Farnaz Ganjeizadeh | California State University, East Bay (original) (raw)

Papers by Farnaz Ganjeizadeh

Procedia Manufacturing, 2017

For a sustainable Leagile Supply chain it is important to measure and optimize the leagility. Gov... more For a sustainable Leagile Supply chain it is important to measure and optimize the leagility. Governance of leagility sustenance needs the supply chain performance to be measured and optimized through a means termed by us as 'Leagility Index'. The paper details the modelling approach for calculating leagility index. The calculation is proposed using conjoint analysis. The sustenance model further optimizes the supply chain using Simulated Annealing (SA) using a practical process adoption scheme. The index acts as a guide for sustenance model of supply chain.

Procedia Manufacturing, 2017

For a sustainable Leagile Supply chain it is important to measure and optimize the leagility. Gov... more For a sustainable Leagile Supply chain it is important to measure and optimize the leagility. Governance of leagility sustenance needs the supply chain performance to be measured and optimized through a means termed by us as 'Leagility Index'. The paper details the modelling approach for calculating leagility index. The calculation is proposed using conjoint analysis. The sustenance model further optimizes the supply chain using Simulated Annealing (SA) using a practical process adoption scheme. The index acts as a guide for sustenance model of supply chain.

Robotics and Computer-Integrated Manufacturing

International journal of engineering research and technology, Mar 29, 2014

Speaker recognition approaches rely heavily on the use of Gaussian Mixture Models (GMMs) for spea... more Speaker recognition approaches rely heavily on the use of Gaussian Mixture Models (GMMs) for speaker modelling. The models can represent arbitrary distributions of feature vectors extracted from speech waveforms, and are easy to train. Traditional GMM-based implementations are computationally complex, utilizing large numbers of parameters. These approaches have typically been used in "offline" settings, where results are not generated in real-time. This work seeks to reduce the computational complexity of the GMM-UBM approach, allowing it to produce results in shorter amounts of time. The preliminary results of this study demonstrate the feasibility of reducing the number of parameters while maintaining speaker recognition performance. This work provides a foundation for further work in reducing computational complexity, which we intend to use for future real-time hardware implementations.

International journal of engineering research and technology, Jul 1, 2014

This work aims to visualize the variability of recorded human speech based on differences in spea... more This work aims to visualize the variability of recorded human speech based on differences in speaker ethnicity, gender, age and recording environment. Analysis of this mismatch can be done using Gaussian Mixture Models (GMMs), which have historically been used in the field of speaker recognition, trained on Mel-Frequency Cepstral Coefficient (MFCC) feature vectors extracted from the speech waveforms. Certain parameters in the GMM models are extracted and mapped to two dimensions via the Principal Component Analysis (PCA) technique. The twodimensional values are visualized and compared based on their ethnicity, age and gender. The database used consists of 42 speakers of different ethnicity, gender and age. The analysis showed that speaker voices recorded in the same noisy environment appear more closely on the two-dimensional plot, confirming that the noise level in every recording plays an important role which differentiates speakers.

International journal of engineering research and technology, Aug 30, 2014

Over the last decade, electric vehicles (EVs) have evolved rapidly due to their energy saving and... more Over the last decade, electric vehicles (EVs) have evolved rapidly due to their energy saving and environmentally friendly components. This has led to the improvement of EV batteries. One of the most useful batteries that has been significantly developed for the vehicle applicant is the lithiumion battery. Due to its high energy and power densities, long life cycle, and environmentally friendly components, many kinds of lithium-ion batteries have been developed. In this paper, two types of commercial lithium ion batteries are studied: LiFePO 4 (LFP), and LiMn 2 O 4 (LMO). The reliability of these two batteries was presented by using Weibull analysis. With Weibull distribution, Beta or shape parameter, and Eta or scale parameter were calculated and used to compare their characteristic lives.

Procedia Manufacturing, 2017

This work utilizes looks-like analysis and the Bass diffusion model to generate sales forecasts o... more This work utilizes looks-like analysis and the Bass diffusion model to generate sales forecasts of a responsive neurostimulation (RNS) system. Due to the lack of historical data, a combination of techniques is utilized to predict the device's demand. Lookslike analysis is used to analyse analogous devices and their sales patterns to select the device closest to the RNS system. Next, parameters for the Bass diffusion model are estimated, and potential baseline forecasts are developed using two methods. Results suggest that peak sales for the device will occur around years 2021-2024.

Robotics and Computer-integrated Manufacturing, Feb 1, 2017

Traditionally, software development processes have relied on the use of the "Waterfall" and "Vee"... more Traditionally, software development processes have relied on the use of the "Waterfall" and "Vee" models. Later, Agile methodologies were used to handle the challenges of managing complex projects during the development phase. Agile methodologies are a group of incremental and iterative methods that are more effective, and have been used in project management. Kanban and Scrum are two powerful Agile project management approaches in software development. The objective of Scrum and Kanban is achieved by optimizing the development process by identifying the tasks, managing time more effectively, and setting-up teams. A review of the literature reveals that there is a lack of statistical evidence to conclude which methodology is more effective in dealing with the traditional project management factors of budget handling, risk control, quality of the project, available resources, having clear project scope, and schedule handling. This research statistically compares the effectiveness of the Scrum and Kanban methods in terms of their effects on the project management factors for software development projects. Numerical analysis is performed based on survey responses from those with experience in the Scrum and Kanban methods. Results suggest that both Scrum and Kanban lead to the development of successful projects, and that the Kanban method can be better than the Scrum method in terms of managing project schedule.

The objective of the graduate program in Engineering Management at California State University Ea... more The objective of the graduate program in Engineering Management at California State University East Bay is to train professionals for leadership roles in engineering, manufacturing and service industries. This program will enable individuals with a degree in engineering, science or related fields working in manufacturing and service industries to advance their careers by preparing for management positions. Also, professionals in management positions will benefit from this curriculum by obtaining a formal education in engineering management. The San Francisco Bay Area is a prime location for offering such a degree because of the large concentration of high tech engineering, manufacturing and service industries. This paper details the development of the M.S. Degree program. We discuss the resource constraints that had to be overcome by developing a curriculum that pulls resources from various departments on campus. The designed curriculum allows us to offer the program without requesting additional faculty positions. Other considerations include issues such as specific needs of Bay Area professionals and class offerings. We utilize the strengths of the university to develop a balanced curriculum including courses from Engineering, Management, Finance, and Statistics. Special considerations are given to admission requirements, prerequisite structure, and course offerings such that we can create a large pool of qualified applicants for the program. Motivation California State University, East Bay (CSUEB) began an engineering program in 1997, starting with a single offering in Industrial Engineering at the undergraduate level. The original vision was to slowly grow the program to a sustainable critical mass by introducing other engineering disciplines and degree options over time. The need for the proposed graduate degree program was initially discussed in the Industrial Advisory Board (IAB) meeting of the CSU East Bay's Engineering Page 10.457.1

International journal of engineering research and technology, Oct 27, 2014

There are multiple uncertainties during Research and Development (R&D) phase of the projects such... more There are multiple uncertainties during Research and Development (R&D) phase of the projects such as technological and market uncertainties which are transform into project risks. Hence, the development of risk models is essential to assist the managers to make appropriate decisions during the initial stage of the project life cycle. Although, many approaches are developed for performing the risk analysis during the growth and maturity periods of the project, the methodology for risk evaluation during R&D phase needs further research. In this paper we describe a new approach for dealing with the impact of the risks of the technological projects during R &D phase. This approach is based on the analysis of Knowledge gaps i.e. the gap between what we should know in order to succeed in the project and what we really know in the following two phases: Phase 1-Risk identification and assessment; and Phase 2-Risk mitigation.

International journal of engineering research and technology, 2014

This work aims to visualize the variability of recorded human speech based on differences in spea... more This work aims to visualize the variability of recorded human speech based on differences in speaker ethnicity, gender, age and recording environment. Analysis of this mismatch can be done using Gaussian Mixture Models (GMMs), which have historically been used in the field of speaker recognition, trained on Mel-Frequency Cepstral Coefficient (MFCC) feature vectors extracted from the speech waveforms. Certain parameters in the GMM models are extracted and mapped to two dimensions via the Principal Component Analysis (PCA) technique. The twodimensional values are visualized and compared based on their ethnicity, age and gender. The database used consists of 42 speakers of different ethnicity, gender and age. The analysis showed that speaker voices recorded in the same noisy environment appear more closely on the two-dimensional plot, confirming that the noise level in every recording plays an important role which differentiates speakers.

Procedia Manufacturing, 2020

The black liquor is concentrated in a multiple evaporation system to achieve steam economy. The f... more The black liquor is concentrated in a multiple evaporation system to achieve steam economy. The focus of this paper is to solve complex mass and energy balance non-linear equations and to reduce them to a simple matrix form using MATLAB. A detailed analysis is done to observe parameters effects on the entire process and on steam consumption according to the increase in the number of effects of evaporation. Complexity of the process is solved using mathematical modelling and simulation with MATLAB and MINITAB using ANOVA Analysis. The process is repeated for three-effect, five-effect and seven-effect evaporator. The comparison is analysed to show the effectiveness of steam economy and to conclude if it is beneficial to increase the number of evaporators to have effective energy conservation. According to the mathematical analysis, the number of effects is important to achieve steam economy, whereas the number of effects has no impact on parameters.

The ability to automate the evaluation of resource requirements with a given set of strategies is... more The ability to automate the evaluation of resource requirements with a given set of strategies is extremely important in the deployment of a cost effective academic plan. Very limited optimization/simulation approaches have been reported and the optimization approaches are very restrictive. Even though the simulation models can analyze practical scenarios, simulation analysis must be done every time a decision is required. We propose a hybrid simulation-artificial intelligence approach that overcomes the practical limitations of the simulation approach. We describe this approach in the context of academic resource planning in the Engineering Department at CSUEB.

2005 Annual Conference Proceedings

The objective of the graduate program in Engineering Management at California State University Ea... more The objective of the graduate program in Engineering Management at California State University East Bay is to train professionals for leadership roles in engineering, manufacturing and service industries. This program will enable individuals with a degree in engineering, science or related fields working in manufacturing and service industries to advance their careers by preparing for management positions. Also, professionals in management positions will benefit from this curriculum by obtaining a formal education in engineering management. The San Francisco Bay Area is a prime location for offering such a degree because of the large concentration of high tech engineering, manufacturing and service industries. This paper details the development of the M.S. Degree program. We discuss the resource constraints that had to be overcome by developing a curriculum that pulls resources from various departments on campus. The designed curriculum allows us to offer the program without requesting additional faculty positions. Other considerations include issues such as specific needs of Bay Area professionals and class offerings. We utilize the strengths of the university to develop a balanced curriculum including courses from Engineering, Management, Finance, and Statistics. Special considerations are given to admission requirements, prerequisite structure, and course offerings such that we can create a large pool of qualified applicants for the program. Motivation California State University, East Bay (CSUEB) began an engineering program in 1997, starting with a single offering in Industrial Engineering at the undergraduate level. The original vision was to slowly grow the program to a sustainable critical mass by introducing other engineering disciplines and degree options over time. The need for the proposed graduate degree program was initially discussed in the Industrial Advisory Board (IAB) meeting of the CSU East Bay's Engineering Page 10.457.1

Procedia Manufacturing, 2017

This work utilizes looks-like analysis and the Bass diffusion model to generate sales forecasts o... more This work utilizes looks-like analysis and the Bass diffusion model to generate sales forecasts of a responsive neurostimulation (RNS) system. Due to the lack of historical data, a combination of techniques is utilized to predict the device's demand. Lookslike analysis is used to analyse analogous devices and their sales patterns to select the device closest to the RNS system. Next, parameters for the Bass diffusion model are estimated, and potential baseline forecasts are developed using two methods. Results suggest that peak sales for the device will occur around years 2021-2024.

2017 IEEE Global Engineering Education Conference (EDUCON), 2017

Because a freshman-level introductory engineering course is typically one of few courses used in ... more Because a freshman-level introductory engineering course is typically one of few courses used in fulfilling a broad set of technical and non-technical program learning outcomes (i.e. for ABET accreditation purposes), a significant challenge involved in designing and teaching such courses is to cover a broad array of topics in a way that is engaging and beneficial to students. We revamped the freshman-level introductory engineering course at CSU-East Bay to better suit this purpose, and in this work, we focused on obtaining a deeper understanding of student learning across a set of six technical and non-technical concepts. We evaluated the relationship between student performance on each concept with the students' final course performance, and found that students who perform well on the technical concepts generally have better final course performance. We also investigated how performance on each concept affects performance on other concepts. We found that there is significant co...

There are multiple uncertainties during Research and Development (R&D) phase of the projects such... more There are multiple uncertainties during Research and Development (R&D) phase of the projects such as technological and market uncertainties which are transform into project risks. Hence, the development of risk models is essential to assist the managers to make appropriate decisions during the initial stage of the project life cycle. Although, many approaches are developed for performing the risk analysis during the growth and maturity periods of the project, the methodology for risk evaluation during R&D phase needs further research. In this paper we describe a new approach for dealing with the impact of the risks of the technological projects during R &D phase. This approach is based on the analysis of Knowledge gaps i.e. the gap between what we should know in order to succeed in the project and what we really know in the following two phases: Phase 1-Risk identification and assessment; and Phase 2-Risk mitigation.

International journal of engineering research and technology, 2013

Speaker recognition approaches rely heavily on the use of Gaussian Mixture Models (GMMs) for spea... more Speaker recognition approaches rely heavily on the use of Gaussian Mixture Models (GMMs) for speaker modelling. The models can represent arbitrary distributions of feature vectors extracted from speech waveforms, and are easy to train. However, they make several simplifying assumptions on the distribution of the feature vectors, including Gaussianity and timeindependence, which are not accurate given the nature of speech. This work seeks to quantify the effects of these assumptions as they pertain to speaker recognition system performance. Experiments are performed using a traditional GMM-UBM system. Initial results suggest that the Gaussian distribution assumption can negatively impact performance, while further investigation is needed to make definitive conclusions.

Procedia Manufacturing, 2017

For a sustainable Leagile Supply chain it is important to measure and optimize the leagility. Gov... more For a sustainable Leagile Supply chain it is important to measure and optimize the leagility. Governance of leagility sustenance needs the supply chain performance to be measured and optimized through a means termed by us as 'Leagility Index'. The paper details the modelling approach for calculating leagility index. The calculation is proposed using conjoint analysis. The sustenance model further optimizes the supply chain using Simulated Annealing (SA) using a practical process adoption scheme. The index acts as a guide for sustenance model of supply chain.

Procedia Manufacturing, 2017

For a sustainable Leagile Supply chain it is important to measure and optimize the leagility. Gov... more For a sustainable Leagile Supply chain it is important to measure and optimize the leagility. Governance of leagility sustenance needs the supply chain performance to be measured and optimized through a means termed by us as 'Leagility Index'. The paper details the modelling approach for calculating leagility index. The calculation is proposed using conjoint analysis. The sustenance model further optimizes the supply chain using Simulated Annealing (SA) using a practical process adoption scheme. The index acts as a guide for sustenance model of supply chain.

Robotics and Computer-Integrated Manufacturing

International journal of engineering research and technology, Mar 29, 2014

Speaker recognition approaches rely heavily on the use of Gaussian Mixture Models (GMMs) for spea... more Speaker recognition approaches rely heavily on the use of Gaussian Mixture Models (GMMs) for speaker modelling. The models can represent arbitrary distributions of feature vectors extracted from speech waveforms, and are easy to train. Traditional GMM-based implementations are computationally complex, utilizing large numbers of parameters. These approaches have typically been used in "offline" settings, where results are not generated in real-time. This work seeks to reduce the computational complexity of the GMM-UBM approach, allowing it to produce results in shorter amounts of time. The preliminary results of this study demonstrate the feasibility of reducing the number of parameters while maintaining speaker recognition performance. This work provides a foundation for further work in reducing computational complexity, which we intend to use for future real-time hardware implementations.

International journal of engineering research and technology, Jul 1, 2014

This work aims to visualize the variability of recorded human speech based on differences in spea... more This work aims to visualize the variability of recorded human speech based on differences in speaker ethnicity, gender, age and recording environment. Analysis of this mismatch can be done using Gaussian Mixture Models (GMMs), which have historically been used in the field of speaker recognition, trained on Mel-Frequency Cepstral Coefficient (MFCC) feature vectors extracted from the speech waveforms. Certain parameters in the GMM models are extracted and mapped to two dimensions via the Principal Component Analysis (PCA) technique. The twodimensional values are visualized and compared based on their ethnicity, age and gender. The database used consists of 42 speakers of different ethnicity, gender and age. The analysis showed that speaker voices recorded in the same noisy environment appear more closely on the two-dimensional plot, confirming that the noise level in every recording plays an important role which differentiates speakers.

International journal of engineering research and technology, Aug 30, 2014

Over the last decade, electric vehicles (EVs) have evolved rapidly due to their energy saving and... more Over the last decade, electric vehicles (EVs) have evolved rapidly due to their energy saving and environmentally friendly components. This has led to the improvement of EV batteries. One of the most useful batteries that has been significantly developed for the vehicle applicant is the lithiumion battery. Due to its high energy and power densities, long life cycle, and environmentally friendly components, many kinds of lithium-ion batteries have been developed. In this paper, two types of commercial lithium ion batteries are studied: LiFePO 4 (LFP), and LiMn 2 O 4 (LMO). The reliability of these two batteries was presented by using Weibull analysis. With Weibull distribution, Beta or shape parameter, and Eta or scale parameter were calculated and used to compare their characteristic lives.

Procedia Manufacturing, 2017

This work utilizes looks-like analysis and the Bass diffusion model to generate sales forecasts o... more This work utilizes looks-like analysis and the Bass diffusion model to generate sales forecasts of a responsive neurostimulation (RNS) system. Due to the lack of historical data, a combination of techniques is utilized to predict the device's demand. Lookslike analysis is used to analyse analogous devices and their sales patterns to select the device closest to the RNS system. Next, parameters for the Bass diffusion model are estimated, and potential baseline forecasts are developed using two methods. Results suggest that peak sales for the device will occur around years 2021-2024.

Robotics and Computer-integrated Manufacturing, Feb 1, 2017

Traditionally, software development processes have relied on the use of the "Waterfall" and "Vee"... more Traditionally, software development processes have relied on the use of the "Waterfall" and "Vee" models. Later, Agile methodologies were used to handle the challenges of managing complex projects during the development phase. Agile methodologies are a group of incremental and iterative methods that are more effective, and have been used in project management. Kanban and Scrum are two powerful Agile project management approaches in software development. The objective of Scrum and Kanban is achieved by optimizing the development process by identifying the tasks, managing time more effectively, and setting-up teams. A review of the literature reveals that there is a lack of statistical evidence to conclude which methodology is more effective in dealing with the traditional project management factors of budget handling, risk control, quality of the project, available resources, having clear project scope, and schedule handling. This research statistically compares the effectiveness of the Scrum and Kanban methods in terms of their effects on the project management factors for software development projects. Numerical analysis is performed based on survey responses from those with experience in the Scrum and Kanban methods. Results suggest that both Scrum and Kanban lead to the development of successful projects, and that the Kanban method can be better than the Scrum method in terms of managing project schedule.

The objective of the graduate program in Engineering Management at California State University Ea... more The objective of the graduate program in Engineering Management at California State University East Bay is to train professionals for leadership roles in engineering, manufacturing and service industries. This program will enable individuals with a degree in engineering, science or related fields working in manufacturing and service industries to advance their careers by preparing for management positions. Also, professionals in management positions will benefit from this curriculum by obtaining a formal education in engineering management. The San Francisco Bay Area is a prime location for offering such a degree because of the large concentration of high tech engineering, manufacturing and service industries. This paper details the development of the M.S. Degree program. We discuss the resource constraints that had to be overcome by developing a curriculum that pulls resources from various departments on campus. The designed curriculum allows us to offer the program without requesting additional faculty positions. Other considerations include issues such as specific needs of Bay Area professionals and class offerings. We utilize the strengths of the university to develop a balanced curriculum including courses from Engineering, Management, Finance, and Statistics. Special considerations are given to admission requirements, prerequisite structure, and course offerings such that we can create a large pool of qualified applicants for the program. Motivation California State University, East Bay (CSUEB) began an engineering program in 1997, starting with a single offering in Industrial Engineering at the undergraduate level. The original vision was to slowly grow the program to a sustainable critical mass by introducing other engineering disciplines and degree options over time. The need for the proposed graduate degree program was initially discussed in the Industrial Advisory Board (IAB) meeting of the CSU East Bay's Engineering Page 10.457.1

International journal of engineering research and technology, Oct 27, 2014

There are multiple uncertainties during Research and Development (R&D) phase of the projects such... more There are multiple uncertainties during Research and Development (R&D) phase of the projects such as technological and market uncertainties which are transform into project risks. Hence, the development of risk models is essential to assist the managers to make appropriate decisions during the initial stage of the project life cycle. Although, many approaches are developed for performing the risk analysis during the growth and maturity periods of the project, the methodology for risk evaluation during R&D phase needs further research. In this paper we describe a new approach for dealing with the impact of the risks of the technological projects during R &D phase. This approach is based on the analysis of Knowledge gaps i.e. the gap between what we should know in order to succeed in the project and what we really know in the following two phases: Phase 1-Risk identification and assessment; and Phase 2-Risk mitigation.

International journal of engineering research and technology, 2014

This work aims to visualize the variability of recorded human speech based on differences in spea... more This work aims to visualize the variability of recorded human speech based on differences in speaker ethnicity, gender, age and recording environment. Analysis of this mismatch can be done using Gaussian Mixture Models (GMMs), which have historically been used in the field of speaker recognition, trained on Mel-Frequency Cepstral Coefficient (MFCC) feature vectors extracted from the speech waveforms. Certain parameters in the GMM models are extracted and mapped to two dimensions via the Principal Component Analysis (PCA) technique. The twodimensional values are visualized and compared based on their ethnicity, age and gender. The database used consists of 42 speakers of different ethnicity, gender and age. The analysis showed that speaker voices recorded in the same noisy environment appear more closely on the two-dimensional plot, confirming that the noise level in every recording plays an important role which differentiates speakers.

Procedia Manufacturing, 2020

The black liquor is concentrated in a multiple evaporation system to achieve steam economy. The f... more The black liquor is concentrated in a multiple evaporation system to achieve steam economy. The focus of this paper is to solve complex mass and energy balance non-linear equations and to reduce them to a simple matrix form using MATLAB. A detailed analysis is done to observe parameters effects on the entire process and on steam consumption according to the increase in the number of effects of evaporation. Complexity of the process is solved using mathematical modelling and simulation with MATLAB and MINITAB using ANOVA Analysis. The process is repeated for three-effect, five-effect and seven-effect evaporator. The comparison is analysed to show the effectiveness of steam economy and to conclude if it is beneficial to increase the number of evaporators to have effective energy conservation. According to the mathematical analysis, the number of effects is important to achieve steam economy, whereas the number of effects has no impact on parameters.

The ability to automate the evaluation of resource requirements with a given set of strategies is... more The ability to automate the evaluation of resource requirements with a given set of strategies is extremely important in the deployment of a cost effective academic plan. Very limited optimization/simulation approaches have been reported and the optimization approaches are very restrictive. Even though the simulation models can analyze practical scenarios, simulation analysis must be done every time a decision is required. We propose a hybrid simulation-artificial intelligence approach that overcomes the practical limitations of the simulation approach. We describe this approach in the context of academic resource planning in the Engineering Department at CSUEB.

2005 Annual Conference Proceedings

The objective of the graduate program in Engineering Management at California State University Ea... more The objective of the graduate program in Engineering Management at California State University East Bay is to train professionals for leadership roles in engineering, manufacturing and service industries. This program will enable individuals with a degree in engineering, science or related fields working in manufacturing and service industries to advance their careers by preparing for management positions. Also, professionals in management positions will benefit from this curriculum by obtaining a formal education in engineering management. The San Francisco Bay Area is a prime location for offering such a degree because of the large concentration of high tech engineering, manufacturing and service industries. This paper details the development of the M.S. Degree program. We discuss the resource constraints that had to be overcome by developing a curriculum that pulls resources from various departments on campus. The designed curriculum allows us to offer the program without requesting additional faculty positions. Other considerations include issues such as specific needs of Bay Area professionals and class offerings. We utilize the strengths of the university to develop a balanced curriculum including courses from Engineering, Management, Finance, and Statistics. Special considerations are given to admission requirements, prerequisite structure, and course offerings such that we can create a large pool of qualified applicants for the program. Motivation California State University, East Bay (CSUEB) began an engineering program in 1997, starting with a single offering in Industrial Engineering at the undergraduate level. The original vision was to slowly grow the program to a sustainable critical mass by introducing other engineering disciplines and degree options over time. The need for the proposed graduate degree program was initially discussed in the Industrial Advisory Board (IAB) meeting of the CSU East Bay's Engineering Page 10.457.1

Procedia Manufacturing, 2017

This work utilizes looks-like analysis and the Bass diffusion model to generate sales forecasts o... more This work utilizes looks-like analysis and the Bass diffusion model to generate sales forecasts of a responsive neurostimulation (RNS) system. Due to the lack of historical data, a combination of techniques is utilized to predict the device's demand. Lookslike analysis is used to analyse analogous devices and their sales patterns to select the device closest to the RNS system. Next, parameters for the Bass diffusion model are estimated, and potential baseline forecasts are developed using two methods. Results suggest that peak sales for the device will occur around years 2021-2024.

2017 IEEE Global Engineering Education Conference (EDUCON), 2017

Because a freshman-level introductory engineering course is typically one of few courses used in ... more Because a freshman-level introductory engineering course is typically one of few courses used in fulfilling a broad set of technical and non-technical program learning outcomes (i.e. for ABET accreditation purposes), a significant challenge involved in designing and teaching such courses is to cover a broad array of topics in a way that is engaging and beneficial to students. We revamped the freshman-level introductory engineering course at CSU-East Bay to better suit this purpose, and in this work, we focused on obtaining a deeper understanding of student learning across a set of six technical and non-technical concepts. We evaluated the relationship between student performance on each concept with the students' final course performance, and found that students who perform well on the technical concepts generally have better final course performance. We also investigated how performance on each concept affects performance on other concepts. We found that there is significant co...

There are multiple uncertainties during Research and Development (R&D) phase of the projects such... more There are multiple uncertainties during Research and Development (R&D) phase of the projects such as technological and market uncertainties which are transform into project risks. Hence, the development of risk models is essential to assist the managers to make appropriate decisions during the initial stage of the project life cycle. Although, many approaches are developed for performing the risk analysis during the growth and maturity periods of the project, the methodology for risk evaluation during R&D phase needs further research. In this paper we describe a new approach for dealing with the impact of the risks of the technological projects during R &D phase. This approach is based on the analysis of Knowledge gaps i.e. the gap between what we should know in order to succeed in the project and what we really know in the following two phases: Phase 1-Risk identification and assessment; and Phase 2-Risk mitigation.

International journal of engineering research and technology, 2013

Speaker recognition approaches rely heavily on the use of Gaussian Mixture Models (GMMs) for spea... more Speaker recognition approaches rely heavily on the use of Gaussian Mixture Models (GMMs) for speaker modelling. The models can represent arbitrary distributions of feature vectors extracted from speech waveforms, and are easy to train. However, they make several simplifying assumptions on the distribution of the feature vectors, including Gaussianity and timeindependence, which are not accurate given the nature of speech. This work seeks to quantify the effects of these assumptions as they pertain to speaker recognition system performance. Experiments are performed using a traditional GMM-UBM system. Initial results suggest that the Gaussian distribution assumption can negatively impact performance, while further investigation is needed to make definitive conclusions.