scholarly journals Sound Model Generation using Most Frequent Model Search for Recognizing Animal Vocalization

Author(s):  
Youjung Ko ◽  
Yoonjoong Kim
2017 ◽  
Vol 1 (2) ◽  
pp. 200-210
Author(s):  
Rivdya Eliza ◽  
Fitri Aulia

The purpose of this research are: 1) to know the learning activity of learners mathematics which is taught by Search, Solve, Create, and Share (SSCS), and 2) model to know the ability of problem solving of mathematics learners who taught by SSCS learning model in the class XI MIA MAN 1 Muara Labuh academic year 2016/2017. This research belongs to a kind of quasi-experimental research with randomized control group only design. In this study design, a group of subjects taken from a particular population were randomly assigned into two groups, the experimental group and the control group. After analyzing the data, it is known that the learning activity of the students after applying the SSCS learning model has improved towards the better from the first meeting to the fifth meeting, ie 35%, 45%, 55%, 68%, 77%. Based on the hypothesis test obtained ttable = 1.645 and tcount = 2.598 so obtained (2.598> 1.645) at 95% confidence interval. Because tcount > ttable then hypothesis in this research accepted. Thus, students 'math-problem-solving skills taught by SSCS learning models are higher than the students' uneducated mathematical problem-solving skills with SSCS learning modelsKeywords: Problem solving abilities, search, solve, sreate and share (SSCS) learning models


2020 ◽  
Vol 96 (3s) ◽  
pp. 756-757
Author(s):  
Е.С. Шамин ◽  
Е.Л. Харченко

Данная работа посвящена описанию возможного алгоритма создания моделей резиста с постоянным порогом и расчета окон процесса на их основе. Приведенные изыскания реализованы в виде программного средства, использующего средства моделирования фотолитографии Mentor Graphics Calibre. This work is dedicated to the description of one of possible algorithms of constant threshold resist model generation used for photolithography process window calculation. This algorithm has been realized in the form of a program using Mentor Graphics Calibre modeling tools.


2020 ◽  
Vol 176 (3-4) ◽  
pp. 271-297
Author(s):  
Mario Alviano ◽  
Carmine Dodaro

Many efficient algorithms for the computation of optimum stable models in the context of Answer Set Programming (ASP) are based on unsatisfiable core analysis. Among them, algorithm OLL was the first introduced in the context of ASP, whereas algorithms ONE and PMRES were first introduced for solving the Maximum Satisfiability problem (MaxSAT) and later on adapted to ASP. In this paper, we present the porting to ASP of another state-of-the-art algorithm introduced for MaxSAT, namely K, which generalizes ONE and PMRES. Moreover, we present a new algorithm called OLL-IN-ONE that compactly encodes all aggregates of OLL by taking advantage of shared aggregate sets propagators. The performance of the algorithms have been empirically compared on instances taken from the latest ASP Competition.


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