341 research outputs found

    On the Vulnerability of Smart Card Transactions

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    poster abstractAbstract: The number of non-cash transactions is increasing every year at a rapid pace because of the underlying flexibility in the payment mechanism and the improved reliability and protection offered by many networks and debit and credit card issuers and acquirers. According to a study by Capgemini, the growth of the number of non-cash-based transactions per inhabitant in the United States increased by 40% from 2012 to 2013. This clearly indicates a strong shift towards a cashless society. However, the above trend is also coupled with an increasing trend in card fraud schemes ranging from gas pump skimmers to application fraud. Even the most recent chip and pin technology has been the victim of fraud as detailed in performing a man-in-the-middle attack by inserting a programmed chip called FUN card. In this study, we investigate the functionalities of smart cards and their susceptibility to fraud based on interference at the hardware level. We specifically analyze processor cards with a cryptographic processors and research the possibility to change the behavior of the hardware either in offline or online transactions in way that may be able to reveal the private key used to authenticate the transaction between the acquirer and the issuer. The results of these investigations can be used to enhance the current encryption as well as the authentication mechanisms used in card transactions

    Generalized F-tests for the Multivariate Normal Mean

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    Based on Lauter\u27s (Biometrics, 1996) exact t test for biometrical studies related to the multivariate normal mean, we develop a generalized F-test for the multivariate normal mean and extend it to multiple comparison. The proposed generalized F- tests have simple approximate null distributions. A Monte Carlo study and two real examples show that the generalized F-test is at least as good as the optional individual LÄauter\u27s test and can improve its performance in some situations where the projection directions for the LÄauter\u27s test may not be suitably chosen. It is discussed that the generalized F-test could be superior to individual Lauter\u27s tests and the classical Hotelling T2-test for the general purpose of testing the multivariate normal mean. It is shown by Monte Carlo studies that the extended generalized F- test outperforms the commonly-used classical test for multiple comparison of normal means in the case of high dimension with small sample sizes. AMS Classification: 62F03; 62F0

    Sample Size Determination for Interval Estimation of the Prevalence of a Sensitive Attribute Under Randomized Response Models

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    © 2022 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.Studies with sensitive questions should include a sufficient number of respondents to adequately address the research interest. While studies with an inadequate number of respondents may not yield significant conclusions, studies with an excess of respondents become wasteful of investigators’ budget. Therefore, it is an important step in survey sampling to determine the required number of participants. In this article, we derive sample size formulas based on confidence interval estimation of prevalence for four randomized response models, namely, the Warner’s randomized response model, unrelated question model, item count technique model and cheater detection model. Specifically, our sample size formulas control, with a given assurance probability, the width of a confidence interval within the planned range. Simulation results demonstrate that all formulas are accurate in terms of empirical coverage probabilities and empirical assurance probabilities. All formulas are illustrated using a real-life application about the use of unethical tactics in negotiation.Peer reviewe

    Design of Affordable 3D Printers

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    poster abstractThe recent expiration of Fused Deposition Modeling (FDM) patents sparked a growth in the 3D printing industry. Fused Deposition Modeling is the most common way of 3D printing parts. It takes a material, usually a plastic, melts it, and then builds a part layer by layer from the molten material. As patents for 3D printing technologies continue to expire, 3D printing will continue to see a large growth in popularity for several different applications; however, there are currently limitations on 3D printers preventing them from entering certain markets. The goal of our project was to address two of the biggest current limitations: the cost of the 3D printer and the ability to print with different materials. We addressed these issues by researching and building two different types of 3D printers along with researching different ways to print different materials. The goal for the first project was to design and assemble an affordable ceramic 3D printer. We researched and purchased an affordable delta 3D printer kit and an affordable ceramic extrusion system. The goal for the second project was to design and assemble an affordable dual extruder desktop 3D printer that could print two different plastics. We successfully built the delta 3D printer and it is working correctly. The dual extruder desktop 3D printer has been assembled. For both projects, we were able to assemble low-cost 3D printers. In conclusion, this research has resulted in two affordable 3D printers with the potential to 3D print different materials

    Accelerating L 1 -penalized expectation maximization algorithm for latent variable selection in multidimensional two-parameter logistic models

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    © 2023 Shang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/One of the main concerns in multidimensional item response theory (MIRT) is to detect the relationship between observed items and latent traits, which is typically addressed by the exploratory analysis and factor rotation techniques. Recently, an EM-based L1-penalized log-likelihood method (EML1) is proposed as a vital alternative to factor rotation. Based on the observed test response data, EML1 can yield a sparse and interpretable estimate of the loading matrix. However, EML1 suffers from high computational burden. In this paper, we consider the coordinate descent algorithm to optimize a new weighted log-likelihood, and consequently propose an improved EML1 (IEML1) which is more than 30 times faster than EML1. The performance of IEML1 is evaluated through simulation studies and an application on a real data set related to the Eysenck Personality Questionnaire is used to demonstrate our methodologies.Peer reviewe

    Estimation of the directions for unknown parameters in semiparametric models

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    Semiparametric models are useful in econometrics, social sciences and medicine application. In this paper, a new estimator based on least square methods is proposed to estimate the direction of unknown parameters in semi-parametric models. The proposed estimator is consistent and has asymptotic distribution under mild conditions without the knowledge of the form of link function. simulations show that the proposed estimator is significantly superior to maximum score estimator given by Manski (1975) for binary response variables. When the error term is long-tailed distributions or distribution with no moments, the proposed estimator perform well. Its application is illustrated with data of exportibg participation of manufactures in Guangdon

    Acute renal impairment in coronavirus-associated severe acute respiratory syndrome

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    Acute renal impairment in coronavirus-associated severe acute respiratory syndrome.BackgroundSevere acute respiratory syndrome (SARS) is a newly emerged infection from a novel coronavirus (SARS-CoV). Apart from fever and respiratory complications, acute renal impairment has been observed in some patients with SARS. Herein, we describe the clinical, pathologic, and laboratory features of the acute renal impairment complicating this new viral infection.MethodsWe conducted a retrospective analysis of the plasma creatinine concentration and other clinical parameters of the 536 SARS patients with normal plasma creatinine at first clinical presentation, admitted to two regional hospitals following a major outbreak in Hong Kong in March 2003. Kidney tissues from seven other patients with postmortem examinations were studied by light microscopy and electron microscopy.ResultsAmong these 536 patients with SARS, 36 (6.7%) developed acute renal impairment occurring at a median duration of 20 days (range 5–48 days) after the onset of viral infection despite a normal plasma creatinine level at first clinical presentation. The acute renal impairment reflected the different prerenal and renal factors that exerted renal insult occurring in the context of multiorgan failure. Eventually, 33 SARS patients (91.7%) with acute renal impairment died. The mortality rate was significantly higher among patients with SARS and acute renal impairment compared with those with SARS and no renal impairment (91.7% vs. 8.8%) (P < 0.0001). Renal tissues revealed predominantly acute tubular necrosis with no evidence of glomerular pathology. The adjusted relative risk of mortality associated with the development of acute renal impairment was 4.057 (P < 0.001). By multivariate analysis, acute respiratory distress syndrome and age were the most significant independent risk factors predicting the development of acute renal impairment in SARS.ConclusionAcute renal impairment is uncommon in SARS but carries a high mortality. The acute renal impairment is likely to be related to multi-organ failure rather than the kidney tropism of the virus. The development of acute renal impairment is an important negative prognostic indicator for survival with SARS

    Photoresponse of polyaniline-functionalized graphene quantum dots

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    Polyaniline-functionalized graphene quantum dots (PANI-GQD) and pristine graphene quantum dots (GQDs) were utilized for optoelectronic devices. The PANI-GQD based photodetector exhibited higher responsivity which is about an order of magnitude at 405 nm and 7 folds at 532 nm as compared to GQD-based photodetectors. The improved photoresponse is attributed to the enhanced interconnection of GQD by island-like polymer matrices, which facilitate carrier transport within the polymer matrices. The optically tunable current–voltage (I–V) hysteresis of PANI-GQD was also demonstrated. The hysteresis magnifies progressively with light intensity at a scan range of ±1 V. Both GQD and PANI-GQD devices change from positive to negative photocurrent when the bias reaches 4 V. Photogenerated carriers are excited to the trapping states in GQDs with increased bias. The trapped charges interact with charges injected from the electrodes which results in a net decrease of free charge carriers and a negative photocurrent. The photocurrent switching phenomenon in GQD and PANI-GQD devices may open up novel applications in optoelectronics
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