• Journal of Communications and Networks
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• 제18권1호
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• pp.27-39
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• 2016

This paper derives and analyzes a novel block fast Fourier transform (FFT) based joint detection algorithm. The paper compares the performance and complexity of the novel block-FFT based joint detector to that of the Cholesky based joint detector and single user detection algorithms. The novel algorithm can operate at chip rate sampling, as well as higher sampling rates. For the performance/complexity analysis, the time division duplex (TDD) mode of a wideband code division multiplex access (WCDMA) is considered. The results indicate that the performance of the fast FFT based joint detector is comparable to that of the Cholesky based joint detector, and much superior to that of single user detection algorithms. On the other hand, the complexity of the fast FFT based joint detector is significantly lower than that of the Cholesky based joint detector and less than that of the single user detection algorithms. For the Cholesky based joint detector, the approximate Cholesky decomposition is applied. Moreover, the novel method can also be applied to any generic multiple-input-multiple-output (MIMO) system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 C
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• pp.1907-1909
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• 1996

In this paper, ultrsonic detection properties at a premolde joint utilized in a 23kV cables are studied. In a experiment a artificial defect within a joint and a measuring system are builded for generating discharges, gathering data about a detection properties, respectively. The experiment results show that one point detection is not allowed for monitoring a global status of a joint discharges and a detection sensitivity is less than 100pC. And also the attenuation and wave speed at the material of joint insulator are obtained.

• Architectural research
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• 제13권4호
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• pp.53-60
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• 2011

Damage detection algorithms based on a one-dimensional beam model can detect damage within a beam span caused by flexure only but cannot detect damage at a joint with prescribed boundary conditions or at the middle part of a beam section where the neutral axis is located. Considering the damage at a welded joint of beam elements in steel structures and modeling the damage with twodimensional plane elements, this study presents a new approach to detecting damage in the depth direction of the joint and beam section. Three damage scenarios at the upper, middle, and lower parts of a welded joint of a rectangular symmetric section are investigated. The damage is detected by evaluating the difference in the receptance magnitude between the undamaged and damaged states. This study also investigates the effect of measurement locations and noise on the capability of the method in detecting damage. The numerical results show the validity of the proposed method in detecting damage at the beam's welded joint.

• Wind and Structures
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• 제21권6호
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• pp.709-726
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• 2015

In this study, a novel vision-based bolt-loosening monitoring technique is proposed for bolted joints connecting tubular steel segments of the wind turbine tower (WTT) structure. Firstly, a bolt-loosening detection algorithm based on image processing techniques is developed. The algorithm consists of five steps: image acquisition, segmentation of each nut, line detection of each nut, nut angle estimation, and bolt-loosening detection. Secondly, experimental tests are conducted on a lab-scale bolted joint model under various bolt-loosening scenarios. The bolted joint model, which is consisted of a ring flange and 32 sets of bolt and nut, is used for simulating the real bolted joint connecting steel tower segments in the WTT. Finally, the feasibility of the proposed vision-based technique is evaluated by bolt-loosening monitoring in the lab-scale bolted joint model.

• 한국정보통신학회논문지
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• 제10권1호
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• pp.42-48
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• 2006

본 논문에서는 차세대 복합 시분할 부호분할 다중접속 이동통신 시스템에서 타 셀 사용자 간섭 제거를 위한 결합검출 방안을 제안한다. 결합검출 기술은 차세대 복합 시분할 부호분할 다중접속 이동통신 시스템 TD-CDMA 시스템에서의 가장 큰 특징이라 할 수 있는 기술로서 셀 내의 서로 다른 사용자의 신호 간섭을 제거하여 동시에 사용자 데이터를 복원할 수 있다. 종래의 연구에서는 2단계 결합 검출 방식을 이용하여 목적 셀의 사용자 간섭 뿐 아니라 타 셀 간섭을 제거해 줄 수 있는 방안이 제안되었으나 이 방안에서는 타 셀 간섭 제거를 위한 구체적인 사용자 인식에 대한 방안이 없다. 따라서 주변 타 셀 내의 사용자의 간섭의 크기에 상관없이 모든 사용자에 대하여 결합검출을 수행해야 하며 2단계 결합검출의 복잡도가 매우 높다. 본 논문에서는 타 셀 사용자의 간섭의 크기에 따라서 선택적으로 2단계 결합 검출을 수행하는 방안을 제안한다. 제안된 방식은 모의실험을 통하여 성능을 조사하였으며 종래의 결합검출 방식에 비하여 성능의 열화가 없는 동시에 2 단계 결합검출의 복잡도를 크게 줄일 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권1호
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• pp.395-405
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• 2012

A joint template matching algorithm is proposed in this paper to reduce the high rate of miss-detection and false-alarm caused by the traditional template matching algorithm during the process of multi-object detection. The proposed algorithm can reduce the influence on each object by matching all objects together according to the correlation information among different objects. Moreover, the rate of miss-detection and false-alarm in the process of single-template matching is also reduced based on the algorithm. In this paper, firstly, joint template is created from the information of relative positions among different objects. Then, matching criterion according to normalized cross correlation is generated for multi-object matching. Finally, the proposed algorithm is applied to the detection of watermarks in bill. The experiments show that the proposed algorithm has lower miss-detection and false-alarm rate comparing to the traditional NCC algorithm during the process of multi-object detection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권9호
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• pp.4658-4679
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• 2017

Android is now the most popular smartphone platform and remains rapid growth. There are huge number of sensitive privacy information stored in Android devices. Kinds of methods have been proposed to detect Android malicious applications and protect the privacy information. In this work, we focus on extracting the fine-grained features to maximize the information of Android malware detection, and selecting the least joint features to minimize the number of features. Firstly, permissions and APIs, not only from Android permissions and SDK APIs but also from the developer-defined permissions and third-party library APIs, are extracted as features from the decompiled source codes. Secondly, feature selection methods, including information gain (IG), regularization and particle swarm optimization (PSO) algorithms, are used to analyze and utilize the correlation between the features to eliminate the redundant data, reduce the feature dimension and mine the useful joint features. Furthermore, regularization and PSO are integrated to create a new joint feature mining method. Experiment results show that the joint feature mining method can utilize the advantages of regularization and PSO, and ensure good performance and efficiency for Android malware detection.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.513-518
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• 1998

In this paper, a robust fault-tolerant control scheme for robot manipulators overcoming actuator failures is presented. The joint(or actuator) fault considered in this paper is the free-swinging joint failure and causes the loss of torque on a joint. The presented fault-tolerant control framework includes a normal control with normal(non-failed) operation, a fault detection and a fault-tolerant control to achieve task completion. For both no uncertainty case and uncertainty case, a stable normal con-troller and an on-line fault detection scheme are presented. After the detection and identification of joint failures, the robot manipulator becomes the underactuated robot system with failed actuators. A robust adaptive control scheme of robot manipulators with the detected failed-actuators using the brakes equipped at the failed(passive) joints is proposed in the presence of parametric uncertainty and external disturbances. To illustrate the feasibility and validity of the proposed fault-tolerant control scheme, simulation results for a three-link planar robot arm with a failed joint are presented.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.871-876
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• 2022

In the construction industry, fatal accidents related to scaffolds frequently occur. To prevent such accidents, scaffolds should be carefully monitored for their safety status. However, manual observation of scaffolds is time-consuming and labor-intensive. This paper proposes a method that automatically analyzes the installation status of scaffold joints based on images acquired from a Unmanned Aerial Vehicle (UAV). Using a deep learning-based object detection algorithm (YOLOv5), scaffold joints and joint components are detected. Based on the detection result, a two-stage rule-based classifier is used to analyze the joint installation status. Experimental results show that joints can be classified as safe or unsafe with 98.2 % and 85.7 % F1-scores, respectively. These results indicate that the proposed method can effectively analyze the joint installation status in UAV-acquired scaffold images.

• 한국멀티미디어학회논문지
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• 제15권5호
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• pp.606-614
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• 2012

AdaBoost 알고리즘을 이용한 얼굴 검출 방법은 가장 빠르고 신뢰성 있는 얼굴 검출 알고리즘의 하나로 이를 향상하거나 확장한 많은 알고리즘들이 제안되었다. 그러나 이전의 접근들은 대부분 정면 얼굴만을 다루고 있고 AdaBoot 알고리즘을 정면과 기울어진 얼굴에 동일한 특징으로 적용함으로써 기울어진 얼굴에 대한 분별 성능이 제한적이었다. 또한 회전된 얼굴을 검출하기 위하여 입력된 영상을 회전하여 정면 얼굴 검출 방법을 적용하거나 회전된 각도에 따라 다른 검출기를 적용하는 기존 기법들은 연산량이 많고 검출률이 저하되는 문제를 가지고 있다. 본 논문에서는 이러한 문제를 극복하기 위해 JointBoost를 이용한 기울어진 얼굴 검출 방법을 제안한다. JointBoost를 통해 클래스간의 공유된 feature들를 찾음으로써 연산량과 샘플 복잡도를 감소시켰다. 실험 결과를 통해 제안된 방법의 검출률이 동일한 반복 횟수를 가지는 학습에서 기존의 AdaBoost 기법에 비해 2% 이상 우수함을 보인다. 또한 제안된 방법은 얼굴의 존재를 검출할 뿐만 아니라 기울어진 방향에 대한 정보도 제공할 수 있다.