The computer vision branch of the artificial intelligence field is concerned with developing algorithms for analyzing video image content. Extracting edge information, which is the essential process in most pictorial pattern recognition problems. A new method of edge detection technique has been introduces in this research, for detecting boundaries.

           Selection of typical lossy techniques for encoding edge video images are also discussed in this research. The concentration is devoted to discuss the Block-Truncation coding technique and Discrete Cosine Transform (DCT) coding technique. In order to reduce the volume of pictorial data which one may need to store or transmit,

Dust storms are a natural phenomenon occurring in most areas of Iraq. In recent years, the study of this phenomenon has become important because of the danger caused by increasing desertification at the expense of the green cover as well as its impact on human health. In this study  is important to devote the remote sensing of dust storms and its detection.Through this research, the dust storms can be detected in semi-arid areas, which are difficult to distinguish between these storms and desert areas. For the distinction between the dust storm pixels in the image with those that do not contain dust storm can be applied the Normalized Difference Dust Index (NDDI) and Brightness Temperature variation (BTV). MODIS sensors that carried

Background: Mini implant stability is primarily related to local bone density; no studies have evaluated bone density related to mini implant placement for orthodontic anchorage between different age groups in the maxilla and the mandible. The present research aims to evaluate side, gender, age, and regional differences in bone density of the alveolar bone at various orthodontic implant sites. Materials and method: Fifty three individuals who were divided into two groups according to their age into: group I (ages 16-20 years) and group II (ages 21-29 years) had subjected to clinical examination, then 64-multislice computed tomography scan data were evaluated and bone density was measured in Hounsfield unit at 102 points (51 in the maxilla

Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

تعد صناعة السمنت في العراق من اقدم الصناعات الحديثة واكثرها تطورا وتقدما ومن اقواها تاثيرا في الاقتصاد القومي. واذ توفر في صناعة السمنت العراقي كافة المستلزمات الناجحة من حيث توفر المواد الاولية والخبرات الفنية والتقنية واسواق ثابتة وراسخة محليا وعالميا فقد كان من المفروض ان يتم التوسع في هذه الصناعة، وان التخطيط لهذه الصناعة امرا ضروريا خاصة وان مادة السمنت هي احدى اهم المواد الرئيسة التي يؤثر توفره

Abstract

The use of modern scientific methods and techniques, is considered important topics to solve many of the problems which face some sector, including industrial, service and health. The researcher always intends to use modern methods characterized by accuracy, clarity and speed to reach the optimal solution and be easy at the same time in terms of understanding and application.

the research presented this comparison between the two methods of solution for linear fractional programming models which are linear transformation for Charnas & Cooper , and denominator function restriction method through applied on the oil heaters and gas cookers plant , where the show after reac

Beyond the immediate content of speech, the voice can provide rich information about a speaker's demographics, including age and gender. Estimating a speaker's age and gender offers a wide range of applications, spanning from voice forensic analysis to personalized advertising, healthcare monitoring, and human-computer interaction. However, pinpointing precise age remains intricate due to age ambiguity. Specifically, utterances from individuals at adjacent ages are frequently indistinguishable. Addressing this, we propose a novel, end-to-end approach that deploys Mozilla's Common Voice dataset to transform raw audio into high-quality feature representations using Wav2Vec2.0 embeddings. These are then channeled into our self-attentio