• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.845-853
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• 2020

In this paper, we propose a method for classifying environmental sound for selective noise cancellation in industrial sites. Noise in industrial sites causes hearing loss in workers, and researches on noise cancellation have been widely conducted. However, the conventional methods have a problem of blocking all sounds and cannot provide the optimal operation per noise type because of common cancellation method for all types of noise. In order to perform selective noise cancellation, therefore, we propose a method for environmental sound classification based on deep learning. The proposed method uses new sets of acoustic features consisting of temporal and statistical properties of Mel-spectrogram, which can overcome the limitation of Mel-spectrogram features, and uses convolutional neural network as a classifier. We apply the proposed method to five-class sound classification with three noise classes and two non-noise classes. We confirm that the proposed method provides improved classification accuracy by 6.6% point, compared with that using conventional Mel-spectrogram features.

• Progress in Medical Physics
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• v.31 no.3
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• pp.54-62
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• 2020

Dose calculation algorithms play an important role in radiation therapy and are even the basis for optimizing treatment plans, an important feature in the development of complex treatment technologies such as intensity-modulated radiation therapy. We reviewed the past and current status of dose calculation algorithms used in the treatment planning system for radiation therapy. The radiation-calculating dose calculation algorithm can be broadly classified into three main groups based on the mechanisms used: (1) factor-based, (2) model-based, and (3) principle-based. Factor-based algorithms are a type of empirical dose calculation that interpolates or extrapolates the dose in some basic measurements. Model-based algorithms, represented by the pencil beam convolution, analytical anisotropic, and collapse cone convolution algorithms, use a simplified physical process by using a convolution equation that convolutes the primary photon energy fluence with a kernel. Model-based algorithms allowing side scattering when beams are transmitted to the heterogeneous media provide more precise dose calculation results than correction-based algorithms. Principle-based algorithms, represented by Monte Carlo dose calculations, simulate all real physical processes involving beam particles during transportation; therefore, dose calculations are accurate but time consuming. For approximately 70 years, through the development of dose calculation algorithms and computing technology, the accuracy of dose calculation seems close to our clinical needs. Next-generation dose calculation algorithms are expected to include biologically equivalent doses or biologically effective doses, and doctors expect to be able to use them to improve the quality of treatment in the near future.

• The Journal of Society for e-Business Studies
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• v.26 no.2
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• pp.61-81
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• 2021

In the era of untact, the "Chabak" using cars as accommodation spaces is attracting attention as a new form of travel. Due to the advantages, including low costs, convenience, and safety, as well as the characteristics of the vehicle enabling independent travel, the demand for Chabak is continuously increasing. Despite the rapid growth of the market and related industries, little academic has investigated this trend. To establish itself as a new type of travel culture and to sustain the growth of related industries, it is essential to understand the public perception of Chabak. Therefore, based on the marketing mix theory and big data analysis, this study analyzes the public perception of Chabak. The results showed that Chabak has established itself as a consumer-led travel culture, contributing to the aftermarket growth of the automobile industry. Additionally, consumers were found to be increasingly inclined to enjoy travel economically and wisely, and actively share information through social media. This initial study on the new travel trend of Chabak is significant in that it employs big data analysis on a theoretical basis.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.5
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• pp.169-179
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• 2011

Recent personal data breach incidences draw the public's attention to their privacy and personal rights. The new personal data protection law effective in September 2009 imposes additional legal responsibility on personal data controllers and processors. For instance, if a data breach occurs, this new law requires that the processors must notify individuals (data subjects) and data protection authorities of the nature of incidents. This research reviews the U.S. forty six state laws and related acts, and offers a framework for managing incidents. This framework includes five major components: (1) type of personal data required to be reported and notified, (2) the ultimate subject notifying data subjects, (3) event occurrence and notification time phases, (4) notification message details, and (5) direct/indirect communication media. Along with this framework, we also offer directions for effective/manageable guidelines on data breach notification act.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.177-186
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• 2022

The purpose of this study is to suggest operation plans for library programs in preparation for the post-COVID-19 by analyzing the current status of library programs before and after the outbreak of COVID-19 based on the data of the Seongnam public libraries on the Public Data Portal. So, based on 1,317 data collected through the data purification process for duplicates and errors in the files uploaded by Seongnam City, ①programs' subject & type, ②program target users, ③program operation types(online or offline), ④program operating time & number of days, ⑤characteristics of programs preferred by users etc. were analyzed. As results of the analysis, online programs were not operated at all before COVID-19, but online programs started to be operated in earnest after August 2020. Also, there were many experiential activity lectures for infants and elementary school students in 2019, but reading activity lectures for adults and elementary school students increased in 2020. There were many types of online lectures, such as real-time lectures using online video conferencing programs, YouTube video viewing & live broadcasting, and the use of Naver Band & Cafe.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.83-93
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• 2022

Research is underway to solve the traffic problem by using crowdsourcing, where drivers use their mobile devices to provide traffic information. If it is used for traffic event detection through crowdsourcing, the task of collecting related data is reduced, which lowers time cost and increases accuracy. In this paper, we propose a scheme to collect traffic-related data using crowdsourcing and to detect events affecting traffic through this. The proposed scheme uses machine learning algorithms for processing large amounts of data to determine the event type of the collected data. In addition, to find out the location where the event occurs, a keyword indicating the location is extracted from the collected data, and the administrative area of the keyword is returned. In this way, it is possible to resolve a location that is broadly defined in the existing location information or incorrect location information. Various performance evaluations are performed to prove the superiority and feasibility of the proposed scheme.

• Journal of Physiology & Pathology in Korean Medicine
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• v.36 no.1
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• pp.1-6
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• 2022

The tuber of Pinellia ternata (Thunb.) Brei (TPT) used in traditional Oriental medicine for the treatment of cough, sputum, vomiting, and insomnia, possesses antioxidant, antibacterial, and anti-inflammatory effects. Although recent studies have reported the anticancer effects of TPT in several cancer cells, it is still unclear whether TPT regulates tumor-associated macrophage (TAM) characterized by the immunosuppressive M2 macrophage phenotype. Our results showed that the ethanol extract of TPT (ETPT) suppressed the migration of RAW264.7 mouse macrophage cells and THP-1 human monocytes differentiated into macrophages towards the conditioned media (CM) collected from lung cancer cells, suggesting that ETPT would attenuate the recruitment of macrophages into tumors. In addition, ETPT suppressed the interleukin (IL)-4 or IL-6-induced M2 macrophage polarization in RAW264.7 cells. ETPT treatment not only downregulated the mRNA expression of M2 macrophage markers including arginase-1, mannose receptor C type 1 (MRC-1), and IL-10, but also inhibited the phosphorylation of signal transducer and activator of transcription 3 (STAT3) and STAT6, general regulators of M2 macrophage polarization. Finally, the transwell assay results showed that the CM from M2-polarized RAW264.7 cells increased the migration of mouse lewis lung carcinoma (LLC) cells, while those from RAW264.7 cells co-treated with ETPT and IL-6 significantly reduced the migration of LLC cells. Taken together, our observations clearly demonstrate that ETPT suppressed the cancer cell migration by regulating macrophage recruitment and M2 macrophage polarization.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.361-366
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• 2022

There are several ways to process large amounts of data. Depending on the processing method, there is a big difference in processing speed to create a large data list. Typically, to make a large data list, large data is converted into a normalized query, and the result of the query is stored in a List Map and converted into a printable form. This process occurs as a cause of lowering the processing speed step by step. In the process of storing the results of the created query as a List Map, the processing speed differs because the data is stored in a different format for each type of data. Through the simultaneous processing of GO language, we want to solve the problem of the existing difference in processing speed. In other words, it compares the results of GO language concurrency processing by providing how different and how it proceeds between the format contained in the existing List Map and the method of processing using concurrency in large data lists for faster processing. do.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.151-159
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• 2021

The purpose of this study is to attempt a convergent study by analyzing modern funk ceramic artworks through 'Irony', which was mainly used in rhetoric and literature. The irony has come to modern times and has embraced the type of irony by Jung Keut-Byul, a literary critic who has discovered that the classifications and definitions are different from each other, and who has solved these problems and has newly classified the irony (the irony of oxymoron, the irony as a counterstatement, the irony of dramatic turn, the irony as a poetic truth) as a framework for analyzing the works of 20th century punk potters. As a result, the formative language found in funk ceramic art had many similarities with the irony of duality of surface and reality, and its humorous and comic character was more prominent than the heavy, melodramatic tone shown in literature. It was also found that the media characteristics and craft properties of ceramic art, such as clay and glaze, have become the drivers for ceramic sculptors to draw attention in funk art.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.134-143
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• 2021

Recently, with the development of mobile devices and social media services, contents recommendation schemes have been studied. They are typically applied to the job curation systems. Most existing university education content recommendation schemes only recommend the most frequently taken subjects based on the student's school and major. Therefore, they do not consider the type or field of employment that each student wants. In this paper, we propose a university educational contents recommendation scheme for job curation services. The proposed scheme extracts companies that a user is interested in by analyzing his/her activities in the job curation system. The proposed scheme selects graduates or mentors based on the reliability and similarity of graduates who have been employed at the companies of interest. The proposed scheme recommends customized subjects, comparative subjects, and autonomous activity lists to users through collaborative filtering.