• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 한국정밀공학회 2005년도 추계학술대회 논문집
• /
• pp.208-211
• /
• 2005

The volumetric interferometer, which uses the interference of wavefronts emitted from two single mode fibers, measures the target position in 3-D. In this paper, we suggest a new calculation method which doesn't need a non-linear optimization and an initial guess. We find the relationship between the coefficients of the Zernike polynomials for a spherical wavefront and its center and reconstruct a spherical wavefront by using the Zernike polynomials from two interference fringes like a lateral shearing interferometer. The target position can be obtained from the coefficients of the Zernike polynomials of the reconstructed wavefront. We can get the target position in 3-D with $sub-{\mu}m$ errors in a simulation.

• Journal of Positioning, Navigation, and Timing
• /
• 제10권1호
• /
• pp.49-54
• /
• 2021

Indoor positioning system becomes of increasing interests due to the demands for accurate indoor location information where Global Navigation Satellite System signal does not approach. Wi-Fi access points (APs) built in many construction in advance helps developing a Wi-Fi Received Signal Strength Indicator (RSSI) based indoor localization. This localization method first collects pairs of position and RSSI measurement set, which is called fingerprint database, and then estimates a user's position when given a query measurement set by comparing the fingerprint database. The challenge arises from nonlinearity and noise on Wi-Fi RSSI measurements and complexity of handling a large amount of the fingerprint data. In this paper, machine learning techniques have been applied to implement Wi-Fi based localization. However, most of existing indoor localizations focus on single position estimation. The main contribution of this paper is to develop multi-target localization by using deep neural, which is beneficial when a massive crowd requests positioning service. This paper evaluates the proposed multilocalization based on deep learning from a multi-story building, and analyses its learning effect as increasing number of target positions.

• Speech Sciences
• /
• 제14권4호
• /
• pp.115-128
• /
• 2007

The purposes of this paper were to develop an automatic script to collect such acoustic parameters as duration, intensity, pitch and the first two formant values of English words produced by two native Canadian speakers either alone or in a two-word phrase at a normal speed and to compare those values by the position in the phrases. A Praat script was proposed to obtain the comparable parameters at evenly divided time point of the target word. Results showed that the total duration of the word in the phrase was shorter than that of the word produced alone. That was attributed to the pronunciation style of the native speakers generally placing the primary word stress in the first word position. Also, the reduction ratio of the male speaker depended on the word position in the phrase while the female speaker didn't. Moreover, there were different contours of intensity and pitch by the position of the target word in the phrase while almost the same formant patterns were observed. Further studies would be desirable to examine those parameters of the words in the authentic speech materials.

• The Transactions of the Korean Institute of Power Electronics
• /
• 제4권6호
• /
• pp.616-623
• /
• 1999

Elevator velocity pattern is basL'C! on combining the time-based velocity pattern according to which the car m trip from starting position to vicinity of target position, and distance-based velocity pattern for precise landing ( of car. To obtain the lide comfortability, the impact caused by velocity pattern switching should be minimizLD b by removing the discontinuity of velocity and acceleration. In this paper, new velocity pattern generation m method which ensure the continuity of velocity and acceleration during pattern switching is proposed. P ProPOSLD velocity pattern also shorten the landing time to the target position.

• Journal of Drive and Control
• /
• 제17권4호
• /
• pp.8-14
• /
• 2020

Intelligent devices using ICT technology have been introduced in the field of construction machinery to improve productivity and stability. Among the intelligent devices, Machine Guidance is a device that provides real-time posture, location, and work range to drivers by installing various sensors, controllers, and satellite navigation systems on construction machines. Conversely, the efficiency of equipment that requires location information, such as machine guidance, will be greatly reduced in buildings, and tunnels in the GPS blind spots. Thus, the other high-precision positioning technologies are required in the GPS blind spot zone. In this study, we will develop a relative position measurement system that provides precise location information such as construction machinery and robots in a local area where the GPS reception is difficult. A relative position measurement system tracks a marker in the form of a sphere installed on a vehicle by using the image base tracking technology, and measures the distance and direction information to the marker to calculate a position.

• Journal of the Institute of Electronics and Information Engineers
• /
• 제52권3호
• /
• pp.13-18
• /
• 2015

This paper proposes an optimum vision system analysis and a reliable high-precision positioning system that converges a GNSS and a vision system in order to resolve position error and outdoor shaded areas two disadvantages of GNSS. For location determination of the object, it should receive signal from at least four GNSS. However, in urban areas, exact location determination is difficult due to factors like high buildings, obstacles, and reflected waves. In order to deal with the above problem, a vision system was employed. First, determine an exact position value of a target object in urban areas whose environment is poor for a GNSS. Then, identify such target object by a vision system and its position error is corrected using such target object. A vehicle can identify such target object using a vision system while moving, make location data values, and revise location calculations, thereby resulting in reliable high precision location determination.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제11권11호
• /
• pp.5459-5473
• /
• 2017

Recently, a tracking algorithm called the spatial-temporal context model has been proposed to locate a target by using the contextual information around the target. This model has achieved excellent results when the target undergoes slight occlusion and appearance changes. However, the target location in the current frame is based on the location in the previous frame, which will lead to failure in the presence of fast motion because of the lack of a prediction mechanism. In addition, the spatial context model is updated frame by frame, which will undoubtedly result in drift once the target is occluded continuously. This paper proposes two improvements to solve the above two problems: First, four possible positions of the target in the current frame are predicted based on the displacement between the previous two frames, and then, we calculate four confidence maps at these four positions; the target position is located at the position that corresponds to the maximum value. Second, we propose a target reliability criterion and design an adaptive threshold to regulate the updating speed of the model. Specifically, we stop updating the model when the reliability is lower than the threshold. Experimental results show that the proposed algorithm achieves better tracking results than traditional STC and other algorithms.

• Journal of Electrical Engineering and Technology
• /
• 제7권4호
• /
• pp.606-614
• /
• 2012

A practical recursive linear robust estimation scheme is proposed for target localization in the sensor network which provides range difference of arrival (RDOA) measurements. In order to radically solve the known practical difficulties such as sensitivity for initial guess and heavy computational burden caused by intrinsic nonlinearity of the RDOA based target localization problem, an uncertain linear measurement model is newly derived. In the suggested problem setting, the target localization performance of the conventional linear estimation schemes might be severely degraded under the low SNR condition and be affected by the target position in the sensor network. This motivates us to devise a new sensor network localization algorithm within the framework of the recently developed robust least squares estimation theory. Provided that the statistical information regarding RDOA measurements are available, the estimate of the proposition method shows the convergence in probability to the true target position. Through the computer simulations, the omnidirectional target localization performance and consistency of the proposed algorithm are compared to those of the existing ones. It is shown that the proposed method is more reliable than the total least squares method and the linear correction least squares method.

• BMB Reports
• /
• 제49권3호
• /
• pp.135-136
• /
• 2016

Small interfering RNAs (siRNAs) have been developed to intentionally repress a specific gene expression by directing RNA-induced silencing complex (RISC), mimicking the endogenous gene silencer, microRNAs (miRNAs). Although siRNA is designed to be perfectly complementary to an intended target mRNA, it also suppresses hundreds of off-targets by the way that miRNAs recognize targets. Until now, there is no efficient way to avoid such off-target repression, although the mode of miRNA-like interaction has been proposed. Rationally based on the model called "transitional nucleation" which pre-requires base-pairs from position 2 to the pivot (position 6) with targets, we developed a simple chemical modification which completely eliminates miRNA-like off-target repression (0%), achieved by substituting a nucleotide in pivot with abasic spacers (dSpacer or C3 spacer), which potentially destabilize the transitional nucleation. Furthermore, by alleviating steric hindrance in the complex with Argonaute (Ago), abasic pivot substitution also preserves near-perfect on-target activity (∼80-100%). Abasic pivot substitution offers a general means of harnessing target specificity of siRNAs to experimental and clinical applications where misleading and deleterious phenotypes from off-target repression must be considered.

• Proceedings of the Korean Society of Medical Physics Conference
• /
• 한국의학물리학회 2002년도 Proceedings
• /
• pp.439-441
• /
• 2002

The aim of this study is to reconstruct the 3D target volume from multiple projection images. It was assumed that we were already aware of the target position exactly, and all processes were performed in Target Coordinates whose origin was the center of the target. We used six projections: two projections were used to make a Reconstruction Box and four projections were for image acquisition. Reconstruction Box was made up of voxels of 3D matrix. Projection images were transformed into 3D volume in this virtual box using geometrical based back-projection method. Algorithm was applied to an ellipsoid model and horse-shoe shaped model. Projection images were created using C program language by geometrical method and reconstruction was also accomplished using C program language and Matlab(The Mathwork Inc., USA). For ellipsoid model, reconstructed volume was slightly overestimated but target shape and position was proved to be correct. For horse-shoe shaped model, reconstructed volume was somewhat different from original target model but there was a considerable improvement in target volume determination.