65 research outputs found

    Adaptive Edge-guided Block-matching and 3D filtering (BM3D) Image Denoising Algorithm

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    Image denoising is a well studied field, yet reducing noise from images is still a valid challenge. Recently proposed Block-matching and 3D filtering (BM3D) is the current state of the art algorithm for denoising images corrupted by Additive White Gaussian noise (AWGN). Though BM3D outperforms all existing methods for AWGN denoising, still its performance decreases as the noise level increases in images, since it is harder to find proper match for reference blocks in the presence of highly corrupted pixel values. It also blurs sharp edges and textures. To overcome these problems we proposed an edge guided BM3D with selective pixel restoration. For higher noise levels it is possible to detect noisy pixels form its neighborhoods gray level statistics. We exploited this property to reduce noise as much as possible by applying a pre-filter. We also introduced an edge guided pixel restoration process in the hard-thresholding step of BM3D to restore the sharpness of edges and textures. Experimental results confirm that our proposed method is competitive and outperforms the state of the art BM3D in all considered subjective and objective quality measurements, particularly in preserving edges, textures and image contrast

    Improving Face Recognition from Caption Supervision with Multi-Granular Contextual Feature Aggregation

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    We introduce caption-guided face recognition (CGFR) as a new framework to improve the performance of commercial-off-the-shelf (COTS) face recognition (FR) systems. In contrast to combining soft biometrics (eg., facial marks, gender, and age) with face images, in this work, we use facial descriptions provided by face examiners as a piece of auxiliary information. However, due to the heterogeneity of the modalities, improving the performance by directly fusing the textual and facial features is very challenging, as both lie in different embedding spaces. In this paper, we propose a contextual feature aggregation module (CFAM) that addresses this issue by effectively exploiting the fine-grained word-region interaction and global image-caption association. Specifically, CFAM adopts a self-attention and a cross-attention scheme for improving the intra-modality and inter-modality relationship between the image and textual features, respectively. Additionally, we design a textual feature refinement module (TFRM) that refines the textual features of the pre-trained BERT encoder by updating the contextual embeddings. This module enhances the discriminative power of textual features with a cross-modal projection loss and realigns the word and caption embeddings with visual features by incorporating a visual-semantic alignment loss. We implemented the proposed CGFR framework on two face recognition models (ArcFace and AdaFace) and evaluated its performance on the Multi-Modal CelebA-HQ dataset. Our framework significantly improves the performance of ArcFace in both 1:1 verification and 1:N identification protocol.Comment: This article has been accepted for publication in the IEEE International Joint Conference on Biometrics (IJCB), 202

    Forecasting Temperature in the Coastal Area of Bay of Bengal-An Application of Box-Jenkins Seasonal ARIMA Model

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    Temperature is one of the most vital elements of the climate system and forecasting of the temperature helps the stakeholders those who are depends on it directly or indirectly to prepare  in advance. Country like Bangladesh whose economy mostly geared up by the agricultural product need to know the upcoming pattern of temperature beforehand to take necessary actions. This study has been conducted on the monthly maximum and minimum temperature data (1949-2012) from the second largest and port city of Bangladesh, Chittagong. Non-parametric Mann-Kendall test has been adopted to identify the trend of the series and found that though the maximum temperature is increasing but not significantly but the minimum temperature is increasing significantly. The anomaly plot is just portrait the ups and downs of minimum and maximum temperature and found minimum temperature is increasing from last two decades whereas the maximum temperature has abrupt changes with increase and decrease. The linear trend analysis shows the climate line for maximum and minimum temperature are 35.67 and 10.23 degree Celsius respectively and the rate for significant increase of minimum temperature is 0.07 degree Celsius. The forecasting Seasonal ARIMA model for maximum temperature is SARIMA (1, 1, 1) (2, 0, 0) [12] and for minimum temperature is SARIMA (1, 1, 1) (1, 0, 1) [12]. The resulted outcomes indicate the increasing pattern of temperature in upcoming days in this area of Bangladesh. Keywords: temperature, Seasonal ARIMA, forecasting, climate, Chittagon

    Boron Nitride nanotube reinforced Titanium matrix composite

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    Boron nitride nanotube reinforcement at titanium matrix composite increased the strength of the composite both at room and high temperature. At higher sintering temperature, nanotube reacts with titanium first forming TiB2 transition phase at the interface and then in-situ formed TiB phases in the matrix, which is also responsible for enhanced mechanical properties

    Directionality of DNA mismatch repair in escherichia coli

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    Non-canonical base pairs that escape the proof-reading activity of the DNA polymerase emerge from DNA replication as DNA mismatches. To promote genomic integrity, these DNA mismatches are corrected by a secondary protection system, called DNA mismatch repair (MMR). Understanding the details of MMR is important for human health as defects in mismatch repair can result in cancer (e.g. hereditary nonpolyposis colorectal cancer, also known as Lynch syndrome). Being normally stochastic in nature, mismatches can emerge at random locations in a chromosome. Therefore, using a molecular tool to generate substrates for the MMR system at a defined locus has been particularly useful in my study of DNA mismatch repair in vivo. In this study, I have used a CTG•CAG repeat array, also called the “TNR array”, to generate frequent substrates for the MMR system in Escherichia coli. In E. coli, the MMR system searches for hemimethylated GATC motifs around a mismatch to initiate removal of the faulty nascent (un-methylated) strand. Analysing the usage of GATC motifs around the TNR array, I have found that the MMR system preferentially utilizes the GATC motifs on the origin distal side of the TNR array demonstrating that the bidirectionality of MMR in vitro is constrained in live cells. My results suggest that in vivo MMR operates by searching for the nearest hemimethylated GATC site located between the mismatch and the replication fork and excision of the nascent strand occurs directionally away from the fork towards the mismatch. Previous in vitro studies have established that the excision reaction during MMR terminates at a discrete point about 100 bp beyond a mismatch. However, in vivo recombination at a 275 bp tandem repeat, which has been proposed to be mediated by single stranded DNA generated during the excision reaction, has suggested that the end point of the excision reaction in live cells may extend much further from the mismatch than this. I have used this assay for extended excision to determine the influence of GATC sites on excision tracts. In this study, modification of the GATC motifs on the origin proximal side of the TNR has shown that the excision reaction does not stop at a GATC motif on the origin proximal side of the mismatch. In addition, sequential modifications of GATC motifs on the origin distal side of the TNR array, thereby shifting the start point of the excision reaction to a greater distance, have suggested that the length of an excision tract is a function of the distance it covers from the start point rather than from a mismatch. My observation of directionality with respect to DNA replication in the recognition of GATC sites suggested that MMR and DNA replication might be coupled in some way and that perhaps active (or blocked) MMR might impede the progress of the replication fork. However, no replication intermediates were detected using two-dimensional agarose gel electrophoresis of genomic DNA fragment containing the TNR array upon restriction digestion. I was therefore unable to support the hypothesis that active or blocked MMR led to a slowing down of DNA replication. Given my observation of a decrease in MMR by separating the mismatch from the closest origin distal GATC site, I set out to test whether MMR caused any selection pressure for the genomic distribution of GATC motifs. To do this, I generated artificial model genomes using a Markovian algorithm based on the nucleotide composition and codon usage in E. coli. Strikingly, the comparison of the distribution of GATC motifs in the E. coli genome with those from artificial sequences has shown that GATC motifs are distributed randomly in E. coli genome, except for a small clustering effect which has been detected for short spaced (0-40 basepairs) GATC motifs. The observed distribution of slightly over-represented GATC motifs in the E. coli genome appears to be a function of the total number of GATC motifs and it seems that the DNA mismatch repair system has evolved to utilize the natural distribution of GATC motifs to maintain genomic integrity

    Brain Cancer Segmentation Using YOLOv5 Deep Neural Network

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    An expansion of aberrant brain cells is referred to as a brain tumor. The brain's architecture is extremely intricate, with several regions controlling various nervous system processes. Any portion of the brain or skull can develop a brain tumor, including the brain's protective coating, the base of the skull, the brainstem, the sinuses, the nasal cavity, and many other places. Over the past ten years, numerous developments in the field of computer-aided brain tumor diagnosis have been made. Recently, instance segmentation has attracted a lot of interest in numerous computer vision applications. It seeks to assign various IDs to various scene objects, even if they are members of the same class. Typically, a two-stage pipeline is used to perform instance segmentation. This study shows brain cancer segmentation using YOLOv5. Yolo takes dataset as picture format and corresponding text file. You Only Look Once (YOLO) is a viral and widely used algorithm. YOLO is famous for its object recognition properties. You Only Look Once (YOLO) is a popular algorithm that has gone viral. YOLO is well known for its ability to identify objects. YOLO V2, V3, V4, and V5 are some of the YOLO latest versions that experts have published in recent years. Early brain tumor detection is one of the most important jobs that neurologists and radiologists have. However, it can be difficult and error-prone to manually identify and segment brain tumors from Magnetic Resonance Imaging (MRI) data. For making an early diagnosis of the condition, an automated brain tumor detection system is necessary. The model of the research paper has three classes. They are respectively Meningioma, Pituitary, Glioma. The results show that, our model achieves competitive accuracy, in terms of runtime usage of M2 10 core GPU

    Inverse sinusoidal pulse width modulation switched electric vehicles’ battery charger

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    This paper documents an efficient, cost-effective and sustainable grid-connected electric vehicles (EVs) battery charger based on a buck converter to reduce the harmonics injected into the mains power line. To utilize the switching converter as an effective power factor controller (PFC), inverse sinusoidal pulse width modulation (ISPWM) signals have been applied. A mathematical relationship between the sending-end power factor and the duty ratio of the switching converter has been presented. To ensure the sustenance of the proposed method, a simulation model of the proposed battery charging system has been tested on PSIM simulation platform. The simulation results yield to a lossless charging system with a sending-end power factor close to unity. An experimental testbed comprising a 60 V battery bank of 100 A-h capacity with a charging current of 7 A has been generated. The laboratory assessments present an 88.1% efficient charging prototype with a resultant sending-end power factor of 0.89. The laboratory framework concerns with the comparative analysis of the power efficiency, sending-end power factor and lines current total harmonic distortion (THD) values obtained for different charging methods and the evaluations corroborate the reliability of the proposed work

    Modeling of Potato Shelf Life on Evaporative Cooling Storage

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    A model of evaporative cooling storage system was designed to increase potato shelf life for improving potato storage system. Two cultivars of potato ‘Diamant’ (100 gm and 51 gm per tuber) and ‘LalPakri (23 gm and 11 gm per tuber) were placed on four shelves of the bin. Each shelf holds 240 kg of potato from 23 march 2013 to December 2013. Potato spoilage, sprouting, shrinkage, moisture content, vitamin C and total sugar content of potato were measured. Experimental results revealed that potato spoilage progressively increased from April to November and sprouting of potato gradually increased from June to October, but stopped in November. The cumulative spoilage and sprouting were much lower in the improved bin compared to traditional farmer’s practices. Shrinkage of potato was found higher in farmer’s practice than that of storage bin from October to November. Moisture content of potato was higher during May and reduced gradually to the lowest value during November in both of practices. No significant difference was found in two practices on vitamin-C content. Sugar content of ‘Diamant; potato was lower in the storage bin during November. According to data analysis and regression curve storage bin model was more appropriate for both cultivars than farmer practice and significantly more appropriate for ‘LalPakri’ potato
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