• International journal of advanced smart convergence
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• v.12 no.4
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• pp.434-442
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• 2023

The relationship between acute kidney injury (AKI) prediction and nephrotoxic drugs, or drugs that adversely affect kidney function, is one that has yet to be explored in the critical care setting. One contributing factor to this gap in research is the limited investigation of drug modalities in the intensive care unit (ICU) context, due to the challenges of processing prescription data into the corresponding drug representations and a lack in the comprehensive understanding of these drug representations. This study addresses this gap by proposing a novel approach that leverages patient prescription data as a modality to improve existing models for AKI prediction. We base our research on Electronic Health Record (EHR) data, extracting the relevant patient prescription information and converting it into the selected drug representation for our research, the extended-connectivity fingerprint (ECFP). Furthermore, we adopt a unique multimodal approach, developing machine learning models and 1D Convolutional Neural Networks (CNN) applied to clinical drug representations, establishing a procedure which has not been used by any previous studies predicting AKI. The findings showcase a notable improvement in AKI prediction through the integration of drug embeddings and other patient cohort features. By using drug features represented as ECFP molecular fingerprints along with common cohort features such as demographics and lab test values, we achieved a considerable improvement in model performance for the AKI prediction task over the baseline model which does not include the drug representations as features, indicating that our distinct approach enhances existing baseline techniques and highlights the relevance of drug data in predicting AKI in the ICU setting.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.9
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• pp.497-507
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• 2014

This paper investigates the standard features of Carrier aggregation (CA), the related UE RF requirements in 3GPP release 12 and estimated CA evolution in future. The main CA feature of 3GPP release 12 in WG4 perspectives includes 2Uplink(UL) CA, 3Downlink(DL) CA and TDD-FDD CA. To support these features in UE, UE-to-UE coexistence problem and RF requirements generated by unwanted emissions such as inter-modulation and harmonics are analyzed. Also, future CA technology such as LTE in unlicensed bands is described.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.225-227
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• 2003

Traditional photogrammetry and satellite image rectification technique have been developed based on control-points for many decades. These techniques are driven from linked points in image space and the corresponding points in the object space in rigorous colinearity or coplanarity conditions. Recently, digital imagery facilitates the opportunity to use features as well as points for images rectification. These implementations were mainly based on rigorous models that incorporated geometric constraints into the bundle adjustment and could not be applied to the new high-resolution satellite imagery (HRSI) due to the absence of sensor calibration and satellite orbit information. This research is an attempt to establish a new Line Based Transformation Model (LBTM), which is based on linear features only or linear features with a number of ground control points instead of the traditional models that only use Ground Control Points (GCPs) for satellite imagery rectification. The new model does not require any further information about the sensor model or satellite ephemeris data. Synthetic as well as real data have been demonestrated to check the validity and fidelity of the new approach and the results showed that the LBTM can be used efficiently for rectifying HRSI.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.4
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• pp.374-381
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• 2021

Raman spectrometers are studied and developed for the military purposes because of their nondestructive inspection capability to capture unique spectral features induced by molecular structures of colorless and odorless chemical warfare agents(CWAs) in any phase. Raman spectrometers often suffer from random noise caused by their detector inherent noise, background signal, etc. Thus, reducing the random noise in a measured Raman spectrum can help detection algorithms to find spectral features of CWAs and effectively detect them. In this paper, we propose a denoising autoencoder for Raman spectra with a loss function for sample efficient learning using noisy dataset. We conduct experiments to compare its effect on the measured spectra and detection performance with several existing noise reduction algorithms. The experimental results show that the denoising autoencoder is the most effective noise reduction algorithm among existing noise reduction algorithms for Raman spectrum based standoff detection of CWAs.

• Applied Microscopy
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• v.45 no.4
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• pp.208-213
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• 2015

Nanomanipulators installed in focused ion beam (FIB), which is used in the lift-out of lamella when preparing transmission electron microscopy specimens, have recently been employed for electrical resistance measurements, tensile and compression tests, and in situ reactions. During the pick-up process of a single nanowire (NW), there are crucial problems such as Pt, C and Ga contaminations, damage by ion beam, and adhesion force by electrostatic attraction and residual solvent. On the other hand, many empirical techniques should be considered for successful pick-up process, because NWs have the diverse size, shape, and angle on the growth substrate. The most important one in the in-situ precedence, therefore, is to select the optimum pick-up process of a single NW. Here we provide the advanced methodologies when manipulating NWs for in-situ mechanical and electrical measurements in FIB.

• The Journal of the Acoustical Society of Korea
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• v.25 no.2E
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• pp.74-78
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• 2006

This paper proposes an effective method for classifying emotions of the music from its acoustical signals. Two feature sets, timbre and tempo, are directly extracted from the modified discrete cosine transform coefficients (MDCT), which are the output of partial MP3 (MPEG 1 Layer 3) decoder. Our tempo feature extraction method is based on the long-term modulation spectrum analysis. In order to effectively combine these two feature sets with different time resolution in an integrated system, a classifier with two layers based on AdaBoost algorithm is used. In the first layer the MDCT-driven timbre features are employed. By adding the MDCT-driven tempo feature in the second layer, the classification precision is improved dramatically.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.78.4-79
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• 2017

Thermal inflation is an additional inflationary mechanism before the big bang nucleosynthesis, which solves the moduli problem and naturally provides a plausible dark matter candidate. Thermal inflation leaves a slight enhancement followed by huge suppression of a factor of ~50 in the curvature and matter power spectrum, which can be expressed in terms of a single characteristic scale $k_b$. Here we describe the observability of the small-scale features of thermal inflation from various observations, such as CMB distortion, satellite galaxy abundance in the Milky-Way-sized galaxies, and 21-cm power spectrum before the epoch of reionization.

• Journal of Mechanical Science and Technology
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• v.15 no.12
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• pp.1728-1738
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• 2001

Measurements have been made in an automotive HVAC b1ower for two different centrifugal fans. This work is directed at improving the performance of a conventional forward-curved centrifugal fan for a given small blower casing. Mean velocities and pressure have been measured using a miniature five-hole probe and a pressure scanning unit connected to an online data acquisition system. First, we obtained the fan performance versus flow rates showing a significant attenuation of unstable nature achieved with the new fan rotor in the surging operation range. Second, aerodynamic characterizations were carried out by investigating the velocity and pressure fields in the casing flow passage for different fan operating conditions. The measurements stowed that performance coefficients are strongly influenced by flow characteristics at the throat region. The main flow features ware common in both fans, but improved performance is achieved with tole new fan rotor, particularly in lower flow rate legions. Based on the measured results, design improvements were carried out in an acceptable operation range, which gave considerable insight into what features of flow behavior ware most important.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.45-54
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• 2018

This paper presents a vision-based fall detection system to automatically monitor and detect people's fall accidents, particularly those of elderly people or patients. For video analysis, the system should be able to extract both spatial and temporal features so that the model captures appearance and motion information simultaneously. Our approach is based on 3-dimensional convolutional neural networks, which can learn spatiotemporal features. In addition, we adopts a thermal camera in order to handle several issues regarding usability, day and night surveillance and privacy concerns. We design a pan-tilt camera with two actuators to extend the range of view. Performance is evaluated on our thermal dataset: TCL Fall Detection Dataset. The proposed model achieves 90.2% average clip accuracy which is better than other approaches.

• Tuberculosis and Respiratory Diseases
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• v.83 no.2
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• pp.107-115
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• 2020

Aging is often viewed as a progressive decline in fitness due to cumulative deleterious alterations of biological functions in the living system. Recently, our understanding of the molecular mechanisms underlying aging biology has significantly advanced. Interestingly, many of the pivotal molecular features of aging biology are also found to contribute to the pathogenesis of chronic lung disorders such as chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis, for which advanced age is the most crucial risk factor. Thus, an enhanced understanding of how molecular features of aging biology are intertwined with the pathobiology of these aging-related lung disorders has paramount significance and may provide an opportunity for the development of novel therapeutics for these major unmet medical needs. To serve the purpose of integrating molecular understanding of aging biology with pulmonary medicine, in this review, recent findings obtained from the studies of aging-associated lung disorders are summarized and interpreted through the perspective of molecular biology of aging.