• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1041-1043
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• 2016

This letter proposes a new blind fractionally spaced equalization (FSE). The conventional linear program (LP) FSE reduces the degree of freedom (DOF) by abandoning many equalization filter taps, which causes severe performance degradations. We use singular value decomposition (SVD) to obtain the signal subspace and to fully utilize all samples for performance improvement. The proposed scheme has similar performance with the nuclear norm minimization and has as low complexity as the LP equalizer.

• Journal of Distribution Science
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• v.20 no.6
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• pp.1-10
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• 2022

Purpose: This research proposes a new modified Recency-Frequency-Monetary (RFM) model by extending the model with spatial analysis for supporting decision-makers in discovering the promotional target market. Research design, data and methodology: This quantitative research utilizes data-mining techniques and the RFM model to cluster a university's provider schools. The RFM model was modified by adapting its variables to the university's marketing context and adding a district's potential (D) variable based on heatmap analysis using Geographic Information System (GIS) and K-means clustering. The K-prototype algorithm and the Elbow method were applied to find provider school clusters using the proposed RFM-D model. After profiling the clusters, the target segment was assigned. The model was validated using empirical data from an Indonesian university, and its performance was compared to the Customer Lifetime Value (CLV)-based RFM utilizing accuracy, precision, recall, and F1-score metrics. Results: This research identified five clusters. The target segment was chosen from the highest-value and high-value clusters that comprised 17.80% of provider schools but can contribute 75.77% of students. Conclusions: The proposed model recommended more targeted schools in higher-potential districts and predicted the target segment with 0.99 accuracies, outperforming the CLV-based model. The empirical findings help university management determine the promotion location and allocate resources for promotional information distribution and student recruitment.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.64-76
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• 2024

We study three sports media start-ups that seek to promote business model innovation (BMI) in which Web 3.0 and metaverse are converged. In results, LM starts from an innovative digital space platform offering a unique combination of virtual real estate, games, and non-fungible tokens (NFTs) which come with real-world earning potential. It creates value by integrating virtual real estate, training academies, blockchain games, and meta shops to offer a unique experience, capture value by offering monetization tools for buying and trading limited edition NFTs of favorite influencers from various sports leagues, offering access to premier real-world events and VIP game contests, and delivers value by building community to play games with favorite athletes or teams including trivia games, allowing fans to engage with their favorite athletes in a unique exclusive way. SL starts from the customizable digital identities especially for young sports fans like generation (gen) Z to play, hang out, and express themselves with their own avatars. SI starts from a leading Web3.0 metaverse innovator creating NFTs with the greatest athletes of all time, allowing athletes and creators to set up a profile and mint NFTs directly onto the blockchain. It tries to have the partnerships with great athletes revolutionizing the sports media industry to connect sports heroes and their super fans through an immersive, artistic, inspirational NFTs and unlockable content creating a sticky community between them.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.244-259
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• 2021

The economic value of personal information has its importance as an objective measure of valuation in commercial, legal, and policy areas. Until recently, however, personal information subjects have not properly recognized the economic value of personal information, which has led to the inability to exercise the right to self-determination of personal information by unconsciously agreeing to the terms and conditions of personal information service without recognizing the value of personal information provided to the service provider when subscribing to a specific service. Therefore, we will examine the methodologies for calculating the economic value of personal information and the practical guarantee of the right to self-determination of personal information and analyze the economic value of personal information through a survey. Also, we would like to propose various ways for the subject of personal information with limited cognitive resources to visually accept the economic value of personal information required by the terms and conditions and suggest the optimal visualization of personal information economic value to exercise the right to self-determination of personal information. To do so, in this paper, we have conducted two survey experiments to estimate the economic value of personal information. Based on the price of personal information by category retrieved from surveys, we have visualized the price of personal information in various forms and asked respondents to choose the optimal infographic that best represents the value of personal information visually. As a result, we have proposed an optimal usage of the infographic to 'nudge' information subjects about their right to self-determination of personal information, therefore opening the possibility of diminishing privacy paradox.

• Journal of information and communication convergence engineering
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• v.12 no.1
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• pp.60-65
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• 2014

This paper describes an efficient framework for the extraction of a brain tumor from magnetic resonance (MR) images. Before the segmentation process, a median filter is used to filter the image. Then, the morphological gradient is computed and added to the filtered image for intensity enhancement. After the enhancement process, the thresholding value is calculated using the mean and the standard deviation of the image. This thresholding value is used to binarize the image followed by the morphological operations. Moreover, the combination of these morphological operations allows to compute the local thresholding image supported by a flood-fill algorithm and a pixel replacement process to extract the tumor from the brain. Thus, this framework provides a new source of evidence in the field of segmentation that the specialist can aggregate with the segmentation results in order to soften his/her own decision.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.1055-1064
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• 2003

In many automated systems, such as manufacturing systems and process plants, a fieldbus is a very important component for the exchange of various and sometimes crucial information. Some of the information has a tendency to rapidly lose its value as time elapses after its creation. Such information or data is called real-time data that includes sensor values and control commands. In order to deliver these data in time, the fieldbus network should be tailored to have short delay with respect to the individual time limit of various data. Fine-tuning the network for a given traffic requires the knowledge on the relationship between the protocol parameters such as timer values and the performance measure such as network delay. This paper presents a mathematical performance model to calculate communication delays of the Profibus-FMS network when the timer value and the traffic characteristics are given.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3080-3099
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• 2016

In this paper, we propose an algorithm for energy efficient cooperative communication in wireless sensor network (WSN). The algorithm computes the appropriate transmission distance corresponding to optimal broadcast bit error probability, while taking the circuit energy consumption and the number of cooperating nodes into consideration. The algorithm guarantees minimum energy consumption by choosing higher value of bit error probability for cooperative phase and lower value of bit error probability for broadcast phase while maintaining the required end-to-end reliability. The simulation results show that the proposed algorithm provides significant energy saving gain when compared with traditional fixed distance schemes and is suitable for applications demanding energy efficiency with high quality of reception.

• Journal of the Korea Society for Simulation
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• v.13 no.2
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• pp.1-12
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• 2004

This paper estimated the arrival angle and electric wave delay time using the space method law and the directions of arrival (DOA) estimation algorithm in case of signal correlation. Space method law is the method used to repress cross correlation before applying the weight value to the receiving signal. The values of the diagonal elements in the correlation matrix were averaged to replace as the diagonal elements value. In the area of wireless communication or mobile communication, there are high correlations in case of low delay time difference in multiple waves. This causes the quality of the communication to drop due to interference with the desired signal elements. This paper estimated the arrival angle and electric wave delay time using the space method law and the MUSIC algorithm. With the arrival angle algorithm, the arrival angle cannot be estimated below 5 in case of signal correlations because the angle resolution capacity decreases accordingly. The super resolution capacity was estimated to determine the arrival angle below 5 in this paper. In addition, the proposed algorithm estimated the short delay time difference to be below 20ns.

• ETRI Journal
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• v.40 no.5
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• pp.677-686
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• 2018

A novel data hiding technique based on modified histogram shifting that incorporates multi-bit secret data hiding is proposed. The proposed technique divides the image pixel values into embeddable and nonembeddable pixel values. Embeddable pixel values are those that are within a specified limit interval surrounding the peak value of an image. The limit interval is calculated from the number of secret bits to be embedded into each embeddable pixel value. The embedded secret bits can be perfectly extracted from the stego image at the receiver side without any overhead bits. From the simulation, it is found that the proposed technique produces a better quality stego image compared to other data hiding techniques, for the same embedding rate. Since the proposed technique only embeds the secret bits in a limited number of pixel values, the change in the visual quality of the stego image is negligible when compared to other data hiding techniques.

• Proceedings of the IEEK Conference
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• summer
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• pp.395-399
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• 2004

We present modality conversion as an effective means for QoS management. We show that modality conversion, in combination with content scaling, would give a wider range of adaptation to support QoS at media level. Here, we consider modality conversion with respect to resource constraint and human factor. To represent modality conversion as well as content scaling, we present the overlapped content value (OCV) model that relates the content value of different modalities with resources. The specification of user preference on modality conversion is divided into qualitative and quantitative levels. The user preference is then integrated into the OCV model so that modality conversion correctly reflects the user's wishes. For the conversion of multiple contents, an optimization problem is formulated and solved by dynamic programming. The experiments show that the proposed approach is efficient to be applied in practice.