Mohamed Rasmy

A Multimodal Hand Vein, Hand Geometry, and Fingerprint Prototype Design for High Security Biometrics

Prior research evidenced that the unimodal biometric systems have several tradeoffs like noisy data, intra-class variations, restricted degrees of freedom, non-universality, spoof attacks, and unacceptable error rates. In order for the biometric system to be more secure and to provide higher accuracy, more than one form of biometrics are required. Hence, the need arise for multimodal biometrics using combinations of different biometric modalities. We describe the design and development of whole hands biometrics prototype system that acquires left and right (L/R) index and ring fingerprints (FP), L/R near-infra-red (NIR) dorsal hand vein (HV) patterns, and L/R NIR dorsal hand geometry (HG) shape. Large database of 500-1000 subjects for whole hands is planned for data collection. The acquired sample images were found to have good quality for all features and patterns extraction to all modalities. The designed prototype can be considered for authentication and identification purposes. Advantages of this system over few existing multimodal systems are its being very hard to spoof attacks on the sensory level and the NIR HV and NIR HG thermal images are good signals for liveness detection.

Supply Chain Performance Measurement Approaches: Review and Classification

Interest in the topic of supply chain performance measurement has notably increased in the last two decades and considerable research has been conducted in this area. The objective of this paper is not just to review the advancements in theory on supply chain performance measurement per se, but rather to provide a taxonomy with which research in the field can be mapped and evaluated. The need for a structured topological approach to the development of supply chain performance measurement frameworks and methods is addressed. Findings are based on the analysis of a huge number of publications including the most recent reviews conducted in the contemporary literature (books, theses, journal articles and conference papers). The researchers believe that currently existing supply chain performance measurement frameworks can be classified into nine different types grouped according to the key criteria of measurement. This research reveals that most of the already existing approaches are static, inflexible and lack continual improvement which constitutes a gap between the theory and their potential application. Thus, future contributions to the topic are essential and possible.

A Hybrid Dynamic Framework for Supply Chain Performance Improvement

Improving supply chain performance has become a critical issue for gaining a competitive edge for companies. Many critical drawbacks prevent the existing performance measurement systems from making a significant contribution to the development and improvement of supply chain management and thus, several research is still needed in this area. In an attempt to fill this gap, an enhanced process-based approach for measuring, managing, and hence improving supply chain performance is presented. The proposed framework is dynamic, continuous, and hybrid. It integrates various sciences, methodologies, and tools, namely systems thinking, strategic planning, optimization, balanced scorecards, supply chain operations reference model, and theory of constraints thinking processes into a cohesive performance measurement system. In this paper, a comparison between the proposed approach and currently existing systems is provided highlighting how each methodology contributed in the enhancement.

An Innovative Fuzzy Logic Based Approach for Supply Chain Performance Management

In the last decade, the topic of supply chain performance measurement has attracted the attention of many researchers and practitioners worldwide. A series of significant changes and advancements in the theory and applications has been noticed. Nevertheless, gaps still exist. Current supply chain performance measurement systems still suffer from being too inward looking, ignoring external environmental factors that might affect the overall supply chain performance in the future when setting new targets. In this paper, we introduce an innovative approach to supply chain performance management. The proposed idea integrates fuzzy logic with trend impact analysis and provides a scenarios-based method that simulates and quantifies the possible effect of external factors on the supply chain performance, and thus enables setting realistic achievable targets. The idea is novel and beyond the state of the art of supply chain performance measurement.

Electrocardiogram signals identification for cardiac arrhythmias using prony's method and neural network

A new method is presented to identify Electrocardiogram (ECG) signals for abnormal heartbeats based on Pronys modeling algorithm and neural network. Hence, the ECG signals can be written as a finite sum of exponential depending on poles. Neural network is used to identify the ECG signal from the calculated poles. Algorithm classification including a multi-layer feed forward neural network using back propagation is proposed as a classifying model to categorize the beats into one of five types including normal sinus rhythm (NSR), ventricular couplet (VC), ventricular tachycardia (VT), ventricular bigeminy (VB), and ventricular fibrillation (VF).

Configuration irrigation schedule based on expert systems and operations research

Abstract This paper presents configuration design knowledge to solve irrigation scheduling problem in agriculture domain and a general approach for configuration management knowledge. It also introduces a Configuration Agriculture Irrigation Schedule (CAIS) tool that produces the configuration irrigation schedule design according to the CommonKADS methodology. A configuration that satisfy the user requirements, and that additionally satisfy some optimality criteria is required. By integrating Dynamic programming and inference knowledge, with demand including different objective, that it is used in generating the inference steps (PPSM) to select the suitable components of the inference steps minimizing the number of components and/or maximizing the accuracy of the result of each inference step. Operations Research techniques greatly improved the understanding of the interactions of a large number of components and enhanced the decision selection under uncertain outcomes.

Multimodal biometrics system based on face profile and ear

Face recognition from a side profile view, has recently received significant attention in the literature. Even though current face recognition systems have reached a certain level of maturity at angles up to 30 degrees, their success is still limited with side profile angles. This paper presents an efficient technique for the fusion of face profile and ear biometrics. We propose to use a Block-based Local Binary Pattern (LBP) to generate the features for recognition from face profile images and ear images. These feature distributions are then fused at the score level using simple mean rule. Experimental results show that the proposed multimodal system can achieve 97:98% recognition performance, compared to unimodal biometrics of face profile 96.76%, and unimodal biometrics of ear 96.95%, details in the Experimental Results Section. Comparisons with other multimodal systems used in the literature, like Principal Component Analysis (PCA), Full-space Linear Discriminant Analysis (FSLDA) and Kernel Fisher discriminant analysis (KFDA), are presented in the Experimental Results Section.

One-dimensional steady state seawater intrusion in leaky aquifers

Abstract An iterative technique is presented to compute the location and shape of the interior interface for the one-dimensional steady state seawater intrusion problem in a coastal leaky aquifer. Upper and lower bounds on the location of the top tip point of the interface are deduced based upon the aquifer geometry. Moreover, the dependency of the locations of the top tip point as well as the toe of the interface on the inland boundary condition are obtained through variational analysis of the governing equations. A considerable reduction in the computational effort is shown to be possible provided there is available information about whether the water hinge point lies on or outside the interface. Numerical results are furnished to indicate the efficiency of the proposed algorithm.