This report explores emerging techniques to boost multimedia transfer effectiveness, given the escalating need for improved quality and performance in multimedia interactions. The analysis involves a thorough literature assessment and comparison of present strategies to pinpoint key tendencies and propose novel approaches. The methodology involves examining recent technological enhance ments in video coding standards, quality appraisal methods, and compression tech niques. Specific domains investigated comprise firmware component architectures, 4D indexing structures, and iterative filtering frameworks. The study in addition weighs tradeoffs between video quality, encoding intricacy, and bitrate demands. Key determinations consist of

This study focuses on the impact of technology on creating a dystopian world as presented by the English playwright Caryl Churchill in her play A Number (2002). This dramatic work came as a reaction to the most crucial and valuable turning point in the scientific achievements of human engineering, namely, the cloning of the sheep called Dolly. Therefore, A Number is a play that presents an analytical stage for imagining the biotechnological and scientific future. This dramatic vignette captures the playwright’s fears towards the abnormal progress of technology and science and how far such technological progress affects human relationships and identity. It also portrays how technological progress results in the feeling of a lack of

Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that usin

The availability of different processing levels for satellite images makes it important to measure their suitability for classification tasks. This study investigates the impact of the Landsat data processing level on the accuracy of land cover classification using a support vector machine (SVM) classifier. The classification accuracy values of Landsat 8 (LS8) and Landsat 9 (LS9) data at different processing levels vary notably. For LS9, Collection 2 Level 2 (C2L2) achieved the highest accuracy of (86.55%) with the polynomial kernel of the SVM classifier, surpassing the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) at (85.31%) and Collection 2 Level 1 (C2L1) at (84.93%). The LS8 data exhibits similar behavior. Conv

Context has a significant impact on the interpretation of Qur'anic and literary texts, especially in ancient Arabic poetry since that language is no longer considered as a contemporary understandable language. Hence this research is entitled: (the impact of context on the morphological semantics in the Diwan of Abi Al-Aswad Al-Dau’ali) and the morphological meanings indicated by the morphological formula which lack the combination of other contextual clues. The researcher depended on the analytical approach to show the impact of pairing occurring between the contextual elements on determining the morphological meaning.
The most important findings reached at:
1- Context has a great impact in dispelling the possibilities arising fr

his project try to explain the using ability of spatial techniques for land cover change detection on regional level with the time parameter and did select for explain these abilities study case (Hewaizah marsh ) . this area apply to many big changes with the time. These changes made action on characters and behaviors of this area as well as all activities in it . This Project concerting to recognize the Using importance of remote sensing and GIS Methodology in data collecting for the changes of land use and the methodology for the analyses and getting the results for the next using as a base data for development and drawing the plans as well as in regional planning .This project focus on practical

This paper deals with a central issue in the field of human communication and reveals the roaming monitoring of the incitement and hatred speech and violence in media, its language and its methods. In this paper, the researcher seeks to provide a scientific framework for the nature of the discourse of incitement, hatred speech, violence, and the role that media can play in solving conflicts with their different dimensions and in building community peace and preventing the emergence of conflicts among different parties and in different environments. In this paper, the following themes are discussed:
The root of the discourse of hatred and incitement
The nature and dimensions of the discourse of incitement and hatred speech
The n

The study was conducted at research station A, department of field crops, college of agricultural engineering sciences, university of Baghdad during summer 2021 to evaluate the effect of boron and some growth regulators on some growth criteria and yield of soybean crop (cv. shimaa). The experiment  was carried out according to split plots by using randomized complete block design with three replications. The main plots included three concentrations of boron (75, 150 and 225) mg.L^-1, the sub-plots included three levels of growth regulators, spraying kinetin (100 mg. L^-1), spraying ethrel (200 mg.L^-1) and spraying kinetin (100 mg.L^-1) + spraying ethrel (200 mg.L^-1) as

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s