Yousef Oleyaei-Motlagh | University of Pittsburgh (original) (raw)

Papers by Yousef Oleyaei-Motlagh

2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC), 2020

Recent advancements in machine learning and the availability of massive data sets now facilitate ... more Recent advancements in machine learning and the availability of massive data sets now facilitate the development of neural network models to predict aviation noise based on aircraft trajectories. In this paper, we use a long short-term memory recurrent neural network to predict aviation noise at a ground location near Washington National Airport. The model is developed using over 10 months of achieved radar data and noise readings. Beyond trajectory information, meta-data regarding the aircraft type and weather data is integrated into the model. While specific to a ground station and airport, the model is able to accurately predict aviation noise above 55 db with a mean absolute error of 2.3 dB.

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Academic, Mar 28, 2014

The main purpose of this study is to find out the causality relationships between the strategic ... more The main purpose of this study is to find out the causality relationships between the strategic management of technology (SMOT) objects in the selected Iranian high technology companies, based on the balanced scorecard (BSC) and fuzzy logic approaches. Evaluations of critical technological indicators in the selected high technology-based companies illustrated they have used different cognitive procedures in their strategic management of technology studies, which have previously been discussed throughout the SMOT literature. Technology strategy maps try to make convergences between the objects of SMOT using benefits of the technology balanced scorecard (TBSC) in the high technology environment. Technology strategy maps empower high technology companies in both technology and business areas, based on the four perspectives of proposed TBSC. The first step in our evaluations is based on-field studies questionnaires responded to by 150 personnel from different industries. The next step is based on the empirical collected data from 24 high technology companies; causal and effect relationship analysis between each of these objects was calculated and mapped using the fuzzy cognitive map (FCM). Obtained fuzzy cognitive strategy map (FCSM) simply explains the causality relationships between the objects of the SMOT, which were not well understood in the traditional technology strategy maps.

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Six Sigma is known as the best quality management system, which has been applied in different pl... more Six Sigma is known as the best quality management system, which has been applied in different
places with distinct tasks. Any implementation of Six Sigma project normally can succeed only
when human resource management is applied within the organization, properly. In this paper,
we illustrate the intense of relationships between the human resources management indices and
Six Sigma project implementation indices for some selected Iranian manufacturing firms. By
using the fuzzy cognitive maps (FCM), we are able to show the strength of relationships among
various indices. This study helps quality and human resource managers learn how to manage
the critical indices to achieve their determined goals and to increase Six Sigma project
performance throw human resource management perspective.

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Conference Presentations by Yousef Oleyaei-Motlagh

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مقالات فارسی by Yousef Oleyaei-Motlagh

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Documents by Yousef Oleyaei-Motlagh

Conf paper

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2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC), 2020

Recent advancements in machine learning and the availability of massive data sets now facilitate ... more Recent advancements in machine learning and the availability of massive data sets now facilitate the development of neural network models to predict aviation noise based on aircraft trajectories. In this paper, we use a long short-term memory recurrent neural network to predict aviation noise at a ground location near Washington National Airport. The model is developed using over 10 months of achieved radar data and noise readings. Beyond trajectory information, meta-data regarding the aircraft type and weather data is integrated into the model. While specific to a ground station and airport, the model is able to accurately predict aviation noise above 55 db with a mean absolute error of 2.3 dB.

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Academic, Mar 28, 2014

The main purpose of this study is to find out the causality relationships between the strategic ... more The main purpose of this study is to find out the causality relationships between the strategic management of technology (SMOT) objects in the selected Iranian high technology companies, based on the balanced scorecard (BSC) and fuzzy logic approaches. Evaluations of critical technological indicators in the selected high technology-based companies illustrated they have used different cognitive procedures in their strategic management of technology studies, which have previously been discussed throughout the SMOT literature. Technology strategy maps try to make convergences between the objects of SMOT using benefits of the technology balanced scorecard (TBSC) in the high technology environment. Technology strategy maps empower high technology companies in both technology and business areas, based on the four perspectives of proposed TBSC. The first step in our evaluations is based on-field studies questionnaires responded to by 150 personnel from different industries. The next step is based on the empirical collected data from 24 high technology companies; causal and effect relationship analysis between each of these objects was calculated and mapped using the fuzzy cognitive map (FCM). Obtained fuzzy cognitive strategy map (FCSM) simply explains the causality relationships between the objects of the SMOT, which were not well understood in the traditional technology strategy maps.

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Six Sigma is known as the best quality management system, which has been applied in different pl... more Six Sigma is known as the best quality management system, which has been applied in different
places with distinct tasks. Any implementation of Six Sigma project normally can succeed only
when human resource management is applied within the organization, properly. In this paper,
we illustrate the intense of relationships between the human resources management indices and
Six Sigma project implementation indices for some selected Iranian manufacturing firms. By
using the fuzzy cognitive maps (FCM), we are able to show the strength of relationships among
various indices. This study helps quality and human resource managers learn how to manage
the critical indices to achieve their determined goals and to increase Six Sigma project
performance throw human resource management perspective.

Bookmarks Related papers MentionsView impact