The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.

Regression testing being expensive, requires optimization notion. Typically, the optimization of test cases results in selecting a reduced set or subset of test cases or prioritizing the test cases to detect potential faults at an earlier phase. Many former studies revealed the heuristic-dependent mechanism to attain optimality while reducing or prioritizing test cases. Nevertheless, those studies were deprived of systematic procedures to manage tied test cases issue. Moreover, evolutionary algorithms such as the genetic process often help in depleting test cases, together with a concurrent decrease in computational runtime. However, when examining the fault detection capacity along with other parameters, is required, the method falls sh

Solid waste is a major issue in today's world. Which can be a contributing factor to pollution and the spread of vector-borne diseases. Because of its complicated nonlinear processes, this problem is difficult to model and optimize using traditional methods. In this study, a mathematical model was developed to optimize the cost of solid waste recycling and management. In the optimization phase, the salp swarm algorithm (SSA) is utilized to determine the level of discarded solid waste and reclaimed solid waste. An optimization technique SSA is a new method of finding the ideal solution for a mathematical relationship based on leaders and followers. It takes a lot of random solutions, as well as their outward or inward fluctuations, t

Most of the Internet of Things (IoT), cell phones, and Radio Frequency Identification (RFID) applications need high speed in the execution and processing of data. this is done by reducing, system energy consumption, latency, throughput, and processing time. Thus, it will affect against security of such devices and may be attacked by malicious programs. Lightweight cryptographic algorithms are one of the most ideal methods Securing these IoT applications. Cryptography obfuscates and removes the ability to capture all key information patterns ensures that all data transfers occur Safe, accurate, verified, legal and undeniable.  Fortunately, various lightweight encryption algorithms could be used to increase defense against various at

Many image processing and machine learning applications require sufficient image feature selection and representation. This can be achieved by imitating human ability to process visual information. One such ability is that human eyes are much more sensitive to changes in the intensity (luminance) than the color information. In this paper, we present how to exploit luminance information, organized in a pyramid structure, to transfer properties between two images. Two applications are presented to demonstrate the results of using luminance channel in the similarity metric of two images. These are image generation; where a target image is to be generated from a source one, and image colorization; where color information is to be browsed from o

In this paper, several combination algorithms between Partial Update LMS (PU LMS) methods and previously proposed algorithm (New Variable Length LMS (NVLLMS)) have been developed. Then, the new sets of proposed algorithms were applied to an Acoustic Echo Cancellation system (AEC) in order to decrease the filter coefficients, decrease the convergence time, and enhance its performance in terms of Mean Square Error (MSE) and Echo Return Loss Enhancement (ERLE). These proposed algorithms will use the Echo Return Loss Enhancement (ERLE) to control the operation of filter's coefficient length variation. In addition, the time-varying step size is used.The total number of coefficients required was reduced by about 18% , 10% , 6%