Visual Cryptography in Biometrics Passport

Every human being is unique in their nature such as traits and physical symptoms so computer science is using the biometric f or perfect identification within large database. Visual cryptography scheme is a cryptographic technique, which allows visual information e.g. printed text, handwritten notes, and picture to be encrypted in such a way that the decryption can be performed by the human visual system, without the aid of computers. Biometric passport is a smart card technology product created by use of biometric data and computer chip f or authenticate identification of citizen of particular country. Current passport has certain shortcoming. In the is method it is proposed to convert scan images of retina, fingerprint and face in secret image and meaningful shares by use of visual cryptography. In this method wi th use of Visual Cryptography three biometrics i.e . retina image, fingerprint image and fa ce image encrypted in two meaningful shares when these two share stacking on one another fingerprint image revealed and that can be verified with on the spot live fingerprint image for perfect identification accuracy

Pyrovskite: A software package for the high throughput construction, analysis, and featurization of two- and three-dimensional perovskite systems

The increased computational and experimental interest in perovskite systems comprising novel phases and reduced dimensionality has greatly expanded the search space for this class of materials. In similar fields, unified frameworks exist for the procedural generation and subsequent analysis of these complex condensed matter systems. Given the relatively recent rise in popularity of these novel perovskite phases, such a framework has yet to be created. In this work, we introduce Pyrovskite, an open source software package to aid in both the high-throughput and fine-grained generation, simulation, and subsequent analysis of this expanded family of perovskite systems. Additionally we introduce a new descriptor for octahedral distortions in systems including but not limited to perovskites. This descriptor quantifies diagonal displacements of the B-site cation in a BX$_6$ octahedral coordination environment, which has been shown to contribute to increased Rashba-Dresselhaus splitting in perovskite systems.Comment: 8 pages, 4 figure

Three rare and accidental findings of hemoglobinopathies encountered in high-performance liquid chromatography: case series

Hemoglobinopathies are the leading cause of some major genetic and social health problem in India. Among all hemoglobinopathies, sickle cell disorder and thalassemia are commonly found in Gujarat state. Double heterozygous state of hemoglobin S and D, hemoglobin E trait, hemoglobin D disease are very uncommon. In present instance, one case of 25-year-old male was diagnosed with sickle cell hemoglobin D disease. The case was confirmed through slide-based sickle test and high-performance liquid chromatography (HPLC). The peripheral smear findings showed presence of microcytic hypochromic red blood cells (RBCs) and many sickled RBCs. Ultrasonography (USG) findings showed hepatomegaly. Second case of 30-year-old female was diagnosed with hemoglobin E trait. The case was confirmed by HPLC. The peripheral findings showed normocytic normochromic RBCs and occasional target cells. Presence of gross hepatomegaly on palpation. Third case of 20-year-old female was diagnosed with hemoglobin D trait. The case was confirmed by HPLC. The peripheral findings showed normocytic normochromic RBCs

Vehicle classification using the convolution neural network approach

We present vehicle detection classification using the Convolution Neural Network (CNN) of the deep learning approach. The automatic vehicle classification for traffic surveillance video systems is challenging for the Intelligent Transportation System (ITS) to build a smart city. In this article, three different vehicles: bike, car and truck classification are considered for around 3,000 bikes, 6,000 cars, and 2,000 images of trucks. CNN can automatically absorb and extract different vehicle dataset’s different features without a manual selection of features. The accuracy of CNN is measured in terms of the confidence values of the detected object. The highest confidence value is about 0.99 in the case of the bike category vehicle classification. The automatic vehicle classification supports building an electronic toll collection system and identifying emergency vehicles in the traffic

CANNY EDGE DETECTION BASED REAL-TIME INTELLIGENT PARKING MANAGEMENT SYSTEM

Real-time traffic monitoring and parking are very important aspects for a better social and economic system. Python-based Intelligent Parking Management System (IPMS) module using a USB camera and a canny edge detection method was developed. The current situation of real-time parking slot was simultaneously checked, both online and via a mobile application, with a message of Parking “Available” or “Not available” for 10 parking slots. In addition, at the time entering in parking module, gate open and at the time of exit parking module, the gate closes automatically using servomotor and sensors. Results are displayed in figures with the proposed method flow chart

Dynamics of photoexcited state of semiconductor quantum dots

Thesis (Ph. D.)--University of Rochester. Dept. of Physics and Astronomy, 2015.In this thesis, non-adiabatic molecular dynamics (NAMD) of excited states in semiconductor quantum dots are investigated. Nanoscale systems provide important opportunities for theory and computation for research because the experimental tools often provide an incomplete picture of the structure and/or function of nanomaterials, and theory can often fill in missing features crucial in understanding what is being measured. The simulation of NAMD is an indispensable tool for understanding complex ultrafast photoinduced processes such as charge and energy transfer, thermal relaxation, and charge recombination. Based on the state-of-the-art ab initio approaches in both the energy and time domains, the thesis presents a comprehensive discussion of the dynamical processes in quantum dots, ranging from the initial photon absorption to the final emission. We investigate the energy relaxation and transfer rates in pure and surface passivated quantum dots of different sizes. The study establishes the fundamental mechanisms of the electron and hole relaxation processes with and without hole traps. We develop and implement more accurate and efficient methods for NAMD. These methods are advantageous over the traditional ones when one encounters classically forbidden transitions. We also explore the effect of decoherence and nonadiabatic couplings on the dynamics. The results indicate significant influence on the accuracy and related computational cost of the simulated dynamics

Study of Prevalence of Thalassemia and its variants using HPLC – A Hospital based Retrospective Study

Background: Structural defect in haemoglobin are the most common inherited abnormalities of hemoglobin synthesis. Objective: Early and accurate diagnosis of hemoglobinopathies. Diagnosis of these disorders through HPLC is most convient investigation for diagnosis of hemoglobinapathies. Results and conclusion: Abnormal hemoglobin fractions on HPLC were seen in 338 cases of total 730 samples examined. Out of all the cases, β Thalassemia Minor was the predominant abnormality. 75 cases (10.27%) were β Thalassemia Major and 17 cases (2.325%) were β Thalassemia Intermedia. 2 cases with diagnosis of Sickle β thalassemia were reported. In our study, one case of δβ thalassemia and 4 cases of δβ thalassemia trait were also reported. HPLC is easy and convient method to rule out hemoglobinopathies. The trend of labelling the diagnosis of hemoglobinopathy with HPLC instead of Hb Electrophoresis is rapidly rising. Thus, HPLC is a better tool to rule out hemoglobinopathy and improve the life standards of general population

A Vision-Based Real-Time Adaptive Traffic Light Control System Using Vehicular Density Value and Statistical Block Matching Approach

In India, traffic control management is a difficult task due to an increment in the number of vehicles for the same infrastructure and systems. In the smart-city project, the Adaptive Traffic Light Control System (ATLCS) is one of the major research concerns for an Intelligent Transportation System (ITS) development to reduce traffic congestion and accidents, create a healthy environment, etc. Here, we have proposed a Vehicular Density Value (VDV) based adaptive traffic light control system method for 4-way intersection points using a selection of rotation, area of interest, and Statistical Block Matching Approach (SBMA). Graphical User Interface (GUI) and Hardware-based results are shown in the result section. We have compared, the normal traffic light control system with the proposed adaptive traffic light control system in the results section. The same results are verified using a hardware (raspberry-pi) device with different sizes, colors, and shapes of vehicles using the same method