• International conference on construction engineering and project management
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• 2022.06a
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• pp.1043-1050
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• 2022

Markov chains and Monte Carlo Simulation were applied to account for the probabilistic nature of pavement deterioration over time using data collected in the field. The primary purpose of this study was to evaluate pavement network performance of Western Australia (WA) by applying the existing pavement management tools relevant to WA road construction networks. Two approaches were used to analyze the pavement networks: evaluating current pavement performance data to assess WA State Road networks and predicting the future states using past and current pavement data. The Markov chains process and Monte Carlo Simulation methods were used to predicting future conditions. The results indicated that Markov chains and Monte Carlo Simulation prediction models perform well compared to pavement performance data from the last four decades. The results also revealed the impact of design, traffic demand, and climate and construction standards on urban pavement performance. This study recommends an appropriate and effective pavement engineering management system for proper pavement design and analysis, preliminary planning, future pavement maintenance and rehabilitation, service life, and sustainable pavement construction functionality.

• Annual Conference of KIPS
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• 2022.11a
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• pp.40-42
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• 2022

People's focus steadily shifted toward fashion as a popular aesthetic expression as their quality of life improved. Humans are inevitably drawn to things that are more aesthetically appealing. This human proclivity has resulted in the evolution of the fashion industry over time. However, too many clothing alternatives on e-commerce platforms have created additional obstacles for clients in recognizing their suitable outfit. Thus, in this paper, we proposed a personalized Fashion Recommender system that generates recommendations for the user based on their previous purchases and history. Our model aims to generate recommendations using an image of a product given as input by the user because many times people find something that they are interested in and tend to look for products that are like that. In the system, we first reduce data dimensionality by component analysis to avoid the curse of dimensionality, and then the final suggestion is generated by neural network. To create the final suggestions, we have employed neural networks to evaluate photos from the H&M dataset and a nearest neighbor backed recommender.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.4
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• pp.155-162
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• 2013

Routing protocol in ad hoc mobile networking has been an active research area in recent years. However, the environments of ad hoc network tend to have vulnerable points from attacks, because ad hoc mobile network is a kind of wireless network without centralized authentication or fixed network infrastructure such as base stations. Also, existing routing protocols that are effective in a wired network become inapplicable in ad hoc mobile networks. To address these issues, several secure routing protocols have been proposed: SAODV and SRPTES. Even though our protocols are intensified security of networks than existing protocols, they can not deal fluidly with frequent changing of wireless environment. Moreover, demerits in energy efficiency are detected because they concentrated only safety routing. In this paper, we propose an energy efficient secure routing protocol for various ad hoc mobile environment. First of all, we provide that the nodes distribute security information to reliable nodes for secure routing. The nodes constitute tree-structured with around nodes for token escrow, this action will protect invasion of malicious node through hiding security information. Next, we propose multi-path routing based security level for protection from dropping attack of malicious node, then networks will prevent data from unexpected packet loss. As a result, this algorithm enhances packet delivery ratio in network environment which has some malicious nodes, and a life time of entire network is extended through consuming energy evenly.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.3
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• pp.91-99
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• 2012

Jinju city is operating by selecting 8 places as the flood inundation risk area and by designating shelters on this area targeting districts damaged by typhoon and heavy rain, in the past. This study selected the research area as Nabul district and Sangpyeong district where are located in the town and that has high population density out of districts with inundation risk. The network analysis of GIS was applied to the suitability assessment on location of shelter by calculating the moving speed and the arriving time after dividing it into children, general adults, and aged people in consideration of the evacuation condition in inundation disaster. As a result, it was indicated that optimal evacuation plan time for children and aged people exceeded in getting to the shelter because of evacuation time excess and that even general adults outrun the prescribed evacuation time in some districts. Accordingly, a problem for evacuation time was improved by additionally designating 1-2 shelters to existing shelters in Nabul and Sangpyeong districts. A countermeasure is needed to reduce life and property damage in disaster occurrence by implementing the evacuation warning and the age-based evacuation plan more specifically in the future.

• Structural Engineering and Mechanics
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• v.58 no.3
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• pp.459-473
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• 2016

Various vague and unstructured problems encountered the civil engineering/designers that persuaded by their experiences. One of these problems is the structural failure of the reinforced concrete (RC) building determination. Typically, using the traditional Limit state method is time consuming and complex in designing structures that are optimized in terms of one/many parameters. Recent research has revealed the Artificial Neural Networks potentiality in solving various real life problems. Thus, the current work employed the Multilayer Perceptron Feed-Forward Network (MLP-FFN) classifier to tackle the problem of predicting structural failure of multistoried reinforced concrete buildings via detecting the failure possibility of the multistoried RC building structure in the future. In order to evaluate the proposed method performance, a database of 257 multistoried buildings RC structures has been constructed by professional engineers, from which 150 RC structures were used. From the structural design, fifteen features have been extracted, where nine features of them have been selected to perform the classification process. Various performance measures have been calculated to evaluate the proposed model. The experimental results established satisfactory performance of the proposed model.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.113-121
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• 2007

Commonly, in the Sensor Network that composed with multiple nodes uses Ad-hoc protocol to communicate each other. Each sensed data packets are collected by base node and processed by Host PC. But the Ad-hoc protocol is too vulnerable to Sinkhole attack, where the intruder attracts surrounding nodes with unfaithful routing information, and then performs selective forwarding or changes the data passing through it. The Sinkhole attack increases overhead over the network and boosts energy consumption speed to decrease network's life time. Since the other attacks can be easily adopted through sinkhole attack, the countermeasure must be considered carefully. In this paper, we proposed the Hop-depth algorithm that detects intruder in Sinkhole attack and colluded nodes. First, the proposed algorithm makes list of suspected nodes and identifies the real intruder in the suspected node list through the Hop-depth count value. And recalculates colluder's path information to find the real intruder. We evaluated the performance of the proposed algorithm using NS2. We compared and analyzed the success ratio of finding real intruder, false positive ratio, false negative ratio, and energy consumption.

• The Journal of the Korea Contents Association
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• v.11 no.6
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• pp.51-58
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• 2011

One of the objectives of research on routing methods in wireless sensor networks is maximizing the energy life of sensor nodes that have limited energy. In this study, we tried to even energy use in a wireless sensor network by giving a weight to the transition probability of ACS(Ant Colony System), which is commonly used to find the optimal path, based on the amount of energy in a sensor and the distance of the sensor from the sink. The proposed method showed improvement by 46.80% on the average in energy utility in comparison with representative routing method GPSR (Greedy Perimeter Stateless Routing), and its residual energy after operation for a specific length of time was 6.7% more on the average than that in ACS.

• Journal of Internet Computing and Services
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• v.13 no.3
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• pp.23-30
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• 2012

In order to show the gap between theory and practice, this paper first gives some experimental results for theoretical and real neighbor sets on a test-bed sensor network. The results prove that existing management protocols (e.g., duty-cycling, routing or aggregation) based on the theoretical communication radius cannot achieve their original goal, efficiency. In this paper, we present a practical duty-cycling mechanism based on the real neighbor set, allowing for energy-efficiency. It also guarantees to suppress duplicated transmissions of sensing values with similarity within a specific threshold in each zone (i.e., a portion of intended divided network). Simulation results performed with a set of real sensor data show that our mechanism increases the network life time while guaranteeing the transmission of necessary sensing values.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1272-1277
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• 2010

Target detection and tracking wireless sensor network must have various signal processing ability. Wireless sensor nodes need to light weight signal processing algorithm because of energy constraints and communication bandwidth constraints. General signal processing algorithm of wireless sensor node consists of de-noising, received signal strength computation, feature extraction and signal compression. Wireless sensor network life-time and performance of target detection and classification depend on sensor node signal processing. In this paper, we propose energy efficient signal processing algorithm using wavelet transform. The proposed method estimates exact target position.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9A
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• pp.850-857
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• 2005

Sensor networks consist of sensor nodes with small size, low cost, lowpower consumption, and multi-functions to sense, to process and to communicate. The main issue in sensor networks has been focused on minimizing power consumption of sensors to maximize network life time. In some critical applications, however, the most important issue is to transmitsensing information to the end user (the sink node) with reliability. Reliable information forwarding using multiple paths in sensor networks (ReinForM) has been proposed to achieve desired reliability in the error-prone channel, but it needs increasing transmission riverhead as the channel error rate becomes high and the number of hops between the source node and the sink node increases. In this paper, we propose a reliable transmission rnechanissmusing intermediate source nodes in sensor networks (ReTrust) to reduce packet overhead while keeping the desired reliability. ReTrust has beenshown to provide desired reliability and reduced overhead via simulationsand analysis.