• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.25-33
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• 2016

In order to visualize point based Location-Based Social Network Services(LBSNS) data on multi-scaled tile map effectively, it is necessary to apply tile-based clustering method. Then determinating reasonable numbers and size of tiles is required. However, there is no such criteria and the numbers and size of tiles are modified based on data type and the purpose of analysis. In other words, researchers' subjectivity is always involved in this type of study. This is when Modifiable Areal Unit Problem(MAUP) occurs, that affects the results of analysis. Among LBSNS, geotagged Twitter data were chosen to find the influence of MAUP in scale effects perspective. For this purpose, the degree of spatial autocorrelation using spatial error model was altered, and change of distributions was analyzed using Morna's I. As a result, positive spatial autocorrelation showed in the original data and the spatial autocorrelation was decreased as the value of spatial autoregressive coefficient was increasing. Therefore, the intensity of the spatial autocorrelation of Twitter data was adjusted to five levels, and for each level, nine different size of grid was created. For each level and different grid sizes, Moran's I was calculated. It was found that the spatial autocorrelation was increased when the aggregation level was being increased and decreased in a certainpoint. Another tendency was found that the scale effect of MAUP was decreased when the spatial autocorrelation was high.

• Journal of Ecology and Environment
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• v.43 no.2
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• pp.191-201
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• 2019

Macroecologists and biogeographers continue to predict the distribution of species across space based on the relationship between biotic processes and environmental variables. This approach uses data related to, for example, species abundance or presence/absence, climate, geomorphology, and soils. Researchers have acknowledged in their statistical analyses the importance of accounting for the effects of spatial autocorrelation (SAC), which indicates a degree of dependence between pairs of nearby observations. It has been agreed that residual spatial autocorrelation (rSAC) can have a substantial impact on modeling processes and inferences. However, more attention should be paid to the sources of rSAC and the degree to which rSAC becomes problematic. Here, we review previous studies to identify diverse factors that potentially induce the presence of rSAC in macroecological and biogeographical models. Furthermore, an emphasis is put on the quantification of rSAC by seeking to unveil the magnitude to which the presence of SAC in model residuals becomes detrimental to the modeling process. It turned out that five categories of factors can drive the presence of SAC in model residuals: ecological data and processes, scale and distance, missing variables, sampling design, and assumptions and methodological approaches. Additionally, we noted that more explicit and elaborated discussion of rSAC should be presented in species distribution modeling. Future investigations involving the quantification of rSAC are recommended in order to understand when rSAC can have an adverse effect on the modeling process.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.1
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• pp.33-40
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• 2010

Because sampling interval for data collection tends to be short compared with the overall processing time, in chemical process, instrumental process related tanks or furnace collected data have a significant autocorrelation. Insufficient control technique and frequent control actions cause unstable condition of the process. Traditional control charts which were developed based on iid (independently and identically distributed) among data cannot be applied on the existence of autocorrelation. Also unstable process is difficult to identity or diagnose. Because large-scale process has a lot of measurable variables and multi-step-structures among data, it is difficult to find relation between measurable variables and nonconformity. In this paper, we suggested an appicable model to diagnose the process and to find relation between measurable variables (CTQ) and nonconformity in the process having autocorrelation, unstable condition frequently, a lot of measurable variables, and multi-step-structure. And we applied this model to real process, to verify that the process engineers could easily and effectively diagnose the process and control the nonconformity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.3
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• pp.557-561
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• 1997

In this paper, we present three new classes of binary pseudorandom sequences of period ${2_n}-1$ with ideal autocorrelation. These sequences are newly found by an extensive computer search, and the conjectures on the construction of these sequences are formulated. We also classify the binary sequences of period ${2_n}-1$ with ideal autocorrelation, and enumerate them.

• Journal of the Korea Institute of Military Science and Technology
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• v.6 no.1
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• pp.59-67
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• 2003

Multipath is an inevitable error source in radio navigation system such as GPS, it causes signal tracking errors such as carrier tracking errors, code tracking errors. Since code tracking error is a dominant error in absolute positioning, this paper focuses on the improvement of code tracking performance. This paper proposes a method that detects the change of autocorrelation function's slope and mitigates the multipath error. Also, this paper shows the performance evaluation results by post-processing the digitized RF samples.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.7C
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• pp.915-920
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• 2004

In this paper, we propose the new polyphase sequence with the best nonperiodic autocorrelation property in the viewpoint of the merit factors, which are important criteria for a nonperiodic autocorrelation property. We propose the general implementation of a polyphase sequence generator over an integer residue ring by using a linear feedback shift register(LFSR), in addition, we analyze the linear complexities of polyphase sequences based on the proposed implementation method.

• The Korean Journal of Ecology
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• v.22 no.6
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• pp.349-354
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• 1999

The spatial distributions of allelic frequencies and ecological traits by randomization were studied in the natural population of two species (Pinus rigida and Pyrola japonica). Both species showed significant positive spatial autocorrelation as measured by Moran's I. In P. rigida, the genetic similarity was shown in individuals within up to a scale of 18 m distance and this is partly due to combination of pollen and seed dispersal by wind or men. In P. japonica, significant spatial autocorrelation was consisted of a scale of 8 m intervals. These population structure in the distribution of allelic frequencies is related to mating systems such as outcrossing and vegetative spread. The results also indicate that positive species associations between P. rigida and P. japonica can occur when both species select the same habitat or require the same environmental conditions.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.2
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• pp.80-87
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• 1994

Fetal monitoring is a routine procedure to obtain a record of physiologic functions during pregnancy and labor. It is required to determine fetal heart frequency accurately. There are various types of fetal heart rate(FHR) determination and the most frequently applied method is transabdominal Doppler ultrasound. However, in the case of weak or noise corrupted Doppler ultrasound signals, conventional peak detections and the autocorrelation function method have many difficulties to determine FHR precisely. Also the autocorrelation function is effected by threshold level and window size. To solve these problems, the high resolution pitch determination algorinthm is introduced to detect FHR from Doppler ultrasound signals. This scheme digitally processes Doppler ultrasound signal for digital rectification, envelope detection, decimation and correlation calculation of two interconnected segments and then FHR is determined by its maximal value. Even in the case of a greatly smeared noise signal, this algorithm is able to search FHR more accurately than autocorrelation function by means of compensating FHR with a constant correlation threshold. This algorithm is simulated by 386-MATLAB on PC 486/DX and verified that it is superior to the autocorrelation function method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.6C
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• pp.582-588
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• 2006

In this paper, the relationship among M-ary Sidel'nikov sequences generated by different primitive elements and decimation are studied. Their autocorrelation function and autocorrelation distribution are derived. It is proved that Sidel'nikov sequences for a given period are equivalent under the decimation, cyclic shift, and scalar multiplication of the sequence.

• Journal of the Optical Society of Korea
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• v.20 no.3
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• pp.435-440
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• 2016

We developed a simple and real-time readout autocorrelator for several tens and sub-10fs pulses, based on the two photon absorption phenomena of a commercial GaP photodetector including a transimpedance amplifier. With a suitable gain adjustment, we demonstrated that the interferometric autocorrelation for sub-nJ pulses delivered as a high output voltage as to resolve all fringes in an autocorrelation trace with features of low noise and a low offset voltage. By fitting the measured quadratic power dependence of output voltages, we obtained the quantum efficiency of TPA for the GaP detector comparable with those of a GaAsP diode and an SHG with a thin BBO crystal. The autocorrelator of a TPA based GaP photodetector is highly suitable for sensitively measuring a few cycle pulses with a broad spectral distribution from 600 nm to 1100 nm.