The aim of this research is to investigation the optimization of the machining parameters (spindle speed, feed rate, depth of cut, diameter of cutter and number of flutes of cutter) of surface roughness for free-form surface of composite material (Aluminum 6061 reinforced boron carbide) by using HSS uncoated flat end mill cutters which are rare use of the free-form surface. Side milling (profile) is the method used in this study by CNC vertical milling machine. The purpose of using ANFIS to obtain the better prediction of surface roughness values and decreased of the error prediction value and get optimum machining parameters by using Taguchi method for the best surface roughness at spindle speed 4500 r.p.m, 920mm/rev feed rate, 0.6mm de

The main objectives of this study were investigating the effects of the maximum size of coarse Attapulgite aggregate and micro steel fiber content on fresh and some mechanical properties of steel fibers reinforced lightweight self-compacting concrete (SFLWSCC). Two series of mixes were used depending on maximum aggregate size (12.5 and 19) mm, for each series three different steel fibers content were used (0.5 %, 1%, and 1.5%). To evaluate the fresh properties, tests of slump flow, T500 mm, V funnel time, and J ring were carried out. Tests of compressive strength, splitting tensile strength, flexural tensile strength, and calculated equilibrium density were done to evaluate mechanical properties. For reference mixes, the

MJ Abbas, AK Hussein, Journal of Physical Education, 2019

  The research dealt with the design of the cost accounting system for the transport service and its Role in improving the efficiency of pricing decisions through the application of the cost system based on ABC activities. The main activities were defined and cost guides were to measure the cost of each service and to determine the cost of each service for the purpose of providing management with appropriate information and pricing decisions The problem of research in the lack of adoption by some public companies in the service sector on the cost accounting system to calculate the cost of service as well as the lack of identification of productive activities and service activities and therefore cannot make the appropriate decision t

Krawtchouk polynomials (KPs) and their moments are promising techniques for applications of information theory, coding theory, and signal processing. This is due to the special capabilities of KPs in feature extraction and classification processes. The main challenge in existing KPs recurrence algorithms is that of numerical errors, which occur during the computation of the coefficients in large polynomial sizes, particularly when the KP parameter (p) values deviate away from 0.5 to 0 and 1. To this end, this paper proposes a new recurrence relation in order to compute the coefficients of KPs in high orders. In particular, this paper discusses the development of a new algorithm and presents a new mathematical model for computing the

In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.

An Optimal Algorithm for HTML Page Building Process

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

This paper proposes a novel meta-heuristic optimization algorithm called the fine-tuning meta-heuristic algorithm (FTMA) for solving global optimization problems. In this algorithm, the solutions are fine-tuned using the fundamental steps in meta-heuristic optimization, namely, exploration, exploitation, and randomization, in such a way that if one step improves the solution, then it is unnecessary to execute the remaining steps. The performance of the proposed FTMA has been compared with that of five other optimization algorithms over ten benchmark test functions. Nine of them are well-known and already exist in the literature, while the tenth one is proposed by the authors and introduced in this article. One test trial was shown t