• Convergence Security Journal
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• v.14 no.7
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• pp.45-51
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• 2014

The most important point in the QoS management system to ensure the quality of the IoT system design goal is quality measurement system and the quality evaluation system. This research study is a matrix model for the IoT based on key quality measures by diagnosis system structure and function. Developing for the quality metrics measured Internet of Things environment will provide the foundation for the Internet of Things quality measurement/analysis. IoT matrix system for quality evaluation is a method to describe the functional requirements and the quality requirements in a single unified table for quality estimation performed. Comprehensive functional requirements and quality requirements by assessing the association can improve the reliability and usability evaluation. When applying the proposed method IoT quality can be improved while reducing the QoS signaling, the processing, the basis for more efficient quality assurances as a whole.

• The KIPS Transactions:PartA
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• v.8A no.2
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• pp.125-132
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• 2001

IBM developed the MPI-IO, we call it MPI-2, on the General Parallel File System. We designed and implemented various Matrix Multiplication Benchmarks to evaluate its performances. The MPI-IO on the General Parallel File System shows four kinds of data access methods : the non-collective and blocking, the collective and blocking, the non-collective and non-blocking, and the split collective operation. In this paper, we propose benchmarks to measure the IO time and the computation time for the data access methods. We describe not only its implementation but also the performance evaluation results.

• Journal of Engineering Education Research
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• v.21 no.3
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• pp.66-75
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• 2018

This paper is the second part of the January 2018 issue of the Korean Society for Engineering Education, The "Equilibrium and Unbalance Analysis of Taegeuk Pattern DNA Matrix Codes," and is an extension of the paper published in the IoT Section of the 2017 Summer Conference in Jeju. In this paper, we have reviewed the history of what is life, and 5G Mobile communication: with IoT followed by recent research on influenza RNA gene mutation and DNA mutation variants, and the insights of Watson and Crick. Inspired by a single Franklin DNA X-ray diffraction photograph, they received the Nobel Prize for the Nature publication of DNA that has three patterns and regular repeatability. Professor MoonHo Lee has solved the three patterns in Diagonal, Left to Right, and Vertical matrices in a 2x2 matrix[CU; AG] and A = T = U = 30% C = G = 20%. We also proposed DNA Watch. This is the Healthcare IoT, which is seen by the DNA Watch on the wrist, the type of Tai Chi pattern of the body, and is immediately connected to the smartphone and delivered to the doctor.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.11a
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• pp.4-7
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• 2015

In this paper, we propose a matrix completion algorithm for Internet of Things (IoT) localization. The proposed algorithm recovers the Gram matrix of sensors by performing optimization over the Riemannian manifold of fixed-rank positive semidefinite matrices. We compute and show the closed forms of all the differentially geometric components required for applying nonlinear conjugate gradients combined with Armijo line search method. The numerical experiments show that the performance of the proposed algorithm in solving IoT localization is outstanding compared with the state-of-the-art matrix completion algorithms both in noise and noiseless scenarios.

• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.580-591
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• 2019

This paper focuses on to improving object detection performance using the camera and LiDAR on autonomous vehicle platforms by fusing detected objects from individual sensors through a late fusion approach. In the case of object detection using camera sensor, YOLOv3 model was employed as a one-stage detection process. Furthermore, the distance estimation of the detected objects is based on the formulations of Perspective matrix. On the other hand, the object detection using LiDAR is based on K-means clustering method. The camera and LiDAR calibration was carried out by PnP-Ransac in order to calculate the rotation and translation matrix between two sensors. For Sensor fusion, intersection over union(IoU) on the image plane with respective to the distance and angle on world coordinate were estimated. Additionally, all the three attributes i.e; IoU, distance and angle were fused using logistic regression. The performance evaluation in the sensor fusion scenario has shown an effective 5% improvement in object detection performance compared to the usage of single sensor.

• Journal of Computing Science and Engineering
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• v.11 no.3
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• pp.100-108
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• 2017

In the field of Internet of Things (IoT), smarter embedded devices offer functions via web services. The Quality-of-Service (QoS) prediction is a key measure that guarantees successful IoT service applications. In this study, a collaborative filtering method is presented for predicting response time of IoT service due to time-awareness characteristics of IoT. First, a calculation method of service response time similarity between different users is proposed. Then, to improve prediction accuracy, initial similarity values are adjusted and similar neighbors are selected by a similarity threshold. Finally, via a densified user-item matrix, service response time is predicted by collaborative filtering for current active users. The presented method is validated by experiments on a real web service QoS dataset. Experimental results indicate that better prediction accuracy can be achieved with the presented method.

• Journal of IKEEE
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• v.24 no.4
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• pp.1180-1183
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• 2020

Recently, the daily life safety detection functionalities such as fall accident detection and burn danger detection are widely disseminated along with the development of IoT and smart home. These safety detection functionalities are mostly performed by artificial intelligence. However, simple accuracy measurement of the safety detection in laboratory environment is often far from practical performance in daily life environment. To mitigate this problem, this paper introduces two techniques, i.e. living lab and confusion matrix. Living lab is more than simple simulation of daily life environment, and it enables users to directly participate technology development and product design. Various performance measures induced from confusion matrix significantly help to evaluate the performance of artificial intelligence system for proper application purposes.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.243-248
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• 2021

Although many different types of covert channels have been suggested in the literature, there are little work in directly applying game theory to building up covert channel. This is because researchers have mainly focused on tailoring game theory for covert channel analysis, identification, and covert channel problem solving. Unlike typical adaptation of game theory to covert channel, we show that game theory can be utilized to establish a new type of covert channel in IoT devices. More specifically, we propose a covert channel that can be constructed by utilizing the Nash Equilibrium with sensor data collected from IoT devices. For covert channel construction, we set random seed to the value of sensor data and make payoff from random number created by running pseudo random number generator with the configured random seed. We generate I × J (I ≥ 2, J ≥ 2) matrix game with these generated payoffs and attempt to obtain the Nash Equilibrium. Covert channel construction method is distinctly determined in accordance with whether or not to acquire the Nash Equilibrium.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.65-71
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• 2017

Since existing Internet of Things(IoT) is vulnerable, it may cause property damage due to the information leakage. Especially, the smart door lock system built on the IoT can cause more damage. To solve these problems, this paper classify the data generated by the sensor according to the condition and send an alarm message to the user's smartphone through Google Cloud Message (GCM). We made it possible to check the images in real time through the smartphone application and control the door lock using the TCP / IP protocol. Also, we applied OTP-Based Matrix SEED algorithm to door lock system to improve security.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.766-772
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• 2016

Recent advances in networking and computers, especially internet of things (IoT) technologies, have improved the quality of home life and industrial sites. However, the security vulnerability of IoT technologies causes life-threatening issues and information leakage concerns. Studies regarding security algorithms are being conducted. In this paper, we proposed SEED algorithms based on one time passwords (OTPs). The specified server sent time data to the client every 10 seconds. The client changed the security key using time data and generated a ciphertext by combining the changed security key and the matrix. We applied the SEED algorithms with enhanced security to Linux-based embedded boards and android smart phones, then conducted a door lock control experiment (door lock & unlock). In this process, the power consumed for decryption was measured. The power consumption of the OTP-based algorithm was measured as 0.405-0.465W. The OTP-based algorithm didn't show any difference from the existing SEED algorithms, but showed a better performance than the existing algorithms.