• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.2
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• pp.13-29
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• 1997

This paper considers a new routing problem, successive max-min connection ratio problem (SMCRP), arised in circuit telecommunication networks such as SONET and WDM optical transport network. An optimization model for SMCRP is established based on link-flow formulation. It's first optimization process is an integral version of maximum concurrent flow problem. Integer condition does not give the same connection-ratio of each node-pair at an optimal solution any more. It is also an integral multi-commodity flow problem with fairness restriction. In order to guarantee fairness to every node-pair the minimum of connection ratios to demand is maximized. NP- hardness of SMCRP is proved and a heuristic algorithm with polynomial-time bound is developed for the problem. Augmenting path and rerouting flow are used for the algorithm. The heuristic algorithm is implemented and tested for networks of different sizes. The results are compared with those given by GAMS/OSL, a popular commercial solver for integer programming problem.n among ferrite-pearlite matrix, the increase in spheroidal ratio with increasing fatigue limitation, 90% had the highest, 14.3% increasing more then 70%, distribution range of fatigue.
ife was small in same stress level. (2) $\sqrt{area}_{max}$ of graphite can be used to predict fatigue limit of Ductile Cast Iron. The Statistical distribution of extreme values of $\sqrt{area}_{max}$ may be used as a guideline for the control of inclusion size in the steelmaking.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.1
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• pp.58-64
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• 2005

The nodes of Ad-hoc network are made up of location registration for sending information and a great number of packet transmissions to maintain routing route among the nodes. under this environment, a huge number of traffics would be generated as mobility variable occurs more than in physical network. Hence, in this paper, focused on to study the relationship of nodes to analyze the extend of the traffic in order to control the traffics of the multi-hop in Ad-hoc.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1161-1167
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• 2003

The nodes of Ad hoc network are made up of location registration for sending informations and a great number of packet transmissions to maintain routing route among the nodes. Under this environment, a huge number of traffics would be generated as mobility variable occurs more than in physical network. Hence, in this paper, focused on to study the relationship of nodes to analyze the extent of the traffic in order to control the traffics of the multi-hop in Ad hoc.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.653-655
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• 2015

The nodes of Ad-hoc network are made up of location registration for sending informations and a great number of packet transmissions to maintain routing route among the nodes. Under this environment, a huge number of traffics would be generated as mobility variable occurs more than in physical network. Hence, in this paper, focused on to study the relationship of nodes to analyze the extent of the traffic in order to control the traffics of the multi-hop in Ad-hoc.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.601-603
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• 2013

The nodes of Ad-hoc network are made up of location registration for sending informations and a great number of packet transmissions to maintain routing route among the nodes. Under this environment, a huge number of traffics would be generated as mobility variable occurs more than in physical network. Hence, in this paper, focused on to study the relationship of nodes to analyze the extent of the traffic in order to control the traffics of the multi-hop in Ad-hoc.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.623-625
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• 2012

The nodes of Ad-hoc network are made up of location registration for sending informations and a great number of packet transmissions to maintain routing route among the nodes. Under this environment, a huge number of traffics would be generated as mobility variable occurs more than in physical network. Hence, in this paper, focused on to study the relationship of nodes to analyze the extent of the traffic in order to control the traffics of the multi-hop in Ad-hoc.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2480-2496
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• 2020

Considering that high-dose X-ray radiation during CT scans may bring potential risks to patients, in the medical imaging industry there has been increasing emphasis on low-dose CT. Due to complex statistical characteristics of noise found in low-dose CT images, many traditional methods are difficult to preserve structural details effectively while suppressing noise and artifacts. Inspired by the deep learning techniques, we propose a densely connected residual network (DCRN) for low-dose CT image noise cancelation, which combines the ideas of dense connection with residual learning. On one hand, dense connection maximizes information flow between layers in the network, which is beneficial to maintain structural details when denoising images. On the other hand, residual learning paired with batch normalization would allow for decreased training speed and better noise reduction performance in images. The experiments are performed on the 100 CT images selected from a public medical dataset-TCIA(The Cancer Imaging Archive). Compared with the other three competitive denoising algorithms, both subjective visual effect and objective evaluation indexes which include PSNR, RMSE, MAE and SSIM show that the proposed network can improve LDCT images quality more effectively while maintaining a low computational cost. In the objective evaluation indexes, the highest PSNR 33.67, RMSE 5.659, MAE 1.965 and SSIM 0.9434 are achieved by the proposed method. Especially for RMSE, compare with the best performing algorithm in the comparison algorithms, the proposed network increases it by 7 percentage points.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.67-80
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• 2023

Rice is an important food crop for most of the population in Nowadays, psychologists consider social media an important tool to examine mental disorders. Among these disorders, depression is one of the most common yet least cured disease Since abundant of writers having extensive followers express their feelings on social media and depression is significantly increasing, thus, exploring the literary text shared on social media may provide multidimensional features of depressive behaviors: (1) Background: Several studies observed that depressive data contains certain language styles and self-expressing pronouns, but current study provides the evidence that posts appearing with self-expressing pronouns and depressive language styles contain high emotional temperatures. Therefore, the main objective of this study is to examine the literary cyber writers' posts for discovering the symptomatic signs of depression. For this purpose, our research emphases on extracting the data from writers' public social media pages, blogs, and communities; (3) Results: To examine the emotional temperatures and sentences usage between depressive and not depressive groups, we employed the SentiStrength algorithm as a psycholinguistic method, TF-IDF and N-Gram for ranked phrases extraction, and Latent Dirichlet Allocation for topic modelling of the extracted phrases. The results unearth the strong connection between depression and negative emotional temperatures in writer's posts. Moreover, we used Naïve Bayes, Support Vector Machines, Random Forest, and Decision Tree algorithms to validate the classification of depressive and not depressive in terms of sentences, phrases and topics. The results reveal that comparing with others, Support Vectors Machines algorithm validates the classification while attaining highest 79% f-score; (4) Conclusions: Experimental results show that the proposed system outperformed for detection of depression trends in literary cyber writers using sentiment analysis.

• The Journal of the Korea Contents Association
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• v.8 no.5
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• pp.9-18
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• 2008

Web-services have originally been devised to share information as open services. In connection with it, hacking incidents have surged. Currently, Web-log analysis plays a crucial clue role in detecting Web-hacking. A growing number of cases are really related to perceiving and improving the weakness of Web-services based on Web-log analysis. Such as this, Web-log analysis plays a central role in finding out problems that Web has. Hence, Our research thesis suggests Web-DoS-hacking detective technique In the process of detecting such problems through SOM algorithm, the emergence frequency of BMU(Best Matching Unit) was studied, assuming the unit with the highest emergence frequency, as abnormal, and the problem- detection technique was recommended through the comparison of what's called BMU as input data.