Decision-making in Operations Research is the main point in various studies in our real-life applications. However, these different studies focus on this topic. One drawback some of their studies are restricted and have not addressed the nature of values in terms of imprecise data (ID). This paper thus deals with two contributions. First, decreasing the total costs by classifying subsets of costs. Second, improving the optimality solution by the Hungarian assignment approach. This newly proposed method is called fuzzy sub-Triangular form (FS-TF) under ID. The results obtained are exquisite as compared with previous methods including, robust ranking technique, arithmetic operations, magnitude ranking method and centroid ranking method. This

In this work, a large part of Baghdad University campus has been selected. The determination of Geoidal height for the local area requires Ground Control Points which both Ellipsoidal and Orthometric heights are known to compute the difference between them. The first step of the leveling process began by selected the Ground Control Points (GCPs) around the area of the work, and then divided them into two groups of the network traverse stations. They were leveled and adjusted depend on the number of the Bench Marks (B.M.s). Total Station TS (Nikon Nivo 5C) and Global Positioning System (GPS-Garmin 78 map) are used to do this application. The aim of the proposed work was to determine the height of the Geoid surface in the study area. The Geoi

The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid est

Photocatalytic degradation of methylene blue was studied using CdS and ZnS as catalyst. The photocatalytic activity of the specimen was studied by exposing to UV-radiation. The result shows that the degradation efficiency of the dye for CdS micro-particles was 92% after 7 hours and for ZnS micro-particles was 88.29% for the same time interval.

Sustainable development has recently gained significant attention in the field of water Quality (WQ), which is critical for a healthy lifestyle. Our work suggests an intelligent hybrid model for assessing water quality using a water portability dataset, which was used to evaluate the water quality. The dataset contains physical and chemical features such as pH, Organic Carbon, sulfate, etc. Based on the combination of a Decision Tree Algorithm (DTA) and fuzzy logic Approaches, the findings revealed that sulfate was the most important factor in the model, with an accuracy of 1.00, followed by pH with an accuracy of 0.9667, and solids and chloramines with an accuracy of 0.95. The other parameters achieved a similar accuracy of 0.9167, showing

The aim of this paper is to present a weak form of -light functions by using -open set which is -light function, and to offer new concepts of disconnected spaces and totally disconnected spaces. The relation between them have been studied. Also, a new form of -totally disconnected and inversely -totally disconnected function have been defined, some examples and facts was submitted.

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

As one type of resistance furnace, the electrical tube furnace (ETF) typically experiences input noise, measurement noise, system uncertainties, unmodeled dynamics and external disturbances, which significantly degrade its temperature control performance. To provide precise, and robust temperature tracking performance for the ETF, a robust composite control (RCC) method is proposed in this paper. The overall RCC method consists of four elements: First, the mathematical model of the ETF system is deduced, then a state feedback control (SFC) is constructed. Third, a novel disturbance observer (DO) is designed to estimate the lumped disturbance with one observer parameter. Moreover, the stability of the closed loop system including controller