• KIPS Transactions on Software and Data Engineering
• /
• v.7 no.3
• /
• pp.91-98
• /
• 2018

Automatic detection of pig wasting diseases is an important issue in the management of group-housed pigs. In particular, porcine respiratory diseases are one of the main causes of mortality among pigs and loss of productivity in intensive pig farming. In this paper, we propose a noise-robust system for the early detection and recognition of pig wasting diseases using sound data. In this method, first we convert one-dimensional sound signals to two-dimensional gray-level images by normalization, and extract texture images by means of dominant neighborhood structure technique. Lastly, the texture features are then used as inputs of convolutional neural networks as an early anomaly detector and a respiratory disease classifier. Our experimental results show that this new method can be used to detect pig wasting diseases both economically (low-cost sound sensor) and accurately (over 96% accuracy) even under noise-environmental conditions, either as a standalone solution or to complement known methods to obtain a more accurate solution.

• Journal of Satellite, Information and Communications
• /
• v.2 no.2
• /
• pp.53-58
• /
• 2007

The Satellite Mobile Communication System holds several advantages, such as wide coverage that guarantees the communication in a huge area. It is suitable in the ocean and forest and especially in emergency situation. However, the licensed frequency is not always occupied within all coverage and all the time. The actual utilization rate is relatively low compared to other wireless communications such as cellular systems. There are a large amount of white spaces in its coverage. Therefore, it is necessary to consider introducing additional services such as data communication, in order to increase the spectrum utilization as well as the revenue of the Satellite service provider. In this paper, we first analyze the possibility to implement new services in the licensed band of satellite mobile phone by its provider. Then we address the most significant issue for the implementation of current service, which is how to accurately detect the satellite mobile terminals. Finally, we suggest two new possible solutions namely, eigenvalue detection based methods to find out the existence of transmitted signal from the satellite mobile terminals.

• KIPS Transactions on Software and Data Engineering
• /
• v.5 no.8
• /
• pp.369-376
• /
• 2016

Among various vehicle extraction techniques, OBPCA (Object-Based Point Cloud Analysis) calculates features quickly by coarse-grained rectangles from top-view of the vehicle candidates. However, it uses only a top-view rectangle to detect a vehicle. Thus, it is hard to extract rectangular objects with similar size. For this reason, accuracy issue has raised on the OBPCA method which influences on DEM generation and traffic monitoring tasks. In this paper, we propose a novel method which uses the most distinguishing vertical elevations to calculate additional features. Our proposed method uses same features with top-view, determines new thresholds, and decides whether the candidate is vehicle or not. We compared the accuracy and execution time between original OBPCA and the proposed one. The experiment result shows that our method produces 6.61% increase of precision and 13.96% decrease of false positive rate despite with marginal increase of execution time. We can see that the proposed method can reduce misclassification.

• Journal of the Korea Society of Computer and Information
• /
• v.3 no.3
• /
• pp.17-22
• /
• 1998

As time goes on, that becomes an issue still more for truth from error of a seal in electronic settlement , or in important document in the field of image recognition. But on the other hand image treatment method of a seal have has the weakness until now. It makes indistinct distinction of part that light and darkness is changed sharply as the edge of things. So it has difficult that edge detection is extracted. In this paper, I investigated the pixel in a specific area by using enhanced smothing method and searched a value of frquent occurrence. The value of pixel is substituted and edge detection is extracted. After then it could be classified rightly according as viligence test is dynamically changed. I applied conventional of Yager's generated intersection operator among fuzzy logic operator in ART1 learning Algorithm. Application of suggested ART1 learning algorithm, it results in improved image recognition rate than a case of using the conventional ART1 algorithm

• KIEAE Journal
• /
• v.7 no.4
• /
• pp.147-152
• /
• 2007

Numerous non-destructive tests(NDT) to assess the safety of real structures have been developed. System identification(SI) techniques using dynamic responses and behaviors of structural systems become an outstanding issue of researchers. However the conventional SI techniques are identified to be non-practical to the complex and tall buildings, due to limitation of the availability of an accurate data that is magnitude or location of external loads. In most SI approaches, the information on input loading and output responses must be known. In many cases, measuring the input information may take most of the resources, and it is very difficult to accurately measure the input information during actual vibrations of practical importance, e.g., earthquakes, winds, micro seismic tremors, and mechanical vibration. However, the desirability and application potential of SI to real structures could be highly improved if an algorithm is available that can estimate structural parameters based on the response data alone without the input information. Thus a technique to estimate structural properties of building without input measurement data and using limited response is essential in structural health monitoring. In this study, shaking table tests on three-story plane frame steel structures were performed. Out-put only model analysis on the measured data was performed, and the dynamic properties were inverse analyzed using least square method in time domain. In results damage detection was performed in each member level, which was performed at story level in conventional SI techniques of frequency domain.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.05a
• /
• pp.947-950
• /
• 2015

In the cause of car accidents in Korea, drowsy driving has shown that it is larger fctors than drunk driving. Therefore, in order to prevent drowsy driving accidents, drowsiness detection and warning system for drivers has recently become a very important issue. Furthermore, Many researches have been published that measuring alpha wave of EEG signals is the effective way in order to be aware of drowsiness of drivers. In this study, we have developed EEG measuring device that applies a signal processing algorithm using the LabView program for detecting drowsiness. According to results of drowsiness inducement experiments for small test subjects, it was able to detect the pattern of EEG, which means drowsy state based on the changing of power spectrum, counterpart of alpha wave. After all, Comparing to the results of drowsiness pattern between commercial equipments and developed device, we could confirm acquiring similar pattern to drowsiness pattern. With this results, the driver's drowsiness prevention system expect that it will be able to contribute to lowering the death rate caused by drowsy driving accidents.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.26 no.5
• /
• pp.285-290
• /
• 2006

The evaluation of clamping condition has been regarded as the main issue in the safety-maintenance of the clamped high-tension bolts. For this, this paper proposes a method to estimate the axial stress by measuring the TOF (Time-Of-Flight) of ultrasonic wave, which is based on the acoustoelasticity or the dependency of sound speed on the stress. In this method, however, the variation of sound speed within the range of stress induced under the field condition is very small, and thus the accuracy of the TOF measurement is important. We adopted the phase detection method using tone-burst ultrasonic wave to measure the precise TOF. In order to verify the usefulness of the proposed method experiments are carried out and the results were compared with the stress measured by the strain gage. The results show good agreement with each other, and from these we can conclude that the proposed method is highly useful fnr the evaluation of clamping condition in the clamped high-tension bolts.

• Journal of the Korean Institute of Gas
• /
• v.17 no.2
• /
• pp.28-35
• /
• 2013

The number of large and complex buildings is growing and they are usually concentrated in metropolitan cities. There is a possibility in such buildings that a small accident can expand to a massive disaster since their scale and complexity. To deal with this issue, a research on gas sensors which can detect multiple gases and early-warning systems has been conducted. Proper criteria or standards are necessary for effective application and operation of such sensor-based disaster monitoring system. In this study, we have proposed the alarm criteria of concentration of hazardous gases for the detection and the alarm release. For each alarm level, systematic disaster response plans consist of responsive actions and information delivery have been prepared. These disaster monitoring criteria can help the detection of hazardous gas-related disaster in the early stage of accident and the provision of appropriate emergency responses.

• Asian Pacific Journal of Cancer Prevention
• /
• v.16 no.12
• /
• pp.4971-4975
• /
• 2015

Background: Several methods have been presented for the evaluation of the endometrium in patients with abnormal uterine bleeding, which include minimal invasive and invasive approaches such as diagnostic curettage or endometrial biopsy by Pipelle. Many studies have been performed in order to compare two methods; diagnostic curettage and outpatient endometrial biopsy. This investigation compared sampling adequacy, endometrial histopathology, failure rates, duration and costs between diagnostic curettage in a hospital and endometrial biopsy. Materials and Methods: This single blind clinical trial was performed on 130 patients older than 35 years who was referred to Amir training hospital in 2013 for elective diagnostic curettage because of abnormal uterine bleeding. For all patients eligible for the study, an endometrial sample by Pipelle was taken without anesthesia or dilatation. Then under general anesthesia diagnostic curettage was performed by sharp curette. Sampling duration was calculated and both samples were sent to the same pathologist. The diagnostic values of two methods in the diagnosis of normal endometrium, endometrial hyperplasia and carcinoma were compared. The costs of these two methods were also compared. Data analysis was performed by SPSS (version 16.0) software. Chi-Square, Fisher, and Pearson tests were used and were considered statistically significant at P values less than 0.05. Results: Two methods were agreed upon 88% of sampling adequacy and 94% of pathological results. Specificity of 100% and sensitivity of 90% for detection of proliferative endometrium, secretory endometrium, simple hyperplasia without atypia and 100% for cancer were recorded. Pipelle diagnostic accuracy in comparison with curettage, have been reported over 97%, so the failure rate in this study was below 5%. Sensitivity of Pipelle for detection of atrophic endometrium was reported below 50%. Duration and cost was lower in Pipelle versus curettage. Conclusions: It is concluded that due to high agreement and cohesion coefficient between curettage and Pipelle on the issue of sampling adequacy, histopathology finding (except atrophic endometrium), low failure rate, duration of sampling and cost, Pipelle can be introduced as a suitable alternative of diagnostic curettage.

• Proceedings of the Korea Contents Association Conference
• /
• 2005.11a
• /
• pp.529-532
• /
• 2005

In anomaly intrusion detection, how to model the normal behavior of activities performed by a user is an important issue. To extract the normal behavior as a profile, conventional data mining techniques are widely applied to a finite audit data set. However, these approaches can only model the static behavior of a user in the audit data set This drawback can be overcome by viewing the continuous activities of a user as an audit data stream. This paper proposes a new clustering algorithm which continuously models a data stream. A set of features is used to represent the characteristics of an activity. For each feature, the clusters of feature values corresponding to activities observed so far in an audit data stream are identified by the proposed clustering algorithm for data streams. As a result, without maintaining any historical activity of a user physically, new activities of the user can be continuously reflected to the on-going result of clustering.