• Journal of The Korean Association For Science Education
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• v.19 no.1
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• pp.1-7
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• 1999

The purpose of this study was to survey the high school students' concern levels on decision-making problems based on biology, This study is a exploratory research to develop teaching strategies and curriculum of the common science for the enhancement of the students' decision-making ability in problems involved biological knowledges. The survey subjects were 101 first graders of the high school in Seoul area. The survey instrument developed was 5-point scale of Likert type consisted of 24 question items. The survey results showed that the concern level on selection of method for learning was the highest. The concern levels on selection of method for sports or diet which are the individual faced problems were high, and concern levels on the problems social issued such as decisions about standard for noise, pros and cons of approval for brain death or artificial abortion were high, too. The students' concern levels on problems individual context were significantly higher than concern levels on problems social context (p<0.01). The males' concern levels were higher than females' on 'AIDS', 'incinerator for rubbish', 'atomic power plant', 'protection policy for decreasing species', 'standard for noise' (p<0.05), And the males' concern levels were higher than females' on domain of 'ecosystem and environment pollution'. But the females had higher concern levels than males on 'diet' and 'surrogate mother' (p<0.05). The analyzed results were discussed in respects of implication for teaching strategies and curriculum.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.6
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• pp.44-49
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• 2009

EAS (electronic article surveillance) systems have increased rapidly for article surveillance. In this paper, the strength of the EMF (electromagnetic fields) of EAS systems were measured. Pacemaker and ICD were investigated for inappropriate response resulting from EM (electromagnetic) EAS systems. The strength of EMF and the response of pacemaker and ICD were measured in the inner left side, outer right sides and the center of gates of the 6.3 kHz and 14.25 kHz EAS systems at a height of 130cm. As the result, EMF of the EAS system using 14.25 kHz was stronger than that of 6.3 kHz. AU interferences were observed only for 14.25 kHz, and the noisy ECG was found in three static positions on the pacemaker. The ICD resulted in noise reversion and VF (ventricular fibrillation) both static and moving positions by the EMP of 14.25 kHz EAS system. Therefore, it is necessary to post a message warning radiation of EMF from every EAS systems and possible risk of pacemakers and ICDs.

• Korean Journal of Radiology
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• v.25 no.4
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• pp.374-383
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• 2024

Objective: To evaluate the diagnostic performance and image quality of 1.5-mm slice thickness MRI with deep learningbased image reconstruction (1.5-mm MRI + DLR) compared to routine 3-mm slice thickness MRI (routine MRI) and 1.5-mm slice thickness MRI without DLR (1.5-mm MRI without DLR) for evaluating temporal lobe epilepsy (TLE). Materials and Methods: This retrospective study included 117 MR image sets comprising 1.5-mm MRI + DLR, 1.5-mm MRI without DLR, and routine MRI from 117 consecutive patients (mean age, 41 years; 61 female; 34 patients with TLE and 83 without TLE). Two neuroradiologists evaluated the presence of hippocampal or temporal lobe lesions, volume loss, signal abnormalities, loss of internal structure of the hippocampus, and lesion conspicuity in the temporal lobe. Reference standards for TLE were independently constructed by neurologists using clinical and radiological findings. Subjective image quality, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were analyzed. Performance in diagnosing TLE, lesion findings, and image quality were compared among the three protocols. Results: The pooled sensitivity of 1.5-mm MRI + DLR (91.2%) for diagnosing TLE was higher than that of routine MRI (72.1%, P < 0.001). In the subgroup analysis, 1.5-mm MRI + DLR showed higher sensitivity for hippocampal lesions than routine MRI (92.7% vs. 75.0%, P = 0.001), with improved depiction of hippocampal T2 high signal intensity change (P = 0.016) and loss of internal structure (P < 0.001). However, the pooled specificity of 1.5-mm MRI + DLR (76.5%) was lower than that of routine MRI (89.2%, P = 0.004). Compared with 1.5-mm MRI without DLR, 1.5-mm MRI + DLR resulted in significantly improved pooled accuracy (91.2% vs. 73.1%, P = 0.010), image quality, SNR, and CNR (all, P < 0.001). Conclusion: The use of 1.5-mm MRI + DLR enhanced the performance of MRI in diagnosing TLE, particularly in hippocampal evaluation, because of improved depiction of hippocampal abnormalities and enhanced image quality.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.504-511
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• 2010

In this paper, we propose the face region recognition system for City-Security CCTV(Closed Circuit Television) using hippocampal neural network which is modelling of human brain's hippocampus. This system is composed of feature extraction, learning and recognition part. The feature extraction part is constructed using PCA(Principal Component Analysis) and LDA(Linear Discriminants Analysis). In the learning part, it can label the features of the image-data which are inputted according to the order of hippocampal neuron structure to reaction-pattern according to the adjustment of a good impression in a dentate gyrus and remove the noise through the auto-associative memory in the CA3 region. In the CA1 region receiving the information of the CA3, it can make long-term memory learned by neuron. Experiments confirm the each recognition rate, that are shape change and light change. The experimental results show that we can compare a feature extraction and learning method proposed in this paper of any other methods, and we can confirm that the proposed method is superior to existing methods.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.1
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• pp.89-97
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• 2011

We analyze the performance of various techniques to overcome degradation of performance of STAP caused by nonhomogeneous clutter. The performance of NHD that used to eliminate outliers from nonhomogeneous clutter is improved by using the projection statistics(PS) that is robust to multiple outliers. The method of clutter covariance matrix estimation using a median value and the conventional method are also investigated and then compared. From the simulation results of STAP, the method of clutter covariance matrix estimation using a median value shows better performance than the conventional method for the calculation of the SINR loss, and MSMI for the single target and the multiple targets regardless of the NHD methods.

• Applied Microscopy
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• v.42 no.2
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• pp.105-109
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• 2012

Electron tomography (ET) of biological specimens is performed from a series of images obtained over a range of tilt angles in a transmission electron microscope. When using the high voltage electron microscope (HVEM), various noises appear in EM images acquired from thick sections by high voltage electron beam. In order to obtain an adequate result in electron tomograms that allow visualization of rather complex and mega-cellular structure such as brain tissue, it is necessary to remove the noise in each original tilt images of thick section. Using band-pass filtering of original tilt images, the filtered images are obtained and used to assemble a reconstructed tomogram. The qualified 3D tomogram from filtered images results in a considerable reduction of the noises compared to conventional tomogram. In conclusion, this study suggests that band-pass filtering is effective to improve the brightness and intensity of HVEM produced tomograms acquired from micron-thick sections of biological specimens.

• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.167-174
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• 2008

The introduction of confocal microscopy makes it possible to observe the structural change of live neuronal cell. Neuro-degenerative disease, such as Alzheimer;s and Parkinson’s diseases are especially related to the morphological change of dendrite spine. That’s the reason for the study of segmentation and extraction from confocal microscope image. The difficulty comes from uneven intensity distribution and blurred boundary. Therefore, the image processing technique which can overcome these problems and extract the structural information should be suggested. In this paper, we propose robust structural information extracting technique with confocal microscopy images of dendrite in brain neurons. First, we apply the nonlinear diffusion filtering that enhance the boundary recognition. Second, we segment region of interest using iterative threshold selection. Third, we perform skeletonization based on Fast Marching Method that extracts centerline and boundary for analysing segmented structure. The result of the proposed method has been less sensitive to noise and has not been affected by rough boundary condition. Using this method shows more accurate and objective results.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1333-1342
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• 2018

Until now, Electroencephalography(: EEG) has been the most important and convenient method for the diagnosis and treatment of epilepsy. However, it is difficult to identify the wave characteristics of an epileptic EEG signals because it is very weak, non-stationary and has strong background noise. In this paper, we analyse the effect of dimensionality reduction methods on Epileptic EEG feature selection and classification. Three dimensionality reduction methods: Pincipal Component Analysis(: PCA), Kernel Principal Component Analysis(: KPCA) and Linear Discriminant Analysis(: LDA） were investigated. The performance of each method was evaluated by using Support Vector Machine SVM, Logistic Regression(: LR), K-Nearestneighbor(: K-NN), Decision Tree(: DR) and Random Forest(: RF). From the experimental result, PCA recorded 75% of highest accuracy in SVM, LR and K-NN. KPCA recorded 85% of best performance in SVM and K-KNN while LDA achieved 100% accuracy in K-NN. Thus, LDA dimensionality reduction is found to provide the best classification result for epileptic EEG signal.

• Korean Journal of Audiology
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• v.24 no.3
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• pp.119-126
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• 2020

Background and Objectives: In distracting listening conditions, individuals need to pay extra attention to selectively listen to the target sounds. To investigate the amount of listening effort required in reverberating and noisy backgrounds, a semantic mismatch was examined. Subjects and Methods: Electroencephalography was performed in 18 voluntary healthy participants using a 64-channel system to obtain N400 latencies. They were asked to listen to sounds and see letters in 2 reverberated×2 noisy paradigms (i.e., Q-0 ms, Q-2000 ms, 3 dB-0 ms, and 3 dB-2000 ms). With auditory-visual pairings, the participants were required to answer whether the auditory primes and letter targets did or did not match. Results: Q-0 ms revealed the shortest N400 latency, whereas the latency was significantly increased at 3 dB-2000 ms. Further, Q-2000 ms showed approximately a 47 ms delayed latency compared to 3 dB-0 ms. Interestingly, the presence of reverberation significantly increased N400 latencies. Under the distracting conditions, both noise and reverberation involved stronger frontal activation. Conclusions: The current distracting listening conditions could interrupt the semantic mismatch processing in the brain. The presence of reverberation, specifically a 2000 ms delay, necessitates additional mental effort, as evidenced in the delayed N400 latency and the involvement of the frontal sources in this study.

• Journal of Audiology & Otology
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• v.24 no.3
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• pp.119-126
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• 2020

Background and Objectives: In distracting listening conditions, individuals need to pay extra attention to selectively listen to the target sounds. To investigate the amount of listening effort required in reverberating and noisy backgrounds, a semantic mismatch was examined. Subjects and Methods: Electroencephalography was performed in 18 voluntary healthy participants using a 64-channel system to obtain N400 latencies. They were asked to listen to sounds and see letters in 2 reverberated×2 noisy paradigms (i.e., Q-0 ms, Q-2000 ms, 3 dB-0 ms, and 3 dB-2000 ms). With auditory-visual pairings, the participants were required to answer whether the auditory primes and letter targets did or did not match. Results: Q-0 ms revealed the shortest N400 latency, whereas the latency was significantly increased at 3 dB-2000 ms. Further, Q-2000 ms showed approximately a 47 ms delayed latency compared to 3 dB-0 ms. Interestingly, the presence of reverberation significantly increased N400 latencies. Under the distracting conditions, both noise and reverberation involved stronger frontal activation. Conclusions: The current distracting listening conditions could interrupt the semantic mismatch processing in the brain. The presence of reverberation, specifically a 2000 ms delay, necessitates additional mental effort, as evidenced in the delayed N400 latency and the involvement of the frontal sources in this study.