The current study tackles how slavery and racial segregation, which have obviously made an enormous impact in the United States of America for many years, can be defeated through optimism. The study opens with an introduction that clarifies some background about Langston Hughes as a poet who writes against slavery and oppression done to the American Blacks during an era which was known for racial segregation in the United States of America. The poet sheds light , in his poetry, upon the role of African Americans in activating hope and optimism to get freedom which has been reached at the end. The first section of the study analyzes the meaning of slavery and segregation as reflected in some selected poems, showing the oppressive face of

Purpose: To validate a UV-visible spectrophotometric technique for evaluating niclosamide (NIC) concentration in different media across various values of pH. Methods: NIC was investigated using a UV-visible spectrophotometer in acidic buffer solution (ABS) of pH 1.2, deionized water (DW), and phosphate buffer solution (PBS), pH 7.4. The characterization of NIC was done with differential scanning calorimeter (DSC), powder X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The UV analysis was validated for accuracy, precision, linearity, and robustness. Results: The DSC spectra showed a single endothermic peak at 228.43 °C (corresponding to the melting point of NIC), while XRD and FTIR analysis confirmed the identit

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

Information systems and data exchange between government institutions are growing rapidly around the world, and with it, the threats to information within government departments are growing. In recent years, research into the development and construction of secure information systems in government institutions seems to be very effective. Based on information system principles, this study proposes a model for providing and evaluating security for all of the departments of government institutions. The requirements of any information system begin with the organization's surroundings and objectives. Most prior techniques did not take into account the organizational component on which the information system runs, despite the relevance of

The aim of this work is to study the effect of diesel fuel percentage on the combustion processes in compression ignition engine using dual – fuel (diesel and LPG).

 The brake thermal efficiency increased with the increase of diesel fuel rate at low loads, and decreased when load increased. To get sufficient operation in engine fueled with dual fuel, it required sufficient flow rate of diesel fuel, if the engine fueled with insufficient diesel fuel erratic operation with miss fire cycles presented.

Dual-fuel operation at part load showed higher specific fuel consumption than straight diesl operation. At full loads, brake specific fuel consumption of duel fuel engine approaches that for diesel fuel values.

One hundred isolates of Pseudomonas aeruginosa were obtained from patients admitted to Baghdad hospitals, Iraq during the period between May 2018 until July 2018. These isolates were distributed as 15 isolates from blood, 25 isolates from urinary tract infections, 10 isolates from sputum, 12 isolates from wounds, 15 isolates from ear infections, 15 isolates from bronchial wash of patients suffering from respiratory tract infections in addition to 8 isolates from cystic fibrosis patients. The isolates were initially identified by culturing on MacConkey agar, blood agar and P. aeruginosa agar then diagnosed by performing some morphological and biochemical tests. The second diagnosis was done by API 20E system followed by Vitek 2 compact syste

The study aimed to identify the effect of the ethical perception of a sample of managers in public organizations on responsible behavior in light of the rapid changes taking place in the external environment. To achieve this, the researcher followed the descriptive analytical approach by applying a questionnaire of two parts. The first part dealt with the ethical perception according to the scale of Johnson (2015), which consisted of (22) items. The second part dealt with measuring responsible behavior, which consisted of (20) items based on the scale of Development of Ethical Behavior (Narvaez, 2006) for a sample of (125) respondents randomly chosen. The results showed that the estimation degree of managers in public governmental o

Background: Acrylic resin polymer s used in prosthodontic treatment as a denture base material for several decades. Separation and debonding of artificial teeth from denture bases present a laboratory and clinical problem affect patient and dentist. The aim of this study is to evaluate the effect of oxygen plasma and argon plasma treatment of acrylic teeth and thermocycling on bonding strength to hot cured acrylic resin denture base material. Materials and Methods: Sixty denture teeth (right maxillary central incisor) are selected. The denture teeth are waxed onto the beveled surface of rectangular wax block according to Japanese standard for artificial teeth. The control group consisted of 20 denture teeth specimen without any treatment.

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