Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the power and popular tool for data and image processing in computer vision, used for many applications like “image recognition”, “object detection”, “semantic segmentation”, In this research paper, provide survey a background for many techniques designed to 3 Dimensions point cloud semantic segmentation in different domains on many several available free datasets and also making a comparison between these methods.
Normal concrete is weak against tensile strength, has low ductility, and also insignificant resistance to cracking. The addition of diverse types of fibers at specific proportions can enhance the mechanical properties as well as the durability of concrete. Discrete fiber commonly used, has many disadvantages such as balling the fiber, randomly distribution, and limitation of the Vf ratio used. Based on this vision, a new technic was discovered enhancing concrete by textile-fiber to avoid all the problems mentioned above. The main idea of this paper is the investigation of the mechanical properties of SCC, and SCM that cast with 3D AR-glass fabric having two different thicknesses (6, 10 mm), and different layers (1,2 laye
... Show MoreTo evaluate and improve the efficiency of photovoltaic solar modules connected with linear pipes for water supply, a three-dimensional numerical simulation is created and simulated via commercial software (Ansys-Fluent). The optimization utilizes the principles of the 1st and 2nd laws of thermodynamics by employing the Response Surface Method (RSM). Various design parameters, including the coolant inlet velocity, tube diameter, panel dimensions, and solar radiation intensity, are systematically varied to investigate their impacts on energetic and exergitic efficiencies and destroyed exergy. The relationship between the design parameters and the system responses is validated through the development of a predictive model. Both single and mult
... Show MoreRecurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al
... Show MoreAccurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct
Based on the German language department’s theoretical and practical aspects as well as educational programs, the present study discusses the semantic relations in text sentences and their role in the science of translation. Through clarifying the semantic relationship between the text sentence and the methods used to express a news item, a situation or an occurrence and through the statement of the multiple theoretical semantic structures of the text’s construction and interrelation, a translator can easily translate a text into the target language.
It is known that language learners face multiple difficulties in writing and creating an inte
... Show MoreThe main purpose of the research is to study the significance of the event in the explicit source and its significance in the Mimi source and to explain the difference between them in the Holy Quran, especially since most linguists were not interested in what the Mime source indicates in the text, but focused on its form and form, as they defined it as the name Linguists and grammarians did not mention a difference in meaning between the explicit source and the Mimi source, and they interpret the second in the first sense, which led me to choose this topic, to know the significance of each source through Appeal to the maqam and occasion in a challenge D The exact meaning.
هذه الدراسة مكرسة للخصائص الوظيفية والدلالية المعقدة للفئات اللفظية من التوتر والنوع في اللغة الروسية سيتم الكشف في هذه الدراسة عن السمات الدلالية والأسلوبية للفرق بين الأفعال المكتملة وغير المكتملة، قد تكون الاختلافات مرتبطة بخصائص المعاني المعجمية للكلمات، وكذلك معاني اللواحق المكونة للكلمات) السوابق واللواحق). يعكس استخدام هذه الفئة النحوية في أنماط مختلفة بوضوح تفاصيل كل منها، لأن درجة واقعية ال
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