• 한국산학기술학회논문지
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• 제20권9호
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• pp.198-203
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• 2019

본 논문에서는 모든 지식산업분야에서 기록 및 발췌된 자료들을 모아 보관이 용이하도록 도서 제본을 목적으로 하는 최적의 모터 제어 및 겉표지 자동 투입 기능을 적용한 접착식 무선 제본기를 설계하고자 한다. 접착식 무선 제본기의 소음 개선을 위해 기기의 동력을 기존 컴프레셔 방식에서 AC 인덕션 모터 제어 방식으로 변경하였으며 작업 속도향상을 위해 겉표지 자동 투입 기능을 적용하였다. 또한, 모터 제어 시 가장 큰 문제점인 모터의 정 역회전 중에 발생하는 급제동과 급가속 반복으로 인한 모터 및 감속기 파손 현상을 방지하기 위해 완충식 공간 위치 제어 시스템을 구현하여 모터의 안정적 동작과 내구성을 보장하였다. 이 외에도 제본기 간소화를 위해 복잡한 내부 구조를 단순화하고 부피와 무게를 감소시켰다. 따라서, 본 기기 설계 후 실험값을 측정 한 결과 소음은 기존 135dB에서 71.7dB로 약 57% 감소되었으며 작업 시간은 기존 18sec에서 9.58sec로 약 57% 단축되었다. 그리고 겉표지 자동 투입구는 1회 공급 시 최대 130매까지 공급이 가능하도록 설계하였다.

• Smart Structures and Systems
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• 제31권4호
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• pp.335-349
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• 2023

Bridges constantly undergo deterioration and damage, the most common ones being concrete damage and exposed rebar. Periodic inspection of bridges to identify damages can aid in their quick remediation. Likewise, identifying components can provide context for damage assessment and help gauge a bridge's state of interaction with its surroundings. Current inspection techniques rely on manual site visits, which can be time-consuming and costly. More recently, robotic inspection assisted by autonomous data analytics based on Computer Vision (CV) and Artificial Intelligence (AI) has been viewed as a suitable alternative to manual inspection because of its efficiency and accuracy. To aid research in this avenue, this study performs a comparative assessment of different architectures, loss functions, and ensembling strategies for the autonomous segmentation of bridge components and damages. The experiments lead to several interesting discoveries. Nested Reg-UNet architecture is found to outperform five other state-of-the-art architectures in both damage and component segmentation tasks. The architecture is built by combining a Nested UNet style dense configuration with a pretrained RegNet encoder. In terms of the mean Intersection over Union (mIoU) metric, the Nested Reg-UNet architecture provides an improvement of 2.86% on the damage segmentation task and 1.66% on the component segmentation task compared to the state-of-the-art UNet architecture. Furthermore, it is demonstrated that incorporating the Lovasz-Softmax loss function to counter class imbalance can boost performance by 3.44% in the component segmentation task over the most employed alternative, weighted Cross Entropy (wCE). Finally, weighted softmax ensembling is found to be quite effective when used synchronously with the Nested Reg-UNet architecture by providing mIoU improvement of 0.74% in the component segmentation task and 1.14% in the damage segmentation task over a single-architecture baseline. Overall, the best mIoU of 92.50% for the component segmentation task and 84.19% for the damage segmentation task validate the feasibility of these techniques for autonomous bridge component and damage segmentation using RGB images.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.95-100
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• 2023

Due to Traffic accidents people faces health and economical casualties around the world. As the population increases vehicles on road increase which leads to congestion in cities. Congestion can lead to increasing accident risks due to the expansion in transportation systems. Modern cities are adopting various technologies to minimize traffic accidents by predicting mathematically. Traffic accidents cause economical casualties and potential death. Therefore, to ensure people's safety, the concept of the smart city makes sense. In a smart city, traffic accident factors like road condition, light condition, weather condition etcetera are important to consider to predict traffic accident severity. Several machine learning models can significantly be employed to determine and predict traffic accident severity. This research paper illustrated the performance of a hybridized neural network and compared it with other machine learning models in order to measure the accuracy of predicting traffic accident severity. Dataset of city Leeds, UK is being used to train and test the model. Then the results are being compared with each other. Particle Swarm optimization with artificial neural network (PSO-ANN) gave promising results compared to other machine learning models like Random Forest, Naïve Bayes, Nearest Centroid, K Nearest Neighbor Classification. PSO- ANN model can be adopted in the transportation system to counter traffic accident issues. The nearest centroid model gave the lowest accuracy score whereas PSO-ANN gave the highest accuracy score. All the test results and findings obtained in our study can provide valuable information on reducing traffic accidents.

• 제어로봇시스템학회논문지
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• 제21권6호
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• pp.547-552
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• 2015

In this paper, an ARS-EKF based motion counting algorithm for repetitive exercises such as calisthenics is proposed using a smartwatch. Raw sensor signals from accelerometers and gyroscopes are widely used for conventional smartwatch counting algorithms based on pattern recognition. However, generated features from raw data are not intuitive to reflect the movement of motions. The proposed motion counter algorithm is composed of navigation based feature generation and counting with error correction. The candidate features for each activity are velocity and attitude calculated through an ARS-EKF algorithm. In order to select those features which reveal the characteristics of each motion, an exercise frame from the initial sensor frame is introduced. Counting processes are basically based on the zero crossing method, and misdetected counts are eliminated via simple classification algorithms considering the frequency of the counted motions. Experimental results show that the proposed algorithm efficiently and accurately counts the number of exercises.

• Smart Structures and Systems
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• 제25권2호
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• pp.229-240
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• 2020

In this research, toggled actuator forces were examined. For achieving to this object, an actuator was installed in a toggle pattern in a S.D.O.F frame and actuator forces were investigated thru a numerical analysis process. Within past twenty years, researchers tried to use strong bracing systems as well as huge dampers to stabilize tall buildings during intensive earthquakes. Eventually, utilizing of active control systems containing actuators to counter massive excitations in structures was emerged. However, the more powerful earthquake excitations, the more robust actuators were required to be installed in the system. Subsequently, the latter process made disadvantage to the active control system due to very high price of the robust actuators as well as their large demands for electricity. Therefore, through a numerical process (Part I), influence of toggled actuator pattern was investigated. The algorithm used in the system was LQR and ATmega328 was selected as a control platform. For comparison, active tendon control system was chosen. The final results show clearly that using the toggle pattern mitigates the required actuator forces enormously leading to deploy much lighter actuators.

• 통상정보연구
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• 제12권2호
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• pp.133-158
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• 2010

Since 11 September 2001, the awareness of terrorists' actions has clearly risen. The potential threat of terrorists using containers poses a large risk to our economies and to our societies. In order to protect cargo from damage and terrorist threats, business and government turn to RFID and IC tags, and tradition container is replaced by IC smart container. In this study, presented application of IC tag and future tasks to Container transport by sea in viewpoint of security strengthening. First, realization and international SCM realization structural order that cover container supply chain whole of international standardization and association between industry are certainly needed. Second, it may have to try in technical development for IC tag Ratio that can read elevation moment develop suitable IC tag or reader in International Standard. Third, Need to establish concrete use policy as soon as possible in national dimension at the same time effort for international standard normalization of frequency. Finally, it shows to uses jointly with electron sealing and must solve problem about usable plan and information leak.

• Tribology and Lubricants
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• 제33권4호
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• pp.148-152
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• 2017

The feel of writing is important to customers when they buy smart devices with stylus such as smartphones and tablet computers. With an aim to reproduce the tactile sensibility of writing instruments when people write on the glass display using a stylus, this study focuses on the frequency characteristics of writing instruments that can describe the vibrations of writing instruments sliding over counter surfaces. In addition, this study includes the effect of various factors influencing the friction of writing instruments such as lubricant, nib material, and contact type. We perform sliding experiments with six types of writing instruments and a sheet of paper to understand the relation between the friction conditions of the nib and the frequency characteristics. As this research focuses on the tactile perception of human skin when people use a writing instrument, the analysis of frequency characteristics is performed in the perceptible frequency range of mechanoreceptors in the human skin. As a result, three types of frequency characteristics are identified. Low frequency peaks are observed for a metal nib with ink; high frequency peaks are observed for a nib without ink; and, middle frequency peaks with a wide range of distribution occurs for fabric nibs with ink. Therefore, to implement the proper feel of writing, at least three types of vibrations have to be made.

• Journal of Computing Science and Engineering
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• 제7권3호
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• pp.187-197
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• 2013

Security has long been a challenging problem in wireless networks, mainly due to its broadcast nature of communication. This opens up simple yet effective measures to thwart useful communications between legitimate radios. Spread spectrum technologies, such as direct sequence spread spectrum (DSSS), have been developed as effective countermeasures against, for example, jamming attacks. This paper surveys previous research on securing a DSSS channel even further, using physical layer attributes-keyless DSSS mechanisms, and watermarked DSSS (WDSSS) schemes. The former has been motivated by the fact that it is still an open question to establish and share the secret spread sequence between the transmitter and the receiver without being noticed by adversaries. The basic idea of the latter is to exploit the redundancy inherent in DSSS's spreading process to embed watermark information. It can be considered a counter measure (authentication) for an intelligent attacker who obtains the spread sequence to generate fake messages. This paper also presents and evaluates an adaptive DSSS scheme that takes both jam resistance and communication efficiency into account.

• 정보처리학회논문지C
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• 제11C권3호
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• pp.287-292
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• 2004

브랜드의 카운터 방식 전자화폐 알고리즘(BOCC)은 이동 환경에 적절하지만, 스마트 카드내 금액정보를 공격할 수 있다. 따라서 토큰 데이터에 지불 한계 금액을 삽입함으로써 상한금액을 넘어서 사용하지 못하도록 하고, 상한과 하한 값을 같게 하면 고정금액 토큰이 된다. 또한 온라인 거래에서 더욱 빈번히 발생 가능한 환불성을 추가한다. 기존의 BOCC는 이산대수문제(Discrete Logarithm Problem)에 근거하기 때문에 지수 승을 반복해서 수행하여야 한다. 그런데 제한된 계산 능력을 가진 이동단말의 경우는 계산량을 줄여야 한다. 따라서 타원곡선 알고리즘(ECC)을 적용함으로써 기능은 동일하나 계산량 감소를 얻을 수 있다

• International Journal of Advanced Culture Technology
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• 제10권1호
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• pp.230-235
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• 2022

This study is to select an optimal object detection algorithm for designing a self-checkout counter to improve the inconvenience of payment systems for products without existing barcodes. To this end, a performance comparison analysis of YOLO v2, Tiny YOLO v2, and the latest YOLO v5 among deep learning-based object detection algorithms was performed to derive results. In this paper, performance comparison was conducted by forming learning data as an example of 'donut' in a bakery store, and the performance result of YOLO v5 was the highest at 96.9% of mAP. Therefore, YOLO v5 was selected as the artificial intelligence object detection algorithm to be applied in this paper. As a result of performance analysis, when the optimal threshold was set for each donut, the precision and reproduction rate of all donuts exceeded 0.85, and the majority of donuts showed excellent recognition performance of 0.90 or more. We expect that the results of this paper will be helpful as the fundamental data for the development of an automatic payment system using AI self-service technology that is highly usable in the non-face-to-face era.