Fingerprint Recognition System

Fingerprint Identification System (FIS) is very commonly used in the bio-identification applications. This Project finds out the current techniques for fingerprint recognition. The performance depends upon the quality of images. Fingerprint verification is used for the purpose of criminal investigations, terrorist identification and security issues. This system consists of many stages like image preprocessing, feature extraction and feature match. For each stage, some methods are used. The program is coded by using the MATLAB. For this system some methods at coding and algorithm level, used to improve the performance of the recognition system. Fingerprint recognition system based on minutia based matching which is used in various fingerprint algorithms and techniques. The approach of this project involves how the minutia points are removed from the fingerprint images and after that perform the fingerprint matching between two fingerprint images. The significance of this work is to monitor the matching and similarity for two or more fingerprint images simultaneously

Classical R & D and Laboratory Practises of 8-Methoxy-5-(Morpholin-4-Ylmethyl)-4,4a,5,9b-tetrahydro-1H-pyrazino[2,3-b]indole-2,3-Dicarbonitrile

 Industrial R & D is known for its post attraction after receiving a minimum qualification to get a job in research and development.  Due to ever –increasing failure rates, high cost, unsatisfactory safety profile and limited efficacy associated with production of drug.  It is also seen most of the R & Ds are convert production base R & D.  When we work on any drug in research development we started the thinking of government policies rather than a result.  Actively supports a full range of research focused on using innovation to develop practical solutions to key industry issues - including new product development and commercialization. R & D may be better known in the industry for its work in the field of certification, but it is activity as a research & development (R&D) centre in gemmology has been no less significant. Today, it is the only full-fledged research laboratory in field of gemmology in India, is very difficult recognised as a research certification laboratory. Well equipped with the most sophisticated instruments, R&D department is on par with many international laboratories, having wide ranging capabilities in different aspects of gemmology. Classical laboratory R & D is a platform to create a research mind in small spaces with negative result is best result in research that can improve the research hand and capabilities. We practiced economical laboratory R & D in small space. Here we investigated laboratoty drug through classical R&D of synthetic new drug in minimum sophisticated analytical tools and instrument.&nbsp

Ex-AS-CRED Method for Inter Domain Routing of BGP

Border Gateway Protocol (BGP) acts as a main part of the global infrastructure. Attacks against BGP are increasing and severity. Many of the security mechanisms based on public key cryptography suffer from performance, trust model and other different issues. In this paper we are presenting the new method for solving the security and trust issues in BGP protocol traffic. The recently presented approach is AS-CRED which works on reputation and alert service which not only detect anomalous BGP updates, but also provides a quantitative view of AS tendencies to perpetrate anomalous behavior. The AS-CRED was basically based on the term of credit score. From the practical results, the proposed AS-CRED was efficient for solving the trust issues in complex world of finance which includes the huge amount of entities as well as highly uncertain interactions. However, this limitation of AS-CRED is that prediction approach of future anomalous behavior needs to improve with more accuracy. In this paper we presenting the new method called Ex-AS-CRED [Ex-Extended] with aim of adding the more descriptive AS behaviors and hence the final information of AS reputation is used for prediction of invalid behaviors of BGP. DOI: 10.17762/ijritcc2321-8169.16044

Road Accident Analysis using Data Classification and Association Mining

Roadway traffic safety is a major concern for transportation governing agencies as well as ordinary citizens.Data Mining is taking out of hidden patterns from huge database. It is commonly used in a marketing, surveillance, fraud detection and scientific discovery. In data mining, machine learning is mainly focused as research which is automatically learnt to recognize complex patterns and make intelligent decisions based on data. Globalization has affected many countries. There has been a drastic increase in the economic activities and consumption level, leading to expansion of travel and transportation. The increase in the vehicles, traffic lead to road accidents. Considering the importance of the road safety, government is trying to identify the causes of road accidents to reduce the accidents level. The exponential increase in the accidents data is making it difficult to analyse the constraints causing the road accidents. The paper describes how to mine frequent patterns causing road accidents from collected data set. We find associations among road accidents and predict the type of accidents for existing as well as for new roads. We make use of association and classification rules to discover the patterns between road accidents and as well as predict road accidents for new roads

Review on Analysis of Road Accidents Systems

Data Mining is removing from concealed examples from enormous database. It is generally utilized as a part of a showcasing, observation, extortion identification and logical revelation. In data mining, machine learning is basically engaged as research which is naturally learnt to perceive complex examples and settle on clever choices in light of data. Globalization has influenced numerous nations. There has been an extreme increment in the financial exercises and utilization level, prompting extension of movement and transportation. The expansion in the vehicles, activity prompt road accidents. Thinking about the significance of the road wellbeing, government is endeavoring to distinguish the reasons for road accidents to decrease the accidents level. The exponential increment in the accidents data is making it hard to break down the limitations causing the road accidents. The paper portrays how to mine continuous examples causing road accidents from gathered data set

Implementation on Maximizing Network Topology Lifetime using Mobile Node Rotation

Wireless sensor network (WSN) is facing key challenges like extending network lifetime due to sensor nodes having limited power supplies. Extending WSN lifetime is complicated because nodes often experience differential power consumption. For example, nodes closer to the sink in a given routing topology transmit more data and thus consume power more rapidly than nodes farther from the sink. Inspired by the huddling behavior of emperor penguins where the penguins take turns on the cold extremities of a penguin �huddle�, we propose mobile node rotation, a new method for using low-cost mobile sensor nodes to address differential power consumption and extend WSN lifetime. Specifically, we propose to rotate the nodes through the high power consumption locations. We propose efficient algorithms for single and multiple rounds of rotations

Open-label, randomized, crossover comparative bioavailability study of cefixime from two tablet formulations after single oral administration

Background: Cefixime is an oral extended spectrum third generation cephalosporin, which has marked in vitro bactericidal activity against a wide variety of Gram-positive and Gram-negative organisms, effective in the treatment of community-acquired infections such as respiratory tract infection and urinary tract infection. The objective of this randomized, crossover study was to compare the bioequivalence (BE) of two tablets of test (Milixim® 200 mg, containing 200 mg of cefixime) with Reference formulation (Cefixime, 400 mg).Methods: A total of 12 healthy volunteers were randomly assigned to crossover, single-dose treatment regimens. Serial blood samples were collected, and plasma concentrations of cefixime were analyzed using the high-performance liquid chromatographic technique. Pharmacokinetic parameters and BE limits were calculated using non-compartmental methods.Results: The mean Cmax for the test and reference formulations were 4435.0298±149 and 4408.2150±1021 ng/mL, respectively. The mean area under the serum concentration curve (AUC)0-t were 38108.2614±8583.6535 and 38457.5791±8105.2529 ng/hr/mL The mean ratios (test: reference) for Cmax, AUC0-t, were 99.7% and 98.5%, respectively. There were no significant differences in pharmacokinetic parameters between groups. Overall, the 90% confidence interval for the intra-individual ratios of the log-transformed Cmax and AUC values of the two formulations were within the BE interval of 80-125%.Conclusion: The study has demonstrated the BE of milixim and reference formulation of cefixime

Garenoxacin in skin & skin structure infections complicated by bear bite

Animal bites have always been a common problem to humans. The incidence of resistant organisms is also increasing in the community. Garenoxacin a novel oral des-fluoroquinolone with potent antimicrobial activity against common pathogens causing skin and soft tissue infections, including resistant strains offers the benefit of broad spectrum of coverage including gram positive, gram negative and anaerobic organisms. The result of the case study indicates that garenoxacin is very effective in treating skin and soft tissue infections caused by animal bites

DAY-TRADERS WORKING IN STOCK MARKET & RISK PROFILE OF NONCOMMUNICABLE DISEASES

Background: A Day-trader who is involved typical working day. He/she would have to endure extremes of unpredictable market fluctuations placing them at a greater risk of non-communicable disease. The data regarding these health issues among day-traders working in stock market in India is deficient. Objectives: This study was devised with the aim of studying the risk profile among day-traders and compare them with a comparative group. Materials & Methods: A total of 128 (64 Day-traders; 64 IT-Professionals) were interviewed using the WHO-Steps Questionnaire. Proportions, Mean values, Odds ratio and p-values were calculated with the help of statistical package STATA version 14. Results: The overall mean age of the study participants was 42.24 ±6.61 with the mean age 41.78 ±5.16 and 42.7 ±7.82 respectively. The prevalence rates of alcohol use, tobacco use, inadequate physical activity and inadequate diet among day traders were 68.6%, 56.3%, 64% and 89% respectively. More than 50% were overweight or had abdominal obesity and more than three-fourths had high blood pressure. Conclusions: The burden of NCD risk factors was high in the study population compared to the national averages. The prevalence of risk factors was high in day-traders as compared to IT professionals. Use of tobacco and prevalence of obesity & hypertension were found to be high among day-traders. KEYWORDS: Stock market; Day-trader; Risk-profile; Non-communicable disease; WHO-STEPs approach

A Vision Based Lane Marking Detection, Tracking and Vehicle Detection on Highways

Changing street conditions is an important issue in the applications in mechanized route of vehicles essentially because of vast change in appearance in lane markings on by variables such substantial movement and changing daylight conditions of the specific time of day. A path identification framework is an imperative segment of numerous computerized vehicle frameworks. In this paper, we address these issues through lane identification and vehicle recognition calculation to manage testing situations, for example, a lane end and flow, old lane markings, and path changes. Left and right lane limits will be distinguished independently to adequately handle blending and part paths utilizing a strong calculation. Vehicle discovery is another issue in computerized route of vehicles. Different vehicle discovery approaches have been actualized yet it is hard to locate a quick and trusty calculation for applications, for example, for vehicle crashing (hitting) cautioning or path evolving system .Vision-based vehicle recognition can likewise enhance the crash cautioning execution when it is consolidated with a lane marking identification calculation. In crash cautioning applications, it is vital to know whether the obstruction is in the same path with the sense of self vehicle or not