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Calibrating Range Measurements of Lidars Using Fixed Landmarks in Unknown Positions
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We consider the problem of calibrating range measurements of a Light Detection and Ranging (lidar) sensor that is dealing with the sensor nonlinearity and heteroskedastic, range-dependent, measurement error. We solved the calibration problem without using additional hardware, but rather exploiting assumptions on the environment surrounding the sensor during the calibration procedure. More specifically we consider the assumption of calibrating the sensor by placing it in an environment so that its measurements lie in a 2D plane that is parallel to the ground. Then, its measurements come from fixed objects that develop orthogonally w.r.t. the ground, so that they may be considered as fixed points in an inertial reference frame. Moreover, we consider the intuition that moving the distance sensor within this environment implies that its measurements should be such that the relative distances and angles among the fixed points above remain the same. We thus exploit this intuition to cast the sensor calibration problem as making its measurements comply with this assumption that “fixed features shall have fixed relative distances and angles”. The resulting calibration procedure does thus not need to use additional (typically expensive) equipment, nor deploy special hardware. As for the proposed estimation strategies, from a mathematical perspective we consider models that lead to analytically solvable equations, so to enable deployment in embedded systems. Besides proposing the estimators we moreover analyze their statistical performance both in simulation and with field tests. We report the dependency of the MSE performance of the calibration procedure as a function of the sensor noise levels, and observe that in field tests the approach can lead to a tenfold improvement in the accuracy of the raw measurements.

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Al-nahrain University Science
Breaking Knapsack Cipher Using Population Based Incremental Learning
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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Automatic voice activity detection using fuzzy-neuro classifier
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Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto

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Publication Date
Fri Jan 01 2016
Journal Name
Bio-inspired Computing – Theories And Applications
Image Segmentation Using Membrane Computing: A Literature Survey
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Publication Date
Sun Nov 01 2020
Journal Name
Iraqi Journal Of Laser
Urinary Tract Lithotripsy Using Holmium: YAG (2100nm) Laser
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Background: Laser urinary stone lithotripsy is an established endourological modality. Ho:YAG(2100nm) laser have broadened  the indications for ureteroscopic stone managements  to include larger stone sizes throughout the whole urinary tract.

Purpose: To evaluate the effectiveness and safety of Holmium: YAG(2100nm) laser lithotripsy with a semirigid uretero scope for urinary stone calculi in a prospective cohort of 17 patients.

Patients and Methods: Holmium: YAG(2100nm) laser lithotripsy was performed with a semirigid ureteroscope in 17 patients from September 2016 to December  2016. Calculi were located in the lower ureter in 9 patients (52.9%), the midure

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Euro Dinar Trading Analysis Using WARIMA Hybrid Model
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The rise in the general level of prices in Iraq makes the local commodity less able to compete with other commodities, which leads to an increase in the amount of imports and a decrease in the amount of exports, since it raises demand for foreign currencies while decreasing demand for the local currency, which leads to a decrease in the exchange rate of the local currency in exchange for an increase in the exchange rate of currencies. This is one of the most important factors affecting the determination of the exchange rate and its fluctuations. This research deals with the currency of the European Euro and its impact against the Iraqi dinar. To make an accurate prediction for any process, modern methods can be used through which

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Publication Date
Thu Dec 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Hexapod Robot Static Stability Enhancement using Genetic Algorithm
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Abstract

Hexapod robot is a flexible mechanical robot with six legs. It has the ability to walk over terrain. The hexapod robot look likes the insect so it has the same gaits. These gaits are tripod, wave and ripple gaits. Hexapod robot needs to stay statically stable at all the times during each gait in order not to fall with three or more legs continuously contacts with the ground. The safety static stability walking is called (the stability margin). In this paper, the forward and inverse kinematics are derived for each hexapod’s leg in order to simulate the hexapod robot model walking using MATLAB R2010a for all gaits and the geometry in order to derive the equations of the sub-constraint workspaces for each

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Emergency Fuel Rationing system using RFID Smart Cards
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Rationing is a commonly used solution for shortages of resources and goods that are vital for the citizens of a country. This paper identifies some common approaches and policies used in rationing as well asrisks that associated to suggesta system for rationing fuelwhichcan work efficiently. Subsequently, addressing all possible security risks and their solutions. The system should theoretically be applicable in emergency situations, requiring less than three months to implement at a low cost and minimal changes to infrastructure.

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Arabic Sentiment Analysis (ASA) Using Deep Learning Approach
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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

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Publication Date
Mon Jan 09 2023
Journal Name
2023 15th International Conference On Developments In Esystems Engineering (dese)
Abstract Pattern Image Generation using Generative Adversarial Networks
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Publication Date
Wed Sep 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Application
Suggested methods for prediction using semiparametric regression function
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Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m

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