Methods for Fuzzy Demand Assessment for It Specialties

Mammadova, Masuma

doi:10.21303/2461-4262.2019.00939

Cited by 5 publications

(5 citation statements)

References 7 publications

(11 reference statements)

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“…Fuzzy systems are one of the most important areas applying the theory of fuzzy sets [29]. Such systems are often based on a structural model in the form of fuzzy rules.…”

Section: Computer Sciencesmentioning

confidence: 99%

Development of the principles of fuzzy rule-based system for hepatocelular carcinoma staging

2021

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The article proposes the principles for the development of a fuzzy rule-based physician decision support system n to determine the stages of the most common hepatocellular carcinoma (HCC) among malignant tumors of liver. The stages of HCC, i.e., critical situations, are expressed by different combinations of clinical signs of input data and emerging clinical conditions. These combinations shape the multiplicity of possible situations (critical situations) by forming linguistic rules that are in fuzzy relations with one another. The article presents the task of developing a fuzzy rules-based system for HCC staging by classifying the set of possible situations into given classes. In order to solve the problem, fuzzy rules of clinical situations and critical situations deviated from them are developed according to the possible clinical signs of input data. The rules in accordance with the decision-making process are developed in two phases. In the first phase, three input data are developed: nine rules are developed to determine possible clinical conditions based on the number, size, and vascular invasion of tumor. In the second phase, seven rules are developed based on possible combinations of input data on the presence of lymph nodes and metastases in these nine clinical conditions. At this stage, the rules representing the fuzzification of results obtained are also described. The latter provide an interpretation of results and a decision on related stage of HCC. It also proposes a functional scheme of fuzzy rules-based system for HCC staging, and presents the working principle of structural blocks. The fuzzy rule-based system for HCC staging can be used to support physicians to make diagnostic and treatment decisions

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“…Fuzzy systems are one of the most important areas applying the theory of fuzzy sets [29]. Such systems are often based on a structural model in the form of fuzzy rules.…”

Section: Computer Sciencesmentioning

confidence: 99%

Development of the principles of fuzzy rule-based system for hepatocelular carcinoma staging

2021

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“…The learner's knowledge on different specialties is examined in different disciplines. The relationships between the demand for each specialty group and the disciplines it includes and the real knowledge of the learner on different disciplines can be illustrated by fuzzy demand and supply models [30][31][32].…”

Section: Developing Relationship Function Among Elements Of Specialtimentioning

confidence: 99%

Modelling Support Systems for Selecting Professions for Applicants in the Content of Personalization of Education

Gasimov

2020

EUREKA: Physics and Engineering

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Various methods are currently being used in examining the initial "START" knowledge of applicants and their placement for specialties. Studies show that applicants are placed on the decreasing principle in terms of their overall scores at universities. In this case, applicants with a high level of knowledge are placed in the prestigious specialties as medicine and law as they require high results. Though, while applying for other professions, the applicants do not perform enough results on the key disciplines for the profession, they are placed in those professions when the general results enable it. This causes them to face a number of problems while working both in education process and in the industry.To avoid this problem and to place applicants in a specialty that is more relevant to their level of knowledge, the introduction of an individual approach to the evaluation of initial level of knowledge may be more promising.This article presents a modeling of the "evaluation -placement" support system for the individual approach to assessing applicants' knowledge and positioning them in relevant specialties. The main goal of the system is to give each applicant the opportunity to choose and study the specialty that is more relevant to their knowledge and skills, as well as to analyze the results for each discipline along with the overall results. The system is implemented using fuzzy logic based artificial neural networks.The network consists of 100 neurons in the input layer, two hidden layers and one output layer. The number of neurons at the output is the same as the number of specialties taught at university. one of the most promising technologies in assessing students' competence [8]. Intelligent analysis in the educational environment is based on decision making, statistics, pattern recognition, cluster analysis, classification, regression and factor analysis, fuzzy logic, artificial neural networks and other methods [9][10][11][12][13][14][15]. The personalization of education or the determination of individual learning trajectories for each student is also possible through the use of artificial intelligence in the learning process. One of the characteristics of learners is their learning style [16].The trajectory of the personal education is a three-stage process that involves evaluating the basic knowledge and directing to occupations, from the initial assessment to the beginning of education and the stages of the educational process [17].There are many articles in the scientific literature on the use of intellectual systems at different stages of the educational process. A creation concept has been specified for a learning management system of new generation that allows forming individual learning trajectories based on analysis of student's achievements, wishes and peculiarities. Forming individual learning trajectories based on student's achievements and functional state analysis provides the possibility to build educational process automatically that will be suitable for a specific student and satisf...

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“…With the rapid development of technology, it can be seen that the filter circuit is an important circuit, in analog signal processing systems, which are widely used in many fields such as electro nics, communications, control systems and instrumentation [1][2][3][4]. In industry, electronic circuits have been applied to various devices, for example, to measure and control the rotational speed of motors, such as the voltage controlled oscillator circuit [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

The design of a fully balanced current–tunable active RC integrator

Roungrid,

Khwunnak,

Lertkonsarn

2023

Eureka: PE

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The design of the active RC integrator presented in this research utilizes a fully balanced technique and current-tunable frequencies to create the active RC integrator and reliable circuit. The circuit is made up of six npn bipolar junction transistors (BJT), six resistors (R), and a capacitor (C), with the fully balanced technique used to make the circuit structure uncomplicated and symmetrical with signal differencing. This approach results in a low number of internal devices in the circuit, making it an attractive option for integrated circuit (IC) development. One of the key features of the fully balanced current-tunable active RC integrator is its ability to be frequency-tunable with bias current (If). This feature enables the circuit to be used in a variety of applications, including filter circuits, communication signal generators, instrumentation signal generators, and various automatic controls. The fully balanced design also ensures that the circuit is stable and robust, even in the presence of device parameter variations. To evaluate the performance of the active RC integrator, simulations were conducted using Pspice. The results show that a fully current-tunable active RC integrator can be precisely tuned with the active bias to a value consistent with the theoretically calculated value. This demonstrates the efficiency and reliability of the circuit design and simulation method. The Monte Carlo (MC) method was also used to analyze the circuit performance in cases where the resistor (R) and capacitor (C) device had a 10 percent error and the transistor gain (β) was set to an error of 50 percent. The MC analysis showed that the phase shift (degree) and magnitude (dB) of the circuit were stable, and the circuit's performance was not significantly impacted by the device parameter variations. This further demonstrates the robustness and versatility of the fully balanced current-tunable active RC integrator design. Finally, harmonic distortion was evaluated to confirm the performance of the designed and developed fully balanced current-tunable active RC integrator. The results showed low levels of harmonic distortion, which indicates that the circuit is suitable for high-performance applications that require low distortion

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Methods for Fuzzy Demand Assessment for It Specialties

Cited by 5 publications

References 7 publications

Development of the principles of fuzzy rule-based system for hepatocelular carcinoma staging

Development of the principles of fuzzy rule-based system for hepatocelular carcinoma staging

Modelling Support Systems for Selecting Professions for Applicants in the Content of Personalization of Education

The design of a fully balanced current–tunable active RC integrator

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