This document provides abstracts summarizing 18 undergraduate research projects supported by CUNY Compact funds in Spring 2008. The projects covered a diverse range of topics across various departments including physics, biology, mathematics, engineering, architecture and chemistry. For each project, the abstract lists the student researcher, faculty mentor, department, and provides a brief 3 sentence summary of the project title, aims, methods, and results or conclusions.
TOP Most Read Articles in Informatics Engineeringieijjournal
Informatics is rapidly developing field. The study of informatics involves human-computer interaction and how an interface can be built to maximize user-efficiency. Due to the growth in IT, individuals and organizations increasingly process information digitally. This has led to the study of informatics to solve privacy, security, healthcare, education, poverty, and challenges in our environment. The Informatics Engineering, an International Journal (IEIJ) is a open access peer-reviewed
journal that publishes articles which contribute new results in all areas of Informatics. The goal of this journal is to bring together researchers and practitioners
from academia and industry to focus on the human use of computing fields such as communication, mathematics, multimedia, and human-computer interaction design and establishing new collaborations in these areas.
Dmitry Georgievich Luchinsky is a senior research scientist with over 30 years of experience in engineering and research. He has led over 20 research projects in various fields including optics, rocket motors, cryogenic flows, and more. He has published over 150 research articles. Currently he works as a senior research scientist applying physics modeling to problems in industry.
OM: Advanced Bio-Well Practical Hands on Training - Feb.5-6-7/2016Krishna Madappa
OM: As our global and concentrated Bio-Well community grows, so should our dedicated training.
Dr.K.Korotkov & Krishna see this as an essential educational module for creating a next generation of Bio-Well professional users.
As the software platforms continue to amplify the non-linearity and our understanding of our multi dimensional presence, we are here to ennoble a seamless interface to this evolutionary level of Human Development.
Ultimately our singular purpose is to assist all our Bio-Well users globally to be the stewards of the advanced science of Bio-Electrography and inspire a generation towards the "Sciences of Optimal Human Excellence".
A Comparative Study of Machine Learning Algorithms for EEG Signal Classificationsipij
In this paper, different machine learning algorithms such as Linear Discriminant Analysis, Support vector
machine (SVM), Multi-layer perceptron, Random forest, K-nearest neighbour, and Autoencoder with SVM
have been compared. This comparison was conducted to seek a robust method that would produce good
classification accuracy. To this end, a robust method of classifying raw Electroencephalography (EEG)
signals associated with imagined movement of the right hand and relaxation state, namely Autoencoder
with SVM has been proposed. The EEG dataset used in this research was created by the University of
Tubingen, Germany. The best classification accuracy achieved was 70.4% with SVM through feature
engineering. However, our prosed method of autoencoder in combination with SVM produced a similar
accuracy of 65% without using any feature engineering technique. This research shows that this system of
classification of motor movements can be used in a Brain-Computer Interface system (BCI) to mentally
control a robotic device or an exoskeleton.
A Comparative Study of Machine Learning Algorithms for EEG Signal Classificationsipij
In this paper, different machine learning algorithms such as Linear Discriminant Analysis, Support vector
machine (SVM), Multi-layer perceptron, Random forest, K-nearest neighbour, and Autoencoder with SVM
have been compared. This comparison was conducted to seek a robust method that would produce good
classification accuracy. To this end, a robust method of classifying raw Electroencephalography (EEG)
signals associated with imagined movement of the right hand and relaxation state, namely Autoencoder
with SVM has been proposed. The EEG dataset used in this research was created by the University of
Tubingen, Germany. The best classification accuracy achieved was 70.4% with SVM through feature
engineering. However, our prosed method of autoencoder in combination with SVM produced a similar
accuracy of 65% without using any feature engineering technique. This research shows that this system of
classification of motor movements can be used in a Brain-Computer Interface system (BCI) to mentally
control a robotic device or an exoskeleton.
A Comparative Study of Machine Learning Algorithms for EEG Signal Classificationsipij
In this paper, different machine learning algorithms such as Linear Discriminant Analysis, Support vector
machine (SVM), Multi-layer perceptron, Random forest, K-nearest neighbour, and Autoencoder with SVM
have been compared. This comparison was conducted to seek a robust method that would produce good
classification accuracy. To this end, a robust method of classifying raw Electroencephalography (EEG)
signals associated with imagined movement of the right hand and relaxation state, namely Autoencoder
with SVM has been proposed. The EEG dataset used in this research was created by the University of
Tubingen, Germany. The best classification accuracy achieved was 70.4% with SVM through feature
engineering. However, our prosed method of autoencoder in combination with SVM produced a similar
accuracy of 65% without using any feature engineering technique. This research shows that this system of
classification of motor movements can be used in a Brain-Computer Interface system (BCI) to mentally
control a robotic device or an exoskeleton.
A COMPARATIVE STUDY OF MACHINE LEARNING ALGORITHMS FOR EEG SIGNAL CLASSIFICATIONsipij
In this paper, different machine learning algorithms such as Linear Discriminant Analysis, Support vector
machine (SVM), Multi-layer perceptron, Random forest, K-nearest neighbour, and Autoencoder with SVM
have been compared. This comparison was conducted to seek a robust method that would produce good
classification accuracy. To this end, a robust method of classifying raw Electroencephalography (EEG)
signals associated with imagined movement of the right hand and relaxation state, namely Autoencoder
with SVM has been proposed. The EEG dataset used in this research was created by the University of
Tubingen, Germany. The best classification accuracy achieved was 70.4% with SVM through feature
engineering. However, our prosed method of autoencoder in combination with SVM produced a similar
accuracy of 65% without using any feature engineering technique. This research shows that this system of
classification of motor movements can be used in a Brain-Computer Interface system (BCI) to mentally
control a robotic device or an exoskeleton.
TOP Most Read Articles in Informatics Engineeringieijjournal
Informatics is rapidly developing field. The study of informatics involves human-computer interaction and how an interface can be built to maximize user-efficiency. Due to the growth in IT, individuals and organizations increasingly process information digitally. This has led to the study of informatics to solve privacy, security, healthcare, education, poverty, and challenges in our environment. The Informatics Engineering, an International Journal (IEIJ) is a open access peer-reviewed
journal that publishes articles which contribute new results in all areas of Informatics. The goal of this journal is to bring together researchers and practitioners
from academia and industry to focus on the human use of computing fields such as communication, mathematics, multimedia, and human-computer interaction design and establishing new collaborations in these areas.
Dmitry Georgievich Luchinsky is a senior research scientist with over 30 years of experience in engineering and research. He has led over 20 research projects in various fields including optics, rocket motors, cryogenic flows, and more. He has published over 150 research articles. Currently he works as a senior research scientist applying physics modeling to problems in industry.
OM: Advanced Bio-Well Practical Hands on Training - Feb.5-6-7/2016Krishna Madappa
OM: As our global and concentrated Bio-Well community grows, so should our dedicated training.
Dr.K.Korotkov & Krishna see this as an essential educational module for creating a next generation of Bio-Well professional users.
As the software platforms continue to amplify the non-linearity and our understanding of our multi dimensional presence, we are here to ennoble a seamless interface to this evolutionary level of Human Development.
Ultimately our singular purpose is to assist all our Bio-Well users globally to be the stewards of the advanced science of Bio-Electrography and inspire a generation towards the "Sciences of Optimal Human Excellence".
A Comparative Study of Machine Learning Algorithms for EEG Signal Classificationsipij
In this paper, different machine learning algorithms such as Linear Discriminant Analysis, Support vector
machine (SVM), Multi-layer perceptron, Random forest, K-nearest neighbour, and Autoencoder with SVM
have been compared. This comparison was conducted to seek a robust method that would produce good
classification accuracy. To this end, a robust method of classifying raw Electroencephalography (EEG)
signals associated with imagined movement of the right hand and relaxation state, namely Autoencoder
with SVM has been proposed. The EEG dataset used in this research was created by the University of
Tubingen, Germany. The best classification accuracy achieved was 70.4% with SVM through feature
engineering. However, our prosed method of autoencoder in combination with SVM produced a similar
accuracy of 65% without using any feature engineering technique. This research shows that this system of
classification of motor movements can be used in a Brain-Computer Interface system (BCI) to mentally
control a robotic device or an exoskeleton.
A Comparative Study of Machine Learning Algorithms for EEG Signal Classificationsipij
In this paper, different machine learning algorithms such as Linear Discriminant Analysis, Support vector
machine (SVM), Multi-layer perceptron, Random forest, K-nearest neighbour, and Autoencoder with SVM
have been compared. This comparison was conducted to seek a robust method that would produce good
classification accuracy. To this end, a robust method of classifying raw Electroencephalography (EEG)
signals associated with imagined movement of the right hand and relaxation state, namely Autoencoder
with SVM has been proposed. The EEG dataset used in this research was created by the University of
Tubingen, Germany. The best classification accuracy achieved was 70.4% with SVM through feature
engineering. However, our prosed method of autoencoder in combination with SVM produced a similar
accuracy of 65% without using any feature engineering technique. This research shows that this system of
classification of motor movements can be used in a Brain-Computer Interface system (BCI) to mentally
control a robotic device or an exoskeleton.
A Comparative Study of Machine Learning Algorithms for EEG Signal Classificationsipij
In this paper, different machine learning algorithms such as Linear Discriminant Analysis, Support vector
machine (SVM), Multi-layer perceptron, Random forest, K-nearest neighbour, and Autoencoder with SVM
have been compared. This comparison was conducted to seek a robust method that would produce good
classification accuracy. To this end, a robust method of classifying raw Electroencephalography (EEG)
signals associated with imagined movement of the right hand and relaxation state, namely Autoencoder
with SVM has been proposed. The EEG dataset used in this research was created by the University of
Tubingen, Germany. The best classification accuracy achieved was 70.4% with SVM through feature
engineering. However, our prosed method of autoencoder in combination with SVM produced a similar
accuracy of 65% without using any feature engineering technique. This research shows that this system of
classification of motor movements can be used in a Brain-Computer Interface system (BCI) to mentally
control a robotic device or an exoskeleton.
A COMPARATIVE STUDY OF MACHINE LEARNING ALGORITHMS FOR EEG SIGNAL CLASSIFICATIONsipij
In this paper, different machine learning algorithms such as Linear Discriminant Analysis, Support vector
machine (SVM), Multi-layer perceptron, Random forest, K-nearest neighbour, and Autoencoder with SVM
have been compared. This comparison was conducted to seek a robust method that would produce good
classification accuracy. To this end, a robust method of classifying raw Electroencephalography (EEG)
signals associated with imagined movement of the right hand and relaxation state, namely Autoencoder
with SVM has been proposed. The EEG dataset used in this research was created by the University of
Tubingen, Germany. The best classification accuracy achieved was 70.4% with SVM through feature
engineering. However, our prosed method of autoencoder in combination with SVM produced a similar
accuracy of 65% without using any feature engineering technique. This research shows that this system of
classification of motor movements can be used in a Brain-Computer Interface system (BCI) to mentally
control a robotic device or an exoskeleton.
This document provides acknowledgements and contents for an undergraduate project report on developing an EEG-based brain-computer interface (BCI) using motor imagery signals. It thanks various individuals and departments for their guidance and support throughout the project. The project aims to classify left and right hand movements from EEG data to lay the foundation for communicating with patients who have lost motor function. It reviews the history of EEG-based BCIs and techniques like common spatial patterns (CSP) and linear discriminant analysis (LDA) that are implemented in the methods and results sections to classify the motor imagery signals.
CLASSIFICATION OF ELECTROENCEPHALOGRAM SIGNALS USING XGBOOST ALGORITHM AND SU...IRJET Journal
This document presents a study that uses the XGBoost algorithm and support vector machine to classify electroencephalogram (EEG) signals. The study acquires EEG data from healthy subjects and subjects with epilepsy during seizure and non-seizure periods. It preprocesses the data, extracts features using linear discriminant analysis, and feeds the extracted features into XGBoost and SVM classifiers. The results indicate that XGBoost exhibited superior classification performance compared to SVM for analyzing and classifying EEG signals.
Thomas Charles Ferree has over 25 years of experience in signal processing, algorithm development, and neuroscience research. He has a PhD in Physics from the University of Colorado and has held positions at several universities and research institutions. His research has focused on developing algorithms and models for analyzing EEG, EIT, and other biological signal data to study visual attention, stroke detection, and the neurological effects of various stimuli. He has extensive experience developing software and analyzing data across various computing platforms.
International Journal of Biometrics and Bioinformatics(IJBB) Volume (3) Issue...CSCJournals
This paper proposes a novel approach for measuring electrical impedance tomography (EIT) of local living tissue using an artificial intelligence algorithm. EIT is a non-invasive medical imaging technique that measures impedance distribution in tissue. The paper addresses challenges in estimating inner tissue impedance values and improving electrode structure. It introduces a "divided electrode" arrangement and equivalent circuit model to model local tissue impedance. An artificial intelligence algorithm called Alopex is used initially for parameter estimation, followed by the Newton method for higher accuracy, overcoming limitations of each approach individually. This novel hybrid model improves spatial resolution and accuracy of estimating tissue impedance values.
This paper reviews recent developments in the design of microfluidic concentration gradient generators for biological applications. It discusses how gradient generator designs leverage mass transport principles like diffusion and convection to control gradients. The review provides guidance on design considerations for different biological assays and summarizes factors to account for when using gradient generators. It also outlines perspectives on future improvements to gradient generator technology.
0 eeg based 3 d visual fatigue evaluation using cnnHoopeer Hoopeer
This document describes a new multi-scale convolutional neural network (CNN) called MorletInceptionNet that is designed to detect visual fatigue levels using electroencephalogram (EEG) signals as input. The network uses Morlet wavelet-like kernels to extract time-frequency features from the EEG data. It then uses inception modules of different kernel sizes to extract multi-scale temporal features, which are concatenated and fed into fully connected layers for classification. An evaluation of the network on EEG data collected during a visual fatigue experiment showed it achieved better classification accuracy and kappa values than five state-of-the-art methods, demonstrating it is effective at automatically evaluating visual fatigue levels from EEG signals.
This document is a resume for Dr. Arulmurugan Ambikapathi that summarizes his expertise and achievements. It lists his educational background, including a Ph.D. and positions held at various academic and research institutions. It also outlines his research focus on image processing, analysis, and applications in computer vision, deep learning, and automated optical inspection. Major projects and awards are mentioned, demonstrating his leadership and accomplishments in industrial research and academic publications.
The document summarizes research conducted by Joerg Lahann's lab to develop a targeted drug delivery system using multifunctional nanoparticles. The lab is fabricating nanoparticles through a process called electrohydrodynamic co-jetting that allows creation of particles with specific properties. Characterization equipment like SEM and Nanosight are used to analyze the nanoparticles and ensure they are safe and effectively target tumor sites before animal testing. Future work includes further testing the particles' ability to pass the blood-brain barrier and preferentially bind to certain tissues.
Classification of electroencephalography using cooperative learning based on...IJECEIAES
Modern technologies are widely used today to diagnose epilepsy, neurological disorders, and brain tumors. Meanwhile, it is not cost-effective in terms of time and money to use a large amount of electroencephalography (EEG) data from different centers and collect them in a central server for processing and analysis. Collecting this data correctly is challenging, and organizations avoid sharing their and client information with others due to data privacy protection. It is difficult to collect these data correctly and it is challenging to transfer them to research centers due to the privacy of the data. In this regard, collaborative learning as an extraordinary approach in this field paves the way for the use of information repositories in research matters without transferring the original data to the centers. This study focuses on the use of a heterogeneous client balancing technique with an interval selection approach and classification of EEG signals with ResNet50 deep architecture. The test results achieved an accuracy of 99.14 compared to similar methods.
The document summarizes research on neural engineering related to cochlear implants and intracortical microelectrodes. It discusses:
1) Cochlear implant research involving developing a method to fit implants using stapedius electromyography recordings in rats.
2) Chronic neural interfacing research using intracortical microelectrodes to record brain activity, the challenges of long-term recordings due to tissue encapsulation, and methods explored to address this like enzyme-aided electrode insertion.
3) The quantification of recording performance over time and correlations with electrode impedance.
DEEP FACIAL DIAGNOSIS: DEEP TRANSFER LEARNING FROM FACE RECOGNITION TO FACIAL...IRJET Journal
This document discusses using deep learning techniques like transfer learning and convolutional neural networks (CNNs) to perform computer-aided facial diagnosis of diseases from photographs. Specifically, it explores diagnosing single diseases like beta-thalassemia and multiple diseases including beta-thalassemia, hyperthyroidism, Down syndrome, and leprosy. The researchers achieve over 90% accuracy on these facial diagnosis tasks using deep transfer learning from pre-trained face recognition models, outperforming traditional machine learning methods. This shows promise for non-invasive disease screening using facial analysis with deep learning.
This document summarizes a study that demonstrates the use of equally-sloped tomography (EST) to improve electron tomography reconstruction. EST acquires projection images at constant slope increments, allowing the use of a pseudo-polar fast Fourier transform to directly relate the projection and volume grids. The study applied EST to reconstruct frozen keyhole limpet hemocyanin molecules and a bacterial cell from tilt-series data. EST reconstructions exhibited higher contrast, less noise, clearer boundaries, and reduced missing wedge effects compared to other reconstruction methods. Surprisingly, EST reconstructions using only two-thirds of the original projections appeared to have the same resolution as full reconstructions using other methods, suggesting EST can reduce radiation dose requirements or allow higher resolutions.
This document describes an experiment to test the transmission of "informational copies" (ICs) of chemical substances via communication lines. Participants will download ICs of substances like aspirin and glucophage from a technical center and measure the effects on water samples using high-precision pH and conductivity meters. The results will be presented at the Water Conference and broadcast online. Previous studies have found effects of ICs on blood coagulation and glucose levels in diabetic patients. The experiment aims to provide additional evidence for the work of scientist Jacques Benveniste on digital transmission of substance information.
NASA's NCSU-NSCORT Report and Personnel List La Shun L. CarrollLa Carroll
This document describes a research program involving 12 principal investigators from various institutions studying plant gravitational biology. The goal is to study calcium signaling's central role in plants' gravity response using molecular, cellular, and physiological approaches. The research utilizes transgenic plants, calcium imaging, and studies gravity-responsive plant tissues and proteins. The program involves graduate education, outreach to teachers and students, and research on characterizing plants' molecular genetic and biochemical gravity response mechanisms. It is funded through 2000 and has involved various research, publications, and presentations by the investigators.
This document summarizes the skills and experience of Yanjun Chen, including 6 years of experience in optical, electrical, and mechanical subsystem design, system integration, and image processing. Chen has a M.S. in Bioengineering from UIC and B.S. in Optoelectronic Information Engineering from Harbin Institute of Technology. Areas of expertise include optical coherence tomography, adaptive optics, and ultra-precision motion control.
A survey on bio-signal analysis for human-robot interactionIJECEIAES
The use of bio-signals analysis in human-robot interaction is rapidly increasing. There is an urgent demand for it in various applications, including health care, rehabilitation, research, technology, and manufacturing. Despite several state-of-the-art bio-signals analyses in human-robot interaction (HRI) research, it is unclear which one is the best. In this paper, the following topics will be discussed: robotic systems should be given priority in the rehabilitation and aid of amputees and disabled people; second, domains of feature extraction approaches now in use, which are divided into three main sections (time, frequency, and time-frequency). The various domains will be discussed, then a discussion of each domain's benefits and drawbacks, and finally, a recommendation for a new strategy for robotic systems.
Top Cited Article in Informatics Engineering Research: October 2020ieijjournal
Informatics is rapidly developing field. The study of informatics involves human-computer interaction and how an interface can be built to maximize user-efficiency. Due to the growth in IT, individuals and organizations increasingly process information digitally. This has led to the study of informatics to solve privacy, security, healthcare, education, poverty, and challenges in our environment. The Informatics Engineering, an International Journal (IEIJ) is a open access peer-reviewed journal that publishes articles which contribute new results in all areas of Informatics. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on the human use of computing fields such as communication, mathematics, multimedia, and human-computer interaction design and establishing new collaborations in these areas.
This document is a resume for Gaurav Gandhi, a Biomedical Engineer with over 3 years of experience in research and development. He has a Master's degree in Biomedical Engineering from Drexel University and is currently working on developing medical devices at Artann Labs, including an ultrasonometer for skeletal assessment and a method for enhancing brain drug delivery using acoustic techniques. He is proficient in various engineering and programming skills and seeks opportunities in the medical device industry.
How To Write Law Essays Exams By S.I. Strong (EnglClaire Webber
The document provides instructions for creating an account and submitting assignment requests on the HelpWriting.net website. It outlines a 5-step process: 1) Create an account with a password and email, 2) Complete an order form with instructions and deadline, 3) Review bids from writers and choose one, 4) Receive the paper and authorize payment if satisfied, 5) Request revisions until fully satisfied and receive a refund if plagiarized.
Give You Wedding A Hint Of Luxury. When You Plan, UsClaire Webber
The document discusses the importance of intelligence fusion centers in sharing information between federal, state, and local law enforcement agencies. It notes that if the FBI had informed local law enforcement about the previous arrest of the Orlando nightclub shooter for domestic violence with his ex-girlfriend, and his link to terror groups, it could have helped prevent the deadly shooting. Fusion centers are presented as important for facilitating communication across different levels of law enforcement.
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This document provides acknowledgements and contents for an undergraduate project report on developing an EEG-based brain-computer interface (BCI) using motor imagery signals. It thanks various individuals and departments for their guidance and support throughout the project. The project aims to classify left and right hand movements from EEG data to lay the foundation for communicating with patients who have lost motor function. It reviews the history of EEG-based BCIs and techniques like common spatial patterns (CSP) and linear discriminant analysis (LDA) that are implemented in the methods and results sections to classify the motor imagery signals.
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This document presents a study that uses the XGBoost algorithm and support vector machine to classify electroencephalogram (EEG) signals. The study acquires EEG data from healthy subjects and subjects with epilepsy during seizure and non-seizure periods. It preprocesses the data, extracts features using linear discriminant analysis, and feeds the extracted features into XGBoost and SVM classifiers. The results indicate that XGBoost exhibited superior classification performance compared to SVM for analyzing and classifying EEG signals.
Thomas Charles Ferree has over 25 years of experience in signal processing, algorithm development, and neuroscience research. He has a PhD in Physics from the University of Colorado and has held positions at several universities and research institutions. His research has focused on developing algorithms and models for analyzing EEG, EIT, and other biological signal data to study visual attention, stroke detection, and the neurological effects of various stimuli. He has extensive experience developing software and analyzing data across various computing platforms.
International Journal of Biometrics and Bioinformatics(IJBB) Volume (3) Issue...CSCJournals
This paper proposes a novel approach for measuring electrical impedance tomography (EIT) of local living tissue using an artificial intelligence algorithm. EIT is a non-invasive medical imaging technique that measures impedance distribution in tissue. The paper addresses challenges in estimating inner tissue impedance values and improving electrode structure. It introduces a "divided electrode" arrangement and equivalent circuit model to model local tissue impedance. An artificial intelligence algorithm called Alopex is used initially for parameter estimation, followed by the Newton method for higher accuracy, overcoming limitations of each approach individually. This novel hybrid model improves spatial resolution and accuracy of estimating tissue impedance values.
This paper reviews recent developments in the design of microfluidic concentration gradient generators for biological applications. It discusses how gradient generator designs leverage mass transport principles like diffusion and convection to control gradients. The review provides guidance on design considerations for different biological assays and summarizes factors to account for when using gradient generators. It also outlines perspectives on future improvements to gradient generator technology.
0 eeg based 3 d visual fatigue evaluation using cnnHoopeer Hoopeer
This document describes a new multi-scale convolutional neural network (CNN) called MorletInceptionNet that is designed to detect visual fatigue levels using electroencephalogram (EEG) signals as input. The network uses Morlet wavelet-like kernels to extract time-frequency features from the EEG data. It then uses inception modules of different kernel sizes to extract multi-scale temporal features, which are concatenated and fed into fully connected layers for classification. An evaluation of the network on EEG data collected during a visual fatigue experiment showed it achieved better classification accuracy and kappa values than five state-of-the-art methods, demonstrating it is effective at automatically evaluating visual fatigue levels from EEG signals.
This document is a resume for Dr. Arulmurugan Ambikapathi that summarizes his expertise and achievements. It lists his educational background, including a Ph.D. and positions held at various academic and research institutions. It also outlines his research focus on image processing, analysis, and applications in computer vision, deep learning, and automated optical inspection. Major projects and awards are mentioned, demonstrating his leadership and accomplishments in industrial research and academic publications.
The document summarizes research conducted by Joerg Lahann's lab to develop a targeted drug delivery system using multifunctional nanoparticles. The lab is fabricating nanoparticles through a process called electrohydrodynamic co-jetting that allows creation of particles with specific properties. Characterization equipment like SEM and Nanosight are used to analyze the nanoparticles and ensure they are safe and effectively target tumor sites before animal testing. Future work includes further testing the particles' ability to pass the blood-brain barrier and preferentially bind to certain tissues.
Classification of electroencephalography using cooperative learning based on...IJECEIAES
Modern technologies are widely used today to diagnose epilepsy, neurological disorders, and brain tumors. Meanwhile, it is not cost-effective in terms of time and money to use a large amount of electroencephalography (EEG) data from different centers and collect them in a central server for processing and analysis. Collecting this data correctly is challenging, and organizations avoid sharing their and client information with others due to data privacy protection. It is difficult to collect these data correctly and it is challenging to transfer them to research centers due to the privacy of the data. In this regard, collaborative learning as an extraordinary approach in this field paves the way for the use of information repositories in research matters without transferring the original data to the centers. This study focuses on the use of a heterogeneous client balancing technique with an interval selection approach and classification of EEG signals with ResNet50 deep architecture. The test results achieved an accuracy of 99.14 compared to similar methods.
The document summarizes research on neural engineering related to cochlear implants and intracortical microelectrodes. It discusses:
1) Cochlear implant research involving developing a method to fit implants using stapedius electromyography recordings in rats.
2) Chronic neural interfacing research using intracortical microelectrodes to record brain activity, the challenges of long-term recordings due to tissue encapsulation, and methods explored to address this like enzyme-aided electrode insertion.
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This document discusses using deep learning techniques like transfer learning and convolutional neural networks (CNNs) to perform computer-aided facial diagnosis of diseases from photographs. Specifically, it explores diagnosing single diseases like beta-thalassemia and multiple diseases including beta-thalassemia, hyperthyroidism, Down syndrome, and leprosy. The researchers achieve over 90% accuracy on these facial diagnosis tasks using deep transfer learning from pre-trained face recognition models, outperforming traditional machine learning methods. This shows promise for non-invasive disease screening using facial analysis with deep learning.
This document summarizes a study that demonstrates the use of equally-sloped tomography (EST) to improve electron tomography reconstruction. EST acquires projection images at constant slope increments, allowing the use of a pseudo-polar fast Fourier transform to directly relate the projection and volume grids. The study applied EST to reconstruct frozen keyhole limpet hemocyanin molecules and a bacterial cell from tilt-series data. EST reconstructions exhibited higher contrast, less noise, clearer boundaries, and reduced missing wedge effects compared to other reconstruction methods. Surprisingly, EST reconstructions using only two-thirds of the original projections appeared to have the same resolution as full reconstructions using other methods, suggesting EST can reduce radiation dose requirements or allow higher resolutions.
This document describes an experiment to test the transmission of "informational copies" (ICs) of chemical substances via communication lines. Participants will download ICs of substances like aspirin and glucophage from a technical center and measure the effects on water samples using high-precision pH and conductivity meters. The results will be presented at the Water Conference and broadcast online. Previous studies have found effects of ICs on blood coagulation and glucose levels in diabetic patients. The experiment aims to provide additional evidence for the work of scientist Jacques Benveniste on digital transmission of substance information.
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This document describes a research program involving 12 principal investigators from various institutions studying plant gravitational biology. The goal is to study calcium signaling's central role in plants' gravity response using molecular, cellular, and physiological approaches. The research utilizes transgenic plants, calcium imaging, and studies gravity-responsive plant tissues and proteins. The program involves graduate education, outreach to teachers and students, and research on characterizing plants' molecular genetic and biochemical gravity response mechanisms. It is funded through 2000 and has involved various research, publications, and presentations by the investigators.
This document summarizes the skills and experience of Yanjun Chen, including 6 years of experience in optical, electrical, and mechanical subsystem design, system integration, and image processing. Chen has a M.S. in Bioengineering from UIC and B.S. in Optoelectronic Information Engineering from Harbin Institute of Technology. Areas of expertise include optical coherence tomography, adaptive optics, and ultra-precision motion control.
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The use of bio-signals analysis in human-robot interaction is rapidly increasing. There is an urgent demand for it in various applications, including health care, rehabilitation, research, technology, and manufacturing. Despite several state-of-the-art bio-signals analyses in human-robot interaction (HRI) research, it is unclear which one is the best. In this paper, the following topics will be discussed: robotic systems should be given priority in the rehabilitation and aid of amputees and disabled people; second, domains of feature extraction approaches now in use, which are divided into three main sections (time, frequency, and time-frequency). The various domains will be discussed, then a discussion of each domain's benefits and drawbacks, and finally, a recommendation for a new strategy for robotic systems.
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Informatics is rapidly developing field. The study of informatics involves human-computer interaction and how an interface can be built to maximize user-efficiency. Due to the growth in IT, individuals and organizations increasingly process information digitally. This has led to the study of informatics to solve privacy, security, healthcare, education, poverty, and challenges in our environment. The Informatics Engineering, an International Journal (IEIJ) is a open access peer-reviewed journal that publishes articles which contribute new results in all areas of Informatics. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on the human use of computing fields such as communication, mathematics, multimedia, and human-computer interaction design and establishing new collaborations in these areas.
This document is a resume for Gaurav Gandhi, a Biomedical Engineer with over 3 years of experience in research and development. He has a Master's degree in Biomedical Engineering from Drexel University and is currently working on developing medical devices at Artann Labs, including an ultrasonometer for skeletal assessment and a method for enhancing brain drug delivery using acoustic techniques. He is proficient in various engineering and programming skills and seeks opportunities in the medical device industry.
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The document discusses the importance of intelligence fusion centers in sharing information between federal, state, and local law enforcement agencies. It notes that if the FBI had informed local law enforcement about the previous arrest of the Orlando nightclub shooter for domestic violence with his ex-girlfriend, and his link to terror groups, it could have helped prevent the deadly shooting. Fusion centers are presented as important for facilitating communication across different levels of law enforcement.
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Carcinoembryonic antigen (CEA) is a classic tumor marker that has been used in clinical studies of colon cancer. CEA is one of several markers such as CA242, CA199, CA72-4 that can indicate the presence of colon cancer. While some newer markers like TGF also show promise as colon cancer markers, CEA remains an important biomarker that is routinely measured to detect and monitor colon cancer.
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The document discusses how to develop effective study skills for distance learning, including becoming an independent learner through self-assessment questionnaires and identifying learning styles. It outlines learning outcomes around locating relevant information, time management, and reflection. The document emphasizes gaining an understanding of distance learning skills to aid academic progress and achieving good grades in an engineering management degree program.
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The document discusses the pros and cons of lobbying. It begins by defining lobbying as attempting to influence government officials' decisions, especially legislators. It notes that lobbying is done by individuals, corporations, advocacy groups, and other interested parties. While lobbying allows for representation of various constituencies, it can also be dominated by powerful corporate interests that seek to influence policy for their own benefit rather than the public good. When special interests have outsized influence, it can undermine democracy by diminishing the impact of voters' choices. The document suggests lobbying has led to fundamental changes in the US that are detrimental to democracy.
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This presentation was provided by Rebecca Benner, Ph.D., of the American Society of Anesthesiologists, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
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Abstracts Of The Emerging Scholars Program Research Projects Fall 2010 Supported By CUNY Compact Funds
1. Abstracts of the Emerging Scholars Program Research Projects
Supported by CUNY Compact funds
Spring 2008
Student Name Faculty Mentor Department Project Title
Igor Ashurov Oleg Berman
Ian Rubenstein Reginald Blake
Kurt Sealey Reginald Blake
Giuseppe Macaluso Daniel Capruso
Feng Yan Tang Daniel Capruso
Michael Dulski Daniel Capruso
Tamara Shand Sanjoy Chakraborty
Taznia Sultana Sanjoy Chakraborty
Tomar Yakov Sanjoy Chakraborty
Adelle Thomas Andrew Douglas
Parveen Chowdhury Laura Ghezzi
Jian Hong Li Urmi Ghosh-Dastidar
Elisa Eishamy Victoria Gitman
Stacy Cruickshank Richard Hanley
Fejzije Bala Nasreen Haque
Marakia Jean-Noel Nasreen Haque
Luis Calzadilla Niloufar Haque
Esther Goldstein Caroline Hellman
Franklin Fung Delaram Kahrobaei
Weiyan Guo Delaram Kahrobaei
Kazy Islam Delaram Kahrobaei
Crystal Hernandez Laina Karthikeyan
Thinh H. Le Lufeng Leng
PHYS
PHYS
PHYS
SS
SS
SS
BIO
BIO
BIO
MATH
MATH
MATH
MATH
ENG
BIO
BIO
BIO
ENG
MATH
MATH
MATH
BIO
PHYS
The Properties of Electric and Magnetic Dipoles and the Interaction between
Various Dipole Molecules (DNA)
Enhanced Observation Capability of the New Generation Geostationary Satellites
for Better Vegetation Monitoring
Enhanced Observation Capability of the New Generation Geostationary Satellites
for Better Vegetation Monitoring
A Computerized Test of a Hypothesis Involving the Effect of the Poggendorff
Illusion on an Embedded Stimulus
A Simplified Chinese Character Version of a Computerized Forensic Evaluation
Stimuli and Response Choices to Test the Effects of Landscape Planar Elevation
and Spatial Frequency Filtering on Perception of the Mona Lisa
Endocrine Disruptors and Reproductive Axis, Puberty
Endocrine Disruptors and Reproductive Axis, Puberty
Estrogen and its Neuroprotective Effect
The Life and Work of Fiona Murnaghan
Karen Smith: A Young World Leader in Commutative Algebra and Algebraic Geometry
Mathematical Modeling of Bird Flu Propagation
Julia Robinson: A Pioneer in Logic
Water and Work: The History and Ecology of Downtown Brooklyn
Biodiversity in the Gowanus Canal
Molecular Profiling of Microbial Populations in Extreme Environments
Alterations in Brain Protein Profile in Alzheimer's Disease
House and Home Papers: Domesticity in the Works of Stowe, Alcott, Cather,
and Wharton
Group Theory and Cryptography
Work and Life of Sarah Rees
Some Applications of Combinatorial Group Theory in Cryptography
Antiviral Properties of Fruit Juices
Brillouin/Erbium Fiber Laser
2. Abstracts of the Emerging Scholars Program Research Projects
Supported by CUNY Compact funds
Spring 2008
Student Name Faculty Mentor Department Project Title
Mikhail Tsich Zongmin Li BIO The Effect of Long-Term Exposure to Anti-bacterial Soap on the Development
of Microbial Resistancy
Lori Younge Janet Liou-Mark MATH An African-American Woman Mathematician: Dr. Martha Euphemia Lofton Haynes
Preston Webber Djafar Mynbaev TCET Electronic Circuitry for Improving Performance of an Optical Communications Link
Prashant Rana Djafar Mynbaev TCET Design of Electronic Dispersion Compensation Circuitry for Optical Communications
Meisha-Gay Ringrose Mark Noonan ENG Legal Regulations Pertaining to Air and Water Pollution along the Brooklyn Waterfront
Crystal Hernandez Howard Sisco SS Validation of a Cultural Value Scale
Nerrine Douglas Simboonath Singh SS Unity in Diversity: Diasporic Encounters and the New Hinduism in the
North American Diaspora
Cheng Tan Shelly Smith ARCH Documentation Phase 2 and Structural Analysis - The Timothy Knapp House, Rye, NY
Osei Gyebi CMCE
Jorman Pena Shelly Smith ARCH Documentation Phase 2 and Structural Analysis - The Timothy Knapp House, Rye, NY
Shazadi Mohammed Suresh Tewani CHEM Hydrogen Gas is the Fuel of Future
Mary Bellamy Shauna Vey HU One Hundred Years of Child Labor Onstage in America
Francesca Montijo Huseyin Yuce MATH The Tale of Zero
NSF supported students - DUE 0622493
Mukhtar Adyinka Sidi Berri MECH The Use of CAD/CAM in Industrial Product Design
Eddy Moises Sidi Berri MECH The Use of CAD/CAM in Industrial Product Design
Adam Atia Aparicio Carranza CET Synchronous Binary Counter
Shadrack Mbogho Candido Cabo CST Computer Systems
Javier Joya Henry Africk Math Mathematical Simulations
2
3. Title: The Properties of Electric and Magnetic Dipoles and the Interaction between Various
Dipole Molecules (DNA)
Undergraduate Researcher: Igor Ashurov
Faculty Mentor: Dr. Oleg Berman
We studied dipole properties, such as electrostatic forces between dipoles that keep the double
helix in DNA molecular strands together. We also estimated the net force between various
molecular compounds like H20 and the CO-HN group. The electric field and electric potential
generated by various dipole molecules have also been calculated. Moreover, we have extended
our quantitative analysis on the magnetic field generated by magnetic dipoles. The classical
electrodynamics framework has been applied for these calculations.
Title: Enhanced Observation Capability of the New Generation Geostationary Satellites for
Better Vegetation Monitoring
Undergraduate Researchers: Kurt Sealey and Ian Rubenstein
Faculty Mentor: Dr. Reginald Blake
GOES-R ABI will be the first GOES (Geostationary Operational Environmental Satellite) imaging
instrument to provide observations in both the visible and the near infrared spectral bands. The
sensor will, therefore, be ideal for generating vegetation indices that can be used for monitoring
the state of the vegetation cover as well as for identifying vegetation stress and drought. In
addition to its improved spectral capability, the advantage of GOES-R ABI has enhanced spatial
(2 km) and temporal (every 5 min.) resolution. This project focuses on the results of the work on
generating the NDVI (Normalized Difference Vegetation Index) and evaluating compositing
algorithms using Meteosat 8/9 SEVIRI data as a proxy for GOES-R ABI prototype. A set of
remapped and reprojected MSG SEVIRI half-hourly images covering Europe and Africa has been
analyzed since May 2006. Collection of a set of SEVIRI full-disk 2-byte images started in late
February 2007. Both of these datasets are used to test NDVI algorithms and assess their
accuracy. Preliminary results indicate that with enhanced observation capability of the new
generation geostationary satellite, the advantages of GOES-R ABI can be demonstrated through
its improved spectral, spatial and temporal resolutions.
Additional Mentors: Peter Romanov1
, Hui Xu2
, Dan Tarpley3
1
CICS, University of Maryland
2
IMSG Inc., Kensington, MD
3
NOAA/NESDIS/STAR, Camp Springs, MD
Title: A Computerized Test of a Hypothesis Involving the Effect of the Poggendorff Illusion
on an Embedded Stimulus
Undergraduate Researcher: Giuseppe Macaluso
Faculty Mentor: Dr. Daniel Capruso
Aim: The Poggendorff illusion occurs when an intervening rectangle causes an apparent visual
misalignment of two collinear stimuli. The aim of the project is to devise a test of an original
hypothesis that the Poggendorff Illusion may also induce a misjudgment of the angle or vertical
elevation of a line embedded within the central rectangle.
Method: The Method of Adjustment was selected because it allows the measurement of
perceptual judgments with the minimum number of trials. In order to accomplish rapid, paperless
data collection of multiple subjects in a psychology laboratory, Visual Basic 2005 was used to
create the experimental computer application.
Results: A Visual Basic 2005 application (computer program) was created. The application tests
the accuracy of two types of perceptual judgment under random administration of both control
3
4. and experimental conditions: (1) Judgment of Angular Line Orientation: Control trials are
presented in which oblique target lines of varying angular orientation are presented to the right or
left of a rectangle, and the subject must use graphical user interface (GUI) buttons to adjust the
angle of a response line embedded within the rectangle to match the angle of the target sample.
Experimental trials are also presented in which the response stimulus is embedded within the
rectangle of a Poggendorff display with collinear peripheral lines of varying angular orientation.
The subject must match the response line to the angle of the collinear target lines. (2) Judgment
of Elevation: Control trials are presented in which oblique lines of varying angular orientation are
presented at the top or bottom of the rectangle. The subject must adjust the elevation of the
response line with GUI buttons until the embedded line is bisected by two horizontal collinear
peripheral lines. Experimental trials are also presented in which the subject must adjust the
elevation of the response line so that it is bisected by the two oblique collinear lines in a
Poggendorff display.
Conclusion: A computer application has been developed that can be used to empirically test a
hypothesis that the Poggendorff configuration will affect judgments of angular orientation and
elevation in embedded stimuli.
Title: A Simplified Chinese Character Version of a Computerized Forensic Evaluation
Undergraduate Researcher: Feng Yan Tang
Faculty Mentor: Dr. Daniel Capruso
Aim: New York has a rapidly increasing Chinese immigrant population for whom it is difficult to
provide forensic psychiatric services due to a language barrier. The aim of the project was to
produce a Chinese character version of a computerized fitness evaluation. The computer
application will evaluate and train monolingual Chinese immigrants regarding fitness to proceed
on criminal matters in the New York State legal system.
Method and Results: The 105 question item pool of an existing computerized forensic evaluation
produced at the New York City College of Technology was translated into a simplified Chinese
character set and created as a digital file. Because the various dialects of Chinese are mutually
intelligible with the same set of written (not spoken) language characters, the computer
application can be used with any literate Chinese forensic patient.
Conclusion: The production of a Chinese version of the Computerized Fitness Evaluation allows
provision of improved forensic services to Chinese immigrant forensic patients, many of whom
have a limited comprehension of the legal system in New York State. Because English and
Spanish language versions of the forensic program already exist, production of the Chinese
computer application will also allow cross-cultural research into differences in fitness to proceed
among persons born in the USA versus various Hispanic and Chinese immigrant groups.
Title: Stimuli and Response Choices to Test the Effects of Landscape Planar Elevation and
Spatial Frequency Filtering on Perception of the Mona Lisa
Undergraduate Researcher: Michael Dulski
Faculty Mentor: Dr. Daniel Capruso
Aim: The perceptual instability and illusory movement apparent in the smile of Leonardo
DaVinci’s “Mona Lisa” has been the subject of comment and speculation by art historians, critics,
and scientists. The primary aim of the project was to devise digital stimuli that will allow an
empirical test of an original hypothesis that Mona Lisa’s smile is, at least in part, caused by a
Poggendorff type perceptual illusion induced by the unequal elevations of the landscape planes
on either side of Mona Lisa’s head. A secondary aim of the project was to construct stimuli that
would also allow an empirical test of Livingstone’s spatial frequency hypothesis of perception of
Mona Lisa’s smile.
4
5. Method: A 717x1101 (WxH) pixel image of the Mona Lisa was manipulated in Adobe Photoshop
CS3. In order to test the original hypothesis, the landscape background was retouched and
leveled using the “healing brush” and “clone stamp” tools. To test Livingstone’s spatial frequency
hypothesis, Mona Lisa’s face was cropped to 278 x 350 pixels and then passed through high and
low pass frequency filters. Finally, matching to sample response choices for the smile were
produced using the “liquefy” and “smudge” tools to warp the mouth into a greater or lesser smile
without noticeably changing the image to a casual observer.
Results: For experimental purposes, the following digital stimuli have been produced: (1) A Mona
Lisa with background landscape planes of equal elevation; (2) High and low spatial frequency
filtered versions of Mona Lisa’s face; and (3) More acute versus flattened versions of Mona Lisa’s
smile to be used as response choices in testing the effects of altered background and high versus
low spatial frequency filtering on perception of Mona Lisa’s facial expression.
Conclusion: The digitally altered stimuli will be used in a computer application to be constructed
which will provide automated empirical testing of whether alterations in surrounding contextual
landscape or spatial frequency may account for illusory or unstable perception of the Mona Lisa
smile.
Title: Endocrine Disruptors and Reproductive Axis, Puberty
Undergraduate Researchers: Tamara Shand and Taznia Sultana
Faculty Mentor: Dr. Sanjoy Chakraborty
After several accidental discoveries and the beginnings of modern research, scientists have
revealed overwhelming evidence that there is at least one group of chemicals, namely endocrine
disrupting chemicals (EDC), both natural and man-made, which are responsible directly or
indirectly for damage to the homeostasis of living things. The endocrine system that regulates our
body’s major functions, including normal growth, maturation, and reproduction utilizes many
hormones. Hormones, the chemical messengers, work through specific receptors that are
expressed all over the body. EDCs that are found in the environment potentially interfere with the
proper functioning of the hormonal system by binding to their receptors. In this project, some
specific EDCs and their profound effect on sexual characteristics, including earlier menarch in
girls and reduced sperm quality in males, were studied.
Title: Estrogen and Its Neuroprotective Effect
Undergraduate Researcher: Tomar Yakov
Faculty Mentor: Dr. Sanjoy Chakraborty
Glucose is the main metabolic fuel for the neuronal cells. In the event of low glucose
(hypoglycemia) the regions of the brain like the cortex, hippocampus and hypothalamus become
vulnerable to injury. Reports of necrotic and apoptotic cell death in the neocortex has been
reported. We studied the effect of hypoglycemia on hypothalamic cells and explored estrogen as
a potent neuroprotective agent. Reports are available that estrogen acts a neuroprotective agent
in animal models, but the contribution of estrogen receptors in the estrogen-primed
neuroprotection in hypothalamic cell line remains unsolved.
Title: The Life and Work of Fiona Murnaghan
Undergraduate Researcher: Adelle Thomas
Faculty Mentor: Dr. Andrew Douglas
Dr. Fiona Murnaghan is a Professor of Mathematics at the University of Toronto. Since earning
her PhD from the University of Chicago in 1987, she has made many important contributions to
5
6. the field of Representation theory of p-adic groups. We examined her rise to success from grade
school, through graduate school and finally as a Professor of Mathematics. Next, we studied the
general area in which Dr. Murnaghan’s research lies, group theory. After learning the basic
results of group theory, we examined one of its classical results: A description of the symmetry
group of each platonic solid. This work was presented at the NSF sponsored Women in
Mathematics Conference, held at City Tech on May 2, 2008.
Title: Karen Smith: A young world leader in Commutative Algebra and Algebraic Geometry
Undergraduate Researcher: Parveen Chowdhury
Faculty Mentor: Dr. Laura Ghezzi
This project concerned Karen Smith (1965 - ), Professor of Mathematics at the University of
Michigan. Dr. Smith is a world leader in Commutative Algebra and Algebraic Geometry. She has
been the recipient of prestigious awards, and is a devoted mother of three children. We explored
her path towards a career in mathematics, her outstanding achievements, and her extremely
positive influence on the numerous undergraduate students, graduate students and postdocs that
she has mentored. We also briefly researched the role of Commutative Algebra and Algebraic
Geometry in modern mathematics, to better understand Dr. Smith’s contributions to these fields.
This work was presented at the NSF sponsored Women in Mathematics Conference, held at City
Tech on May 2, 2008.
Title: Mathematical Modeling of Bird Flu Propagation
Undergraduate Researcher: Jian Hong Li
Faculty Mentor: Dr. Urmi Ghosh-Dastidar
This is a continuation of the project that we started in fall of 2007.
We built a bird-flu propagation model using mathematical tools. This model is based on numerous
assumptions (please see the abstract of Emerging Scholar Program, fall 2007 for further
information). We found four equilibrium points. Three out of these four equilibrium points are in
the feasible region. For each of these equilibrium points, the system of differential equations is
linearized and corresponding eigen-values are found. We found that two of these equilibrium
points are unstable since one of the eigen-values is positive for both cases. We found that the
remaining equilibrium point is asymptotically stable because all three eigen-values associated to
this equilibrium point have negative real parts. Our analytical results nicely agree with numerical
simulation.
Title: Julia Robinson: A Pioneer In Logic
Undergraduate Researcher: Elisa Eishamy
Faculty Mentors: Dr. Victoria Gitman
In 1976, the American mathematician Julia Robinson (1919-1985) became the first woman to be
elected to the National Academy of Sciences. Robinson's work on existential definability and
exponential Diophantine equations provided much of the basis for the solution of the famous
Hilbert's Tenth Problem. Even though it was Yuri Matiyasevich who proved the negative solution
to the Tenth Problem and not Robinson, his solution built fundamentally on Robinson’s joint work
with Hilary Putnam and Martin Davis. Robinson made major contributions to the field of
mathematical logic and became an inspiration to aspiring women mathematicians worldwide. Our
poster will take a journey through Julia Robinson's life and her accomplishments as well as give
an overview of Hilbert’s Tenth Problem and the Matiyasevich, Robinson, Davis, Putnam (MRDP)
solution. This work was presented at the NSF sponsored Women in Mathematics Conference,
held at City Tech on May 2, 2008.
6
7. Title: Water and Work: The History and Ecology of Downtown Brooklyn
Undergraduate Researcher: Stacy Cruickshank
Faculty Mentor: Dr. Richard E. Hanley
The Water and Work: History and Ecology of Downtown Brooklyn project was made possible
through a National Endowment for the Humanities (NEH) sponsored faculty development seminar
at the New York City College of Technology. The City Tech faculty seeks to understand the
historical, technological, social and ecological forces that have created Downtown Brooklyn.
The Emerging Scholars Program has afforded me the wonderful opportunity to work along with
faculty members on their quest to discover and thoroughly study the Brooklyn Waterfront; the
fruition of which will result in the development of a humanities course for all freshmen students.
My involvement with this project has proved very interesting and informative – from learning
about Walt Whitman and his poetry about Brooklyn and Manhattan (which he referred to as
Manahatta) to learning about containerization. I worked along with faculty members in creating an
archive of the various planned events. The first such event was a panel discussion that featured
three eminent scholars, who focused on the Brooklyn waterfront from their areas of specialization.
Professor Karen Karbiener discussed Walt Whitman’s close relationship to the waterfront and
showed its presence in his poetry. Professor Joshua Freeman focused on the history of
waterfront labor in Brooklyn since World War II and Professor Betsy McCully focused on the
natural history of Brooklyn’s waterfront. Some of the other events include a “history hunters”
workshop at the Brooklyn Historical Society, during which the facilitators focused on key events of
U.S history that had a critical link with, or to Brooklyn; namely the Revolutionary War’s Battle of
Long Island, the Brooklyn Navy Yard in WW II, and Brooklyn’s various influxes of immigrants, just
to name a few. The workshop ended with a discussion on some key places in Green Point’s
historical development. This proved to be very timely and informative as one of our scheduled
events was a walk through Green Point and Williamsburg.
The team also plans to visit the Barge Museum in Red Hook and have a tour of the Brooklyn
Navy Yard. All the places that we have scheduled walks and tours to, have proved to be very rich
sources of information about the forces in the creation of Downtown Brooklyn.
I am also a contributor on the Word Press website, on the Water and Work section created by
Matthew Gold, one of the faculty members for relevant Water and Work blog entries. This entails
writing blog entries on synopses or announcements of the activities we have had or upcoming
events and also, putting links to articles of topics related to Water and Work.
It is indeed a pleasure working with the faculty members on this project. We are all learning and
discovering much exciting information about the history of the Brooklyn Waterfront, which we
believe will translate into an excellent awareness course in the humanities for freshmen students.
Title: Biodiversity in the Gowanus Canal
Undergraduate Researcher: Fejzije Bala
Faculty Mentor: Dr. Nasreen Haque
Every living organism has a specific role in maintaining the balance of the ecosystem. As a result
of this balance, all organisms including bacteria can contribute to a healthy and balanced
ecosystem. When this balance is disturbed, the ecosystem can suffer. The Gowanus Canal, an
estuary in New York City is infamous for its level of pollution. Different industries discharge their
waste, which is the prime reason for the pollution. We are studying the microbial populations
colonizing in this water body. In spite of measures being taken, various microbes survive in this
environment. Probably, the metabolic activity of these organisms aids in their survival. Our
hypothesis is that inhibitory factors for diseased conditions can be obtained from the
microorganisms. Our aims are (1) to identity the microbes in the canal, (2) to observe the role of
7
8. extracts of these microorganisms in inhibition of pathogenic microbes and (3) the characterization
of bacteria by cloning and sequencing of specific DNA.
Gram staining revealed both gram-negative and gram-positive microbial populations. A
differential pattern of mobility was observed amongst microorganisms by the Motility Test.
Bioassays were performed to test the inhibitory effect of extracts from various cultured bacteria.
Extracts of microorganisms (#29, 31, 32, 35) prevented the growth of different pathogens
(S.aureus, E.coli, S.marcesces, C.defficile)in the laboratory.
Marine microbes are revealing new compounds for anti-cancer, anti-inflammatory and other
diseases. These studies could provide alternative sources of drugs as shown in the above-
mentioned findings.
Title: Molecular Profiling of Microbial Populations in Extreme Environments
Undergraduate Researcher: Marakia Jean-Noel
Faculty Mentor: Dr. Nasreen Haque
Microbial diversity is a major contributor to the biogeochemical processes in the estuarine
environment. The growth and development of these organisms in turn, depends on the presence
of other biotic organisms and the physical and chemical conditions around it. Despite the
significant and profound effect of the microbial population on the estuarine ecosystem, the
relationship between estuarine benthos and society is not well understood. The Gowanus Canal
in New York City is extremely polluted. Preliminary data obtained by regular EPA monitoring
shows a trend of decrease in dissolved oxygen (DO), phosphate and nitrate levels over the years.
There are no documented records on the existing microorganisms in this area. The present study
aims to study the microbial biodiversity at the molecular level in the canal.
Advances in technology allow for rapid localization, isolation and analysis of microorganisms
based on genetic differences. This is an important tool in ecological research. The identification
process involves isolation of DNA, PCR-based amplification of the specific 16S rDNA and
sequence analysis. As a first step we have cultured bacteria from the canal on agar plates and
successfully isolated genomic DNA.
Title: Alterations in Brain Protein Profile in Alzheimer’s Disease
Undergraduate Researcher: Luis Calzadilla
Faculty Mentor: Dr. Niloufar Haque
ABSTRACT PENDING
Title: House and Home Papers: Domesticity in the Works of Stowe, Alcott, Cather, and
Wharton
Undergraduate Researcher: Esther Goldstein
Faculty Mentor: Dr. Caroline Hellman
Professor Hellman’s research involves establishing a complete understanding of the relationship
between social history and literary accomplishment. She proposes that domestic space is a rich,
generative site for political and social changes. The research I have conducted consisted of
exploring women writers from the mid-nineteenth century to the early twentieth century and how
they portray domesticity in their literature. More specifically, my aim was to investigate four major
women writers, Stowe, Alcott, Cather, and Wharton. I researched works from the mid-nineteenth
century to the twentieth century to see if these four major writers had been influenced by other
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9. writers’ literatures of domestic space. I examined the influence of Charlotte Perkins Gilman’s
book, Women and Economics, on post-1898 works of Wharton and Cather. I assisted Professor
Hellman with research in determining whether particular primary and secondary sources are
relevant on Stowe, Alcott, Cather, Wharton, and Gilman’s writings on domesticity. I also studied
the extent Downing’s, Architecture of a Country House, influenced Stowe, Alcott, and Wharton’s
ideas of architectural design.
Title: Group Theory and Cryptography
Undergraduate Researcher: Franklin Fung
Faculty Mentor: Dr. Delaram Kahrobaei
The objective of this work was to write a paper which presents the theory of modern cryptography
to the public. We mentioned its utilities and how to construct schemes and algorithms with it so
that information can be transmitted over an insecure channel trustingly. This will help us to
understand the basic task of cryptography which allows two or more users enable a
communication over an insecure channel without information being altered and kept in secrecy.
By doing that we discussed the mathematical backgrounds needed and the concepts involved in
cryptography.
Title: Work and Life of Sarah Rees
Undergraduate Researcher: Weiyan Guo
Faculty Mentor: Dr. Delaram Kahrobaei
This project was a study of the British Mathematician, Sarah Rees (1957- ), Professor of
Mathematics at the University of New Castle in England. Professor Rees is a world leader in
research at the junction of Group theory, geometry and combinatorics. Of her most recent
projects, one examines connections between group theory and formal language theory, the other
studies quantum computation from a group theoretic perspective. She has been internationally
known for her work, and she is a devoted mother of a child. In this project the decision problem
known as word problem and its hardness using an article of Sarah Rees, was explored. This
work was presented at the NSF sponsored Women in Mathematics Conference, held at City Tech
on May 2, 2008.
Title: Some Applications of Combinatorial Group Theory in Cryptography
Undergraduate Researcher: Kazy Islam
Faculty Mentor: Dr. Delaram Kahrobaei
Two important problems from non-commutative version of public key-encryption namely Diffie-
Hellman and Elgamal key exchange system were presented. An introduction of combinatorial
group theory, particularly two decision problems, namely word and conjugacy problems was also
developed. It was shown that we can apply these problems in non-commutative versions of public
key encryption. Particularly, a non-commutative ElGamal due to Kahrobaei and Khan was
explored.
Title: Antiviral Properties of Fruit Juices
Undergraduate Researcher: Crystal Hernandez
Faculty Mentor: Dr. Laina Karthikeyan
Defined phytochemicals in potable juices have been shown to possess antiviral properties both in
vitro and in vivo. However, cytotoxicity by chemical treatment of cells may mask any antiviral
9
10. effects. Accordingly, such testing is critical to validate the effect of the juices in question as
antiviral agents.
Antiviral testing in cell culture has addressed the potential issue of cytotoxicity by monolayer
pretreatment with cranberry and Concord grape juices. Such cytotoxicity testing employed trypan
blue exclusion and cell subpassage. However, confirmatory testing to identify subtle effects by
juices and other phytochemicals or nutraceuticals needs to be tested by a metabolic assay. The
metabolic assay used is a non-destructive bioluminescent cytotoxicity assay, which quantitatively
measures the release of adenylate kinase (AK) from damaged cells (ToxiLight
R
BioAssay, Lonza
Rockland, Inc., Rockland, ME ). Release of AK from damaged cells, in complex with ADP,
luciferein and luciferase additives from the Toxilight
R
BioAssay kit, yields an ATP spark – which
can be detected by placement of the reaction mix in a luminometer.
The luminometer detects the ADP to ATP conversion.
This project is a collaborative effort with Dr. Steve Lipson (St. Francis College).
Title: Brillouin/Erbium Fiber Laser
Undergraduate Researcher: Thinh H. Le
Faculty Mentor: Dr. Lufeng Leng
We have constructed a Brillouin/Erbium fiber laser and evaluated the performance of its various
configurations. We have identified an optimum laser configuration and improved its performance
by 1. employing different lengths of single mode fiber in the laser cavity; 2. employing different
lengths of Erbium fiber; 3. varying the injected Brillouin pump power; 4. varying the pump power
of the Erbium doped fiber amplifier in the laser cavity; 5. including a polarization controller in the
cavity for better Brillouin scattering efficiency. Optical and electrical spectra of the Brillouin/Erbium
fiber laser output show that more stable output power and lower noise level have been achieved.
Title: The Effect of Long-Term Exposure to Anti-bacterial Soap on the Development of
Microbial Resistancy
Undergraduate Researcher: Mikhail Tsich
Faculty Mentor: Dr. Zongmin Li
It has been clinically proven that overuse of antibiotics can cause sensitive bacteria to evolve
resistance to their antibacterial action. However, it is not well defined yet whether overuse of
antibacterial soap has a similar effect. Antibacterial soap is any cleaning product to which active
antibacterial ingredients have been added. Many, or even most, liquid hand and body soaps
contain antibacterial chemicals, such as triclosan and alcohol. Some studies have found that
soaps containing antimicrobial active ingredients remove more bacteria than simply washing with
plain soap and water. Nevertheless, long-term exposure to residual antibacterial soap on skin
may result in selection of antibiotic-resistant strains of pathogens. This may also contribute to the
production of so-called "super bug". In this study, we investigate the effect of long term exposure
to low dosage of antibacterial soap on two common pathogenic bacteria: Staphyloccocus aurues,
a Gram positive coccal bacterium and E. coli, a Gram negative rod-shaped bacterium. The results
may bring us insights into the relationship between antibiotic resistancy and overuse of
antibacterial soap.
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11. Title: An African-American Woman Mathematician: Dr. Martha Euphemia Lofton Haynes
Undergraduate Researcher: Lori Younge
Faculty Mentor: Dr. Janet Liou-Mark
Dr. Martha Euphemia Lofton Haynes is the first African American Woman to receive her Ph.D. in
Mathematics. She received her Ph.D. from the Catholic University of America in 1943. The title of
her thesis is “Determination of Sets of Independent Conditions Characterizing Certain Special
Cases of Symmetric Correspondences.” Not only was Dr. Haynes well involved in the academic
community, but she was also involved in many non-academic community related activities. She
was a teacher, leader, philanthropist and mathematician. During her lifetime, Dr. Haynes has
accomplished much and through her example, other women mathematicians can do the same.
This work was presented at the NSF sponsored Women in Mathematics Conference, held at City
Tech on May 2, 2008.
Title: Electronic Circuitry for Improving Performance of an Optical Communications Link
Undergraduate Researcher: Preston Webber
Faculty Mentors: Dr. Djafar Mynbaev
Optical communications is the linchpin of modern communications, delivering tremendous
amounts of information at any point on the globe. However, optical communications links still
have their drawbacks, and one of the major drawbacks is the dispersion that an optical signal
experiences while traveling down an optical fiber. Dispersion results in the spread of optical
pulses, which eventually reduces the bandwidth of optical links. Typically, network operators cope
with dispersion by using optical devices; however, optical-based approach suffers from the non-
existence of optical processing devices.
We’d like to explore another approach: The use of electronic circuitry for improving performance
of optical communications links. This approach relies on mature electronic technology, but needs
to overcome the problem of dealing with very weak optical signals. Our goal is to design the
electronic circuits that will reduce the optical-pulse spreads to acceptable level.
Title: Design of Electronic Dispersion Compensation Circuitry for Optical Communications
Undergraduate Researcher: Prashant Rana
Faculty Mentor: Dr. Djafar Mynbaev
Optical communication systems are used to provide high-speed communication connections.
Single mode optical fiber (SMF) is the transmission medium used for long distance
telecommunication with very low losses and high bandwidth. However, SMF still suffers from
dispersion, which limits its bandwidth. All forms of dispersion degrade a light wave signal,
reducing the data carrying capacity through pulse-broadening. We concentrate here on chromatic
dispersion (CD), which results from a variation in propagation delay with wavelength, and is
affected by fiber materials and dimensions.
One of the means to cope with CD is electronic dispersion compensation (EDC) that utilizes
advance DSP technique. The main component of an EDC module is a filter. Main types of
electronic filters, as defined by their transfer functions, are the following:
1) Butterworth filters: It is designed to have a frequency response, which is as flat as
mathematically possible in the passband.
2) Chebyshev filters: Chebyshev filters have the property that they minimize the error between
the idealized filter characteristic and the actual over the range of the filter, but with ripples in the
passband.
11
12. 3) Bessel filters: Bessel filters are characterized by almost constant group delay across the
entire passband, thus preserving the wave shape of filtered signals in the passband.
4) Ideal filter: Ideal filters allow a specified frequency range of interest to pass through while
attenuating a specified unwanted frequency range.
The goal of this project is designing the EDC circuitry using the best applicable filter to
compensate for chromatic dispersion of an optical signal. The classifications of filters and their
mathematical models have been examined. The future work will involve mathematical description
of the optical signal, its spectral analysis and the filter design, which include choosing the filter
type and its parameters.
Title: Legal Regulations Pertaining to Air and Water Pollution Along the Brooklyn
Waterfront
Undergraduate Researcher: Meisha-Gay Ringrose
Faculty Mentor: Dr. Mark Noonan
Meisha-Gay Ringrose worked with Professor Mark Noonan on the NEH grant "Water and Work."
She attended various tours and talks on how the Brooklyn Waterfront is changing, and is writing a
research paper on legal issues pertaining to commercial and community development along the
Brooklyn waterfront.
Title: Validation of a Cultural Value Scale
Undergraduate Researcher: Crystal Hernandez
Faculty Mentor: Dr. Howard Sisco
Purpose
The faculty sponsor is the creator of a Cultural Value Scale, a 37 item inventory developed to
identify respondents’ individual differences on six main cultural values recently recognized in
most societies. The inventory uses a 7 point rating scale ranging from strongly agree to strongly
disagree. Respondents rate the degree to which each statement is representative of them. Until
now a validated measurement instrument has not existed to allow social scientists to
systematically investigate how cultural values moderate different types of behaviors. The
purpose of this professor/student collaborative effort was to take data already collected in this IRB
approved study, and validate the scale using statistical software.
Method
Collected data from 205 students participating from the New York City College of Technology was
coded and transcribed into data files for analyses using Statistical Package for Social Sciences
(SPSS). Construct Validity (analyzed via Principle Component Analysis, PCA) and Reliability
(analyzed via Reliability Analysis) was assessed using the newly coded data. The student
assisted with data coding and entry, analyses, and the writing up of results for this project.
Results and Conclusion
Results of the factor analysis (PCA) provide strong evidence of the convergent and discriminant
validity of the Cultural Value Scale scores. As predicted, the Cultural Value items loaded on their
hypothesized factors. Six latent factors accounted for a substantial portion of variance. This
suggests that there are not any statistically significant cross-loading of items on to non
hypothesized factors. Results of the reliability analysis indicated acceptable coefficient alpha
(r=.77). Overall, statistical analyses of the Cultural Value Scale indicate a valid and reliable
measurement tool worthy of further study.
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13. Title: Unity in Diversity: Diasporic Encounters and the New Hinduism in the North
American Diaspora
Undergraduate Researcher: Nerrine Douglas
Faculty Mentor: Dr. Simboonath Singh
This research project is based on an ethnographic case study of an Indo-Caribbean Hindu temple
in Toronto, Canada. It focuses on how a new ethnic and immigrant congregation (such as
Caribbean Hindus) is experiencing a ‘cultural revolution’ as its traditional ethno-cultural identities
and practices are gradually being transformed as a result of particular globalizing, immigration
and transnational processes. One area in which the traditional Indo-Caribbean Hindu identity is
being constructed and transformed is in the area of religious institution, particularly in Hindu
temples where, for the first time, Caribbean Hindus are worshipping and interacting, or
“encountering/meeting-up” with their long lost, under the same roof, so to speak, with their lost
and historically estranged ancestral sisters and brothers from the Indian subcontinent, namely,
South Asian/Asian Indian Hindus. The meeting-up or “coming together” of these two culturally
disparate groups, and the subsequent melding together of these two cultural traditions, have
important implications for the development of a new Diasporic Hindu identity in both Canada and
the United States. Thus, the idea of the new immigration and the character of the “new
immigrant”: the notion that the new immigrants as transnational, global and cosmopolitan have
clear theoretical implications for future research and theorizing about the emergence of new and
hybridized identities and cultures in the West.
Several Hindu temples in the Queens, Jamaica and Richmond Heights areas of New York were
visited. We have touched the “tip of the iceberg” so to speak, as ethnographic and/or qualitative-
based research often is highly processual i.e., it requires extensive visits to the research sites
(temples) and, is therefore, very time consuming. We continue to engage in the preliminary
survey of some of the diverse and wonderful sites where Hindu temples are allocated all over
New York.
Title: Documentation Phase 2 and Structural Analysis: The Timothy Knapp House, Rye NY
Undergraduate Researchers: Cheng (Bryan) Q. Tan and Jorman Pena
Faculty Mentor: Dr. Shelley E. Smith
The Emerging Scholars program has been an opportunity to work along with Professor Shelley
Smith, and a fellow student, Bryan Tan. Together we continued this project from last term to
document and record architectural information for the Timothy Knapp House. This term we also
began to analyze the loads on the structure and find any possible areas of improvement. For the
analysis of the Timothy Knapp House the first task was to find the accurate dimensions and
material properties for the wood framing, and also to determine by physical inspection the
possible causes of the deformations in the house. After assisting in collecting data with Bryan, I
proceeded by accurately identifying primary beams and girders, researching the history of timber
framing, and determining the design loads and stresses that correspond to the time period. The
most interesting and challenging aspect of the analysis was the roof, which underwent four
phases of construction and is what is called a “saltbox”—a wooden frame house with a long,
pitched roof that slopes down to the back. Along with the changing roof and multiple layers of
beams being used to support the roof, and the settlement caused by the fireplace, the house was
undergoing movement which led to cracked walls and bowing in one area of the house. Careful
observation revealed settlement along floor sections on the first and second floor around the
chimney stack, which support these theories. Tentatively, the conclusions were based not only on
mathematical equations but also physical inspection of the property, which is why this experience
is very valuable and necessary in the field of construction and architecture.
The knowledge gained from applying technical knowledge used in the classroom to real world
problems is important for all students who wish to explore their field in greater detail. Also, the
opportunity to work with others from different fields on a historic project over three centuries old is
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14. an example of how the Emerging Scholars program can give back to students and the
community.
Title: Hydrogen Gas is the Fuel of Future
Undergraduate Researcher: Shazadi Mohammed
Faculty Mentor: Dr. Suresh Tewani
Our detailed literature survey and research predicts that “Hydrogen Gas is the Fuel of Future,”
especially in this energy shrinking economy. Scientists are really working hard on making
hydrogen fuel (Chemical and Engineering News, January 2008). The US government and
petroleum companies are spending huge sums for alternative fuel research in the hope that one-
day gasoline and other fuels will be replaced by hydrogen fuel. Gram per gram hydrogen is 4
times more energetic as compared to gasoline. Hydrogen gas burns clean with water as the only
byproduct as compared to other conventional fuels, which release carbon dioxide, soxes and
noxes.
The focus of our study is to investigate pathways to make large amounts of hydrogen gas in a
safe and cheaper process. My preliminary research readings indicate that “Water splitting”
[2H2O • 2H2 + O2] will be the best process to gain pure hydrogen and no toxic byproducts. The
energy used in this process will be derived from Sun using solar cells. A synthetic chemical,
Ru(bippy)3 will be used in place of Chlorophyll.
In my experiments, I used a multimeter, a solar panel, wires, a beaker of water and 2 carbon
rods. By performing these experiment, I discovered that on the negative side of the wire the
hydrogen gas was forming and on the positive side oxygen gas was forming. While the gas was
forming the readings on the multimeter were high up to a volt reading of 4.6 V and when upon
removing the solar panel the readings of the multimeter were gradually decreasing. Results of
initial experiments and detailed literature survey will be presented.
Title: One Hundred Years of Child Labor Onstage in America
Undergraduate Researcher: Mary Bellamy
Faculty Mentor: Dr. Shauna Vey
My mentor, Dr. Shauna Vey is in the process of writing a book that will focus on the working
conditions of 19
th
century child performers. As her assistant, my duties were to read through
19
th
archives of the century newspaper The New York Clipper searching for stories and
advertisements that gave details about the working children. Some of the information that I
gained from my research will be used to supplement biographical sketches and to help create a
broader picture of the working world of child entertainers.
I was able to gain the appropriate information by utilizing the availability of various research aides
at the research division of the New York Public Library for the Performing Arts. One of those
research aides was the microfilm. The microfilm allowed me to view articles from The New York
Clipper. I was not only looking for information on the star performers of the 19
th
century, but for
information about those children who were barely able to make a living. I also used the internet to
perform searches in order to get additional information.
Helping Dr. Vey with her research project has taught me a number of things. I learned that many
scholars have mentioned the stories behind the well known child performers but have not
explored the wider context of child workers. I also learned that it was a common practice for the
19
th
century troupe managers to buy and sell the children’s contracts in order to boost ticket
sales. A large majority of the children’s families supported the transactions because the whole
family performed in various entertainment venues. Many of the children died because of poor
work conditions and strenuous routines. Although the newspaper mentioned those deaths in their
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15. articles, no one really questioned the safety of the children’s work environment. In conclusion,
what I learned personally from this experience was how to be thorough, concise and orderly.
Title: The Tale of Zero
Undergraduate Researcher: Francesca Montijo
Faculty Mentor: Dr. Huseyin Yuce
This is the history of how one digit number, zero, shaped the human mind. From its birth in
ancient times to present time, it has been the center of the biggest questions in sciences and
religions. The power of zero also lies within its twin infinity and the battle between nothingness
and eternity.
This most important number in mathematics is now used in everyday’s life. Present work shows
the power of zero throughout the ages and demonstrates the paradoxes posed by this innocent-
looking number with examples driven from calculus.
Title: The Use of CAD/CAM in Industrial Product Design
Undergraduate Researchers: Eddy Moises and Mukhtar Adyinka
Faculty Mentor: Dr. Sidi Berri
Design of new products in the industrial world requires the use of a wide variety of engineering
methods. The most commonly used and rapidly growing methods are CAD (Computer-Aided
Design), CAM (Computer-Aided Manufacturing), and RP (Rapid Prototyping).
This research project investigates the use of CAD/CAM/RP in the design of new products. Once
the CAD model is developed, it is sent to a CAM module within a software package called
MasterCAM to simulate the different machining operations. Then, the model is exported to a rapid
prototyping machine. This final phase allows the CAD/CAM model to be directly sliced into a
number of thin layers, which are then physically built up one on top of the other. The more slices
the piece is cut into the more precise the product will come out but the more time it will take to
finish the prototype.
In this project several 3D models of different products are developed using MasterCAM. Working
prototypes of the 3D models are made of tough ABS plastic using a 3D printer. Finally, the
prototypes are used to better understand and communicate product designs and to make rapid
tooling to manufacture the new product.
Title: Synchronous Binary Counter
Undergraduate Researcher: Adam Atia
Faculty Mentor: Dr. Aparicio Carranza
The objective of this project is to design and implement a synchronous counter that will count the
following sequence: 4 – 7 – 3 – 5 – 2 – 4. The counter will be implemented using the 7400 series
Integrated Circuits (ICs), resistors, Light Emitting Diodes (LED), etc., and placed into a
breadboard. For the second approach a Complex Programmable Logic Device (CPLD) will be
used. A CPLD contains a bunch of PLD blocks whose inputs and outputs are connected together
by a global interconnection matrix. The flexibility of using CPLDs is that it replaces many discrete
components, is programmed using a programming language similar to C, known as VHDL (Very
High Speed IC Hardware Description Language). Programmable logic devices are much more
efficient for designing circuits (especially for complex circuits) opposed to wiring a number of
Integrated Circuit chips using the “old fashioned” breadboard method. Using Altera’s UP2 board,
which contains a CPLD, the EPM7128S, along with several other components, the Binary
Synchronous Counter is implemented. Synchronous counters are key elements in digital
electronics for sequencing any set of binary states, processes, or operations relative to an input
clock signal.
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