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Showing 2 results for Bimodal

Ghasem Moslehi, Omolbanin Mashkani,
Volume 29, Issue 1 (3-2018)
Abstract

In single machine scheduling problems with availability constraints, machines are not available for one or more periods of time. In this paper, we consider a single machine scheduling problem with flexible and periodic availability constraints. In this problem, the maximum continuous working time for each machine increases in a stepwise manner with two different values allowed. Also, the duration of unavailability for each period depends on the maximum continuous working time of the machine in that same period, again with two different values allowed. The objective is to minimize the number of tardy jobs. In the first stage, the complexity of the problem is investigated and a binary integer programming model, a heuristic algorithm and a branch-and-bound algorithm are proposed in a second stage. Computational results of solving 1680 sample problems indicate that the branch-and-bound algorithm is capable of not only solving problems of up to 20 jobs but also of optimally solving 94.76% of the total number of problems. Based on numerical results obtained, a mean average error of 2% is obtained for the heuristic algorithm.


Fatima Zohra Allam, Latifa Hamami-Mitiche, Hicham Bousbia-Salah,
Volume 33, Issue 1 (3-2022)
Abstract

For several years, considerable efforts have been made in the field of biometric research. The major interest of this line of research is linked, among other things, to the recognition of the individual because the security needs are becoming increasingly important, and the economic stakes are colossal. There are many and diverse biometric applications that provide a substantial level of security.
Unimodal biometric systems allow a person to be recognized using a single biometric modality, but cannot guarantee correct identification with certainty. While multimodal biometric systems, using several biometric modalities, guarantee better recognition.
In this article, we are interested in the study of evaluation tools for biometric systems. For this, we will first calculate three essential parameters, namely: False Rejection Rate (FRR), False Acceptance Rate (FAR) and Equal Error Rate (EER). Second, we will determine the performance curves, in this case, the ROC curve (Receiver Operating Characteristic) and the DET curve (Detection Error Tradeoff). The calculation of these metrics allows the evaluation of unimodal and bimodal biometric systems to compare the benefit of merging the biometric modalities.

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