• Design Convergence Study
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• v.16 no.5
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• pp.1-20
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• 2017

Cardio-cerebrovascular disease is one of the chronic diseases that often attack people in Korea, and in fact, it ranks second in terms of death rate. This disease can be prevented by improving lifestyle, usual health care is important. But, in Korea most of the prevention or management programs adopt passive methods like using guide books or giving lectures, so it is not very effective in preventing the disease. Presently, the smart health care market is being developed in Korea and overseas. As an example, quantified self is being spread through wearable devices which are intended to measure each individual's health conditions and quantify body data into numbers for bettering habits. Accordingly, this author will explore and discuss wearable health care devices so as to prevent and manage cardio-cerebrovascular disease in a more active way. First, this study has classified wearable health care devices presently commercialized or related with cardio-cerebrovascular disease into wrist, clothes, or attaching types by the way of their attachment and analyzed them. After that, summing that up, this author performed cross-tabulations with other ways of preventing cardio-cerebrovascular disease. This will contribute to improving one's health care behavior about disease more actively and also work as an active interdisciplinary mechanism in research dealing with how to prevent disease afterwards.

• Design Convergence Study
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• v.15 no.2
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• pp.17-35
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• 2016

Along with popularization of smart phone and routinization of social network service, enterprises are using several social network services as a marketing channel to raise brand awareness and conduct PR. Enterprises have been utilizing an element of 'Gamification' representing a functional aspect and emotional pleasure of a game in order to attract users' attention and increase their voluntary participation since the early social network service marketing. However, social network service system contains functional roles of Gamification components rather than they function separately. Hence, this research intends to examine Gamification elements of social network service and characteristics occurred when enterprise uses several social network services as a marketing channel. Besides, it aims at suggesting a marketing guideline for Gamification based on social network that may induce users' interest and increase an immersion effect. Firstly, this study examined concepts and characteristics of social network service and Gamification centered on literature research. Secondly, it summarized a game mechanics, dynamics and a fun type of Gamification components. Thirdly, based on theoretical research, it collected Gamification marketing cases of 5 enterprises including 'Coca Cola Korea', 'Lotte Mart', 'Canon Korea', "Kolon Sports' and 'Uniqlo Korea' that utilize more than 3 of 4 social network services including 'Kakao Story', 'Band', 'Facebook' and 'Instagram' used the most in our nation, analyzing characteristics of Gamification marketing and deriving a suggestion. Finally, it suggested a guideline for Gamification and social network service to build a foundation for a Gamification marketing plan through social network service.

• The Korean Journal of Franchise Management
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• v.8 no.2
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• pp.25-36
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• 2017

Purpose - Recently, entrepreneurship education has been revitalized with interest in entrepreneurship. Entrepreneurship education is an educational service activity that is provided for entrepreneurship and individual start-up success within a certain period of time. According to previous studies on entrepreneurship and entrepreneurship, the satisfaction of entrepreneurship education affects entrepreneurship and as a result increases entrepreneurship. In recent years, the number of female entrepreneurs has also increased as the number of entrepreneurial issues has increased. Based on previous studies, this research proposed the theoretical framework about the structural relationships among mentoring quality (career development, psychological social, role modeling), education satisfaction, recommendation intention and entrepreneurial intention. This study is to find out the possibility of attempting to create a theoretical basis for entrepreneurial mentoring education in entrepreneurship education program. Research design, data, and methodology - In this model, mentoring quality consists of three sub-dimensions such as career development, psychological social, and role modeling. In order to test research model and hypotheses, the data were collected from 203 female college students who participated in entrepreneurial education. The data were analyzed using frequency analysis, confirmatory factor analysis, correlation analysis, and structural equational modeling with SPSS 24.0 and SmartPLS 3.0 statistical program. Result - The results of the study are as follows. First, role modeling has a positive effect on recommendation intention and entrepreneurial intention. Second, career development has a strong negative effect on the entrepreneurial intention. Third, career development and role modeling had a positive effect on educational satisfaction, and educational satisfaction had positive influence on recommendation intention and entrepreneurial intention. Conclusions - As women's social advancement becomes more active, start-up support programs including entrepreneurship mentoring are increasing. The results of this study suggest how to use the mentoring program mix and how to allocate the resources for the education program when the entrepreneurial education manager plans and executes the mentoring education program. For example, this study shows that career development and role modeling enhance educational satisfaction, and in turn increase recommendation intention and entrepreneurial intention. This means that entrepreneurship education should consist of contents that include career development functions such as sponsorship, guidance, protection, and provision of challenging work. In addition, the findings of this study indicate that mentors should perform the function of allowing the participants to have confidence and professional thinking ability at the time of start up based on their experiences.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.737-746
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• 2023

As the core infrastructure to lead technical innovation for the fourth industrial revolution, economic value and utilizations of radiowaves are increased rapidly. The objectives of this study are to recognize the growing trend of radio stations that transmit information using radiowaves, a limited resource of the country, and to propose developed plans for the radio stations operation system in line with the changing radio technology and use environment. To be specific, the detailed implementation procedures and methods of the system were derived in accordance with the government's plan to convert the complete inspection of radio stations into a SDoC(Self Declaration of Conformity) by the telco. SDoC is a policy that grants autonomy and responsibility for radio waves interference management to existing telecom operator recognized as having radio stations operating capabilities. It has significance in that the function of radio stations inspection, which is a representative technical regulation, is efficiently distributed to the government and the private sector. This study has significance in providing reference for expediting deregulation in the radiowaves management policy.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.113-123
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• 2023

This paper introduces the Cherry system, a user-independent blockchain donation system. This is a procedure that is delivered to the beneficiary's bank account through a virtual account when a donor makes a donation, so there is no difference from the existing donation delivery method from the user's point of view However, within the blockchain, Cherry Points, a virtual currency based on the user ID, are issued and delivered to the beneficiary, while all transactions and the beneficiary's usage history are managed on the blockchain. By adopting this method, there was an improvement in blockchain performance, with transaction processing exceeding 1,000 TPS in typical transaction condition and service completion within 21.3 seconds. By applying the automatic influence control algorithm to this system, the influence according to stake, which is an individual donation, is greatly reduced to 0.3 after 2 months, thereby concentrating influence could be controlled automatically. In addition, it was designed to enable micro tracking by adding a tracking function by timestamp to the donation ledger for each individual ID, which greatly improved the transparency in the use of donations. From a service perspective, existing blockchain donation systems were handled as limited donation delivery methods. Since it is a direct service in a user-independent method, convenience has been greatly improved by delivering donations in various forms.

• The Transactions of the Korea Information Processing Society
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• v.13 no.2
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• pp.48-59
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• 2024

As functions that support virtualization on their own in hardware are developed, user applications having various workloads are operating efficiently in the virtualization system. SR-IOV is a virtualization support function that takes direct access to PCI devices, thus giving a high I/O performance by minimizing the need for hypervisor or operating system interventions. With SR-IOV, network I/O acceleration can be realized in virtualization systems that have relatively long I/O paths compared to bare-metal systems and frequent context switches between the user area and kernel area. To take performance advantages of SR-IOV, network resource management policies that can derive optimal network performance when SR-IOV is applied to an instance such as a virtual machine(VM) or container are being actively studied.This paper evaluates and analyzes the network performance of SR-IOV implementing I/O acceleration is compared with Virtio in terms of 1) network delay, 2) network throughput, 3) network fairness, 4) performance interference, and 5) multi-network. The contributions of this paper are as follows. First, the network I/O process of Virtio and SR-IOV was clearly explained in the virtualization system, and second, the evaluation results of the network performance of Virtio and SR-IOV were analyzed based on various performance metrics. Third, the system overhead and the possibility of optimization for the SR-IOV network in a virtualization system with high VM density were experimentally confirmed. The experimental results and analysis of the paper are expected to be referenced in the network resource management policy for virtualization systems that operate network-intensive services such as smart factories, connected cars, deep learning inference models, and crowdsourcing.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.30-40
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• 2024

Building an accurate 3-D spatial road network model has become an active area of research now-a-days that profess to be a new paradigm in developing Smart roads and intelligent transportation system (ITS) which will help the public and private road impresario for better road mobility and eco-routing so that better road traffic, less carbon emission and road safety may be ensured. Dealing with such a large scale 3-D road network data poses challenges in getting accurate elevation information of a road network to better estimate the CO₂ emission and accurate routing for the vehicles in Internet of Vehicle (IoV) scenario. Clustering and regression techniques are found suitable in discovering the missing elevation information in 3-D spatial road network dataset for some points in the road network which is envisaged of helping the public a better eco-routing experience. Further, recently Explainable Artificial Intelligence (xAI) draws attention of the researchers to better interprete, transparent and comprehensible, thus enabling to design efficient choice based models choices depending upon users requirements. The 3-D road network dataset, comprising of spatial attributes (longitude, latitude, altitude) of North Jutland, Denmark, collected from publicly available UCI repositories is preprocessed through feature engineering and scaling to ensure optimal accuracy for clustering and regression tasks. K-Means clustering and regression using Support Vector Machine (SVM) with radial basis function (RBF) kernel are employed for 3-D road network analysis. Silhouette scores and number of clusters are chosen for measuring cluster quality whereas error metric such as MAE ( Mean Absolute Error) and RMSE (Root Mean Square Error) are considered for evaluating the regression method. To have better interpretability of the Clustering and regression models, SHAP (Shapley Additive Explanations), a powerful xAI technique is employed in this research. From extensive experiments , it is observed that SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions with an accuracy of 97.22% and strong performance metrics across all classes having MAE of 0.0346, and MSE of 0.0018. On the other hand, the ten-cluster setup, while faster in SHAP analysis, presented challenges in interpretability due to increased clustering complexity. Hence, K-Means clustering with K=4 and SVM hybrid models demonstrated superior performance and interpretability, highlighting the importance of careful cluster selection to balance model complexity and predictive accuracy.

• Smart Structures and Systems
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• v.34 no.2
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• pp.97-116
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• 2024

The standard l₁-norm regularization is recently introduced for impact force identification, but generally underestimates the peak force. Compared to l₁-norm regularization, l_p-norm (0 ≤ p < 1) regularization, with a nonconvex penalty function, has some promising properties such as enforcing sparsity. In the framework of sparse regularization, if the desired solution is sparse in the time domain or other domains, the under-determined problem with fewer measurements than candidate excitations may obtain the unique solution, i.e., the sparsest solution. Considering the joint sparse structure of impact force in temporal and spatial domains, we propose a general l_p-norm (0 ≤ p < 1) regularization methodology for simultaneous identification of the impact location and force time-history from highly incomplete measurements. Firstly, a nonconvex optimization model based on l_p-norm penalty is developed for regularizing the highly under-determined problem of impact force identification. Secondly, an iteratively reweighed l₁-norm algorithm is introduced to solve such an under-determined and unconditioned regularization model through transforming it into a series of l₁-norm regularization problems. Finally, numerical simulation and experimental validation including single-source and two-source cases of impact force identification are conducted on plate structures to evaluate the performance of l_p-norm (0 ≤ p < 1) regularization. Both numerical and experimental results demonstrate that the proposed l_p-norm regularization method, merely using a single accelerometer, can locate the actual impacts from nine fixed candidate sources and simultaneously reconstruct the impact force time-history; compared to the state-of-the-art l₁-norm regularization, l_p-norm (0 ≤ p < 1) regularization procures sufficiently sparse and more accurate estimates; although the peak relative error of the identified impact force using l_p-norm regularization has a decreasing tendency as p is approaching 0, the results of l_p-norm regularization with 0 ≤ p ≤ 1/2 have no significant differences.

• Journal of Internet of Things and Convergence
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• v.10 no.4
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• pp.89-99
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• 2024

The purpose of this study was to examine how functional movement screen (FMS) affects the health fitness of adults and to consider how injury prevention measures that utilize the strengths of each function are helpful. The subjects of the study were 40 ordinary people who received level 1 in the physical fitness evaluation results of National Fitness 100. For data processing, correlation analysis was performed to determine the relationship between variables, and paired t-test was performed to compare differences between variables according to gender. The research results are as follows. First, a correlation between FMS and health fitness was confirmed. Second, gender differences were confirmed in FMS measurement. Third, gender differences were confirmed in the health fitness test. By utilizing the advantages of functional movement screen (FMS) measurement, we presented how it contributes to injury prevention for recreational athletes, and presented an effective exercise method by analyzing the differences in FMS measurement and health fitness according to gender. Through these FMS measurements and health fitness measurement research, we hope to apply IT technology and wearable technology to improve the health of adults and prevent injuries, and improve the physical strength and health of the people.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1321-1321
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• 2024

Concrete arch dams, unlike conventional concrete gravity dams, have thin arch-shaped cross sections and must be designed considering a three-dimensional shape. In particular, double-curvature arch dams, which have arch-shaped vertical and horizontal sections, require careful consideration during design due to their unique shape. Although stress analysis is complex, and various factors need to be considered during the design, these dams offer economic advantages as they require less material. Consequently, numerous double-curvature arch dams have been constructed worldwide, and ongoing research focuses on optimizing their shapes. In this study, an efficient optimization algorithm was developed for the shape optimization of concrete arch dams with double-curvature using genetic algorithms and improved population initializing technique. The developed technique utilized domain knowledge in the field of arch dams to generate an excellent initial population. To assess the relevance of domain knowledge, an investigation was conducted on the accumulated knowledge and empirical formulas from literature. Two pieces of domain knowledge can be gleaned from the iterative structural design experiences associated with arch dams. First, it concerns the thickness of the central cantilever of an arch dam. For minimum tensile stress, it is best to make the thickness as thin as possible at the dam crest and gradually become thicker as it goes down. The second aspect concerns the sliding stability of the arch dam, which depends on the central angle of the horizontal section. This angel is important for stability because the plane arch serves to transfer the hydraulic load from the reservoir to both abutments. Also, preliminary design formulas for arch dams from a manual written by the United States Bureau of Reclamation (USBR) were used. On the other hand, since domain knowledge is based on engineering experiences and data from existing dams, its usability should be verified by comparing it with the results of design optimization performed by classic genetic algorithms. To validate the performance of the optimization algorithm with the improved population initialization technique, a test site with an existing dam was selected, and algorithmic application tests were conducted. Stress analysis is performed for each design iteration, evaluating constraints and calculating fitness as the objective function. The results confirmed that the algorithm developed in this study exhibits superior performance in terms of average fitness and convergence rate compared to classic genetic algorithms.