In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

This research will cover different aspects of estimating process of construction work in a desert area. The inherent difficulties which accompany the cost estimating of the construction works in desert environment in a developing country, will stem from the limited information available, resources scarcity, low level of skilled workers, the prevailing severe weather conditions and many others, which definitely don't provide a fair, reliable and accurate estimation. This study tries to present unit price to estimate the cost in preliminary phase of a project.  Estimations are supported by developing mathematical equations based on the historical data of maintenance, new construction of managerial and school projects.

A New Perspective About Masculinity and the Issue of Identity in Ernest Hemingway's The Old Man and The Sea and Michael Ondaatje's in The Skin of a lion

In this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected  from the Ministry of Planning on the water turbidity of five areas in Baghdad to know which of these areas are less turbid in clear water to see which months during the year are less turbid in clear water in the specified area.

Stereolithography (SLA) has become an essential photocuring 3D printing process for producing parts of complex shapes from photosensitive resin exposed to UV light. The selection of the best printing parameters for good accuracy and surface quality can be further complicated by the geometric complexity of the models. This work introduces multiobjective optimization of SLA printing of 3D dental bridges based on simple CAD objects. The effect of the best combination of a low-cost resin 3D printer’s machine parameter settings, namely normal exposure time, bottom exposure time and bottom layers for less dimensional deviation and surface roughness, was studied. A multiobjective optimization method was utilized, combining the Taguchi me

This paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

مثل اللغة العربية، إلى جانب اللغات الشقيقة لها، لهجات الخضوع العربي، والتي لا يمكن عزلها أو إنكارها. لهذه الوحدة خصائصها ومميزاتها الخاصة. هذه الخصائص والصفات جعلتنا ننظر إلى موضوع يقع بين اللغة العربية واللهجات العربية القريبة. تستخدم اللغة العربية واللغات الشقيقة لها للدعوة، من أجل توطيد النداء، معرفة محاضر وغرض استخدام أداة دون غيرها من الأدوات. استند هذا البحث إلى مقدمة وموضوعين مسبوقين بمقدمة ومتبوع

This paper is concerned with the blow-up solutions of a system of two reaction-diffusion equations coupled in both equations and boundary conditions. In order to understand how the reaction terms and the boundary terms affect the blow-up properties, the lower and upper blow-up rate estimates are derived. Moreover, the blow-up set under some restricted assumptions is studied.

This study examined the problem of identifying the vocabulary of the methodology of teaching Arabic language in the faculties of Media. The researcher noticed the existence of an overlap between the syllabuses of the general specialization of the Arabic language and its Media sections in the universities with the special professional vocabulary that suits the study of the media student. Thus ,this study is regarded as a real attempt to present a methodological model of media language that concerns with fillfuling students ‘linguistic and knowledgeable needs relying on measuring their benefits from the methodological Arabic curriculum .  Key words:problem,  teaching’ methodology of Arabic language, media language.