Yield response of lentil to directly applied and residual phosphorus in a Mediterranean environment

The response of lentil grown under rainfed conditions to directly applied and residual phosphorus (P) was described by a modified Mitscherlich equation, accounting for the effects of rainfall on (1) potential yield, and (2) the availability of soil-P to the crop. The response of lentil yield to directly applied and residual P was studied in two-course cereal–lentil rotational trials under rainfed conditions in a Mediterranean-type environment. Cereal crops were grown at different P application rates during 4 growing seasons at 3 sites, representing different rainfall zones in northwest Syria. Lentil (Lens culinaris Med.) was grown during 4 seasons at the same sites, each lentil crop following a cereal crop. In 3 out of 4 lentil-growing seasons, additional P was applied to lentil in subplots to compare the residual and direct effects of P application. The initial contents of extractable soil-P (P-Olsen) were low at all sites, in the range of 2–5 ppm P. Under the conditions of the experiments, lentil appeared to benefit slightly more from P applied to the preceding wheat crop (residual P) than from directly applied P. It is shown that the modified Mitscherlich equation could be used as a basis for P fertilizer recommendations for rainfed farming. As for lentil, it was concluded that a single application of P to the wheat crop in a wheat/lentil rotation could reduce the cost of lentil production, without reducing lentil yield.     

Sintering-driven effects on the band gap of (Pb,La)(Ti,Ni)O3 photovoltaic ceramics

In this work, the influence of the sintering temperature on the physical properties of (Pb_0.8La_0.2)(Ti_0.9Ni_0.1)O₃ (PLT-Ni) ceramics is reported. The experimental data revealed that the energy band gap of PLT-Ni ceramics could be tailored from approximately 2.7 to 2.0 eV by changing the sintering temperature from 1100°C to 1250°C. It is demonstrated that the simple substitution of Ti⁴⁺ by Ni²⁺ cations is effective to decrease the intrinsic band gap while increasing the tetragonality factor and the spontaneous polarization. However, the additional red-shift observed in the absorption edge of the PLT-Ni with increasing the sintering temperature was associated with a continuous increase in the oxygen vacancies () amount. It is believed that the impact of the creation of these thermally induced is manifold. The presence of and Ni²⁺ ions generate the Ni²⁺- defect-pairs that promoted both a decrease in the intrinsic band gap and an additional increase of the tetragonality factor, consequently, increasing the spontaneous polarization. The creation of Ni²⁺- defects also changed the local symmetry of Ni²⁺ ions from octahedral to a square pyramid, thus lifting the degeneracy of the Ni²⁺ 3d orbitals. With the increase in the sintering temperature, lower-energy absorbing intraband states were also formed due to an excess of , being responsible for an add-on shoulder in the absorption edge, extending the light absorption curve to longer wavelengths and leading to an additional absorption in “all investigated” spectrum as well.     

Synthesis and characterization of saturated and unsaturated copolyesters based on bis-1,4-(dicarboxymethoxy) benzene

Saturated copolyester were prepared by copolyesterification of bis-1,4-(dicarboxymethoxy) benzene and phthalic anhydride with diethylene glycol, triethylene glycol, tetraethylene glycol, 1,4-butane diol, 1,2-propane diol, and 1,6-hexamethylene glycol. Also, unsaturated copolyesters were prepared by copolyesterification of bis-1,4-(dicarboxymethoxy) benzene and maleic anhydride with the same glycols. All the copolyester resins obtained have been characterized and unsaturated copolyesters in the form of films were determined. IR and ¹H-NMR spectroscopy were used for both qualitative and quantitative analysis of the copolyesters resins and their hydrolyzate products, after curing with styrene. © 1992 John Wiley & Sons, Inc.     

Augmented grasshopper optimization algorithm by differential evolution: a power scheduling application in smart homes

With the increasing number of electricity consumers, production, distribution, and consumption problems of produced energy have appeared. This paper proposed an optimization method to reduce the peak demand using smart grid capabilities. In the proposed method, a hybrid Grasshopper Optimization Algorithm (GOA) with the self-adaptive Differential Evolution (DE) is used, called HGOA. The proposed method takes advantage of the global and local search strategies from Differential Evolution and Grasshopper Optimization Algorithm. Experimental results are applied in two scenarios; the first scenario has universal inputs and several appliances. The second scenario has an expanded number of appliances. The results showed that the proposed method (HGOA) got better power scheduling arrangements and better performance than other comparative algorithms using the classical benchmark functions. Moreover, according to the computational time, it runs in constant execution time as the population is increased. The proposed method got 0.26?% enhancement compared to the other methods. Finally, we found that the proposed HGOA always got better results than the original method in the worst cases and the best cases.

     

Recognizing arabic handwritten characters using deep learning and genetic algorithms

Automated techniques for Arabic content recognition are at a beginning period contrasted with their partners for the Latin and Chinese contents recognition. There is a bulk of handwritten Arabic archives available in libraries, data centers, historical centers, and workplaces. Digitization of these documents facilitates (1) to preserve and transfer the country’s history electronically, (2) to save the physical storage space, (3) to proper handling of the documents, and (4) to enhance the retrieval of information through the Internet and other mediums. Arabic handwritten character recognition (AHCR) systems face several challenges including the unlimited variations in human handwriting and the leakage of large and public databases. In the current study, the segmentation and recognition phases are addressed. The text segmentation challenges and a set of solutions for each challenge are presented. The convolutional neural network (CNN), deep learning approach, is used in the recognition phase. The usage of CNN leads to significant improvements across different machine learning classification algorithms. It facilitates the automatic feature extraction of images. 14 different native CNN architectures are proposed after a set of try-and-error trials. They are trained and tested on the HMBD database that contains 54,115 of the handwritten Arabic characters. Experiments are performed on the native CNN architectures and the best-reported testing accuracy is 91.96%. A transfer learning (TF) and genetic algorithm (GA) approach named “HMB-AHCR-DLGA” is suggested to optimize the training parameters and hyperparameters in the recognition phase. The pre-trained CNN models (VGG16, VGG19, and MobileNetV2) are used in the later approach. Five optimization experiments are performed and the best combinations are reported. The highest reported testing accuracy is 92.88%.

     

Progress and challenges in sustainability,compatibility, and production of eco-composites: A state-of-art review

Owing to economic and environmental benefits, new generations of materials/commodities follow “from waste to wealth” strategy. Recently, there has been a huge upsurge in research on the development of eco-composites using recycled plastic polymers and agro-residues because the eco-composites satisfy the stringent environment regulations and are cost-effective. Herein, we present a detailed review on the potential use of several types of natural fillers as an efficient reinforcement for recycled plastic polymers. In particular, the characterization of different categories of eco-composites according to their morphological, physical, thermal, and mechanical properties is extensively reviewed and their results are analyzed, compared, and highlighted. Furthermore, a framework to produce functional eco-composites, which includes functionalization of ingredients, critical issues on microstructural parameters, processing, and fabrication methods, is outlined and supported with sufficient data from the literature. Finally, the review outlines the emerging challenges and future prospects of eco-composites to be addressed by interested researchers to bridge the gap between research and commercialization of such a class of material. Overall, the acquired knowledge will guide researchers, scientists, and manufacturers to plan, select, and develop various forms of eco-composites with enhanced properties and optimized production processes.     

PCET based copy-move forgery detection in images under geometric transforms

With the advent of the powerful editing software and sophisticated digital cameras, it is now possible to manipulate images. Copy-move is one of the most common methods for image manipulation. Several methods have been proposed to detect and locate the tampered regions, while many methods failed when the copied region undergone some geometric transformations before being pasted, because of the de-synchronization in the searching procedure. This paper presents an efficient technique for detecting the copy-move forgery under geometric transforms. Firstly, the forged image is divided into overlapping circular blocks, and Polar Complex Exponential Transform (PCET) is employed to each block to extract the invariant features, thus, the PCET kernels represent each block. Secondly, the Approximate Nearest Neighbor (ANN) Searching Problem is used for identifying the potential similar blocks by means of locality sensitive hashing (LSH). In order to make the algorithm more robust, morphological operations are applied to remove the wrong similar blocks. Experimental results show that our proposed technique is robust to geometric transformations with low computational complexity.     

Design of hexa‐band planar inverted‐F antenna using hybrid BSO‐NM algorithm for mobile phone communications

This article presents a new design of multiband planar inverted‐F antenna with slotted ground plane and S‐etched slot on the radiation patch. The proposed antenna is optimized using an efficient global hybrid optimization method combining bacterial swarm optimization and Nelder‐Mead (BSO‐NM) algorithm to cover a very important six service bands including GSM900, GPS1575, DCS1800, PCS1900, ISM2450, and 4G5000 MHz with enhanced bandwidths. The BSO‐NM algorithm in Matlab code is linked to the CST Microwave studio software to simulate the antenna. To validate the results, the antenna is analyzed using the finite difference time domain (FDTD) method. A good agreement is achieved between the results of EM simulation and that produced from the FDTD method. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2013.     

New Hybrid Access Method for Femtocell through Adjusting QoS

The increasing number of mobile users raises issues about coverage extension in some areas such as rural zones, indoor or underground locations： one of suggestion solution to accommodate this growing of mobile user is femtocell. Femtocell have been attracting considerable attention in mobile communications, it is a small base station that install to improve the indoor coverage of a given cellular and to enhance user＇s capacity. Call admission control and resource allocation infemtocell＇s hybrid mode are an essential performance promotion issue. Developing methods for femtocell utilization is very comparative nowadays. The two major limitations of wireless communication are capacity and range. The main contribution of our paper is developing resource allocation scheme that can manage the femocell resources between subscriber （femtocell user） and non-subscriber （macrocell user in order to maximizing the system utilizations, we provide a mechanism that leads to serve more users by admitting more subscribers basing on adjusting QoS of the connected users.     

Normalized Efficient Routing Protocol for WSN

WSNs （wireless sensor networks） consist of thousands of tiny nodes having the capability of sensing, computation, and wireless communications. Unfortunately these devices are limited energy devices, that is means we must save energy as much as possible, to increase network life time as long as possible. In this paper we introduce NEER--normalized energy efficient routing protocol that increases network life time through switching between AODV protocol that depends on request-reply routing, and MRPC that depends on residual battery in routing.