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Foreground detection is a task for detecting the moving objects in the scene like in video surveillance. Several basic background models are often used due to their high efficiency.
In this study, a new edge detection method based on Neutrosophic Set (NS) struc- ture via using maximum norm entropy (EDA-MNE) is proposed.
It is really important to diagnose jaw tumor in its early stages to improve its prognosis. A differential diagnosis could be performed using X-ray images; therefore, accurate and fully automatic jaw lesions image segmentation is a challenging and essential task. The aim of this work was to develop a novel, fully automatic and effective method for jaw lesions in panoramic X-ray image segmentation.
This is the second volume of the Encyclopedia of Neutrosophic Researchers, edited from materials offered by the authors who responded to my invitation. The introduction contains a short history of neutrosophics, together with links to the main papers and books.
Malignant melanoma is among the fastest increasing malignancies in many countries. Due to its propensity to metastasize and lack of effective therapies for most patients with advanced disease, early detection of melanoma is a clinical imperative. In non-Caucasian populations, melanomas are frequently located in acral volar areas and their dermoscopic appearance differs from the non-acral ones. Although lesion segmentation is a natural preliminary step towards its further analysis, so far virtually no acral skin lesion segmentation method has been proposed. Our goal was to develop an effective segmentation algorithm dedicated for acral lesions.
In this paper, the TODIM method is used to solve the multi-attribute decision-making problem with unknown attribute weight in venture capital, and the decision information is given in the form of single-valued neutrosophic numbers. In order to consider the objectivity and subjectivity of decision-making problems reasonably, the optimal weight is obtained by combining subjective weights and objective weights.
This book presents the selected peer-reviewed papers from the International Conference on Communication Systems and Networks (ComNet) 2019. Highlighting the latest findings, ideas, developments and applications in all areas of advanced communication systems and networking, it covers a variety of topics, including next-generation wireless technologies such as 5G, new hardware platforms, antenna design, applications of artificial intelligence (AI), signal processing and optimization techniques. Given its scope, this book can be useful for beginners, researchers and professionals working in wireless communication and networks, and other allied fields.
Essential infrastructures such as bridges are designed to provide a long-lasting and intergenerational functionality. In those cases, sustainability becomes of paramount importance when the infrastructure is exposed to aggressive environments, which can jeopardise their durability and lead to significant maintenance demands. The assessment of sustainability is however often complex and uncertain. The present study assesses the sustainability performance of 16 alternative designs of a concrete bridge deck in a coastal environment on the basis of a neutrosophic group analytic hierarchy process (AHP). The use of neutrosophic logic in the field of multi-criteria decision-making, as a generalisation of the widely used fuzzy logic, allows for a proper capture of the vagueness and uncertainties of the judgements emitted by the decision-makers. TOPSIS technique is then used to aggregate the different sustainability criteria. From the results, it is derived that only the simultaneous consideration of the economic, environmental and social life cycle impacts of a design shall lead to adequate sustainable designs. Choices made based on the optimality of a design in only some of the sustainability pillars will lead to erroneous conclusions. The use of concrete with silica fume has resulted in a sustainability performance of 46.3% better than conventional concrete designs.
This book presents the proceedings of the 2020 International Conference on Intelligent Systems Applications in Multi-modal Information Analytics, held in Changzhou, China, on June 18–19, 2020. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering. It addresses a number of broad themes, including data mining, multi-modal informatics, agent-based and multi-agent systems for health and education informatics, which inspire the development of intelligent information technologies. The contributions cover a wide range of topics such as AI applications and innovations in health and education informatics; data and knowledge management; multi-modal application management; and web/social media mining for multi-modal informatics. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals, and a useful reference guide for newcomers to the field.