• Journal of IKEEE
• /
• v.23 no.2
• /
• pp.529-533
• /
• 2019

Combined cycle power plants are often used to produce power. These days prediction of power plant output based on operating parameters is a major concern. This paper presents an approach to using computational intelligence technique to predict the output power of combined cycle power plant. Computational intelligence techniques have been developed and applied to many real world problems. In this paper, tree architectures of fuzzy neural networks are considered to predict the output power. Tree architectures of fuzzy neural networks have an advantage of reducing the number of rules by selecting fuzzy neurons as nodes and relevant inputs as leaves optimally. For the optimization of the networks, two-step optimization method is used. Genetic algorithms optimize the binary structure of the networks by selecting the nodes and leaves as binary, and followed by random signal-based learning further refines the optimized binary connections in the unit interval. To verify the effectiveness of the proposed method, combined cycle power plant dataset obtained from the UCI Machine Learning Repository Database is considered.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.3
• /
• pp.291-298
• /
• 2019

In this paper, we propose a Fresnel transform method using various wavelet functions to efficiently decompose digital holograms. After implementing the proposed wavelet function-based Fresnelet transforms, we apply it to the digital hologram and analyze the energy characteristics of the coefficients. The implemented wavelet transform-based Fresnelet transform is well suited for reconstructing and processing holograms which are optically obtained or generated by computer-generated hologram technique. After analyzing the characteristics of the spline function, we discuss wavelet multiresolution analysis method based on it. Through this process, we proposed a transform tool that can effectively decompose fringe patterns generated by optical interference phenomena. We implement Fresnelet transform based on wavelet function with various decomposition properties and show the results of decomposing fringe pattern using it. The results show that the energy distribution of the coefficients is significantly different depending on whether the random phase is included or not.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.12
• /
• pp.4946-4960
• /
• 2020

In a device-to-device (D2D) underlaid cellular network, there exist two types of co-channel interference. One type is inter-layer interference caused by spectrum reuse between D2D transmitters and cellular users (CUEs). Another type is intra-layer interference caused by spectrum sharing among D2D pairs. To mitigate the inter-layer interference, we first derive the interference limited area (ILA) to protect the coverage probability of cellular users by modeling D2D users' location as a Poisson point process, where a D2D transmitter is allowed to reuse the spectrum of the CUE only if the D2D transmitter is outside the ILA of the CUE. To coordinate the intra-layer interference, the spectrum sharing criterion of D2D pairs is derived based on the (signal-to-interference ratio) SIR requirement of D2D communication. Based on this criterion, D2D pairs are allowed to share the spectrum when one D2D pair is far from another sufficiently. Furthermore, to maximize the energy efficiency of the system, a resource allocation scheme is proposed according to weighted graph coloring theory and the proposed ILA restriction. Simulation results show that our proposed scheme provides significant performance gains over the conventional scheme and the random allocation scheme.

• Journal of the Korean Magnetic Resonance Society
• /
• v.24 no.4
• /
• pp.136-142
• /
• 2020

Apolipoprotein B-100 (apo B-100), the main protein component that makes up LDL (Low density lipoprotein), consists of 4,536 amino acids and serves to combine with the LDL receptor. The oxidized LDL peptides by malondialdehyde (MDA) or acetylation in vivo were act as immunoglobulin (Ig) antigens and peptide groups were classified into 7 peptide groups with subsequent 20 amino acids (P1-P302). The biomimetic peptide P99 (KGTYG LSCQR DPNTG RLNGE) out of B-group peptides carrying the highest value of IgM antigens were selected for structural studies that may provide antigen specificity. Circular Dichroism (CD) spectra were measured for peptide secondary structure in the range of 190-260 nm. Experimental results show that P99 has pseudo α-helice and random coil structure. Homonuclear (COSY, TOCSY, NOESY) 2D-NMR experiments were carried out for NMR signal assignments and structure determination for P99. On the basis of these completely assigned NMR spectra and proton distance information, distance geometry (DG) and molecular dynamic (MD) were carried out to determine the structures of P99. The proposed structure was selected by comparisons between experimental NOE spectra and back-calculated 2D NOE results from determined structure showing acceptable agreement. The total Root-Mean-Square-Deviation (RMSD) value of P99 obtained upon superposition of all atoms were in the set range. The solution state P99 has mixed structure of pseudo α-helix and β-turn(Gln[9] to Thr[13]). These NMR results are well consistent with secondary structure from experimental results of circular dichroism. Structural studies based on NMR may contribute to the prevent oxidation studies of atherosclerosis and observed conformational characteristics of apo B-100 in LDL using monoclonal antibodies.

• Journal of The Korean Astronomical Society
• /
• v.55 no.2
• /
• pp.23-36
• /
• 2022

We present a method to determine nitrogen abundance ratios with respect to iron ([N/Fe]) from molecular CN-band features observed in low-resolution (R ~ 2000) stellar spectra obtained by the Sloan Digital Sky Survey (SDSS) and the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). Various tests are carried out to check the systematic and random errors of our technique, and the impact of signal-to-noise (S/N) ratios of stellar spectra on the determined [N/Fe]. We find that the uncertainty of our derived [N/Fe] is less than 0.3 dex for S/N ratios larger than 10 in the ranges T_eff = [4000, 6000] K, log g = [0.0, 3.5], [Fe/H] = [-3.0, 0.0], [C/Fe] = [-1.0, +4.5], and [N/Fe] = [-1.0, +4.5], the parameter space that we are interested in to identify N-enhanced stars in the Galactic halo. A star-by-star comparison with a sample of stars with [N/Fe] estimates available from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) also suggests a similar level of uncertainty in our measured [N/Fe], after removing its systematic error. Based on these results, we conclude that our method is able to reproduce [N/Fe] from low-resolution spectroscopic data, with an uncertainty sufficiently small to discover N-rich stars that presumably originated from disrupted Galactic globular clusters.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.2
• /
• pp.135-144
• /
• 2022

Electromagnetic topology (EMT) technique is a method to analyze each component of the electromagnetic propagation environment and combine them in the form of a network in order to effectively model the complex propagation environment. In a typical commercial communication channel model, since the propagation environment is complex and difficult to predict, a probabilistic propagation channel model that utilizes an average solution, although with low accuracy, is used. However, modeling techniques using EMT technique are considered for application of propagation and coupling analysis of threat electromagnetic waves such as electromagnetic pulses, radio wave models used in electronic warfare, local communication channel models used in 5G and 6G communications that require relatively high accuracy electromagnetic wave propagation characteristics. This paper describes the effective implementation method, algorithm, and program implementation of the electromagnetic topology (EMT) method analyzed in the frequency domain. Also, a method of deriving a response in the time domain to an arbitrary applied signal source with respect to the EMT analysis result in the frequency domain will be discussed.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.6
• /
• pp.741-747
• /
• 2022

Fatigue lowers an individual's ability and makes it difficult to perform work. As fatigue accumulates, concentration decreases and thus the possibility of causing a safety accident increases. Awareness of fatigue is subjective, but it is necessary to quantitatively measure the level of fatigue in the actual field. In previous studies, it was proposed to measure the level of fatigue by expert judgment by adding objective indicators such as bio-signal analysis to subjective evaluations such as multidisciplinary fatigue scales. However this method is difficult to evaluate fatigue in real time in daily life. This paper is a study on the fatigue classification model that determines the fatigue level of workers in real time using speech data recorded in the field. Machine learning models such as logistic classification, support vector machine, and random forest are trained using speech data collected in the field. The performance evaluation showed good performance with accuracy of 0.677 to 0.758, of which logistic classification showed the best performance. From the experimental results, it can be seen that it is possible to classify the fatigue level using speech signals.

• Journal of The Korean Society of Integrative Medicine
• /
• v.11 no.1
• /
• pp.131-140
• /
• 2023

Purpose : The purpose of this study is to find out which shoulder abduction angle among the three representative angles of lower trapezius strengthening exercises most effectively improves rounded shoulder posture. Methods : Thirty-one people with rounded shoulders, the subjects of this study, were selected. With the use of a random number table, group A was randomly assigned to a Y-type exercise, group B to a T-type exercise, and group C to an MPC exercise. In the prone position, both arms are abducted at the angles suggested for each group (145 °, 90 °, and 45 °, respectively), and the hands are holding dumbbells to assume a functional posture. With the start signal, the thumb raised the arm to the sky and the arm is raised to the level of the ear for 10 seconds and then returned to the original position. Each week, the strength required was increased by changing the resistance weight, number of times, and set, and the exercise was performed three times a week for a total of four weeks. Results : There was a significant difference in the change in shoulder height of each group after four weeks of exercise in comparison to the amount of change in height before and after exercise in all groups (p<.05). However, no significant difference was observed between all groups in the change in muscle activity of the lower trapezius muscle in each group following four weeks of exercise (p>.05). Conclusion : The results of this study showed that the three lower trapezius strengthening exercises have a positive effect on the improvement of rounded shoulders. In consideration of these results, it is therefore proposed that the various lower trapezius strengthening exercises be applied in parallel during physical therapy for patients with rounded shoulders in clinical practice.

• Proceedings of the Korean Society of Plant Pathology Conference
• /
• 2003.10a
• /
• pp.66.2-66
• /
• 2003

A gain-of-function mutant, SHM-11 obtained through gamma-ray mutagenesis, is resistant to rice blast caused by Magnaporthe grisea while wild type Sanghaehyanghyella is highly susceptible to the same disease. The resistance in the mutant was not race-specific when we tested with four races (KJ-201, KI-1113a, KI-313, KI-409) of M. grisea. To identify genes involved disease resistance in the gain-of-function mutant, genes specifically expressed in the mutant were selected by suppression subtractive hybridization using cDNAS of blast-inoculated mutant and wild type as a tester and a driver, respectively, Random 200 clones from the subtracted library were selected and analyzed by DNA sequencing. The sequenced genes represented three major groups related with disease resistance； genes encoding PR proteins, genes probably for phytoalexin biosynthesis, and genes involved in disease resistance signal transduction. A gene encoding a putative receptor-like protein kinase was identified as highly expressed only in the gain-of-function mutant after blast infection. The role of the putative receptor-like protein kinase gene during blast resistance will be further studied.

• Current Optics and Photonics
• /
• v.7 no.3
• /
• pp.237-247
• /
• 2023

In middle- and long-distance imaging systems, due to the atmospheric turbulence caused by temperature, wind speed, humidity, and so on, light waves propagating in the air are distorted, resulting in image-quality degradation such as geometric deformation and fuzziness. In remote sensing, astronomical observation, and traffic monitoring, image information loss due to degradation causes huge losses, so effective restoration of degraded images is very important. To restore images degraded by atmospheric turbulence, an image-restoration method based on improved compound multibranch feature fusion (CMFNetPro) was proposed. Based on the CMFNet network, an efficient channel-attention mechanism was used to replace the channel-attention mechanism to improve image quality and network efficiency. In the experiment, two-dimensional random distortion vector fields were used to construct two turbulent datasets with different degrees of distortion, based on the Google Landmarks Dataset v2 dataset. The experimental results showed that compared to the CMFNet, DeblurGAN-v2, and MIMO-UNet models, the proposed CMFNetPro network achieves better performance in both quality and training cost of turbulent-image restoration. In the mixed training, CMFNetPro was 1.2391 dB (weak turbulence), 0.8602 dB (strong turbulence) respectively higher in terms of peak signal-to-noise ratio and 0.0015 (weak turbulence), 0.0136 (strong turbulence) respectively higher in terms of structure similarity compared to CMFNet. CMFNetPro was 14.4 hours faster compared to the CMFNet. This provides a feasible scheme for turbulent-image restoration based on deep learning.