• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.3
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• pp.235-249
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• 2018

The Artificial Neural Network (ANN) model has been known as one of the most effective theories for automatic ship berthing, as it has learning ability and mimics the actions of the human brain when performing the stages of ship berthing. However, existing ANN controllers can only bring a ship into a berth in a certain port, where the inputs of the ANN are the same as those of the teaching data. This means that those ANN controllers must be retrained when the ship arrives to a new port, which is time-consuming and costly. In this research, by using the head-up coordinate system, which includes the relative bearing and distance from the ship to the berth, a novel ANN controller is proposed to automatically control the ship into the berth in different ports without retraining the ANN structure. Numerical simulations were performed to verify the effectiveness of the proposed controller. First, teaching data were created in the original port to train the neural network; then, the controller was tested for automatic berthing in other ports, where the initial conditions of the inputs in the head-up coordinate system were similar to those of the teaching data in the original port. The results showed that the proposed controller has good performance for ship berthing in ports.

• Journal of architectural history
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• v.21 no.1
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• pp.47-63
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• 2012

This research aims to demonstrate the sociocultural significance of architectural journals produced in the 1970s during which a fundamental reconsideration of architectural discipline has been made. To this end, we established a method of analysis adapted to the characteristics of architectural journals of that period. In this formulation, the relative autonomy of architectural journal with regard to various actors and institutions involved in its production emerged as a major criterion for the analysis of a journal. From this methodological reflection, we analyzed two French architectural journals, AMC published between 1973 and 1981 and l'Architecture d'Aujourd'hui between 1974 and 1977, which were produced both in close relation with parisian architectural schools (UPA) in the context of reestablishment of architectural education and beginning of architectural research in France after the events of May 1968. If these journals reflected and strengthened the architectural reality and especially the social network of their protagonists, it is equally important to note that they have transformed it into cultural network, and this by the mechanism proper to their preparation and their textual organization.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.133-136
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• 1997

The human chromosome analysis is widely used to diagnose genetic disease and various congenital anomalies. Many researches on automated chromosome karyotype analysis has been carried out, some of which produced commercial systems. However, there still remains much room or improving the accuracy of chromosome classification. In this paper, We propose an optimal pattern classifier by neural network to improve the accuracy of chromosome classification. The proposed pattern classifier was built up of multi-step multi-layer neural network(MMANN). We reconstructed chromosome image to improve the chromosome classification accuracy and extracted three morphological features parameters such as centromeric index(C.I.), relative length ratio(R.L.), and relative area ratio(R.A.). This Parameters employed as input in neural network by preprocessing twenty human chromosome images. The experiment results show that the chromosome classification error is reduced much more than that of the other classification methods.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2000.11a
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• pp.45-67
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• 2000

Broadband access technologies plays an important role in the national information infrastructure. In the evolution path of the information infrastructure, the relative economics of alternative access technology is the most critical determining factor. In this paper, we discuss the economics of local loop access technologies of existing technologies, such as, ADSL, HFC, and new PLC. To do this, we suggest appropriate configuration of access network system and its associated numerical equations. To modelize access network system and drive the numerical equations, we consider the DS (Double Star) and the T&B (Tree ＆ Brench) architecture and analyse the adequate block diagram of each access system for each technology We introduce the density of subscriber as a key variable and the equation of allocating optimal number of cell in a service area. We analyze the relative economics of local loop architecture in two different situations, that is, urban and rural. From the empirical implementation, we found that for the case of urban area, where the cost of cable and infrastructure is not necessary, there is not much difference in the cost per one subscriber. However, for the case of rural region, we found that there is remarkable difference in the cost per one subscriber among technologies. Therefore we conclude that the economics of local loop architecture is depend on the density of subscriber and existing network infrastructures. we hope that this paper contribute to the optimal technology selection of consmer, technology Providers, and government.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.305-319
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• 2019

The prediction of the sum of container is very important in the field of container transport. Many influencing factors can affect the prediction results. These factors are usually composed of many variables, whose composition is often very complex. In this paper, we use gray relational analysis to set up a proper forecast index system for the prediction of the sum of containers in foreign trade. To address the issue of the low accuracy of the traditional prediction models and the problem of the difficulty of fully considering all the factors and other issues, this paper puts forward a prediction model which is combined with a back-propagation (BP) neural networks and the support vector machine (SVM). First, it gives the prediction with the data normalized by the BP neural network and generates a preliminary forecast data. Second, it employs SVM for the residual correction calculation for the results based on the preliminary data. The results of practical examples show that the overall relative error of the combined prediction model is no more than 1.5%, which is less than the relative error of the single prediction models. It is hoped that the research can provide a useful reference for the prediction of the sum of container and related studies.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.12
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• pp.105-114
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• 2019

The goal of this study is to quantitatively evaluate the effects of the additional construction of urban railroads. To this end, 1) establish accessibility as a measure of quantitative evaluation of construction effects; 2) select the 'Integration' of Space Syntax as a quantifiable indicator of accessibility; 3) represent the Seoul railroads as a network; 4) calculate the 'Integration' form the network before and after the additional construction of the urban railroads. By calculating the change of the 'Integration' of the individual nodes and the change of the sum of the 'Integration' of given zones, the change in accessibility of a particular node and the change in accessibility of a particular region were calculated. After analyzing the change in accessibility in nodes and areas as well, it was confirmed that the additional construction of urban railroads was improving accessibility as a whole of Seoul. It was also identified that there was a degree of difference in the extent of the accessibility change for the different areas. It is particularly noteworthy that changes occur in the accessibility ranking. While certain regions were improving relative rankings, others fell in rank. With this finding, it could be argued that active consideration of the areas in which the relative decline occurs is needed when the planned urban railroad is being built.

• Advances in Computational Design
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• v.7 no.3
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• pp.253-279
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• 2022

This study investigated and predicted the Marshall stability of glass-fiber asphalt mix, carbon-fiber asphalt mix and glass-carbon-fiber asphalt (hybrid) mix by using machine learning techniques such as Artificial Neural Network (ANN), Support Vector Machine (SVM) and Random Forest(RF), The data was obtained from the experiments and the research articles. Assessment of results indicated that performance of the Artificial Neural Network (ANN) based model outperformed applied models in training and testing datasets with values of indices as; coefficient of correlation (CC) 0.8492 and 0.8234, mean absolute error (MAE) 2.0999 and 2.5408, root mean squared error (RMSE) 2.8541 and 3.3165, relative absolute error (RAE) 48.16% and 54.05%, relative squared error (RRSE) 53.14% and 57.39%, Willmott's index (WI) 0.7490 and 0.7011, Scattering index (SI) 0.4134 and 0.3702 and BIAS 0.3020 and 0.4300 for both training and testing stages respectively. The Taylor diagram also confirms that the ANN-based model outperforms the other models. Results of sensitivity analysis show that Carbon fiber has a major influence in predicting the Marshall stability. However, the carbon fiber (CF) followed by glass-carbon fiber (50GF:50CF) and the optimal combination CF + (50GF:50CF) are found to be most sensitive in predicting the Marshall stability of fibrous asphalt concrete.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.3
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• pp.104-109
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• 2021

In this paper, we experimentally demonstrate a self-seeding FP-LD (Fabry Perot Laser Diode) to verify the possibility of a new tunable light source that can be used in WDM-PON (Wavelength Division Multiplexing - Passive Optical Network) system. The conventional implementation of WDM-PON using a tunable light source has a disadvantage that the center wavelength of the AWG (Arrayed Waveguide Grating) device and the tunable light source must be precisely aligned. However, the proposed tunable light source has the advantage that the tunable wavelength is automatically aligned with the center wavelength of the AWG as well as simple structure. The implemented tunable light source had a tunable band of about 14 nm or more, and the maximum RIN (Relative Intensity Noise) of about -124 dB/Hz, which showed the possibility of modulating 10 Gb/s signal by an external modulator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.133-152
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• 2022

Rice is a fundamental staple food commodity all around the world. Globally, it is grown over 167 million hectares and occupies almost 1/5^th of total cultivated land under cereals. With a total production of 782 million metric tons in 2018. In Pakistan, it is the 2^nd largest crop being produced and 3^rd largest food commodity after sugarcane and rice. The stem borers a type of pest in rice and other crops, Scirpophaga incertulas or the yellow stem borer is very serious pest and a major cause of yield loss, more than 90% damage is recorded in Pakistan on rice crop. Yellow stem borer population of rice could be stimulated with various environmental factors which includes relative humidity, light, and environmental temperature. Focus of this study is to find the environmental factors changes i.e., temperature, relative humidity and rainfall that can lead to cause outbreaks of yellow stem borers. this study helps to find out the hot spots of insect pest in rice field with a control of farmer's palm. Proposed system uses temperature, relative humidity, and rain sensor along with artificial neural network to predict yellow stem borer attack and generate warning to take necessary precautions. result shows 85.6% accuracy and accuracy gradually increased after repeating several training rounds. This system can be good IoT based solution for pest attack prediction which is cost effective and accurate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.7B
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• pp.697-710
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• 2004

Differentiated services (DiffServ) model has been prevailed as a scalable approach to provide quality of service in the Internet. However, there are difficulties in providing the guaranteed service in terms of end-to-end systems since differentiated services network considers quality of service of aggregated traffic due to the scalability and many researches have been mainly focused on per hop behavior or a single domain behavior. Furthermore quality of service may be time varying according to the network conditions. In this paper, we study dynamic class mapping mechanism to guarantee the end-to-end quality of service for multimedia traffics with the minimum network cost over differentiated services network. The proposed algorithm consists of an effective implementation of relative differentiated service model, quality of service advertising mechanism and dynamic class mapping mechanism. Finally, the experimental results are provided to show the performance of the proposed algorithm.