An Extended Neutrosophic Stepwise Weight Assessment Ratio Analysis Technique Based on GIS for Analysing Flash Floods

Nabil M.; Hassan H.; Khalid A.

doi:https://doi.org/10.54216/IJNS.210302

Fusion: Practice and Applications | 2023

An effective Decision making model through Fusion Optimization and risk associated with flash flood hazards: A case study Asyut, Egypt

One of the most dangerous natural disasters, which causes massive damage all over the world, is flash floods. Therefore, the assessment of flash floods disasters is considered increasingly urgent and important. The widely used techniques for studying and analyzing the causes and impact of natural hazards are multi-criteria techniques. Several researchers used traditional multi-criteria decision-making techniques in the estimation process of flash floods problems as the analytical hierarchy process, decision making trial and evaluation laboratory and analytic network process. The main disadvantage of these traditional models is the incapability of simulating and reflecting uncertain human thoughts. Since neutrosophic logic has a great ability for simulating human’s thoughts and increase the flexibility of expert's preferences in real world problems, we applied it in this study. There are different locations in Egypt that are at a serious risk of flooding, especially in Upper Egypt. Asyut has suffered from frequent flash floods, with some flood events that lead to mortality, damages, and economic losses in the last decades. The intensity of floods in Egypt varies from year to year, according to several climatic and hydrological variables. This study focuses on using a Neutrosophic Decision making trial and evaluation laboratory (N-DEMATEL) technique with remotely sensed data and geographical information system (GIS) for producing a flash floods hazard map. The N-DEMATEL technique is applied to determine the weights of various factors that related to flash flooding, including elevation, slope, topographic wetness index, distance from the stream, flow accumulation, aspect, flow direction, soil, land cover, watershed, curvature, drainage density , total population , population density and precipitation. The obtained weight of selected criteria used then to produce the flood hazard map (FHM) using a raster calculator tool in geographic information system.

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Nabil M. AbdelAziz mail -

Hassan H. Mohammed mail -

Khalid A. Eldrandaly mail

link https://doi.org/10.54216/FPA.120105

Volume & Issue

Vol. Volume 12 / Iss. Issue 1

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Fusion: Practice and Applications | 2023

Ultrasound Image Noise Reduction and Enhancement Model based on Yellow Saddle Goatfish Optimization Algorithm

In the modern-day diagnostics, ultrasound play an important role in different applications such as vascular, gynecological, cardiac, and obstetrical for diagnosis the various diseases. The main benefit of the ultrasound is that it is non-invasive method and inexpensive. However, in the real-scenario, ultrasound images contain speckle noise which negatively impact the image quality in terms of edges, texture information, and boundaries. In order to eliminate noise, various filters are deployed by researchers in the literature. The limitations of their method are that a fixed level of noise is removed using conventional filters in which parameter values of the filters are fixed. However, in the real-time situation, the noise is random and adaptive filters are required which eliminate any level of noise. To achieve this goal, this paper proposes an adaptive filtering model for eliminate speckle noise based on yellow saddle goatfish optimization (YSGO) algorithm. The YSGO algorithm is based on the hunting behaviour of the fishes. In the proposed model, bilateral filter and speckle-reducing anisotropic diffusion filtering methods and enhancement power law method are taken under consideration. Further, the parameter values of the filtering method and enhancement methods are determined using the nature-inspired YSGO algorithm. The YSGO algorithm minimize the noise and enhances the image brightness and edge information based on the objective function. In our model, mean square error (MSE) and entropy is taken as the objective function. Further, the proposed model is applied on the standard ultrasound images. The visual analysis of the images is done based on the subjective analysis whereas various performance metrics are measured for measure the image quality in the objective analysis. The results reveals that the proposed model outperforms over the existing models in terms of PSNR.

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Anamika Goel mail -

Jawed Wasim mail -

Prabhat Kumar Srivastava mail -

Aditi Sharma mail

link https://doi.org/10.54216/FPA.120201

Volume & Issue

Vol. Volume 12 / Iss. Issue 2

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International Journal of BIM and Engineering Science | 2023

Incorporating BIM into the Academic Curricula of Faculties of Architecture within the Framework of Standards for Engineering Education

Governments and the architectural, engineering, and construction industry (AEC) around the world have paid great attention to the application of Building Information Modeling in their projects due to the many advantages it offers, which called on educational institutions to include BIM in their curricula and to qualify new graduates with the competencies and expertise necessary to keep pace with development and to supply the cadres of AEC companies.This research presents educational frameworks and current approaches to integrating BIM into educational curricula around the world, and critical success factors for integrating BIM into education. In this research, an educational BIM framework was proposed based on the research and studies presented in the BIM and Education field and a detailed work plan based on engineering standards (ABET – NARS) for the BIM integrating process in the Faculty of Architecture - Damascus University. The work plan was based on a gradual transition for BIM integration, starting from the first year to the fifth year within three levels.The proposed framework was verified by the academics at the Faculty of Architecture - Damascus University through conducting qualitative interviews to evaluate and improve the framework Comments were taken into account when developing the final proposal. At the end of the research, many recommendations and future directions were presented.

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Lara Raad mail -

Rana Maya mail -

Petr DlasK mail

link https://doi.org/10.54216/IJBES.060201

Volume & Issue

Vol. Volume 6 / Iss. Issue 2

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International Journal of BIM and Engineering Science | 2023

PV-glass interfaces for the Syndicate of Engineers building in Latakia

Building Integrated Photovoltaics (BIPVs) systems are a promising and innovative technology that has gained significant attention in the last decade. These systems aid buildings in meeting their energy demands, thereby addressing the rising energy needs. This case study was conducted on the Engineers Association Branch in Latakia.The experimental method was used to calculate the needed electrical loads, it was found that replacing 74m² of south-facing traditional glass windows of the Syndicate of Engineers building, with polycrystalline photovoltaic windows (P-Si), will produce 59.2 kilowatts, which is a sufficient amount to cover the total electrical load for the lighting and the operating office equipment, this mean to have a zero-energy building over a period of 30 to 35 years, in addition to save 65000kg of CO2 for the 30 later years. This study is particularly important in Syria's reconstruction phase, which will involve the construction of numerous tower buildings with large glass facades, where space for installing solar panels may be limited on the roofs, Therefore, the integration of solar panels in the facades is the ideal solution to cover the needed loads.

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Yara Drebati mail -

Doha Jdeed mail -

Bilal Zaarour mail

link https://doi.org/10.54216/IJBES.060202

Volume & Issue

Vol. Volume 6 / Iss. Issue 2

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International Journal of BIM and Engineering Science | 2023

Application of Artificial Intelligence Tools with BIM Technology in Construction Management: Literature Review

Nowadays, the construction sector industry energizes all other industries to diversify their service areas, nonetheless this sector needs to keep leading with technological developments. Following the adoption of Building Information Modeling technology (BIM), the construction projects has become more controlled and coordinated, which has contributed to improve productivity rates and to rationalize resources usage. This research is studied the developments in construction, especially technologies that adopt artificial intelligence (AI) with BIM technology such as machine learning, Augmented Reality techniques (AR), digital assistants, robots, automatic planning, scheduling, and optimization. These techniques can be used during design and construction stages to improve collaborative processes that have become a cornerstone of BIM technologies, as well as financial control and scheduling. Through using BIM, the construction industry can adopt AI technologies like autonomous systems and rely on machine learning in project management to access AI-based project self-management.

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Ali Louai Mostafa mail -

Mohamed Ali Mohamed mail -

Sonia Ahmed mail -

Waleed Mahfouz M. A. Youssef mail

link https://doi.org/10.54216/IJBES.060203

Volume & Issue

Vol. Volume 6 / Iss. Issue 2

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International Journal of Wireless and Ad Hoc Communication | 2023

An Enterprise of Cognitive Fog Computing For Disturbance Recognition in Internet of Things

The Internet of Things (IoT) is a cutting-edge piece of cybernetic infrastructure that will eventually link all manner of previously disconnected physical objects to the web. The IoT is rapidly expanding into many facets of human life. IoT's attack surface has grown as a result of the technology's hyper-connectivity and inherent heterogeneity. In addition, IoT devices are used in both managed and unmanaged settings, leaving them open to innovative attacks. Fog computing is used in the proposed intrusion detection system for IoT applications to implement intrusion detection in a decentralised manner. Attack detection at fog nodes and summarization on a cloud server make up the proposed system's two parts. The local fog nodes in the IoT environment examine the traffic, and then they send a report to the cloud server that summarises the current global security state of the IoT application. According to the results of the experiments, the fog nodes are able to identify the attack 27% more quickly while also reducing the number of false alarms. The work that has been recommended provides a beginning point for the creation of a fog-based intrusion detection system that can be used for applications related to the IoT. The proposed system has a false alarm rate of only 0.32% and an accuracy of 98.15 percent. The proposed method can only identify attacks that conform to specific patterns.

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Prashant Kumar Shukla mail

link https://doi.org/10.54216/IJWAC.070102

Volume & Issue

Vol. Volume 7 / Iss. Issue 1

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International Journal of Wireless and Ad Hoc Communication | 2023

Enhancing Healthcare Monitoring through the Integration of IoT Networks and Machine Learning

The technology that was developed during the fourth industrial revolution has contributed to the recent surge of interest that has been seen in the field of medicine. In particular, the importance of personal medical information obtained via knowledgeable self-diagnosis is becoming more apparent. However, the disclosure of such private medical information raises several concerns regarding trustworthiness and security. Accidents involving personally identifiable medical information could happen on the computer, but more frequently than not, they take place during the process of information exchange and data transfer. So, the goal of this research is to improve the trustworthiness of managing such sensitive data by making blockchain technology better. The objective of the project was to create smart healthcare systems by utilising blockchain technology and the Internet of Things (IoT). Moreover, they utilised various measuring instruments to collect data and carry out an individual electrocardiogram assessment. Through an examination of the fused threshold, the observed biosignals were analysed to provide a tailored diagnostic. In this article, we describe the implementation of a monitoring system that analyses individual biometric information by making use of measuring devices. Machine learning has been included in the deployed system, which has resulted in better dependability and security of the system's information.

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Vikas panthi mail -

Amit Kumar Mishra mail

link https://doi.org/10.54216/IJWAC.070103

Volume & Issue

Vol. Volume 7 / Iss. Issue 1

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American Journal of Business and Operations Research | 2023

Deep Multiple Instance Learning Approach for Classification in Clinical Decision Support Systems

To get around the drawbacks of conventional classification algorithms that required manual feature extraction and the high computational cost of neural networks, this paper introduces a deep convolutional neural network with multiple instance learning approaches, namely dynamic max pooling and sparse representation. For the categorization of tuberculosis lung illness, this model combines deep convolutional neural networks and multiple instance learning. The design was composed of four phases: pre-processing, instance production, feature extraction, and classification. To perform feature extraction, a model based on a customized version of the VGG16 architecture was trained from scratch. Multiple instance learning techniques such as Diverse Density (DD) and the Maximum pattern bag formulation of the Support Vector Machine were used to evaluate how well the proposed classification algorithm performed in comparison (SVM).The numerical findings demonstrated that the new method offered a higher level of accuracy than the methods that had been used in the past. When evaluating the efficacy of the current method, accuracy, specificity, sensitivity, and error rate were all taken into consideration. The accuracy of the max-pooling based framework and the sparse representation framework was found to be greater than that of the other multiple instance strategies, coming in at 91.51% and 89.84%, respectively, when compared to that of the other methods. The improved accuracy of the present system that makes use of deep neural networks is mostly attributable to the contributions made by features such as transfer learning and automatic feature extraction.

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Vani V. mail -

Piyush Kumar Pareek mail

link https://doi.org/10.54216/AJBOR.100206

Volume & Issue

Vol. Volume 10 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2023

Assessment of the preventive management of peripheral diabetic neuropathy by using neutrosophic AHP and neutrosophic uninorm operator

Diabetes mellitus is a disease that plagues all countries in the world. One of the affectations caused by this chronic disease is damage to peripheral nervous tissues. This is the cause of ulcers and amputations in parts of the foot of the diabetic patient. In this paper, we propose a method to evaluate the patient’s degree of preventive management of peripheral diabetic neuropathy. For this purpose, the Neutrosophic Analytic Hierarchy Process (AHP) method is used to assess the importance of factors influencing the prevention of peripheral neuropathic complications associated with diabetes mellitus in some patients. For the final evaluation, the aggregator called neutrosophic uninorm is used; especially, the operator based on the combining function utilized in the Prospector expert system.

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Lisbeth Josefina R. Chacón mail -

Paola Gabriela O. Villalba mail -

Victoria Estefanía E. Pastor mail -

Lizbeth C. Eugenio Zumbana mail -

Maria Augusta L. Sánchez mail -

Andrea C. Peñafiel Luna mail

link https://doi.org/10.54216/IJNS.210301

Volume & Issue

Vol. Volume 21 / Iss. Issue 3

Details open_in_new

International Journal of Neutrosophic Science | 2023

An Extended Neutrosophic Stepwise Weight Assessment Ratio Analysis Technique Based on GIS for Analysing Flash Floods

Flash floods are a sudden natural hazard caused by successive heavy rains in a short period of time. The world suffers from heavy and frequent rains due to climate change. So, the risk assessment of flash floods is considered increasingly important and urgent. Egypt is considered one of the countries exposed to sudden floods resulting from heavy rains, especially in Upper Egypt. Multi-criteria techniques are widely used to study and analyze the causes and effects of natural hazards. In contrast to the traditional multi-criteria techniques used in the process of estimating flood problems, we applied neutrosophic logic in this study that has a great ability for simulating and reflecting uncertain human’s thoughts in real world problems. Our study area sits in Southeast Sohag, and it is one of the most flash floods prone regions of Egypt's Eastern Desert. This area of Sohag has suffered from frequent flash floods, with some flood events resulting in human casualties in the last decades. This study focuses on using a neutrosophic stepwise weight assessment ration analysis (N-SWARA) technique with remotely sensed data and geographical information system (GIS) for producing a flash floods hazard map. The N-SWARA technique is applied to determine the weights of various factors that related to flash flooding, including elevation, slope, topographic wetness index, distance from the stream, flow accumulation, aspect, and flow direction. The obtained weight of selected criteria used then to produce the flood hazard map (FHM) using a raster calculator tool in geographic information system. The weight of each factor calculated by using the N-SWARA multi criteria analysis method and obtained the following results: 0.39 for slope, 0.21 for elevation, 0.12 for distance, 0.08 for flow direction, 0.05 for flow accumulation, 0.09 for TWI and 0.03 for aspect.

groups

Nabil M. AbdelAziz mail -

Hassan H. Mohammed mail -

Khalid A. Eldrandaly mail

link https://doi.org/10.54216/IJNS.210302

Volume & Issue

Vol. Volume 21 / Iss. Issue 3

Details open_in_new