• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.574-592
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• 2016

Range-free localization algorithm computes a normal node's position by estimating the distance to anchors which know their actual position. In recent years, reliable anchor selection research has been gained a lot of attention because this approach improves localization accuracy by selecting the only subset of anchors called reliable anchor. The distance estimation accuracy and the geometric shape formed by anchors are the two important factors which need to be considered when selecting the reliable anchors. In this paper, we study the relationship between a relative position of three anchors and localization error. From this study, under ideal condition, which is with zero localization error, we find two conditions for anchor selection, thereby proposing a novel anchor selection algorithm that selects three anchors matched most closely to the two conditions, and the validities of the conditions are proved using two theorems. By further employing the conditions, we finally propose a novel range-free localization algorithm. Simulation results show that the proposed algorithm shows considerably improved performance as compared to other existing works.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.47-55
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• 2020

In this paper, we propose one stage multi-scale face detector based Fully Convolution Network using anchor free method. Recently almost all state-of-the-art face detectors which predict location of faces using anchor-based methods rely on pre-defined anchor boxes. However this face detectors need to hyper-parameters and additional computation in training. The key idea of the proposed method is to eliminate hyper-parameters and additional computation using anchor free method. To do this, we apply two ideas. First, by eliminating the pre-defined set of anchor boxes, we avoid the additional computation and hyper-parameters related to anchor boxes. Second, our detector predicts location of faces using multi-feature maps to reduce foreground/background imbalance issue. Through Quantitative evaluation, the performance of the proposed method is evaluated and analyzed. Experimental results on the FDDB dataset demonstrate the effective of our proposed method.

• Journal of Ocean Engineering and Technology
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• v.16 no.2
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• pp.44-52
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• 2002

The mechanism of pullout resistance of compression anchor is analysed. This anchor is developed through the field pullout tests and the laboratory element test. The compression anchor is characterized by decrease of progressive failure, simple site work, economy and durability compared with tension anchor. The characteristics of compression anchor, compared with tension anchor. mainly are summarized as follows ; (1) The plastic displacement of anchor body is very small during pullout of anchor. (2) Total anchor length decreases by the shortening of free length; (3) The progressive failure is decreased.; (4) The safety factor for pullout resistance increases with time after construction of anchor.

• Journal of Korea Multimedia Society
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• v.25 no.4
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• pp.600-609
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• 2022

In supervised learning, labeling of all data is essential, and in particular, in the case of object detection, all objects belonging to the image and to be learned have to be labeled. Due to this problem, continual learning has recently attracted attention, which is a way to accumulate previous learned knowledge and minimize catastrophic forgetting. In this study, a continaul learning model is proposed that accumulates previously learned knowledge and enables learning about new objects. The proposed method is applied to CenterNet, which is a object detection model of anchor-free manner. In our study, the model is applied the knowledge distillation algorithm to be enabled continual learning. In particular, it is assumed that all output layers of the model have to be distilled in order to be most effective. Compared to LWF, the proposed method is increased by 23.3%p mAP in 19+1 scenarios, and also rised by 28.8%p in 15+5 scenarios.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.3
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• pp.895-906
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• 2014

A fundamental study of the dynamically penetrating anchor (DPA - colloquially known as torpedo anchor) embedded into deep seabed was conducted using measurement data and numerical approaches. Numerical simulation of such a structure penetration was often suffered by severe mesh distortion arising from very large soil deformation, complex contact condition and nonlinear soil behavior. In recent years, a Coupled Eulerian-Lagrangian method (CEL) has been used to solve geomechanical boundary value problems involving large deformations. In this study, 3D finite element analyses using the CEL formulation are carried out to simulate the construction process of dynamic anchors. Through comparisons with results of field measurements, the CEL method in the present study is in good agreement with the general trend observed by in-situ measurements and thus, predicts a realistic large deformation movement for the dynamic anchors by free-fall dropping, which the conventional FE method cannot. Additionally, the appropriate parametric studies needed for verifying the characteristic of dynamic anchor are also discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.1
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• pp.33-42
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• 2013

This paper presents a multihop range-free localization algorithm to estimate the physical location of a normal node with local connectivity information in anisotropic sensor networks. In the proposed algorithm, a normal node captures the detour degree of the shortest path connecting an anchor pair and itself by comparing the measured hop count and the expected hop count, and the node estimates the distances to the anchors based on the detour degree. The normal node repeats this procedure with all anchor combinations and pinpoints its location using the obtained distance estimates. The proposed algorithm requires fewer anchors and less communication overhead compared to existing range-free algorithms. We showed the superiority of the proposed algorithm over existing range-free algorithms through MATLA simulations.

• Smart Structures and Systems
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• v.7 no.4
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• pp.303-317
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• 2011

A specially designed tendon, which is proposed by embedding an FBG sensor into the center king cable of a 7-wire strand tendon, was applied to monitor the prestress force and load transfer of ground anchor. A series of tensile tests and a model pullout test were performed to verify the feasibility of the proposed smart tendon as a measuring sensor of tension force and load transfer along the tendon. The smart tendon has proven to be very effective for monitoring prestress force and load transfer by measuring the strain change of the tendon at the free part and the fixed part of ground anchor, respectively. Two 11.5 m long proto-type ground anchors were made simply by replacing a tendon with the proposed smart tendon and prestress forces of each anchor were monitored during the loading-unloading step using both FBG sensor embedded in the smart tendon and the conventional load cell. By comparing the prestress forces measured by the smart tendon and load cell, it was found that the prestress force monitored from the FBG sensor located at the free part is comparable to that measured from the conventional load cell. Furthermore, the load transfer of prestressing force at the tendon-grout interface was clearly measured from the FBGs distributed along the fixed part. From these pullout tests, the proposed smart tendon is not only expected to be an alternative monitoring tool for measuring prestress force from the introducing stage to the long-term period for health monitoring of the ground anchor but also can be used to improve design practice through determining the economic fixed length by practically measuring the load transfer depth.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.1-6
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• 2009

Localization of nodes is a key technology for application of wireless sensor network. Having a GPS receiver on every sensor node is costly. In the past, several approaches, including range-based and range-free, have been proposed to calculate positions for randomly deployed sensor nodes. Most of them use some special nodes, called anchor nodes, which are assumed to know their own locations. Other sensors compute their locations based on the information provided by these anchor nodes. This paper uses a single mobile anchor node to move in the sensing field and broadcast its current position periodically. We provide a weighted centroid localization algorithm that uses coefficients, which are decided by the influence of mobile anchor node to unknown nodes, to prompt localization accuracy. We also suggest a criterion which is used to select mobile anchor node which involve in computing the position of nodes for improving localization accuracy. Weighted centroid localization algorithm is simple, and no communication is needed while locating. The localization accuracy of weighted centroid localization algorithm is better than maximum likelihood estimation which is used very often. It can be applied to many applications.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.77-87
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• 2018

Many researches have been focused on localization in WSNs. However, the solutions for localization in static WSN are hard to apply to the mobile WSN. The solutions for mobile WSN localization have the assumption that there are a significant number of anchor nodes in the networks. In the resource limited situation, these solutions are difficult in applying to the static and mobile mixed WSN. Without using the anchor nodes, a localization service cannot be provided in efficient, accurate and reliable way for mixed wireless sensor networks which have a combination of static nodes and mobile nodes. Also, accuracy is an important consideration for localization in the mixed wireless sensor networks. In this paper, we presented a method to satisfy the requests for the accuracy of the localization without anchor nodes in the wireless sensor networks. Hop coordinates measurements are used as an accurate method for anchor free localization. Compared to the other methods with the same data in the same category, this technique has better accuracy than other methods. Also, we applied a minimum spanning tree algorithm to satisfy the requests for the efficiency such as low communication and computational cost of the localization without anchor nodes in WSNs. The Java simulation results show the correction of the suggested approach in a qualitative way and help to understand the performance in different placements.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7B
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• pp.595-605
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• 2012

DV-Hop is one of the well known range-free localization algorithms. The algorithm works well in case of isotropic network since the sensor and anchor nodes are placed in the entire area. However, it results in large errors in case of anisotropic networks where the hop count between nodes is not linearly proportional to the Euclidean distance between them. Hence, we proposed a novel range-free algorithm for anisotropic networks to improve the localization accuracy. In the paper, the Euclidean distance between anchor node and unknown node is estimated by the average hop distance calculated at each hop count with hop count and distance information between anchor nodes. By estimating the unknown location of nodes with the estimated distance estimated by the average hop distance calculated at each hop, the localization accuracy is improved. Simulation results show that the proposed algorithm has more accuracy than DV-Hop.