Cavaleri, Liborio;Chatzarakis, George E.;Trapani, Fabio Di;Douvika, Maria G.;Roinos, Konstantinos;Vaxevanidis, Nikolaos M.;Asteris, Panagiotis G.
Advances in materials Research
/
v.6
no.2
/
pp.169-184
/
2017
Electro-Discharge machining (EDM) is a thermal process comprising a complex metal removal mechanism. This method works by forming of a plasma channel between the tool and the workpiece electrodes leading to the melting and evaporation of the material to be removed. EDM is considered especially suitable for machining complex contours with high accuracy, as well as for materials that are not amenable to conventional removal methods. However, several phenomena can arise and adversely affect the surface integrity of EDMed workpieces. These have to be taken into account and studied in order to optimize the process. Recently, artificial neural networks (ANN) have emerged as a novel modeling technique that can provide reliable results and readily, be integrated into several technological areas. In this paper, we use an ANN, namely, the multi-layer perceptron and the back propagation network (BPNN) to predict the mean surface roughness of electro-discharge machined surfaces. The comparison of the derived results with experimental findings demonstrates the promising potential of using back propagation neural networks (BPNNs) for getting a reliable and robust approximation of the Surface Roughness of Electro-discharge Machined Components.
Kim, Ghiseok;Kim, Dae-Yong;Kim, Geon Hee;Cho, Byoung-Kwan
Journal of Biosystems Engineering
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v.38
no.1
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pp.48-54
/
2013
Purpose: This study evaluated the feasibility of using a discrete wavelet transform (DWT) method as a preprocessing tool for visible/near-infrared spectroscopy (VIS/NIRS) with a spectroscopic transmittance dataset for predicting the internal quality of cherry tomatoes. Methods: VIS/NIRS was used to acquire transmittance spectrum data, to which a DWT was applied to generate new variables in the wavelet domain, which replaced the original spectral signal for subsequent partial least squares (PLS) regression analysis and prediction modeling. The DWT concept and its importance are described with emphasis on the properties that make the DWT a suitable transform for analyzing spectroscopic data. Results: The $R^2$ values and root mean squared errors (RMSEs) of calibration and prediction models for the firmness, sugar content, and titratable acidity of cherry tomatoes obtained by applying the DWT to a PLS regression with a set of spectra showed more enhanced results than those of each model obtained from raw data and mean normalization preprocessing through PLS regression. Conclusions: The developed DWT-incorporated PLS models using the db5 wavelet base and selected approximation coefficients indicate their feasibility as good preprocessing tools by improving the prediction of firmness and titratable acidity for cherry tomatoes with respect to $R^2$ values and RMSEs.
Background: The pain caused by local anesthetic injection can lead to patient anxiety prior to surgery, potentially necessitating sedation or general anesthesia during the excision procedure. In this study, we aim to compare the pain relief efficacy and safety of using a digital automatic anesthetic injector for local anesthesia. Methods: Thirty-three patients undergoing excision of a benign soft tissue tumor under local anesthesia were prospectively enrolled from September 2021 to February 2022. A single-blind, randomized controlled study was conducted. Patients were divided into two groups by randomization: the experimental group with digital automatic anesthetic injector method (I-JECT group) and the control group with conventional injection method. Before surgery, the Amsterdam preoperative anxiety information scale was used to measure the patients' anxiety. After local anesthetic was administered, the Numeric Pain Rating Scale was used to measure the pain. The amount of anesthetic used was divided by the surface area of the lesion was recorded. Results: Seventeen were assigned to the conventional group and 16 to the I-JECT group. The mean Numeric Pain Rating Scale was 1.75 in the I-JECT group and 3.82 in conventional group. The injection pain was lower in the I-JECT group (p< 0.01). The mean Amsterdam preoperative anxiety information scale was 11.00 in the I-JECT group and 9.65 in conventional group. Patient's anxiety did not correlate to injection pain regardless of the method of injection (p= 0.47). The amount of local anesthetic used per 1 cm2 of tumor surface area was 0.74 mL/cm2 in the I-JECT group and 2.31 mL/cm2 in the conventional group. The normalization amount of local anesthetic was less in the I-JECT group (p< 0.01). There was no difference in the incidence of complications. Conclusion: The use of a digital automatic anesthetic injector has shown to reduce pain and the amount of local anesthetics without complication.
Kim, Jae-hun;Ha, Sang-woo;Choi, Jin-gyu;Son, Byung-chul
Journal of Korean Neurosurgical Society
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v.58
no.4
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pp.368-372
/
2015
Objective : The occurrence of acute cerebral infection following deep brain stimulation (DBS) is currently being reported with elevation of C-reactive protein (CRP) level. The aim of the present study was to establish normal range of the magnitude and time-course of CRP increases following routine DBS procedures in the absence of clinical and laboratory signs of infection. Methods : A retrospective evaluation of serial changes of plasma CRP levels in 46 patients undergoing bilateral, two-staged DBS was performed. Because DBS was performed as a two-staged procedure involving; implantation of lead and internal pulse generator (IPG), CRP was measured preoperatively and postoperatively every 2 days until normalization of CRP (post-lead implantation day 2 and 4, post-IPG implantation day 2, 4, and 6). Results : Compared with preoperative CRP levels ($0.12{\pm}0.17mg/dL$, n=46), mean CRP levels were significantly elevated after lead insertion day 2 and 4 ($1.68{\pm}1.83mg/dL$, n=46 and $0.76{\pm}0.38mg/dL$, n=16, respectively, p<0.001). The mean CRP levels at post-lead implantation day 2 were further elevated at post-IPG implantation day 2 ($3.41{\pm}2.56mg/dL$, n=46, respectively, p<0.01). This elevation in post-IPG day 2 rapidly declined in day 4 ($1.24{\pm}1.29mg/dL$, n=46, p<0.05) and normalized to preoperative value at day 6 ($0.42{\pm}0.33mg/dL$, n=46, p>0.05). Mean CRP levels after IPG implantation were significantly higher in patients whose IPGs were implanted at post-lead day 3 than those at post-lead day 5-6 ($3.99{\pm}2.80mg/dL$, n=30, and $2.31{\pm}1.56mg/dL$, n=16, respectively, p<0.05). However, there was no difference in post-IPG day 2 and 4 between them (p>0.05). Conclusion : The mean postoperative CRP levels were highest on post-IPG insertion day 2 and decreased rapidly, returning to the normal range on post-IPG implantation day 6. The duration of post-lead implantation period influenced the magnitude of CRP elevation at post-IPG insertion day 2. Information about the normal response of CRP following DBS could help to avoid unnecessary diagnostic and therapeutic efforts.
Total solar irradiance (750), total UV irradiunce (TUV) and erythemal UV irradiance (EUV) measured at King Sejong station $(62.22^{\circ}S,\;58.78^{\circ}W)$ in west Antarctica have been used together with total ozone, cloud amount and snow cover to examine the effects of ozone, cloud and snow surface on these surface solar inadiunce over the period of 1998-2003. The data of three solar components for each scan were grouped by cloud amount, n in oktas $(0{\leq}n<3,\;3{\leq}n<4,\;4{\leq}n<5,\;5{\leq}n<6,\;6{\leq}n<7\;and\;7{\leq}n<8)$ and plotted against solar zenith angle (SZA) over the range of $45^{\circ}\;to\;75^{\circ}$. The radiation amplification factor (RAE) is used to quantify ozone effect on EUV. RAF of EUV decreases from 1.51 to 0.94 under clear skies but increases from 0.94 to 1.85 under cloudy skies as SZA increases, and decreases from 1.51 to 1.01 as cloud amount increases. The effects of cloud amount and snow surface on EUV are estimated as a function of SZA and cloud amount after normalization of the data to the reference total ozone of 300 DU. In order to analyse the transmission of solar radiation by cloud, regression analyses have been performed for the maximum values of solar irradiance on clear sky conditions $(0{\leq}n<3)$ and the mean values on cloudy conditions, respectively. The maximum regression values for the clear sky cases were taken to represent minimum aerosol conditions fur the site and thus appropriate for use as a normalization (reference) factor for the other regressions. The overall features for the transmission of the three solar components show a relatively high values around SZAs of $55^{\circ}\;and\;60^{\circ}$ under all sky conditions and cloud amounts $4{\leq}n<5$ and $5{\leq}n<6$. The transmission is, in general, the largest in TUV and the smallest in EUV among the three components of the solar irradiance. If the ground is covered with snow on partly cloudy days $(6{\leq}n<7)$, EUV increases by 20 to 26% compared to snow-free surface around SZA $60^{\circ}-65^{\circ}$, due to multiple reflections and scattering between the surface and the clouds. The relative difference between snow surface and snow-free surface slowly increases from 9% to 20% as total ozone increases from 100 DU to 400 DU under partly cloud conditions $(3{\leq}n<6)$ at SZA $60^{\circ}$. The snow effects on TUV and TSO are relatively high with 32% and 34%, respectively, under clear sky conditions, while the effects changes to 36% and 20% for TUV and TSO, respectively, as cloud amount increases.
Kim, Seong Su;Shin, Yong Cheol;Lee, Sun Do;Lee, Nam Ju;Kim, Jong Cheol;Lee, Chun Ho
The Korean Journal of Nuclear Medicine Technology
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v.17
no.1
/
pp.11-17
/
2013
Purpose: The use of SUV which should be normalized by lean body mass (LBM) is recommended for PET response criteria in solid tumors. LBM which was determined by whole body CT was used for SUV normalization (SUL) in this study. The purpose of the present study was to assess interobserver and intraobserver reproducibility of SUL measurements in reference organs. Materials and Methods: F-18 FDG PET/CT was conducted on 52 subjects and LBMs were directly determine by whole body CT for normalization of SUV. The 3 cm diameter spherical VOI, $1\times2$ cm cylindrical VOI, 2 cm diameter spherical VOI were placed in the liver, descending aorta and spleen, respectively. Experienced two observers measured SULmax and SULmean in each organ. Repeated measurements were conducted two weeks apart by observer 1 blind to previous results. Similarly, measurements were conducted on the same patients by observer 2. For assessing reproducibility(or repeatability), the paired t-test, Pearson's correlation coefficients (CC), and technical error of measurement (TEM) were calculated. Results: For interobserver reproducibility in liver SULmax and SULmean, no significant differences were found between observers(paired t-test, P=0.536, 0.293, respectively). CC and TEM for liver SULmean were 0.909 (P=0.000) and 0.067 SUL unit, respectively. Corresponding figures for liver SULmax were 0.882 (P=0.000) and 0.117 SUL unit, respectively. For intraobserver reproducibility in liver SULmax and SULmean, no significant differences were observed within observer1 (paired t-test, P=0.374, 0.268, respectively). CC and TEM for liver SULmean were 0.924 (P=0.000) and 0.061 SUL, respectively. Corresponding figures for liver SULmax were 0.908 (P=0.000) and 0.104 SUL, respectively. Similarly, no significant differences were found in SULmax and SULmean of the spleen and aorta between observers. Conclusion: The current study demonstrated that both SULmean and SULmax measurements in normal reference organs are highly reproducible. Reproducibility of SULmean in reference organs were slightly better than SULmax. Interobsever technical error of measurement was less than 0.10 SUL unit for liver SULmean, and 0.12 SUL unit for liver SULmax. Intraobsever technical error of measurement was less than 0.07 SUL unit for liver SULmean, and 0.11 SUL unit for liver SULmax.
Purpose: This study examined the effects of gender, age, underlying disease, duration after onset of symptoms, preoperative invasive procedures, bacterial culture of joint fluid, and stage of infection by the Gachter classification on the prognosis of patients with infectious knee arthritis who underwent arthroscopic surgery. Materials and Methods: From June 2014 to December 2016, 51 patients who underwent arthroscopic surgery for infective knee arthritis were enrolled in this study. The average follow-up period was 14.2±2.1 months (range, 12-20 months). The subjects were 27 men (52.9%) and 24 women (47.1%), with an average age of 55.1±17.6 years (range, 13-84 years). A preoperative evaluation of the joint aspiration with a count of more than 50,000 leukocytes and a polymorphonuclear leukocyte count of 95% or more was performed. All patients underwent arthroscopic surgery and postoperative continuous joint irrigation. Results: The initial mean value of the C-reactive protein decreased from 9.55±6.76 mg/dl (range, 1.51-31.06 mg/dl) to a final mean of 0.74±1.26 mg/dl (range, 0.08-6.77 mg/dl); the mean duration of C-reactive protein normalization was 27.6±18.9 days (range, 8-93 days). Among the 51 patients who received arthroscopic surgery and antibiotics, 44 patients (86.3%) with infectious knee arthritis completed treatment with improved clinical symptoms, such as fever, pain, and edema, and the C-reactive protein decreased to less than 0.5 mg/dl. Finally, 5 cases were treated with two or more arthroscopic operations, and 2 cases were converted to arthroplasty after prosthesis of antibiotic-loaded acrylic cement. Conclusion: The duration of surgery after the onset of symptoms and the stage according to the Gächter classification are important prognostic factors for predicting the successful treatment of infectious knee arthritis. On the other hand, the other factors were not statistically significant. Nevertheless, patients with bacteria cultured from the joint fluids appear to reflect the treatment period because the period of normalization of the C-reactive protein is shorter than that of the control group.
In the beginning brain waves were used for monkeys to control robot arm with neural activity. In recent years there are research that measured brain waves are used for the control of programs which monitor the progression of dementia or enhance of attention in children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD). Moreover, low-price devices that can be used as a game control interface have become available. One of the problems associated with control using brain waves is that the mean amplitude, mean wavelength, and mean vibrational frequency of the brain waves differ from individual to individual. This paper attempts to propose a method to normalize measured brain waves using normal distribution and calculate the waveforms that can be used in controlling games. For this, a framework in which brain waves are converted in seven stages has been suggested. In addition, the estimation process in each stage has been described. In an experiment the waveforms of two subjects have been compared using the proposed method in the BCI English word learning program. The level of similarity between two subjects' waveforms has been compared with correlation coefficient. When the proposed method was applied, both meditation and concentration increased by 13% and 8%, respectively. Because the proposed regularization method is converted into a waveform fit for control functions by reducing personal characteristics reflected in the brain waves, it is fitting for application programs such as games.
Journal of the Institute of Electronics Engineers of Korea SP
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v.41
no.3
/
pp.209-219
/
2004
In order to implement a real time hardware for keyword spotting, we propose a Single-End-Point DTW(SEP-DTW) algorithm which is simple and less complex for computation. The SEP-DTW algorithm only needs a single end point which enables efficient applications, and it has a small wont of computations because the global search area is divided into successive local search areas. Also, we adopt new local constraints and a new distance measure for a better performance of the SEP-DTW algorithm. Besides, we make a normalization of feature same vectors so that they have the same variance in each frequency bin, and each frame has the same energy levels. To construct several reference patterns for each keyword, we use a clustering algorithm for all training patterns, and mean vectors in every cluster are taken as reference patterns. In order to detect a key word for input streams of speech, we measure the distances between reference patterns and input pattern, and we make a decision whether the distances are smaller than a pre-defined threshold value. With isolated speech recognition and keyword spotting experiments, we verify that the proposed algorithm has a better performance than other methods.
Seo, Young-Wook;Ahn, Chi Kook;Lee, Hoonsoo;Park, Eunsoo;Mo, Changyeun;Cho, Byoung-Kwan
Journal of Biosystems Engineering
/
v.41
no.1
/
pp.51-59
/
2016
Purpose: This study examined the performance of two spectroscopy methods and multivariate classification methods to discriminate viable pepper seeds from their non-viable counterparts. Methods: A classification model for viable seeds was developed using partial least square discrimination analysis (PLS-DA) with Fourier transform near-infrared (FT-NIR) and Raman spectroscopic data in the range of $9080-4150cm^{-1}$ (1400-2400 nm) and $1800-970cm^{-1}$, respectively. The datasets were divided into 70% to calibration and 30% to validation. To reduce noise from the spectra and compare the classification results, preprocessing methods, such as mean, maximum, and range normalization, multivariate scattering correction, standard normal variate, and $1^{st}$ and $2^{nd}$ derivatives with the Savitzky-Golay algorithm were used. Results: The classification accuracies for calibration using FT-NIR and Raman spectroscopy were both 99% with first derivative, whereas the validation accuracies were 90.5% with both multivariate scattering correction and standard normal variate, and 96.4% with the raw data (non-preprocessed data). Conclusions: These results indicate that FT-NIR and Raman spectroscopy are valuable tools for a feasible classification and evaluation of viable pepper seeds by providing useful information based on PLS-DA and the threshold value.
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