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

Classifying butterfly species is crucial in biodiversity studies and environmental monitoring. However, manual classification is often a laborious process that requires specialized expertise and is prone to error, especially when species have similar visual characteristics. To address these drawbacks, this paper presents a hybrid approach that combines machine learning with deep learning for feature extraction. To enhance the visibility of important features, preprocessing techniques such as background removal and binarization are applied to butterfly images. Feature extraction was performed using the SqueezeNet convolutional neural network, pretrained on the ImageNet dataset. By discarding the final classification layer, the networ

The international reporting auditor witness rapidly developed over the past years, where profession began give attention to the development of auditor reporting and improve its informational report through the issuance and amendment of some relevant international auditing standards. The reality of the situation refers to the failure to inform the auditor in Iraq in  many areas, including: Clearly defined management responsibility for the preparation of financial and auditor's responsibility to express an opinion on these statements and Amendment of opinion when the financial statements as a whole is free from material misstatement based on the evidence is sufficient and appropriate audit, or not to build the auditor's ability to obt

In the present study, the aim was made to identify the relationship between thyroid autoimmunity (TAI) and female infertility. The study was performed on 30 infertile women and 22 age-matched healthy fertile control age (33 ± 5 years). Overall, serum prolactin (PRL), thyroid stimulating hormone (TSH) assay is the key test for the diagnosis and management of hypo and hyperthyroidism. Anti-TPO Ab and anti-TG Ab were measured. The mean ± SE of serum PRL (31.080 ± 3.06) ng/ml was significantly (P<0.05) higher in infertile group compared with control (16.191±1.36) ng/ml. Serum TSH was significantly (P<0.05) higher in infertile group (5.689 ± 1.12) µIU/ml compared to control group (2.282 ± 0.18) µIU/ml. The prevalence of positive

At a time of increasing human potential in the face of crises and risks through the use of technology on a large scale and steadily in various fields of life, and the vulnerability of business organizations as a result of mistakes. The failure of a sudden these errors or omissions or symptoms. Also, some crises occur outside the control of management, others caused by leakage of important information and sometimes secret may be a strategy or a new plan or new project occurs outside the organization to the opposite of what is planned. Therefore, the crisis management are critical to all organizations, because the active management of the crisis helps to ensure the continued prosperity of the organization. Here comes from the resea

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

This study aims to find out the effectiveness of a cognitive-behavioral counseling program in enhancing self-management in reducing the academic procrastination of tenth-grade male students. The sample consisted of (26) male students divided into an experimental group of (13) students and a control group of (13) students. Two scales of self-management and academic procrastination were used, prepared by the researcher. The counseling program was prepared by the researcher. The results showed the program's effectiveness in enhancing self-management and reducing academic procrastination in the posttest, as it showed the continuation of this enhancement in self-management and the increase in the reduction of procrastination in the follow-up

The subject of social capital is of great importance, as it provides an analytical framework for researchers interested in understanding the impact of the Internet on many dimensions of human and social life. And because social networking sites have infiltrated societies and produced new variables at the level of human and social communication, this study came to examine the relationship between the use of the social networking site Facebook and the accumulation of social capital among a sample of University of Algeria 3 students, by researching the variables of intensity of use and patterns of use as independent variables and their relationship to social capital. The results of the field study revealed a strong relationship between the