• Journal of Korea Society of Digital Industry and Information Management
• /
• v.7 no.4
• /
• pp.75-79
• /
• 2011

With the rapid growth of digital communication and the internet, the importance of conducting research on data encryption methods is increasing. Some of the pertinent researches that have been conducted so far introduced data encryption methods using chaos systems, and numerous researches are currently being conducted on such methods. The signals produced by the chaos systems are called "determined noise," and if this is applied to data encryption, very effective results can be obtained. Using the Henon map, the relationship between the non-linearity of the chaos system and the strength of encryption was analyzed, and a linear-structure chaos system that uses non-linearity as a variable for encryption strength was constructed. Using the constructed chaos system, an image was encrypted and decoded, and the correlation coefficient of the linear-structure chaos system's performance was calculated and then analyzed.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.9
• /
• pp.898-904
• /
• 2006

Ionospheric storms, caused by the interaction between Solar and geomagnetic activities, may degrade the differential GNSS(Global Navigation Satellite Systems) performance significantly, and the importance of the ionospheric storm research is growing for the GBAS(Ground-Based Augmentation System) and SBAS(Satellite-Based Augmentation System) development. In order to support Korean GNSS augmentation system development, a software tool for analyzing the regional ionosphere is being developed and its preliminary results are discussed. After brief description of the ionosphere and ionospheric storm, the research topics on the GBAS applications are discussed. The need for ionospheric spatial gradient analysis is described and some results on the ionospheric spatial gradient during recent storm periods are discussed.

• The Korean Journal of Community Living Science
• /
• v.27 no.4
• /
• pp.739-753
• /
• 2016

This study was performed to identify the tendency and benefits of outdoor recreation in rural areas. The preferences and importance of the benefits of outdoor recreation activities in rural areas were simultaneously compared and analyzed through the discussion of a four quadrants portfolio map using importance-performance analysis. The social benefits in quadrant i had the characteristics of 'sharing nice experiences with others', 'having contact/interchange with others', 'colleagueship/helping each other', 'being together with friends', and 'making new friends.' These social benefit types were perceived as very important characteristics, but the real level of achievement was rather low. Thus it seems necessary, in the process of program development, to apply the social benefit types to the characteristics of the participants. The experience of nature and relaxation benefits in quadrant ii had the characteristics of 'relaxation and recreation', 'understanding nature', 'nature experience', 'getting away from everyday life', and 'experiencing new things.' These benefits and experience of nature were regarded as very important characteristics by the participants in outdoor recreation and, at the same time, their real achievements were highly recognized, thus they seemed to be proper types for the goals involved in developing an outdoor recreation activity program in rural areas. The personal and challenge benefits in quadrant iv had the characteristics of 'training of mental ability', 'improvement of self-esteem', 'fitness', 'increase in determination', 'possible danger', 'achievement', 'excitement', and 'adventure.' These benefits had less importance to the participants, but had relatively high achievement, thus it might be important to make further suggestions for the direction of development according to the participants' tendency, seasons and facilities.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.1
• /
• pp.54-60
• /
• 2021

AR (Augmented Reality) is a technology that provides virtual content to the real world and provides additional information to objects in real-time through 3D content. In the past, a high-performance device was required to experience AR, but it was possible to implement AR more easily by improving mobile performance and mounting various sensors such as ToF (Time-of-Flight). Also, the importance of mobile augmented reality is growing with the commercialization of high-speed wireless Internet such as 5G. Thus, this paper proposes a system that can provide AR services via GNN (Graph Neural Network) using cameras and sensors on mobile devices. ToF of mobile devices is used to capture depth maps. A 3D point cloud was created using RGB images to distinguish specific colors of objects. Point clouds created with RGB images and Depth Map perform downsampling for smooth communication between mobile and server. Point clouds sent to the server are used for 3D object detection. The detection process determines the class of objects and uses one point in the 3D bounding box as an anchor point. AR contents are provided through app and web through class and anchor of the detected object.

• Journal of Korean Society of Transportation
• /
• v.23 no.8 s.86
• /
• pp.193-202
• /
• 2005

Due to the importance of SCM(Supply Chain management) in business logistics. many studies related to the SCM performance measurement have been conducted. However, previous SCM performance measurement models have not reflected both ways, operational efficiency and response for market shift. The aim of this research is to suggest a dynamic model to measure SCM performance both with operational efficiency and response for market shift, based on previous SCOR model. To achieve this aim, we developed a cognitive map-based model described eleven KPIs (Key Performance Indicators) with different weight values. And, to measure response level for market shift, we used the concept of entropy-elasticities. Finally, through some actual cases, merits that have no previous models were shown.

• The Korean Journal of Franchise Management
• /
• v.9 no.3
• /
• pp.19-29
• /
• 2018

Purpose - Due to the increase in coffee consumption and competition, domestic coffee franchise companies are currently entering the overseas market. Therefore, coffee franchise companies are pursuing a variety of marketing strategies to meet customer needs and gain competitive advantage in overseas markets. From this perspective, overseas franchise companies need to ensure that their servicescapes meet the needs of their overseas customers. For these purposes, the study is to identify the impact servicescapes on customer satisfaction and customer loyalty focused on Global Coffee Franchise Company "C", which extended its business worldwide in Mongolia. Research design, data, and methodology - The data were collected from customers who had visited the stores of 'C' company in Ulaanbaatar, Mongolia. 435 valid questionnaires collected through online survey coded and analyzed using frequency, confirmatory factor analysis, correlations analysis, and structural equation modeling with SPSS 24 and SmartPLS 3.0. Result - Firstly, seating comfort, facility aesthetics, and cleanliness, ambient conditions among servicescapes influenced customer satisfaction. Secondly, servicescapes didn't affect the loyalty directly. Third, customer satisfaction had positive effect on loyalty. Fourthly, cleanliness which was ranked lower in Korea had a great effect on customer satisfaction in Mongolia. Fifthly, IPMA(Importance-performance map analysis) shows that the importance of servicescapes is higher for women than for men, and facility aesthetics for female and cleanliness is the most important for male. Conclusions - The results of this study show that there is a positive (+) effect on customer satisfaction in order of cleanliness, ambient conditions, aesthetics, and seating comfort. Therefore, franchise companies considering or advancing into Mongolia should consider importance in order of cleanliness, ambient conditions and aesthetics when entering Mongolia market. For example, franchise managers should select Monday as a "clean day," and all merchants should spend all of their open hours and keep their stores clean in accordance with the head office manual. In addition, franchise managers need to hire a VMD (visual merchandising) experts to build up a physical environment that will effectively highlight the space-specific display of the store so that Mongolian local customers can have a satisfactory climate and aesthetics. And, the IMPA analysis between servicescapes and customer satisfaction shows that women are more susceptible to servicescapes than men. Especially, in the case of women, the importance of esthetics is high, but the performance is low. Thus, if the aesthetics are actively improved, customer satisfaction can be effectively increased.

• The Journal of the Acoustical Society of Korea
• /
• v.42 no.6
• /
• pp.544-551
• /
• 2023

Speech enhancement used to improve the perceptual quality and intelligibility of noise speech has been studied as a method using a complex-valued spectrum that can improve both magnitude and phase in a method using a magnitude spectrum. In this paper, a study was conducted on how to apply attention mechanism to complex-valued spectrum-based speech enhancement systems to further improve the intelligibility and quality of noise speech. The attention is performed based on additive attention and allows the attention weight to be calculated in consideration of the complex-valued spectrum. In addition, the global average pooling was used to consider the importance of the feature map. Complex-valued spectrum-based speech enhancement was performed based on the Deep Complex U-Net (DCUNET) model, and additive attention was conducted based on the proposed method in the Attention U-Net model. The results of the experiments on noise speech in a living room environment showed that the proposed method is improved performance over the baseline model according to evaluation metrics such as Source to Distortion Ratio (SDR), Perceptual Evaluation of Speech Quality (PESQ), and Short Time Object Intelligence (STOI), and consistently improved performance across various background noise environments and low Signal-to-Noise Ratio (SNR) conditions. Through this, the proposed speech enhancement system demonstrated its effectiveness in improving the intelligibility and quality of noisy speech.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2010.06a
• /
• pp.81-82
• /
• 2010

Emerging global economic growth and increasing demand for energy supply and demand imbalance and the excessive use of fossil fuels existing the rapidly increasing greenhouse gas emissions and resource depletion of global energy crisis is deepening. Accordingly, improvement of living conditions around and through the natural ecological preservation and the need for a comfortable life for the meeting the importance of energy management and consumption are emerging. Many in the field of architecture for energy-saving measures, and conducting research and verify green building energy ratings and low energy for the initial steps that can be verified from the Energy Performance of BIM(Building Information Model) technology development and commercialization of the building energy to predict the performance objectively, leverages technology in an existing building energy performance analysis and possibilities of BIM-based green building process presented. In this study, using BIM for existing building energy performance analysis of data collected through the objective and efficient management of the energy it consumes Mapping and Management Plan is to research on.

• Korean Journal of Remote Sensing
• /
• v.34 no.1
• /
• pp.45-74
• /
• 2018

Landslide is a natural hazard that threats lives and properties in many areas around the world. Landslides are difficult to recognize, particularly in rainforest regions. Thus, an accurate, detailed, and updated inventory map is required for landslide susceptibility, hazard, and risk analyses. The inconsistency in the results obtained using different features selection techniques in the literature has highlighted the importance of evaluating these techniques. Thus, in this study, six techniques of features selection were evaluated. Very-high-resolution LiDAR point clouds and orthophotos were acquired simultaneously in a rainforest area of Cameron Highlands, Malaysia by airborne laser scanning (LiDAR). A fuzzy-based segmentation parameter (FbSP optimizer) was used to optimize the segmentation parameters. Training samples were evaluated using a stratified random sampling method and set to 70% training samples. Two machine-learning algorithms, namely, Support Vector Machine (SVM) and Random Forest (RF), were used to evaluate the performance of each features selection algorithm. The overall accuracies of the SVM and RF models revealed that three of the six algorithms exhibited higher ranks in landslide detection. Results indicated that the classification accuracies of the RF classifier were higher than the SVM classifier using either all features or only the optimal features. The proposed techniques performed well in detecting the landslides in a rainforest area of Malaysia, and these techniques can be easily extended to similar regions.

• International Journal of Computer Science & Network Security
• /
• v.21 no.3
• /
• pp.83-93
• /
• 2021

COVID-19 poses a major risk to global health, highlighting the importance of faster and proper diagnosis. To handle the rise in the number of patients and eliminate redundant tests, healthcare information exchange and medical data are transmitted between healthcare centres. Medical data sharing helps speed up patient treatment; consequently, exchanging healthcare data is the requirement of the present era. Since healthcare professionals share data through the internet, security remains a critical challenge, which needs to be addressed. During the COVID-19 pandemic, computed tomography (CT) and X-ray images play a vital part in the diagnosis process, constituting information that needs to be shared among hospitals. Encryption and image steganography techniques can be employed to achieve secure data transmission of COVID-19 images. This study presents a new encryption with the image steganography model for secure data transmission (EIS-SDT) for COVID-19 diagnosis. The EIS-SDT model uses a multilevel discrete wavelet transform for image decomposition and Manta Ray Foraging Optimization algorithm for optimal pixel selection. The EIS-SDT method uses a double logistic chaotic map (DLCM) is employed for secret image encryption. The application of the DLCM-based encryption procedure provides an additional level of security to the image steganography technique. An extensive simulation results analysis ensures the effective performance of the EIS-SDT model and the results are investigated under several evaluation parameters. The outcome indicates that the EIS-SDT model has outperformed the existing methods considerably.