Nowadays, the use of natural bio-products in pharmaceuticals is gaining popularity as safe alternatives to chemicals and synthetic drugs. Algal products are offering a pure, healthy and sustainable choice for pharmaceutical applications. Algae are photosynthetic microorganisms that can survive in different environmental conditions. Algae have many outstanding properties that make them excellent candidate for use in therapeutics. Algae grow in fresh and marine waters and produce in their cells a wide range of biologically active chemical compounds. These bioactive compounds are offering a great source of highly economic bio-products. The prese

Deep Learning Techniques For Skull Stripping of Brain MR Images

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of

 This study investigated three aims for the extent of effectiveness of the two systems in educational development of educators. To achieve this, statistical analysis was performed between the two groups that consisted of (26) participants of the electronic teaching method and (38) participants who underwent teaching by the conventional electronic lecture. The results indicated the effectiveness of the “electronic teaching method” and the “electronic lecture method” for learning of the participants in educational development. Also, it indicated the level of equivalence from the aspect of effectiveness of the two methods and at a confidence level of (0.05). This study reached several conclusions, recommendations, and suggestio

Hierarchical temporal memory (HTM) is a biomimetic sequence memory algorithm that holds promise for invariant representations of spatial and spatio-temporal inputs. This article presents a comprehensive neuromemristive crossbar architecture for the spatial pooler (SP) and the sparse distributed representation classifier, which are fundamental to the algorithm. There are several unique features in the proposed architecture that tightly link with the HTM algorithm. A memristor that is suitable for emulating the HTM synapses is identified and a new Z-window function is proposed. The architecture exploits the concept of synthetic synapses to enable potential synapses in the HTM. The crossbar for the SP avoids dark spots caused by unutil

    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

The research aims to identify how to enhance the quality of the human resources, focusing on four dimensions (efficiency, effectiveness, flexibility, and reliability), by adopting an adventure learning method that combines theoretical and applied aspects at the same time, when developing human resources and is applied using information technology, and that Through its dimensions, which are (cooperation, interaction, communication, and understanding), as the research problem indicated a clear deficiency in the cognitive perception of the mechanism of employing adventure learning dimensions in enhancing human resources quality, so the importance of research was to present treatments and proposals to reduce this problem. To achieve

The aims of the research is to know the role of Organisational learning in building talent management strategies in the Ministry of Science and Technology , where we see the challenges facing organizations today dictate now and in the future activation of scientific expertise to meet these challenges and the dissemination of these concepts within the priorities and data organizational culture of these organizations despite having a lot of the importance of organizational knowledge and learning applications .Despite learning and adopting some of the organizations have to enhance their competitiveness, we find a lot of organizations, including (The ministry researched) still do not realize the importance of the role of organization