Modeling and implementation of an automatic Access control system for secure permises using facial recognition

Security is a major concern within companies to prevent access to information by unauthorized persons.  In this work, we are interested in access control through facial recognition. To realize this access control system based on facial recognition, we used an embedded system under Arduino which gives us the possibility to assemble the performances of programming and electronics, more precisely, we programmed electronic systems for the automatic opening of doors without the action of a human being. From a sample of 100 individuals composed of 40 women and 60 men, 75 of whom were registered and 25 non-registered, our access control system obtained the results of 70 true positives, 5 false negatives, 8 false positives and 17 true negatives that constitute our confusion matrix. However, from the set of tests performed we can conclude that multi-modality fusion can be leveraged to increase the performance of the verification system as the verification performance of multimodal systems (feature fusion or score fusion) can be applied to give even better results

Parallel and Distributed Computation of a Fingerprint Access Control System

This work evaluates the runtime performance of a single-mode biometric recognition system for fingerprint-based access control to secure premises. To speed up the computation time in this system, we resorted to parallel programming, targeting more loops in the verification module. Our approach would therefore be to parallelize all loops that are computationally intensive during the verification of fingerprints in the database. On this, we exploited Microsoft's Task Parallel Library, specifically exploiting the for and for each loop. On the test set performed in sequential and parallel versions in the different data sizes, namely 50, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, and 600, we can state that the results obtained by the sequential and parallel implementations of our performance test programs allowed us to determine the best approach. Therefore, it is very clear that the sequential program is too greedy in terms of computation time compared to the parallel program which minimizes the computation time

Analysis of the Performance Measures of a Non-Markovian Fuzzy Queue via Fuzzy Laplace Transforms Method

Laplace transforms play an essential role in the analysis of classical non-Markovian queueing systems. The problem addressed here is whether the Laplace transform approach is still valid for determining the characteristics of such a system in a fuzzy environment. In this paper, fuzzy Laplace transforms are applied to analyze the performance measures of a non-Markovian fuzzy queueing system FM/ FG/1. Starting from the fuzzy Laplace transform of the service time distribution, we define the fuzzy Laplace transform of the distribution of the dwell time of a customer in the system. By applying the properties of the moments of this distribution, the derivative of this fuzzy transform makes it possible to obtain a fuzzy expression of the average duration of stay of a customer in the system. This expression is the fuzzy formula of the same performance measure that can be obtained from its classical formula by the Zadeh extension principle. The fuzzy queue FM/ FE_k /1 is particularly treated in this text as a concrete case through its service time distribution. In addition to the fuzzy arithmetic of L-R type fuzzy numbers, based on the secant approximation, the properties of the moments of a random variable and Little's formula are used to compute the different performance measures of the system. A numerical example was successfully processed to validate this approach. The results obtained show that the modal values of the performance measures of a non-Markovian fuzzy queueing system are equal to the performance measures of the corresponding classical model computable by the Pollaczeck-Khintchine method. The fuzzy Laplace transforms approach is therefore applicable in the analysis of a fuzzy FM/FG/1 queueing system in the same way as the classical M/G/1 model

Modeling and implementation of an automatic Access control system for secure permises using facial recognition

Security is a major concern within companies to prevent access to information by unauthorized persons.  In this work, we are interested in access control through facial recognition. To realize this access control system based on facial recognition, we used an embedded system under Arduino which gives us the possibility to assemble the performances of programming and electronics, more precisely, we programmed electronic systems for the automatic opening of doors without the action of a human being. From a sample of 100 individuals composed of 40 women and 60 men, 75 of whom were registered and 25 non-registered, our access control system obtained the results of 70 true positives, 5 false negatives, 8 false positives and 17 true negatives that constitute our confusion matrix. However, from the set of tests performed we can conclude that multi-modality fusion can be leveraged to increase the performance of the verification system as the verification performance of multimodal systems (feature fusion or score fusion) can be applied to give even better results

Comparative studies between minimum spanning tree algorithms and shortest paths tree algorithms

This paper solves the problem of optimal modelling in a transmission network based on the minimum weight spanning tree method while comparing these results with those obtained by the shortest path method. More precisely, we have modelled the electrical transmission network passing through the twenty-six provinces of the Democratic Republic of Congo, based on the PRIM and KRUSKAL algorithms, which allow the calculation of the minimum weight spanning tree while comparing these results with those obtained by the DIJKSTRA algorithm, which is based on the calculation of shortest paths between the nodes of the network. The aim is to minimize the investment in defining the overall architecture of the DRC's electricity transmission network. The results of this work show that the cost of a network optimized by the minimum spanning tree algorithm is limited to a maximum of 36% of the cost of any other implementation of the same network. The savings that can be made by using the right optimization method when implementing power networks are not negligible and it is well worthwhile for decision-makers in this sector to keep this in mind

STUDY AND IMPROVEMENT OF PERFORMANCE OF NoSQL DATABASES: MongoDB, HBase and OrientDB.

This dissertation adds to the various research works in the field of NoSQL "Not only SQL" databases. These new models propose a new way of organizing and storing data designed mainly to remedy the constraints imposed by the ACID properties on relational models. Our objective was to develop a comparative performance study, between three NoSQL solutions widely used in the market, namely: MongoDB, HBase and OrientDB, to propose to decision makers, elements of information for possible choices of the best appropriate solution for their companies. The Benchmark used to decide between these solutions is the Yahoo Cloud Serving Benchmark

Implementation of an access control system based on bimodal biometrics with fusion of global decisions: Application to facial recognition and fingerprints

Single-mode biometric systems suffer from several problems that make them unsuitable for current biometric applications that require high levels of reliability and security. These problems include the use of a single biometric trait that is prone to noise, poor capture, lack of biometric points, and deterioration of biometric input quality. In this paper, we are interested in decision fusion access control on a biometric bimodal pattern recognition system based on fingerprints and facial recognition. To realize this access control system based on facial recognition and fingerprints, we used an embedded system under Arduino, we programmed electronic systems for the automatic opening of doors without human action being. The performance evaluation of decision fusion access control on a biometric bimodal pattern recognition system is realized by means of the confusion matrix, the calculations of the evaluation parameters (Sensitivity, Specificity, Positive Predictive Value, Negative Predictive Value and False Negative). From a sample of 500 individuals, 250 of whom were registered and 250 non-registered, our access control system obtained the results of 248 true positives, 2 false negative, 1 false positive and 249 true negatives which constitute our confusion matrix. However, from the set of tests performed we can conclude that by taking advantage of the fusion of these two modalities, we increase the verification performance of system as the verification performance of bimodal system (fingerprint decision fusion and facial recognition) is applied to give even better results compared to single mode systems

Parallel and Distributed Computation of a Fingerprint Access Control System

This work evaluates the runtime performance of a single-mode biometric recognition system for fingerprint-based access control to secure premises. To speed up the computation time in this system, we resorted to parallel programming, targeting more loops in the verification module. Our approach would therefore be to parallelize all loops that are computationally intensive during the verification of fingerprints in the database. On this, we exploited Microsoft's Task Parallel Library, specifically exploiting the for and for each loop. On the test set performed in sequential and parallel versions in the different data sizes, namely 50, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, and 600, we can state that the results obtained by the sequential and parallel implementations of our performance test programs allowed us to determine the best approach. Therefore, it is very clear that the sequential program is too greedy in terms of computation time compared to the parallel program which minimizes the computation time

COMPARATIVE STUDIES BETWEEN A FACIAL RECOGNITION SYSTEM AND A FINGERPRINT RECOGNITION SYSTEM FOR ACCESS CONTROL

This paper investigates the decisions made on two singles modal biometric systems based on facial recognition and fingerprints for access control. In order to carry out this study on the access control system based on fingerprint and facial recognition, we made biometric recognition systems based on fingerprints and facial recognition that interacts with an embedded system under Arduino to give us the possibility to assemble the performances of programming and electronics, more precisely, we programmed electronic systems for the automatic opening of doors without the action of a human being. In a sample of one hundred individuals composed of 40 females and 60 males, 75 of whom were enrolled and 25 of whom were not, our two singles modal access control systems each obtained the following results: 70 true positives, 5 false negatives, 8 false positives and 17 true negatives for the facial recognition system, compared to 73 true positives, 2 false negatives, 4 false positives and 21 true negatives for the fingerprint recognition system, which constitute our confusion matrix. From all the tests carried out, we can say that the decisions made by the fingerprint recognition system are better than the decisions made by the facial recognition system

Implementation of an access control system based on bimodal biometrics with fusion of global decisions: Application to facial recognition and fingerprints

Single-mode biometric systems suffer from several problems that make them unsuitable for current biometric applications that require high levels of reliability and security. These problems include the use of a single biometric trait that is prone to noise, poor capture, lack of biometric points, and deterioration of biometric input quality. In this paper, we are interested in decision fusion access control on a biometric bimodal pattern recognition system based on fingerprints and facial recognition. To realize this access control system based on facial recognition and fingerprints, we used an embedded system under Arduino, we programmed electronic systems for the automatic opening of doors without human action being. The performance evaluation of decision fusion access control on a biometric bimodal pattern recognition system is realized by means of the confusion matrix, the calculations of the evaluation parameters (Sensitivity, Specificity, Positive Predictive Value, Negative Predictive Value and False Negative). From a sample of 500 individuals, 250 of whom were registered and 250 non-registered, our access control system obtained the results of 248 true positives, 2 false negative, 1 false positive and 249 true negatives which constitute our confusion matrix. However, from the set of tests performed we can conclude that by taking advantage of the fusion of these two modalities, we increase the verification performance of system as the verification performance of bimodal system (fingerprint decision fusion and facial recognition) is applied to give even better results compared to single mode systems