• Journal of Chest Surgery
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• v.51 no.1
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• pp.29-34
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• 2018

Background: We evaluated the feasibility and outcomes of pulmonary resection and mediastinal node dissection (MND) by video-assisted thoracoscopic surgery (VATS) following neoadjuvant therapy for stage IIIA N2 non-small cell lung cancer (NSCLC). Methods: From November 2009 to December 2013, a total of 35 consecutive patients with pathologically or radiologically confirmed stage IIIA N2 lung cancer underwent pulmonary resection and MND, performed by a single surgeon, following neoadjuvant chemoradiation. Preoperative patient characteristics, surgical outcomes, postoperative drainage, postoperative complications, and mortality were retrospectively analyzed. Results: VATS was completed in 17 patients. Thoracotomy was performed in 18 patients, with 13 planned thoracotomies and 5 conversions from the VATS approach. The median age was $62.7{\pm}7.9years$ in the VATS group and $60{\pm}8.7years$ in the thoracotomy group. The patients in the VATS group tended to have a lower diffusing capacity for carbon monoxide (p=0.077). There were no differences between the 2 groups in the method of diagnosing the N stage, tumor response and size after induction, tumor location, or histologic type. Complete resection was achieved in all patients. More total and mediastinal nodes were dissected in the VATS group than in the thoracotomy group (p<0.05). The median chest tube duration was 5.3 days (range, 1 to 33 days) for the VATS group and 7.2 days (range, 2 to 28 days) for the thoracotomy group. The median follow-up duration was 36.3 months. The 5-year survival rates were 76% in the VATS group and 57.8% in the thoracotomy group (p=0.39). The 5-year disease-free survival rates were 40.3% and 38.9% in the VATS and thoracotomy groups, respectively (p=0.8). Conclusion: The VATS approach following neoadjuvant treatment was safe and feasible in selected patients for the treatment of stage IIIA N2 NSCLC, with no compromise of oncologic efficacy.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.101-111
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• 2014

Spatial events are predictable using data mining classification algorithms. Decision trees have been used as one of representative classification algorithms. And they were normally used in the classification tasks that have label class values. However since using rule ranking methods, spatial prediction have been applied in the spatial prediction problems. This paper compared rule ranking methods for the spatial prediction application using a decision tree. For the comparison experiment, C4.5 decision tree algorithm, and rule ranking methods such as Laplace, M-estimate and m-branch were implemented. As a spatial prediction case study, landslide which is one of representative spatial event occurs in the natural environment was applied. Among the rule ranking methods, in the results of accuracy evaluation, m-branch showed the better accuracy than other methods. However in case of m-brach and M-estimate required additional time-consuming procedure for searching optimal parameter values. Thus according to the application areas, the methods can be selectively used. The spatial prediction using a decision tree can be used not only for spatial predictions, but also for causal analysis in the specific event occurrence location.

• Journal of Korea Spatial Information System Society
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• v.9 no.2
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• pp.13-23
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• 2007

Recently there is growing Interest in LBS(Location Based Service) requiring real-time services and the spatial main memory DBMS for efficient Telematics services. In order to optimize existing disk-based multi-dimensional Indexes of the spatial main memory DBMS in the main memory, multi-dimensional index structures have been proposed, which minimize failures in cache access by reducing the entry size. However, because the reduction of entry size requires compression based on the MBR of the parent node or the removal of redundant MBR, the cost of MBR reconstruction increases in index update and the efficiency of search is lowered in index search. Thus, to reduce the cost of MBR reconstruction, this paper proposed the RSMBR(Relative-Sized MBR) compression technique, which applies the base point of compression differently in case of broad distribution and narrow distribution. In case of broad distribution, compression is made based on the left-bottom point of the extended MBR of the parent node, and in case of narrow distribution, the whole MBR is divided into cells of the same size and compression is made based on the left-bottom point of each cell. In addition, MBR was compressed using a relative coordinate and size to reduce the cost of search in index search. Lastly, we evaluated the performance of the proposed RSMBR compression technique using real data, and proved its superiority.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.7
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• pp.3373-3378
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• 2012

Background: Head and neck squamous cell carcinoma (HNSCC) is the 8th most common cancer worldwide. Although older age, male gender, smoking and alcohol consumption are known risk factors, an increasing number of HNSCC patients are without typical risk factors. Our aim was to define demographics of HNSCC in Iran and the potential risk factors related to Iranian ethnicity and lifestyle. Methods: We conducted a cross-sectional analytical study on 262 patients with primary SCC of the larynx, hypopharynx or tongue referred to our pathology department during 1995-2010. Patients' demographics, tumor characteristics and risk factors such as smoking, alcohol consumption and anemia were analyzed and compared in two groups of patients: over 40 years (older group) and 40 years or less (young group); Chi-square and Mann-Whitney analytical tests were employed. Results: 5.7% of patients were young adults. The male to female ratio was 1.5 in the younger group and 5.6 in the older group. In young adults, 40% of tumors were located in larynx and 40% in the tongue. Age >40 was significantly associated with laryngeal location (P<0.001). History of smoking and drinking was significantly associated with age >40 and SCC of larynx in both age groups. Cervical lymph node involvement was significantly correlated with SCC of tongue (P<0.001), however, considering young adults only, SCC of hypopharynx was most frequently accompanied by lymph node involvement (60%). The most prevalent tumor among men was SCC of larynx whereas SCC of hypopharynx was the most prevalent tumor among women (61%), of whom 18.2% were ${\leq}40$. Conclusions: The incidence of HNSCC among young adults seems to be higher in Iran compared to other countries. Reduction in exposure to known risk factors, especially tobacco smoking in forms of cigarettes and bubble pipes, and search for other causative agents of HNSCC in young population is recommended.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1840-1848
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• 2017

Linear wireless sensor networks typically construct a network topology with a high reliability through sequential 1:1 mapping among sensor nodes, so that they are used in various surveillance applications of major national infrastructures. Most existing techniques for identifying sensor nodes in those networks are using GPS, AOA, and RSSI mechanisms. However, GPS or AOA based node identification techniques affect the size or production cost of the nodes so that it is not easy to construct practical sensor networks. RSSI based techniques may have a high deviation regrading location identification according to propagation environments and equipment quality so that complexity of error correction algorithm may increase. We propose a timestamps based sequential localization algorithm that uses transmit and receive timestamps in a message between sensor nodes without using GPS, AOA, and RSSI techniques. The algorithms for distance measurement between each node are expected to measure distance within up to 1 meter in case of an crystal oscillator of 300MHz or more.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.2
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• pp.206-214
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• 2016

Recently, radio frequency energy transfer (RFET) attracts more and more interests for powering sensor nodes in the wireless sensor network (WSN). In the conventional WSN, reducing energy consumption of sensor nodes is of primary importance. On the contrary, in the WSN with RFET, reducing energy consumption is not an important issue. However, in the WSN with RFET, the energy harvesting rate of each sensor node depends on its location, which causes the unbalanced available energy among sensor nodes. Hence, to improve the performance of the WSN with RFET, it is important to develop network protocols considering this property. In this paper, we study this issue with jointly considering routing, scheduling, and power control in the WSN with RFET. In addition, we study this issue with considering two different objectives: 'Max-min' with which we tries to maximize the performance of a sensor node having the minimum performance and 'Max-min fairness' with which we tries to achieve max-min fairness among sensor nodes. We show that our solutions can improve network performance significantly and we also discuss the differences between 'Max-min' and 'Max-min fairness'.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.89-92
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• 2020

According to the various IoT(Internet of Things) services, there have been lots of task offloading researches for IoT devices. Since there are service response delay and core network load issues in conventional cloud computing based offloadings, fog computing based offloading has been focused whose location is close to the IoT devices. However, even in the fog computing architecture, the load can be concentrated on the for computing node when the number of requests increase. To solve this problem, the opportunistic fog computing concept which offloads task to available computing resources such as cars and drones is introduced. In previous fog and opportunistic fog node researches, the offloading is performed immediately whenever the service request occurs. This means that the service requests can be offloaded to the opportunistic fog nodes only while they are available. However, if the service response delay requirement is satisfied, there is no need to offload the request immediately. In addition, the load can be distributed by making the best use of the opportunistic fog nodes. Therefore, this paper proposes a delayed offloading scheme to satisfy the response delay requirements and offload the request to the opportunistic fog nodes as efficiently as possible.

• Smart Media Journal
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• v.12 no.1
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• pp.9-16
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• 2023

Recently, a convolutional neural network (CNN) based system is being developed to overcome the limitations of human resources in the apple quality classification of farmhouse. However, since convolutional neural networks receive only images of the same size, preprocessing such as sampling may be required, and in the case of oversampling, information loss of the original image such as image quality degradation and blurring occurs. In this paper, in order to minimize the above problem, to generate a image patch based graph of an original image and propose a random walk-based positional encoding method to apply the graph transformer model. The above method continuously learns the position embedding information of patches which don't have a positional information based on the random walk algorithm, and finds the optimal graph structure by aggregating useful node information through the self-attention technique of graph transformer model. Therefore, it is robust and shows good performance even in a new graph structure of random node order and an arbitrary graph structure according to the location of an object in an image. As a result, when experimented with 5 apple quality datasets, the learning accuracy was higher than other GNN models by a minimum of 1.3% to a maximum of 4.7%, and the number of parameters was 3.59M, which was about 15% less than the 23.52M of the ResNet18 model. Therefore, it shows fast reasoning speed according to the reduction of the amount of computation and proves the effect.

• Journal of the Korean Society of Radiology
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• v.82 no.5
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• pp.1246-1257
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• 2021

Purpose To assess the predictive factors and describe the imaging features of mediastinal lymph node (MLN) metastases in patients with head and neck cancer. Materials and Methods We compared the clinical features and disease characteristics (sex, age, site of primary tumor, histologic type, history of prior treatments, TNM stages, and metastasis in cervical LNs) of patients with head and neck cancers between the MLN metastasis and no MLN metastasis groups. We also evaluated the chest CT (distribution and maximum dimension of the largest LN) and PET/CT (maximum standardized uptake value) features of MLN metastases based on the MLN classification. Results Of the 470 patients with head and neck cancer, 55 (11.7%) had MLN metastasis, involving 150 mediastinal stations. Hypopharynx cancer, recurrent tumor, T4 stage, N2/N3 stages, and M1 stage were found to be significant predicting factors for MLN metastasis. The most common location of MLN metastasis was ipsilateral station 2 (upper paratracheal LNs, 36.4%), followed by ipsilateral station 11 (interlobar LNs, 27.3%) and ipsilateral station 10 (hilar LNs, 25.5%). Conclusion Metastasis to MLNs should be considered in patients with head and neck cancer, especially in cases that are associated with a hypopharyngeal cancer, recurrent tumor, and high TNM stages.

• The KIPS Transactions:PartC
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• v.13C no.5 s.108
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• pp.627-634
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• 2006

Overlay network eliminates the need to change the application-layer tree when the underlying network changes and enables the overlay network to survive in environments where nonmember nodes do not support multicast functionality. An overlay protocol monitors group dynamics, while underlying unicast protocols track network dynamics, resulting in more stable protocol operation and low control overhead even in a highly dynamic environment. But, if overlay multicast protocols does not know the location information of node, this makes it very difficult to build an efficient multicasting tree. So, we propose a Hierarchical Overlay Multicast Architecture (HOMA) with the location information. Because proposed architecture makes static region-based dynamic group by multicast members, it is 2-tired overlay multicasts of application layer that higher layer forms overlay multicast network between members that represent group, and support multicast between multicast members belonging to region at lower layer. This use GPS, take advantage of geographical region, and realizes a region-sensitive higher layer overlay multicast tree which is impervious to the movements of nodes. The simulation results show that our approach solves the efficiency problem effectively.