• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.191-207
• /
• 2021

Up to this day, mobile communications have evolved rapidly over the decades, mainly focusing on speed-up to meet the growing data demands of 2G to 5G. And with the start of the 5G era, efforts are being made to provide such various services to customers, as IoT, V2X, robots, artificial intelligence, augmented virtual reality, and smart cities, which are expected to change the environment of our lives and industries as a whole. In a bid to provide those services, on top of high speed data, reduced latency and reliability are critical for real-time services. Thus, 5G has paved the way for service delivery through maximum speed of 20Gbps, a delay of 1ms, and a connecting device of 106/㎢ In particular, in intelligent traffic control systems and services using various vehicle-based Vehicle to X (V2X), such as traffic control, in addition to high-speed data speed, reduction of delay and reliability for real-time services are very important. 5G communication uses high frequencies of 3.5Ghz and 28Ghz. These high-frequency waves can go with high-speed thanks to their straightness while their short wavelength and small diffraction angle limit their reach to distance and prevent them from penetrating walls, causing restrictions on their use indoors. Therefore, under existing networks it's difficult to overcome these constraints. The underlying centralized SDN also has a limited capability in offering delay-sensitive services because communication with many nodes creates overload in its processing. Basically, SDN, which means a structure that separates signals from the control plane from packets in the data plane, requires control of the delay-related tree structure available in the event of an emergency during autonomous driving. In these scenarios, the network architecture that handles in-vehicle information is a major variable of delay. Since SDNs in general centralized structures are difficult to meet the desired delay level, studies on the optimal size of SDNs for information processing should be conducted. Thus, SDNs need to be separated on a certain scale and construct a new type of network, which can efficiently respond to dynamically changing traffic and provide high-quality, flexible services. Moreover, the structure of these networks is closely related to ultra-low latency, high confidence, and hyper-connectivity and should be based on a new form of split SDN rather than an existing centralized SDN structure, even in the case of the worst condition. And in these SDN structural networks, where automobiles pass through small 5G cells very quickly, the information change cycle, round trip delay (RTD), and the data processing time of SDN are highly correlated with the delay. Of these, RDT is not a significant factor because it has sufficient speed and less than 1 ms of delay, but the information change cycle and data processing time of SDN are factors that greatly affect the delay. Especially, in an emergency of self-driving environment linked to an ITS(Intelligent Traffic System) that requires low latency and high reliability, information should be transmitted and processed very quickly. That is a case in point where delay plays a very sensitive role. In this paper, we study the SDN architecture in emergencies during autonomous driving and conduct analysis through simulation of the correlation with the cell layer in which the vehicle should request relevant information according to the information flow. For simulation: As the Data Rate of 5G is high enough, we can assume the information for neighbor vehicle support to the car without errors. Furthermore, we assumed 5G small cells within 50 ~ 250 m in cell radius, and the maximum speed of the vehicle was considered as a 30km ~ 200 km/hour in order to examine the network architecture to minimize the delay.

• Journal of KIISE:Databases
• /
• v.32 no.4
• /
• pp.452-472
• /
• 2005

We propose XIR-Branching, a novel method for processing partial match queries on heterogeneous XML documents using information retrieval(IR) techniques and novel instance join techniques. A partial match query is defined as the one having the descendent-or-self axis '//' in its path expression. In its general form, a partial match query has branch predicates forming branching paths. The objective of XIR-Branching is to efficiently support this type of queries for large-scale documents of heterogeneous schemas. XIR-Branching has its basis on the conventional schema-level methods using relational tables(e.g., XRel, XParent, XIR-Linear[21]) and significantly improves their efficiency and scalability using two techniques: an inverted index technique and a novel prefix match join. The former supports linear path expressions as the method used in XIR-Linear[21]. The latter supports branching path expressions, and allows for finding the result nodes more efficiently than containment joins used in the conventional methods. XIR-Linear shows the efficiency for linear path expressions, but does not handle branching path expressions. However, we have to handle branching path expressions for querying more in detail and general. The paper presents a novel method for handling branching path expressions. XIR-Branching reduces a candidate set for a query as a schema-level method and then, efficiently finds a final result set by using a novel prefix match join as an instance-level method. We compare the efficiency and scalability of XIR-Branching with those of XRel and XParent using XML documents crawled from the Internet. The results show that XIR-Branching is more efficient than both XRel and XParent by several orders of magnitude for linear path expressions, and by several factors for branching path expressions.

• Journal of Intelligence and Information Systems
• /
• v.17 no.1
• /
• pp.153-169
• /
• 2011

Today using Internet environment is considered absolutely essential for establishing corporate marketing strategy. Companies have promoted their products and services through various ways of on-line marketing activities such as providing gifts and points to customers in exchange for participating in events, which is based on customers' membership data. Since companies can use these membership data to enhance their marketing efforts through various data analysis, appropriate website membership management may play an important role in increasing the effectiveness of on-line marketing campaign. Despite the growing interests in proper membership management, however, there have been difficulties in identifying inappropriate members who can weaken on-line marketing effectiveness. In on-line environment, customers tend to not reveal themselves clearly compared to off-line market. Customers who have malicious intent are able to create duplicate IDs by using others' names illegally or faking login information during joining membership. Since the duplicate members are likely to intercept gifts and points that should be sent to appropriate customers who deserve them, this can result in ineffective marketing efforts. Considering that the number of website members and its related marketing costs are significantly increasing, it is necessary for companies to find efficient ways to screen and exclude unfavorable troublemakers who are duplicate members. With this motivation, this study proposes an approach for managing duplicate membership based on the social network analysis and verifies its effectiveness using membership data gathered from real websites. A social network is a social structure made up of actors called nodes, which are tied by one or more specific types of interdependency. Social networks represent the relationship between the nodes and show the direction and strength of the relationship. Various analytical techniques have been proposed based on the social relationships, such as centrality analysis, structural holes analysis, structural equivalents analysis, and so on. Component analysis, one of the social network analysis techniques, deals with the sub-networks that form meaningful information in the group connection. We propose a method for managing duplicate memberships using component analysis. The procedure is as follows. First step is to identify membership attributes that will be used for analyzing relationship patterns among memberships. Membership attributes include ID, telephone number, address, posting time, IP address, and so on. Second step is to compose social matrices based on the identified membership attributes and aggregate the values of each social matrix into a combined social matrix. The combined social matrix represents how strong pairs of nodes are connected together. When a pair of nodes is strongly connected, we expect that those nodes are likely to be duplicate memberships. The combined social matrix is transformed into a binary matrix with '0' or '1' of cell values using a relationship criterion that determines whether the membership is duplicate or not. Third step is to conduct a component analysis for the combined social matrix in order to identify component nodes and isolated nodes. Fourth, identify the number of real memberships and calculate the reliability of website membership based on the component analysis results. The proposed procedure was applied to three real websites operated by a pharmaceutical company. The empirical results showed that the proposed method was superior to the traditional database approach using simple address comparison. In conclusion, this study is expected to shed some light on how social network analysis can enhance a reliable on-line marketing performance by efficiently and effectively identifying duplicate memberships of websites.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.46 no.3
• /
• pp.75-85
• /
• 2009

This work proposes a 13b 100MS/s 0.13um CMOS ADC for 3G communication systems such as two-carrier W-CDMA applications simultaneously requiring high resolution, low power, and small size at high speed. The proposed ADC employs a four-step pipeline architecture to optimize power consumption and chip area at the target resolution and sampling rate. Area-efficient high-speed high-resolution gate-bootstrapping circuits are implemented at the sampling switches of the input SHA to maintain signal linearity over the Nyquist rate even at a 1.0V supply operation. The cascode compensation technique on a low-impedance path implemented in the two-stage amplifiers of the SHA and MDAC simultaneously achieves the required operation speed and phase margin with more reduced power consumption than the Miller compensation technique. Low-glitch dynamic latches in sub-ranging flash ADCs reduce kickback-noise referred to the differential input stage of the comparator by isolating the input stage from output nodes to improve system accuracy. The proposed low-noise current and voltage references based on triple negative T.C. circuits are employed on chip with optional off-chip reference voltages. The prototype ADC in a 0.13um 1P8M CMOS technology demonstrates the measured DNL and INL within 0.70LSB and 1.79LSB, respectively. The ADC shows a maximum SNDR of 64.5dB and a maximum SFDR of 78.0dB at 100MS/s, respectively. The ABC with an active die area of $1.22mm^2$ consumes 42.0mW at 100MS/s and a 1.2V supply, corresponding to a FOM of 0.31pJ/conv-step.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.1
• /
• pp.15-33
• /
• 2021

In this study, the possibility of discriminating Fire blight (FB) infection tested using the hyperspectral imagery. The reflectance of healthy and infected leaves and branches was acquired with 5 nm of full width at high maximum (FWHM) and then it was standardized to 10 nm, 25 nm, 50 nm, and 80 nm of FWHM. The standardized samples were divided into training and test sets at ratios of 7:3, 5:5 and 3:7 to find the optimal bands of FWHM by the decision tree analysis. Classification accuracy was evaluated using overall accuracy (OA) and kappa coefficient (KC). The hyperspectral reflectance of infected leaves and branches was significantly lower than those of healthy green, red-edge (RE) and near infrared (NIR) regions. The bands selected for the first node were generally 750 and 800 nm; these were used to identify the infection of leaves and branches, respectively. The accuracy of the classifier was higher in the 7:3 ratio. Four bands with 50 nm of FWHM (450, 650, 750, and 950 nm) might be reasonable because the difference in the recalculated accuracy between 8 bands with 10 nm of FWHM (440, 580, 640, 660, 680, 710, 730, and 740 nm) and 4 bands was only 1.8% for OA and 4.1% for KC, respectively. Finally, adding two bands (550 nm and 800 nm with 25 nm of FWHM) in four bands with 50 nm of FWHM have been proposed to improve the usability of multispectral image sensors with performing various roles in agriculture as well as detecting FB with other combinations of spectral bands.

• Journal of Service Research and Studies
• /
• v.13 no.1
• /
• pp.108-126
• /
• 2023

This study explored the sustainability of a blockchain-based cultural art performance video platform through the construction of Gyeonggi Art On, a new media art broadcasting station in Gyeonggi-do. In addition, the technical limitations of video content transaction using block chain, legal and institutional issues, and the protection of personal information and intellectual property rights were reviewed. As for the research method, participatory observation methods such as in-depth interviews with developers and operators and participation in meetings were conducted. The researcher participated in and observed the entire development process, including designing and developing blockchain nodes, smart contracts, APIs, UI/UX, and testing interworking between blockchain and content distribution services. Research Question 1: The results of the study on 'Which technology model is suitable for a blockchain-based performance video content distribution public platform?' are as follows. 1) The blockchain type suitable for the public platform for distribution of art performance video contents based on the blockchain is the private type that can be intervened only when the blockchain manager directly invites it. 2) In public platforms such as Gyeonggi ArtOn, among the copyright management model, which is an art based on NFT issuance, and the BC token and cloud-based content distribution model, the model that provides content to external demand organizations through API and uses K-token for fee settlement is suitable. 3) For public platform initial services such as Gyeonggi ArtOn, a closed blockchain that provides services only to users who have been granted the right to use content is suitable. Research question 2: What legal and institutional problems should be reviewed when operating a blockchain-based performance video distribution public platform? The results of the study are as follows. 1) Blockchain-based smart contracts have a party eligibility problem due to the nature of blockchain technology in which the identities of transaction parties may not be revealed. 2) When a security incident occurs in the block chain, it is difficult to recover the loss because it is unclear how to compensate or remedy the user's loss. 3) The concept of default cannot be applied to smart contracts, and even if the obligations under the smart contract have already been fulfilled, the possibility of incomplete performance must be reviewed.

• Journal of Intelligence and Information Systems
• /
• v.22 no.2
• /
• pp.57-79
• /
• 2016

It is a rising trend that the number of users using one of the social media channels, the Social Network Service, so called the SNS, is getting increased. As per to this social trend, more companies have interest in this networking platform and start to invest their funds in it. It has received much attention as a tool spreading and expanding the message that a company wants to deliver to its customers and has been recognized as an important channel in terms of the relationship marketing with them. The environment of media that is radically changing these days makes possible for companies to approach their customers in various ways. Particularly, the social network service, which has been developed rapidly, provides the environment that customers can freely talk about products. For companies, it also works as a channel that gives customized information to customers. To succeed in the online environment, companies need to not only build the relationship between companies and customers but focus on the relationship between customers as well. In response to the online environment with the continuous development of technology, companies have tirelessly made the novel marketing strategy. Especially, as the one-to-one marketing to customers become available, it is more important for companies to maintain the relationship marketing with their customers. Among many SNS, Facebook, which many companies use as a communication channel, provides a fan page service for each company that supports its business. Facebook fan page is the platform that the event, information and announcement can be shared with customers using texts, videos, and pictures. Companies open their own fan pages in order to inform their companies and businesses. Such page functions as the websites of companies and has a characteristic of their brand communities such as blogs as well. As Facebook has become the major communication medium with customers, companies recognize its importance as the effective marketing channel, but they still need to investigate their business performances by using Facebook. Although there are infinite potentials in Facebook fan page that even has a function as a community between users, which other platforms do not, it is incomplete to regard companies' Facebook fan pages as communities and analyze them. In this study, it explores the relationship among customers through the network of the Facebook fan page users. The previous studies on a company's Facebook fan page were focused on finding out the effective operational direction by analyzing the use state of the company. However, in this study, it draws out the structural variable of the network, which customer committment can be measured by applying the social network analysis methodology and investigates the influence of the structural characteristics of network on the business performance of companies in an empirical way. Through each company's Facebook fan page, the network of users who engaged in the communication with each company is exploited and it is the one-mode undirected binary network that respectively regards users and the relationship of them in terms of their marketing activities as the node and link. In this network, it draws out the structural variable of network that can explain the customer commitment, who pressed "like," made comments and shared the Facebook marketing message, of each company by calculating density, global clustering coefficient, mean geodesic distance, diameter. By exploiting companies' historical performance such as net income and Tobin's Q indicator as the result variables, this study investigates influence on companies' business performances. For this purpose, it collects the network data on the subjects of 54 companies among KOSPI-listed companies, which have posted more than 100 articles on their Facebook fan pages during the data collection period. Then it draws out the network indicator of each company. The indicator related to companies' performances is calculated, based on the posted value on DART website of the Financial Supervisory Service. From the academic perspective, this study suggests a new approach through the social network analysis methodology to researchers who attempt to study the business-purpose utilization of the social media channel. From the practical perspective, this study proposes the more substantive marketing performance measurements to companies performing marketing activities through the social media and it is expected that it will bring a foundation of establishing smart business strategies by using the network indicators.

• Korean Journal of Environment and Ecology
• /
• v.36 no.6
• /
• pp.651-661
• /
• 2022

Plants social network analysis, which combines plants society and social network analyses, is a new research method for understanding plants society. This study was conducted to investigate the relationship between species, using plant social network analysis targeting Taejongdae in Busan, and build basic data for management. Taejongdae, located in the warm temperate forest in Korea, is a representative coastal forest of Busan Metropolitan City, and the Pinus thunbergii-Eurya japonicacommunity is widely distributed. This study set up 100 quadrats (size of 100m²each) in Taejongdae to investigate the species that emerged and analyzed the interspecies association focusing on major species. Based on the results, a sociogram was created using the Gephi 0.9.2, and the network centrality and structure were analyzed. The results showed that the frequency of appearance was high in the order of P. thunbergii, E. japonica, Quercus serrata, Sorbus alnifolia, Ligustrum japonicum, and Styrax japonicusand that many evergreen broad-leaved trees appeared due to the environmental characteristics of the site. The plants social network of Taejongdae was composed of a small-scale network with 50 nodes and 172 links and was divided into 4 groups through modularization. The succession sere identified through a sociogram confirmed that the group that include P. thunbergiiand E. japonicawould progress to a deciduous broadleaf community dominated by Q. serrataand Carpinus tschonoskii, using hub nodes such as Prunus serrulataf. spontaneaand Toxicodendron trichocarpum. Another succession sere was highly likely to progress to an evergreen broad-leaved community dominated by Machilus thunbergiiand Neolitsea sericea, using M. thunbergiias a medium. In some areas, a transition to a deciduous broad-leaved community dominated by Celtis sinensis, Q. variabilisand Zelkova serratausing Lindera obtusilobaand C. sinensisas hub nodes was expected.

• Journal of Internet Computing and Services
• /
• v.16 no.1
• /
• pp.67-74
• /
• 2015

In recent years, frequent itemset mining for considering the importance of each item has been intensively studied as one of important issues in the data mining field. According to strategies utilizing the item importance, itemset mining approaches for discovering itemsets based on the item importance are classified as follows: weighted frequent itemset mining, frequent itemset mining using transactional weights, and utility itemset mining. In this paper, we perform empirical analysis with respect to frequent itemset mining algorithms based on transactional weights. The mining algorithms compute transactional weights by utilizing the weight for each item in large databases. In addition, these algorithms discover weighted frequent itemsets on the basis of the item frequency and weight of each transaction. Consequently, we can see the importance of a certain transaction through the database analysis because the weight for the transaction has higher value if it contains many items with high values. We not only analyze the advantages and disadvantages but also compare the performance of the most famous algorithms in the frequent itemset mining field based on the transactional weights. As a representative of the frequent itemset mining using transactional weights, WIS introduces the concept and strategies of transactional weights. In addition, there are various other state-of-the-art algorithms, WIT-FWIs, WIT-FWIs-MODIFY, and WIT-FWIs-DIFF, for extracting itemsets with the weight information. To efficiently conduct processes for mining weighted frequent itemsets, three algorithms use the special Lattice-like data structure, called WIT-tree. The algorithms do not need to an additional database scanning operation after the construction of WIT-tree is finished since each node of WIT-tree has item information such as item and transaction IDs. In particular, the traditional algorithms conduct a number of database scanning operations to mine weighted itemsets, whereas the algorithms based on WIT-tree solve the overhead problem that can occur in the mining processes by reading databases only one time. Additionally, the algorithms use the technique for generating each new itemset of length N+1 on the basis of two different itemsets of length N. To discover new weighted itemsets, WIT-FWIs performs the itemset combination processes by using the information of transactions that contain all the itemsets. WIT-FWIs-MODIFY has a unique feature decreasing operations for calculating the frequency of the new itemset. WIT-FWIs-DIFF utilizes a technique using the difference of two itemsets. To compare and analyze the performance of the algorithms in various environments, we use real datasets of two types (i.e., dense and sparse) in terms of the runtime and maximum memory usage. Moreover, a scalability test is conducted to evaluate the stability for each algorithm when the size of a database is changed. As a result, WIT-FWIs and WIT-FWIs-MODIFY show the best performance in the dense dataset, and in sparse dataset, WIT-FWI-DIFF has mining efficiency better than the other algorithms. Compared to the algorithms using WIT-tree, WIS based on the Apriori technique has the worst efficiency because it requires a large number of computations more than the others on average.

• Korean Journal of Heritage: History & Science
• /
• v.52 no.3
• /
• pp.172-187
• /
• 2019

Knowledge of intangible cultural heritage is usually disseminated through word-of-mouth and actions rather than written records. Thus, people assemble to teach others about it and form communities. Accordingly, to understand and spread information about intangible cultural heritage properly, it is necessary to understand not only their attributes but also a community's relational characteristics. Community members include specialized transmitters who work under the auspices of institutions, and general transmitters who enjoy intangible cultural heritage in their daily lives. They converse about intangible cultural heritage in close relationships. However, to date, research has focused only on professionals. Thus, this study focused on the roles of general transmitters of intangible cultural heritage information by investigating intangible cultural heritage communities centering around Jeongseon Arirang; a social network analysis was performed. Regarding the research objectives presented in the introduction, the main findings of the study are summarized as follows. First, there were 197 links between 74 members of the Jeongseon Arirang Transmission Community. One individual had connections with 2.7 persons on average, and all were connected through two steps in the community. However, the density and the clustering coefficient were low, 0.036 and 0.32, respectively; therefore, the cohesiveness of this community was low, and the relationships between the members were not strong. Second, 'Young-ran Yu', 'Nam-gi Kim' and 'Gil-ja Kim' were found to be the prominent figures of the Jeongseon Arirang Transmission Community, and the central structure of the network was concentrated around these three individuals. Being located in the central structure of the network indicates that a person is popular and ranked high. Also, it means that a person has an advantage in terms of the speed and quantity of the acquisition of information and resources, and is in a relatively superior position in terms of bargaining power. Third, to understand the replaceability of the roles of Young-ran Yu, Nam-gi Kim, and Gil-ja Kim, who were found to be the major figures through an analysis of the central structure, structural equivalence was profiled. The results of the analysis showed that the positions and roles of Young-ran Yu, Nam-gi Kim, and Gil-ja Kim were unrivaled and irreplaceable in the Jeongseon Arirang Transmission Community. However, considering that these three members were in their 60s and 70s, it seemed that it would be necessary to prepare measures for the smooth maintenance and operation of the community. Fourth, to examine the subgroup hidden in the network of the Jeongseon Arirang Transmission Community, an analysis of communities was conducted. A community refers to a subgroup clearly differentiated based on modularity. The results of the analysis identified the existence of four communities. Furthermore, the results of an analysis of the central structure showed that the communities were formed and centered around Young-ran Yu, Hyung-jo Kim, Nam-gi Kim, and Gil-ja Kim. Most of the transmission TAs recommended by those members, students who completed a course, transmission scholarship holders, and the general members taught in the transmission classes of the Jeongseon Arirang Preservation Society were included as members of the communities. Through these findings, it was discovered that it is possible to maintain the transmission genealogy, making an exchange with the general members by employing the present method for the transmission of Jeongseon Arirang, the joint transmission method. It is worth paying attention to the joint transmission method as it overcomes the demerits of the existing closed one-on-one apprentice method and provides members with an opportunity to learn their masters' various singing styles. This study is significant for the following reasons: First, by collecting and examining data using a social network analysis method, this study analyzed phenomena that had been difficult to investigate using existing statistical analyses. Second, by adopting a different approach to the previous method in which the genealogy was understood, looking at oral data, this study analyzed the structures of the transmitters' relationships with objective and quantitative data. Third, this study visualized and presented the abstract structures of the relationships among the transmitters of intangible cultural heritage information on a 2D spring map. The results of this study can be utilized as a baseline for the development of community-centered policies for the protection of intangible cultural heritage specified in the UNESCO Convention for the Safeguarding of Intangible Cultural Heritage. To achieve this, it would be necessary to supplement this study through case studies and follow-up studies on more aspects in the future.