Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

Hand gestures are currently considered one of the most accurate ways to communicate in many applications, such as sign language, controlling robots, the virtual world, smart homes, and the field of video games. Several techniques are used to detect and classify hand gestures, for instance using gloves that contain several sensors or depending on computer vision. In this work, computer vision is utilized instead of using gloves to control the robot's movement. That is because gloves need complicated electrical connections that limit user mobility, sensors may be costly to replace, and gloves can spread skin illnesses between users. Based on computer vision, the MediaPipe (MP) method is used. This method is a modern method that is discover

Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

      The present study deals with the strategies used in the Arabic translations of the most popular genres of children’s literature; namely fairy tales and fables as an attempt to identify the best methods and strategies to be adopted in translating these genres to fulfill the ultimate purpose of enriching the children’s knowledge in addition to attracting their interest and arousing the joy sought for in every piece of literature.

The study sets off from three dominating trends: the first calls for the adoption of domestication strategy of translation as the most appropriate and effective strategy in translation for children. In the same line, the second opposes using the foreignization strategy, w

plaque forming assay was used enumerate the number of plaque forming cells of anti-HBc in eight patintes with chronic hepatitis and eight health

AA Noaimi, IRAQI JOURNAL OF COMMUNITY MEDICINE, 2013 - Cited by 1

Introduction: Rheumatoid arthritis (RA) is one of the most prevalent systemic inflammatory diseases worldwide. Cardiac complications present the most common mortality cause among RA patients. One of the most important comorbid conditions with RA is diabetic hyperglycemia mainly type 2 diabetes mellitus (T2DM). Aim of the study: The present study was conducted to assess prevalence of T2DM among patients diagnosed with RA from Iraq. Methodology: We included a randomly selected 100 rheumatoid arthritis. All included patients were subjected to anthropometric measurements, diabetic profile assessment and ESR, CRP and rheumatoid factor measurement. Results: Among the included RA patients, 28 patients were diagnosed with new-onset DM. Our

Background: Because of many factors play a role in the developing of late lower arch crowding, therefore the objective of the current study is to do vertical analysis for subjects with late lower dental arch crowding. The conducted study is the first attempt to do vertical analysis for Iraqi subjects with late lower arch crowding to see if there is a vertical discrepancy in such patients. Subjects and methods: Eighty subjects were selected according to certain inclusion criteria from patients attending the Orthodontic Department in the College of Dentistry, Baghdad University, patients ranged between 18-25 years old. The 80 patients were divided into two groups (crowding and normal), 40 patients each (20 males and 20 females). A study cast