• Journal of Information Processing Systems
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• v.19 no.6
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• pp.745-755
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• 2023

The wire rope is an indispensable production machinery in coal mines. It is the main force-bearing equipment of the underground traction system. Accurate detection of wire rope defects and positions exerts an exceedingly crucial role in safe production. The existing defect detection solutions exhibit some deficiencies pertaining to the flexibility, accuracy and real-time performance of wire rope defect detection. To solve the aforementioned problems, this study utilizes the camera to sample the wire rope before the well entry, and proposes an object based on YOLOv5. The surface small-defect detection model realizes the accurate detection of small defects outside the wire rope. The transfer learning method is also introduced to enhance the model accuracy of small sample training. Herein, the enhanced YOLOv5 algorithm effectively enhances the accuracy of target detection and solves the defect detection problem of wire rope utilized in mine, and somewhat avoids accidents occasioned by wire rope damage. After a large number of experiments, it is revealed that in the task of wire rope defect detection, the average correctness rate and the average accuracy rate of the model are significantly enhanced with those before the modification, and that the detection speed can be maintained at a real-time level.

• Tunnel and Underground Space
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• v.30 no.4
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• pp.382-393
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• 2020

The engineered barrier system of high-level radioactive waste disposal must maintain its performance in the long term, because it must play a role in slowing the rate of leakage to the surrounding rock mass even if a radionuclide leak occurs from the canister. In particular, it is very important to clarify gas dilation flow phenomenon clearly, that occurs only in a medium containing a large amount of clay material such as a bentonite buffer, which can affect the long-term performance of the bentonite buffer. Accordingly, DECOVALEX-2019 Task A was conducted to identify the hydraulic-mechanical mechanism for the dilation flow, and to develop and verify a new numerical analysis technique for quantitative evaluation of gas migration phenomena. In this study, based on the conventional two-phase flow and mechanical behavior with effective stresses in the porous medium, the hydraulic-mechanical model was developed considering the concept of damage to simulate the formation of micro-cracks and expansion of the medium and the corresponding change in the hydraulic properties. Model verification and validation were conducted through comparison with the results of 1D and 3D gas injection tests. As a result of the numerical analysis, it was possible to model the sudden increase in pore water pressure, stress, gas inflow and outflow rate due to the dilation flow induced by gas pressure, however, the influence of the hydraulic-mechanical interaction was underestimated. Nevertheless, this study can provide a preliminary model for the dilation flow and a basis for developing an advanced model. It is believed that it can be used not only for analyzing data from laboratory and field tests, but also for long-term performance evaluation of the high-level radioactive waste disposal system.

• The KIPS Transactions:PartA
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• v.18A no.6
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• pp.271-280
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• 2011

Time-Triggered Architecture (TTA), one of real-time software design paradigms which executes tasks in timely manner, has long been advocated as being better suited in fore-sighting system behavior than event-triggered architecture (ETA). To gain this valuable feature of TTA, however, precise task designing process is mandatory. Alternatively, ETA tries to execute tasks whenever paired events are occurred. It provides intuitive and flexible basement to add/remove tasks and, moreover, better response time performance. However ETA is difficult to analyze because system behavior might be different depending on the order of interrupts detected by the system. Many previous researches recommended TTA when developing safety-critical real-time systems, but cost problem of task designing process and insufficient consensus for applying rigorous software engineering practice are still challenging in practice. This paper describes software refactoring process which applying TTA approach into ETA based embedded software in artificial heart system. We implemented dedicated interrupt monitoring program to capture existing tasks' real-time characteristics. Based on the captured information, proper task designing process is done. Real-time analysis using RMA (Rate-Monotonic Analysis) verified that new design guarantees timeliness of the system. Empirical experiments revealed that revised design is as efficient, when measured in terms of system's external output, as the old design and enhances predictability of the system behavior as well.

• ETRI Journal
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• v.37 no.2
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• pp.222-232
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• 2015

In this paper, we propose a dual-phase approach to improve the process of heart disease prediction in a mobile environment. Firstly, only the confident frequent rules are extracted from a patient's clinical information. These are then used to foretell the possibility of the presence of heart disease. However, in some cases, subjects cannot describe exactly what has happened to them or they may have a silent disease - in which case it won't be possible to detect any symptoms at this stage. To address these problems, data records collected over a long period of time of a patient's heart rate variability (HRV) are used to predict whether the patient is suffering from heart disease. By analyzing HRV patterns, doctors can determine whether a patient is suffering from heart disease. The task of collecting HRV patterns is done by an online artificial neural network, which as well as learning knew knowledge, is able to store and preserve all previously learned knowledge. An experiment is conducted to evaluate the performance of the proposed heart disease prediction process under different settings. The results show that the process's performance outperforms existing techniques such as that of the self-organizing map and gas neural growing in terms of classification and diagnostic accuracy, and network structure.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.782-787
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• 2004

Internet Engineering Task Force (IETF) has been considering the deployment of the Random Early Detection (RED) in order to avoid the increasing of packet loss rates which caused by an exponential increase in network traffic and buffer overflow. Although RED mechanism can prevent buffer overflow and hence reduce an average values of packet loss rates, but this technique is ineffective in preventing the consecutive drop in the high traffic condition. Moreover, it increases a probability and average number of consecutive dropped packet in the low traffic condition (named as "uncritical condition"). RED mechanism effects to TCP congestion control that build up the consecutive of the unnecessary transmission rate reducing; lead to low utilization on the link and consequently degrade the network performance. To overcome these problems, we have proposed a new mechanism, named as Extended Drop slope RED (ExRED) mechanism, by modifying the traditional RED. The numerical and simulation results show that our proposed mechanism reduces a drop probability in the uncritical condition.

• Journal of the Korean Society of Safety
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• v.23 no.1
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• pp.46-50
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• 2008

The purpose of the present study was to investigate the mariner's information characteristics in ship-ta-ship collision situation using the full mission ship-handling simulator. Risk levels of ship-to-ship collision were manipulated by whether the target ship complies with the naval regulations and by movement patterns of target ship. Dependent variables reflecting mariner's information characteristics in ship-ta-ship collision situation were measured in terms of radar detection reaction time, free recall performance of past navigation situation, and subjective ratings for the task difficulty. The results showed that, in general, the mariners appeared to be deteriorated in their radar detection reaction time and free recall performance as the risk of ship-ta-ship collision increased. Also, the mariners tended to rate required tasks more difficult in the high risk ship-ta-ship collision situation.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.275-280
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• 2009

Femtocells are viewed as a promising option for mobile operators to improve coverage and provide high-data-rate services in a cost-effective manner Femtocells can be used to serve indoor users, resulting in a powerful solution for ubiquitous indoor and outdoor coverage. TThe frequency accuracy and phase alignment is necessary for ensuring the quality of service (QoS) forapplications such as voice, real-time video, wireless hand-off, and data over a converged access medium at the femtocell. But, the GPS has some problem to be used at the femtocell, because it is difficult to set-up, depends on the satellite condition, and very expensive. The IEEE 1588 specification provides a low-cost means for clock synchronisation over a broadband Internet connection. The Time of Packet (ToP) specified in IEEE 1588 is able to synchronize distributed clocks with an accuracy of less than one microsecond in packet networks. However, the timing synchronization over packet switched networks is a difficult task because packet networks introduce large and highly variable packet delays. This paper proposes an enhanced filter algorithm to reduce ths packet delay variation effects and maintain ToP slave clock synchronization performance. The results are presented to demonstrate in the intra-networks and show the improved performance case when the efficient ToP filter algorithm is applied.

• ETRI Journal
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• v.38 no.3
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• pp.444-454
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• 2016

Voice service is very demanding in cognitive radio networks (CRNs). The available spectrum in a CRN for CR users varies owing to the presence of licensed users. On the other hand, voice packets are delay sensitive and can tolerate a limited amount of delay. This makes the support of voice traffic in a CRN a complicated task that can be achieved by devising necessary considerations regarding the various network functionalities. In this paper, the support of secondary voice users in a CRN is investigated. First, a novel packet scheduling scheme that can provide the required quality of service (QoS) to voice users is proposed. The proposed scheme utilizes the maximum packet transmission rate for secondary voice users by assigning each secondary user the channel with the best level of quality. Furthermore, an analytical framework developed for a performance analysis of the system, is described in which the effect of erroneous spectrum sensing on the performance of secondary voice users is also taken into account. The QoS parameters of secondary voice users, which were obtained analytically, are also detailed. The analytical results were verified through the simulation, and will provide helpful insight in supporting voice services in a CRN.

• The Journal of the Acoustical Society of Korea
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• v.23 no.5
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• pp.383-389
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• 2004

In this paper. we propose the bias compensation methods and the eigenvoice method using the mean of dimensional eigenvoice to improve the performance of rapid speaker adaptation based on eigenvoice under mismatch between training and test environment. Experimental results for vocabulary-independent word recognition task (using PBW 452 DB) show that the proposed methods yield improvements for small adaptation data. We obtained about 22∼30% relative improvement by the bias compensation methods as amount of adaptation data varied from 1 to 50, and obtained 41% relative improvement in error rate by the eigenvoice method using the mean of dimensional eigenvoice with only single adaptation word.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9C
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• pp.734-742
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• 2008

In spatially multiplexed MIMO systems that enable high data rate transmission over wireless communication channels, the spatial demultiplexing at the receiver is a challenging task and various demultiplexing methods have been developed. Among the previous methods, maximum likelihood detection with QR decomposition and M-algorithm (QRM-MLD), sphere decoding (SD), QOC, and MOC schemes have been reported to achieve a (near) maximum likelihood (ML) hard decision performance. In general, however, the reliability of soft output of these schemes is not satisfactory. In this paper, we propose a method which enhances the reliability of soft output. By computer simulations, we demonstrate the improved performance by the proposed method.