scholarly journals Garage location selection for residential house by WASPAS-SVNS method

2017 ◽  
Vol 23 (3) ◽  
pp. 421-429 ◽  
Author(s):  
Romualdas BAUŠYS ◽  
Birutė JUODAGALVIENĖ
Keyword(s):  
Mathematical Model ◽  
Real Life ◽  
Neutrosophic Set ◽  
Single Family ◽  
Initial Information ◽  
Location Selection ◽  
Modeling Uncertainty ◽  
Residential House ◽  
Selection For ◽  
The Mathematical Model

The paper deals with the location selection problem of the garage at the parcel of a single-family residential house. The mathematical model for this real life problem is constructed within MCDM framework. The significance of the chosen criteria was evaluated by AHP approach. The formulated MCDM problem is solved applying WASPAS extension, namely WASPAS-SVNS. The applied single-valued neutrosophic set allows to modeling uncertainty of the initial information explicitly. A numerical example is considered in order to verify the proposed approach.

scholarly journals A Pot-Like Vibrational Microfluidic Rotational Motor

Micromachines ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 177
Author(s):  
Suzana Uran ◽  
Matjaž Malok ◽  
Božidar Bratina ◽  
Riko Šafarič
Keyword(s):  
Mathematical Model ◽  
Rotational Speed ◽  
Mechanical Energy ◽  
Real Life ◽  
Frequency Region ◽  
Theoretical Research ◽  
Practical Challenge ◽  
The Mathematical Model ◽  
Motor Structure ◽  
Proper Balance

Constructing a micro-sized microfluidic motor always involves the problem of how to transfer the mechanical energy out of the motor. The paper presents several experiments with pot-like microfluidic rotational motor structures driven by two perpendicular sine and cosine vibrations with amplitudes around 10 μm in the frequency region from 200 Hz to 500 Hz. The extensive theoretical research based on the mathematical model of the liquid streaming in a pot-like structure was the base for the successful real-life laboratory application of a microfluidic rotational motor. The final microfluidic motor structure allowed transferring the rotational mechanical energy out of the motor with a central axis. The main practical challenge of the research was to find the proper balance between the torque, due to friction in the bearings and the motor’s maximal torque. The presented motor, with sizes 1 mm by 0.6 mm, reached the maximal rotational speed in both directions between −15 rad/s to +14 rad/s, with the estimated maximal torque of 0.1 pNm. The measured frequency characteristics of vibration amplitudes and phase angle between the directions of both vibrational amplitudes and rotational speed of the motor rotor against frequency of vibrations, allowed us to understand how to build the pot-like microfluidic rotational motor.

scholarly journals SIMULATION AND SENSITIVITY ANALYSIS ON THE PARAMETER OF NON-TARGETED IRRADIATION EFFECTS MODEL

2018 ◽  
Vol 81 (1) ◽  
Author(s):  
Muhamad Hanis Nasir ◽  
Fuaada Mohd Siam
Keyword(s):  
Mathematical Model ◽  
Sensitivity Analysis ◽  
Real Life ◽  
Double Strand Breaks ◽  
Signal Molecules ◽  
Danger Signal ◽  
Survival Fraction ◽  
Strand Breaks ◽  
Radiation Induced ◽  
The Mathematical Model

Real-life situations showed damage effects on non-targeted cells located in the vicinity of an irradiation region, due to danger signal molecules released by the targeted cells. This effect is widely known as radiation-induced bystander effects (RIBE). The purpose of this paper is to model the interaction of non-targeted cells towards bystander factors released by the irradiated cells by using a system of structured ordinary differential equations. The mathematical model and its simulations are presented in this paper. In the model, the cells are grouped based on the number of double-strand breaks (DSBs) and mis-repair DSBs because the DSBs are formed in non-targeted cells. After performing the model's simulations, the analysis continued with sensitivity analysis. Sensitivity analysis will determine which parameter in the model is the most sensitive to the survival fraction of non-targeted cells. The proposed mathematical model can explain the survival fraction of non-targeted cells affected by the bystander factors.

scholarly journals Mathematical modeling of emergency situations at objects of production and gas transportation

2018 ◽  
Vol 251 ◽  
pp. 04012 ◽  
Author(s):  
Victor Orlov ◽  
Elena Detina ◽  
Oleg Kovalchuk
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Model ◽  
Life Cycle ◽  
Real Life ◽  
Functional Safety ◽  
Emergency Situations ◽  
Managerial Decisions ◽  
Management Of Resources ◽  
Rational Management ◽  
The Mathematical Model

Mathematical modeling attracts the attention of researchers from different fields, as one of the rigorous methods of justifying the conducted researchs. Mathematical modeling makes it possible forecast to real life situations. Based on the mathematical model, the work provides the innovative recommendations for making managerial decisions on increasing the reliability and functional safety of the pipeline at all stages of its life cycle. The results obtained allow: 1) to consider issues related to the rational management of resources for the maintenance of the infrastructure of gas chemical complexes in conditions of limited means; 2) is have adapt RAMS methodology to the complex of Russian standards and the base of normative and methodological documentation on managing the life cycle processes of systems of to product and transportat of gas.

AN AUTOMATED MULTI-OBJECTIVE INVIGILATOR-EXAM ASSIGNMENT SYSTEM

2010 ◽  
Vol 09 (02) ◽  
pp. 223-238 ◽  
Author(s):  
ZEHRA KAMISLI OZTURK ◽  
GURKAN OZTURK ◽  
MUJGAN SAGIR
Keyword(s):  
Mathematical Model ◽  
Exact Solution ◽  
User Interfaces ◽  
Assignment Problem ◽  
Real Life ◽  
Web Based ◽  
Multi Objective ◽  
The Core ◽  
Real Life Problem ◽  
The Mathematical Model

This paper is concerned with the invigilator-exam assignment problem. A web-based Automated Invigilator Assignment System (AIAS), consists of a mathematical model; a database storing the information and web-based user interfaces is constructed to solve the problem by providing an environment for a practical usage. The core of the system is the mathematical model developed for obtaining the exact solution. We conclude the paper by presenting a real-life problem solved by the proposed approach.

scholarly journals Use of Fuzzy Matrices for the Diagnosis of Diabetes, Anaemia and Hypertension

2020 ◽  
Vol 8 (2) ◽  
Author(s):  
Rajeev Sapre ◽  
Muktai Desai ◽  
Mugdha Pokharanakar
Keyword(s):  
Mathematical Model ◽  
Real Life ◽  
Medical Knowledge ◽  
Medical Documentation ◽  
Diagnostic Process ◽  
Uncertain Information ◽  
Fuzzy Relations ◽  
Degree Of Confidence ◽  
User Friendly ◽  
The Mathematical Model

The mathematical model presented here aims to enhance the precision in diagnostic process of diabetes, anaemia and hypertension by means of fuzzy interface. In real life, the imprecise nature of medical documentation and uncertain information provided by patients often do not give the desired degree of confidence to the diagnosis. To that end using the capability of fuzzy logic in representing, interpreting and utilizing data and information that are vague and lack certainty, a new algorithm based on different fuzzy matrices and fuzzy relations is developed. In the process a medical knowledge base is developed with the help of 51 doctors. The model achieved 94.44% accuracy in the diagnosis, which shows its usefulness. To implement this model-based diagnosis procedure a user-friendly Excel program is designed.  

Sinking Failure of Drag Embedment Anchors Due to Wave-Induced Seabed Liquefaction

2018 ◽  
Vol 01 (04) ◽  
pp. 1850006
Author(s):  
V. S. Ozgur Kirca ◽  
B. Mutlu Sumer
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Model ◽  
Grain Size ◽  
Relative Density ◽  
Parametric Study ◽  
Soil Depth ◽  
Real Life ◽  
Wave Induced ◽  
The Mathematical Model ◽  
O 10

This paper presents the results of an integrated mathematical modeling exercise for sinking of Drag Embedment Anchors (DEA) in a seabed liquefied by waves. The mathematical model consists of three elements (sub-models): (1) Mathematical model for residual liquefaction under waves; (2) Mathematical model for sinking of DEAs in the liquefied soil; and (3) Mathematical model for upward progression of compaction front in the post-liquefaction stage. The study demonstrates the implementation of the model with reference to a selected group of real-life DEAs. The results generally show that the ultimate sinking depths of DEAs are rather large (tens of centimeters short of the liquefaction depth), and accordingly, the ultimate sinking times of DEAs are rather small (O(10[Formula: see text]min)) as a result of the massive weights of these anchors. The paper presents a parametric study carried out in a systematic way to understand the influence of parameters such as the relative density of soil, the soil depth, and the grain size on the end results.

Mathematical Models of Waiting Time

1990 ◽  
Vol 83 (8) ◽  
pp. 622-627
Author(s):  
Sheldon P. Gordon ◽  
Florence S. Gordon
Keyword(s):  
Mathematical Model ◽  
Mathematical Models ◽  
Waiting Time ◽  
Mathematical Expectation ◽  
Real Life ◽  
Research Projects ◽  
Mathematical Ideas ◽  
Life Data ◽  
Real Life Data ◽  
The Mathematical Model

The old saying goes, “Time and tide wait for no man.” In today's society, an equally apt line might be, “Everyone waits for almost everything.” This widespread experience with waiting lends a marvelous opportunity to develop some very nice mathematics and apply it to problems with which our students can easily identify. In this art icle, we shall consider several mathematical models that can be used to study different waiting situations. The mathematics used involves just simple ideas from probability and mathematical expectation. Some related ideas are given in Mathers (1976). We shall also consider how computer simulations can be introduced to bring an added dimension to these topics. Most important, we shall see how such mathematical ideas furnish an ideal vehicle for involving students in actual individual research projects to collect real-life data, analyze it, and compare the results to predictions based on the mathematical model.

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