• Journal of the Korea Society of Computer and Information
• /
• v.26 no.9
• /
• pp.13-25
• /
• 2021

In the age of digital innovation based on the Internet, Information and Communication and Artificial Intelligence technologies, huge amounts of datasets are being generated, collected, accumulated, and opened on the web by various public institutions providing useful and public information. In order to analyse, gain useful insights and information from data, Formal Concept Analysis(FCA) has been successfully used for analyzing, classifying, clustering and visualizing data based on the binary relation between objects and attributes in the dataset. In this paper, we present an approach for enhancing the analysis of relational attributes of data within the extended framework of FCA, which is designed to classify, conceptualize and visualize sets of objects described not only by attributes but also by relations between these objects. By using the proposed tool, RCA wizard, several experiments carried out on some public open datasets demonstrate the validity and usability of our approach on generating and visualizing conceptual hierarchies for extracting more useful knowledge from datasets. The proposed approach can be used as an useful tool for effective data analysis, classifying, clustering, visualization and exploration.

• Journal of the Architectural Institute of Korea Planning & Design
• /
• v.35 no.7
• /
• pp.63-72
• /
• 2019

The purpose of this study is to apply the types of urban street pattern and the shape of streets to the master plan of a religious community complexes. The street pattern is a framework of urban structure and to understand the urban structure is helpful to understand the nature of urban streets. By analysing the precedent researches, the types of street patterns are classified as a serial pattern, a branching pattern, a grid pattern and a web pattern. The street patterns are hierarchically composed and classified as a differential development and sequential development. There are boundaries and gates where the street space is differentiated to the more private level. The urban streets continue to the architectural streets such as arcades, deck streets, corridors, lobbies and halls. The purposes and results of the master plan of this religious community complexes are as follows. 1) The school area, housing area and service area are properly separated and connected. They are separated by the building masses and connected by the street space in between. 2) The street pattern of this complexes is a serial pattern where the streets are the center of each functional building groups. The entry square is divided by the symbolic building. The one branch is school street and the other is living street. These streets are combined again to the festival street. 3) The architectural streets are organically related to the urban streets. 4) Each street spaces are of adequate form according to its properties as a place. 5) There are boundaries or gates such as a gab between buildings, posts, arches and deck streets according to the relationship between streets.

• Korean Medical Education Review
• /
• v.23 no.2
• /
• pp.80-89
• /
• 2021

Professional identity formation (PIF) is an essential concept in professional education. Many scholars have explored conceptual frameworks of PIF and conducted empirical studies to advance an understanding of the construct in medical education. Despite its importance, it is unclear what educational approaches and assessment practices are actually implemented in medical education settings. Therefore, we conducted a literature review of empirical studies reporting educational practices for medical learners' PIF. We searched the Web of Science database using keywords and chose 37 papers for analysis based on inclusion and exclusion criteria. Thematic analysis was conducted. Most empirical papers (92%) were from North America and Western Europe and used qualitative research methods, including mixed methods (99%). The papers reported the use of reflection activities and elective courses for specific purposes, such as art as an educational activity. Patient and healthcare experiences were also found to be a central theme in medical learners' PIF. Through an iterative analysis of the key themes that emerged from the PIF studies, we derived the following key concepts and implications: (1) the importance of creating informal and incidental learning environments, (2) ordinary yet authentic patient experiences, (3) a climate of psychosocial safety in a learning environment embracing individual learners' background and emotional development, and (4) the reconceptualization of PIF education and assessment. In conclusion, research on PIF should be diversified to include various cultural and social contexts. Theoretical frameworks should also be diversified and developed beyond Kegan's developmental framework to accommodate the nonlinear and dynamic nature of PIF.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.7
• /
• pp.37-44
• /
• 2021

Automatic classification of brain MRI images play an important role in early diagnosis of brain tumors. In this work, we present a deep learning-based brain tumor classification model in MRI images using ensemble of deep features. In our proposed framework, three different deep features from brain MR image are extracted using three different pre-trained models. After that, the extracted deep features are fed to the classification module. In the classification module, the three different deep features are first fed into the fully-connected layers individually to reduce the dimension of the features. After that, the output features from the fully-connected layers are concatenated and fed into the fully-connected layer to predict the final output. To evaluate our proposed model, we use openly accessible brain MRI dataset from web. Experimental results show that our proposed model outperforms other machine learning-based models.

• International Journal of Knowledge Content Development & Technology
• /
• v.11 no.2
• /
• pp.55-75
• /
• 2021

This article examines the accessibility and usability of library websites to students with visual and physical disabilities in public universities in Kenya. The study used survey research design and adopted a mixed methods approach. Data were gathered using survey questionnaire, focus group discussions, structured interviews, and observation. The study population consisted of six public universities that had a longstanding tradition of enrolling students with disabilities. Census was used to obtain a study sample comprising of students with visual disabilities (86), students with physical disabilities (91), University Librarians (6), Personnel from Disability Mainstreaming departments (6), Systems Librarians (6) and Library Personnel who provided information services to students with disabilities (133). The Social Model of Disability and IFLA Access to Libraries for Persons with Disabilities checklist were used as conceptual and theoretical framework in the study. Study results revealed that all the libraries had library websites. However, the websites did not have disability services page or information specific to individuals with disabilities. Also a section of students with disabilities lacked awareness of the existence of library websites and e-resources available through them. Additionally, the website design posed various access challenges. The study concluded that people with disabilities were excluded from access and use of library websites in public universities. The authors recommended that library websites must contain disability services page containing information specific to persons with disabilities. Moreover, libraries should evaluate their websites to ensure compliance with W3C requirements for web content accessibility. Additionally, libraries should develop disability policy to provide guidance on provision of information services to persons with disabilities.

• International Journal of Computer Science & Network Security
• /
• v.22 no.2
• /
• pp.406-412
• /
• 2022

Storing large amounts of data has always been a big problem from the beginning of computing history. Big Data has made huge advancements in improving business processes by finding the customers' needs using prediction models based on web and social media search. The main purpose of big data stream processing frameworks is to allow programmers to directly query the continuous stream without dealing with the lower-level mechanisms. In other words, programmers write the code to process streams using these runtime libraries (also called Stream Processing Engines). This is achieved by taking large volumes of data and analyzing them using Big Data frameworks. Streaming platforms are an emerging technology that deals with continuous streams of data. There are several streaming platforms of Big Data freely available on the Internet. However, selecting the most appropriate one is not easy for programmers. In this paper, we present a detailed description of two of the state-of-the-art and most popular streaming frameworks: Apache Ignite and Hazelcast. In addition, the performance of these frameworks is compared using selected attributes. Different types of databases are used in common to store the data. To process the data in real-time continuously, data streaming technologies are developed. With the development of today's large-scale distributed applications handling tons of data, these databases are not viable. Consequently, Big Data is introduced to store, process, and analyze data at a fast speed and also to deal with big users and data growth day by day.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.3
• /
• pp.396-402
• /
• 2022

User interactions are being developed in various forms, and in particular, interactions using human gestures are being actively studied. Among them, hand gesture recognition is used as a human interface in the field of realistic media based on the 3D Hand Model. The use of interfaces based on hand gesture recognition helps users access media media more easily and conveniently. User interaction using hand gesture recognition should be able to view images by applying fast and accurate hand gesture recognition technology without restrictions on the computer environment. This paper developed a fast and accurate user hand gesture recognition algorithm using the open source media pipe framework and machine learning's k-NN (K-Nearest Neighbor). In addition, in order to minimize the restriction of the computer environment, a stereoscopic image control system based on user hand gesture recognition was designed and implemented using a web service environment capable of Internet service and a docker container, a virtual environment.

• Fashion & Textile Research Journal
• /
• v.24 no.3
• /
• pp.303-314
• /
• 2022

This study examined the impact of the social features (identification, interaction, information value) and technical features (visibility affordance, metavoicing affordance, social connecting affordance) in live commerce on consumers' attachment, which in turn affects consumers' continued intent to watch live commerce and intent to purchase from the platform. Consumers' attachment was represented by emotional attachment to the live shopping streamer and functional dependence on live commerce. Furthermore, this study investigated the effect of attachment on continuous watching intention and purchase intention. Using a web-based survey and consumers in their 20s and 30s (average age: 30.32) as a sample, this study collected 274 usable responses. The results showed that among the live commerce social system constructs, identification and interaction positively affected emotional attachment to the live commerce streamer. Among the live commerce technical system constructs, visibility affordance and social connecting affordance positively influenced functional dependence on live commerce. Both emotional attachment to the live streamer and functional dependence on live commerce were positively related to a continued intent to watch, which influenced the intent to purchase. This study empirically investigated live commerce based on the socio-technical systems framework and confirmed that both social and technical factors have a significant effect on consumers. This study also identified the impact of live commerce on consumers' attitudes through attachment theory. In addition, it has proved the antecedents and effect of continuous watching of live commerce on purchase behavior by focusing on continuous watching intention where less attention was paid in live commerce research.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.31 no.6
• /
• pp.1105-1114
• /
• 2021

Due to the recent surge in popularity of cryptocurrency, the threat of cryptojacking, a malicious code for mining cryptocurrencies, is increasing. In particular, web-based cryptojacking is easy to attack because the victim can mine cryptocurrencies using the victim's PC resources just by accessing the website and simply adding mining scripts. The cryptojacking attack causes poor performance and malfunction. It can also cause hardware failure due to overheating and aging caused by mining. Cryptojacking is difficult for victims to recognize the damage, so research is needed to efficiently detect and block cryptojacking. In this work, we take representative distinct symptoms of cryptojacking as an indicator and propose a new architecture. We utilized the K-Nearst Neighbors(KNN) model, which trained computer performance indicators as behavior-based dynamic analysis techniques. In addition, a K-means model, which trained the frequency of malicious script words for script similarity-based static analysis techniques, was utilized. The KNN model had 99.6% accuracy, and the K-means model had a silhouette coefficient of 0.61 for normal clusters.

• The Journal of Korean Medicine
• /
• v.43 no.2
• /
• pp.75-91
• /
• 2022

Objectives: The purpose of this overview was to summarize the evidence regarding the effectiveness of Cognitive Behavioral Therapy (CBT) for sleep disorders through systematic reviews (SRs) and meta-analyses (MAs). Methods: An overview of systematic review was conducted according to the study protocol (reviewregistry1320). A comprehensive literature search was performed using three databases (Pubmed, Cochrane Central Register of Controlled Trials, and Web of Science) and three Korean databases (KoreaMed, KMbase, and ScienceON). Final studies were selected by three authors according to inclusion and exclusion criteria, and data needed for analysis were extracted by a pre-planned extraction framework. Methodological quality of systematic review was assessed using the 'Assessment of multiple systematic reviews 2 (AMSTAR2)'. Results: Fourteen SRs and MAs were included, of which eleven SRs were performed MAs. Twelve studies studied insomnia among sleep disorders, and the rest are nightmares and sleep disturbances with PTSD. Ten studies reported the effect of CBT on sleep disorders measured by insomnia severity index (ISI) and sleep onset latency (SOL), and all reported a significant improvement effect. Eight studies reported the effect of CBT on sleep disorders measured by wake time after sleep onset (WASO), and seven studies reported a significant improvement effect. The methodological quality of the studies evaluated with AMSTAR 2 was mainly low or very low because of omission of protocol registration and excluded study list. Conclusions: Practical guidelines and studies show that CBT is effective for sleep disorders, but access to CBT needs to be improved.