Response surface methodology (RSM) based on central composite design was successfully applied to redesign MRS media for maximizing both biomass and bacteriocin production from Lactobacillus plantarum NH40. First, glucose and yeast extract were chosen as the best carbon and nitrogen sources based on classical optimization results of one factor at time which also revealed the possibility of eliminating peptone and meat extract from the original composition of medium without affecting the growth and bacteriocin production. Statistical experimental design based on a regression model generated using the Design expert 7 software showed that the optimum concentrations of glucose, yeast extract, tween80, NH₄Cr, CH

Prodigiosin is a ‘natural red pigment produced by Serratia marcescens which exhibits immunosuppressive and anticancer properties in addition to antimicrobial activities. This work presents an attempt to maximize the production of prodigiosin by two different strategies: one factor at time (OFAT) and statistical optimization. The result of OFAT revealed that sucrose and peptone were the best carbon and nitrogen sources for pigment production with concentration of prodigiosin of about 135 mg/ L. This value was increased to 331.6mg/ L with an optimized ratio of C/N (60:40) and reached 356.8 with pH 6 and 2% inoculum size at end of classical optimization. Statistical experimental design based on Response surface methodology was co

Background: COVID-19 is an ongoing disease that caused, and still causes, many challenges for humanity. In fact, COVID-19 death cases reached more than 4.5 million by the end of August 2021, although an improvement in the medical treatments and pharmaceutical protocols was obtained, and many vaccines were released. Objective: To, statistically, analyze the data of COVID-19 patients at Alshifaa Healthcare Center (Baghdad, Iraq). Methods: In this work, a statistical analysis was conducted on data included the total number, positive cases, and negative cases of people tested for COVID-19 at the Alshifaa Healthcare Center/Baghdad for the period 1 September – 31 December 2020. The number of people who got the test was 1080, where 424 w

DBNRSK Sayed, Journal of Strategic Research in Social Science (JoSReSS), 2020

Due to the developments taking place in the field of communications, informatics systems and knowledge management in the current century, and the obligations and burdens imposed on the business organization to keep pace with these developments, the traditional methods of administrative decision-making are no longer feasible, as recent trends have emerged in management that focus on the need to rely on quantitative methods such as operations research.. The latter is one of the results of World War II, which appeared for the first time in Britain to manage war operations. The first method used in this field is the linear programming method. The use of operations research has developed greatly in the past years, and the methods of analysis in

Literature on the use of the first-person pronoun in abstracts and conclusion sections of final-year projects is limited. In case of Algerian Master students, it is too scant. The present paper aims at filling this gap through a study concerned with students’ and engagement in their final projects (memoirs). This quantitative study examines the use of “we” and its various types, “our- us-I, my, the researcher” in memoirs chosen at random from the d-space portal of the University of Adrar, southern Algeria. Sixty-five papers, submitted in the fields of Linguistics or didactics between 2015 and 2020 and representing nearly half of the whole memoirs’ depository at the library’s d-space, constituted the corpus of study. The des

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

In all applications and specially in real time applications, image processing and compression plays in modern life a very important part in both storage and transmission over internet for example, but finding orthogonal matrices as a filter or transform in different sizes is very complex and importance to using in different applications like image processing and communications systems, at present, new method to find orthogonal matrices as transform filter then used for Mixed Transforms Generated by using a technique so-called Tensor Product based for Data Processing, these techniques are developed and utilized. Our aims at this paper are to evaluate and analyze this new mixed technique in Image Compression using the Discrete Wavelet Transfo