• Journal of Digital Convergence
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• v.19 no.9
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• pp.257-269
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• 2021

The purpose of this study is to collect biosignal data in a non-invasive and non-restrictive manner using a BCG (Ballistocardiogram) sensor, and utilize artificial intelligence machine learning algorithms in ICT and high-performance computing environments. And it is to present and study a method for developing and validating a data-based blood glucose prediction model. In the blood glucose level prediction model, the input nodes in the MLP architecture are data of heart rate, respiration rate, stroke volume, heart rate variability, SDNN, RMSSD, PNN50, age, and gender, and the hidden layer 7 were used. As a result of the experiment, the average MSE, MAE, and RMSE values of the learning data tested 5 times were 0.5226, 0.6328, and 0.7692, respectively, and the average values of the validation data were 0.5408, 0.6776, and 0.7968, respectively, and the coefficient of determination (R²) was 0.9997. If research to standardize a model for predicting blood sugar levels based on data and to verify data set collection and prediction accuracy continues, it is expected that it can be used for non-invasive blood sugar level management.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.940-945
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• 2021

Future network architectures such as Named Data Networking (NDN) were born to change the way data can be transmitted from current host-centric network technologies to information-centric network technologies. Recently, many studies are being conducted to graft Vehicular NDN to the communication network technology of smart vehicles including connected vehicles. Explosion of data traffic due to Interest/Data packet broadcasting in Vehicular NDN environment is a very important problem to be solved in order to realize VNDN-based data communication. In this paper, the generation of data packet copies according to the increase in network size, vehicle speed, and frequency of interest packets in VNDN network is simulated and evaluated using ndnSIM, in order to show how severe the data broadcast storm phenomenon. The CDP(Copies of Data Packets) increased proportionally in the increase of network size or Interest frequency.

• Smart Media Journal
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• v.7 no.4
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• pp.30-36
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• 2018

Single domain model like DataLake framework is in spotlight because it can improve data efficiency and process data smarter in big data environment, where large scaled business system generates huge amount of data. In particular, efficient operation of network, storage, and computing resources in logical single domain model is very important for physically partitioned multi-site data process. Based on the advantages of Data Lake framework, we define and extend the concept of Connected Data Architecture and functions of DataLake framework for integrating multiple sites in various domains and managing the lifecycle of data. Also, we propose the design of CDA-based AI service and utilization scenarios in various application domain.

• Journal of Advanced Navigation Technology
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• v.23 no.4
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• pp.328-332
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• 2019

Advances in web technology have enabled technical convergence in various system environments to be carried out through the web interface. The Web can be categorized from the Web 1.0 to the 4.0, depending on its role, it has the characteristics of connects information, connects people, connects knowledge, and connects intelligence. In addition, various technological needs occurred through the mobile app during the 4th Industrial Revolution, and functions such as 3D, virtual reality, augmented reality, video/audio processing were enabled on the web, which was a simple means of providing information. Technical standards have been studied to support these period needs. In this paper, I would like to mention one of the Web assembly. We will explore ways to link and fuse Web assembly with existing web systems (or platforms) and analyze their technical implications through a variety of examples. In addition, we will conduct a study on the architecture that can fuse the existing javascript with the web assembly, and discuss the future direction of the study.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.219-224
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• 2021

The convergence of various industries has removed the boundaries of software application fields and reduced the restrictions on convergence fields. Software requirements are diversified and they want to reconfigure software requirements in a fast cycle. Since various changes in requirements have to be accepted technically, research on methodologies and standards to increase the efficiency of software productivity and methods for standardizing and producing software are needed. In this study, we studied how the reusability and complexity of the software asset reconfiguration system appeared according to the developer's characteristics and environment to utilize the assets optimized in previous studies. At this time, we measured how the change in complexity according to the usability and asset composition method that appears according to the developer's characteristics appears, but there is a limit to the collected data, so it is necessary to secure the quality of the measured value through continuous data collection. In addition, an intelligent system application plan is needed to supplement the problem of context classification in the use stage of complex assets.

• Journal of Platform Technology
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• v.9 no.3
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• pp.70-77
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• 2021

The purpose of Serious games in immersive Metaverse platform to provide users both fun and intriguing learning experiences. We proposes a serious game for self-trainable fire evacuation drill with collaboration among avatars synchronized with multiple trainees and optionally with real-time supervising placed at different remote physical locations. The proposed system architecture is composed of wearable motion sensors and a Head Mounted Display to synchronize each user's intended motions to her/his avatar activities in a cyberspace in Metaverse environment. The proposed system provides immersive as well as inexpensive environments for easy-to-use user interface for cyber experience-based fire evacuation training system. The proposed configuration of the user-avatar interface, the collaborative learning environment, and the evaluation system on the VR serious game are expected to be applied to other serious games. The game was implemented only for the predefined fire scenario for buildings, but the platform can extend its configuration for various disaster situations that may happen to the public.

• Journal of the Korea Society of Computer and Information
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• v.26 no.2
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• pp.79-88
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• 2021

In this paper, we propose a API Gateway technique for the expansion of human resource management module, one of the ERP functions. The institution has introduced ERP (Enterprise Resource Planning) based on its efforts to transform all human and physical resources into business competitiveness and its response to the digital knowledge informatization environment, and listed it as multiple success factors. Human resource management is one of the factors that have been dealt with. However, ERP's Human Resources Management Module remains in the role of functional personnel management. How to utilize human resources begins with navigating and recognizing human resources. The proposed API Gateway technique leverages blockchain networks to design and implement APIs for human resource sharing and navigation, including the possibility of extending ERP's human resource management module. Secondly, it was designed and implemented using a smart contract that behaves like an API for preventing information forgery. The proposed method will not only be used as a tool that can actively utilize human resources, but will also be a complete resource for utilizing big data technology.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.81-93
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• 2022

Recently, there have been many studies on object recognition around the vehicle and recognition of traffic signs and traffic lights in autonomous driving. In particular, such the recognition of traffic lights is one of the core technologies in autonomous driving. Therefore, many studies for such the recognition of traffic lights have been performed, the studies based on various deep learning models have increased significantly in recent. In addition, as a high-quality AI training data set for voice, vision, and autonomous driving is released on AIHub, it makes it possible to develop a recognition model for traffic lights suitable for the domestic environment using the data set. In this study, we developed a recognition model for traffic lights that can be used in Korea using the AIHub's training data set. In particular, in order to improve the recognition performance, we used various models of YOLOv4 and YOLOv5, and performed our recognition experiments by defining various classes for the training data. In conclusion, we could see that YOLOv5 shows better performance in the recognition than YOLOv4 and could confirm the reason from the architecture comparison of the two models.

• Smart Media Journal
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• v.12 no.4
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• pp.19-26
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• 2023

IoT edge services utilizing neuromorphic hardware architectures are suitable for autonomous IoT applications as they perform intelligent processing on the device itself. However, spiking neural networks applied to neuromorphic hardware are difficult for IoT developers to comprehend due to their complex structures and various hyper-parameters. In this paper, we propose a method for generating spiking neural network (SNN) models that satisfy user performance requirements while considering the constraints of neuromorphic hardware. Our proposed method utilizes previously trained models from pre-processed data to find optimal SNN model parameters from profiling data. Comparing our method to a naive search method, both methods satisfy user requirements, but our proposed method shows better performance in terms of runtime. Additionally, even if the constraints of new hardware are not clearly known, the proposed method can provide high scalability by utilizing the profiled data of the hardware.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.145-151
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• 2009

There are excessively hot units of a microprocessor in today's nano-scale process technology, which are called hotspots. Hotspots' heat dissipation is not perfectly conquered by mechanical cooling techniques such as heatsink, heat spreader, and fans; Hence, an architecture-level temperature simulation of microprocessors is evident experiment so that designers can make reliable chips in high temperature environments. However, conventional thermal simulators cannot be used in temperature evaluation of real machine, since they are too slow, or too coarse-grained to estimate overall system models. This paper proposes methodology of monitoring accurate runtime temperature with Hotspot[4], and introduces its implementation. With this tool, it is available to track runtime thermal behavior of a microprocessor at architecture-level. Therefore, Dynamic Thermal Management such as Dynamic Voltage and Frequency Scaling technique can be verified in the real system.