It is an analytical study carried out at university of Basra  using a sample included the dean ,assistants and managers of scientific dept. in the university for about(63)managers .The study aimed at discovering  a model of  crises management in the university.The researcher adopted the descriptive survey methodology.To achieve the objective of the study ,a questionnaire of (41)statements was developed covering five main  variables like ,signal detection, prevention and preparedness, response, recovery and learning .The validity of the questionnaire was done by a group of referees .Its stability was determined by Cronbach^,s  Alfa  .The questionnair^,s stability coefficient was(0.

Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

A solar cell was manufactured from local materials and was dyed using dyes extracted from different organic plants. The solar cell glass slides were coated with a nano-porous layer of Titanium Oxide and infused with two types of acids, Nitric acid and Acetic acid. The organic dyes were extracted from Pomegranate, Hibiscus, Blackberry and Blue Flowers. They were then tested and a comparison was made for the amount of voltage they generate when exposed to sunlight. Hibiscus sabdariffa extract had the best performance parameters; also Different plants give different levels of voltage.

    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

The global food supply heavily depends on utilizing fertilizers to meet production goals. The adverse impacts of traditional fertilization practices on the environment have necessitated the exploration of new alternatives in the form of smart fertilizer technologies (SFTs). This review seeks to categorize SFTs, which are slow and controlled-release Fertilizers (SCRFs), nano fertilizers, and biological fertilizers, and describes their operational principles. It examines the environmental implications of conventional fertilizers and outlines the attributes of SFTs that effectively address these concerns. The findings demonstrate a pronounced environmental advantage of SFTs, including enhanced crop yields, minimized nutrient loss, improved nut

Scheduling Timetables for courses in the big departments in the universities is a very hard problem and is often be solved by many previous works although results are partially optimal. This work implements the principle of an evolutionary algorithm by using genetic theories to solve the timetabling problem to get a random and full optimal timetable with the ability to generate a multi-solution timetable for each stage in the collage. The major idea is to generate course timetables automatically while discovering the area of constraints to get an optimal and flexible schedule with no redundancy through the change of a viable course timetable. The main contribution in this work is indicated by increasing the flexibility of generating opti

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

Herein, an efficient inorganic/organic hybrid photocatalyst composed of zeolitic imidazolate framework (ZIF-67) decorated with Cd0.5Zn0.5S solid solution semiconductor was constructed. The properties of prepared ZIF- [email protected] nanocomposite and its components (ZIF-67 and Cd0.5Zn0.5S) were investigated using XRD, FESEM, EDX, TEM, DRS and BET methods. The photocatalytic activity of fabricated [email protected] nanocomposite were measured toward removal of methyl violet (MV) dye as a simulated organic contaminant. Under visible-light and specific conditions (photocatalyst dose 1 g/l, MV dye 10 mg/l, unmodified solution pH 6.7 and reaction time 60 min.), the acquired [email protected] photocatalyst showed advanced photocatalytic activity

Background: The aim of this in vitro study was to evaluate and compare the microleakage between Vertise Flow T M composite material and other conventional (Filtek Z250, riva light cure and SDR) composite materials when restoring CII mesial box only cavity at gingival margin through die penetration test Materials and methods: Forty maxillary first premolars were prepared with class II box design only cavities. Samples were divided into four groups of ten teeth according to material used: group I (FiltekZ250 only). Group II (SDR+FiltekZ250). Group III (Vertise Flow +FiltekZ250). Group IV (Riva light cure+ FiltekZ250). After 24 hrs. immersion in 2% in methylene blue, samples were sectioned and micro leakage was estimated. Results: None of the