This paper is an attempt to help the manager of a manufactory to

plan for the next year by a scientific approach, to maximize the profit and Ø¢ provide optimal Ø¢ monthly quantities of Ø¢ production, Ø¢ inventory,

work-force, prices and sales. The computer programming helps us to execute that huge number of calculations.

Variable selection in Poisson regression with high dimensional data has been widely used in recent years. we proposed in this paper using a penalty function that depends on a function named a penalty. An Atan estimator was compared with Lasso and adaptive lasso. A simulation and application show that an Atan estimator has the advantage in the estimation of coefficient and variables selection.

     This paper investigated an Iraqi dataset from Korek Telecom Company as Call Detail Recorded (CDRs) for six months falling between Sep. 2020-Feb. 2021. This data covers 18 governorates, and it falls within the period of COVID-19. The Gravity algorithm was applied into two levels of abstraction in deriving the results as the macroscopic and mesoscopic levels respectively. The goal of this study was to reveal the strength and weakness of people migration in-between the Iraqi cities. Thus, it has been clear that the relationship between each city with the others is based on   and  of mobile people. However, the COVID-19 effects on the people’s migration needed to be explored. Whereas the main function of the gravity model is to

People’s ability to quickly convey their thoughts, or opinions, on various services or items has improved as Web 2.0 has evolved. This is to look at the public perceptions expressed in the reviews. Aspect-based sentiment analysis (ABSA) deemed to receive a set of texts (e.g., product reviews or online reviews) and identify the opinion-target (aspect) within each review. Contemporary aspect-based sentiment analysis systems, like the aspect categorization, rely predominantly on lexicon-based, or manually labelled seeds that is being incorporated into the topic models. And using either handcrafted rules or pre-labelled clues for performing implicit aspect detection. These constraints are restricted to a particular domain or language which is

Voice denoising is the process of removing undesirable voices from the voice signal. Within the environmental noise and after the application of speech recognition system, the discriminative model finds it difficult to recognize the waveform of the voice signal. This is due to the fact that the environmental noise needs to use a suitable filter that does not affect the shaped waveform of the input microphone. This paper plans to build up a procedure for a discriminative model, using infinite impulse response filter (Butterworth filter) and local polynomial approximation (Savitzky-Golay) smoothing filter that is a polynomial regression on the signal values. Signal to noise ratio (SNR) was calculated after filtering to compare the results

In this paper an attempt to provide a single degree of freedom lumped model for fluid structure interaction (FSI) dynamical analysis will be presented. The model can be used to clarify some important concept in the FSI dynamics such as the added mass, added stiffness, added damping, wave coupling ,influence mass coefficient and critical fluid depth . The numerical results of the model show that the natural frequency decrease with the increasing of many parameters related to the structure and the fluid .It is found that the interaction phenomena can become weak or strong depending on the depth of the containing fluid .The damped and un damped free response are plotted in time domain and phase plane for different model parameters It is fou

The aim of this paper is to construct the analysis mathematical model for stream cipher cryptosystems in order to be cryptanalysis using the cryptanalysis tools based on plaintext attack (or part from it) or ciphertext only attack, choosing Brüer generator as study case of nonlinear stream cipher system.
The constructing process includes constructing the linear (or non-linear) equations system of the attacked nonlinear generator. The attacking of stream cipher cryptosystem means solving the equations system and that means finding the initial key values for each combined LFSR. 

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet