Object Position Estimation based on Dual Sight Perspective Configuration

Development of the coordination system requires the dataset because the dataset could provide information around the system that the coordination system can use to make decisions. Therefore, the capability to process and display data-related positions of objects around the robots is necessary. This paper provides a method to predict an object’s position. This method is based on the Indoor Positioning System (IPS) idea and object position estimation with the multi-camera system (i.e., stereo vision). This method needs two input data to estimate the ball position: the input image and the robot’s relative position. The approach adopts simple and easy calculation technics: trigonometry, angle rotations, and linear function. This method was tested on a ROS and Gazebo simulation platform. The experimental result shows that this configuration could estimate the object’s position with Mean Squared Error was 0.383 meters. Besides, R squared distance calibration value is 0.9932, which implies that this system worked very well at estimating an object’s position.

NTRU Over Galois Rings

As a cryptosystem, Nth Truncated Polynomial Ring (NTRU) is established on the fast and easy calculation. Improving the security is aimed by enlarging a ring where the processes execute and enhancing the number of a private key and a public key. In this study, NTRU takes over the Galois rings and is analysed by adding a new private key.

Correlations for Easy Calculation of the Critical Coalescence Concentration (CCC) of Simple Frothers

Can the critical coalescence concentration (CCC) of the flotation frothers be predictable? What is the relation between their molecular structure and their CCC values? A literature survey found specific correlations between the hydrophilic-lipophilic balances (HLB) and HLB/Mw (where Mw stands for the molecular mass) of homologue series of frothers and their CCC values, but the results are invalid when the molecule’s functional groups change. For this reason, 37 frothers with known values of CCC were analyzed. The CCC values of seven frothers were determined, and the rest were taken from the literature. The frothers were subdivided in homologue series with an increasing number of the carbon atoms with an account for the type and the location of the functional group, thus deriving three types of correlations lnCCC = f(HLB) applicable for: (i) alcohols; (ii) propylene glycols alkyl ethers and propylene glycols; (iii) ethylene glycols alkyl ethers. The average accuracy of these correlations between CCC and HLB is 93%.

Boubaker Wavelet Functions for Solving Higher Order Integro-Differential Equations

In the present paper, the properties of Boubaker orthonormal polynomials are used to construct new Boubaker wavelet orthonormal functions which are continuous on the interval [0, 1). Then, a Boubaker wavelet orthonormal operational matrix of the derivative is obtained with the new general procedure. The matrix elements can be expressed in a simple form that reduces the computational complexity. The collocation method of the Boubaker orthonormal wavelet functions together with the application of the derived operational matrix of the derivative are then utilized to transform the higher-order integro-differential equation into a solution of linear algebraic equations. As a result, the solution of the original problem reduces to the solution of a linear system of algebraic equations and can be sufficiently solved by an approximate technique. The main advantage of the suggested method is that the orthonormality property greatly simplifies the original problem and leads to easy calculation of the coefficients of expansion. Special attention is needed to perform the convergence analysis. The error is analyzed when a sufficiently smooth function is expanded in terms of the Boubaker orthonormal wavelet functions, then an estimation of the upper bound of the error is calculated. The results obtained by the technique in the current work are reported by solving some numerical examples and the accuracy is checked by comparing the results with the exact solution.

Lithium Battery Monitoring and Mathematically Modelling its Equation

Ever since people have managed to start shifting to electric vehicles, the lack of a cost-efficient battery monitoring system has been a real lack of concern for this mode of transportation. Not everyone wants to start a car after 6 months only to realize later that the battery is dead. Hence knowing the status of the battery on the back of our hand is crucial. This system will provide a steady supply of data about the status of vulnerable lithium-ion car battery which may include parameters such as the state of discharge (SOD) and state of temperature (SOT) to smartphones thereby eliminating this nuisance and also have inbuilt protection to help extend the battery life and avoid unwanted repairs which increases the maintenance costs. Using machine learning concepts like linear regressions and plotting’s. A mathematical equation was developed for the lithium battery and this equation will provide an easy calculation for above discussed parameters and reduce the circuit complexity

A new method for calculating individual subitizing ranges

A large body of research has shown that human adults are fast and accurate at enumerating arrays of ~1-4 items. This phenomenon has been called subitizing. Above this range, enumeration is slower and less accurate. The subitizing range has been related to individual differences in variables such as mathematical abilities, working memory, etc. The two most common methods for calculating subitizing range today – bilinear fit and sigmoid fit – have their strengths and weaknesses. By combining these two methods, we overcome their biggest limitations and come up with a novel way for calculating Individual Subitizing Range (ISR). This paper introduces this new method as well as empirical studies designed to test the new method. We replicated classic effects from the literature and obtain a high correlation with the sigmoid fit method. This paper includes a Matlab code for easy calculation of ISR as well as a ready-to-use experimental file for testing ISR. We hope that these tools would be of use to researchers studying individual differences in the subitizing range.

Analytic Formulas to Calculate Symmetric Brothers of a Node in a Perfect Binary Tree

The paper puts forward and solves the problem of calculating the symmetric brother nodes of a given node in a perfect binary tree. By analyzing the relationships between a node and its ancestors, the position at which a node lies in term of the subtree rooted by an ancestor is expressed with a mathematical formula and consequently the mathematical formula to express its symmetric nodes is derived out. The formulas enable an easy calculation of a node and its symmetric nodes in the perfect binary tree.

Calculation and measurement of mean room surface exitance: The accuracy evaluation

Cuttle proposed mean room surface exitance as a new interior lighting design methodology, which focuses on lit appearance rather than visual performance. A few challenges exist, among which, an easy calculation method and a practical measurement strategy are two important aspects. Cuttle has developed a simplified equation for mean room surface exitance calculation and proposed that mean room surface exitance can be estimated by measuring indirect corneal illuminance from a position that ‘ brings most of the space into view’; however, no solid proof was provided. In this work, first, we demonstrate that the simplified equation is reasonably accurate by comparing its predictions with the results based on numerical simulation of a wide range of surface reflectance combinations. Two luminaire locations, which are carefully selected to have the same input to the simplified equation but leading to very different surface exitance distributions, are adopted to further verify the simplified equation; second, through a theoretical analysis and numerical simulation, we show that both indirect corneal illuminance and indirect cylindrical illuminance vary significantly with the measurement location and can be very different from mean room surface exitance. Therefore, we conclude that the method of measuring mean room surface exitance suggested in prior publications may not provide accurate results.