• Journal of the Korea Society for Simulation
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• v.28 no.2
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• pp.97-105
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• 2019

The tactical mobile ad-hoc network(MANET) consists of distributed autonomous networks between individual ground nodes, which is effective in terms of network survivability and flexibility. However, due to constraints such as limited power, terrain, and mobility, frequent link disconnection and shadow area may occur in communication. On the other hand, the satellite network has the advantage of providing a wide-area wireless link overcoming terrain and mobility, but has limited bandwidth and high-latency characteristic. In the future battlefield, an integrated network architecture for interworking multi-layer networks through a heterogeneous network gateway (HNG) is required to overcome the limitations of the existing individual networks and increase reliability and efficiency of communication. In this paper, we propose a new HNG architecture and detailed algorithm that integrates satellite network and the tactical MANET and enables reliable data transfer based on flow characteristics of traffic. The simulations validated the proposed architecture using Riverbed Modeler, a network-level simulator.

• Journal of Engineering Education Research
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• v.21 no.6
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• pp.3-12
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• 2018

The importance of software in the engineering field is increasing day by day, so the utilization and understanding of the simulation software in the engineering design stage has become the core competence of the engineer. This study presents a new software education method for multiple systems in the field of mechanical engineering using a workflow execution environment as a sub-module of a computational platform (called EDISON platform) that can incorporate in-house software tools developed by many simulation tool developers. It can execute not only individual software tools such as fluid flow, structure, optimal design, but also conduct connective executions of multiple software tools. Based on this simulation environment, a methodology was proposed that can be applied to convergence types of engineering educations. By properly using this methodology, it is expected that beginning engineers could encourage their specialties understanding the big pictures of the analysis processes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.121-126
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• 2018

IEEE 802.1 TSN TG is developing standards for end-to-end delay bounds and zero packet loss based on Ethernet technology. We focus on packet forwarding techniques. TSN packet forwarding techniques can be classified into Synchronous and Asynchronous framework. Synchronous approach allocates fixed time period for a class, yet is complex for large networks. Asynchronous approach provides delay guarantee by regulator-scheduler pair, yet is unnecessarily complex, too. We propose network components for TSN Asynchronous architecture, which remove the complexity of maintaining flow state for regulation decisions. Despite such a simplicity, the proposed architecture satisfies the TSN's delay requirements provided the limited high priority traffic's maximum packet length.

• Journal of Convergence for Information Technology
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• v.9 no.7
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• pp.25-32
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• 2019

This paper proposes the method of an in-vehicle gateway to reduce the reprogramming time for the ECU (Electronic Control Unit). In order to reduce the reprogramming time, the gateway must prohibit transmitting messages, that are not related to reprogramming, to the destination CAN network, and no ECU should diagnose the DTC(Diagnostic Trouble Code) that indicates CAN communication error caused by prohibiting CAN messages by the gateway. Moreover, STmin, which are the minimum time between two consecutive CAN messages, should be minimized. In order to do this, this paper proposes the method that uses the link control command specified in UDS(Unified Diagnostic Services) and hardware based gateway functionality that are supported by the latest MCU(Micro Controller Unit). The proposed method is developed using TC275 based embedded system, and its results are presented.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.1-7
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• 2019

Recently, multimedia streaming service has been activated, and the demand for high-quality multimedia convergence contents services is predicted to increase significantly in the future. The issues of the increasing network load due to the rise of multimedia streaming traffic must be addressed in order to provide QoS guaranteed services. To do this, an efficient network resource management and mobility support technologies are needed through seamless mobility support for heterogeneous networks. Therefore, in this paper, an MIH technology was used to recognize the network situation information in advance and reduce packet loss due to handover delays, and an ACLMIH-FHPMIPv6 is designed that can provide an intelligent interface through introducing a hierarchical mobility management technique in FPMIPv6 integrated network.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.813-824
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• 2021

To improve educational performance by analyzing the learning trends of adult learners of Open High Schools, various algorithm models using artificial intelligence were designed and performance was evaluated by applying them to real data. We analyzed Log data of 115 adult learners in the cyber education system of Open High Schools. Most adult learners of Open High Schools learned more than recommended learning time, but at the end of the semester, the actual learning time was significantly reduced compared to the recommended learning time. In the second half of learning, the participation rate of VODs, formation assessments, and learning activities also decreased. Therefore, in order to improve educational performance, learning time should be supported to continue in the second half. In the latter half, we developed an artificial intelligence algorithm models using Tensorflow to predict learning time by data they started taking the course. As a result, when using CNN(Convolutional Neural Network) model to predict single or multiple outputs, the mean-absolute-error is lowest compared to other models.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.699-708
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• 2021

In this paper, a steering control and speed control algorithm was presented for autonomous driving based on two vision sensors and road speed sign board. A car speed control algorithm was developed to recognize the speed sign by using TensorFlow, a deep learning program provided by Google to the road speed sign image provided from vision sensor B, and then let the car follows the recognized speed. At the same time, a steering angle control algorithm that detects lanes by analyzing road images transmitted from vision sensor A in real time, calculates steering angles, controls the front axle through PWM control, and allows the vehicle to track the lane. To verify the effectiveness of the proposed algorithm's steering and speed control algorithms, a car's prototype based on the Python language, Raspberry Pi and OpenCV was made. In addition, accuracy could be confirmed by verifying various scenarios related to steering and speed control on the test produced track.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.12
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• pp.85-94
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• 2018

The purpose of this paper was to propose a model that recognizes potential users' emotional response toward design by classifying Electroencephalography(EEG). Studies in neuroscience and psychology have made an effort to recognize subjects' emotional response by analyzing EEG data. And this approach has been adopted in design since it is critical to monitor users' subjective response in the preface of design. Moreover, the building design process cannot be reversed after construction, recognizing clients' affection toward design alternatives plays important role. An experiment was conducted to record subjects' EEG data while they view their most/least liked images of small-house designs selected by them among the eight given images. After the recording, a subjective questionnaire, PANAS, was distributed to the subjects in order to describe their own affection score in quantitative way. Google TensorFlow was used to build and train the model. Dataset for model training and testing consist of feature columns for recorded EEG data and labels for the questionnaire results. After training and testing, the measured accuracy of the model was 0.975 which was higher than the other machine learning based classification methods. The proposed model may suggest one quantitative way of evaluating design alternatives. In addition, this method may support designer while designing the facilities for people like disabled or children who are not able to express their own feelings toward alternatives.

• Journal of IKEEE
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• v.25 no.2
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• pp.315-321
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• 2021

In this paper, we have developed the multiple channel measurement system for IC Socket Test. The one can test the current-voltage measurements for pitting the several device specification, which analyze the thin current from several ㎂ to 5A with very low resistor mΩ. The increasement of the IC socket channel with lead pitch under 0.25 mm be need to perform several functions, concurrently. The system to perform these functions be designed to integrate several SMU(source measure unit) on board. So, we can reduce the 2 minutes test time per channel point to 40 sec, with daisy chain test method. Using by graphic interface, I-V curve mode and data logging technologies, we can implement the test flow methods and can make economies the time and cost.

• Convergence Security Journal
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• v.20 no.5
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• pp.3-10
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• 2020

Recently, the Internet and networks are regarded as essential infrastructures that constitute society, and security threats have been constantly increased. However, the network switch that actually transmits packets in the network can cope with security threats only through firewall or network access control based on fixed rules, so the effective defense for the security threats is extremely limited in the network itself and not actively responding as well. In this paper, we propose an in-network security framework using the high-level data plane programming language, P4 (Programming Protocol-independent Packet Processor), to deal with DDoS attacks and IP spoofing attacks at the network level by monitoring all flows in the network in real time and processing specific security attack packets at the P4 switch. In addition, by allowing the P4 switch to apply the network user's or administrator's policy through the SDN (Software-Defined Network) controller, various security requirements in the network application environment can be reflected.