• Journal of the Korea Institute of Military Science and Technology
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• v.6 no.1
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• pp.91-107
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• 2003

A 2-dimensional search process in the time and frequency domain is required to acquire the GPS signal, when the code phase and the carrier Doppler for the specified GPS satellite signal are unknown. This paper proposes a new scheme, called Squared-D Searching Method, which can reduce the number of carrier frequency candidates, and a new scheme, named extended Multiple Correlator(XMC), which can reduce the number of code phase candidates. The Squared-D Searching Method can take the twice of Doppler frequency, therefore it can find carrier frequency candidates. The XMC is different from the general multiple correlator in that a combined form of the locally generated codes is used for despreading. Also, this paper tries to analyze a signal detection probability of a GPS receiver under more realistic environments. The result shows that lower detection probability can be obtained when the phase differences among the codes are larger in the correlation arms of a multiple correlator. This phenomenon is not easy to explain with the previous results. And besides, the result shows that proposed acquisition schemes give better performance than a conventional acquisition scheme.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.107-110
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• 2003

In this paper, the optimal position selection of error sensors and transducers to attenuate interior noise from outside noise sources using active control techniques is presented. To get an optimal control characteristics in adaptive noise control systems, it is necessary to optimize the positions of sensors and transducers. A new type of simulated annealing method has been proposed as searching technique to find optimal transducers and sensors positions in which the sum of the squared pressures at sensor position in an enclosure can be best minimized. Computer simulations and experiments have been performed to show the effectiveness of the proposed method.

• Journal of International Society for Simulation Surgery
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• v.2 no.1
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• pp.26-32
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• 2015

Purpose When a surgeon examines the morphology of skull of patient, locations of craniometric landmarks of 3D computed tomography(CT) volume are one of the most important information for surgical purpose. The locations of craniometric landmarks can be found manually by surgeon from the 3D rendered volume or 2D sagittal, axial, and coronal slices which are taken by CT. Since there are many landmarks on the skull, finding these manually is time-consuming, exhaustive, and occasionally inexact. These inefficiencies raise a demand for a automatic localization technique for craniometric landmark points. So in this paper, we propose a novel method through which we can automatically find these landmark points, which are useful for surgical purpose. Materials and Methods At first, we align the experimental data (CT volumes) using Frankfurt Horizontal Plane (FHP) and Mid Sagittal Plane(MSP) which are defined by 3 and 2 cranial landmark points each. The target landmark of our experiment is the anterior nasal spine. Prior to constructing a statistical cubic model which would be used for detecting the location of the landmark from a given CT volume, reference points for the anterior nasal spine were manually chosen by a surgeon from several CT volume sets. The statistical cubic model is constructed by calculating weighted intensity means of these CT sets around the reference points. By finding the location where similarity function (squared difference function) has the minimal value with this model, the location of the landmark can be found from any given CT volume. Results In this paper, we used 5 CT volumes to construct the statistical cubic model. The 20 CT volumes including the volumes, which were used to construct the model, were used for testing. The range of age of subjects is up to 2 years (24 months) old. The found points of each data are almost close to the reference point which were manually chosen by surgeon. Also it has been seen that the similarity function always has the global minimum at the detection point. Conclusion Through the experiment, we have seen the proposed method shows the outstanding performance in searching the landmark point. This algorithm would make surgeons efficiently work with morphological informations of skull. We also expect the potential of our algorithm for searching the anatomic landmarks not only cranial landmarks.