Honey has a long history of use in many cultures as food and medicine. It is a food of animal origin closely linked to the territory, due to honeybees need the flora to obtain the honey. Melissopalynology plays a significant role in the identification of the distinctive food print of honey throughout its pollen content, being essential for guaranteeing origin. Algeria is the largest country in North Africa and possesses a diversified territory with different ecosystems that host wide plant biodiversity. Apiculture relies heavily on the pollination of plant species and the conservation of biodiversity, but also is a good source of economic income in rural areas. In Algeria, knowledge about plant resources for honey bees and the properties of the honey is raising interest. In this context, this chapter aims to provide a comprehensive overview of the different ecosystems of Algeria, the main pollen types found in the pollen spectra of honey and the principal honey types described.

Alors que la professionnalisation de toute formation exige la prise en considération des besoins des formés et des exigences de la profession, l’Algérie continue d’importer des offres de formation con\c cues dans d’autres pays et dédiées à des publics particuliers. Distincts de ces publics, les formés algériens se préparant à enseigner les langues étrangères ont besoin de formations plus adaptées à leurs attentes et à celles des acteurs impliqués. Ce résultat, auquel nous avons abouti, suite à l’analyse des maquettes de formation, nous a conduits à proposer des réflexions et un profil psychologique-type pouvant améliorer la formation des enseignants et leur future pratique.

Abstract

In this chapter, we have conducted a statistical study of the annual extreme precipitation (AMP) for 856 grid cells and during the period of 1979–2012 in Algeria. In the first step, we compared graphically the forecasts of the three parameters of the generalized extreme value (GEV) distribution (location, scale and shape) which are estimated by the Spherical model. We used the Cross validation method to compare the two methods kriging and Co-kriging, based on the based on some statistical indicators such as Mean Errors (ME), Root Mean Square Errors (RMSE) and Squared Deviation Ratio (MSDR). The Kriging forecast error map shows low errors expected near the stations, while co-Kriging gives the lowest errors on average at the national level, which means that the method of co-Kriging is the best. From the results of the return periods, we calculate that after 50 years the estimated of the annual extreme precipitation will exceed the maximum AMP is observed in the 33-year.

In recent decades, vascular surgery has seen the arrival of endovascular techniques for the treatment of vascular diseases such as aortic diseases (aneurysms, dissections, and atherosclerosis). The 3D printing process by addition of material gives an effector of choice to the digital chain, opening the way to the manufacture of shapes and complex geometries, impossible to achieve before with conventional methods. This chapter focuses on the bio-design study of the thoracic aorta in adults. A bio-design protocol was established based on medical imaging, extraction of the shape, and finally, the 3D modeling of the aorta; secondly, a bio-printing method based on 3D printing that could serve as regenerative medicine has been proposed. A simulation of the bio-printing process was carried out under the software Simufact Additive whose purpose is to predict the distortion and residual stress of the printed model. The binder injection printing technique in a Powder Bed Printer (PBP) bed is used. The results obtained are very acceptable compared with the results of the error elements found.

The most important components used in aerospace, ships, and automobiles are designed with free form surfaces. An impeller is one of the most important components that are difficult to machine because of its twisted blades. This research book is based on the premise that a STEP-NC program can document “generic” manufacturing information for an impeller. This way, a STEP-NC program can be made machine-independent and has an advantage over the conventional G-code-based NC program that is always generated for a specific CNC machine. Rough machining is recognized as the most crucial procedure influencing machining efficiency and is critical for the finishing process. The research work reported in this chapter focuses on introduces a fully STEP-compliant CNC by putting forward an interpolation algorithm for non uniform rational basic spline (NURBS) curve system for rough milling tool paths with an aim to solve the problems of kinematic errors solutions in five axis machine by neural network implementation.

Nowadays, we assist the global extension of reliability optimization problems from the design phase of systems and sub-systems to the design and operational phases, not only of systems and sub-systems, but also of bio functionality design. This chapter investigates the relative performances of particle swarm optimization (PSO) variants when used to find reliability in the total hip prosthesis by finding the maximization of jumping distance (JD) to avoid dislocation and the minimization of system’s stability to offer mobility. Statistical analysis of different cases of head diameters of 22, 28, 36, 40 mm has been conducted to survey the convergence and relative performances of the main PSO variants when applied to solve reliability in the total hip prosthesis.

In recent decades, vascular surgery has seen the arrival of endovascular techniques for the treatment of vascular diseases such as aortic diseases (aneurysms, dissections, and atherosclerosis). The 3D printing process by addition of material gives an effector of choice to the digital chain, opening the way to the manufacture of shapes and complex geometries, impossible to achieve before with conventional methods. This chapter focuses on the bio-design study of the thoracic aorta in adults. A bio-design protocol was established based on medical imaging, extraction of the shape, and finally, the 3D modeling of the aorta; secondly, a bio-printing method based on 3D printing that could serve as regenerative medicine has been proposed. A simulation of the bio-printing process was carried out under the software Simufact Additive whose purpose is to predict the distortion and residual stress of the printed model. The binder injection printing technique in a Powder Bed Printer (PBP) bed is used. The results obtained are very acceptable compared with the results of the error elements found.

This chapter focuses on double gate (DG) Tunneling Field Effect Transistor (TFET), having band engineering and high - k dielectrics. The basic structure of TFET device is derived and developed by p-i-n diode, containing two heavily doped degenerated semiconductor “p” and “n” regions and lightly doped intrinsic “i” region, respectively. The chapter explores the idea of high-k dielectric engineering as well as band engineering concept with DG -TFET. TFET is a type of field effect device in which current transport phenomena occur due to quantum tunneling between source and channel. The estimation of device characteristics and performance of TFET is time consuming and costly due to lack of rapid advancement in technology. TFET devices have become the most popular switching device among semiconductor players. The chapter summarizes the obtained results by popular device analysis technique, modeling and simulation of DG -TFET.

This work presents the prediction of the rate of progression in oil drilling based on random forest algorithm, which is part of the family of ensemble machine learning. The ROP parameter plays a very important role in oil drilling, which has a great impact on drilling costs, and its prediction allows drilling engineers to choose the best combination of input parameters for better progress in drilling operations. To resolve this problem, several works have been realized with the different modeling techniques as machine learning: RNAs, Bayesian networks, SVM etc. The random forest algorithm chosen for our model is better than the other MLS techniques. in speed or precision, following what we found in the literature and tests done with the open source machine learning tool on historical oil drilling logs from fields of Hassi Terfa located in southern Algeria.