• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.542-549
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• 2004

The compressive strength of concrete is commonly used criterion in producing concrete. However, the tests on the compressive strength are complicated and time-consuming. More importantly, it is too late to make improvement even if the test result does not satisfy the required strength, since the test is usually performed at the 28th day after the placement of concrete at the construction site. Therefore, accurate and realistic strength estimation before the placement of concrete is being highly required. In this study, the estimation of the compressive strength of concrete was performed by probabilistic neural network (PNN) on the basis of concrete mix proportions. The estimation performance of PNN was improved by considering the correlation between input data and targeted output value. Adaptive probabilistic neural network (APNN) was proposed to automatically calculate the smoothing parameter in the conventional PNN by using the scheme of dynamic decay adjustment algorithm. The conventional PNN and APNN were applied to predict the compressive strength of concrete using actual test data of a concrete company. APNN showed better results than the conventional PNN in predicting the compressive strength of concrete.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10a
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• pp.130-131
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• 2007

Wireless Sensor Network typically incorporates diverse applications within the same network. A sensor node may have multiple sensors i.e. light, temperature, seismic etc with different transmission characteristics. Each application has different characteristics and requirements in terms of transmission rates, bandwidth, packet loss and delay demands may be initiated towards the sink. In this paper we propose Heterogeneous Traffic Oriented Rate Control Protocol (HTRCP) which ensures efficient rate control for diverse applications according to the priority specified by the sink. Moreover. HTRCP ensures the node priority based hop by hop dynamic rate adjustment for high link utilization.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.664-669
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• 1994

This paper focuses on development and implementation of a performance management algorithm for IEEE802.4 token bus networks to serve large-scale integrated manufacturing systems. Such factory automation networks have to satisgy delay constraints imposed on time-critical messages while maintaining as much network capacity as possible for non-time-critical messages. This paper presents a network perfomance manager that adjusts queue apacity as well as timers by using a set of fuzzy rules and fuzzy inference mechanism. The efficacy of the performance management has been demonstrated by a series of simulation experiments.

• Applied Microscopy
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• v.46 no.2
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• pp.100-104
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• 2016

Electron microscopy is currently the only available technique with a spatial resolution sufficient to identify fine neuronal processes and synaptic structures in densely packed neuropil. For large-scale volume reconstruction of neuronal connectivity, serial block-face scanning electron microscopy allows us to acquire thousands of serial images in an automated fashion and reconstruct neural circuits faster by reducing the alignment task. Here we introduce the whole reconstruction procedure of synaptic network in the rat hippocampal CA1 area and discuss technical issues to be resolved for improving image quality and segmentation. Compared to the serial section transmission electron microscopy, serial block-face scanning electron microscopy produced much reliable three-dimensional data sets and accelerated reconstruction by reducing the need of alignment and distortion adjustment. This approach will generate invaluable information on organizational features of our connectomes as well as diverse neurological disorders caused by synaptic impairments.

• Water for future
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• v.23 no.1
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• pp.109-118
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• 1990

In this study, the effectiveness of existing streamflow data collection networks in the Han and the Nakdong River Basin is evaluated for various gaging plans of 5, 10, 15 and 20years planning horizons by the nonlinear integer programming method, and also a technique for adjustment and planning of the existing network is provided for the purpose of increasing the efficiency of the network in terms of ecomony. The objective function is minimization of the average sampling mean square error of regional regression model with regression parameters estimated by generalized least squares method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.10
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• pp.2142-2149
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• 2002

Contacting with ground in the post-card area size only, tire supports entire automobile weight. As well, it characterizes most of automobile running performance. Among the design parameters, the carcass contour becomes a key design factor. This paper deals with the time-effective optimal design of tire crown contour in order to improve the tire wear performance by employing a back-propagation neural network model.

• Journal of Korean Society for Geospatial Information Science
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• v.2 no.1 s.3
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• pp.121-129
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• 1994

A number of existing cadastral control stations have been destroyed and shifted by a long lapse of time and careless management. Also, results of them are partly poor owing to dependence on conventional survey method. Because of these, it is very difficult in use of results. Hereupon, correction of cadastral results is necessary in level of government. But it is very consumable to check and adjust results with existing equipments and related techniques only. It is required that this problem can be resolved efficiently. This study analyzed the conformability for cadastral control network to GPS, GPS, which determine precise 3-D coordinates on a short time, to positioning of cadastral stations. We chose DaeJon city for the test area of this study and analyzed the precision of network composed of sixteen cadastral control stations. We made comparision the old result and the new outcome which obtained from coordinate transformation method and horizontal network adjustment method. As a result of this, we detected the blunder of cadastral stations. Furthermore, we suggested effective network type according to precision analysis of GPS observation network. Therefore, there is no doubt that GPS surveying can be applied to checking and adjustment of cadastral control network. Hereafter, it is expected that the practical use of GPS is advanced in a field of cadastration.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.126-136
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• 2018

The purpose of this study was to develop a severity-adjustment model for predicting mortality in acute stroke patients using machine learning. Using the Korean National Hospital Discharge In-depth Injury Survey from 2006 to 2015, the study population with disease code I60-I63 (KCD 7) were extracted for further analysis. Three tools were used for the severity-adjustment of comorbidity: the Charlson Comorbidity Index (CCI), the Elixhauser comorbidity index (ECI), and the Clinical Classification Software (CCS). The severity-adjustment models for mortality prediction in patients with acute stroke were developed using logistic regression, decision tree, neural network, and support vector machine methods. The most common comorbid disease in stroke patients were hypertension, uncomplicated (43.8%) in the ECI, and essential hypertension (43.9%) in the CCS. Among the CCI, ECI, and CCS, CCS had the highest AUC value. CCS was confirmed as the best severity correction tool. In addition, the AUC values for variables of CCS including main diagnosis, gender, age, hospitalization route, and existence of surgery were 0.808 for the logistic regression analysis, 0.785 for the decision tree, 0.809 for the neural network and 0.830 for the support vector machine. Therefore, the best predictive power was achieved by the support vector machine technique. The results of this study can be used in the establishment of health policy in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.139-150
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• 2020

The purpose of this study was to understand the influence of social network site (SNS) addiction on the ability of nursing students to adjust to university life and to generate the basic data to develop programs that could improve this ability. The data was collected from questionnaires that were filled out by 255 nursing students in two universities located in Jeollanam-do and Gyeonggi-do from May 16, 2020 to May 20, 2020. The data was analyzed using the SPSS 23.0 program (frequency, ANOVA, Pearson's correlation, multiple regression). The mean scores of SNS addiction and adjustment to university life were 2.16±0.54 (range:1-5) and 3.13±0.39 (range:1-5) respectively. SNS addiction accounts for 27% of the variance in adjustment to university life. The study concluded that SNS addiction negatively affects adjustment to university life among nursing students. To ensure better adjustment a program should be developed to treat SNS addiction early. Also, a study will have to be conducted to determine the time when tendency toward SNS addiction becomes apparent, to initiate treatment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1768-1789
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• 2016

In contemporary video streaming systems based on HTTP protocol, video players at the client side are responsible for adjusting video quality to network conditions and user expectations. However, when multiple video clips are streamed simultaneously, an intricate application logic implemented in the video players overlays the TCP mechanism which is responsible for a balanced access to a shared network link. As a result, some video players may not obtain a fair share of network throughput and may be vulnerable to an unstable video bit-rate. Therefore, we propose to simplify the algorithms implemented in the video players, which are responsible for the adjustment of video quality and constrain their functionality only to sending feedback to a server about a state of the player buffer. The main logic of the system is shifted to the server, which is now responsible for bit-rate selection and prioritisation of the video streams transmitted to multiple clients. To verify our proposition, we performed several experiments in a laboratory environment which show that when the server cooperates with the clients, the video players experience fewer quality switches and the system achieves better fairness when allocating network throughput among the video players. However, this comes at the cost of worse utilisation of network bandwidth.