• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.145-149
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• 2017

One of the challenges facing precision manufacturers is the increasing feature complexity of tight tolerance parts. All engineering drawings must account for the size, form, orientation, and location of all features to ensure manufacturability, measurability, and design intent. Geometric controls per ASME Y14.5 are typically applied to specify dimensional tolerances on engineering drawings and define size, form, orientation, and location of features. Many engineering drawings lack the necessary geometric dimensioning and tolerancing to allow for timely and accurate inspection and verification. Plus-minus tolerancing is typically ambiguous and requires extra time by engineering, programming, machining, and inspection functions to debate and agree on a single conclusion. Complex geometry can result in long inspection and verification times and put even the most sophisticated measurement equipment and processes to the test. In addition, design, manufacturing and quality engineers are often frustrated by communication errors over these features. However, an approach called profile tolerancing offers optimal definition of design intent by explicitly defining uniform boundaries around the physical geometry. It is an efficient and effective method for measurement and quality control. There are several advantages for product designers who use position and profile tolerancing instead of linear dimensioning. When design intent is conveyed unambiguously, manufacturers don't have to field multiple question from suppliers as they design and build a process for manufacturing and inspection. Profile tolerancing, when it is applied correctly, provides manufacturing and inspection functions with unambiguously defined tolerancing. Those data are manufacturable and measurable. Customers can see cost and lead time reductions with parts that consistently meet the design intent. Components can function properly-eliminating costly rework, redesign, and missed market opportunities. However a supplier that is poised to embrace profile tolerancing will no doubt run into resistance from those who would prefer the way things have always been done. It is not just internal naysayers, but also suppliers that might fight the change. In addition, the investment for suppliers can be steep in terms of training, equipment, and software.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.31-40
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• 2012

This paper proposes a visual landmark, and presents a parking assistance system using the landmarks. The visual landmark is a feature corresponding to the parking slots, it must be selected considering the parking lot's environment. The parking lot has simple repetitive pattern environment without noticeable features. The previous landmarks are not proper to the parking lot's environment. We propose the visual landmark for this environment. We estimate the vehicle's location using the proposed landmarks, and expect the vehicle's trajectory according to the vehicle's state. The system's inputs are images from the camera fixed to the vehicle. The presented system estimates the vehicle's location using the input images, and assists a driver through displaying the expected vehicle's trajectory from the steering angle. The experimental results showed the proposed landmark's performance and the parking assistance system's performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.353-360
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• 2012

This paper describes a SLAM method which estimates landmark locations and robot pose simultaneously. The particle filter can deal with nonlinearity of robot motion as well as the non Gaussian property of robot motion uncertainty and sensor error. The state to be estimated includes the locations of landmarks in addition to the robot pose. In the experiment, four beacons which transmit ultrasonic signal are used as landmarks. The robot receives the ultrasonic signals from the beacons and detects the distance to them. The method uses rang scanning sensor to build geometric feature of the environment. Since robot location and heading are estimated by the particle filter, the scanned range data can be converted to the geometric map. The performance of the method is compared with that of the deadreckoning and trilateration.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.70-75
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• 2022

Accurately measuring location is necessary to provide a variety of services. The data for indoor positioning measures the RSSI values from the WiFi device through an application of a smartphone. The measured data becomes the raw data of machine learning. The feature data is the measured RSSI value, and the label is the name of the space for the measured position. For this purpose, the machine learning technique is to study a technique that predicts the exact location only with the WiFi signal by applying an efficient technique to classification. Ensemble is a technique for obtaining more accurate predictions through various models than one model, including backing and boosting. Among them, Boosting is a technique for adjusting the weight of a model through a modeling result based on sampled data, and there are various algorithms. This study uses Xgboost among the above techniques and evaluates performance with other ensemble techniques.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_1
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• pp.483-491
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• 2013

By a development of car navigation systems and mobile or positioning technology, it increases interest in location based services, especially pedestrian navigation systems. Updating of digital maps is important because digital maps are mass data and required to short updating cycle. In this paper, we proposed change detection for different network data-sets based on areal feature matching. Prior to change detection, we defined type of updating between different network data-sets. Next, we transformed road lines into areal features(block) that are surrounded by them and calculated a shape similarity between blocks in different data-sets. Blocks that a shape similarity is more than 0.6 are selected candidate block pairs. Secondly, we detected changed-block pairs by bipartite graph clustering or properties of a concave polygon according to types of updating, and calculated Fr$\acute{e}$chet distance between segments within the block or forming it. At this time, road segments of KAIS map that Fr$\acute{e}$chet distance is more than 50 are extracted as updating road features. As a result of accuracy evaluation, a value of detection rate appears high at 0.965. We could thus identify that a proposed method is able to apply to change detection between different network data-sets.

• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.47-56
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• 2005

A moving object has a various features that its spatial location, shape, and size are changed as time goes. In addition, the moving object has both temporal feature and spatial feature. It is one of the highly interested feature information in video data. In this paper, we propose an efficient content-based multimedia information retrieval system, so tailed ECoMOT which enables user to retrieve video data by using a trajectory information of moving objects in video data. The ECoMOT includes several novel techniques to achieve content-based retrieval using moving objects' trajectories : (1) Muitiple trajectory modeling technique to model the multiple trajectories composed of several moving objects; (2) Multiple similar trajectory retrieval technique to retrieve more similar trajectories by measuring similarity between a given two trajectories composed of several moving objects; (3) Superimposed signature-based trajectory indexing technique to effectively search corresponding trajectories from a large trajectory databases; (4) convenient trajectory extraction, query generation, and retrieval interface based on graphic user interface

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1351-1367
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• 2018

Image registration is an essential process for image fusion, change detection and time series analysis using multi-sensor images. For this purpose, we need to detect accurately the difference of scale and rotation between the multi-sensor images with difference spatial resolution. In this paper, we propose a new feature matching method using variable circular template for image registration between multi-resolution images. The proposed method creates a circular template at the center of a feature point in a coarse scale image and also a variable circular template in a fine scale image, respectively. After changing the scale of the variable circular template, we rotate the variable circular template by each predefined angle and compute the mutual information between the two circular templates and then find the scale, the angle of rotation and the center location of the variable circular template, respectively, in fine scale image when the mutual information between the two circular templates is maximum. The proposed method was tested using Kompsat-2, Kompsat-3 and Kompsat-3A images with different spatial resolution. The experimental results showed that the error of scale factor, the error of rotation angle and the localization error of the control point were less than 0.004, $0.3^{\circ}$ and one pixel, respectively.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.3
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• pp.121-129
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• 2024

The rapid advancement of digital technology and the COVID-19 pandemic have significantly accelerated the growth of online commerce, highlighting the need for support mechanisms that enable small business owners to effectively respond to these market changes. In response, this paper presents a foundational technology leveraging the Online to Offline (O2O) strategy to automatically capture products displayed on retail shelves and utilize these images to create virtual stores. The essence of this research lies in precisely identifying and recognizing the location and names of displayed products, for which a single-class-targeted, lightweight model based on YOLOv8, named ESD-YOLOv8, is proposed. The detected products are identified by their names through feature-point-based technology, equipped with the capability to swiftly update the system by simply adding photos of new products. Through experiments, product name recognition demonstrated an accuracy of 74.0%, and position detection achieved a performance with an F2-Score of 92.8% using only 0.3M parameters. These results confirm that the proposed method possesses high performance and optimized efficiency.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.99-105
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• 2009

Crack detection method of a rotating blade was suggested in this paper. A rotating blade was modeled with a cantilever beam connected to a hub undergoing rotating motion. The existence and the location of crack were able to be recognized from the vertical response of end tip of a rotating cantilever beam by employing Discrete Hidden Markov Model (DHMM) and Empirical Mode Decomposition (EMD). DHMM is a famous stochastic method in the field of speech recognition. However, in recent researches, it has been proved that DHMM can also be used in machine health monitoring. EMD is the method suggested by Huang et al. that decompose a random signal into several mono component signals. EMD was used in this paper as the process of extraction of feature vectors which is the important process to developing DHMM. It was found that developed DHMMs for crack detection of a rotating blade have shown good crack detection ability.

• Fire Science and Engineering
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• v.22 no.3
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• pp.278-286
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• 2008

When big fire in high rise building and multiplex happens, the needs for high prevention system of disaster are being increased for getting the real-time scene state, quick lifesaver, and safe life security. In this paper the proposed evacuation guidance algorithm which analyzed the feature and danger of fire in high rise buildings, gave simplicity and scalability. Our research shows as fire and disaster occur in high rise buildings we construct sensor networks and sense realtime location information on fire alive people, and the situation information for fire instructed quick and safe escaping route by using mesh routing algorithm scheme relative to exit sign.