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.
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%.
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. 相似文献
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. 相似文献
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. 相似文献
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. 相似文献
We propose a new formulation of quantum algorithm which allows to distribute amplitudes over two copies of small quantum subsystems. The new method gives a fixed number of copies and applied to the control of multi-qubit system. The analysis for the amount of error due to the distribution process has been presented for a system of 10 qubits with a small quantum subsystems to be copied. The present scheme provides a new way to distribute amplitudes over small quantum subsystems. 相似文献
Scenarios are possible future states of the world that represent alternative plausible conditions under different assumptions. Often, scenarios are developed in a context relevant to stakeholders involved in their applications since the evaluation of scenario outcomes and implications can enhance decision-making activities. This paper reviews the state-of-the-art of scenario development and proposes a formal approach to scenario development in environmental decision-making. The discussion of current issues in scenario studies includes advantages and obstacles in utilizing a formal scenario development framework, and the different forms of uncertainty inherent in scenario development, as well as how they should be treated. An appendix for common scenario terminology has been attached for clarity. Major recommendations for future research in this area include proper consideration of uncertainty in scenario studies in particular in relation to stakeholder relevant information, construction of scenarios that are more diverse in nature, and sharing of information and resources among the scenario development research community. 相似文献