An effective DeepWINet CNN model for off-line text-independent writer identification

Pattern Analysis and Applications - Writer identification based on handwriting recognition is considered one of the most common research areas in pattern recognition and biometrics. It has...     

Containerization technologies: taxonomies,applications and challenges

Modern scientific research challenges require new technologies, integrated tools, reusable and complex experiments in distributed computing infrastructures. But above all, computing power for efficient data processing and analyzing. Containers technologies have emerged as a new paradigm to address such intensive scientific applications problems. Their easy deployment in a reasonable amount of time and the few required computational resource make them more suitable. Containers are considered light virtualization solutions. They enable performance isolation and flexible deployment of complex, parallel, and high-performance systems. Moreover, they gained popularity to modernize and migrate scientific applications in computing infrastructure management. Additionally, they reduce computational time processing. In this paper, we first give an overview of virtualization and containerization technologies. We discuss the taxonomies of containerization technologies of the literature, and then we provide a new one that covers and completes those proposed in the literature. We identify the most important application domains of containerization and their technological progress. Furthermore, we discuss the performance metrics used in most containerization techniques. Finally, we point out research gaps in the related aspects of containerization technology that require more research.

     

Rapid and efficient hand gestures recognizer based on classes discriminator wavelet networks

Multimedia Tools and Applications - The vision based on hand gesture recognition is one of the key challenges in behavior understanding and computer vision. It offers to machines the possibility of...     

Optimization of nutrient-induced germination of Bacillus sporothermodurans spores using response surface methodology

Spores of Bacillus sporothermodurans are known to be contaminant of dairy products and to be extremely heat-resistant. The induction of endospore germination before a heat treatment could be an efficient method to inactivate these bacteria and ensure milk stability. In this study, the nutrient-induced germination of B. sporothermodurans LTIS27 spores was studied. Testing the effect of 23 nutrient elements to trigger an important germination rate of B. sporothermodurans spores, only d-glucose, l-alanine, and inosine were considered as strong independent germinants. Both inosine and l-alanine play major roles as co-germinants with several other amino acids. A central composite experimental design with three factors (l-alanine, d-glucose, and temperature) using response surface methodology was used to optimize the nutrient-induced germination. The optimal rate of nutrient-induced germination (100%) of B. sporothermodurans spores was obtained after incubation of spore for 60 min at 35 °C in presence of 9 and 60 mM of d-glucose and l-alanine, respectively. The results in this study can help to predict the effect of environmental factors and nutrients on spore germination, which will be beneficial for screening of B. sporothermodurans in milk after induction their germination. Moreover, the chosen method of optimization of the nutrient-induced germination was efficient in finding the optimum values of three factors.     

A multiresolution wavelet networks architecture and its application to pattern recognition

This paper aims at addressing a challenging research in both fields of the wavelet neural network theory and the pattern recognition. A novel architecture of the wavelet network based on the multiresolution analysis (MRWN) and a novel learning algorithm founded on the Fast Wavelet Transform (FWTLA) are proposed. FWTLA has numerous positive sides compared to the already existing algorithms. By exploiting this algorithm to learn the MRWN, we suggest a pattern recognition system (FWNPR). We show firstly its classification efficiency on many known benchmarks and then in many applications in the field of the pattern recognition. Extensive empirical experiments are performed to compare the proposed methods with other approaches.     

Application of iterative dynamic programming to optimal control of a distiltation column

Iterative Dynamic Programming (IDP) is proven to be a useful technique for solving constrained dynamic optimisation problems. A high purity binary distillation column model has been chosen to investigate some of the IDP properties as well as its applicability. The investigated problems cover transitions from one steady state to another with the minimization of a quadratic cost function with associated terminal constraints.     

Nonlinear state feedback design for continuous polynomial systems

The objective of this paper is to simplify the complexity of practical implementation of the input-state feedback linearization technique for the control of input-affine systems. A polynomial approach which makes use of the Taylor series expansion and the Kronecker product is developed. Our work aims to address the problem of synthesizing a polynomial control via a nonlinear analytical coordinates transformation. To check the effectiveness of the investigated approach, we consider the control problem of a series DC motor. A comparative study with the input-state feedback linearization control is developed.     

Improving the performance of retail stores subject to execution errors: coordination versus RFID technology

This paper analyzes a Newsvendor type inventory model in which a manufacturer sells a single product to a retailer store whose inventory is subject to errors stemming from execution problems. Hence, within the store, all of the products are not available on shelf for sales either because the replenishment of the shelf from the backroom is subject to execution errors that mainly result in products lost in the backroom or products misplaced on the other shelves of the store. We compare two situations: in the first situation, the two supply chain actors are aware of errors and optimize their ordering decisions by taking into account this issue. The second situation deals with the case where an advanced automatic identification system such as the Radio Frequency Identification technology is deployed in order to eliminate errors. Each situation is developed for three scenarios: in the centralized scenario, we consider a single decision-maker who is concerned with maximizing the entire supply chain’s profit; in the decentralized uncoordinated scenario, the retailer and the manufacturer act as different parties and do not cooperate. The third scenario is the decentralized coordinated scenario where we give conditions for coordinating the channel by designing a buyback contract. The authors would like to thank the editor, Prof. Dr. Hans-Otto Guenther, and two anonymous referees for their constructive comments to improve this article.     

The creep of an elastoviscoplastic beam under a bending loading

Thermoplastics start to manifest a nonlinear mechanical behavior from relatively low loading levels. Under a bending solicitation, which generates a nonuniform stress field, the material behavior becomes more challenging. Indeed, a flexed specimen may have different behaviors from one point to another according to the local stress state. In the present work, a six-parameter rheological model is used to simulate the nonlinear behavior of an elastoviscoplastic beam, subjected to a three-point bending load. In the framework of Euler–Bernoulli theory, the mathematical formulation of a bent beam behavior involves the bending curvature function. This function allows the determination of the strain and stress fields along and through the beam. However, when the beam reaches the viscoplastic stage, the differential equation providing the bending curvature of the beam requires a numerical integration, which has been accomplished in this work. This theoretical modeling approach is supported by experimental creep tests carried out on polyamide specimens (PA6). The testing results are qualitatively consistent with the predictions of the proposed rheological model.     

The news-vendor problem with drop-shipping and resalable returns

As e-commerce expands, more and more products are offered online to attract internet consumers’ interest. These products are then shipped to consumers’ home by a drop-shipper. Drop-shipping seems to be a good option to sell products in addition to physical stores. Furthermore, both types of products, either sold in store or on Internet can be returned by consumers, with often a higher return ratio for those purchased on Internet. To model these two sales channel and the interactions between them, we consider a News-Vendor (NV) managing both a physical store and an online sale channel that can be fulfilled by a drop-shipping option. We also consider the possibility of reselling products that are returned by consumers during the selling season. The concavity of the expected profit is proven and the optimality condition is obtained. Promising results are obtained from a numerical analysis. In particular, we show that the expected profit can be 14.4% less than the optimal expected profit if the return effect is ignored. Using drop-shipping option can reduce the optimal store inventory by 31.2% and if the NV has no drop-shipping option, the expected profit can be 9% less.