The main purpose of the paper is to identify the controllability of an existing production system; yogurt production line in Abu Ghraib Dairy Factory which has several machines of food processing and packing that has been studied. Through the starting of analysis, instability in production has been found in the factory. The analysis is built depending on experimental observation and data collection for different processing time of the machines, and statistical analysis has been conducted to model the production system. Arena Software is applied for simulating and analyzing the current state of the production system, and results are expanded to improve the system production and efficiency. Research method is applied to contribute in knowi

The nonlinear refractive index and the nonlinear absorption coefficient of unmodified and functional poly(methyl methacrylate) PMMA films were studied before and after the addition of the filler by the z-scan technique, using a Q-switched Nd:YAG laser at two wavelengths: 532 nm and 1064 nm, and at three input energies (13, 33 and 53) mJ. Both linear and nonlinear refractive indices and absorption coefficients of polymer films were studied by using UV-VIS spectrophotometer. The results show that the creation of functional PMMA from unmodified PMMA will increase the nonlinear optical properties in the functional PMMA/copper matrix more than in the unmodified PMMA/copper matrix. Hence, the functional PMMA appears promising as a useful third

   A microbubble air flotation technique was used to remove chromium ions from simulated wastewater (e.g. water used for electroplating, textiles, paints and pigments, and tanning leather). Experimental parameters were investigated to analyze the flotation process and determine the removal efficiency. These parameters included the location of the sampling port from the bottom of the column, where the diffuser is located to the top of flotation column (30, 60, and 90 cm), the type of surfactant (anionic, SDS, or cationic, CTAB) and its concentration (5, 10, 15, and 20 mg/L), the pH of the initial solution (3, 5, 7, 9, and 11), the initial contaminant concentration (10, 20, 30, and 40 mg/L), the gas flow rate (0.1, 0.2, 0.3, and 0.5 L/mi

A steganography hides information within other information, such as file, message, picture, or video. A cryptography is the science of converting the information from a readable form to an unreadable form for unauthorized person. The main problem in the stenographic system is embedding in cover-data without providing information that would facilitate its removal. In this research, a method for embedding data into images is suggested which employs least significant bit Steganography (LSB) and ciphering (RSA algorithm) to protect the data. System security will be enhanced by this collaboration between steganography and cryptography.

This research estimates the effect of independent factors like filler  (3%, 6%, 9%, 11% weight fraction), normal load (5N, 10N, 15N), and time sliding (5,7 , 9 minutes) on wear behavior of unsaturated polyester resin reinforced with jute fiber and waste eggshell and, rice husk powder composites by utilizing a statistical approach. The specimens polymeric composite prepared from resin unsaturated polyester filled with (4% weight fraction) jute fiber, and (3%, 6%, 9%, 11% weight fraction) eggshell, and rice husk by utilizing (hand lay-up) molding. Dry sliding wear experiments were carried utilizing a standard (pin on disc test setup) following a well designed empirical schedule that depends on Taguchi’s experimental design L9 (MINIT

    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

            Semi-parametric regression models have been studied in a variety of applications and scientific fields due to their high flexibility in dealing with data that has problems, as they are characterized by the ease of interpretation of the parameter part while retaining the flexibility of the non-parametric part. The response variable or explanatory variables can have outliers, and the OLS approach have the sensitivity to outliers. To address this issue, robust (resistance) methods were used, which are less sensitive in the presence of outlier values in the data. This study aims to estimate the partial regression model using the robust estimation method with the wavel

he assignment model represents a mathematical model that aims at expressing an important problem facing enterprises and companies in the public and private sectors, which are characterized by ensuring their activities, in order to take the appropriate decision to get the best allocation of tasks for machines or jobs or workers on the machines that he owns in order to increase profits or reduce costs and time As this model is called multi-objective assignment because it takes into account the factors of time and cost together and hence we have two goals for the assignment problem, so it is not possible to solve by the usual methods and has been resorted to the use of multiple programming The objectives were to solve the problem of

The inverse kinematics of redundant manipulators has infinite solutions by using conventional methods, so that, this work presents applicability of intelligent tool (artificial neural network ANN) for finding one desired solution from these solutions. The inverse analysis and trajectory planning of a three link redundant planar robot have been studied in this work using a proposed dual neural networks model (DNNM), which shows a predictable time decreasing in the training session. The effect of the number of the training sets on the DNNM output and the number of NN layers have been studied. Several trajectories have been implemented using point to point trajectory planning algorithm with DNNM and the result shows good accuracy of the end