Systems
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v.16
no.6
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pp.721-729
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2006
Numbers of research on ontology construction and its application are being done for knowledge and information processing using computers. But, the current ontology development methods and ontology construction tools are using in restricted field on propose. Therefore, proper ontology development processes and ontology construction tools on ontology characteristic are needed. In this paper, we propose ontology construction process(OntoProcess) that non-experts in specific field are able to construct ontology through conceptualization of knowledge and formalization of concepts from language resource. Beside, some problems may be occurred while numbers of people are working together to construct ontology: i)duplicated concept definition in conceptualization process of knowledge and ii)decreasing efficiency of ontology construction by short understanding about formal language and tool operation in formalization process. To solve the problems, we propose an ontology construction process for multiple developers (OntoProcess) using meta ontology. We develop an ontology construction system(OntoCS) based on proposed processes, and we show the efficiency of proposed processes and system from ontology construction experiment.
Background and Objectives: The influence of music training on different areas of the brain has been extensively researched, but the underlying neurobehavioral mechanisms remain unknown. In the present study, the effects of training for more than three years in Carnatic music (an Indian form of music) on the discrimination ability of different areas of the brain were tested using P300 analysis at three electrode placement sites. Subjects and Methods: A total of 27 individuals, including 13 singers aged 16-30 years (mean±standard deviation, 23±3.2 years) and 14 non-singers aged 16-30 years (mean age, 24±2.9 years), participated in this study. The singers had 3-5 years of formal training experience in Carnatic music. Cortical activities in areas corresponding to attention, discrimination, and memory were tested using P300 analysis, and the tests were performed using the Intelligent Hearing System. Results: The mean P300 amplitude of the singers at the Fz electrode placement site (5.64±1.81) was significantly higher than that of the non-singers (3.85±1.60; t(25)=3.3, p<0.05). The amplitude at the Cz electrode placement site in singers (5.90±2.18) was significantly higher than that in non-singers (3.46±1.40; t(25)=3.3, p<0.05). The amplitude at the Pz electrode placement site in singers (4.94±1.89) was significantly higher than that in non-singers (3.57±1.50; t(25)=3.3, p<0.05). Among singers, the mean P300 amplitude was significantly higher in the Cz site than the other placement sites, and among non-singers, the mean P300 amplitude was significantly higher in the Fz site than the other placement sites, i.e., music training facilitated enhancement of the P300 amplitude at the Cz site. Conclusions: The findings of this study suggest that more than three years of training in Carnatic singing can enhance neural coding to discriminate subtle differences, leading to enhanced discrimination abilities of the brain, mainly in the generation site corresponding to Cz electrode placement.
Background and Objectives: The influence of music training on different areas of the brain has been extensively researched, but the underlying neurobehavioral mechanisms remain unknown. In the present study, the effects of training for more than three years in Carnatic music (an Indian form of music) on the discrimination ability of different areas of the brain were tested using P300 analysis at three electrode placement sites. Subjects and Methods: A total of 27 individuals, including 13 singers aged 16-30 years (mean±standard deviation, 23±3.2 years) and 14 non-singers aged 16-30 years (mean age, 24±2.9 years), participated in this study. The singers had 3-5 years of formal training experience in Carnatic music. Cortical activities in areas corresponding to attention, discrimination, and memory were tested using P300 analysis, and the tests were performed using the Intelligent Hearing System. Results: The mean P300 amplitude of the singers at the Fz electrode placement site (5.64±1.81) was significantly higher than that of the non-singers (3.85±1.60; t(25)=3.3, p<0.05). The amplitude at the Cz electrode placement site in singers (5.90±2.18) was significantly higher than that in non-singers (3.46±1.40; t(25)=3.3, p<0.05). The amplitude at the Pz electrode placement site in singers (4.94±1.89) was significantly higher than that in non-singers (3.57±1.50; t(25)=3.3, p<0.05). Among singers, the mean P300 amplitude was significantly higher in the Cz site than the other placement sites, and among non-singers, the mean P300 amplitude was significantly higher in the Fz site than the other placement sites, i.e., music training facilitated enhancement of the P300 amplitude at the Cz site. Conclusions: The findings of this study suggest that more than three years of training in Carnatic singing can enhance neural coding to discriminate subtle differences, leading to enhanced discrimination abilities of the brain, mainly in the generation site corresponding to Cz electrode placement.
The agricultural sector is completely different from other sectors since it completely relies on various natural and climatic factors. Climate changes have many effects, including lack of annual rainfall and pests, heat waves, changes in sea level, and global ozone/atmospheric CO2 fluctuation, on land and agriculture in similar ways. Climate change also affects the environment. Based on these factors, farmers chose their crops to increase productivity in their fields. Many existing agricultural ontologies are either domain-specific or have been created with minimal vocabulary and no proper evaluation framework has been implemented. A new agricultural ontology focused on subdomains is designed to assist farmers using Jaccard relative extractor (JRE) and Naïve Bayes algorithm. The JRE is used to find the similarity between two sentences and words in the agricultural documents and the relationship between two terms is identified via the Naïve Bayes algorithm. In the proposed method, the preprocessing of data is carried out through natural language processing techniques and the tags whose dimensions are reduced are subjected to rule-based formal concept analysis and mapping. The subdomain ontologies of weather, pest, and soil are built separately, and the overall agricultural ontology are built around them. The gold standard for the lexical layer is used to evaluate the proposed technique, and its performance is analyzed by comparing it with different state-of-the-art systems. Precision, recall, F-measure, Matthews correlation coefficient, receiver operating characteristic curve area, and precision-recall curve area are the performance metrics used to analyze the performance. The proposed methodology gives a precision score of 94.40% when compared with the decision tree(83.94%) and K-nearest neighbor algorithm(86.89%) for agricultural ontology construction.
Artificial intelligence-based natural language processing technology is playing an important role in helping users write English-language documents. For academic documents in particular, the English proofreading services should reflect the academic characteristics using formal style and technical terms. But the services usually does not because they are based on general English sentences. In addition, since existing studies are mainly for improving the grammatical completeness, there is a limit of fluency improvement. This study proposes an automatic academic English editing methodology to deliver the clear meaning of sentences based on the use of technical terms. The proposed methodology consists of two phases: misspell correction and fluency improvement. In the first phase, appropriate corrective words are provided according to the input typo and contexts. In the second phase, the fluency of the sentence is improved based on the automatic post-editing model of the bidirectional recurrent neural network that can learn from the pair of the original sentence and the edited sentence. Experiments were performed with actual English editing data, and the superiority of the proposed methodology was verified.
Ayed Ahmad Hamdan Al-Radaideh;Mohd Shafry bin Mohd Rahim;Wad Ghaban;Majdi Bsoul;Shahid Kamal;Naveed Abbas
KSII Transactions on Internet and Information Systems (TIIS)
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v.17
no.7
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pp.1807-1822
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2023
Innovation and rapid increased functionality in user friendly smartphones has encouraged shutterbugs to have picturesque image macros while in work environment or during travel. Formal signboards are placed with marketing objectives and are enriched with text for attracting people. Extracting and recognition of the text from natural images is an emerging research issue and needs consideration. When compared to conventional optical character recognition (OCR), the complex background, implicit noise, lighting, and orientation of these scenic text photos make this problem more difficult. Arabic language text scene extraction and recognition adds a number of complications and difficulties. The method described in this paper uses a two-phase methodology to extract Arabic text and word boundaries awareness from scenic images with varying text orientations. The first stage uses a convolution autoencoder, and the second uses Arabic Character Segmentation (ACS), which is followed by traditional two-layer neural networks for recognition. This study presents the way that how can an Arabic training and synthetic dataset be created for exemplify the superimposed text in different scene images. For this purpose a dataset of size 10K of cropped images has been created in the detection phase wherein Arabic text was found and 127k Arabic character dataset for the recognition phase. The phase-1 labels were generated from an Arabic corpus of quotes and sentences, which consists of 15kquotes and sentences. This study ensures that Arabic Word Awareness Region Detection (AWARD) approach with high flexibility in identifying complex Arabic text scene images, such as texts that are arbitrarily oriented, curved, or deformed, is used to detect these texts. Our research after experimentations shows that the system has a 91.8% word segmentation accuracy and a 94.2% character recognition accuracy. We believe in the future that the researchers will excel in the field of image processing while treating text images to improve or reduce noise by processing scene images in any language by enhancing the functionality of VGG-16 based model using Neural Networks.
This paper aims at analyzing Robert Southey's Thalaba the Destroyer in relation to cultural colonialism of the British Romantic period and investigating the ways in which this text portrays the Other through its literary representation of the East. Especially, this paper attempts to show that the Oriental world constructed in Southey's text reveals the imperial subject's self-conscious awareness of its unstable relation with the unknown Other. For this purpose, this paper attends to the formal aspects of Thalaba the Destroyer, examining the process by which the reader's generic expectations about the "epic" undergo complex revisions and frustrations through reading this text. The epic elements contained in Thalaba the Detroyer include the battle between good and evil and the hero's moral epiphany arising from his struggle against malicious enemies. Yet, Thalaba the Destroyer constantly destabilizes the distinction between self and other by leading the reader to recognize the uncomfortable similarity between the poem's tyrannical figures and imperialistic monarchs in the Western civilization. Thus, when the hero enacts a revolution against despotism, the resistant power points not only to the imagined false kingdom within the text, but to the core of the real Empire that seeks to construct its own "garden" in the global scene. In addition, Southey's "panoramic" description of Oriental objects and stories in his footnotes lacks a framing perspective, erasing and de-stabilizing subject/object distinctions. In these footnotes, he exposes his profound attraction to the culture of "Other" and also conveys his aspiration to transforming Eastern myths and stories into profitable literary texts. Southey's attitude to the East in the footnotes appears to be partially grounded upon the interest of mercantile capitalists of the West, who need to discover potential commodities. Yet, simultaneously, he reveals a sense of moral hesitation about his own desire for the materiality of the East, along with deep anxiety arising from the fear of punishment.
A staple of feminist literary anthologies which was instrumental in reevaluating the writer Susan Glaspell, Trifles(1916) has received numerous comments from feminist scholars so far. Most of them tend to concentrate on the themes of female solidarity and justice challenging the androcentric system of law and order. Lacking in the plethora of thematic approaches to the play's feminist subject, however, are formal analyses considering the way in which the play's generic form assists in communicating such thematic concerns of feminism. An alternative to the typical scenario at the courtroom whose mistreatment of women must have loomed large to the young Glaspell as she revisited the old trial of a midwestern murderess which she had covered as a journalist for a local newspaper in Iowa, Trifles serves as a corrective to the courtroom dynamics offering a 'dramatic justice' as opposed to a strictly legal procedure. What this article discovers at the heart of this dramatic justice is the celebration of the unsayable, or what Wolfgang Iser termed negativity, of women's experience which has no room for reflection in the legal discourse at the courtroom tyrannized by the sayable and the evident. Examining how the dramatic form of Trifles gives a voice to the unsayable of woman's experience, which can not be properly represented at the courtroom governed by the straightforward and definitive male rhetoric, the article argues that the play is a better form than its fictional adaptation "A Jury of Her Peers"(1917) in that it syntactically suppresses the monopolizing operation of the verbal by giving precedence to the scenic and non-verbal which is constituted of setting, props, gesture and eye contacts. As a theoretical frame of reference with which to examine the modes of the unsayable in the play the article brings the concept of 'negativity,' defined by Iser as textual effects or modes of the unspeakable and unsaid, into the discussion of the taciturnity of the absent heroine and the non-verbal representation of drama.
In this paper, I'll try to read Don Lee's Yellow intertextually with a more canonical text, Sherwood Anderson's Winesburg, Ohio, in order to see what kind of traditions and techniques Yellow references and/or rewrites as a way of tracking this production. Yellow's formal properties as a short story cycle are established through its use of particular conventions. For instance, Yellow follows the short story cycle model that includes the assemblage of recurring characters into one locale. Yellow's characters are all connected to and at some point located in the fictional small town of Rosarita Bay, California. The text form aligns it with established literary conventions and traditions and suggests the author's reliance upon or trust in those modes. Yellow's setting in a small town alludes to and has often been compared to Anderson's Winesburg, Ohio, which is perhaps one of the most well-known and extensively discussed short story cycles in American literature. Also following convention is Lee's construction of Rosarita Bay and the text's third person narrator as a member of that town. Both Rosarita Bay and the narrator become important figures through the related-tale nature of the text. The method of story-telling is similar to how the town Winesburg and its "seemingly sympathetic and non-overtly judgmental" narrator are operational in Anderson's text. In sum, Yellow is opportune for intertextual reading largely because it is a collection of stories that create a linked series.
Journal of the Korean Institute of Intelligent Systems
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v.17
no.2
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pp.160-166
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2007
When a mail was given to users, each user's response could be different according to his or her preference. This paper presents a solution for this situation by constructing a user preferred ontology for anti-spam systems. To define an ontology for describing user behaviors, we applied associative classification mining to study preference information of users and their responses to emails. Generated classification rules can be represented in a formal ontology language. A user preferred ontology can explain why mail is decided to be spam or ron-spam in a meaningful way. We also suggest a new rule optimization procedure inspired from logic synthesis to improve comprehensibility and exclude redundant rules.
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