84 research outputs found

    Performance Evaluation of Face Recognition Algorithms

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    Biometric - based techniques have emerged for recognizing individuals instead of using passwords, PINs, smart cards, plastic cards, tokens etc fo r authenticating people . Automated face recognition has become a major field of interest. In this field several facial recognition algorithms have been explored in the past few decades . A face recognition system is expected to identify faces present in images and videos automatically. The input to the facial recognition system is a two dimensional image, while the system distinguishes the input image as a users face from a pre - determined library of faces. Finally, the output is a discerned face image. This paper deals wi th the comparison of two popular dimensionality reduction algorithms such as PCA and LDA. Here, our main goal is to evaluate the performance of Principal Component Analysis and Linear Discriminant Analysis for large training data set. Finally, we concluded that LDA outperforms PCA for the large samples of training set

    An Integrated Framework for the Detection of Lung Nodules from Multimodal Images Using Segmentation Network and Generative Adversarial Network Techniques

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    Medical imaging techniques are providing promising results in identifying abnormalities in tissues. The presence of such tissues leads to further investigation on these cells in particular. Lung cancer is seen widely and is deadliest in nature if not detected and treated at an early stage. Medical imaging techniques help to identify the presence of suspicious tissues like lung nodules effectively. But it is very difficult to know the presence of the nodule at an early stage with the help of a single imaging modality. The proposed system increases the efficiency of the system and helps to identify the presence of lung nodules at an early stage. This is achieved by combining different methods for reaching a common outcome. Multiple schemes are combined and the extracted features are used for obtaining a conclusion. The accuracy of the system and the results depend on the quality and quantity of the authentic training data. But the availability of the data from an authentic source for the study is a challenging task. Here the generative adversarial network (GAN), is used as a data source generator. It helps to generate a huge amount of reliable data by using a minimum number of real time and authentic data set. Images generated by the GAN are of resolution 1024 x 1024.Fine tuning of the images by using the real images increases the quality of the generated images and thereby improving the efficiency.   Luna 16 is the primary data source and these images are used for the generation of 1000000 images. Training process with the huge dataset improves the capability of the proposed system. Various parameters are considered for evaluating the performance of the proposed system. Comparative analysis with existing systems highlights the strengths of the proposed system

    Discovery of Self through Language from the Perspective of Margaret Laurence’s The Stone Angel

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    Search for self is the ultimatum of anybody’s life where the realization of their life sprouts with highly endowed discovery. The freedom from despair, destruction, and conflict emerges with the highly evacuated spirit of discontentment. Self-discovery touches the core of the soul when one is alive or on the verge of death. The study aims to converge on the retaliated experience of an old woman who is struck with the concept of ‘pride’ where no room for concern and love for her kith and kin even for herself. The revisit of the past enables her to realize her sense of in-human approach with her deep-rooted sense of class consciousness. The language of despair and destitution of the protagonist witnesses the enlarging vision of her soul in which seclusion resides. The research shows way for further studies on ‘communication gaps’ between the characters

    Automated Defect Detection and Characterization on Pulse Thermography Images Using Computer Vision Techniques

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    Defect detection and characterization plays a vital role in predicting the life span of materials. Defect detection using appropriate inspection technologies at various phases has gained huge importance in metal production lines. It can be accomplished through wise application of non-destructive testing and evaluation (NDE). It is important to characterize defects at an early stage in order to be able to overcome them or take corrective measures. Pulse thermography is a modern NDE method that can be used for defect detection in metal objects. Only a limited amount of work has been done on automated detection and characterization of defects due to thermal diffusion. This paper proposes a system for automatic defect detection and characterization in metal objects using pulse thermography images as well as various image processing algorithms and mathematical tools. An experiment was carried out using a sequence of 250 pulse thermography images of an AISI 316 L stainless steel sheet with synthetic defects. The proposed system was able to detect and characterize defects sized 10 mm, 8 mm, 6 mm, 4 mm and 2 mm with an average accuracy of 96%, 95%, 84%, 77%, 54% respectively. The proposed technique helps in the effective and efficient characterization of defects in metal objects

    Human epidermal growth factor receptor-2 gene expression positivity determined by silver in situ hybridization/immunohistochemistry methods and associated factors in a cohort of Sri Lankan patients with gastric adenocarcinoma : a prospective study

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    Objective: Positive human epidermal growth factor 2 (HER2) expression and its predictive clinicopathological features remain unclear in Sri Lankan gastric cancer (GC) patients. Here, we aimed to determine GC HER2 status predictors by analyzing associations between clinicopathological features and HER2 expression using immunohistochemistry (IHC) and silver in situ hybridization (SISH). Methods: During this 4-year prospective study, clinicopathological data were collected from participants in the National Hospital of Sri Lanka. HER2 IHC and SISH were performed using commercial reagents. Using chi-square tests, associations of HER2-IHC/SISH with clinicopathological features were analyzed. Results: Overall, 145 GC patients were included, 69 had gastrectomies and 76 had biopsies. Positive HER2 expression by IHC was associated with age 5/high-power field, with additional perineural invasion and lymphovascular invasion in resections. These features, excluding lymphovascular invasion but including male sex, were associated with HER2 expression by SISH. Conclusions: Age <60 years, high nuclear grade, tumor necrosis, and perineural invasion are associated factors of HER2 status. These could be used to triage GC patients for HER2 status testing in limited resource settings where IHC/SISH analysis is costly

    The masked demos: Associational anonymity and democratic practice

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    The increased use of anonymous digital platforms raises substantive concerns about accountability in digital spaces. However, contemporary evaluations of anonymity focus too narrowly on its protective function: its ability to protect a diversity of speakers and ideas. Drawing on two examples of anonymous political engagements – Publius’s writing of the Federalist Papers and college students’ use of the social media platform Yik Yak – we develop an account of anonymity’s associational function: the processes by which people generate and negotiate collective identities, discussions, and actions in wider publics. As we argue, anonymity’s associational function can (1) generate conditions under which individuals develop collective interests and identities to foster collective action, and (2) enable novel interactions between these individuals and communities and the larger publics of which they are part. We conclude with a discussion of how attention to associational anonymity can contribute to a more nuanced account of democracy in practice

    Corrosion Protection Effect of Chitosan on the Performance Characteristics of A6063 Alloy

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    This article outlines the behaviour of water-soluble chitosan as an effective inhibitor on aluminium alloy in 3.65% NaCl at room temperature. The inhibitive ability of water-soluble chitosan was examined using electrochemical potentiodynamic polarization techniques, mass loss measurements and computational studies. The outcome of the experiment reveals that chitosan inhibited aluminium alloy in sodium chloride solution exhibits better corrosion protection than the uninhibited because chitosan nanoparticles minimize the ingression of chloride ion into the active sites of aluminium alloy by forming thin film on its surface. The losses in mass by the inhibited aluminium alloy were found to reduce as the concentration of chitosan increases. Results obtained showed that chitosan could offer inhibition efficiency above 70%. Polarization curve demonstrated that chitosan in 3.65% NaCl at room temperature acted as a mixed-type inhibitor. Adsorption of chitosan nanoparticles on the aluminium alloy was found to follow Langmuir adsorption isotherm with correlation regression coefficient (R2 ) value of 0.9961

    31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

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    Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival
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