• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.87-95
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• 2009

As information theoretic learning techniques, error entropy minimization criterion (MEE) and maximum cross correntropy criterion (MCC) have been studied in depth for supervised learning. MEE criterion leads to maximization of information potential and MCC criterion leads to maximization of cross correlation between output and input random processes. The weighted combination scheme of these two criteria, namely, minimization of Error Entropy with Fiducial points (MEEF) has been introduced and developed by many researchers. As an approach to unsupervised, blind channel equalization, we investigate the possibility of applying constant modulus error (CME) to MEE criterion and some problems of the method. Also we study on the application of CME to MEEF for blind equalization and find out that MEE-CME loses the information of the constant modulus. This leads MEE-CME and MEEF-CME not to converge or to converge slower than other algorithms dependent on the constant modulus.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2158-2165
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• 2007

In this paper, a Modified Fuzzy C-Means algorithm with Gaussian Weights(MFCM_GW) is presented for nonlinear blind channel equalization. The proposed algorithm searches the optimal channel output states of a nonlinear channel from the received symbols, based on the Bayesian likelihood fitness function and Gaussian weighted partition matrix instead of a conventional Euclidean distance measure. Next, the desired channel states of a nonlinear channel are constructed with the elements of estimated channel output states, and placed at the center of a Radial Basis Function(RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a simplex genetic algorithm(GA), a hybrid genetic algorithm(GA merged with simulated annealing(SA): GASA), and a previously developed version of MFCM. It is shown that a relatively high accuracy and fast search speed has been achieved.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.8
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• pp.661-669
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• 2021

A mechanical stiffener has been mainly applied on a PCB to secure fatigue life of a solder joint of an electronic components in spaceborne electronics by minimizing bending displacement of the PCB. However, it causes an increase of mass and volume of the electronics. The high damping PCB implemented by multi-layered viscoelastic tapes of a previous research was effective for assuring the fatigue life of the solder joint, but it also has a limitation to decrease accommodation efficiency for the components on the PCB. In this study, we proposed high damping PCB with a multi-layered superelastic shape memory alloy stiffener for spatialminimized, light-weighted, high-integrated structure design of the electronics. To investigate the basic characteristics of the proposed PCB, a static load test, a free vibration test were performed. Then, the high damping characteristic and the design effectiveness of the PCB were validated through a random vibration test.

• Journal of the Korea Convergence Society
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• v.10 no.10
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• pp.197-205
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• 2019

The purpose of this research was examining the effects of problem-based learning strategies(PBL) on problem solving skill conducted in Korea, using meta-analysis technique. This meta-analysis reviewed the results of 41 studies published between 1998 and 2017 in Korea. The overall weighted mean effect size value was .753 with .064 standard error which was calculated by random effects model. PBL strategies have been found to be more effective in mathematics course (d=.922), art course (d=.916), practical art course (d=.827), E-PBL (d=.791) and middle school level (d=.972). As PBL exhibit a substantial effect on students' problem solving skill, it is recommended that teachers should learn how to implement these strategies in their lesson. PBL is expected to contribute to the improvement of teaching methods as the learning environment changes during the 4th Industrial Revolution.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.5
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• pp.533-539
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• 2019

This study proposes a malware classification model that can handle arbitrary length input data using the Microsoft Malware Classification Challenge dataset. We are based on imaging existing data from malware. The proposed model generates a lot of images when malware data is large, and generates a small image of small data. The generated image is learned as time series data by Dynamic RNN. The output value of the RNN is classified into malware by using only the highest weighted output by applying the Attention technique, and learning the RNN output value by Residual CNN again. Experiments on the proposed model showed a Micro-average F1 score of 92% in the validation data set. Experimental results show that the performance of a model capable of learning and classifying arbitrary length data can be verified without special feature extraction and dimension reduction.

• Journal of Korean Academy of Nursing
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• v.50 no.6
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• pp.740-756
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• 2020

Purpose: The purpose of this study was to evaluate the effect on blood pressure (BP) and heart rate (HR) according to aerobic exercise characteristics in adults with hypertension using a systematic review and meta-analysis. Methods: The related researches were selected from PubMed, EMBASE, Cochrane library, CINAHL, PsycINFO, SPORTDiscus and 5 domestic databases up to September 4, 2019. To estimate the effect size, random effect models were used to derive weighted mean differences (WMD) and their 95% confidence intervals (CI) of aerobic exercise on BP and HR. Results: A total of 37 RCTs with 1,813 samples were included. Aerobic exercise was found to significantly reduce systolic BP (WMD, - 8.29 mmHg; 95% CI, - 10.12 to - 6.46), diastolic BP (WMD, - 5.19 mmHg; 95% CI, - 6.24 to - 4.14) and HR (WMD, - 4.22 beats/min; 95% CI, - 5.36 to -3.09). In detail, systolic BP and diastolic BP were significantly decreased in all groups of exercise types, frequency and duration. Systolic BP and diastolic BP were significantly decreased in the moderate and vigorous-intensity group. Exercise characteristics with the most dramatical change in systolic BP were water-based training, moderate-intensity, 3 times a week and 8 to 11 weeks of duration. In diastolic BP, the greatest effect size was over 24 weeks of exercise. Conclusion: Moderate aerobic exercise, especially water-based exercise can be an important part of lifestyle modification for hypertensive patients. Also, it can be recommended in a variety of clinical settings for lowering BP and HR. However, there is insufficient evidence that low-intensity exercise is effective in lowering BP.

• Restorative Dentistry and Endodontics
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• v.48 no.2
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• pp.16.1-16.11
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• 2023

Objectives: The aim of this study was to evaluate the influence of peak kilovoltage (kVp) and a metal artifact reduction (MAR) tool on image quality and the diagnosis of vertical root fracture (VRF) in cone-beam computed tomography (CBCT). Materials and Methods: Twenty single-rooted human teeth filled with an intracanal metal post were divided into 2 groups: control (n = 10) and VRF (n = 10). Each tooth was placed into the socket of a dry mandible, and CBCT scans were acquired using a Picasso Trio varying the kVp (70, 80, 90, or 99), and the use of MAR (with or without). The examinations were assessed by 5 examiners for the diagnosis of VRF using a 5-point scale. A subjective evaluation of the expression of artifacts was done by comparing random axial images of the studied protocols. The results of the diagnoses were analyzed using 2-way analysis of variance and the Tukey post hoc test, the subjective evaluations were compared using the Friedman test, and intra-examiner reproducibility was evaluated using the weighted kappa test (α = 5%). Results: The kVp and MAR did not influence the diagnosis of VRF (p > 0.05). According to the subjective classification, the 99 kVp protocol with MAR demonstrated the least expression of artifacts, while the 70 kVp protocol without MAR led to the most artifacts. Conclusions: Protocols with higher kVp combined with MAR improved the image quality of CBCT examinations. However, those factors did not lead to an improvement in the diagnosis of VRF.

• Journal of Chest Surgery
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• v.56 no.6
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• pp.374-386
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• 2023

Background: The heightened morbidity and mortality associated with repeat cardiac surgery are well documented. Redo median sternotomy (MS) and minimally invasive valve surgery are options for patients with prior cardiac surgery who require mitral valve surgery (MVS). We conducted a systematic review and meta-analysis comparing the outcomes of redo MS and minimally invasive MVS (MIMVS) in this population. Methods: We searched PubMed, EMBASE, and Scopus for studies comparing outcomes of redo MS and MIMVS for MVS. To calculate risk ratios (RRs) for binary outcomes and weighted mean differences (MDs) for continuous data, we employed a random-effects model. Results: We included 12 retrospective observational studies, comprising 4157 participants (675 for MIMVS; 3482 for redo MS). Reductions in mortality (RR, 0.54; 95% confidence interval [CI], 0.37-0.80), length of hospital stay (MD, -4.23; 95% CI, -5.77 to -2.68), length of intensive care unit (ICU) stay (MD, -2.02; 95% CI, -3.17 to -0.88), and new-onset acute kidney injury (AKI) risk (odds ratio, 0.34; 95% CI, 0.19 to 0.61) were statistically significant and favored MIMVS (p<0.05). No significant differences were observed in aortic cross-clamp time, cardiopulmonary bypass time, or risk of perioperative stroke, new-onset atrial fibrillation, surgical site infection, or reoperation for bleeding (p>0.05). Conclusion: The current literature, which primarily consists of retrospective comparisons, underscores certain benefits of MIMVS over redo MS. These include decreased mortality, shorter hospital and ICU stays, and reduced AKI risk. Given the lack of high-quality evidence, prospective randomized control trials with adequate power are necessary to investigate long-term outcomes.

• Animal Bioscience
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• v.37 no.6
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• pp.1065-1076
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• 2024

Objective: This study aimed to assess the effects of dietary mulberry leaves on the growth, production performance, gut microbiota, and immunological parameters of poultry and livestock. Methods: The PubMed, Embase, and Scopus databases were systematically analyzed to identify pertinent studies up to December 2022. The effects of mulberry leaf diet was assessed using the weighted mean difference, and the 95% confidence interval was calculated using a random-effects model. Results: In total, 18 studies that sampled 2,335 poultry and livestock were selected for analysis. Mulberry leaves improved the average daily gain and reduced the feed/meat ratio in finishing pigs, and the average daily gain and average daily feed intake in chicken. In production performance, mulberry leaves lowered the half carcass weight, slaughter rate, and loin eye area in pigs, and the slaughter rate in chickens. Regarding meat quality in pigs, mulberry leaves reduced the cooked meat percentage, shear force, crude protein, and crude ash, and increased the 24 h pH and water content. In chickens, it increased the drip loss, shear force, 45 min and 24 h pH, crude protein, and crude ash. Mulberry leaves also affect the abundances of gut microbiota, including Bacteroides, Prevotella, Megamonas, Escherichia-Shigella, Butyricicoccus, unclassified Ruminococcaceae, Bifidobacterium, Lactobacillus, and Escherichia coli in poultry and livestock. Mulberry leaves at different doses were associated with changes in antioxidant capacity in chickens, and immune organ indexes in pigs. With respect to egg quality, mulberry leaves at different doses improved the shell strength, yolk color, eggshell thickness, and eggshell weight. However, moderate doses diminished the egg yolk ratio and the egg yolk moisture content. Conclusion: In general, dietary mulberry leaves improved the growth, production performance, and immunological parameters in poultry and livestock, although the effects varied at different doses.

• Atmosphere
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• v.34 no.2
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• pp.177-185
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• 2024

As increasing global interest in renewable energy due to the ongoing climate crisis, there is a growing need for efficient technologies to manage such resources. This study focuses on the predictive skill of daily solar power generation using weather observation and forecast data. Meteorological data from the Korea Meteorological Administration and solar power generation data from the Korea Power Exchange were utilized for the period from January 2017 to May 2023, considering both inland (Daejeon) and coastal (Busan) regions. Temperature, wind speed, relative humidity, and precipitation were selected as relevant meteorological variables for solar power prediction. All data was preprocessed by removing their systematic components to use only their residuals and the residual of solar data were further processed with weighted adjustments for homoscedasticity. Four models, MLR (Multiple Linear Regression), RF (Random Forest), DNN (Deep Neural Network), and RNN (Recurrent Neural Network), were employed for solar power prediction and their performances were evaluated based on predicted values utilizing observed meteorological data (used as a reference), 1-day-ahead forecast data (referred to as fore1), and 2-day-ahead forecast data (fore2). DNN-based prediction model exhibits superior performance in both regions, with RNN performing the least effectively. However, MLR and RF demonstrate competitive performance comparable to DNN. The disparities in the performance of the four different models are less pronounced than anticipated, underscoring the pivotal role of fitting models using residuals. This emphasizes that the utilized preprocessing approach, specifically leveraging residuals, is poised to play a crucial role in the future of solar power generation forecasting.