• Smart Structures and Systems
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• v.16 no.3
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• pp.435-457
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• 2015

The most widely known form of multifunctional aircraft structure is smart structures for structural health monitoring (SHM). The aim is to provide automated systems whose purposes are to identify and to characterize possible damage within structures by using a network of actuators and sensors. Unfortunately, environmental and operational variability render many of the proposed damage detection methods difficult to successfully be applied. In this paper, an original robust damage detection approach using output-only vibration data is proposed. It is based on independent component analysis and matrix perturbation analysis, where an analytical threshold is proposed to get rid of statistical assumptions usually performed in damage detection approach. The effectiveness of the proposed SHM method is demonstrated numerically using finite element simulations and experimentally through a conformal load-bearing antenna structure and composite plates instrumented with piezoelectric ceramic materials.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.604-607
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• 2003

Most recommendation systems recommend the products or other information satisfying preferences of users on the basis of the users' previous profile information and other information related to product searches and purchase of users visiting web sites. This study aims to apply these application categories to e-mail more necessary to users. The E-Mail System has the strong personality so that there will be some problems even if e-mails are automatically classified by category through the learning on the basis of the personal rules. In consideration with this aspect, we need the semi-automatic system enabling both automatic classification and recommendation method to enhance the satisfaction of users. Accordingly, this paper uses two approaches as the solution against the misclassification that the users consider as the accuracy of classification itself using the dynamic threshold in Bayesian Learning Algorithm and the second one is the methodological approach using the recommendation agent enabling the users to make the final decision.

• Journal of Information Technology Services
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• v.14 no.4
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• pp.159-169
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• 2015

Customer reviews are one of the important sources for purchase decision makings in online stores. Online stores have tried to provide useful reviews in product pages to customers. To assess the usefulness of customer reviews before other users have voted enough on the reviews, diverse aspects of reviews were utilized in prevous studies. Style and semantic information were utilized in many studies. This study aims to test diverse alogrithms and datasets for identifying a proper classification method and threshold to classify useful reviews. In particular, most researches utilized ratio type helpfulness index as Amazon.com used. However, there is another type of usefulness index utilized in TripAdviser.com or Yelp.com, count type helpfulness index. There was no proper threshold to classify useful reviews yet for count type helpfulness index. This study used reivews and their usefulness votes on restaurnats from Yelp.com to devise diverse datasets and applied text mining approaches to classify useful reviews. Random Forest, SVM, and GLMNET showed the greater values of accuracy than other approaches.

• Clinical and Experimental Reproductive Medicine
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• v.36 no.4
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• pp.255-263
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• 2009

Objective: The objective of the study was to determine the diagnostic performance of transabdominal ultrasound by receiver operating characteristic (ROC) curve analysis, in order to evaluate the usefulness in establishing the diagnosis of polycystic ovary syndrome (PCOS). Methods: Questionnaires were given to 8,793 reproductive women reviewed at Ewha Womans University Mokdong hospital. Ultrasound examinations were performed in 701 women with a transabdominal transducer. Transabdominal ultrasounds were performed in 185 normal control women (normal menstruation without hyperandrogenism or PCO morphology) and 248 PCOS patients according to National Institutes of Health (NIH) PCOS diagnosis criteria. ROC curves were calculated for ovarian volume and follicle number. Results: In normal control group, the mean age were $23.64{\pm}4.26$ years old and the mean ovarian volume and follicle number were $6.03{\pm}1.89\;cm^3$ and $6.49{\pm}1.93$, respectively. The ovarian volume showed an area under the ROC curve (AURC) of 0.761. A ovarian volume decision threshold >$9\;cm^3$ had a sensitivity of 51.0% and a specificity of 91.4% for the diagnosis of PCOS. The follicle number showed an AURC of 0.733. A follicle number decision threshold ${\geq}9$ had a sensitivity of 54.9% and a specificity of 87.0% for the diagnosis of PCOS. A follicle number decision threshold ${\geq}10$ had a sensitivity of 53.2% and a specificity of 90.4%. A follicle number and a ovarian volume did not have a high diagnostic power for screening for PCOS. Conclusion: Our results suggest that transabdominal ultrasound assessment is not effective for the detection of PCOS in young women of reproductive age.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.4
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• pp.423-429
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• 2011

Cooperative spectrum sensing is proposed to overcome some problem such as multipath fading and shadowing and to improve spectrum sensing performance. There are different combining methods for cooperative spectrum sensing: hard decision method and soft decision method. In this paper, we analysis the performance of cooperative spectrum sensing with distance based weight that is kind of a soft decision rule for cognitive radio(CR) systems and CR systems sense the spectrum of the licensed user by using a energy detection method. Threshold is determined in accordance with the constant false alarm rate(CFAR) algorithm for energy detection. The signal of licensed user is OFDM signal and the wireless channel between a licensed user and CR systems is modeled as Gaussian channel. From the simulation results, the cooperative spectrum sensing with distance based weight combining(DWC) and equal gain combing(EGC) methods shows higher spectrum sensing performance than single spectrum sensing does. And the detection probability performance with the DWC is higher than that with the EGC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.5
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• pp.461-474
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• 2009

The cognitive radio (CR) technique is a useful tool for improving spectrum utilization by detecting and using the vacant spectrum bands in which cooperative spectrum sensing is a key element, while avoiding interfering with the primary user. In this paper, we propose a novel cluster-based cooperative spectrum sensing scheme in cognitive radio with two solutions for the purpose of improving in sensing performance. First, for the cluster header, we use the double adaptive energy thresholds and a multi-bit quantization with different quantization interval for improving the cluster performance. Second, in the common receiver, the weighed HALF-voting rule will be applied to achieve a better combination of all cluster decisions into a global decision.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.3
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• pp.345-356
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• 1995

The aim of this paper is to analyze the batch service queueing model M/M(a, b ; ${\mu}_k/1$) under general bulk service rule with mean service rate ${\mu}_k$ for a batch of k units, where $a{\leq}k{\leq}b$. This queueing model consists of the two-dimensional state space so that it is characterized by two-dimensional state Markov process. The steady-state solution and performane measure of this process are derived by using Matrix Geometric method. Meanwhile, a new approach is suggested to calculate the two-dimensional traffic density R which is used to obtain the steady-state solution. In addition, to determine the optimal service initiation threshold a, a decision model of this queueing system is developed evaluating cost of service per batch and cost of waiting per customer. In a job order production system, the decision-making procedure presented in this paper can be applicable to determining when production should be started.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.268-284
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• 2017

The dorsal hand vein biometric system developed has a main objective and specific targets; to get an electronic signature using a secure signature device. In this paper, we present our signature device with its different aims; respectively: The extraction of the dorsal veins from the images that were acquired through an infrared device. For each identification, we need the representation of the veins in the form of shape descriptors, which are invariant to translation, rotation and scaling; this extracted descriptor vector is the input of the matching step. The optimization decision system settings match the choice of threshold that allows accepting/rejecting a person, and selection of the most relevant descriptors, to minimize both FAR and FRR errors. The final decision for identification based descriptors selected by the PSO hybrid binary give a FAR =0% and FRR=0% as results.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.464-467
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• 1999

Usually, more reference signatures result in better performance in signature verification. However, registering .many signatures may be a tedious work for users, so algorithms that use less signatures for the registration without increasing error rate is needed. In this paper, we find the features such as pen-down duration, the number of locally minimum velocity points, and the number of locally maximum curvature points. Then we find the relationship between these features and the optimal decision boundary. We apply this relationship in deciding threshold for signature verification. Experimental results show that the method using three reference signatures has almost same error rate as algorithms with many references.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.5
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• pp.70-75
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• 2000

After the patterning and probe process of wafer have been achieved, the dicing process is necessary to separate chips from a wafer. The dicing process cuts a wafer to lengthwise and crosswise direction to make many chips by using narrow circular rotating diamond blade. But inferior goods are made under the influence of complex dicing environment such as blade, wafer, cutting water and cutting conditions. This paper describes a monitoring algorithm using feature extraction in order to find out an instant of vibration signal change when bad dicing appears. The algorithm is composed of two steps: feature extraction and decision. In the feature extraction, two features processed from vibration signal which is acquired by accelerometer attached on blade head are proposed. In the decision. a threshold method is adopted to classify the dicing process into normal and abnormal dicing. Experiment have been performed for GaAs semiconductor wafer. Based upon observation of the experimental results, the proposed scheme shown a good accuracy of classification performance by which the inferior goods decreased from 35.2% to 12.8%.