scholarly journals On the possibility of employing a surveillance radar station to solve the problems of locating points of aim (points of impact)

2016 ◽  
pp. 13-19
Author(s):  
A. B. Blyakhman ◽  
S. N. Matyugin ◽  
A. G. Prokhorov
Keyword(s):  
Mathematical Model ◽  
Data Analysis ◽  
Target Recognition ◽  
Trial Data ◽  
Full Scale ◽  
Radar Station

We consider the possibility of employing a surveillance radar station to recognise ballistic targets (projectiles) and locate points of aim. We present the results of full-scale live-fire trial data analysis and a method for implementing ballistic target (projectile) recognition by radar stations of the surveillance type. We developed a mathematical model, an algorithm for ballistic target recognition, as well as algorithms and software to locate the point of aim

Pengembangan Media Pembelajaran Interaktif Berbasis Android Untuk Pemahaman Konsep Trigonometri

2018 ◽  
Vol 2 (2) ◽  
pp. 72
Author(s):  
Eka Saraswati ◽  
Devi Novallyan
Keyword(s):  
Data Analysis ◽  
Quantitative Data ◽  
Qualitative Data ◽  
Qualitative Approach ◽  
Trial Data ◽  
Development Model ◽  
Development Research ◽  
Analysis Technique ◽  
Group Trial ◽  
Trigonometric Formula

Tujuan dari penelitian ini adalah mengembangkan media pembelajaran interaktif berbasis android untuk memudahkan pemahaman konsep trigonometri. Penelitian ini merupakan penelitian pengembangan dengan pendekatan kualitatif yang didukung data kuantitatif. Model Pengembangan yang digunakan yaitu ADDIE. Karya inovasi ini dibuat dengan macromediaflash 8. Subjek dalam penelitian ini terdiri dari 8 siswa pada ujicoba kelompok kecil dan 30 siswa pada ujicoba kelompok besar. Teknik pengumpulan data yang digunakan yaitu angket dan wawancara. Teknik analisis data kualitatif dengan menggunakan model Miles Huberman.Hasilpengembangan diperoleh sebuah media pembelajaran yang dapat membantu siswa untuk mempermudah mengingat rumus trigonometri. Kata kunci: Media pembelajaran, android, konsep trigonometri Abstract [The Development of Interactive Android Based Learning Media to Facilitate Understanding of Trigonometric Concepts]. The purpose of this research is to develop interactive android based learning media to facilitate understanding of trigonometric concepts. This research is a development research with qualitative approach supported by quantitative data. Development model used is ADDIE. The innovation work was made with Macromedia Flash 8. The subjects in this study consisted of 8 students on a small group trial and 30 students on a large group trial. Data collection techniques used questionnaires and interviews. Qualitative data analysis technique using Miles Huberman model. The results of the development obtained a learning media that can help students to simplify remembering the trigonometric formula. Keywords: Learning media, android, the concept of trigonometry

scholarly journals A Test of the Phase Model of Psychotherapy Change

2002 ◽  
Vol 47 (8) ◽  
pp. 759-766 ◽  
Author(s):  
Anthony S Joyce ◽  
John Ogrodniczuk ◽  
William E Piper ◽  
Mary McCallum
Keyword(s):  
Data Analysis ◽  
Change Process ◽  
Comparative Trial ◽  
Well Being ◽  
Trial Data ◽  
Phase Model ◽  
Subjective Well Being ◽  
Short Term

Objective: A comparative trial of 2 forms (interpretive and supportive) of short-term, time-limited individual (STI) therapy provided data that were used to test the propositions of the Howard and others phase model of psychotherapy change. Method: Patients completed the Integra Outpatient Tracking Assessment Form on 5 occasions during the 20-session treatments. The measure assesses 3 dimensions: subjective well-being, current symptoms, and current life dysfunction. Howard and others regard these as dimensions that represent successive phases in the therapy change process (that is, well-being improves first, followed by resolution of symptoms, and finally by change in long-standing life dysfunction). We conducted a test of their model, using their approach to data analysis. Results: The comparative trial data provided no support for the phase model. Conclusions: Possible explanations for the absence of confirmatory findings are considered.

scholarly journals Model of the dynamics of a wheeled vehicle for a complex of full-scale-mathematical modeling

2020 ◽  
Vol 1 (4) ◽  
pp. 46-60
Author(s):  
B.B. Kositsyn ◽  
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Model ◽  
Real Time ◽  
Block Diagram ◽  
Plane Motion ◽  
Full Scale ◽  
Practical Significance ◽  
Modes Of Operation ◽  
Wheeled Vehicle ◽  
Full Scale Tests

Introduction. The use of the method of full-scale-mathematical modeling in “real time” opens up wide opportunities associated with the analysis of the modes of operation of the “man – vehicle – environment” system, as well as the study of the loading of units and assemblies of vehicles. The existing research complexes of full-scale mathematical modeling are suitable for obtaining most of the indicators usually determined by full-scale tests. The difference lies in the ability to fully control the course of virtual testing, recording any parameters of the vehicle movement, taking into account the “human factor”, as well as complete safety of the experiment. Purpose of research. The purpose of this work is to create a mathematical model of the dynam-ics of a wheeled vehicle, suitable for use in such a complex of full-scale mathematical modeling and assessment of the load of transmission units in conditions close to real operation. Methodology and methods. The proposed model is based on the existing model of the dynamics of a wheeled vehicle developed at Bauman Moscow State Technical University. Within the framework of the model, the dynamics of a vehicle is described as a plane motion of a rigid body in a horizontal plane. The principle of possible displacements is applied to determine the normal reac-tions of the bearing surface. The interaction of the wheel with the ground in the plane of the support base is described using an approach based on the “friction ellipse” concept. To enable the driver and operator of the full-scale mathematical modeling complex to drive a virtual vehicle in “real time” mode, the mathematical model is supplemented with a control system that communicates between the control parameter set by the driver by pressing the accelerator and brake pedals and the control actions of the vehicle's transmission units, such as: an electric machine, an internal combustion en-gine, a hydrodynamic retarder and a brake system. The article presents a block diagram of the de-veloped control algorithm, as well as approbation of the system's operation in a complex of full-scale mathematical modeling. Results and scientific novelty. A mathematical model of the dynamics of a wheeled vehicle was developed. It opens up wide possibilities for studying the modes of operation of the “driver-vehicle-environment” system in “real time”, using a complex of full-scale mathematical modeling. Practical significance. A mathematical model of the dynamics of a wheeled vehicle was devel-oped. It is supplemented with an algorithm for the distribution of traction / braking torques between the transmission units, which provide a connection between the driver's pressing on the accelerator / brake pedal and the control parameters of each of the units.

Feature Selection for Kick Detection With Machine Learning Using Laboratory Data

2019 ◽  
Author(s):  
Suranga C. H. Geekiyanage ◽  
Adrian Ambrus ◽  
Dan Sui
Keyword(s):  
Machine Learning ◽  
Logistic Regression ◽  
Feature Selection ◽  
Data Analysis ◽  
Laboratory Data ◽  
Surface Flow ◽  
Full Scale ◽  
Rate Of Change ◽  
Laboratory Scale ◽  
Detection Methods

Abstract Conventional kick detection methods mainly include monitoring pit gains, surface flow data (flow in and flow out), surface and down-hole pressure variations, and outputs from physics-based models. Kick detection times depend on a driller’s individual ability to interpret these drilling measurements, symptoms and model predictions. Furthermore, testing a novel data-driven solution in a full-scale operation may induce non-productive time, safety risks and crew fatigue adding to false alarms that inevitably occur during testing. Therefore, the development of better, faster and less human intervention-dependent kick detection on a laboratory scale system is a valuable step before full-scale testing. We have generated a dataset containing seven typical drilling measurements and a sequence of gas kicks from experiments conducted in the laboratory scale. First, we employ data analysis tools following data pre-processing steps, data scaling, outlier detection, and natural feature selection. Next, we consider additional “engineered features” and apply different feature combinations to logistic regression with an ensemble method (boosting) for developing kick detection algorithms. In our data analysis, ‘Delta flow’ (difference between flow in and flow out of the well) and ‘Rate of change of delta flow’ designed features, combined with logistic regression and boosting, give promising results in detecting kicks. Finally, we propose an intelligent algorithm and alarm architecture for a complete kick alarm system, which draws from both data analysis and machine learning models developed in this work.

Correlation of Superpave G*/Sin δ with Rutting Test Results from Accelerated Loading Facility

1998 ◽  
Vol 1630 (1) ◽  
pp. 53-61 ◽  
Author(s):  
James A. Sherwood ◽  
Nathaniel L. Thomas ◽  
Xicheng Qi
Keyword(s):  
Data Analysis ◽  
Predictive Models ◽  
Laboratory Tests ◽  
Fatigue Cracking ◽  
Full Scale ◽  
Test Results ◽  
Testing Facility ◽  
Pavement Testing ◽  
Analysis System ◽  
Highway Research

In 1992, FHWA initiated a Superpave validation study by utilizing the Accelerated Loading Facility (ALF) at the Turner-Fairbank Highway Research Center in McLean, Virginia. The study focused on the validation of the concepts, tests, and predictive models underlying the Superpave binder specifications and mixture analysis system. Twelve full-scale pavement lanes with 48 test sites were constructed at the FHWA Pavement Testing Facility in 1993. Pavement testing with the ALF started in late spring of 1994. The results of accelerated full-scale pavement tests in conjunction with extensive laboratory tests will be used to validate the Superpave binder parameters for rutting and fatigue cracking. Presented in this paper are the results of rutting tests and some of the data analysis completed through June 1997.

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