The aim of this research is to study some types of fibrewise fuzzy topological spaces. The six major goals are explored in this thesis. The very first goal, introduce and study the notions types of fibrewise topological spaces, namely fibrewise fuzzy j-topological spaces, Also, we introduce the concepts of fibrewise j-closed fuzzy topological spaces, fibrewise j-open fuzzy topological spaces, fibrewise locally sliceable fuzzy j-topological spaces and fibrewise locally sectionable fuzzy j-topological spaces. Furthermore, we state and prove several Theorems concerning these concepts, where j={δ,θ,α,p,s,b,β} The second goal is to introduce weak and strong forms of fibrewise fuzzy ω-topological spaces, namely the fibrewise fuzzy -ω-topological spaces, weakly fibrewise fuzzy -ω-topological spaces and strongly fibrewise fuzzy -ω- topological spaces. Also, several characterizations and properties of this class are also given as well. In addition, we focused on studying the relationship between weakly fibrewise fuzzy -ω-topological spaces and strongly fibrewise fuzzy -ω-topological spaces The third goal is to present fibrewise fuzzy types of the most importint separation axioms of ordinary fuzz topology namely fibrewise fuzzy (T_0 spaces, T_1 spaces, R_0 spaces, Hausdorff spaces, functionally Hausdorff spaces, regular spaces, completely regular spaces, normal spaces and normal spaces). It also has a lot of results. The fourth goal is to learn more about fibrewise fuzzy topological spaces, particularly fibrewise fuzzy compact and fibrewise locally fuzzy compact spaces. We also look at the connections between the many fibrewise fuzzy separation axioms and fibrewise fuzzy compact (or fibrewise locally fuzzy compact) spaces. We also provide a list of possible responses The fifth goal is to present a modern concept of fibrewise topological spaces known as fibrewise fuzzy ideal topological spaces. As a result, we define fibrewise closed fuzzy ideal topological spaces, fibrewise open fuzzy ideal topological spaces, and fibrewise fuzzy j-ideal topological spaces, where j ∈{α,P,S,b ,β} The sixth goal is to present a new concepts in fibrewise bitopological spaces known as fibrewise fuzzy ij-closed, fibrewise fuzzy ij-compact, fibrewise fuzzy ij-perfect, fibrewise fuzzy weakly ij-closed, and fibrewise fuzzy almost ij-perfect. It also introduces some concepts such as contact fuzzy point, ij-adherent fuzzy point, fuzzy filter, fuzzy filter base, ij-converges to a fuzzy subset, ij-directed toward a fuzzy set, ij-fuzzy continuous, ij-fuzzy closed functions, ij-fuzzy rigid set, ij-fuzzy continuous functions, weakly ij-fuzzy closed, ij-H-fuzzy set, almost ij-perfect bitopological spaces. Obtain some of its fundamental properties and characterizations as well.
In this research, the problem of ambiguity of the data for the project of establishing the typical reform complex in Basrah Governorate was eliminated. The blurry of the data represented by the time and cost of the activities was eliminated by using the Ranking function and converting them into normal numbers. Scheduling and managing the Project in the Critical Pathway (CPM) method to find the project completion time in normal conditions in the presence of non-traditional relationships between the activities and the existence of the lead and lag periods. The MS Project was used to find the critical path. The results showed that the project completion time (1309.5) dinars and the total cost has reached (33113017769) dinars and the
... Show MoreFace recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security
... Show MoreSome experiments need to know the extent of their usefulness to continue providing them or not. This is done through the fuzzy regression discontinuous model, where the Epanechnikov Kernel and Triangular Kernel were used to estimate the model by generating data from the Monte Carlo experiment and comparing the results obtained. It was found that the. Epanechnikov Kernel has a least mean squared error.
The research dealt with the topic ' the aesthetics of design shape of interior spaces for the syndicate of physicians' as it reflects visions evolving to the level of tasting and positive interpretation for the space of work to be on a high design level.The research consisting of four chapters as follow; The first chapter examined the problem of the research contracted in the following question: Have the design shapes any role in achieving and showing the aesthetic side for the syndicate of physicians? so the goal of the research was showing the aesthetics of design shape of interior spaces for the syndicate of physicians, The chapter also included the objective spatial and temporal limits of research .Finally the terms were specified. T
... Show MoreThe aim of this work is to provide an efficient selection technique as a part of planning process to guide the decision makers to decide the preferences of one supplier over another for purchasing lab instruments in education domain. Fuzzy Analytical Hierarchy Process has used as a multi-criteria decision process, as an industrial engineering tool with certain emphasis on the qualitative aspects required to the decision makers. While the concept of degree of possibility for each criterion is used to reach its relative weights, a specific methodology created to reach the final objective decision of supplier selection. A questionnaire form was developed and distributed to five universities located in Baghdad province with a total
... Show MoreThis paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF
... Show MoreIn the current study, the definition of mapping of fuzzy neutrosophic generalized semi-continuous and fuzzy neutrosophic alpha has generalized mapping as continuous. The study confirmed some theorems regarding such a concept. In the following, it has been found relationships among fuzzy neutrosophic alpha generalized mapping as continuous, fuzzy neutrosophic mapping as continuous, fuzzy neutrosophic alpha mapping as continuous, fuzzy neutrosophic generalized semi mapping as continuous, fuzzy neutrosophic pre mapping as continuous and fuzzy neutrosophic γ mapping as continuous.
Ad-Hoc Networks are a generation of networks that are truly wireless, and can be easily constructed without any operator. There are protocols for management of these networks, in which the effectiveness and the important elements in these networks are the Quality of Service (QoS). In this work the evaluation of QoS performance of MANETs is done by comparing the results of using AODV, DSR, OLSR and TORA routing protocols using the Op-Net Modeler, then conduct an extensive set of performance experiments for these protocols with a wide variety of settings. The results show that the best protocol depends on QoS using two types of applications (+ve and –ve QoS in the FIS evaluation). QoS of the protocol varies from one prot
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