• Imaging Science in Dentistry
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• v.52 no.2
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• pp.155-164
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• 2022

Purpose: The aim of this study was to systematically screen the literature for studies reporting cosmetic material in the oral and maxillofacial complex to shed light on the types of cosmetic materials, their radiographic appearance, and possible complications. Materials and Methods: Five electronic databases were reviewed for eligible studies. The general search terms were "cosmetic," "filler," "face," and "radiograph." Demographics, material types, clinical and radiographic presentation, and complications were recorded. Results: Thirty-one studies with 53 cases met the inclusion criteria. The mean age was 52.6±15.4 years with a 4 : 3 female-to-male ratio. The most common material was calcium hydroxyapatite (CaHa) (n=14, 26.4%), found incidentally. The materials were generally located within the upper cheek and zygoma (n=35, 66.0%), radiographically well-defined (n=44, 83%), and had no effects on the surrounding structures (n=27, 50.9%). The internal structure was radiopaque (calcification, hyperdensity) for gold wires, CaHa, bone implants, and secondary calcification or ossification. Outdated cosmetic materials or non-conservative techniques were infiltrative, had effects on the surrounding structures, and presented with clinical signs, symptoms, or complications. Conclusion: Conventional radiography, cone-beam computed tomography, and multi-detector computed tomography are useful to differentiate several cosmetic materials. Their magnetic resonance imaging appearance was highly variable. The infrequent inclusion of cosmetic materials in the differential diagnosis implies that medical and dental specialists may be unfamiliar with the radiographic appearance of these materials in the face.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.3
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• pp.1-10
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• 2022

With the development of web technology, large amounts of web documents are being produced. This web document contains various spatial texts, and by converting these texts into spatial information, it is the basis for searching for text documents with spatial query. These spatial texts consist of a wide range of areas, including postal codes and local phone numbers, as well as administrative place names and POI names. This paper presents algorithms that can map locations based on spatial text information existing within web documents. Through these algorithms, web documents can be searched for documents describing the region on a map rather than a general web search. In this paper, we demonstrated the presented algorithms are useful by implementing a web geo-text query system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.2074-2093
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• 2022

RSA is known as one of the best techniques for securing secret information across an unsecured network. The private key which is one of private parameters is the aim for attackers. However, it is exceedingly impossible to derive this value without disclosing all unknown parameters. In fact, many methods to recover the private key were proposed, the performance of each algorithm is acceptable for the different cases. For example, Wiener's attack is extremely efficient when the private key is very small. On the other hand, Fermat's factoring can quickly break RSA when the difference between two large prime factors of the modulus is relatively small. In general, if all private parameters are not disclosed, attackers will be able to confirm that the private key is unquestionably inside the scope [3, n - 2], where n is the modulus. However, this scope has already been reduced by increasing the greatest lower bound to [d_il, n - 2], where d_il ≥ 3. The aim of this paper is to decrease the least upper bound to narrow the scope that the private key will remain within this boundary. After finishing the proposed method, the new scope of the private key can be allocated as [d_il, d_ir], where d_ir ≤ n - 2. In fact, if the private key is extremely close to the new greatest lower bound, it can be retrieved quickly by performing a brute force attack, in which d_ir is decreased until it is equal to the private key. The experimental results indicate that the proposed method is extremely effective when the difference between prime factors is close to each other and one of two following requirement holds: the first condition is that the multiplier of Euler totient function is very close to the public key's small value whereas the second condition is that the public key should be large whenever the multiplier is far enough.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.63-68
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• 2022

Currently, there are a total of 68 emergency rooms based on Seoul, South Korea, and there is a portal site that allows you to inquire the location of the emergency room, but it is difficult to use in an actual emergency situation because it consists of selecting a gu and a self-governing dong. In addition, it may be more efficient to go to the emergency room directly because you may miss the golden time necessary for survival in a situation where you call 119 and wait for the rescue team. Therefore, in this paper, we propose a service that can quickly search the location of the emergency room based on a specific location through various functions supported by MongoDB. After downloading emergency room location data based on Seoul Metropolitan City, storing it in MongoDB, processing the data through various processing techniques, and applying a spatial index, you can query the emergency room based on distance from a specific location in real time.

• Journal of Dental Anesthesia and Pain Medicine
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• v.22 no.1
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• pp.1-10
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• 2022

Background: Inferior alveolar nerve block (IANB) is known to have a lower success rate for anesthesia in patients with irreversible pulpitis. This calls for supplementary techniques to effectively anesthetize such patients. This systematic review aimed to evaluate the published literature for determining the success rate of anesthesia induction using post-IANB intraligamentary (IL) injection in the mandibular teeth of patients with symptomatic irreversible pulpitis. The review question was, "What is the success rate of IL injection in the mandibular teeth of patients with irreversible pulpitis as a supplementary technique for endodontic treatment?" Methods: A thorough search of electronic databases and manual searches were performed. The protocol of the review was framed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist and was registered in the International Prospective Register of Ongoing Systematic Reviews (PROSPERO) with a proper criterion for inclusion and exclusion of studies. The included studies were analyzed using the Cochrane Collaboration "Risk of Bias" tool. A meta-analysis that included a comparison of primary nerve block and supplemental IL injection was performed. The success rate was evaluated using the combined risk ratio (RR) with a random risk model. A funnel plot was created to measure publication bias. Results: After all analyses, four studies were included. In the forest plot representation, RRs were 3.56 (95% CI: 2.86, 4.44), which were in favor of the supplemental IL injections. Statistical heterogeneity was found to be 0%. These values suggest that supplemental IL injections provide better success rates for anesthesia. Conclusion: According to the pooled qualitative and quantitative analyses, supplemental IL injections increased anesthetic efficacy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1111-1120
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• 2022

Image Capturing is a matter of viewing images and describing images in language. The problem is an important problem that can be solved by keeping, understanding, and bringing together two areas of image processing and natural language processing. In addition, by automatically recognizing and describing images in text, images can be converted into text and then into speech for visually impaired people to help them understand their surroundings, and important issues such as image search, art therapy, sports commentary, and real-time traffic information commentary. So far, the image captioning research approach focuses solely on recognizing and texturing images. However, various environments in reality must be considered for practical use, as well as being able to provide image descriptions for the intended purpose. In this work, we limit the universally available Korean and English image captioning models and text generation techniques for the purpose of image captioning.

• Journal of the Korean Society of Food Culture
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• v.36 no.2
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• pp.143-157
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• 2021

This study aimed to analyze the periodic prevalence of the vegetables during the Joseon era with JoseonWangjoSilrok as a reference. The JoseonWangjoSilrok articles were collected from the Guksapyeonchanwewonhwe site, using web-crawling techniques to extract the relevant information. Out of 384,582 search results, 9,560 articles with vegetable-related keywords were found. According to the annual average vegetable recordings during the regimes of various kings, there were two peaking curves in the 15^th and 18^th centuryJoseon. The found was: 2,750 in the 18^th century, 2,529 in the 15^th century, 1,424 in the 16^th century, and 1,018 in the 19^th century. A Variable Interest Index was designed to ascertain the interestin vegetables of the 27 Joseon kings. The king most interested in vegetables was the 19^th king Sookjong. The second most interested king was Youngjo. There were 5,105 vegetable-related findings within the JoseonWangjoSilrok related to specific species and categories of vegetables. Among the words found: 1,194 were stem-leaves vegetables (23.39%), 1,017 were root vegetables (19.92%), 1,148 were flower-fruit vegetables (22.49%), 1,144 were spice vegetables (22.41%), 95 were mushrooms (1.86%), and 507 were seaweeds (9.93%). Statistical analysis using ANOVA revealed the chronological factors that affected the vegetables' prevalence index.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.420-426
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• 2022

Breast cancer is among the cancers that may be healed as the disease diagnosed at early times before it is distributed through all the areas of the body. The Automatic Analysis of Diagnostic Tests (AAT) is an automated assistance for physicians that can deliver reliable findings to analyze the critically endangered diseases. Deep learning, a family of machine learning methods, has grown at an astonishing pace in recent years. It is used to search and render diagnoses in fields from banking to medicine to machine learning. We attempt to create a deep learning algorithm that can reliably diagnose the breast cancer in the mammogram. We want the algorithm to identify it as cancer, or this image is not cancer, allowing use of a full testing dataset of either strong clinical annotations in training data or the cancer status only, in which a few images of either cancers or noncancer were annotated. Even with this technique, the photographs would be annotated with the condition; an optional portion of the annotated image will then act as the mark. The final stage of the suggested system doesn't need any based labels to be accessible during model training. Furthermore, the results of the review process suggest that deep learning approaches have surpassed the extent of the level of state-of-of-the-the-the-art in tumor identification, feature extraction, and classification. in these three ways, the paper explains why learning algorithms were applied: train the network from scratch, transplanting certain deep learning concepts and constraints into a network, and (another way) reducing the amount of parameters in the trained nets, are two functions that help expand the scope of the networks. Researchers in economically developing countries have applied deep learning imaging devices to cancer detection; on the other hand, cancer chances have gone through the roof in Africa. Convolutional Neural Network (CNN) is a sort of deep learning that can aid you with a variety of other activities, such as speech recognition, image recognition, and classification. To accomplish this goal in this article, we will use CNN to categorize and identify breast cancer photographs from the available databases from the US Centers for Disease Control and Prevention.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.996-1003
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• 2022

In this paper, we present a new method for determining the scan line and range for vision-based 1-D barcode recognition. This is a study on how to detect valid barcode representative points and directions by applying the DBSCAN clustering method based on block HOG (histogram of gradient) and determine scan lines and barcode crosslines based on this. In this paper, the minimum and maximum search techniques were applied to determine the cross-line range of barcodes based on the obtained scan lines. This can be applied regardless of the barcode size. This technique enables barcode recognition even by detecting only a partial area of the barcode, and does not require rotation to read the code after detecting the barcode area. In addition, it is possible to detect barcodes of various sizes. Various experimental results are presented to evaluate the performance of the proposed technique in this paper.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.1-10
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• 2021

This paper aimed to look at the awareness of foreign workers in social platforms by using text mining, one of the big data techniques and draw suggestions for foreign workers. To achieve this purpose, data collection was conducted with search keyword 'Foreign Worker' from Jan. 1, to Dec. 31, 2020, and frequency analysis, TF-IDF analysis, and degree centrality analysis and 100 parent keywords were drawn for comparison. Furthermore, Ucinet6.0 and Netdraw were used to analyze semantic networks, and through CONCOR analysis, data were clustered into the following eight groups: foreigner policy issue, regional community issue, business owner's perspective issue, employment issue, working environment issue, legal issue, immigration issue, and human rights issue. Based on such analyzed results, it identified national awareness of foreign workers and main issues and provided the basic data on policy proposals for foreign workers and related researches.