scholarly journals Centroidal-polygon: a new modified Euler to improve speed of resistor-inductor circuit equation

2021 ◽  
Vol 24 (3) ◽  
pp. 1399
Author(s):  
Nur Shahirah Zulkifli ◽  
Nooraida Samsudin ◽  
Suzanna Ridzuan Aw ◽  
Wan Farah Hanan Wan Osman ◽  
Shahreen Kasim ◽  
...  
Keyword(s):  
Time Complexity ◽  
First Order ◽  
Electrical Part

Two types of first-order circuits are resistor-capacitor (RC) and resistorinductor (RL). This paper focuses on the RL circuit equation. The centroidalpolygon (CP) scheme will be tested using SCILAB 6.0 software. This new scheme (CP scheme) is addressed to improve the speed. For the first order circuit equation, the complexity is focused on the time complexity, which is speed of the time taken to complete the simulation in the electrical part. The CP scheme is compared with the previous studies, polygon (P) and harmonic-polygon (HP). The result shows that the CP scheme is less computational and an alternative to solve the first order circuit equation, and get the result quickly compared with the previous research.

scholarly journals A Band and Bound Technique for Simple Random Algorithms

1990 ◽  
Vol 4 (3) ◽  
pp. 333-344 ◽  
Author(s):  
Vernon Rego
Keyword(s):  
Markov Chain ◽  
Time Complexity ◽  
Transition Matrix ◽  
Standard Approach ◽  
Initial State ◽  
First Order ◽  
Expected Time ◽  
Order Markov Chain ◽  
Probability Transition Matrix ◽  
Random Algorithm

A simple random algorithm (SRA) is an algorithm whose behavior is governed by a first-order Markov chain. The expected time complexity of an SRA, given its initial state, is essentially the time to absorption of the underlying chain. The standard approach in computing the expected runtime is numerical. Under certain conditions on the probability transition matrix of an SRA, bounds on its expected runtime can be obtained using simple probabilistic arguments. In particular, one can obtain upper and lower (average time) logarithmic bounds for certain algorithms based on SRAs.

HASTA

2014 ◽  
Vol 10 (2) ◽  
pp. 39-54 ◽  
Author(s):  
Shuliang Wang ◽  
Yasen Chen
Keyword(s):  
Time Complexity ◽  
Clustering Algorithm ◽  
Data Input ◽  
Full Size ◽  
First Order ◽  
Potential Value ◽  
Maximum Value ◽  
Data Field ◽  
Data Objects ◽  
Exact Amount

In this paper, a novel clustering algorithm, HASTA (HierArchical-grid cluStering based on daTA field), is proposed to model the dataset as a data field by assigning all the data objects into qusantized grids. Clustering centers of HASTA are defined to locate where the maximum value of local potential is. Edges of cluster in HASTA are identified by analyzing the first-order partial derivative of potential value, thus the full size of arbitrary shaped clusters can be detected. The experimented case demonstrates that HASTA performs effectively upon different datasets and can find out clusters of arbitrary shapes in noisy circumstance. Besides those, HASTA does not force users to preset the exact amount of clusters inside dataset. Furthermore, HASTA is insensitive to the order of data input. The time complexity of HASTA achieves O(n). Those advantages will potentially benefit the mining of big data.

Computability and complexity

2004 ◽  
Author(s):  
Shawn Hedman
Keyword(s):  
Polynomial Time ◽  
Time Complexity ◽  
Finite Graph ◽  
Computability Theory ◽  
Theoretical Computer Science ◽  
Order Logic ◽  
First Order Logic ◽  
First Order ◽  
Mathematical Problems ◽  
Time Required

In this chapter we study two related areas of theoretical computer science: computability theory and computational complexity. Each of these subjects take mathematical problems as objects of study. The aim is not to solve these problems, but rather to classify them by level of difficulty. Time complexity classifies a given problem according to the length of time required for a computer to solve the problem. The polynomial-time problems P and the nondeterministic polynomial-time problems NP are the two most prominent classes of time complexity. Some problems cannot be solved by the algorithmic process of a computer. We refer to problems as decidable or undecidable according to whether or not there exists an algorithm that solves the problem. Computability theory considers undecidable problems and the brink between the undecidable and the decidable. There are only countably many algorithms and uncountably many problems to solve. From this fact we deduce that most problems are not decidable. To proceed beyond this fact, we must state precisely what we mean by an “algorithm” and a “problem.” One of the aims of this chapter is to provide a formal definition for the notion of an algorithm. The types of problems we shall consider are represented by the following examples. • The even problem: Given an n ∈ ℕ, determine whether or not n is even. • The 10-clique problem: Given finite graph, determine whether or not there exists a subgraph that is isomorphic to the 10-clique. • The satisfiability problem for first-order logic: Given a sentence of first-order logic, determine whether or not it is satisfiable. The first problem is quite easy. To determine whether a given number is even, we simply check whether the last digit of the number is 0, 2, 4, 6 or 8. The second problem is harder. If the given graph is large and does contain a 10-clique as a subgraph, then we may have to check many subsets of the graph before we find it. Time complexity gives precise meaning to the ostensibly subjective idea of one problem being “harder” than another. The third problem is the most difficult of the three problems.

Dual systems for all: Higher-order, role-based relational reasoning as a uniquely derived feature of human cognition

2019 ◽  
Vol 42 ◽  
Author(s):  
Daniel J. Povinelli ◽  
Gabrielle C. Glorioso ◽  
Shannon L. Kuznar ◽  
Mateja Pavlic
Keyword(s):  
Temporal Reasoning ◽  
Higher Order ◽  
Important Case ◽  
Human Cognition ◽  
Relational Reasoning ◽  
Dual Systems ◽  
First Order ◽  
Reasoning System ◽  
Role Based

Abstract Hoerl and McCormack demonstrate that although animals possess a sophisticated temporal updating system, there is no evidence that they also possess a temporal reasoning system. This important case study is directly related to the broader claim that although animals are manifestly capable of first-order (perceptually-based) relational reasoning, they lack the capacity for higher-order, role-based relational reasoning. We argue this distinction applies to all domains of cognition.

Stochasting modeling of planetary ring systems

1984 ◽  
Vol 75 ◽  
pp. 461-469 ◽  
Author(s):  
Robert W. Hart
Keyword(s):  
Maximum Entropy ◽  
Ring System ◽  
The Sun ◽  
Ultimate State ◽  
Interparticle Interactions ◽  
Ring Systems ◽  
First Order ◽  
Planetary Ring ◽  
Insight Into

ABSTRACTThis paper models maximum entropy configurations of idealized gravitational ring systems. Such configurations are of interest because systems generally evolve toward an ultimate state of maximum randomness. For simplicity, attention is confined to ultimate states for which interparticle interactions are no longer of first order importance. The planets, in their orbits about the sun, are one example of such a ring system. The extent to which the present approximation yields insight into ring systems such as Saturn's is explored briefly.

Morphological studies of linear (AB)n multiblock copolymers and their blends

1992 ◽  
Vol 50 (1) ◽  
pp. 384-385
Author(s):  
Richard J. Spontak ◽  
Steven D. Smith ◽  
Arman Ashraf
Keyword(s):  
Electron Microscopy ◽  
Microphase Separation ◽  
Multiblock Copolymers ◽  
First Order ◽  
Morphological Studies ◽  
Transmission Electron ◽  
First Order Phase Transition ◽  
Covalently Bonded ◽  
Total Molecular Weight ◽  
First Order Phase

Block copolymers are composed of sequences of dissimilar chemical moieties covalently bonded together. If the block lengths of each component are sufficiently long and the blocks are thermodynamically incompatible, these materials are capable of undergoing microphase separation, a weak first-order phase transition which results in the formation of an ordered microstructural network. Most efforts designed to elucidate the phase and configurational behavior in these copolymers have focused on the simple AB and ABA designs. Few studies have thus far targeted the perfectly-alternating multiblock (AB)n architecture. In this work, two series of neat (AB)n copolymers have been synthesized from styrene and isoprene monomers at a composition of 50 wt% polystyrene (PS). In Set I, the total molecular weight is held constant while the number of AB block pairs (n) is increased from one to four (which results in shorter blocks). Set II consists of materials in which the block lengths are held constant and n is varied again from one to four (which results in longer chains). Transmission electron microscopy (TEM) has been employed here to investigate the morphologies and phase behavior of these materials and their blends.

Exact First Order Finite Element Modeling for Eddy Current NDE

1991 ◽  
Vol 3 (1) ◽  
pp. 235-253 ◽  
Author(s):  
L. D. Philipp ◽  
Q. H. Nguyen ◽  
D. D. Derkacht ◽  
D. J. Lynch ◽  
A. Mahmood
Keyword(s):  
Finite Element ◽  
Finite Element Modeling ◽  
Eddy Current ◽  
Element Modeling ◽  
First Order ◽  
Eddy Current Nde

Challenging the Multidimensional Conception of Perceived Person-Environment Fit

2020 ◽  
pp. 1-9
Author(s):  
Julian M. Etzel ◽  
Gabriel Nagy
Keyword(s):  
Higher Education ◽  
University Students ◽  
Educational Outcomes ◽  
Factor Model ◽  
Higher Order ◽  
Substantial Proportion ◽  
Unique Variance ◽  
First Order ◽  
Person Environment Fit ◽  
Order Factor

Abstract. In the current study, we examined the viability of a multidimensional conception of perceived person-environment (P-E) fit in higher education. We introduce an optimized 12-item measure that distinguishes between four content dimensions of perceived P-E fit: interest-contents (I-C) fit, needs-supplies (N-S) fit, demands-abilities (D-A) fit, and values-culture (V-C) fit. The central aim of our study was to examine whether the relationships between different P-E fit dimensions and educational outcomes can be accounted for by a higher-order factor that captures the shared features of the four fit dimensions. Relying on a large sample of university students in Germany, we found that students distinguish between the proposed fit dimensions. The respective first-order factors shared a substantial proportion of variance and conformed to a higher-order factor model. Using a newly developed factor extension procedure, we found that the relationships between the first-order factors and most outcomes were not fully accounted for by the higher-order factor. Rather, with the exception of V-C fit, all specific P-E fit factors that represent the first-order factors’ unique variance showed reliable and theoretically plausible relationships with different outcomes. These findings support the viability of a multidimensional conceptualization of P-E fit and the validity of our adapted instrument.

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