• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.6 s.111
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• pp.609-618
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• 2006

This study is undertaken for the vibration analysis of tapered thick plate with concentrated mass on elastic foundation. The boundary condition of the plate is analyzed with the 4-sides simply supported and 4-fixed basis. This study find out the frequency following the change in size for each foundational variable on Pasternak foundation, one of the two-parameter elastic foundation parameter that considered the shear layer to the Winkler foundation parameter. The concentrated mass is applied with the consideration of mass of the entire plate, and the change of frequency is studies on each location with the consideration of reacting for the three locations for concentrated mass. And, in order to find out the change of frequency on the thickness of the plate, it considered tapered ratio that linearly changes depending on the length of the plate with the thickness of the plate in x-direction, and the tapered ratio has changes with 4 types ($\alpha$=0.25, 0, 5, 0.75, and 1.0). For the interpretation, the program using finite element method (F.E.M.) is used and the element coordination is used the 8-node serendipity element. Therefore, the purpose of this study is to find out the characteristics of plate vibration under the mechanica vibration or external vibration factor to facilitate as the basic data of the design to secure the stability.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.9
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• pp.461-468
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• 2001

Though shared virtual memory (SVM) system promise low cost solutions for high performance computing they suffer from long memory latencies. These latencies are usually caused by repetitive invalidations on shared data. Since shared data are accessed through synchronization and the patterns by which threads synchronizes are repetitive, a prefetching scheme bases on such repetitiveness would reduce memory latencies. Based on this observation, we propose a prefetching technique which predicts future access behavior by analyzing access history per synchronization variable. Our technique was evaluated on an 8-node SVM system using the SPLASH-2 benchmark. The results show the our technique could achieve 34%~45% reduction in memory access latencies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3151-3168
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• 2021

Internet of Things (IoT) connects several objects with embedded sensors and they are capable of exchanging information between devices to create a smart environment. IoT smart devices have limited resources, such as batteries, computing power, and bandwidth, but comprehensive sensing causes severe energy restrictions, lowering data quality. The main objective of the proposal is to build a hybrid protocol which provides high data quality and reduced energy consumption in IoT sensor network. The hybrid protocol gives a flexible and complete solution for sensor selection problem. It selects a subset of active sensor nodes in the network which will increase the data quality and optimize the energy consumption. Since the unused sensor nodes switch off during the sensing phase, the energy consumption is greatly reduced. The hybrid protocol uses Dijkstra's algorithm for determining the shortest path for sensing data and Ant colony inspired variable path selection algorithm for selecting active nodes in the network. The missing data due to inactive sensor nodes is reconstructed using enhanced belief propagation algorithm. The proposed hybrid method is evaluated using real sensor data and the demonstrated results show significant improvement in energy consumption, data utility and data reconstruction rate compared to other existing methods.

• Journal of Gastric Cancer
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• v.13 no.4
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• pp.242-246
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• 2013

Purpose: Reoperations after gastrectomy for gastric cancer are performed for many types of complications. Unexpected reoperations may cause mental, physical, and financial problems for patients. The aim of the present study was to evaluate the causes of reoperations and to develop a strategic decision-making process for these reoperations. Materials and Methods: From September 2002 through August 2010, 6,131 patients underwent open conventional gastrectomy operations at Samsung Medical Center. Of these, 129 patients (2.1%) required reoperation because of postoperative complications. We performed a retrospective analysis of the patients using an electronic medical record review. Statistical data were analyzed to compare age, sex, stage, type of gastrectomy, length of operation, size of tumor, and number of lymph node metastasis between patients who had been operated and those who had not. Results: The variables of age, sex, tumor stage, type of gastrectomy, length of operation, and number of lymph node metastases did not differ between the 2 groups. However, the mean tumor size in the reoperation group was greater than that in the non-reoperation group ($5.0{\pm}3.7$ [standard deviation] versus $4.1{\pm}2.9$, P=0.007). The leading cause of reoperation was surgical-site infection (n=49, 0.79%). Patients with intra-abdominal bleeding were operated on again in the shortest period after the initial gastrectomy ($6.3{\pm}4.2$ days). Patients with incisional hernia were not reoperated on until after $208.3{\pm}81.0$ days, the longest postoperative period. Conclusions: Tumor size was the major variable leading to reoperation after gastrectomy for gastric cancer. The most common complication requiring the reoperation was a surgical site-related complication.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.12-19
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• 2020

The clustered heterogeneous wireless sensor network is comprised of sensor nodes and cluster heads, which are hierarchically organized for different objectives. In the network, we should especially take care of managing node resources to enhance network performance based on memory and battery capacity constraints. For instances, if some interesting events occur frequently in the vicinity of particular sensor nodes, those nodes might receive massive amounts of data. Data congestion can happen due to a memory bottleneck or link disconnection at cluster heads because the remaining memory space is filled with those data. In this paper, we utilize drones as mobile sinks to resolve data congestion and model the network, sensor nodes, and cluster heads. We also design a cost function and a congestion indicator to calculate the degree of congestion. Then we propose a data congestion map index and a data congestion mapping scheme to deploy drones at optimal points. Using control variable, we explore the relationship between the degree of congestion and the number of drones to be deployed, as well as the number of drones that must be below a certain degree of congestion and within communication range. Furthermore, we show that our algorithm outperforms previous work by a minimum of 20% in terms of memory overflow.

• Journal of Distribution Science
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• v.17 no.3
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• pp.85-95
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• 2019

Purpose - The existing marketing studies using Social Network Analysis have assumed that network structure variables are time-invariant. However, a node's network position can fluctuate considerably over time and the node's network structure can be changed dynamically. Hence, if such a dynamic structural network characteristics are not specified for virtual goods purchase model, estimated parameters can be biased. In this paper, by comparing a time-invariant network structure specification model(base model) and time-varying network specification model(proposed model), the authors intend to prove whether the proposed model is superior to the base model. In addition, the authors also intend to investigate whether coefficients of network structure variables are random over time. Research design, data, and methodology - The data of this study are obtained from a Korean social network provider. The authors construct a monthly panel data by calculating the raw data. To fit the panel data, the authors derive random effects panel tobit model and multi-level mixed effects model. Results - First, the proposed model is better than that of the base model in terms of performance. Second, except for constraint, multi-level mixed effects models with random coefficient of every network structure variable(in-degree, out-degree, in-closeness centrality, out-closeness centrality, clustering coefficient) perform better than not random coefficient specification model. Conclusion - The size and importance of virtual goods market has been dramatically increasing. Notwithstanding such a strategic importance of virtual goods, there is little research on social influential factors which impact the intention of virtual good purchase. Even studies which investigated social influence factors have assumed that social network structure variables are time-invariant. However, the authors show that network structure variables are time-variant and coefficients of network structure variables are random over time. Thus, virtual goods purchase model with dynamic network structure variables performs better than that with static network structure model. Hence, if marketing practitioners intend to use social influences to sell virtual goods in social media, they had better consider time-varying social influences of network members. In addition, this study can be also differentiated from other related researches using survey data in that this study deals with actual field data.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.107-116
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• 2011

In this paper, a traffic adaptive sleep based medium access control (TAS-MAC) protocol for wireless sensor networks (WSNs) is proposed. The protocol aims for WSNs which consist of clustered sensor nodes and is based on TDMA-like schema. It is a typical schedule based mechanism which is adopted in previous protocols such as LEACH and Bit-Map Assisted MAC. The proposed MAC, however, considers unexpected long silent period in which sensor nodes have no data input and events do not happen in monitoring environment. With the simple traffic measurement, the TAS-MAC eliminates scheduling phases consuming energy in previous centralized approaches. A frame structure of the protocol includes three periods, investigation (I), transmission (T), and sleep-period (S). Through the I-period, TAS-MAC aggregates current traffic information from each end node and dynamically decide the length of sleep period to avoid energy waste in long silent period. In spite of the energy efficiency of this approach, the delay of data might increase. Thus, we propose an advanced version of TAS-MAC as well, each node in cluster sends one or more data packets to cluster head during the T-period of a frame. Through simulation, the performance in terms of energy consumption and transmission delay is evaluated. By comparing to BMA-MAC, the results indicate the proposed protocol is more energy efficient with tolerable expense in latency, especially in variable traffic situation.

• Journal of the Korean Regional Science Association
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• v.37 no.4
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• pp.49-59
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• 2021

This study aims to identify the characteristics of the cancelled districts of housing redevelopment and housing reconstruction project. The subject of this study is 189 project districts(121 promoted districts, 68 cancelled districts). Both 121 promoted districts and 68 cancelled districts were analyzed by Decision Tree Analysis. The first separation of the release zone influencing factors was made by the Development Actors. In other words, the most important independent variable for determining the release zone influence factor was shown to be the presence or absence of propulsion actors. Of the 89 districts without propellers, 41 were lifted and 48 were promoted, and 9 out of 100 districts with propellers were lifted and 91 were promoted. The second separation of the impact factors on the zone was then made by Land Owners, and the probability of cancellation increased if the number of landowners was less than 468 and 37 out of 62 were removed. On the other hand, four out of 27 districts with more than 468 landowners were lifted and 23 districts were promoted. The third separation was made by the Average Land Assessment, and 35 zones were lifted below the standard of KRW 269.64 million/m² approximately KRW 8.91 million per pyeong, and two zones were lifted at higher official prices. In the second division, the number of landowners was 468 or more, and in node4, four areas were removed from areas with a public land area ratio of 29.43% or more, and no areas less were released. This study used SPSS Statistics 26 S/W for analysis.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.59-76
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• 2023

Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.7B
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• pp.605-619
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• 2003

The main memory DBMS(MMDBMS) efficiently supports various database applications that require high performance since it employs main memory rather than disk as a primary storage. In this paper, we discuss the index manager of the Tachyon, a next-generation MMDBMS. Recently, the gap between the CPU processing and main memory access times is becoming much wider due to rapid advance of CPU technology. By devising data structures and algorithms that utilize the behavior of the cache in CPU, we are able to enhance the overall performance of MMDBMSs considerably. In this paper, we address the practical implementation issues and our solutions for them obtained in developing the cache-conscious index manager of the Tachyon. The main issues touched are (1) consideration of the cache behavior, (2) compact representation of the index entry and the index node, (3) support of variable-length keys, (4) support of multiple-attribute keys, (5) support of duplicated keys, (6) definition of the system catalog for indexes, (7) definition of external APIs, (8) concurrency control, and (9) backup and recovery. We also show the effectiveness of our approach through extensive experiments.