This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat

The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat

في بداية الستينيات ظهرت شبكة الإنترنت لاستعمالها في أغراض غير تجارية ، ثم تطورت بشكل مذهل خلال السنوات الأخيرة، فبعد أن كانت مجرد شبكة صغيرة أصبحت الآن تضم ملايين المستخدمين حول العالم ، وتحولت من مجرد شبكة بحث أكاديمي إلى بيئة متكاملة للاستثمار والعمل والإنتاج والإعلام والحصول على المعلومات .

 وفي بداية تأسيس الشبكة لم يكن ثمة اهتمام بمسائل الأمن بقدر ما كان الاهتمام ببنائها وتوسيع نش

Loud noise can be extremely harmful to the auditory system as well as to human health. Noise pollution is primarily caused by traffic noise. The study's goal was to determine how various vehicle types and speeds affected the amount of noise generated by traffic. The two factors were investigated at seven different arterial streets throughout Kirkuk city to measure the noise levels. The measurements were performed during peak hours to compare the result with WHO standards for noise specification. Traffic volume and vehicle speed are shown to be the key elements that determine an increase in noise level. 

      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: This is the first nationwide assessment of WHO-designated bacterial resistance in Iraq. Aim: To analyse antimicrobial resistance patterns over 4 years in Iraq, based on data from the national surveillance system. Methods: Using the WHO Antimicrobial Resistance Network software, we collected and analysed 238 973 antimicrobial resistance data from the 106 antimicrobial resistance surveillance sites across Iraq, for 2020–2023, from the Iraqi national surveillance system. The data were analysed using SPSS version 26. Results: Resistance to carbapenem by Acinetobacter baumannii increased markedly, reaching 80% in 2023. Resistance to third-generation cephalosporins was notably high among Acinetobacter baumannii (88.5–92%),