Classification of Myoelectric Signal using Spectrogram Based Window Selection

This paper presents a study of the classification of myoelectric signal using spectrogram with different window sizes. The electromyography (EMG) signals of 40 hand movement types are collected from 10 subjects through NinaPro database. By employing spectrogram, the EMG signals are represented in time-frequency representation.  Ten features are extracted from spectrogram for performance evaluation. In this study, two classifiers namely support vector machine (SVM) and linear discriminate analysis (LDA) are used to evaluate the performance of spectrogram features in the classification of EMG signals. To determine the best window size in spectrogram, three different Hanning window sizes are examined. The experimental results indicate that by applying spectrogram with optimize window size and LDA, the highest mean classification accuracy of 91.29% is obtained

Microcontroller Implementation Of Single Phase Inverter Switching Strategies.

This paper presents the practical microcontroller implementation of single phase inverter switching strategies

Analyze Of Process Parameter Variance In 19nm Wsi2/Tio2 NMOS Device Using 2k-Factorial Design

This project investigates and analyzes the impact of process parameter variance on the drive current (ION) and leakage current (IOFF) for 19nm WSi2/TiO2 NMOS device using 2k-factorial design. The four process parameter, namely halo implant dose, halo implant energy, source/drain (S/D) implant dose and S/D implant energy will be investigated and adjusted to improve the results. The simulated of the device was performed by using ATHENA module. Meanwhile the electrical characterization of the device was implemented by using ATLAS module. These two modules will be combined with 2kfactorial to aid design and optimize the process parameters. The most effective process parameter with respect ION and IOFF were chosen depending on the percentage of the factor effect on S/N ratio that indicates the relative power of factor to reduce variation. The most dominant or significant factors in S/N Ratio are pocket halo implant dose and S/D implant energy. Meanwhile, the values of ION and IOFF values for 19nm WSi2/SiO2 NMOS device after optimization approaches are 591.38 µA/µm and 2.217 pA/µm respectively. The results obtained are meet the requirement of International Technology Roadmap Semiconductor (ITRS) 2013 prediction

Effects of crude methanol extract of Euphorbia hirta on Hematological and Biochemical indices and histological changes of liver in African Catfish Clarias gariepinus (Burchell, 1822).

Methanol extract of Euphorbia hirta was tested in in vivo experiment to investigate the effect on hematological and biochemical indices and histological changes of liver in the African catfish (Clarias gariepinus). The plant methanol extract was included in the feed and administered to the fish. The experiment was conducted for eight weeks and with five diets including control (E. hirta-0), 2 (E. hirta-2), 5(E. hirta-5), 7(E. hirta-7) and 9(E. hirta-9) g E. hirta kg-1 of dry matter diet. Fish fed the E. hirta-9 diet had lowest (p<0.05) RBC and TP compared with the other dietary groups. Histological analyses revealed this group (E. hirta-9) had histopathologic alterations in the liver. Results of this study indicated that methanol extract of E.hirta by 7 g kg-1 can be safely used to improve hematological indices of African catfish without any adverse effect on the liver

Automatic Brain Lesion Detection And Classification Based On Diffusion-Weighted Imaging Using Adaptive Thresholding And A Rule-Based Classifier

In this paper,a brain lesion detection and classification approach using thresholding and a rule-based classifier is proposed.Four types of brain lesions based on diffusion-weighted imaging i.e. acute stroke,solid tumor, chronic stroke,and necrosis are analyzed.The analysis is divided into four stages:pre-processing,segmentation, feature extraction,and classification.In the detection and segmentation stage,the image is divided into 8x8 macro-block regions.Adaptive thresholding technique is applied to segment the lesion’s region.Statistical features are measured on the region of interest.A rulebased classifier is used to classify four types of lesions.Jaccard’s similarity index of the segmentation results for acute stroke,solid tumor,chronic stroke,and necrosis are 0.8, 0.55, 0.27, and 0.42,respectively.The classification accuracy is 93% for acute stroke,73% for solid tumor,84% for chronic stroke,and 60% for necrosis. Overall,adaptive thresholding provides high segmentation performance for hyper-intensity lesions.The best segmentation and classification performance is achieved for acute stroke.The establishment of the technique could be used to automate the diagnosis and to clearly understand major brain lesions

International Nosocomial Infection Control Consortium report, data summary of 50 countries for 2010-2015: Device-associated module

•We report INICC device-associated module data of 50 countries from 2010-2015.•We collected prospective data from 861,284 patients in 703 ICUs for 3,506,562 days.•DA-HAI rates and bacterial resistance were higher in the INICC ICUs than in CDC-NHSN's.•Device utilization ratio in the INICC ICUs was similar to CDC-NHSN's. Background: We report the results of International Nosocomial Infection Control Consortium (INICC) surveillance study from January 2010-December 2015 in 703 intensive care units (ICUs) in Latin America, Europe, Eastern Mediterranean, Southeast Asia, and Western Pacific. Methods: During the 6-year study period, using Centers for Disease Control and Prevention National Healthcare Safety Network (CDC-NHSN) definitions for device-associated health care-associated infection (DA-HAI), we collected prospective data from 861,284 patients hospitalized in INICC hospital ICUs for an aggregate of 3,506,562 days. Results: Although device use in INICC ICUs was similar to that reported from CDC-NHSN ICUs, DA-HAI rates were higher in the INICC ICUs: in the INICC medical-surgical ICUs, the pooled rate of central line-associated bloodstream infection, 4.1 per 1,000 central line-days, was nearly 5-fold higher than the 0.8 per 1,000 central line-days reported from comparable US ICUs, the overall rate of ventilator-associated pneumonia was also higher, 13.1 versus 0.9 per 1,000 ventilator-days, as was the rate of catheter-associated urinary tract infection, 5.07 versus 1.7 per 1,000 catheter-days. From blood cultures samples, frequencies of resistance of Pseudomonas isolates to amikacin (29.87% vs 10%) and to imipenem (44.3% vs 26.1%), and of Klebsiella pneumoniae isolates to ceftazidime (73.2% vs 28.8%) and to imipenem (43.27% vs 12.8%) were also higher in the INICC ICUs compared with CDC-NHSN ICUs. Conclusions: Although DA-HAIs in INICC ICU patients continue to be higher than the rates reported in CDC-NSHN ICUs representing the developed world, we have observed a significant trend toward the reduction of DA-HAI rates in INICC ICUs as shown in each international report. It is INICC's main goal to continue facilitating education, training, and basic and cost-effective tools and resources, such as standardized forms and an online platform, to tackle this problem effectively and systematically