Charpy impact response of glass fiber reinforced composite with nano graphene enhanced epoxy

Fiber reinforced polymer composite materials show several superior properties over conventional engineering materials; on the other hand, most of composite materials also have some drawbacks such as brittle behavior of matrix. This study is aimed to improve the impact response of composite material by adding nano particle into epoxy matrix. For this purpose; an experimental study was conducted to investigate the effect of graphene nano particles inclusion in epoxy resin with glass fiber reinforced composite plate on the Charpy impact response. Glass fiber reinforced (GFR) epoxy composite plates were produced with various graphene nano platelets content such 0, 0.1, 0.25 and 0.5 wt%. Low velocity impact response was investigated by using Charpy impact test method. Impact energy and impact damage results presented in detail

Performance boosting of image matching-based iris recognition systems using deformable circular hollow kernels and uniform histogram fusion images

Identification of people using different biometric data is becoming more important in network society. Biometrics include voice, ears, palms, fingerprints, faces, iris, retina, and hand shapes. Among these features, iris detection gets more attention because each iris type is unique and does not change throughout life. In this study, an iris recognition framework is proposed using deformable circular hollow kernels and uniform histogram fusion images (UHFIs). This system introduces two different approaches for the iris recognition: one with image matching without machine learning and the other one with machine learning. In the first approach, image matching through Gabor features is employed. After getting the circularly cropped UHFI, Gabor features are extracted and employed in the image matching-based recognition system. In addition, a normalized cross-correlation coefficient is used as a similarity metric to compare the Gabor feature vectors. In the second approach, Gabor feature images are extracted and employed in deep learning (DL). According to the experimental results, the proposed system reaches around 89% accuracy on MMU1, 86% accuracy on MMU2, and about 50% accuracy on the CASIAV3 and CASIAV4 datasets when no machine learning is employed. Extensive benchmarking results also indicate that the proposed system boosts the performance of conventional systems by at least around 40% in terms of accuracy in the absence of machine learning. However, in the presence of machine learning, experimental results show that the proposed method with DL achieves an accuracy of up to 100% for MMU1, MMU2, CASIAV3, and CASIAV4 datasets. (c) 2022 SPIE and IS&

A Low-Cost Pupil Center Localization Algorithm Based on Maximized Integral Voting of Circular Hollow Kernels

Pupil center localization is an essential requirement for robust eye gaze tracking systems. In this paper, a low-cost pupil center localization algorithm is presented. The aim is to propose a computationally inexpensive algorithm with high accuracy in terms of performance and processing speed. Hence, a computationally inexpensive pupil center localization algorithm based on maximized integral voting of candidate kernels is presented. As the kernel type, a novel circular hollow kernel (CHK) is used. Estimation of pupil center is employed by applying a rule-based schema for each pixel over the eye sockets. Additionally, several features of CHK are proposed for maximizing the probability of voting for each kernel. Experimental results show promising results with 96.94% overall accuracy with around 13.89 ms computational time (71.99 fps) for a single image as an average time by using a standard PC. An extensive benchmarking study indicates that this method outperforms the learning-free algorithms and it competes with the other methods having a learning phase while their processing speed is much higher. Furthermore, this proposed learning-free system is fast enough to run on an average PC and also applicable to work with even a low-resolution webcam on a real-time video stream

Low dynamic range discrete cosine transform (LDR-DCT) for high-performance JPEG image compression

In mathematical theory, the discrete cosine transform (DCT) is a lossless orthogonal transformation method which means it outputs exactly the same values of the input after the inverse transformation. However, this is impossible in today’s technology due to the limited capacity of processors in which the maximum value that a number can take is 2 64- 1 (20-digit number) in a 64-bit register. Since the DCT employs the floating values higher than this precision, there occurs a round-off error which causes a particular loss of information after the inverse transformation. For this reason, the dynamic range of the DCT coefficients should be reduced so that fewer precision digits are employed in the DCT calculations, thereby the round-off error and loss of information are minimized. In this study, conventional DCT equations are improved both in forward and inverse transformation for the sake of high-performance JPEG image compression. The proposed method reduces the dynamic range of the DCT coefficients and provides a low dynamic range DCT (LDR-DCT) by weighting the DCT coefficients with respect to the frequency level. The effectiveness of the proposed LDR-DCT method is experimented mainly by observing the inter-correlation between the compression ratio and the peak signal-to-noise ratio (PSNR) values which is defined as the compression performance (CP). An extensive experimental benchmarking study is done using the publicly available KODAK image dataset in both grayscale and RGB color spaces, separately. According to the experimental results, the average compression performance (CP) is increased up to about 26% in grayscale images and about 17% in RGB images when the quantization factors (21–121) are employed in the quantization process. Additionally, it is observed that there is an average increment in the compression performance (CP) up to about 8% in grayscale images and about 7% in RGB images when the standard IrfanView quantization tables (quality level of 40 to the quality level of 90) are applied. On the other hand, in the absence of quantization when either the quantization factor of 1 or the standard IrfanView quantization table with the quality level of 100 is applied, it is also observed that there is an average increment in the PSNR value up to about 15% in grayscale images and about 33% in RGB images with respect to the average PSNR values of 24 images in the KODAK image dataset. Therefore, though the proposed LDR-DCT method without quantization does not change the compression ratio, it improves the quality of the output obtained after the inverse transform dramatically. In other words, the conventional DCT method should be replaced by the proposed LDR-DCT method in certain areas where compression is not required. Besides, the study claims that the proposed LDR-DCT method can provide at least the same JPEG image quality as the conventional DCT method with much higher compression ratios if the quantization tables are redesigned accordingly. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature

A confounding rib variation: bilateral symmetric aberrant posterior rib articulations and bridgings

Although mild bone angulation with osseous enlargement often suggests fractures with callus formation, in some cases the diagnosis is synchondrosis

Periton diyalizi hastasında acil hemodiyaliz gereksinimi; laksatif kullanımına bağlı hipermagnezemi: olgu sunumu

Hypermagnesemia is rarely seen in peritoneal dialysis (PD) patients because PD can lower the plasma magnesium (Mg) concentration effectively. In this report, a continuous ambulatory peritoneal dialysis (CAPD) patient with life-threatening hypermagnesemia treated by hemodialysis (HD) is presented. A 52-year-old male patient on PD treatment was admitted to our clinic with complaints of fatigue and muscle weakness. Decrease in deep tendon reflexes (DTR), decrease in muscle strength at bilateral upper and lower extremities, and increased level of magnesium (7.7 mg/dl) were detected. Bradycardia, prolongation of the P-R interval, and an increase in Q-T interval were found on the electrocardiography. HD was performed two times. After HD, all the signs and symptoms of the patient improved. HD is a dialysis modality that should be preferred in the treatment of symptomatic patients with hypermagnesemia, because of providing more rapid clearance of Mg.Periton diyalizi (PD) tedavisi plazma magnezyum (Mg) konsantrasyonunu etkin olarak düşürdüğünden PD hastalarında hipermagnezemi oldukça nadir görülmektedir. Burada, sürekli ayaktan periton diyalizi (SAPD) tedavisi alan bir hastada Mg hidroksit kullanımına bağlı ortaya çıkan, hayatı tehdit eden hipermagnezemi tablosunun acil hemodiyalizle (HD) düzeltildiği bir olgu sunulmuştur. Elli iki yaşında erkek hasta son dönem böbrek yetmezliği (SDBY) nedeniyle SAPD tedavisi uygulamaktayken, halsizlik ve kas güçsüzlüğü yakınmalarıyla polikliniğimize başvurdu. Hastanın yapılan nörolojik muayenesinde; derin tendon reflekslerinde (DTR) ve bilateral alt ve üst ekstremitelerdeki kas gücünde azalma ile birlikte magnezyum düzeyinde artış (7,7 mg/dl) saptandı. Hastanın çekilen elektrokardiyografisinde (EKG) bradikardi, P-R mesafesinde ve Q-T intervalinde uzama mevcuttu. Hasta 2 kez HD’e alındı. Sonrasında hastanın belirti ve bulguları düzeldi. Semptomlu hipermagnezemik hastalarda HD tedavisi daha hızlı Mg klirensi sağlayacağından tercih edilmesi gereken diyaliz modalitesidir

Evaluation of Chest X-ray and Thoracic Computed Tomography in Patients with Suspected Tuberculosis

Objective To investigate if there is any correlation between positive findings detected by posterior-anterior (PA) chest radiograph and thoracic computerized tomography (CT) in cases with suspected lung tuberculosis (TB) due to positive tuberculin skin test (TST) results