scholarly journals Freeway Control Via Ramp Metering: Development of a Basic Building Block for an On-Ramp, Discrete, Stochastic, Mesoscopic, Simulation Model within a Contextual Systems Approach

2000 ◽  
Author(s):  
Mohamed Alkadri
2020 ◽  
Author(s):  
Ibraheem Kateeb ◽  
Larry Burton ◽  
Naser El-Bathy ◽  
Michael Peluso

2016 ◽  
Vol 34 (3) ◽  
pp. 195
Author(s):  
Bambang S. Koentjoro ◽  
Imas S. Sitanggang ◽  
Abdul Karim Makarim

<p>The prediction of national soybean yield and production could be improved its accuracy by integrating a simulation model and Geographic Information Systems (GIS). The objective of this research was to integrate a simulation model with a GIS, to predict the potential yield and production of soybean in the soybean production centers of East Java. This study was conducted from December 2013 till May 2014. The approach used in this study was a systems approach using a simulation model as solution to the problem. The model is SUCROS.SIM (Simple Universal Crops Growth Simulator), which was written using Powersim software and Spreadsheet in order to be fully integrated with GIS. The initial phase of the integration process between SUCROS.SIM and GIS are as follows (a) model validation, using input data of soybean plant assimilate partitioning, (b) climatic data (solar radiation, maximum and minimum temperatures) collected from the climatological station (BMKG) Karangploso Malang and (c) observation data of soybean yields of two varieties (Wilis and Argomulyo) at Muneng Experiment Station. It was found that the coefficients of determination of simulation model of soybean yield potential (R2) range from 0.945-0.992 and RMSE (Root Mean Square Error) values range from 0.11 to 0.25 t/ha. The average of soybean yield potential and production in 2012 at soybean production centers of East Java were 1.94 t/ha and 293,459 ton, respectively. The conclusion is SUCROS.SIM valid to be integrated with GIS.</p>


Author(s):  
Akshata O. Kattimani

Abstract: A Voltage Controlled Divider (VCO) is a basic building block in most of the electronic systems. Phase-locked loop (PLL), tone synthesizers, Frequency Shift Keying (FSK), frequency synthesizers, etc make use of VCO’s to generate an oscillating frequency that can be decided with the help of components. Voltage Controlled Divider can be implemented for analog applications. The project proposes three types of VCO using Electric tool and LT Spice XVII tool. The three VCO’s that are implemented are CMOS Ring Oscillator, Colpitts Oscillator and Relaxation Oscillator. These circuits generate two oscillating frequencies that is decided by the circult components. Keywords: Voltage Controlled Divider (VCO), CMOS Ring Oscillator, Colpitts Oscillator, Relaxation Oscillator, oscillating frequency.


Author(s):  
David Weisburd ◽  
Chester Britt ◽  
David B. Wilson ◽  
Alese Wooditch

Author(s):  
M. Suhail Zubairy

It has always been a self-evident and obvious feature of any kind of communication that there should be an exchange of objects like photons or electrons between the sender and the receiver to convey any information. In this chapter a protocol is presented in which information is transmitted between a sender and receiver with no particles in the transmission channel. The basic building block of this counterfactual communication protocol, the Mach–Zehnder interferometer, is discussed. The concept of interaction-free measurement is also introduced.


2019 ◽  
Vol 31 (5) ◽  
pp. 998-1014 ◽  
Author(s):  
Heiko Hoffmann

It is still unknown how associative biological memories operate. Hopfield networks are popular models of associative memory, but they suffer from spurious memories and low efficiency. Here, we present a new model of an associative memory that overcomes these deficiencies. We call this model sparse associative memory (SAM) because it is based on sparse projections from neural patterns to pattern-specific neurons. These sparse projections have been shown to be sufficient to uniquely encode a neural pattern. Based on this principle, we investigate theoretically and in simulation our SAM model, which turns out to have high memory efficiency and a vanishingly small probability of spurious memories. This model may serve as a basic building block of brain functions involving associative memory.


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