Objectives: To determine the (QoL) for patients with permanent pacemaker and to find-out the relationship between
these patients’ (QoL) and their sociodemographic characteristics such as age, gender, level of education, and
occupation.
Methodology: ٨ purposive non-probability” sample of (62) patient with permanent pacemaker was involved in this
study. The developed questionnaire consists of (4) parts which include !.demographic data form, 2.disease-related
information form, 3.socioeconomic data form, and 4.Permanent pacemaker patient’s quality of life questionnaire data
form. The validity and reliability of the questionnaire were determined through the application of a pilot study. ٨
descriptive statistical a

Objective(s): to assess the factors which are associated with the prolonged prehospital delay of patients with
acute myocardial infarction.
Methodology: A descriptive study was conducted at the Coronary Care unit (CCU) in Al-Yarmok Teaching
Hospital, Ibn AL-Nafis Hospital for Cardiovascular Diseases, AL-Kadumia Teaching Hospital, Baghdad Teaching
Hospital, and AL-Kindy Teaching Hospital during the period of the study from February 2
nd
, 2009 to October 30th
,
2009. A random sample of (160) paƟent who were admiƩed to the hospitals were selected one by one. A
questionnaire was constructed for the purpose of the study, which is comprised of four parts that include (1)
sociodemographic data; (2) prehospital d

The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

Asset management involves efficient planning of economic and technical performance characteristics of infrastructure systems. Managing a sewer network requires various types of activities so the network can be able to achieve a certain level of performance. During the lifetime of the network various components will start to deteriorate leading to bad performance and can damage the infrastructure. The main objective of this research is to develop deterioration models to provide an assessment tool for determining the serviceability of the sewer networks in Baghdad city the Zeppelin line was selected as a case study, as well as to give top management authorities the appropriate decision making. Different modeling techniques

Melanoma, a highly malignant form of skin cancer, affects individuals of all genders and is associated with high mortality rates, especially in advanced stages. The use of tele-dermatology has emerged as a proficient diagnostic approach for skin lesions and is particularly beneficial in rural areas with limited access to dermatologists. However, accurately, and efficiently segmenting melanoma remains a challenging task due to the significant diversity observed in the morphology, pigmentation, and dimensions of cutaneous nevi. To address this challenge, we propose a novel approach called DenseUNet-169 with a dilated convolution encoder-decoder for automatic segmentation of RGB dermascopic images. By incorporating dilated convolution,

Software-Defined Networking (SDN) has evolved network management by detaching the control plane from the data forwarding plane, resulting in unparalleled flexibility and efficiency in network administration. However, the heterogeneity of traffic in SDN presents issues in achieving Quality of Service (QoS) demands and efficiently managing network resources. SDN traffic flows are often divided into elephant flows (EFs) and mice flows (MFs). EFs, which are distinguished by their huge packet sizes and long durations, account for a small amount of total traffic but require disproportionate network resources, thus causing congestion and delays for smaller MFs. MFs, on the other hand, have a short lifetime and are latency-sensitive, but they accou