The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimum err

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

Background: osteoporosis is characterized by a reduction in bone mineral density, skeletal microstructure breakdown, increased bone fragility, and fracture susceptibility. Osteopenia is the preceding step to osteoporosis because it causes a decrease in bone mass, osteoporosis reduces a person's quality of life. Periostin (encoded by Postn), its name is derived from the fact that it was first detected in periosteal osteocytes and osteoblasts. Periostin deficiency has been linked to osteoporosis and weak bones. Study objectives: The purpose of this study was to determine periostin levels in serum of Iraqi patients with osteoporosis and osteopenia, and it is also possible to consider periostin as a diagnostic factor to follow the progression o

Hepatitis, a condition of liver’s inflammation that can be self-limiting or, in certain chances, it may lead to liver cancer, fibrosis or cirrhosis. Hepatitis viruses mainly cause hepatitis in the world. People with hepatitis C have predominant chances to develop diabetes as HCV virus participates in causing type 2 diabetes. HCV virus causes pathogenesis in two ways: it either directly destroys the β cells of pancreas or contributes to the specific autoimmunity of β cells. The present cross sectional study was done in Wazirabad Tahsil of Gujranwala District to analyze the percentage of patients suffering from hepatitis C who had the risk of diabetes mellitus. For this research work, demographic information and data about any other me

ABSTRACT:

Objectives: The study aims to know the effectiveness of the educational program in the patient’s adherence to medication and diet and to know the relationship between the effectiveness of the education program and their demographic data related to the patient’s age, gender, marital status, education level, occupation, monthly income and residence.

Methodology: A quasi -experimental design study was performed on patient who attended to Gastroenterology and Hepatology Teaching Hospital, from March 2021 to September 2021. The non-probability sampling including 50 patients for case study and 30 patients for control group. The questionnaire consists of 3 parts, part one the socio

In recent years, with the growing size and the importance of computer networks, it is very necessary to provide adequate protection for users data from snooping through the use of one of the protection techniques: encryption, firewall and intrusion detection systems etc. Intrusion detection systems is considered one of the most important components in the computer networks that deal with Network security problems. In this research, we suggested the intrusion detection and classification system through merging Fuzzy logic and Artificial Bee Colony Algorithm. Fuzzy logic has been used to build a classifier which has the ability to distinguish between the behavior of the normal user and behavior of the intruder. The artificial bee colony al

Background: Legionella pneumophila (L. pneumophila) is gram-negative bacterium, which causes Legionnaires’ disease as well as Pontiac fever. Objective: To determine the frequency of Legionella pneumophila in pneumonic patients, to determine the clinical utility of diagnosing Legionella pneumonia by urinary antigen testing (LPUAT) in terms of sensitivity and specificity, to compares the results obtained from patients by urinary antigen test with q Real Time PCR (RT PCR) using serum samples and to determine the frequency of serogroup 1 and other serogroups of L. pneumophila. Methods: A total of 100 pneumonic patients (community acquired pneumonia) were enrolled in this study during a period between October 2016 to April 2017; 92 sam

  Cardiovascular diseases CVD are responsible for the majority of death in many countries, the term cardiovascular disease CVD includes several diseases such as: coronary artery diseases (angina, myocardial infaraction MI, atherosclerosis) and stroke. These diseases cause elevation of TC, TG, LDL, VLDL, and MDA levels in plasma and decrease of HDL levels and PON activity in plasma, because of elevation in lipid peroxidation (LPO) activity.  Catechins is a water extract of green tea composed of: (-)epicatchin EC, ECG, EGC, EGCG, (+) catechin C and GC, these compounds play great roles against chronic diseases such as CVD. The effect of catechins extract on the preceding biochemical parameters was investigated in 40 volunteer male