• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.6
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• pp.684-691
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• 2001

In this paper, we design and implement a system which recognizes and tracks a human head on a sequence of images. In this paper, the color of the skin and ellipse modeling is used as feature vectors to recognize the human head. And the modified time-varying edge detection method and the vertical projection method is used to acquire regions of the motion from images with very complex backgrounds. To select the head from the acquired candidate regions, the process for thresholding on the basis of the I-component of YIQ color information and mapping with ellipse modeling is used. The designed system shows an excellent performance in the cases of the rotated heads, occluded heads, and tilted heads as well as in the case of the normal up-right heads. And in this paper, the combinational technique of motion-based tracking and recognition-based tracking is used to track the human head exactly even though the human head moves fast.

• KIISE Transactions on Computing Practices
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• v.20 no.11
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• pp.598-603
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• 2014

In wireless sensor networks, two methods have been generally used to track continuously moving object: a user query-based method and a periodic report-based method. Although the former method generates more overhead as a result of the user queries, the former one is also an energy-efficient method that does not transfer unnecessary information. For the user query-based method, a virtual tree that consist of sensor nodes is used to perform the user query and the sensor reporting. The tree stores the information of the mobile objects, and the stored information triggers a report b the user query. However, in case of a fast-moving object, the tracking accuracy decreases as a result of the time delay of the end-to-end repeated query. In order to solve this problem, we propose a query-relay method that reduces the time delay for mobile object tracking. In the proposed method, the nodes in the tree relay the query to adjacent nodes according to the movement of mobile object that is tracked. When the query messages are relayed. The end-to-end querying time delay is reduced. and a simulation shows that our method is superior to existing ones in terms of tracking accuracy.

• Ecology and Resilient Infrastructure
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• v.4 no.2
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• pp.83-92
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• 2017

Increased investment in environment-friendly transport vehicles has led to rapid transit of railway tracks, double track program, linear improvements in railway lines, and moving railroad routes into the suburbs. They resulted in fast increase of railway yards. However, as the railroad yards being neglected, urban fine sites have been degraded. Local governments kept seeking ways to utilize the railway yards. In addition, Ministry of land, infrastructure and transport enacted "Guidelines for utilization of railway yards". The Guidelines categorized the railway yards into three types; conservation, utilized, and other sites in order to make efficient use of them. The railway yards have been converted and used for parks, rail bike trails, bike paths, and solar projects. It seems that studies are needed on diverse use of the yards and on post evaluation. This study investigated current uses of railway yards, domestic and foreign, and analyzed for the pertinent conditions on natural and cultural landscape, educational value, location and accessibility, potential for recreational area, and development opportunities. In this study, I proposed a quantitative evaluation method, and to find way to diversify the use of railway yards.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.9 no.6
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• pp.746-760
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• 1998

In this paper, an adaptive RSSD(reduced-state sequence detection) receiver is proposed for the purpose of reducing the complexity and decision delay of the adaptive MLSD(maximum-likelihood sequence detection) receiver in the mobile satellite channel. The RSSD receiver reconstructs the trellis with a reduced number of states. The performance degradation due to the reduced states is compensated by modifying the branch metric calculation which uses the symbols in each path memory to estimate the residual ISI(intersymbol interference) terms. The structure of the proposed adaptive RSSD is a modified RSSD utilizing a per-survivor processing as well as the symbol-aided method and a channel estimation using the tentative data sequences. The complexity and performance of the proposed adaptive RSSD are controlled by the number of system states and ISI cancelers and the inserting period of the known symbols. In spite of a suboptimal alternative receiver compared to the adaptive MLSD receiver, the proposed adaptive RSSD receiver is able to reduce the complexity significantly and track the time-varying channel fast and reliably.

• Journal of IKEEE
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• v.22 no.4
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• pp.922-932
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• 2018

Radial distance sensors are widely used for surveying and autonomous navigation. It is necessary to train the operation principle of these sensors and how to apply them. Although commercialization of radial distance sensor continues to be cost-effective through lower performance, but it is still expensive for educational purposes. In this paper, we propose a distance sensor module with object tracking using radial array of low cost phototransistor which can be used for educational robot. The proposed method is able to detect the position of a fast moving object immediately by arranging the phototransistor in the range of 180 degrees and improve the sensing angle range and track the object by the sensor rotation using the servo motor. The scan speed of the proposed sensor is 50~200 times faster than the commercial distance sensor, thus it can be applied to a high performance educational mobile robot with 1ms control loop.

• Korean Journal of Construction Engineering and Management
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• v.23 no.6
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• pp.54-64
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• 2022

The continuous aging of the domestic construction industry and the shortage of human resource are no longer a problem for the future, but must be solved for the survival of the domestic construction industry, given the characteristics of the labor-intensive construction industry and the continuing negative image of young people toward the construction industry. It is undoubtedly a prerequisite. This study is aimed to tackle the fundamental problem of the construction labor shortage faced by the domestic construction industry by comparing and analyzing the case of MMC technology development in the UK, which has been preparing fast-track response measures for the past 5 years to solve the labor shortage problem, and the case of Buildability technology development in Singapore, which is seeking mid- to long-term countermeasures for about 20 years. Also, This research provides the initial research & development roadmap for Korean Countermeasures Strategy.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.1-7
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• Journal of the Korea Society for Simulation
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• v.18 no.2
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• pp.77-89
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• 2009

Visual tracking technique is one of the essential things which are very important in the major fields of modern society. While contour tracking is especially necessary technique in the aspect of its fast performance with target's external contour information, it sometimes fails to track target motion because it is affected by the surrounding edges around target and weak egdes on the target boundary. To overcome these weak points, in this research it is suggested that PDMs can be obtained by generating the virtual 6-DOF motions of the mobile robot with a CCD camera and the image tracking system which is robust to the local minima around the target can be configured by constructing Active Shape Model in modular base. To show the effectiveness of the proposed method, the experiment is performed on the image stream obtained by a real mobile robot and the better performance is confirmed by comparing the experimental results with the ones of other major tracking techniques.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.210-216
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.3
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• pp.71-83
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• 2008

In this paper, the basic principle, the application and the limitation of Infrared thermography technique to detect defects in different kinds of concrete structures are reviewed. Considered are voids beneath the concrete surface with experiments, delamination between concrete surface and fiber reinforced polymer sheet, the deterioration of steel bars in reinforced concrete, surface defects in historical buildings, pavements, bridges, and railway track graves. As a result, we conclude that infrared thermography methods are useful for fast detecting defects; however, they are influenced by environmental factors, specially temperature. Therefore it is recommended to use the infrared thermography technique with other NDT equipments to expect better result.